Biomarker Field of the Invention The present invention relates to a method for identifying a subject to whom a combination therapy is to be administered. The invention also relates to a polypeptide, a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor, a nucleic acid molecule, a T-cell or a T-cell receptor for use in the treatment of cancer and a method of treating cancer. Furthermore, the present invention relates to a method for identifying or predicting a clinical outcome of a cancer patient to a medicament. The invention also relates to a polypeptide, a nucleic acid molecule, a T-cell or a T-cell receptor, or an immune checkpoint inhibitor for use in the treatment of cancer and a method of treating cancer in a patient who has been identified as having, or predicted to have, a clinical response to a previous treatment. Background of the Invention Cancer is a disease characterised by new and abnormal growth of cells within an individual. Cancer develops through a multi-step process involving several mutational events that allow cancer cells to develop, that is to say cells which display the properties of invasion and metastasis. Numerous approaches have been proposed for the treatment of cancer. One approach to the treatment of cancer is to target proteins involved in immune checkpoints in order to modulate an individual’s immune response to cancer. One particular immune checkpoint mechanism that normally down-regulates the immune system in order to prevent excessive and uncontrolled immune responses is programmed cell death protein 1 (PD-1). PD-1 downregulates pathways of T-cell activation and, in individuals with cancer, this can result in natural immune responses against cancers being down- regulated. Antibody-mediated blockade of the checkpoint has been shown to release the potency of the inhibited immune response and improve survival rates. For example, the KEYNOTE-006 study as reported in Robert et al. Lancet Oncol.2019; 20: 1239–51 concerns a phase 3 trial of pembrolizumab in patients with advanced cancer and reports on its efficacy. A further immune checkpoint mechanism of relevance is the cytotoxic T- lymphocyte-associated protein 4 (CTLA-4) immune checkpoint. 13399613-3 Various studies have been conducted to identify biomarkers which correlate with the efficacy of anti-PD-1 checkpoint inhibitor treatments. In a review of studies and trials of immune checkpoint inhibitors, it has been reported that tumor mutational burden (TMB) high groups showed better overall survival and progression free survival than low TMB groups (Kim JY et al.: Tumor Mutational Burden and Efficacy of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis. Cancers (Basel) 2019, 11). In an early-phase trial of anti-PD-1 (nivolumab), it was reported that tumor cell PD-L1 expression correlated with objective response to anti–PD-1 therapy (Taube JM et al.: Association of PD-1, PD-1 Ligands, and Other Features of the Tumor Immune Microenvironment with Response to Anti–PD-1 Therapy. Clinical Cancer Research 2014, 20:5064-5074). In a study of the expression of CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs) in patients with melanoma treated with anti-PD1 immunotherapy, an association was found between CD8+/CD4+ TILs ratio and response to anti-PD1 treatment. Ratios of CD8+/CD4+ lower than 2 predicted lack of response to treatment, while CD8+/CD4+ ratios higher than 2.7 had an 81.3% response rate. In addition, it was reported that the presence of more than 1900/mm ² of CD8+ lymphocytes in the melanoma tumor predicted a 90% response to therapy. An association was also observed between CD8+/CD4+ TILs ratio and response to anti-PD1 treatment patients with metastatic non-small cell lung cancer (NSCLC) (Uryvaev A et al.: The role of tumor- infiltrating lymphocytes (TILs) as a predictive biomarker of response to anti-PD1 therapy in patients with metastatic non-small cell lung cancer or metastatic melanoma. Medical Oncology 2018, 35:25). Indeed, the regulatory approval of checkpoint inhibitors for cancer indications is usually limited to patients with high levels of relevant biomarkers. For example, nivolumab and pembrolizumab are each approved for treatment of patients with lung cancer who have ≥50% (Europe) or ≥1% (USA) PD-L1 expression levels on tumor cells. Similarly, atezolizumab is approved for treatment of patients with urothelial carcinoma who have PD-L1 stained tumor-infiltrating immune cells [IC] covering ≥ 5% of the tumor area. As such, one problem with current checkpoint inhibitor treatments is that certain patients (with low biomarker levels) are excluded from treatment and, in any case, it is observed that the clinical effect of immune checkpoint inhibitors in such patients is low. Another approach to the treatment of cancer is the use of antigenic peptides which comprise fragments of tumor associated antigens (i.e. peptide-based cancer vaccines). 13399613-3 Such antigenic peptides, when administered to an individual, elicit an MHC class I or class II restricted T-cell response against cells expressing the tumor associated antigens. It is to be appreciated that in order for such T-cell responses to occur, the antigenic polypeptide must be presented on an MHC molecule. There is a wide range of variability in MHC molecules in human populations. In particular, different individuals have different HLA alleles which have varying binding affinity for polypeptides, depending on the amino acid sequence of the polypeptides. Thus an individual who has one particular HLA allele may have MHC molecules that will bind a polypeptide of a particular sequence whereas other individuals lacking the HLA allele will have MHC molecules unable to bind and present the polypeptide (or, at least, their MHC molecules will have a very low affinity for the polypeptide and so present it at a relatively low level). Therefore, variability in MHC molecules in the human population means that providing a peptide-based cancer vaccine with broad population coverage is problematic because not all individuals will mount an immune response against a given antigen. WO 2011/101173 discloses vaccination with certain polypeptides from human telomerase reverse transcriptase (hTERT) for the treatment of cancer. WO 2017/207814 discloses a combination therapy treatment of cancer, without definition of a patient group, comprising vaccination with such hTERT polypeptides in combination with administration of an immune checkpoint inhibitor such as a PD-1/PD-L1 checkpoint inhibitor. There continues to be a need for further cancer treatments, particularly in patients with low levels of the biomarkers of: tumor mutational burden, PD-L1 expression, tumor infiltrating lymphocytes or neoantigens, for which conventional checkpoint inhibitor treatments have low or no clinical effect. Furthermore, there continues to be a need for means of monitoring and/or predicting the clinical outcome of a patient to a treatment. The present invention seeks to alleviate the above problems. 13399613-3 Summary of the Invention Aspects of the present invention arise from the observation that in patients treated with a combination therapy of a tumor-associated antigen vaccine and an anti-PD-1 checkpoint inhibitor (pembrolizumab), durable clinical responses were observed in patients whose biopsies were characterised as TMB-low, PD-L1-low and few TILs. This finding is unexpected as the clinical efficacy from pembrolizumab monotherapy is correlated with TMB-high, PD-L1-high, and TILs-abundant tumors. This finding makes plausible the treatment of a patient group which has no, or low, clinical response to immune checkpoint inhibitor monotherapy and the patients of which may even be excluded from immune checkpoint inhibitor monotherapy. Other aspects of the present invention arise from the surprising observation that, in patients administered an hTERT vaccine in combination with an immune checkpoint inhibitor (pembrolizumab), the level of hTERT or the relative change in hTERT levels after vaccination can be used to identify or predict whether or not the patient will exhibit a clinical response. Without wishing to be bound by theory, it is thought that this surprising observation arises because, following administration of the hTERT vaccine, an immune response is generated in those patients that are or will become clinical responders, which targets tumor cells expressing hTERT and leads to a measurable decrease in the hTERT level. This surprising observation makes plausible the evaluation of hTERT levels as a means for identifying and/or predicting a clinical outcome in a cancer patient in response to administration of an hTERT vaccine, with or without an immune checkpoint inhibitor. According to one aspect of the present invention, there is provided a method for identifying a subject to whom a combination therapy is to be administered, wherein the subject is a cancer patient, and wherein the combination therapy comprises administration of: (I) a PD-1/PD-L1 immune checkpoint inhibitor, (II) simultaneously, separately, or sequentially with: (A) a polypeptide comprising a region of at least 12 amino acids of a tumor- associated antigen or a sequence having at least 80% sequence identity to the region; 13399613-3 (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of a tumor- associated antigen or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), the method comprising: (a) evaluating a level of one or more of (i) to (iv) in a biological sample obtained from a cancer patient: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) a tumor infiltrating lymphocyte; and/or (iv) neoantigens, wherein the level of one or more of (i) to (iv) is determined to be low; and (b) identifying the cancer patient who provided the biological sample as a subject to whom the combination therapy is to be administered. Conveniently, the combination therapy comprises administration of: (I) a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. Preferably, the method further comprises the step of: (c) administering the combination therapy to the cancer patient identified in step (b). According to another aspect of the present invention, there is provided a polypeptide for use in the treatment of cancer, the polypeptide comprising a region of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the region, wherein the polypeptide is administered to a subject simultaneously, separately or sequentially with a PD-1/PD-L1 immune checkpoint inhibitor, and wherein the subject is a cancer patient having a level of one or more of (i) to (iv) that is low: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) a tumor infiltrating lymphocyte; and/or 13399613-3 (iv) neoantigens. Conveniently, the polypeptide is administered to a subject simultaneously, separately or sequentially with a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. According to another aspect of the present invention, there is provided a PD-1/PD-L1 immune checkpoint inhibitor for use in the treatment of cancer, wherein the PD-1/PD-L1 immune checkpoint inhibitor is administered to a subject simultaneously, separately or sequentially with: (A) a polypeptide comprising a region of at least 12 amino acids of a tumor- associated antigen or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a region of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), and wherein the subject is a cancer patient having a level of one or more of (i) to (iv) that is low: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) a tumor infiltrating lymphocyte; and/or (iv) neoantigens. According to another aspect of the present invention, there is provided a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor for use in the treatment of cancer, wherein the PD-1/PD-L1 immune checkpoint inhibitor and/or the CTLA-4 immune checkpoint inhibitor is administered to a subject simultaneously, separately or sequentially with: (A) a polypeptide comprising a region of at least 12 amino acids of a tumor- associated antigen or a sequence having at least 80% sequence identity to the region; 13399613-3 (B) a nucleic acid molecule comprising a nucleotide sequence encoding a region of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), and wherein the subject is a cancer patient having a level of one or more of (i) to (iv) that is low: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) a tumor infiltrating lymphocyte; and/or (iv) neoantigens. According to another aspect of the present invention, there is provided a nucleic acid molecule for use in the treatment of cancer, the nucleic acid molecule comprising a nucleotide sequence encoding a region of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the region, wherein the nucleic acid molecule is administered to a subject simultaneously, separately or sequentially with a PD-1/PD-L1 immune checkpoint inhibitor, and wherein the subject is a cancer patient having a level of one or more of (i) to (iv) that is low: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) a tumor infiltrating lymphocyte; and/or (iv) neoantigens. Conveniently, the nucleic acid molecule is administered to a subject simultaneously, separately or sequentially with a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. According to another aspect of the present invention, there is provided a T-cell receptor, or a T-cell displaying the T-cell receptor, for use in the treatment of cancer, wherein the T-cell receptor or the T-cell is specific for a polypeptide consisting of at least 12 amino 13399613-3 acids of a tumor-associated antigen, or a sequence having at least 80% sequence identity to the polypeptide, wherein the T-cell receptor or the T-cell is administered to a subject simultaneously, separately or sequentially with a PD-1/PD-L1 immune checkpoint inhibitor, and wherein the subject is a cancer patient having a level of one or more of (i) to (iv) that is low: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) a tumor infiltrating lymphocyte; and/or (iv) neoantigens. Conveniently, the T-cell receptor or the T-cell is administered to a subject simultaneously, separately or sequentially with a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. According to another aspect of the present invention, there is provided a method of treating cancer in a subject, the method comprising the steps of simultaneously, or separately or sequentially in any order: (I) administering to the patient a PD-1/PD-L1 immune checkpoint inhibitor, (II) administering to the patient: (A) a polypeptide comprising a region of at least 12 amino acids of a tumor- associated antigen or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of a tumor- associated antigen or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), wherein the subject is a cancer patient having a level of one or more of (i) to (iv) that is low: (i) tumor mutational burden; (ii) PD-L1 expression; 13399613-3 (iii) a tumor infiltrating lymphocyte; and/or (iv) neoantigens. Conveniently, step (I) comprises administering to the patient a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. Advantageously, the subject or patient has a clinical response to the method of treating cancer of the invention. Preferably, the clinical response comprises a partial or a complete response. Conveniently, step (I) comprises administering the PD-1/PD-L1 immune checkpoint inhibitor and/or the CTLA-4 immune checkpoint inhibitor to the patient at a dosage of between 100 and 2000 mg, preferably 200 mg. Preferably, step (II) comprises administering the polypeptide of the invention or the cocktail of polypeptides of the invention at a dosage of between 100 and 700 µg, preferably 300 µg. Advantageously, step (II) further comprises simultaneously, separately or sequentially administering an adjuvant, preferably GM-CSF. Conveniently, GM-CFS is administered at a dosage of between 20 and 100 µg, preferably 37.5 µg or 75 μg. Conveniently, the level of any one of (i) to (iv), in the above aspects of the invention, is determined to be low or is low if it is equal to or less than the 50 ^th percentile of a cancer patient population. Preferably, the level of (i) is determined to be low or is low if it is equal to or less than 30, 25, 20, 15, 10, 9, 8, 7, 6, 6.6, 5, 4, 3 or 2 mutations per megabase. Preferably, the level of (i) is determined to be low or is low if it is equal to or less than 10 mutations per megabase. 13399613-3 Advantageously, the PD-L1 expression is tumor cell PD-L1 expression and/or immune cell PD-L1 expression, preferably tumor infiltrating lymphocyte PD-L1 expression. Conveniently, the level of tumor cell PD-L1 expression is determined to be low or is low if a tumor proportional score is less than 50%, preferably less than 1%, and/or wherein the level of tumor infiltrating lymphocyte PD-L1 expression is determined to be low or is low if less than 50% of tumor infiltrating lymphocytes express PD-L1, preferably less than 1% of tumor infiltrating lymphocytes express PD-L1. Conveniently, the level of tumor cell PD-L1 expression is determined to be low or is low if a tumor proportional score is equal to or less than 50%, 20%, 10%, 5% or 1%, preferably equal to or less than 1%, and/or wherein the level of tumor infiltrating lymphocyte PD-L1 expression is determined to be low or is low if equal to or less than 50%, 20%, 10%, 5% or 1% of tumor infiltrating lymphocytes express PD-L1, preferably equal to or less than 1% of tumor infiltrating lymphocytes express PD-L1. Preferably, the level of (iii) is a level of tumor infiltrating lymphocyte density and the level of the tumor infiltrating lymphocyte density is determined to be low or is low if it is equal to or less than the 50 ^th percentile of a cancer patient population. Advantageously, the tumor infiltrating lymphocyte density is a CD8+ T-cell density, preferably wherein the level of the CD8+ T-cell density is determined to be low or is low if it is equal to or less than a density of 1000, 900, 886, 885, 880, 870, 860, 850, 800, 700, 600, 500, 400, 350, 341, 300, 250, 200, 150, 125, 116, 100, 90, 80, 78, 75 or 70 counts/mm ² . Preferably, the level of the CD8+ T-cell density is determined to be low or is low if it is equal to or less than a density of 900 counts/mm ² . Conveniently, the level of (iv) is determined to be low or is low if the number of predicted neoantigenis is equal to or less than 25, 20, 15, 10, 5 or 1, preferably equal to or less than 1 predicted neoantigen. Optionally, the cancer patient is excluded from treatment with a PD-1/PD-L1 immune checkpoint inhibitor monotherapy. 13399613-3 Optionally, the cancer patient is excluded from treatment with a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor monotherapy. Conveniently, the tumor-associated antigen is a universal tumor antigen, preferably wherein the universal tumor antigen is selected from the group consisting of: telomerase reverse transcriptase, survivin, DNA topoisomerase 2-alpha, cytochrome P4501B1 and E3 ubiquitin-protein ligase Mdm2. Preferably, the universal tumor antigen is telomerase reverse transcriptase and wherein the polypeptide comprises a sequence selected from: (i) SEQ ID NO.1; (ii) the sequence of an immunogenic fragment of (i) comprising at least 12 amino acids; or (iii) a sequence having at least 80% sequence identity to (i) or (ii). Advantageously, the polypeptide is a cocktail of polypeptides and wherein the cocktail of polypeptides further comprises: (a) a polypeptide comprising a sequence selected from: (i) SEQ ID NO.2; (ii) the sequence of an immunogenic fragment of (i) comprising at least 12 amino acids; or (iii) a sequence having at least 80% sequence identity to (i) or (ii), and/or (b) a polypeptide comprising a sequence selected from: (iv) SEQ ID NO.3; (v) the sequence of an immunogenic fragment of (iv) comprising at least 12 amino acids; or (vi) a sequence having at least 80% sequence identity to (iv) or (v). Conveniently, the PD-1/PD-L1 immune checkpoint inhibitor comprises one or more selected from: an anti-PD-1 antibody or a functional fragment thereof, an anti-PD-L1 antibody or a functional fragment thereof, a peptide-based or small molecule inhibitor of PD-1, and/or a peptide-based or small molecule inhibitor of PD-L1. 13399613-3 Conveniently, the CTLA-4 immune checkpoint inhibitor comprises one or more selected from: an anti-CTLA-4 antibody or a functional fragment thereof and/or a peptide-based or small molecule inhibitor of CTLA-4. Preferably, the anti-PD-1 antibody or a functional fragment thereof comprises one or more selected from: pembrolizumab and/or nivolumab, and/or wherein the anti-PD-L1 antibody or a functional fragment thereof comprises one or more selected from: durvalumab, atezolizumab and/or avelumab. Conveniently, the anti-PD-1 antibody or a functional fragment thereof comprises one or more selected from: pembrolizumab, nivolumab and/or cemiplimab. Preferably, the anti-CTLA-4 antibody or a functional fragment comprises one or more selected from: ipilimumab or tremelimumab. Advantageously, the polypeptide or one or more polypeptides in the cocktail of polypeptides is linked to a further substance. Conveniently, the combination therapy, the polypeptide, the PD-1/PD-L1 immune checkpoint inhibitor, the nucleic acid molecule, or the T-cell receptor or the T-cell is administered simultaneously, separately or sequentially with a further therapeutic ingredient, preferably wherein the further therapeutic ingredient is a further immune checkpoint inhibitor. Conveniently, the combination therapy, the polypeptide, the PD-1/PD-L1 immune checkpoint inhibitor and/or the CTLA-4 immune checkpoint inhibitor, the nucleic acid molecule, or the T-cell receptor or the T-cell is administered simultaneously, separately or sequentially with a further therapeutic ingredient, preferably wherein the further therapeutic ingredient is a further immune checkpoint inhibitor. Conveniently, there is provided a PD-1/PD-L1 immune checkpoint inhibitor and a CTLA- 4 immune checkpoint inhibitor. 13399613-3 Preferably, there is provided an anti-PD-1 antibody or a functional fragment thereof and an anti-CTLA-4 antibody or a functional fragment thereof, more preferably nivolumab and ipilimumab. According to another aspect of the present invention, there is provided a method for identifying or predicting a clinical outcome of a cancer patient to a medicament, wherein the medicament comprises: (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), the method comprising the step of: (a) evaluating an hTERT level in a biological sample obtained from the cancer patient at a time point subsequent to an administration of the medicament, wherein the evaluated hTERT level is negatively associated with a clinical response of the cancer patient to the medicament or positively associated with a clinical non- response of the cancer patient to the medicament. Conveniently, the method further comprises the step of administering the medicament to the cancer patient prior to step (a). Advantageously, the method further comprises the step of further administering the medicament to the cancer patient identified or predicted to have a clinical response in step (a). Preferably, the method further comprises the steps of: bi) comparing the evaluated hTERT level to a reference value obtained from a population of control subjects; and ci) identifying or predicting a clinical response of the cancer patient to the medicament when the evaluated hTERT level is lower than the reference value, or 13399613-3 identifying or predicting a clinical non-response of the cancer patient to the medicament when the evaluated hTERT level is higher than the reference value. Alternatively, the method further comprises the steps of: bii) comparing the evaluated hTERT level to a control hTERT level in a biological sample obtained from the cancer patient at a time point prior to that obtained in step (a); and cii) identifying or predicting a clinical response of the cancer patient to the medicament when the evaluated hTERT level is decreased relative to the control hTERT level, or identifying or predicting a clinical non-response of the cancer patient to the medicament when the evaluated hTERT level is the same as or increased relative to the control hTERT level. Alternatively, the method further comprises the steps of: biii) comparing a difference in hTERT level between a control hTERT level and the evaluated hTERT level to a reference value obtained from a population of control subjects, wherein the control hTERT level is the hTERT level in a biological sample obtained from the cancer patient at a time point prior to that obtained in step (a); and ciii) identifying or predicting a clinical response of the cancer patient to the medicament when the difference in hTERT level is lower than the reference value, or identifying or predicting a clinical non-response of the cancer patient to the medicament when the difference in hTERT level is higher than the reference value. Conveniently, the method further comprises the step of evaluating the control hTERT level in the biological sample obtained from the cancer patient. Preferably, the control hTERT level is a baseline hTERT level. Advantageously, the baseline hTERT level is the hTERT level in a biological sample obtained from the cancer patient at a time point prior to a first administration of the medicament or within 24 hours of the first administration of the medicament. Alternatively, the method further comprises the steps of: biv) comparing the evaluated hTERT level to a control hTERT level in a biological sample obtained from the cancer patient at a time point prior to that obtained in step (a) 13399613-3 and subsequent to the administration of the medicament and wherein the clinical outcome of the cancer patient has been previously identified or predicted; and civ) identifying or predicting the clinical outcome of the cancer patient as correlating with that previously identified or predicted at the prior time point when the evaluated hTERT level is the same as the control hTERT level. Alternatively, the method further comprises the steps of: bv) comparing the evaluated hTERT level with the hTERT levels in a population of control subjects, wherein the population of control subjects comprises healthy individuals and/or cancer patients previously identified as having, or predicted to have, a clinical response to the medicament; and cv) identifying or predicting a clinical response of the cancer patient to the medicament when the evaluated hTERT level correlates with the hTERT levels in the population of control subjects. Alternatively, the method further comprises the steps of: bvi) comparing the evaluated hTERT level to the hTERT levels in a population of control subjects, wherein the population of control subjects comprises cancer patients previously identified as having, or predicted to have, a clinical non-response to the medicament; and cvi) identifying or predicting a clinical non-response of the cancer patient to the medicament when the evaluated hTERT level correlates with the hTERT levels in the population of control subjects. Conveniently, the hTERT level is evaluated in a biological sample obtained from a cancer patient at a time point between 10 days and 14 weeks subsequent to a first administration of the medicament. Preferably, the hTERT level is an mRNA level of hTERT. Conveniently, the method comprises the step of evaluating the hTERT level by sequencing, preferably RNA sequencing. Advantageously, the sequencing is a sequencing by synthesis method or a sequencing by ligation method. 13399613-3 Conveniently, the sequencing comprises an artificial primer. Preferably, the sequencing comprises the extension of a polynucleotide chain with a nucleotide comprising a label. Conveniently, the label is a fluorescent label. Advantageously, the reference value is an hTERT level of 0.3 transcripts per million (TPM), preferably 0.33 TPM. Alternatively, the reference value is a difference in hTERT level of -0.1 TPM. Alternatively, a clinical response of the cancer patient to the medicament is identified or predicted when the evaluated hTERT level is decreased relative to a baseline hTERT level by a log2(fold change) that is equal to or less than -0.1, preferably equal to or less than -0.11, or wherein a clinical non-response of the cancer patient is identified or predicted when the evaluated hTERT level is increased relative to a baseline hTERT level by a log2(fold-change) that is equal to or greater than 0.03, preferably equal to or greater than 0.034. Conveniently, the method comprises evaluating at least a further hTERT level in at least a further biological sample obtained from the cancer patient at a time point subsequent to the administration of the medicament. Preferably, the biological sample obtained from the cancer patient is a biopsy tissue sample of a cancer or a tumor, or a biopsy tissue sample of a tissue suspected of being a cancer or a tumor, or wherein the biological sample obtained from the cancer patient is a liquid biopsy sample, preferably a blood sample. According to another aspect of the present invention, there is provided a polypeptide for use in the treatment of cancer, the polypeptide comprising a region of at least 12 amino acids of hTERT, or a sequence having at least 80% sequence identity to the region, wherein the polypeptide is administered to a patient who has been identified as having, 13399613-3 or predicted to have, a clinical response to a previous treatment comprising administration of the polypeptide. According to another aspect of the present invention, there is provided a nucleic acid molecule for use in the treatment of cancer, the nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT, or a sequence having at least 80% sequence identity to the region, wherein the nucleic acid molecule is administered to a patient who has been identified as having, or predicted to have, a clinical response to a previous treatment comprising administration of the nucleic acid molecule. According to another aspect of the present invention, there is provided a T-cell receptor, or a T-cell displaying the T-cell receptor, for use in the treatment of cancer, wherein the T-cell receptor or the T-cell is specific for a polypeptide consisting of at least 12 amino acids of hTERT, or a sequence having at least 80% sequence identity to the polypeptide, and wherein the T-cell receptor or the T-cell is administered to a patient who has been identified as having, or predicted to have, a clinical response to a previous treatment comprising administration of the T-cell receptor, or the T-cell displaying the T-cell receptor. According to another aspect of the present invention, there is provided a method of treating cancer in a patient, the method comprising administering a medicament to the patient, the medicament comprising: (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), and wherein the patient has been identified as having, or predicted to have, a clinical response to a previous treatment comprising administration of the medicament. 13399613-3 Preferably, the polypeptide of the invention or the cocktail of polypeptides of the invention is administered at a dosage of between 100 and 700 µg, preferably 300 µg. Advantageously, the polypeptide of the invention or the cocktail of polypeptides of the invention is administered simultaneously, separately or sequentially with an adjuvant, preferably GM-CSF. Conveniently, GM-CFS is administered at a dosage of between 20 and 100 µg, preferably 37.5 µg or 75 μg. Advantageously, the medicament, the polypeptide, the nucleic acid molecule, or the T- cell receptor or the T-cell is administered to the patient simultaneously, separately or sequentially, in any order, with an immune checkpoint inhibitor. Conveniently, the previous treatment comprised administration of the polypeptide, the nucleic acid molecule or the T-cell receptor or the T-cell to the patient simultaneously, separately or sequentially with an immune checkpoint inhibitor. According to another aspect of the present invention, there is provided an immune checkpoint inhibitor for use in the treatment of cancer, wherein the immune checkpoint inhibitor is administered to a patient simultaneously, separately or sequentially with: (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), wherein the patient has been identified as having, or predicted to have, a clinical response to a previous treatment comprising administration of the immune checkpoint inhibitor, simultaneously, separately or sequentially with the polypeptide, the nucleic acid molecule, the T-cell receptor or the T-cell. 13399613-3 According to another aspect of the present invention, there is provided a method of treating cancer in a patient, the method comprising the steps of simultaneously, or separately or sequentially in any order: (I) administering to the patient an immune checkpoint inhibitor, (II) administering to the patient: (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), wherein the patient has been identified as having, or predicted to have, a clinical response to a previous treatment comprising administration of the immune checkpoint inhibitor, simultaneously, separately or sequentially with the polypeptide, the nucleic acid molecule, the T-cell receptor or the T-cell. Conveniently, step (I) comprises administering the immune checkpoint inhibitor to the patient at a dosage of between 100 and 2000 mg, preferably 200 mg. Preferably, step (II) comprises administering the polypeptide of the invention or the cocktail of polypeptides of the invention at a dosage of between 100 and 700 µg, preferably 300 µg. Advantageously, step (II) further comprises simultaneously, separately or sequentially administering an adjuvant, preferably GM-CSF. Conveniently, GM-CFS is administered at a dosage of between 20 and 100 µg, preferably 37.5 µg or 75 μg. Preferably, the immune checkpoint inhibitor is a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. 13399613-3 Conveniently, the patient has been identified as having, or predicted to have, a clinical response using a method of the invention. Preferably, the polypeptide comprises a sequence selected from: (i) SEQ ID NO.1; (ii) the sequence of an immunogenic fragment of (i) comprising at least 12 amino acids; or (iii) a sequence having at least 80% sequence identity to (i) or (ii). Advantageously, the polypeptide is a cocktail of polypeptides and wherein the cocktail of polypeptides further comprises: (a) a polypeptide comprising a sequence selected from: (i) SEQ ID NO.2; (ii) the sequence of an immunogenic fragment of (i) comprising at least 12 amino acids; or (iii) a sequence having at least 80% sequence identity to (i) or (ii), and/or (b) a polypeptide comprising a sequence selected from: (iv) SEQ ID NO.3; (v) the sequence of an immunogenic fragment of (iv) comprising at least 12 amino acids; or (vi) a sequence having at least 80% sequence identity to (iv) or (v). Conveniently, the PD-1/PD-L1 immune checkpoint inhibitor comprises one or more selected from: an anti-PD-1 antibody or a functional fragment thereof, an anti-PD-L1 antibody or a functional fragment thereof, a peptide-based or small molecule inhibitor of PD-1, and/or a peptide-based or small molecule inhibitor of PD-L1; and/or the CTLA-4 immune checkpoint inhibitor comprises one or more selected from: an anti- CTLA-4 antibody or a functional fragment thereof and/or a peptide-based or small molecule inhibitor of CTLA-4. Preferably, the anti-PD-1 antibody or a functional fragment thereof comprises one or more selected from: pembrolizumab, nivolumab and/or cemiplimab; and/or the anti-PD-L1 antibody or a functional fragment thereof comprises one or more selected from: durvalumab, atezolizumab and/or avelumab; and/or 13399613-3 the anti-CTLA-4 antibody or a functional fragment comprises one or more selected from: ipilimumab or tremelimumab. Advantageously, the immune checkpoint inhibitor is a PD-1/PD-L1 immune checkpoint inhibitor and a CTLA-4 immune checkpoint inhibitor, preferably an anti-PD-1 antibody or a functional fragment thereof and an anti-CTLA-4 antibody or a functional fragment thereof, more preferably nivolumab and ipilimumab. Conveniently, the polypeptide or one or more polypeptides in the cocktail of polypeptides is linked to a further substance. Preferably, the medicament, the polypeptide, the nucleic acid molecule, the T-cell receptor or the T-cell, or the immune checkpoint inhibitor is administered simultaneously, separately or sequentially with a further therapeutic ingredient. Conveniently, a clinical response comprises a partial or a complete response and/or wherein a clinical non-response comprises a stable or a progressive disease. According to another aspect of the present invention, there is provided a method for identifying or predicting the presence or absence of a clinical response of a cancer patient to a medicament, wherein the medicament comprises: (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), the method comprising the step of: (a) evaluating an hTERT level in a biological sample obtained from the cancer patient at a time point subsequent to an administration of the medicament, 13399613-3 wherein the evaluated hTERT level is negatively associated with the presence of a clinical response of the cancer patient to the medicament or positively associated with the absence of a clinical non-response of the cancer patient to the medicament. According to another aspect of the present invention, there is provided a method of selecting a patient for further treatment with a medicament, wherein the medicament comprises: (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C), the method comprising the step of: (a) evaluating an hTERT level in a biological sample obtained from the cancer patient at a time point subsequent to an administration of the medicament, wherein the evaluated hTERT level is negatively associated with a clinical response of the cancer patient to the medicament or positively associated with a clinical non- response of the cancer patient to the medicament, and wherein the cancer patient identified as having, or predicted to have, a clinical response is selected as a patient for further treatment with the medicament. Conveniently, the method further comprises the step of: (b) administering the medicament to the cancer patient identified in step (a). Brief Description of the Figures Figure 1 is bar graph summarising the objective responses of metastatic malignant melanoma patients who have been administered the polypeptides of SEQ ID NOS.1, 2 and 3 in combination with pembrolizumab. The data show the cancer stage of each patient (stage IIIB-C, IV) and the objective responses according to iRECIST criteria. The objective responses were based on computerised tomography (CT) scan measurements 13399613-3 of tumor size. The CT scans were performed as a part of the study protocol up to 2 years from initial treatment. iCR: complete response, iPR: partial response, iSD: stable disease, and iCPD/iUPD: confirmed/unconfirmed progressive disease. *Lymph node target lesion was reduced from 17.2mm to 6.3mm (-63% change). A lymph node size of <10mm is considered normal, and a PET/CT scan later confirmed no malignant activity. The patient was therefore considered iCR according to iRECIST. Figure 2 shows graphs summarising the baseline tumor mutational burden (TMB) (Figure 2A) and baseline predicted neoantigens (Figure 2B) in the metastatic melanoma patients who were administered the polypeptides of SEQ ID NOS.1, 2 and 3 in combination with pembrolizumab. The data are shown by grouping patients into those identified as “Responders (R)” i.e. exhibiting a complete response (iCR) or a partial response (iPR) and those identified as “Non-Responders (NR)” i.e. those exhibiting stable disease (iSD) or confirmed/unconfirmed progressive disease (iCPD/iUPD) according to iRECIST criteria. Statistical significance for both TMB and the neoantigen data assessed using the Mann-Whitney test. Figure 3 shows pie charts summarising the objective responses of the metastatic malignant melanoma patients, who have been administered the polypeptides of SEQ ID NOS.1, 2 and 3 in combination with pembrolizumab (as per Figure 1). The data show the objective responses overall (Figure 3A) or grouped by PD-L1 positivity (Figures 3B and 3C). PD-L1 staining was performed using anti-PD-L1 antibody 22C3 pharmDx for Autostainer Link 48. PD-L1 positivity was defined as ≥1% of viable tumor cells (i.e. a tumor proportion score (TPS) of ≥1%). iCR: complete response, iPR: partial response, iSD: stable disease, and iCPD/iUPD: confirmed/unconfirmed progressive disease. Figure 4 shows a heat map of an interferon-gamma signature which is defined by the expression levels at baseline of a validated 18-gene list (Ayers M. et al., J Clin Invest. 2017 Aug 1;127(8):2930-2940). The “row z-score” is shown whereby the RNA expression levels (TPM / transcripts per million) are normalized for each gene across the patients who have been administered the polypeptides of SEQ ID NOS.1, 2 and 3 in combination with pembrolizumab. iCR: complete response, iPR: partial response, iSD: stable disease, and iCPD/iUPD: confirmed/unconfirmed progressive disease. 13399613-3 Figure 5 shows a heat map of the interferon-gamma signature as shown in Figure 4, together with the expression level of hTERT at baseline (“Target antigen”). The row z- score value of each cell is shown in the heat map. Blank cells have a row z-score that is < 0.00. Figure 6 is a schematic showing a treatment regimen for the administration of the polypeptides of SEQ ID NOS. 1, 2 and 3 (“UV1 vaccination”) in combination with pembrolizumab. Figures 7A to 7C are Kaplan-Meier plots showing efficacy readouts in patients who had been administered the polypeptides of SEQ ID NOS. 1, 2 and 3 in combination with pembrolizumab. Figure 7A shows progression-free survival (PFS) and Figure 7B shows overall survival (OS) in all patients (N=30). Figure 7C shows the duration of response (DOR) (n=17). Figure 8 is a spider plot showing the percent change in tumor size from baseline. One line represents one patient, symbol-coded by best overall response according to iRECIST criteria. iCR: complete response, iPR: partial response, iSD: stable disease, and iCPD/iUPD: confirmed/unconfirmed progressive disease. Figure 9A is a line graph showing vaccine-induced T-cell responses against hTERT that were documented in 10 patients who had been administered the polypeptides of SEQ ID NOS.1, 2 and 3 in combination with pembrolizumab. Figure 9A shows the difference between the baseline sample (“BL”) and the highest stimulation index (SI) achieved (“Max”). Cohort 1 or 2 refers to whether patients received a dose of 37.5 μg or 75 μg of GM-CSF respectively. Figure 9B is a line graph showing immune response development over time in the 10 patients. Figure 10 is a heat map showing the change in tumor expression of genes related to T- cell function and activation, cytokine activity, immune checkpoint molecules, and the target antigen (hTERT), as assessed by RNA sequencing. The heat map shows the relative change in expression (transcripts per million (TPM)) from baseline to week 14 of treatment. The Log2(fold change) value of each cell is shown in heat map. Blank cells have a Log2(fold change) that is < 0.00. The Log2(fold change) was uncalculable for cells marked with “X” (zero transcripts per million in either baseline or week 14 biopsy). 13399613-3 Figure 11 is a receiver operating characteristic (ROC) curve produced from data on the difference in hTERT mRNA expression levels between baseline and week 14 of treatment (“TERT delta”) among clinical responders (n=7) and clinical non-responders (n=6). The area under the ROC curve (AUC) was 0.9524 (95% CI, 0.84 to 1.00, p value 0.0066). Figure 12 is a ROC curve produced from hTERT mRNA expression levels (raw transcripts per million (TPM)) determined at week 14 of treatment (“TERT TPM W14”). The AUC was 0.867 (95% CI, 0.62 – 1.0) with a p-value of 0.023. Figure 13A is a spider plot showing the percent change in tumor size from baseline. One line represents one patient, and the plot is coded according to whether the hTERT levels were above or below 0.33 TPM at week 14 of treatment. A dashed line indicates an hTERT level above 0.33 TPM whereas a solid line indicates an hTERT level below 0.33 TPM. The stars indicate the time point of the biopsy. Figure 13B is a spider plot showing the percent change in tumor size from baseline for patients exhibiting stable disease at week 14 of treatment. One line represents one patient and the hTERT level as measured at week 14 is shown for each patient. A dashed line indicates an hTERT level above 0.33 TPM whereas a solid line indicates an hTERT level below 0.33 TPM. The stars indicate the time point of the biopsy. PD: progressive disease; SD: stable disease; PR: partial response; and CR: complete response. Figure 14 is a heat map showing the change in tumor expression of various genes, including the target antigen (hTERT) and the tumor-associated antigen CTAG1B (NY- ESO-1) as assessed by RNA sequencing. The heat map shows the relative change in expression (transcripts per million (TPM)) from baseline to week 14 of treatment. The percentage change value of each cell is shown in the heat map. The percentage change was uncalculable for cells marked with “X” (zero transcripts per million at baseline). iCR: complete response, iPR: partial response, iSD: stable disease, and iPD: progressive disease. 13399613-3 Figure 15 is a heat map showing the change in tumor expression of various genes, including the target antigen (hTERT) and the tumor-associated antigen CTAG1B (NY- ESO-1) as assessed by RNA sequencing. The heat map shows the relative change in expression (transcripts per million (TPM)) from baseline to week 14 of treatment. The Log2(fold change) value of each cell is shown in the heat map. The Log2(fold change) was uncalculable for cells marked with “X” (zero transcripts per million in either baseline or week 14 biopsy). iCR: complete response, iPR: partial response, iSD: stable disease, and iPD: progressive disease. Definitions The terms “polypeptide”, “peptide” and “protein” are used interchangeably herein to refer to a polymer of amino acid residues. The terms apply to amino acid polymers in which one or more amino acid residues is a modified residue, or a non-naturally occurring residue, such as an artificial chemical mimetic of a corresponding naturally occurring amino acid, as well as to naturally occurring amino acid polymers. In some embodiments, the term “polypeptide” refers to a polypeptide of a single sequence. In other embodiments the term “polypeptide” refers to a cocktail (i.e. a mixture) of polypeptides. In some embodiments, the term “polypeptide” refers to one of more (or each) polypeptide within the cocktail of polypeptides. The term “amino acid” as used herein refers to naturally occurring and synthetic amino acids, as well as amino acid analogues and amino acid mimetics that have a function that is similar to the naturally occurring amino acids. Naturally occurring amino acids are those encoded by the genetic code, as well as those modified after translation in cells (e.g. hydroxyproline, gamma-carboxyglutamate, and O-phosphoserine). The phrase “amino acid analogue” refers to compounds that have the same basic chemical structure (an alpha carbon bound to a hydrogen, a carboxy group, an amino group, and an R group) as a naturally occurring amino acid but have a modified R group or modified backbones (e.g. homoserine, norleucine, methionine sulfoxide, methionine methyl sulphonium). The phrase “amino acid mimetic” refers to chemical compounds that have different structures from but similar functions to naturally occurring amino acids. The term “fragment” as used herein in relation to a polypeptide means a consecutive series of amino acids that form part of the polypeptide. An “immunogenic fragment” of a 13399613-3 polypeptide is a fragment as previously defined which is capable of eliciting an immune response, such as a T-cell response, when administered to a subject. In one embodiment, the “immunogenic fragment” is capable of eliciting a CD4+ T-cell response when administered to a subject. In one embodiment, the “immunogenic fragment” is capable of eliciting a CD4+ and/or CD8+ T-cell immune response when administered to a subject. In some embodiments, the immunogenic fragment comprises at least 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28 or 29 amino acids of the polypeptide from which it is derived. The terms “gene”, “polynucleotides”, and “nucleic acid molecules” are used interchangeably herein to refer to a polymer of multiple nucleotides. The nucleic acid molecules may comprise naturally occurring nucleic acids or may comprise artificial nucleic acids such as peptide nucleic acids, morpholin and locked nucleic acid as well as glycol nucleic acid and threose nucleic acid. The term “nucleotide” as used herein refers to naturally occurring nucleotides and synthetic nucleotide analogues that are recognised by cellular enzymes. The terms “cancer” and “tumor” as used herein refer to the presence of cells in a subject that exhibit new, abnormal and/or uncontrolled proliferation. In one embodiment, the cells have the capacity to invade adjacent tissues and/or to spread to other sites in the body (i.e. the cells are capable of metastasis). In one embodiment, the cancer cells are in the form of a tumor (i.e. an abnormal mass of tissue). The term “tumor” as used herein includes both benign and malignant neoplasms. The term “treatment” as used herein refers to any partial or complete treatment and includes: inhibiting the disease or symptom, i.e. arresting its development; and relieving the disease or symptom, i.e. causing regression of the disease or symptom. Thus the term “treatment” as used herein can include delaying, terminating and/or suppressing the progression of a disease as well as the regression and/or disappearance of a disease site. In some embodiments, the term “treatment” as used herein refers to a therapy (e.g. a medicament or a combination therapy) that is suitable to be administered to a patient who is suffering from a disease, such as cancer. 13399613-3 The term “clinical outcome” as used herein refers to whether a patient develops a clinical response or a clinical non-response (as defined below) to a therapy. The term “clinical response” as used herein refers to a patient exhibiting an improvement in a disease or symptom in response to a therapy. In one embodiment, the “clinical response” refers to a patient exhibiting a partial or a complete response to a therapy. Thus in one embodiment, a clinical response consists of a partial or a complete response to the therapy. In one embodiment, a partial response in a cancer patient refers to a decrease in the signs and/or symptoms of a tumor or cancer. In one embodiment, a complete response in a cancer patient refers to the disappearance of the signs and/or symptoms of a cancer or tumor. In a preferred embodiment, a partial or a complete response is assessed using RECIST 1.1 or iRECIST criteria (Eisenhauer EA et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009 Jan;45(2):228-47; or Seymour L, et al. iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics. Lancet Oncol. 2017 Mar;18(3):e143-e152, both incorporated herein by reference). The term “clinical non-response” as used herein refers to a patient in whom a disease or symptom stays the same or progresses. In one embodiment, the “clinical non-response” refers to a patient exhibiting a stable or a progressive disease following administration of a therapy. Thus in one embodiment, a clinical non-response consists of a stable disease or a progressive disease. In one embodiment, a stable disease in a cancer patient refers to the signs and/or symptoms of a tumor or cancer staying the same. In one embodiment, a progressive disease in a cancer patient refers to the cancer or tumor (or the signs/symptoms thereof) growing, spreading and/or getting worse. In one embodiment, the term “progressive disease” incorporates confirmed progressive disease and/or unconfirmed progressive disease. In a preferred embodiment, a stable or a progressive disease is assessed using RECIST 1.1 or iRECIST criteria (Eisenhauer EA et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009 Jan;45(2):228-47; or Seymour L, et al. iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics. Lancet Oncol.2017 Mar;18(3):e143-e152, both incorporated herein by reference). The term “identifying or predicting a clinical outcome” as used herein refers to establishing whether a cancer patient has or will have a clinical response or a clinical 13399613-3 non-response. In some embodiments, the term “identifying a clinical outcome” refers to an evaluated hTERT level indicating that a patient is a clinical responder or a clinical non-responder (i.e. has a clinical response or a clinical non-response respectively, as defined above). In some embodiments, the term “predicting a clinical outcome” refers to an evaluated hTERT level indicating that a patient will be a clinical responder or a clinical non-responder at a future time point, despite the patient not yet meeting the relevant criteria. That is to say, the patient is predicted to exhibit clinical response or to exhibit a clinical non-response/progression (as defined above) at a time point subsequent to the time point at which the hTERT level is evaluated. In one embodiment, the hTERT level is evaluated at week 14 after the first administration of a medicament and the patient exhibits the clinical response or clinical non-response/progression at 10, 20, 30, 35, 38, 40, 50, 55, 58, 60, 70, 80, 90, 100, 150 or 200 days after the time point at which the hTERT level was evaluated. The term “T-cell” (also known as “T lymphocyte”) as used herein refers to a cell of the immune system which has a cell surface T-cell receptor. In one embodiment, the term “T-cell” comprises different types of T cell, such as: CD4+ T-cells (also known as helper T-cells or Th cells), CD8+ T-cells (also known as cytotoxic T-cells or CTLs), memory T- cells and regulatory T-cells (Tregs). The term “CD4+ T-cell” as used herein refers to a T-cell comprising a CD4 glycoprotein on its cell surface. The term “CD8+ T-cell” as used herein refers to a T-cell comprising a CD8 glycoprotein on its cell surface. The term “the T-cell receptor” as used herein refers to an antigen receptor of the T- cell. In some embodiments, the T-cell receptor recognises (i.e. binds to) a polypeptide when presented by an MHC molecule. The term “a T-cell displaying the T-cell receptor” as used herein refers to a T-cell that comprises the T-cell receptor on its cell surface. In some embodiments, the T-cell receptor is responsible for recognising (i.e. binding to) a polypeptide such as when the polypeptide is presented by an MHC molecule. In some embodiments, the binding of the T-cell receptor to the polypeptide when presented by the MHC molecule results in activation of the T-cell displaying the T-cell receptor. T cell activation can be measured using T-cell response assays and ELISPOT assays (Gjertsen MK et al. J Mol Med (Berl) 2003;81:43–50; Inderberg-Suso EM et al., Oncoimmunology 20121(5):670-686, both incorporated herein by reference). 13399613-3 The term “the T-cell receptor or T-cell is specific for a polypeptide” as used herein refers to a T-cell receptor or a T cell comprising the T-cell receptor that is capable of recognising (i.e. binding to) the polypeptide such as when the polypeptide is presented on an MHC molecule. In some embodiments, the polypeptide to which the T-cell receptor (or the T- cell displaying the T-cell receptor) is specific, is of a length that is longer than that which would normally be accommodated on an MHC molecule. In these embodiments, the term “the T-cell receptor or T-cell is specific for a polypeptide” as used herein refers to the recognition by the T-cell receptor or T-cell of an immunogenic fragment of the polypeptide when presented on the MHC molecule. In some embodiments, the binding of the T-cell receptor or T-cell to the polypeptide to which it is specific results in activation of a T-cell. T cell activation can be measured using T-cell response assays and ELISPOT assays (Gjertsen MK et al. J Mol Med (Berl) 2003;81:43–50; Inderberg-Suso EM et al., Oncoimmunology 20121(5):670-686, both incorporated herein by reference). The term “MHC molecule” as used herein refers to a protein structure which assembles with a polypeptide and which is capable of displaying the polypeptide at a cell surface to a T-cell. MHC molecules are encoded by genes within the major histocompatibility complex. In some embodiments, the term “MHC molecule” refers to an MHC class I molecules and/or an MHC class II molecule. The term “immune checkpoint” as used herein refers to any point at which an immune response is limited. Immune checkpoints are inhibitory pathways that slow down or stop immune reactions and prevent excessive tissue damage from uncontrolled activity of immune cells. In one embodiment, the “immune checkpoint” is the programmed cell death protein 1 (PD-1)/programmed cell death 1 ligand 1 (PD-L1) immune checkpoint. A further example of an immune checkpoint is the cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) checkpoint. The term “immune checkpoint inhibitor” as used herein refers to any compound, substance or composition that is capable of down-regulating or blocking an immune checkpoint allowing more extensive immune activity. In some embodiments, the terms “compound, substance or composition” as used herein refer to any one or more of: a small molecule, a chemical compound, an antibody or a fragment thereof (preferably a functional fragment thereof), a nucleic acid molecule or a fragment thereof, a polypeptide 13399613-3 or a fragment thereof, a peptide-based compound, a vaccine or a viral vaccine. The term “checkpoint inhibitor” is used interchangeably herein with “immune checkpoint inhibitor”. In some embodiments, the immune checkpoint inhibitor is an antibody or a functional fragment thereof that specifically binds to a protein involved in the immune checkpoint pathway thereby disrupting and down-regulating the overall activity of the immune checkpoint. Examples of such an immune checkpoint inhibitor include an anti-CTLA-4 antibody, an anti-PD-1 antibody and/or an anti-PD-L1 antibody. In alternative embodiments, the immune checkpoint inhibitor is a peptide-based or small molecule inhibitor (antagonist) that interferes with and/or inhibits the activity of a protein involved in the immune checkpoint pathway and thereby down-regulates the overall activity of the immune checkpoint. Examples of such an immune checkpoint inhibitor include a peptide-based or small molecule inhibitor that targets the CTLA-4 and/or PD-1/PD-L1 proteins in order to down-regulate the CTLA-4 and/or PD-1/PD-L1 checkpoints. In an alternative embodiment, the immune checkpoint inhibitor is targeted at another member of the CD28CTLA4 Ig superfamily such as BTLA, LAG3, ICOS, PDL1 or KIR (Page et al., Annual Review of Medicine 65:27 (2014)). In a further alternative embodiment, the immune checkpoint inhibitor is targeted at a member of the TNFR superfamily such as CD40, OX40, CD137, GITR, CD27 or TIM-3. In one embodiment, the immune checkpoint inhibitor targets Indoleamine 2,3-dioxygenase (IDO). In some embodiments, targeting an immune checkpoint is accomplished with an inhibitory antibody or similar molecule. In other embodiments, it is accomplished with an agonist for the target; examples of this class include the stimulatory targets OX40 and GITR. In a preferred embodiment, the immune checkpoint inhibitor targets an immune checkpoint that is involved in the regulation of a T-cell. In some embodiments, the immune checkpoint that is targeted is a negative regulator of T-cell activity; thus the action of the immune checkpoint inhibitor allows for more extensive T-cell activity. As discussed above, in some embodiments, the immune checkpoint inhibitor targets a member of the CD28CTLA4 immunoglobulin (Ig) superfamily. Proteins in the immunoglobulin superfamily possess an immunoglobulin domain (also known an immunoglobulin fold) which is a characteristic beta-sheet fold. CTLA-4, PD-1 and PD- L1 are examples of members of the CD28CTLA4 Ig superfamily. 13399613-3 The term “PD-1/PD-L1 immune checkpoint inhibitor” as used herein refers to any compound, substance or composition that is capable of down-regulating or blocking the PD-1/PD-L1 immune checkpoint. The term “PD-1/PD-L1 immune checkpoint inhibitor” is used interchangeably herein with “inhibitor of the PD-1/PD-L1 immune checkpoint”. In some embodiments, the terms “compound, substance or composition” as used herein refer to any one or more of: a small molecule, a chemical compound, an antibody or a fragment thereof (preferably a functional fragment thereof), a nucleic acid molecule or a fragment thereof, a polypeptide or a fragment thereof, a peptide-based compound, a vaccine or a viral vaccine. PD-1 is an inhibitory receptor on antigen activated T-cells. It delivers inhibitory signals to the T-cells upon binding to its ligand PD-L1. In one embodiment, the “PD-1/PD-L1 immune checkpoint inhibitor” inhibits the interaction between the PD-1 receptor and the PD-L1 ligand. In one embodiment, the “PD-1/PD-L1 immune checkpoint inhibitor” is an inhibitor of PD-1. In one embodiment, the inhibitor of PD-1 is capable of interacting specifically with PD-1 in order to disrupt its function. In one embodiment, the “PD-1/PD-L1 immune checkpoint inhibitor” is an inhibitor of PD-L1. In one embodiment, the inhibitor of PD-L1 is capable of interacting specifically with PD- L1 in order to disrupt its function. In some embodiments, the “PD-1/PD-L1 immune checkpoint inhibitor” comprises an antibody or a fragment thereof, preferably a functional fragment thereof, a peptide-based inhibitor and/or a small molecule inhibitor. In a preferred embodiment, the PD-1/PD-L1 immune checkpoint inhibitor comprises an anti-PD-1 antibody or a functional fragment thereof and/or an anti-PD-L1 antibody or a functional fragment thereof. That is to say, the antibody or the functional fragment thereof binds specifically to PD-1 and/or PD-L1 respectively. In one embodiment, the peptide-based inhibitor or the small molecule inhibitor comprises an inhibitor of PD-L1 and/or PD-1. That is to say, it targets PD-L1 and/or PD-1 specifically in order to disrupt their normal function and down-regulate or block the overall activity of the PD-1/PD-L1 immune checkpoint. Thus in one embodiment, the peptide-based inhibitor or the small molecule inhibitor is a PD-L1 antagonist and/ a PD-1 antagonist. The term “CTLA-4 immune checkpoint inhibitor” as used herein refers to any compound, substance or composition (e.g. as defined above) that is capable of down-regulating or blocking the CTLA-4 immune checkpoint. The term “CTLA-4 immune checkpoint inhibitor” is used interchangeably herein with “inhibitor of the CTLA-4 immune 13399613-3 checkpoint”. CTLA-4 is an inhibitory receptor that acts as a major negative regulator of T-cell responses. CTLA-4 is upregulated on activated T-cells and binds to B7 family ligands (e.g. CD80 and/or CD86) expressed on antigen-presenting cells. This interaction suppresses further T-cell activity. In one embodiment, the “CTLA-4 immune checkpoint inhibitor” inhibits the interaction between CTLA-4 and a B7 family ligand. In one embodiment, the B7 family ligand is CD80 and/or CD86. In one embodiment, the “CTLA- 4 immune checkpoint inhibitor” is an inhibitor of CTLA-4. In one embodiment, the inhibitor of CTLA-4 is capable of interacting specifically with CTLA-4 in order to disrupt its function. In some embodiments, the “CTLA-4 immune checkpoint inhibitor” comprises an antibody or a fragment thereof, preferably a functional fragment thereof, a peptide-based inhibitor and/or a small molecule inhibitor. In a preferred embodiment, the CTLA-4 immune checkpoint inhibitor comprises an anti-CTLA-4 antibody or a functional fragment thereof. That is to say, the antibody or the functional fragment thereof binds specifically to CTLA- 4. In one embodiment, the peptide-based inhibitor or the small molecule inhibitor comprises an inhibitor of CTLA-4. That is to say, it targets CTLA-4 specifically in order to disrupt its normal function and down-regulate or block the overall activity of the CTLA- 4 immune checkpoint. Thus in one embodiment, the peptide-based inhibitor or the small molecule inhibitor is a CTLA-4 antagonist. In some embodiments, there is provided a PD-1/PD-L1 immune checkpoint inhibitor and a CTLA-4 immune checkpoint inhibitor. In one embodiment, there is provided an anti- PD-1 antibody or a functional fragment thereof and an anti-CTLA-4 antibody or a functional fragment thereof, more preferably nivolumab and ipilimumab. The term “tumor-associated antigen” as used herein refers to an antigen that is associated with a tumor or cancer cell. In some embodiments, the “tumor-associated antigen” is expressed at a higher level on the tumor or cancer cell and at a lower level on the normal cell. In one embodiment, the “tumor-associated antigen” is a “universal tumor antigen”. The term “universal tumor antigen” as used herein refers to an antigen that is expressed in a high proportion of tumor types. In one embodiment, the universal tumor antigen is expressed in at least 50%, 60% or 70% or all tumor types, more preferably in at least 13399613-3 80%, 85% or 90% of all tumor types. In a further embodiment, the universal tumor antigen is also expressed in a high proportion of patients within each tumor type. In one embodiment, the universal tumor antigen is generally expressed in at least 40%, 50%, 60%, 70%, 80% or 90% of patients within each tumor type. In one embodiment, the universal tumor antigen has a direct role in oncogenesis. In one embodiment the universal tumor antigen is selected from the group consisting of telomerase reverse transcriptase, survivin, DNA topoisomerase 2-alpha (Top2α), cytochrome P450 1B1 (CYP1B1) and E3 ubiquitin-protein ligase Mdm2. Preferably, the universal tumor antigen is human telomerase reverse transcriptase (hTERT). The term “telomerase reverse transcriptase” (TERT) as used herein refers to the catalytic component of the telomerase holoenzyme complex whose main activity is the elongation of telomeres by acting as a reverse transcriptase that adds simple sequence repeats to chromosome ends by copying a template sequence within the RNA component of the telomerase enzyme. In some embodiments, the term “telomerase reverse transcriptase” refers to human telomerase reverse transcriptase (hTERT). The full-length hTERT sequence is set out in GenBank accession no. AF015950.1. The amino acid sequence of hTERT is also set forth in SEQ ID NO.6. The term “hTERT level” as used herein refers to the amount of hTERT in a given sample. In one embodiment, the “hTERT level” as used herein refers to an expression level of hTERT. In a preferred embodiment, the “hTERT level” is an mRNA level of hTERT. That is to say, the amount of hTERT mRNA in a given sample. An mRNA level of hTERT can be measured by RNA sequencing (see, for example, Hong, M., et al. RNA sequencing: new technologies and applications in cancer research. J Hematol Oncol 13, 166 (2020), incorporated herein by reference). In one embodiment, the mRNA level of hTERT is measured by sequencing tumor biopsy-derived RNA. In one embodiment, the hTERT level is measured by transcriptome analysis of tumor-derived entities, such as circulating tumor cells, in a liquid biopsy (e.g. a blood sample) (see, for example, Negishi, R., et al. Transcriptomic profiling of single circulating tumor cells provides insight into human metastatic gastric cancer. Commun Biol 5, 20 (2022), incorporated herein by reference). In an alternative embodiment, the “hTERT level” is a protein level of hTERT. That is to say, the amount of hTERT protein in a given sample. A protein level of hTERT can be measured by western blot (see, for example, Hnasko, T.S., Hnasko, R.M. (2015). The Western Blot. In: Hnasko, R. (eds) ELISA. Methods in Molecular Biology, vol 1318. 13399613-3 Humana Press, New York, NY, incorporated herein by reference) or immunohistochemistry (see, for example, Ellingsen, E.B., et al. Characterization of the T cell receptor repertoire and melanoma tumor microenvironment upon combined treatment with ipilimumab and hTERT vaccination. J Transl Med 20, 419 (2022), incorporated herein by reference). The term “the evaluated hTERT level is negatively associated with a clinical response” as used herein refers to a negative correlation between an hTERT level and a clinical response. Thus in some embodiments, a low hTERT level or a decrease in the hTERT levels is indicative or predictive of the cancer patient exhibiting a clinical response. The term “the evaluated hTERT level is positively associated with a clinical non- response” as used herein refers to a positive correlation between an hTERT level and a clinical non-response. Thus in some embodiments, a high hTERT level or an increase in hTERT levels is indicative or predictive of the cancer patient exhibiting a clinical non- response. The term “reference value” as used herein refers to a threshold against which an hTERT level or a change in hTERT levels is compared in order to identify or predict a clinical outcome of a patient. In some embodiments, the reference value is calculated from data on the hTERT levels or the change in hTERT levels in subjects within a population of control subjects. In a preferred embodiment, the reference value is calculated using a Receiver Operating Characteristic (ROC) analysis based on the hTERT levels or change in hTERT levels and clinical data obtained from a population of control subjects. Examples of a ROC analysis are described in Examples 8 and 9 of the present specification. In one embodiment, a ROC analysis is performed using GraphPad Prism 9.4.1 software (San Diego, California, USA) and the Wilson/Brown method. In a preferred embodiment, the reference value enables the identification or prediction of a clinical outcome with high sensitivity and/or high specificity, more preferably high sensitivity and high specificity. In some embodiments the sensitivity and/or specificity is at least 70%, 75%, 80%, 85%, 90%, 95% or 100%. In one embodiment, the reference value is an hTERT level, calculated from the mRNA levels of hTERT in a population of control subjects and corresponds to 0.3 TPM, preferably 0.33 TPM. In other embodiments, the reference value is an hTERT level corresponding to 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.4, 0.5, 0.6, 0.7, 0.77, 0.8 or 0.9 TPM. In an alternative 13399613-3 embodiment, the reference value is a difference in hTERT level, calculated from the difference in hTERT levels between control hTERT levels and evaluated hTERT levels in population of control subjects (measured in terms of mRNA levels) and corresponds to -0.1 TPM. In other embodiments, the reference value is a difference in hTERT level corresponding to -0.6, -0.5, -0.4, -0.3, -0.2, -0.12, 0.005 or 0.006. The term “population of control subjects” as used herein refers to a group of individuals from which data on hTERT levels can be evaluated. In one embodiment, the population of control subjects is a population of cancer patients. That is to say, a group of patients who have been diagnosed with cancer. In one embodiment, the population of cancer patients is a group of patients who have been diagnosed with a particular type of cancer (e.g. malignant melanoma, mesothelioma, head and neck cancer, ovarian cancer, non- small cell lung cancer). In one embodiment, the population of cancer patients is a sample of individuals (e.g. at least 10, 20 or 50 randomly selected individuals) who have been diagnosed with a particular type of cancer and who are taken to be representative of the wider patient population. In one embodiment, the population of cancer patients is a cohort of patients who are undergoing study or treatment. In a further embodiment, the population of control subjects comprises patients that have been diagnosed with different types of cancer. In one embodiment, the population of control subjects is a population of patients having any one or more of the cancers described herein in which the telomerase enzyme is expressed. As the telomerase enzyme is expressed in the majority of human cancers, the population of control subjects is not limited to patients having any one particular type of cancer. It is to be understood that in some embodiments, the population of control subjects comprises a mixture of individuals who exhibit or will develop a clinical response as well as individuals who exhibit or will develop a clinical non-response. In other embodiments, the population of control subjects comprises or consists of patients who have been identified as having, or predicted to have, a clinical response and/or who are healthy individuals (that is to say, who have not been diagnosed with cancer). In other embodiments, the population of control subjects comprises or consists of individuals who have been identified as having, or predicted to have, a clinical non-response. The term “the same as” as used herein in relation to two or more hTERT levels refers to hTERT levels that are similar and/or statistically the same as each other. In one 13399613-3 embodiment, two or more hTERT levels are “the same as” each other if they are within 20% of each other, preferably within 15%, 10% or 5% of each other. That is to say, a first hTERT level is “the same as” a second hTERT level when there is a less than 20% difference between the two levels, preferably a less than 15%, 10% or 5% difference. The term “correlate” as used herein refers to a similarity or association between two or more factors. In one embodiment, a correlation between a clinical outcome of a patient and a prior clinical outcome refers to a similar clinical outcome to that observed at the prior time point (i.e. a continued clinical response or a continued clinical non-response). In one embodiment, a correlation between an evaluated hTERT level and the hTERT levels of the population of control subjects refers to a similarity between the evaluated hTERT level that those observed in the population of control subjects. In one embodiment, the evaluated hTERT level is similar to and/or statistically the same as hTERT levels observed in the population of control subjects or is similar to and/or statistically the same as an average hTERT level calculated from the population of control subjects. In one embodiment, the evaluated hTERT level is within 20% of the average hTERT level, preferably within 15%, 10% or 5%. That is to say, there is less than a 20% difference between the evaluated hTERT level and the average hTERT level, preferably less than a 15%, 10% or 5% difference. The term “baseline hTERT level” as used herein refers the hTERT level in a biological sample obtained from a cancer patient prior to or shortly after an administration of a therapy. Thus in some embodiments, the “baseline hTERT level” refers to the hTERT level in a biological sample obtained from a cancer patient before the therapy has been administered or before it has taken effect. In one embodiment, the “baseline hTERT level” refers to the hTERT level measured in a biological sample obtained from the cancer patient prior to a first administration of a therapy or within 5 days of the first administration of the therapy, preferably within 4, 3 or 2 days of the first administration of the therapy, more preferably within 24 hours of the first administration of the therapy. The term “biological sample” as used herein refers to biological specimen obtained from a patient. In one embodiment, the biological sample is a sample of tumor or cancer tissue obtained by biopsy (i.e. a tumor biopsy or tissue biopsy) or a sample of tissue suspected of being a cancer or tumor. In one embodiment, the tumor biopsy is formalin fixed, paraffin embedded (FFPE). In an alternative embodiment, the tumor biopsy is 13399613-3 snap frozen. In an alternative embodiment, the biological sample is a liquid sample (i.e. a liquid biopsy), preferably a blood sample. The term “blood sample” also comprises samples of plasma, serum and other blood derivatives. In one embodiment, the liquid biopsy comprises tumor-derived entities such as circulating tumor cells, cell free or circulating tumor DNA and/or tumor extracellular vesicles (e.g. exosomes). The term “tumor mutational burden” (TMB) as used herein refers to the number of mutations per megabase (mut/Mb) or per exome harboured by tumor cells in a given neoplasm. Preferably, the term “tumor mutational burden” (TMB) as used herein refers to the number of somatic (non-inherited) mutations per megabase (mut/Mb) or per exome harboured by tumor cells in a given neoplasm. In one embodiment, the mutations included in the calculation have a variant allelic frequency of above 5%. That is to say, the counted mutations are present in more than 5% of the alleles sequenced for that gene. In one embodiment, TMB is calculated from sequencing of DNA extracted from a tumor tissue biopsy as described herein. In one embodiment, whole exome sequencing of the DNA is performed. In another embodiment, whole genome sequencing of the DNA is performed. In an alternative embodiment, TMB is calculated from sequencing of cell- free or circulating tumor DNA from a liquid biopsy. In one embodiment, the liquid biopsy is a blood sample. In some embodiments, it is advantageous to measure TMB based on a blood sample. For example, harvesting biopsies from patients can be both bothersome for the patients and challenging for the physician (if a tumor is located at non-accessible anatomical location). In embodiments where a liquid biopsy is taken, the blood sample is collected, and the plasma is separated to extract “cell-free DNA” (i.e. cfDNA). This DNA may be present due to DNA release from the tumor. In one embodiment, the sequencing procedure involves looking at mutations in genes commonly mutated in a tumor and subsequently calculating the TMB based on the frequency of mutations in these genes. In such embodiments, a panel consisting of approximately 500 genes is used (NovoPM 2.0). In embodiments in which whole exome sequencing is performed, it is preferred that the DNA is obtained from a tissue biopsy. In embodiments in which a panel of genes is sequenced (e.g. for NovoPM), it is preferred that the DNA is extracted cfDNA. In a preferred embodiment, TMB is calculated using the FoundationOne CDx assay (Foundation Medicine, Inc.). The term “PD-L1 expression” as used herein refers to the presence or amount of the ligand PD-L1 detected on a cell. Preferably, the presence or amount detected on the 13399613-3 cell membrane of a cell. In one embodiment, PD-L1 expression is assessed by immunohistochemistry as described herein. Preferably, an anti-PD-L1 antibody is used for the immunohistochemical analysis (O'Malley DP et al., Mod Pathol. 2019 Jul;32(7):929-942, incorporated herein by reference). In one embodiment, one or more of the following anti-PD-L1 antibodies is used: 22C3 (Dako; Carpinteria, California), 28- 8 (Dako; Carpinteria, California), SP142 (Ventana/Roche; Tucson, Arizona), and/or SP263 (Ventana/Roche; Tucson, Arizona). In one embodiment, PD-L1 expression is assessed by an FDA-cleared or approved companion diagnostic, as set out in Table I below. In a preferred embodiment, PD-L1 expression is assessed by the companion diagnostic in accordance with the cancer indication and medicament to be administered as set out in Table I below. Table I: FDA list of cleared or approved companion diagnostic devices 13399613-3 In one embodiment, the term “PD-L1 expression” as used herein refers to the presence or amount of the ligand PD-L1 detected on a tumor cell. Preferably, the presence or amount detected on the cell membrane of the tumor cell. In one embodiment, a “tumor proportional score” (TPS) is calculated as described herein to assess PD-L1 expression. A TPS is calculated according to the formula: TPS = (number of positive PD-L1 tumor cells/total number of viable tumor cells) x 100. In an alternative embodiment, the term “PD-L1 expression” as used herein refers to the presence or amount of the ligand PD- L1 detected on an immune cell. Preferably, the presence or amount detected on the cell membrane of the immune cell. In one embodiment, the immune cell is a tumor infiltrating immune cell, preferably a tumor infiltrating lymphocyte. In some embodiments, the term “PD-L1 expression” as used herein refers to the presence or amount of the ligand PD- L1 detected on a tumor cell and an immune cell, preferably on the cell membrane of the tumor cell and the immune cell. In one embodiment, a “combined positive score” (CPS) is calculated to assess PD-L1 expression on tumor cells and immune cells. A CPS is 13399613-3 calculated according to the formula: CPS = (number of PD-L1 positive cells [tumor cells, immune cells]/total number of viable cells) x 100. The term “tumor infiltrating lymphocyte” as used herein refers to a lymphocyte that has migrated from the blood into a tumor. In one embodiment, the TIL includes: a T-cell, preferably a CD4+ or CD8+ T-cell, a B-cell and/or a natural killer cell. In one embodiment, the presence or amount of a TIL is assessed by immunohistochemistry on a tumor tissue biopsy as described herein. In one embodiment, an anti-CD8α antibody is used to analyse the presence or amount of CD8+ T-cells. In one embodiment, the anti-CD8α antibody is clone C8/144B (Thermo Fisher Scientific Cat# MA5-13473, RRID:AB_11000353). In one embodiment, an anti-CD4 antibody is used to analyse the presence or amount of CD4+ T-cells. In one embodiment, the anti-CD4 antibody is the anti-CD4 antibody [EPR6855] (Abcam Cat# ab133616, RRID:AB_2750883). Preferably, the immunohistochemical analysis is used to calculate the density of TILs (counts/mm ² ). In a preferred embodiment, the TIL is a CD8+ T-cell and an anti-CD8+ antibody is used to calculate the CD8+ T-cell density (counts/mm ² ) in a tumor tissue biopsy sample as described herein. The term “neoantigen” as used herein refers to mutated antigens that are expressed specifically by a tumor cell and are not generally expressed by normal cells. In one embodiment, the level of neoantigens expressed by a tumor cell is predicted using a proprietary platform developed by NEC Oncoimmunity AS (Oslo, Norway). In such embodiments, neoantigens are predicted by analysing which mutations (e.g. based whole-exome sequencing of DNA) are expressed (e.g. confirmed by RNA sequencing) and evaluated as sufficiently different from a normal counterpart, and with good binding properties to patient-specific HLA type, such that they are expected to be recognized by the patients’ immune system (as described in Malone B. et al., Sci Rep. 2020 Dec 23;10(1):22375, incorporated herein by reference). In one embodiment, an antigen presentation (AP) score is used to predict neoantigens. The AP score reflects the features and likelihood of a somatic mutation being recognized by a T cell. In one embodiment, this includes metrics such as RNA expression levels of the mutated antigen, the “distance from self” (i.e. how different does the mutation make the peptide antigen), and how well does the mutated peptide fit with the patients’ HLA alleles. In some embodiments, an artificial intelligence (AI) prediction platform is used for immunogenic neoantigen prediction, preferably the NEC Immune Profiler (NIP). The NIP 13399613-3 software predicts each of the key determinants of antigen presentation (AP) for each somatic mutation, by predicting the potential of all tumor-specific mutated peptides to be efficiently presented by each of the patients Class I HLA-A and -B alleles. In some embodiments, a cut-off AP value of 0.6 or 0.7 is used to predict neoantigens, preferably a cut-off value of 0.6. The term “low” as used herein in relation to the level of TMB, PD-L1 expression, TIL and/or neoantigens refers to a level that is below a threshold (i.e. a specific) value and/or to a level that is below the 50 ^th percentile (i.e. the median) of a population. In one embodiment, the level is equal to or less than the threshold value or 50 ^th percentile. In a further embodiment, the level is equal to or less than the 40 ^th , 30 ^th , 25 ^th , 20 ^th , 10 ^th or 5 ^th percentile of a population. In a preferred embodiment, the population is a cancer patient population (as described below). In one embodiment, the term “low” as used in relation to the level of TMB refers to a level that is below 400, 300, 200, 100, 75, 50, 30, 25, 10, 5, 1, 0.1 or 0.001 somatic mutations per megabase (mut/Mb). Preferably, the term “low” as used herein in relation to the level of TMB refers to a level that is equal to or less than 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 6.6, 5, 4, 3 or 2 mut/Mb, most preferably equal to or less than 10 mut/Mb. In some embodiments, only mutations with a variant-allelic frequency (VAF) above 5% are considered in the TMB calculation. In one embodiment, the patient has a solid tumor and the term “low” refers to a TMB level that is equal to or less than 20, 15, 10 or 5 mut/Mb, preferably equal to or less than 10 mut/Mb. In one embodiment, the patient is to be administered an anti-PD-1 antibody, preferably pembrolizumab. In one embodiment, the patient is a melanoma patient and the term “low” refers to a TMB level that is equal to or less than 30, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 mut/Mb, preferably equal to or less than 20, 16, 15 or 10 mut/Mb. In one embodiment, the patient is to be administered an anti-PD-1 antibody, preferably nivolumab or pembrolizumab; and/or an anti-PD-L1 antibody, preferably atezolizumab. 13399613-3 In one embodiment, the patient is a urothelial carcinoma patient and the term “low” refers to a TMB level that is equal to or less than 30, 25, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 mut/Mb, preferably equal to or less than 20, 16, 15 or 10 mut/Mb. In one embodiment, the patient is to be administered an anti-PD-L1 antibody, preferably atezolizumab. In one embodiment, the patient is a non-small cell lung cancer (NSCLC) patient and the term “low” refers to a TMB level that is equal to or less than 30, 25, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 mut/Mb, preferably equal to or less than 15 or 10 mut/Mb. In one embodiment, the patient is to be administered an anti-PD-1 antibody and/or an anti-PD-L1 antibody, preferably nivolumab, pembrolizumab, atezolizumab and/or durvalumab. In one embodiment, the patient is a gastric cancer patient and the term “low” refers to a TMB level that is equal to or less than 30, 25, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 mut/Mb, preferably equal to or less than 15, 12 or 10 mut/Mb. In one embodiment, the patient is to be administered an anti-PD-1 antibody, preferably toripalimab. In one embodiment, the term “low” as used in relation to the level of neoantigens refers to a number of predicted neoantigens that is equal to or less than 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1. It is preferred that the number of predicted neoantigens is equal to or less than 1. In one embodiment, the term “low” as used in relation to the level of PD-L1 expression on a tumor cell refers to a tumor proportional score (TPS) that is equal to or below 60%, 50%, 40%, 30%, 25%, 20%, 10%, 5% or 1%. Preferably, a TPS that is equal to or less than 1%. More preferably, a TPS that is less than 1%. In one embodiment, the term “low” refers to PD-L1 staining of equal to or less than 60%, 50%, 40%, 30%, 25%, 20%, 10%, 5% or 1% of tumor cells. Preferably PD-L1 staining of equal to or less than 1% of tumor cells. More preferably, PD-L1 staining of less than 1% of tumor cells. In a further embodiment, the term “low” as used in relation to the level of PD-L1 expression on an immune cell refers to equal to or less than 60%, 50%, 40%, 30%, 25%, 20%, 10%, 5% or 1% of immune cells expressing PD-L1. Preferably, equal to or less than 10%, 5% or 1% of immune cells expressing PD-L1. In a preferred embodiment, the immune cell is a 13399613-3 tumor infiltrating immune cell, more preferably a tumor infiltrating lymphocyte. In one embodiment, the term “low” refers to PD-L1 stained tumor-infiltrating immune cells covering equal to or less than 60%, 50%, 40%, 30%, 25%, 20%, 10%, 5% or 1% of the tumor area. Preferably, PD-L1 stained tumor-infiltrating immune cells covering equal to or less than 10%, 5% or 1% of the tumor area. In one embodiment, the term “low” refers to a combined positive score (CPS) that is equal to or less than 60%, 50%, 40%, 30%, 25%, 20%, 15%, 10%, 5% or 1%. Preferably a CPS that is equal to or less than 20% or 10%. In some embodiments, the patient is a NSCLC patient and the term “low” refers to a TPS that is equal to or less than 50%, 20% or 1%; or to PD-L1 staining of equal to or less than 50%, 20% or 1% of tumor cells. Preferably, a TPS of equal to or less than 1%; or to PD-L1 staining of equal to or less than 1% of tumor cells. In one embodiment, the patient is to be administered an anti-PD-1 antibody. In a preferred embodiment, the anti- PD-1 antibody is pembrolizumab or nivolumab. In some embodiments, the patient is a melanoma patient and the term “low” refers to a TPS of equal to or less than 10%, 5% or 1%; or to a tumor PD-L1 expression level of equal to or less than 10%, 5% or 1%. Preferably, a TPS or a tumor PD-L1 expression level of equal to or less than 1%. In one embodiment, the patient is a melanoma patient and the term “low” refers to PD-L1 expression on immune cells that is equal to or less than 10%, 5% or 1% of immune cells. Preferably, PD-L1 expression on equal to or less than 1% of immune cells. In one embodiment, the patient is to be administered an anti- PD-1 antibody and/or anti-PD-L1 antibody. In a preferred embodiment, the anti-PD-1 antibody is nivolumab and the anti-PD-L1 antibody is atezolizumab. In some embodiments, the patient is a head and neck squamous cell carcinomas (HNSCC) patient or an esophageal squamous cell carcinoma (ESCC) patient and the term “low” refers to a combined positive scope (CPS) of equal to or less than 30%, 25%, 20%, 15%, 10% or 5%. Preferably, a CPS of equal to or less than 20% or 10%. In some embodiments, the patient is to be administered an anti-PD-1 antibody. In a preferred embodiment, the anti-PD-1 antibody is pembrolizumab. In some embodiments, the patient is a urothelial carcinoma patient and the term “low” refers to PD-L1 expression on equal to or less than 10%, 5% or 1% of immune cells. 13399613-3 Preferably, PD-L1 expression on equal to or less than 5% or 1% of immune cells. In one embodiment, the term “low” refers to PD-L1 stained tumor-infiltrating immune cells covering equal to or less than 10%, 5% or 1% of the tumor area; preferably PD-L1 stained tumor-infiltrating immune cells covering equal to or less than 5% or 1% of the tumor area. In one embodiment, the patient is to be administered an anti-PD-L1 antibody. In a preferred embodiment, the anti-PD-L1 antibody is atezolizumab. In some embodiments, the patient is a gastric cancer patient and the term “low” refers to the presence of PD-L1 staining in equal to or less than 5% or 1% of tumor cells; or to the presence of PD-L1 staining in equal to or less than 5% or 1% of immune cells. Preferably, equal to or less than 1% of tumor cells or immune cells. In one embodiment, the term “low” refers to a TPS of equal to or less than 5% or 1%, preferably a TPS of equal to or less than 1%. In one embodiment, the patient is to be administered an anti- PD-1 antibody. In a preferred embodiment, the anti-PD-1 antibody is toripalimab. In one embodiment, the term “low” as used in relation to the level of a TIL refers to the level of TIL density. In one embodiment, the TIL is a CD8+ T-cell and the term “low” refers to a density of equal to or below 350, 341, 300, 250, 200, 150, 125, 116, 100, 90, 80, 78, 75 or 70 counts/mm ² . In one embodiment, the TIL is a CD8+ T-cell and the term “low” refers to a density of equal to or less than 2000, 1900, 1800, 1700, 1600, 1500, 1400, 1300, 1200, 1100, 1000, 900, 886, 885, 880, 870, 860, 850, 700, 600, 500 or 400 counts/mm ² . It is preferred that the term “low” refers to a CD8+ T-cell density that is equal to or less than 1000, 900, 886, 885, 880, 870, 860, 850 or 800 counts/mm ² , more preferably equal to or less than 900 or 850 counts/mm ² . In some embodiments, the patient is a melanoma patient and the term “low” refers to a CD8+ T-cell density that is equal to or less than 1900, 1500, 1000, 900, 886, 885, 880, 870, 860, 850 or 800 counts/mm ² , preferable equal to or less than 1000, 900, 886 or 850 counts/mm ² . In some embodiments, the patient is a NSCLC patient and the term “low” refers to a CD8+ T-cell density that is equal to or less than 1000, 900, 886, 885, 880, 870, 860, 850 or 800 counts/mm ² , preferably equal to or less than 900, 886 or 850 counts/mm ² . In some embodiments, the melanoma patient or the NSCLC patient is to be administered an anti-PD-1 antibody. In one embodiment, the anti-PD-1 antibody is pembrolizumab or nivolumab. 13399613-3 In one embodiment, the term “low” as used in relation to the level of a TIL refers to a TIL ratio. In one embodiment, the TIL ratio is a ratio of CD8+/CD4+ T-cells. In some embodiments, the term “low” refers to a CD8+/CD4+ T-cell ratio of equal to or less than 3, 2.9, 2.8, 2.7, 2.6, 2.5, 2.4, 2.3, 2.2, 2.1, 2 or 1.5. The term “cancer patient population” as used herein refers to a group of patients who have been diagnosed with a cancer. In one embodiment, the “cancer patient population” refers to a group of patients who have been diagnosed with a particular type of cancer (e.g. melanoma, mesothelioma, head and neck cancer, ovarian cancer, non-small cell lung cancer) and it is preferred that the members of the group otherwise display similar characteristics. In one embodiment, the “cancer patient population” is a sample of individuals (e.g. at least 10, 20 or 50 randomly selected individuals) who have been diagnosed with a particular type of cancer and who are taken to be representative of the wider patient population. In one embodiment, the “cancer patient population” is a cohort of patients who are undergoing study or treatment. In a further embodiment, the population of cancer patients comprises patients that have been diagnosed with different types of cancer. In one embodiment, the population of cancer patients is a population of patients having any one or more of the cancers described herein in which the telomerase enzyme is expressed. As the telomerase enzyme is expressed in the majority of human cancers, the population of cancer patients is not limited to patients having any one particular type of cancer. The term “the cancer patient is excluded from treatment with a PD-1/PD-L1 immune checkpoint inhibitor monotherapy” as used herein refers to a patient for whom a PD- 1/PD-L1 immune checkpoint inhibitor monotherapy is not deemed appropriate according to an FDA and/or EMA label. In one embodiment, the level of TMB and/or PD-L1 expression is deemed too low according to an FDA and/or EMA label for the patient to receive the PD-1/PD-L1 immune checkpoint inhibitor monotherapy (i.e. as the monotherapy is expected to be ineffective). For example, in certain lung cancers nivolumab and pembrolizumab are indicated for treatment only if a tumor expresses PD- L1 with a TPS of ≥1% (FDA) or ≥50% (EMA). Atezolizumab is approved by the FDA for patients with urothelial carcinoma who have PD-L1 stained tumor-infiltrating immune cells [IC] covering ≥ 5% of the tumor area. The term “the cancer patient is excluded from treatment with a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor monotherapy” as used herein refers to a patient for whom a PD- 13399613-3 1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor monotherapy is not deemed appropriate according to an FDA and/or EMA label. In one embodiment, the level of TMB and/or PD-L1 expression is deemed too low according to an FDA and/or EMA label for the patient to receive the PD-1/PD-L1 immune checkpoint inhibitor and/or the CTLA-4 immune checkpoint inhibitor monotherapy (i.e. as the monotherapy is expected to be ineffective). In this specification, the percentage “identity” between two sequences is determined using EMBOSS Needle Pairwise Sequence Alignment (Rice et al., Trends Genet.2000 Jun;16(6):276-7; Nucleic Acids Res. 2019 Jul 2;47(W1):W636-W641) using default parameters. In particular, EMBOSS Needle can be accessed on the internet using the URL: https://www.ebi.ac.uk/Tools/psa/emboss_needle/. Detailed Description of the Invention In some aspects, the present invention provides a method for identifying a subject to whom a combination therapy is to be administered. The subject is a cancer patient, and the combination therapy comprises administration of: a polypeptide comprising a region of at least 12 amino acids of a tumor-associated antigen or a sequence having at least 80% sequence identity to the region, simultaneously, separately, or sequentially with a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. The method comprises: (a) evaluating a level of one or more of (i) to (iv) in a biological sample obtained from a cancer patient: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) a tumor infiltrating lymphocyte, and/or (iv) neoantigens, wherein the level of one or more of (i) to (iv) is determined to be low; and (b) identifying the cancer patient who provided the biological sample as a subject to whom the combination therapy is to be administered. In a further aspect, the present invention provides a method for identifying or predicting a clinical outcome of a cancer patient to a medicament. The medicament comprises: 13399613-3 (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C). The method comprising the step of (a) evaluating an hTERT level in a biological sample obtained from the cancer patient at a time point subsequent to an administration of the medicament, wherein the evaluated hTERT level is negatively associated with a clinical response of the cancer patient to the medicament or positively associated with a clinical non-response of the cancer patient to the medicament. Polypeptides In some aspects, the polypeptide comprises a region of at least 12 amino acids of a tumor-associated antigen. A tumor-associated antigen is an antigen that is present in cancer cells but is not expressed, or is not as highly expressed, in healthy cells within an individual. Cancer cells may express certain tumor-associated antigens at a higher level than normal cells or the self-antigen may be expressed inappropriately given the tissue in which the cancer cell developed. These tumor-associated antigens thus represent a potential target for cancer therapy. It is preferred that the tumor-associated antigen is a universal tumor antigen, which is an antigen expressed in (nearly) all human tumors. Cancer is a heterogeneous disease and there is high degree of diversity between different types of cancer as well as between individuals with the same type of cancer. By targeting universal tumor antigens, the applicability of the cancer therapy is improved across the patient population (i.e. within and between cancer types). In one embodiment, the universal tumour antigen is expressed in at least 50%, 60% or 70% or all tumour types, more preferably in at least 80%, 85% or 90% of all tumour types. In a further embodiment, the universal tumour antigen is also expressed in a high 13399613-3 proportion of patients within each tumour type. In one embodiment, the universal tumour antigen is generally expressed in at least 40%, 50%, 60%, 70%, 80% or 90% of patients within each tumour type. In one embodiment, the universal tumour antigen has a direct role in oncogenesis. In one embodiment, and in some aspects of the present invention, the polypeptide comprises a region of at least 12 amino acids of hTERT (human telomerase reverse transcriptase). Telomerase is an enzyme that has the function of replicating the 3’ end of the telomere regions of linear DNA strands in eukaryotic cells as these regions cannot be extended by the enzyme DNA polymerase in the normal way. The telomerase enzyme comprises a telomerase reverse transcriptase subunit (“TERT” or “hTERT” for humans) and telomerase RNA. By using the telomerase RNA as a template, the TERT subunit adds a repeating sequence to the 3’ end of chromosomes in eukaryotic cells in order to extend the 3’ end of the DNA strand. The full-length hTERT sequence is set out in GenBank accession no. AF015950.1 and is set forth in SEQ ID NO.6. In alternative embodiments, the tumor-associated antigen is from a protein other than hTERT. In one embodiment, the universal tumor antigen is selected from the group consisting of: survivin, DNA topoisomerase 2-alpha (Top2α), cytochrome P450 1B1 (CYP1B1) and E3 ubiquitin-protein ligase Mdm2. In one embodiment, the universal tumor antigen is survivin (Sørensen et al., Cancer Biol Ther.20087(12):1885-7; Wobser et al., Cancer Immunol Immunother. 200655(10):1294-8). Survivin (also known as Baculoviral IAP repeat-containing protein 5) is encoded by the BIRC5 gene in humans and is an inhibitor of apoptosis. A 142 amino acid isoform of Survivin is set out at UniProtKB reference O15392 (isoform 1). In one embodiment, the universal tumor antigen is DNA topoisomerase 2-alpha (Top2α) (Park et al., Cancer Immunol Immunother.2010 (5):747-57). DNA topoisomerase 2-alpha is encoded by the TOP2A gene in humans and controls the topological states of DNA by transient breakage and subsequent rejoining of DNA strands. Topoisomerase II makes double-strand breaks. A 1,531 amino acid isoform of DNA topoisomerase 2-alpha is set out at UniProtKB reference P11388 (isoform 1). In one embodiment, the universal tumor antigen is cytochrome P4501B1 (CYP1B1) (Gribben et al., Clin Cancer Res.200511(12):4430-6). Cytochrome P4501B1 is encoded by the CYP1B1 gene in humans and is involved in 13399613-3 the metabolism of a diverse range of xenobiotics and endogenous compounds. The 543 amino acid sequence of Cytochrome P450 1B1 is set out at UniProtKB reference Q16678. In one embodiment, the universal tumor antigen is E3 ubiquitin-protein ligase Mdm2 (Gordan and Vonderheide, Cytotherapy.2002;4(4):317-27). E3 ubiquitin-protein ligase Mdm2 is encoded by the MDM2 gene in humans and is a negative regulator of the p53 tumor suppressor. A 491 amino acid isoform of E3 ubiquitin-protein ligase Mdm2 is set out at UniProtKB reference Q00987 (Isoform Mdm2). The sequences of these universal tumor antigens are also reported in WO 2017/207814, the sequences of which are incorporated herein by reference. In some embodiments, the at least one polypeptide is a cocktail (i.e. a mixture) of polypeptides. In one embodiment, the cocktail of polypeptides comprises at least two different polypeptides of the hTERT protein. However, in some embodiments, the cocktail of polypeptides comprises at least two different polypeptides selected from any one of the different tumor-associated antigens. In one embodiment, the cocktail of polypeptides comprises at least two different polypeptides selected from any one of: hTERT, Top2alpha, survivin or CYP1B1. As set out above, in some embodiments the polypeptide comprises a region of at least 12 amino acids of the tumor-associated antigen. It is to be appreciated that different lengths of polypeptide elicit different T cell responses. More specifically, in order to elicit a CD8+ T-cell response, the polypeptide must be presented on MHC class I molecules which will typically only bind polypeptides which are between 8 and 10 amino acid residues in length. On the other hand, in order to elicit a CD4+ T-cell response, it is necessary for the polypeptide to be presented on an MHC class II molecule for which the polypeptides may generally be longer, typically between 12 and 24 amino acid residues in length. Therefore, in one embodiment, the polypeptide comprising a region of at least 12 amino acids of the tumor-associated antigen is capable of eliciting a CD4+ T-cell response (i.e. a helper T cell response) because it is of a longer length (i.e. at least 12 amino acids in length). In one embodiment, a CD4+ T-cell immune response is measured by a T-cell proliferation assay (3H-Thymidine) as previously described in Inderberg-Suso et al. Oncoimmunology. 2012 Aug 1; 1(5): 670–686. In one embodiment, the CD4+ T-cell 13399613-3 immune response is considered positive if the response to the polypeptide is at least 3 times the background (Stimulation Index, SI ≥ 3). In some embodiments, the polypeptide comprising a region of at least 12 amino acids of the tumor-associated antigen is equal to or at least 15 amino acids in length. In some embodiments, the polypeptide is equal to or at least 16, 17, 18, 19, 20, 25 or 30 amino acids in length. In some embodiments, the polypeptide is equal to or less than 1000 amino acids in length, preferably equal to or less than 500, 200, 100, 50, 40 or 30 amino acids in length. More preferably, the polypeptide is equal to or less than 100 amino acids in length. In embodiments where the tumor-associated antigen is telomerase (more specifically, hTERT), it is preferred that the polypeptide comprises a sequence selected from any one of SEQ. ID NOS.1 to 5. It is particularly preferred that the polypeptide comprises the sequence of SEQ. ID NOS. 1, 2 or 3. It is especially preferred that the polypeptide consists of the sequence of SEQ. ID NOS.1, 2 or 3. It is to be understood that such polypeptides are capable of eliciting a CD4+ T-cell response (i.e. a helper T cell response) because each of the polypeptides is at least 12 amino acids in length. SEQ. ID NO: 1 is 30 amino acids in length; SEQ. ID NOS: 2, 3 and 4 are 15 amino acids; and SEQ ID NO: 5 is 16 amino acids in length. In some embodiments, the polypeptide comprises a sequence selected from any one of SEQ ID NOs: 5, 39 and 40. SEQ. ID NO: 5 is 16 amino acids in length. SEQ ID NO: 39 is 30 amino acids in length. SEQ ID NO: 40 is 30 amino acids in length. It is to be appreciated that polypeptides comprising the sequences of SEQ ID NO: 39 or 40 comprise the sequence of EARPALLTSRLRFIPK (SEQ ID NO: 5) which has been reported to induce immune responses in at least 50% of vaccinated individuals (see, for example, Bernhardt et al. Br J Cancer.2006 Dec 4;95(11):1474-82; Inderberg-Suso et al.2012; and Kyte et al. Clin Cancer Res July 12011 (17) (13) 4568-4580). It is to be noted that some of the polypeptides of the present invention (e.g. the polypeptide of SEQ. ID NO. 1) are longer than would normally be accommodated in either an MHC class I or class II molecule. Peptides of this length have been shown to induce more robust immune responses, e.g. by groups working on HPV and cervical cancer vaccination (Welters et al, 2008). Without wishing to be bound by theory, it is 13399613-3 believed that such polypeptides, following their administration to an individual, are endocytosed by cells, subjected to proteolytic degradation in the proteasome and then presented on an MHC class I or class II molecule. Thus such polypeptides may give rise to an MHC class I and/or an MHC class II restricted T-cell response. It is also to be appreciated that longer polypeptides remain extant within an individual for a greater period of time than shorter polypeptides and therefore there is a longer period of time during which they may elicit an immune response. This is particularly significant as regards those polypeptides which have a relatively low MHC binding affinity. In other embodiments, there are provided immunogenic fragments of the aforementioned polypeptides, which comprise at least 12 amino acids of SEQ. ID NOS: 1 to 5. In one embodiment, the immunogenic fragments comprise at least 12, 13 or 14 amino acids of SEQ. ID NOS.1 to 5. In another embodiment, the immunogenic fragments comprise at least 15, 16, 17, 18, 19, 20 or 25 amino acids of SEQ. ID NO.1. Exemplary immunogenic fragments include those set out in SEQ ID NOS.7 to 38. It is to be appreciated that the polypeptides of SEQ. ID NOS.7 to 30 are all immunogenic fragments of the polypeptide of SEQ. ID NO. 1. The polypeptides of SEQ. ID NOS. 31 to 34 are all immunogenic fragments of the polypeptide of SEQ. ID NO.2. The polypeptides of SEQ. ID NOS.35 to 38 are all immunogenic fragments of the polypeptide of SEQ. ID NO.3. In the above described embodiments, a polypeptide of a single sequence is provided. However, in other embodiments, a cocktail (i.e. a mixture) of polypeptides is provided. In one embodiment, the cocktail comprises at least 2 or at least 3 different polypeptides of the tumor-associated antigen. It is particularly preferred that in the cocktail of polypeptides, the polypeptides in the cocktail are capable of being bound by MHC class II molecules of more than one HLA allele. It is also to be understood that in some embodiments the cocktail comprises more than two polypeptides having different sequences (e.g.3, 4 or 5 polypeptides). It is preferred that the cocktail of polypeptides comprises polypeptides of the hTERT protein. In one embodiment, the cocktail of polypeptides comprises at least two different polypeptides comprising sequences from SEQ ID NOS.1 to 5. It is particularly preferred that the polypeptides in the cocktail comprise the sequences of SEQ. ID NOS.1, 2 and 3. It is especially preferred that the polypeptides in the cocktail consist of the sequences of SEQ. ID NOS.1, 2 and 3. In some embodiments the cocktail comprises immunogenic 13399613-3 fragments of the polypeptides, wherein the immunogenic fragments comprise at least 12 amino acids. In one embodiment, each polypeptide in the cocktail is equal to or less than 1000 amino acids in length, preferably equal to or less than 500, 200, 100, 50, 40 or 30 amino acids in length. More preferably, each polypeptide in the cocktail is equal to or less than 100 amino acids in length. In one embodiment, the cocktail of polypeptides comprises one or more of the polypeptides as set out above and a further polypeptide. In one embodiment, the further polypeptide is derived from hTERT. In one embodiment, the further polypeptide is derived from a protein other than hTERT. In one embodiment, the cocktail of polypeptides comprises any one or more sequences derived from hTERT according to SEQ ID NOS: 5, 39 and 40 in combination with any one or more of the sequences according to SEQ ID NOS: 1, 2 and 3. Thus, the cocktail of peptides may comprise any one or more sequences selected from SEQ ID NOs: 1, 2, 3, 5, 39 and 40. In one embodiment, the polypeptides in the cocktail are capable of being bound by MHC class II molecules of more than one HLA allele. It is to be understood that in some embodiments the cocktail comprises more than two or more than three polypeptides having different sequences (e.g.4, 5 or 6 polypeptides). In further embodiments, the polypeptide or one or more of the polypeptides in the cocktail of polypeptides does not have an exact sequence identity to one of the aforementioned polypeptides. Instead, the polypeptide has at least 80% sequence identity to a polypeptide as set out above. It is particularly preferred that the sequence has at least 90%, 95% or 99% sequence identity to that set out above. It is also preferred that any addition or substitution of amino acid sequence results in the conservation of the properties of the original amino acid side chain. That is to say the substitution or modification is “conservative”. Conservative substitution tables providing functionally similar amino acids are well known in the art. Examples of properties of amino acid side chains are hydrophobic amino acids (A, I, L, M, F, P, W, Y, V), hydrophilic amino acids (R, D, N, C, E, Q, G, H, K, S, T), and side chains having the following functional groups or characteristics in 13399613-3 common: an aliphatic side-chain (G, A, V, L, I, P); a hydroxyl group containing side chain (S, T, Y); a sulphur atom containing side-chain (C, M); a carboxylic acid and amide containing side-chain (D, N, E, Q); a base containing side-chain (R, K, H); and an aromatic containing side-chain (H, F, Y, W). In addition, the following eight groups each contain amino acids that are conservative substitutions for one another (see e.g. Creighton, Proteins (1984): 1) Alanine (A), Glycine (G); 2) Aspartic acid (D), Glutamic acid (E); 3) Asparagine (N), Glutamine (Q); 4) Arginine (R), Lysine (K); 5) Isoleucine (I), Leucine (L), Methionine (M), Valine (V); 6) Phenylalanine (F), Tyrosine (Y), Tryptophan (W); 7) Serine (S), Threonine (T); and 8) Cysteine (C), Methionine (M). In some embodiments, the sequence of the polypeptide or the sequence or one or more of the polypeptides in the cocktail of polypeptides is altered in order to change (e.g. increase) the binding affinity of the polypeptide to an MHC molecule of a particular HLA allele, preferably an MHC class II molecule. In other embodiments, a polypeptide as described above has further amino acids, in addition to those set out above, at the N- and/or C-terminal thereof. Such additional amino acids can also be used to alter (e.g. increase) the binding affinity of a polypeptide to an MHC molecule, preferably an MHC class II molecule. It is to be understood that a polypeptide as set our above is not limited to having a sequence corresponding to a fragment of the tumor-associated antigen. That is to say, in some embodiments, the polypeptide comprises additional amino acid sequences at the N-terminal and/or C-terminal, in addition to the region corresponding to the tumor- associated antigen. However, the region corresponding to the tumor-associated antigen (or which is at least 80%, 90%, 95% or 99% identical to it as set out above) is at least 12 amino acids in length. In some further embodiments, the polypeptide or one or more of the polypeptides in the cocktail of polypeptides is linked to a further substance. In one embodiment, the 13399613-3 polypeptide is linked covalently to a further substance. The polypeptide, when linked to the further substance, retains its capability of inducing a CD4+ T-cell response. In one embodiment, the further substance comprises a lipid, a sugar or a sugar chain, an acetyl group, a further polypeptide, a natural or a synthetic polymer and the like. The polypeptide, in certain embodiments, contains a modification such as glycosylation, side chain oxidation or phosphorylation. In some embodiments, a polypeptide as set out above is produced by conventional processes known in the art. Alternatively, the polypeptide is a fragment of a protein produced by cleavage, for example, using cyanogen bromide, and subsequent purification. Enzymatic cleavage may also be used. In further embodiments, the polypeptide is in the form of a recombinant expressed polypeptide. For example, a suitable vector comprising a polynucleotide encoding the polypeptide in an expressible form (e.g. downstream of a regulatory sequence corresponding to a promoter sequence) is prepared and transformed into a suitable host cell. The host cell is then cultured to produce the polypeptide of interest. In other embodiments, the at least one polypeptide is produced in vitro using in vitro translation systems. Nucleic acid molecules In another aspect of the present invention, the methods involve the provision of a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide as set out above, instead of (or in addition to) the polypeptide itself. In embodiments where the tumor-associated antigen is telomerase, it is preferred that the nucleic acid molecule comprises a nucleotide sequence encoding a polypeptide comprising sequences from SEQ. ID NOS.1 to 5. In some embodiments, the nucleic acid molecule comprises a nucleotide sequence encoding a polypeptide comprising sequences from SEQ ID NOS.1 to 5, 39 or 40. It is particularly preferred that the nucleic acid molecule comprises a nucleotide sequence encoding a polypeptide comprising the sequence of SEQ. ID NOS.1, 2 or 3. In some embodiments, the nucleic acid molecule comprises a nucleotide sequence encoding a polypeptide comprising or consisting of the sequence of SEQ ID NO. 39 or 40. It is especially preferred that the nucleic acid molecule comprises a nucleotide sequence encoding a polypeptide consisting of the sequence of SEQ. ID NOS.1, 2 or 3. 13399613-3 In some embodiments, the nucleic acid molecule comprises a nucleotide sequence encoding a polypeptide comprising the sequences of SEQ ID NOS. 1, 2 and 3. In a further embodiment, the nucleic acid molecule comprises a nucleotide sequence encoding a polypeptide comprising one or more sequences selected from SEQ ID NOS. 1, 2, 3, 5, 39 and 40. That is to say, in some embodiments, a single nucleic acid molecule is provided than encodes more than one of the aforementioned polypeptide sequences. In some embodiments, there is provided a cocktail (that is to say a mixture) of nucleic acid molecules such as a cocktail of nucleic acid molecules comprising nucleotide sequences encoding polypeptides from the same self-antigen or from the same tumor- associated antigen or from two or more different self-antigens or from two or more different tumor-associated antigens. In one embodiment, the cocktail comprises at least 2 or at least 3 different nucleic acid molecules comprising nucleotide sequences encoding polypeptides of the self-antigen or of the tumor-associated antigen. It is particularly preferred that in the cocktail of nucleic acid molecules, the encoded polypeptides are capable of being bound by MHC class II molecules of more than one HLA allele. It is also to be understood that in some embodiments the cocktail comprises more than two nucleic acid molecules encoding different polypeptide sequences (e.g.3, 4 or 5 nucleic acid molecules). It is preferred that the cocktail of nucleic acid molecules comprise nucleotide sequences encoding polypeptides of the hTERT protein. It is preferred that the encoded polypeptide sequences in the cocktail comprise sequences from at least 2 different polypeptides comprising sequences from SEQ. ID NOS. 1 to 5. It is particularly preferred that the encoded polypeptides in the cocktail comprise the sequence of SEQ. ID NOS.1, 2 and 3. It is especially preferred that the encoded polypeptides in the cocktail consist of the sequences of SEQ. ID NOS. 1, 2 and 3. In other embodiments, the polypeptide sequences encoded by the cocktail of nucleic acids are as set out above. In alternative variants, the sequence of the encoded polypeptide is not identical to that aforementioned but instead has at least 80%, 90%, 95% or 99% sequence identity thereto. In preferred embodiments, the encoded polypeptide is equal to or less than 1000 amino acids in length preferably equal to or less than 500, 200, 100, 50, 40 or 30 13399613-3 amino acids in length. In especially preferred embodiments, the encoded polypeptide is equal to or less than 100 amino acids in length. In some further embodiments of the present invention, the or each nucleic acid molecule is linked (e.g. covalently) to other substances. It is to be appreciated that, owing to the degeneracy of the genetic code, nucleic acid molecules encoding a particular polypeptide may have a range of polynucleotide sequences. For example, the codons GCA, GCC, GCG and GCT all encode the amino acid alanine. In some embodiments of the present invention, the or each nucleic acid molecule comprises at least one nucleotide different from the naturally occurring sequence encoding the polypeptide. For example, the nucleic acid molecule, which encodes the polypeptide, is different from that comprised within a naturally-occurring hTERT gene. In some embodiments, this arises due to the degeneracy of the genetic code (i.e. the encoded polypeptide is the same). However, in other embodiments, the encoded polypeptide further comprises at least one amino acid at the N and/or C terminus that is different from the amino acid present in the naturally occurring polypeptide. For example, in the embodiments where the polypeptide is from hTERT, the nucleic acid molecule encodes a polypeptide which further comprises at least one amino acid at the N and/or C terminus that is not present in the corresponding position in the amino acid sequence in SEQ ID NO: 6. The nucleic acid molecules may be either DNA or RNA or derivatives thereof. T-cell receptor or T-cell In another aspect of the present invention, the methods involve the provision of a T-cell receptor (or an antigen-binding fragment thereof), or a T-cell displaying the T-cell receptor, which is specific for a polypeptide as set out above, instead of (or in addition to) the polypeptide itself. In some embodiments, the T-cell receptor is an αβ T-cell receptor, or the antigen-binding fragment of the T-cell receptor is an antigen-binding fragment of an αβ T-cell receptor. 13399613-3 In these embodiments, the T-cell receptor, or antigen-binding fragment thereof, is specific for a polypeptide as set out above when presented on an MHC molecule. In some embodiments, the T-cell receptor is a γδ T-cell receptor, or the antigen-binding fragment of the T-cell receptor is an antigen-binding fragment of a γδ T-cell receptor. In these embodiments, the T-cell receptor does not necessarily require presentation of the polypeptide on an MHC molecule in order to recognise the polypeptide. As set out above, the polypeptide comprises a region of at least 12 amino acids of a tumor-associated antigen. Polypeptides of this length may be presented on MHC class II molecules. Therefore, in some embodiments the T-cell receptor, or the T-cell displaying the T-cell receptor is capable of recognising and binding to a polypeptide when presented on an MHC class II molecule. MHC class II molecules typically bind polypeptides that are between 12 and 24 amino acids in length. In embodiments where the T-cell receptor, or the T-cell displaying the T-cell receptor, is described as specific for a polypeptide that is longer than 12 to 24 amino acids in length, it is to be understood that an immunogenic fragment of the polypeptide is presented on the MHC molecule. In embodiments where the tumor-associated antigen is telomerase (hTERT), it is preferred that the T-cell receptor, or the T-cell displaying the T-cell receptor, is specific for a polypeptide consisting of a sequence selected from SEQ ID NOS. 1 to 5, or an immunogenic fragment thereof consisting of at least 12 amino acids. It is particularly preferred that the T-cell receptor, or the T-cell displaying the T-cell receptor, is specific for a polypeptide consisting of the sequence of SEQ ID NO.1, 2 or 3, or an immunogenic fragment thereof consisting of at least 12 amino acids. In some embodiments, the T-cell receptor, or the T-cell displaying the T-cell receptor, is specific for a polypeptide consisting of the sequence of SEQ ID NOs: 5, 39 or 40. In some embodiments, there is provided a cocktail (i.e. a mixture) of T-cell receptors, or a cocktail of T-cells displaying the T-cell receptors. That is to say, the cocktail comprises different T-cell receptors, or T-cells displaying the different T-cell receptors, each of which is specific for a different polypeptide, when presented on an MHC molecule. In one embodiment, the cocktail of different T-cell receptors, or the cocktail of T-cells displaying the different T-cell receptors is specific for different polypeptides from the 13399613-3 same tumor-associated antigen, when each polypeptide is presented on an MHC molecule, or alternatively, is specific for different polypeptides from two or more different tumor-associated antigen, when each polypeptide is presented on an MHC molecule. In one embodiment, the cocktail of different T-cell receptors, or the cocktail of T-cells displaying the different T-cell receptors, is specific for at least 2 or at least 3 different polypeptides of a tumor-associated antigen, when each polypeptide is presented on an MHC molecule. That is to say, in some embodiments, the cocktail is specific for more than 2 or more than 3 polypeptides having different sequences, when each polypeptide is presented on an MHC molecule (e.g.3, 4, or 5 polypeptides). It is particularly preferred that the cocktail of different T-cell receptors, or the cocktail of T-cells displaying the different T-cell receptors, is specific for polypeptides capable of being bound and presented by MHC class I and/or class II molecules of more than one HLA allele. It is preferred that the cocktail of T-cell receptors, or the cocktail of T-cells displaying the T-cell receptors, is specific for different polypeptides of the hTERT protein, when each polypeptide is presented on an MHC molecule. It is preferred that the polypeptides to which the cocktail of T-cell receptors, or the cocktail of T-cells displaying the T-cell receptors, are specific consist of sequences from at least 2 different polypeptides comprising sequences from SEQ. ID NOS. 1 to 5. It is particularly preferred that the polypeptides to which the cocktail of T-cell receptors, or the cocktail of T-cells displaying the T-cell receptors, are specific consist of the sequence of SEQ. ID NOS.1, 2 and 3. It is especially preferred that the polypeptides to which the cocktail of T-cell receptors, or the cocktail of T-cells displaying the T-cell receptors, are specific consist of the sequences of SEQ. ID NOS.1, 2 and 3. In other embodiments, the polypeptide sequences for which the cocktail of T-cell receptors, or the cocktail of T- cells displaying the T-cell receptors have specificity, are as set out above. In some embodiments, a polypeptide to which the cocktail of T-cell receptors, or the cocktail of T-cells displaying the T-cell receptors, is specific is an immunogenic fragment of that polypeptide. It is to be understood that certain aforementioned polypeptides, such as SEQ ID NO.1, are longer than would normally be accommodated on an MHC class II molecule. Therefore, in embodiments in which a T-cell receptor, or a T-cell displaying the T-cell receptor, or a cocktail thereof, is described as specific for a polypeptide comprising or consisting of the sequence of SEQ ID NO.1, it is to be understood that an 13399613-3 immunogenic fragment, comprising at least 12 amino acids of SEQ ID NO. 1, may be presented on the MHC molecule. Analogous considerations apply to other aforementioned polypeptides. In alternative variants, the sequence of the polypeptide to which the or each T-cell receptor, or the or each T-cell displaying the T-cell receptor, is specific is not identical to that aforementioned but instead has at least 80%, 90%, 95% or 99% sequence identity thereto, provided that the polypeptide is still capable of being presented by an MHC molecule where necessary. Immune checkpoint inhibitor In some aspects, the methods of the invention involve the provision of an immune checkpoint inhibitor. In some aspects, the methods of the invention involve the provision of a PD-1 or PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. An immune checkpoint inhibitor is any compound, substance or composition that is capable of down-regulating or blocking an immune checkpoint to allow more extensive immune activity. Herein, in some aspects, the immune checkpoint inhibitor is an inhibitor of the PD-1/PD-L1 immune checkpoint. In some aspects, the immune checkpoint inhibitor is an inhibitor of a different immune checkpoint, such as a CTLA-4 immune checkpoint inhibitor. In one embodiment, the inhibitor of the PD-1/PD-L1 and/or CTLA- 4 immune checkpoint comprises any one or more of the agents as shown in Table 1A. 13399613-3 Table 1A: Agents targeting PD-1/PD-L1 or CTLA-4 approved or in clinical development PD-1, programmed death 1 receptor, PD-L1, programmed cell death ligand 1; IgG, immunoglobulin; mAb, monoclonal antibody; Fc, fragment crystallisable; N/A, not available; DDL1, delta like protein inhibitor. In one embodiment, the inhibitor of the PD-1/PD-L1 immune checkpoint and/or CTLA-4 immune checkpoint comprises an antibody or a fragment thereof. In one embodiment, the antibody or the fragment thereof is capable of binding to a protein involved in the immune checkpoint pathway in order to disrupt or down-regulate the overall activity of the immune checkpoint. In a preferred embodiment, the fragment of the antibody is a functional fragment of the antibody (i.e. a partial fragment of an antibody that is capable 13399613-3 of binding to an antigen). Examples of functional fragments of an antibody include Fab, F(ab')2, Fab', Fv, scFv, a diabody, a nanobody, a linear antibody and a multi-specific antibody. A multi-specific antibody is an antibody formed of two or more different antigen-binding fragments. An example of a fragment of an antibody is an Fc region. In one embodiment, the antibody or the fragment thereof is fucosylated or non-fucosylated, preferably non-fucosylated. In one embodiment, the inhibitor of the PD-1/PD-L1 immune checkpoint comprises an anti-PD-L1 antibody or functional fragment thereof and/or an anti-PD-1 antibody or a functional fragment thereof. An anti-PD-L1 antibody or a functional fragment thereof is capable of binding specifically to PD-L1. An anti-PD-1 antibody or a functional fragment thereof is capable of binding specifically to PD-1. In this way, the antibody or functional fragment thereof inhibits the interaction between the receptor PD-1 and its ligand PD-L1 thereby down-regulating or blocking the overall activity of the PD-1/PD-L1 immune checkpoint. In one embodiment, the inhibitor of the PD-1/PD-L1 immune checkpoint comprising an antibody or a functional fragment thereof is one or more as shown in Table 1A. In a preferred embodiment, the anti-PD-L1 antibody is one or more selected from: durvalumab, atezolizumab and/or avelumab, most preferably durvalumab. In a further preferred embodiment, the anti-PD-1 antibody is one or more selected from: pembrolizumab, nivolumab and/or cemiplimab, most preferably pembrolizumab. In one embodiment, the inhibitor of the CTLA-4 immune checkpoint comprises an anti- CTLA-4 antibody or functional fragment thereof. An anti-CTLA-4 antibody or a functional fragment thereof is capable of binding specifically to CTLA-4. In this way, the antibody or functional fragment thereof inhibits the interaction between the receptor CTLA-4 and a B7 family ligand (e.g. CD80 and/or CD86) thereby down-regulating or blocking the overall activity of the CTLA-4 immune checkpoint. In a preferred embodiment, the anti- CTLA-4 antibody is ipilimumab and/or tremelimumab. In one embodiment, the inhibitor of the PD-1/PD-L1 immune checkpoint and/or CTLA-4 immune checkpoint comprises a probody. The probody comprises an antibody or fragment thereof specific for PD-1, PD-L1 and/or CTLA-4 as described above and a masking peptide that is linked to the antibody or fragment thereof by a cleavable linker 13399613-3 peptide. When a probody reaches the tumor microenvironment, tumor-associated proteases cleave the linker, which releases the masking peptide, enabling the antibody or fragment thereof to bind the target antigen. In one embodiment, the inhibitor of the PD-1/PD-L1 immune checkpoint or CTLA-4 immune checkpoint comprises a peptide-based inhibitor. In one embodiment, the peptide-based inhibitor comprises a linear peptide, a peptidomimetic, a branched- peptide, a cyclopeptide and/or a macrocyclic-peptide. In an alternative embodiment, the inhibitor of the PD-1/PD-L1 immune checkpoint or CTLA-4 immune checkpoint comprises a small molecule inhibitor. The peptide-based inhibitor or the small molecule inhibitor targets a protein involved in one or more of the aforementioned immune checkpoint pathways in order to disrupt or down-regulate the overall activity of the immune checkpoint. In a preferred embodiment, the peptide-based inhibitor or the small molecule inhibitor is an inhibitor of PD-L1, PD-1 or CTLA-4. That is to say, the peptide-based or small molecule inhibitor targets PD-L1, PD-1 or CTLA-4 specifically in order to disrupt their normal function and down-regulate or block the overall activity of the PD-1/PD-L1 immune checkpoint or CTLA-4 immune checkpoint. Thus in one embodiment, the peptide-based inhibitor or the small molecule inhibitor is a PD-L1 antagonist, a PD-1 antagonist and/or a CTLA-4 antagonist. In one embodiment, the peptide-based inhibitor is an inhibitor of PD-1 and is AUNP-12. In some embodiments, the antibody or the fragment thereof, preferably the functional fragment thereof, the peptide-based inhibitor or the small molecule inhibitor as described above is linked (e.g. covalently) or fused to a further substance. The antibody or the fragment thereof, preferably the functional fragment thereof, the peptide-based inhibitor or the small molecule inhibitor that is linked or fused to the further substance is capable of inhibiting the PD-1/PD-L1 immune checkpoint and/or the CTLA-4 immune checkpoint. In one embodiment, the further substance comprises a lipid, a sugar or a sugar chain, an acetyl group, a polypeptide, a natural or a synthetic polymer and the like. Thus in one embodiment, the immune checkpoint inhibitor comprises a fusion protein. In some embodiments, the immune checkpoint inhibitor comprises a multi-specific or a bi-specific activity. In one embodiment, the bispecific activity comprises inhibiting the PD-1/PD-L1 immune checkpoint and inhibiting the CTLA-4 immune checkpoint. In one embodiment, 13399613-3 a bispecific or multispecific antibody or fragment thereof is provided. In a preferred embodiment, the bispecific or multispecific antibody or fragment thereof inhibits the PD- 1/PD-L1 immune checkpoint and inhibits the CTLA-4 immune checkpoint. In one embodiment, the bispecific or multispecific antibody or fragment thereof is specific for PD-L1, PD-1 and/or CTLA-4, preferably specific for PD-1 and CTLA-4. In some embodiments, multi-specific or a bi-specific activity comprises the activity of inhibiting the PD-1/PD-L1 immune checkpoint and/or inhibiting the CTLA-4 immune checkpoint as well as a further activity. In some embodiments, the immune checkpoint inhibitor comprises an antibody or a functional fragment thereof, a peptide-based inhibitor or a small molecule inhibitor which is specific for PD-L1, PD-1 and/or CTLA-4 as well as a further substance (e.g. as described above) which is specific for a further target. In a further embodiment, a plurality of PD-1 or PD-L1 immune checkpoint inhibitors are provided. That is to say, two, three, four, five or more different immune checkpoint inhibitors are provided. In one embodiment, each of the different immune checkpoint inhibitors targets the same immune checkpoint. In a further embodiment, a plurality of immune checkpoint inhibitors is provided. That is to say, two, three, four, five or more different immune checkpoint inhibitors are provided. In one embodiment, each of the different immune checkpoint inhibitors targets the same immune checkpoint. In a preferred embodiment, each of the different immune checkpoint inhibitors targets a different immune checkpoint. In a preferred embodiment, a first and a second immune checkpoint inhibitor are provided. It is preferred that the first immune checkpoint inhibitor is an inhibitor of the PD-1/PD-L1 immune checkpoint and the second immune checkpoint inhibitor is an inhibitor of the CTLA-4 immune checkpoint. In a preferred embodiment, the PD-1/PD-L1 immune checkpoint inhibitor comprises an anti-PD-1 antibody or a functional fragment or an anti-PD-L1 antibody or a functional fragment thereof and the CTLA-4 immune checkpoint inhibitor comprises an anti-CTLA-4 antibody or a functional fragment thereof. In one embodiment, the first immune checkpoint inhibitor is an anti-PD-1 antibody and is nivolumab or pembrolizumab and the second immune checkpoint inhibitor is an anti-CTLA-4 antibody and is ipilimumab. Preferably, the first and the second immune checkpoint inhibitors are nivolumab and ipilimumab. In an alternative embodiment, the first immune checkpoint inhibitor is an anti-PD-L1 antibody and is durvalumab and the second immune checkpoint inhibitor is an anti-CTLA-4 antibody and is ipilimumab. 13399613-3 In a further embodiment, the immune checkpoint inhibitor targets another member of the CD28CTLA-4 Ig superfamily such as BTLA, LAG3, ICOS, PDL1 or KIR (Page et al., Annual Review of Medicine 65:27 (2014)). In further additional embodiments, the immune checkpoint inhibitor is targeted at a member of the TNFR superfamily such as CD40, OX40, CD137, GITR, CD27 or TIM-3. In a further embodiment, the immune checkpoint inhibitor targets Indoleamine 2,3-dioxygenase (IDO). Examples of such suitable therapeutic agents are shown in Table 1B below. Table 1B: Other immunotherapeutic agents in development Heme, Haematologic tumors; ATL, acute T-cell leukemia; CTCL, cutaneous T-cell lymphoma; AML, acute myeloid leukemia PD-1 and inhibitors of the PD-1 pathway Programmed Death- 1 (PD-1) signalling functions in part to regulate T cell activation in peripheral tissues. The PD-1 receptor refers to an immunoinhibitory receptor belonging to the CD28 family. PD-1 is expressed on a number of cell types including T regs, activated B cells, and natural killer (NK) cells, and is expressed predominantly on previously activated T cells in vivo, and binds to two ligands, PD-L1 and PD-L2. PD-1 's endogenous ligands, PD-L1 and PD-L2, are expressed in activated immune cells as well 13399613-3 as nonhaematopoietic cells, including tumor cells. PD-1 as used herein is meant to include human PD-1 (hPD-1), variants, isoforms, and species homologs of hPD-1, and analogs having at least one common epitope with hPD-1. The complete hPD-1 sequence can be found under GENBANK Accession No. U64863. Programmed Death Ligand-1 (PD-L1) is one of two cell surface glycoprotein ligands for PD-1 (the other being PD-L2) that results in downregulation of T cell activation and cytokine secretion upon binding to PD-1. PD-L1 as used herein includes human PD-L1 (hPD-L1), variants, isoforms, and species homologs of hPD-L1, and analogs having at least one common epitope with hPD-L1. The complete hPD-L1 sequence can be found under GENBANK Accession No. Q9NZQ7. Tumors have been demonstrated to escape immune surveillance by expressing PD-L1/L2, thereby suppressing tumor-infiltrating lymphocytes via PD-1/PD- L1,2 interactions (Dong et al. Nat. Med.8:793-800.2002). Inhibition of these interactions with therapeutic antibodies has been shown to enhance T cell response and stimulate antitumor activity (Freeman et al. J. Exp. Med.192: 1027-34.2000). As discussed above, in some embodiments, the anti-PD-1 antibody is nivolumab (CAS Registry Number: 946414-94-4). Alternative names for nivolumab include MDX-1106, MDX-1106-04, ONO-4538, BMS-936558. Nivolumab is a fully human lgG4 blocking monoclonal antibody against PD-1 (Topaliam et al., N. Engl. J. Med.366:2443-54.2012). Nivolumab specifically blocks PD-1, which can overcome immune resistance. The ligands for PD-1 have been identified as PD-L1 (B7-H1), which is expressed on all haemopoietic cells and many nonhaemopoietic tissues, and PD- L2 (B7-DC), whose expression is restricted primarily to dendritic cells and macrophages (Dong, H. et al. 1999. Nat. Med.5: 1365; Freeman, G. J.et al.2000. J. Exp. Med.192: 1027; Latehman, Y. et al.2001. Nat. Immunol 2:261; Tseng, S. Y. et al.2001. J. Exp. Med.193:839). PD- L1 is overexpressed in many cancers and is often associated with poor prognosis (Okazaki T et al, Intern. Immun.200719(7):813) (Thompson RH et al, Cancer Res 2006, 66(7):3381), the majority of tumor infiltrating T lymphocytes predominantly express PD- 1, in contrast to T lymphocytes in normal tissues and peripheral blood T lymphocytes, indicating that up-regulation of PD-1 on tumor-reactive T cells can contribute to impaired antitumor immune responses (Blood 2009114(8): 1537). Specifically, since tumor cells express PD-L1, an immunosuppressive PD-1 ligand, inhibition of the interaction between PD-1 and PD-L1 can enhance T-cell responses in vitro and mediate preclinical antitumor activity. 13399613-3 A number of clinical trials (Phase I, II and III) involving nivolumab have been conducted or are on-going. For example, in a phase I dose escalation trial, nivolumab was safe, and objective responses were 16-31% across tumor types, with most responses being durable for >1 year (Topaliam et al., Presented at Annu. Meet. Am. Soc. Clin. Oncol., Chicago, May 31 -June 4. 2013). In another study, the safety and clinical activity of nivolumab (anti-PD-1, BMS-936558, Q Q-4538) in combination with ipilimumab in patients with advanced melanoma was investigated (Woichok, J Clin Oncol 31, 2013 (suppl; abstr 90122013 ASCO Annual Meeting). As of 2020, nivolumab (under the brand name Opdivo®) has been approved by the FDA for use in a wide range of cancers including: melanoma; lung cancer (both small cell and non-small cell); renal cell carcinoma; Hodgkin’s lymphoma; head and neck cancer; urothelial carcinoma; colorectal cancer; hepatocellular carcinoma; esophageal carcinoma; and malignant pleural mesothelioma. Clinical trials have also led to a number of other PD-1 targeting agents being approved for use in various cancers including pembrolizumab (Keytruda®). As of 2020, pembrolizumab (under the brand name Keytruda®) has been approved for use in: melanoma; lung cancer (both small cell and non-small cell); head and neck cancer; refractory Hodgkin’s lymphoma; primary mediastinal large B-cell lymphoma; skin cancer (melanoma and Merkel cell carcinoma); endometrial carcinoma; renal cell carcinoma; hepatocellular carincoma; microsatellite instability-high or mismatch repair deficient colorectal cancer; and a number of other cancers in cases where tumors express PD- L1, including urothelial carcinoma; gastric cancer; esophageal carcinoma, and cervical cancer. A number of anti-PD-L1 inhibitory agents have undergone clinical investigations, including several anti-PD-L1 inhibitory antibodies, including atezolizumab (also known as MPDL3280A, or under the brand name of Tecentriq®) (Genentech, South San Francisco, CA), BMS-936559 (also known as MDX-1105) (Bristol Meyers Squibb, New York, NY), durvalumab (also known as MEDI4736 or under the brand name IMFINZI®) and avelumab (also known as MSB0010718C or under the brand name Bavencio®). Like nivolumab and pembrolizumab, these antibodies are thought to function principally by blocking PD-1/PD-L1 signalling. Unlike PD-1 antibodies, PD-L1 antibodies spare potential interactions between PD-L2 and PD-1, but additionally block interactions 13399613-3 between PD-L1 and CD80 (Park et al., 2010. Blood 316:1291-98). Atezolizumab was evaluated in multiple tumor types, with safety and preliminary efficacy identified in melanoma; renal cell carcinoma; non-small cell lung carcinoma (NSCLC); and colorectal, gastric, and head/neck squamous cell carcinoma (Herbst et al. presented at Annu. Meet Am. Soc. Clin. Oncol., Chicago, May 31 -June 4. 2013). Atezolizumab has now been approved for use in bladder cancer, breast cancer, lung cancer (both small and non- small cell) and urothelial carcinoma. Durvalumab has been evaluated clinically (e.g. NCT01693562) and has now been approved for use in lung cancer (both small and non- small cell) and urothelial carcinoma. Avelumab has also been approved for use in Merkel cell carcinoma, renal cell carcinoma and urothelial carcinoma. CTLA-4 and inhibitors of the CTLA-4 immune checkpoint: Cytotoxic T-lymphocyte-associated antigen (CTLA-4), also known as CD 152, is a co- inhibitory molecule that functions to regulate T-cell activation. CTLA-4 was initially identified as a negative regulator on the surface of T-cells that was upregulated shortly after initiation of a de novo immune response or stimulation of an existing response in order to dampen the subsequent immune T-cell response and prevent auto-immunity or uncontrolled inflammation. Thus, the magnitude of the developing immune response has been closely tied to CTLA-4 action. In certain embodiments, the anti-CTLA-4 antibody is ipilimumab or tremelimumab. Checkpoint inhibitors function by modulating the immune system's endogenous mechanisms of T cell regulation. Ipilimumab (YERVOY, Bristol-Meyers Squibb, New York, NY) is a monoclonal antibody and is the first such checkpoint inhibitor to be approved by the US Food and Drug Administration (FDA). It has become standard treatment for metastatic melanoma (Hodi et al., N. Engl. J. Med. 363:711-23. 2010; Robert et al., N. Engl. J. Med. 364:2517-26. 2011). Ipilimumab binds and blocks inhibitory signaling mediated by the T-cell surface co-inhibitory molecule cytotoxic T lymphocyte antigen 4 (CTLA-4). Because the mechanism of action is not specific to one tumor type, and because a wealth of preclinical data supports the role of tumor immune surveillance across multiple malignancies (Andre et al, Clin. Cancer Res. 19:28-33. 2013; May et al. Clin. Cancer Res.17:5233-38.2011), ipilimumab is being investigated as a treatment for patients with prostate, lung, renal, and breast cancer, among other 13399613-3 tumor types. Ipilimumab works by activating the immune system by targeting CTLA-4. Another CTLA-4-blocking antibody, tremelimumab, continues to be investigated in clinical trials and has also demonstrated durable responses in patients with melanoma (Kirkwood et al., Clin. Cancer Res.16: 1042-48.2010; Rihas et al. J. Clin. Oncol.31:616- 22, 2013). Combination Therapy In the combination therapy treatment which is the subject of an aspect of this invention, the following are administered to an individual: the polypeptide, nucleic acid molecule, T-cell or T-cell receptor (or antigen- binding fragment thereof) as described above, or a combination thereof (hereinafter “the first component of the treatment”); and one or more PD-1/PD-L1 immune checkpoint inhibitors and/or CTLA-4 immune checkpoint inhibitors as described above (hereinafter “the second components of the treatment”). In a further aspect of the present invention, the following are administered to an individual: (I) a medicament comprising one of (A) to (D) as follows or a combination thereof (hereinafter “the first component of the treatment”): (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C); and (II) one or more immune checkpoint inhibitors as described above (hereinafter “the second components of the treatment”). 13399613-3 In this further aspect of the present invention, the polypeptide, nucleic acid molecule, T- cell or T-cell receptor (or antigen-binding fragment thereof) may also be as described in the sections “Polypeptides”, “Nucleic acid molecules” or “T-cell receptor or T-cell” respectively above, provided that it comprises a feature as set out in (A) to (D) above. Together, the first and second components of the treatment are collectively referred to as “the components of the treatment”. The individual is a cancer patient in need of treatment. In principle, any mode of administration of the components of the treatment may be used. Following administration, the polypeptide is endocytosed by antigen presenting cells, may be subject to antigen processing and is then presented in a complex with an MHC class II molecule on the cell surface. Through interaction with T-cell receptors on the surface of T-cells, a CD4+ T-cell response is elicited. It is to be appreciated that as a result of antigen processing, the polypeptide may also be presented in a complex with an MHC class I molecule on the cell surface and thereby elicit a CD8+ T cell response. In embodiments which provide a nucleic acid molecule, the nucleic acid molecule is also endocytosed and is then transcribed (if the nucleic acid molecule is DNA) and translated, and the encoded polypeptide is synthesised through endogenous cellular pathways. Subsequently, the encoded polypeptide is processed and presented on an MHC molecule in order to elicit the T-cell response, as previously described. Thus the polypeptide or the nucleic acid molecule or the kit, the composition or the pharmaceutical composition (as described below) may be used as a vaccine in order to elicit CD4+ T- cell (as well as CD8+ T cell) immunity. The components of the treatment as explained above may each be administered simultaneously, separately or sequentially to a patient in need of treatment. That is to say, the first component of the treatment may be administered simultaneously, separately or sequentially to the second component of the treatment. Thus, the first and/or second component of the treatment may be administered at a different time or in a substantially simultaneous manner. The term simultaneously as used herein refers to administration of one or more agents at the same time. For example, in certain embodiments, the polypeptide and the immune checkpoint inhibitor are administered simultaneously. Simultaneously includes administration contemporaneously, that is 13399613-3 during the same period of time. In certain embodiments, the components are administered simultaneously in the same hour, or simultaneously in the same day. In some embodiments, the term “sequentially” refers to the components of the treatment being administered within 1, 3, 5, 7, 10, 28, 30 or 60 days of each other. In some embodiments, the term “sequentially” refers to the components of the treatment being administered within 2, 4 or 6 months of each other. The second component of the treatment (i.e. the immune checkpoint inhibitor) is capable of down-regulating or blocking an immune checkpoint to allow more extensive immune activity. In some embodiments, it is preferred to administer the second component of the treatment subsequent to the first component of the treatment. In this way, the second component of the treatment takes effect as a T-cell immune response is initiated in response to vaccination with the first component of the treatment. In one embodiment, it is preferred to administer the second component of the treatment during the initiation phase of vaccination. In some embodiments, this is within 30, 21, 14, 10, 7, 5, 3 or 1 days from the initial vaccination with the first component of the treatment. Further details on treatment regimes in accordance with embodiments of the present invention are described below. Without wishing to be bound by theory, it is thought that the administration of the second component of the treatment subsequent to the first component of the treatment and within the aforementioned timeframe promotes a rapid and effective expansion of T-cells specific to the first component of the treatment from a population of naïve T-cells in the primary lymphoid organs (i.e. a rapid and effective primary immune response). This is thought to be because the second component of the treatment takes effect as the T-cell response is developing and prevents dampening of the response by the immune checkpoint. Therefore, a strong de novo immune response is promoted, which translates into higher clinical benefit as described below. In addition, the administration of the second component of the treatment subsequent to the first component of the treatment and within the aforementioned timeframe is thought to contribute to the generation of an accelerated CD4+ T cell immune response. Sequential or substantially simultaneous administration of each component of the treatment can be effected by any appropriate route including, but not limited to, intradermal routes, oral routes, intravenous routes, sub-cutaneous routes, intramuscular 13399613-3 routes, direct absorption through mucous membrane tissues (e.g., nasal, mouth, vaginal, and rectal), and ocular routes (e.g., intravitreal, intraocular, etc.). The components of the treatment can be administered by the same route or by different routes, preferably the components of the treatment are administered by different routes. In one embodiment, one or more components of the treatment are administered by injection. In one embodiment, one or more components of the treatment are injected directly into a tumor in a patient. If the cancer to be treated is in the nose or mouth of a patient then in some embodiments, one or more components of the treatment are administered by spray and inhalation. In a preferred embodiment, the first component of the treatment is administered intradermally, preferably by an intradermal injection; and the second component of the treatment is administered intravenously. A suitable dosage of the first component of the treatment (e.g. the polypeptide or the cocktail of polypeptides) is between 100 and 700 µg, preferably between 250 to 400 µg, although dosages outside this range may occasionally be required (e.g. from 1-1500 µg). A dosage of 300 µg is particularly preferred. In one embodiment, the first component of the treatment is administered simultaneously, separately or sequentially with an adjuvant, preferably GM-CSF, most preferably sargramostim. A suitable dosage of GM- CSF, preferably sargramostim, is between 20 and 100 µg. In one embodiment, the dosage is 37.5 µg, in a preferred embodiment, the dosage is 75 μg. In one embodiment, the first component is a T-cell and a dose of 10 ⁶ to 10 ¹¹ cells is provided. A suitable dosage of the second component of the treatment (i.e. the immune checkpoint inhibitor) is between 100 and 2000 mg. In a preferred embodiment, the dosage is 1500 mg. In an alternative embodiment, the dosage is between 200 and 300 mg, preferably 200, 220, 240, 260, 280 or 300 mg, most preferably 200 mg. In one embodiment, a dosage in a range from 1 microgram/kg to 10 mg/kg is given, preferably in a range from 1mg/kg to 5 mg/kg, more preferably 3 mg/kg. In some embodiments, a treatment regimen is pursued as follows. In one embodiment, the first component of the treatment (e.g. the polypeptide) is administered to the patient between 4 and 10 times. In a preferred embodiment, the first component of the treatment is administered 8 times. In a further preferred embodiment, the first component of the treatment is administered 8 times within 5 months. It is particularly preferred that 1 to 4 administrations of the first component of the treatment are provided within an initial 13399613-3 period. In one embodiment, the initial period is 10 days or fewer. In one embodiment, the administrations within the initial period are each separated by at least 2 days. In some embodiments, the administrations subsequent to those in the initial period (e.g. administration 5 and onward) are separated by between 2 and 4 weeks, preferably each subsequent administration is given every 4 weeks (28 days). In one embodiment, the second component of the treatment (i.e. the immune checkpoint inhibitor) is administered over at least 12 months, preferably over at least 24 months or until disease progression or unacceptable toxicity. In one embodiment, each administration of the second component is separated by between 2 and 6 weeks, preferably each administration is given every 4 weeks (28 days). In some embodiments, one or more administrations of the first and second components of the treatment are given on the same day (e.g. administration 1, 5, 6, 7 and 8 of the first component of the treatment). In such embodiments, the first component of the treatment is given prior to the administration of the second component of the treatment. In a preferred embodiment, a treatment regimen as shown in Figure 6 is followed. However, it is to be understood that in alternative embodiments, “UV1 vaccination” refers to administration of the first component of the treatment and “pembrolizumab” refers to administration of the second component of the treatment as described above. In one embodiment, the components of the treatment are administered to a patient subsequent to a chemotherapy or radiotherapy treatment. In one embodiment, the components of the treatment are administered to a patient subsequent to a platinum- based chemotherapy treatment. In one embodiment, the patient is in complete or partial response to the chemotherapy treatment. In some embodiments, the components of the treatment are provided in a kit. In some embodiments, additional components are provided in the kit. In one embodiment, the kit further comprises a pharmaceutically acceptable adjuvant, diluent or excipient. Exemplary adjuvants include Poly I:C (Hiltonol), CpG, liposomes, microspheres, virus- like particles (ISCOMS), Freund’s incomplete adjuvant, aluminium phosphate, aluminium hydroxide, alum, bacterial toxins (for example, cholera toxin and salmonella toxin) or 13399613-3 nanoparticle formulations of any sort. Further exemplary adjuvants include Imiquimod or glucopyranosyl Lipid A. A particularly preferred adjuvant is GM-CSF (granulocyte macrophage colony stimulating factor). Exemplary diluents and excipients include sterilised water, physiological saline, culture fluid and phosphate buffer. Exemplary adjuvants for use in vaccines targeting the T cell arm of the immune system, as in the present invention, are detailed in Petrovsky & Aguilar Immunol Cell Biol.200482(5):488- 96, which is incorporated herein by reference. The polypeptide or nucleic acid molecule as described above is, in certain embodiments, coupled to a carrier moiety or an immunogenic carrier moiety or incorporated into a virus or bacterium. Exemplary immunogenic carriers include keyhole limpet haemocyanin, bovine serum albumin, ovalbumin, fowl immunoglobulin and peptide fragments of immunogenic toxins. In one embodiment, the nucleic acid molecule is coupled to or integrated in a carrier selected from the group consisting of dendritic cells, yeast, bacteria, viral vectors, oncolytic viruses, virus like particles, liposomes, micellar nanoparticles or gold nanoparticles. In one embodiment, the nucleic acid molecule is comprised within a lipid nanoparticle or is provided in a lipid or nanoparticle formulation. The kit, in some embodiments, also comprises a further therapeutic ingredient. Exemplary further therapeutic ingredients include interleukin-2 (IL2), interleukin-12 (IL12), a further polypeptide of a self-antigen or tumour associated antigen (that is to say, a polypeptide of a self-antigen or tumour associated antigen aside from those discussed above) chemotherapeutics, pain killers, anti-inflammatory agents and other anti-cancer agents. Further details of additional components of the kit may be found in Remington’s Pharmaceutical Sciences and US Pharmacopoeia, 1984, Mack Publishing Company, Easton, PA, USA. In certain embodiments, the aforementioned components of the kit are provided in the form of a composition or a pharmaceutical composition for the treatment of cancer. It is to be appreciated that, in one embodiment, the suitability of the present invention is not limited to any particular type of cancer. This is because (and as will be described in further detail below) the telomerase enzyme is expressed in the vast majority of human 13399613-3 cancers. Thus in one embodiment, the components of the treatment are administered to a patient suffering from any type of cancer in which the telomerase gene is activated (which, as we discuss below, is the majority of cancer types). Such cancers include but are not limited to breast cancer, prostate cancer, pancreatic cancer, colorectal cancer, lung cancer, bladder cancer, malignant melanoma, leukaemias, lymphomas, ovarian cancer, cervical cancer and biliary tract carcinomas. In one embodiment, the cancer is one or more of malignant melanoma, mesothelioma, head and neck cancer, ovarian cancer and/or non-small cell lung cancer. Preferably, first line malignant melanoma, second line mesothelioma, first line head and neck cancer, second line ovarian cancer and/or first line non-small cell lung cancer. That telomerase is expressed in the vast majority of cancers has been demonstrated in studies such as Kim et al. Science.1994 Dec 23;266(5193):2011-5 and Bearss et al. Oncogene. 2000 Dec 27;19(56):6632-41 (both incorporated herein in their entirety by reference). Kim et al.1994 has demonstrated that, in cultured cells representing 18 different human tissues, 98 of 100 immortal and none of 22 mortal populations were positive for telomerase. The human tissues from which the immoral cell lines having telomerase activity were derived included: skin, connective, adipose, breast, lung, stomach, pancreas, ovary, cervix, kidney, bladder, colon, prostate, CNS, retina and blood. The treatment would therefore be suitable for use against cancers derived from these tissues. Similarly, 90 of 101 biopsies representing 12 human tumor types and none of 50 normal somatic tissues were positive for telomerase. The human tumor types which exhibited telomerase activity included: hepatocellular carcinoma, colon cancer, squamous cell carcinoma (head and neck), Wilms tumor, breast cancer (ductal and lobular, node positive), breast cancer (axillary node negative), prostate cancer, prostatic intraepithelial neoplasia type 3, benign prostatic hyperplasia, neuroblastoma, brain tumors, lung small- cell carcinoma, rhabdomyosarcoma, leiomyosarcoma, hematological malignancies (including acute lymphocytic leukaemia, chronic lymphocytic leukaemia, lymphoma (adult)), Bearss et al.2000 has furthermore demonstrated the presence of telomerase activity in tumor cells taken directly from patients across a wide range of cancer types. These tumor types included: hematologic malignancies (including acute myeloid leukaemia, acute lymphoid leukaemia, chronic myeloid leukaemia, chronic lymphoid leukaemia (early), chronic lymphoid leukaemia (late), myeloma, low-grade lymphoma, high-grade 13399613-3 lymphoma); breast; prostate; lung (including non-small cell and small cell); colon; ovarian; head and neck; kidney; melanoma; neuroblastoma; glioblastoma; hepatocellular carcinoma; gastric; and bladder. Methods A method is provided for identifying a subject to whom the combination therapy described above is to be administered. The method comprises the steps of obtaining a biological sample from a patient and then evaluating a level or one or more biomarkers in the biological sample. The biomarker is one or more selected from (i) tumor mutational burden; (ii) PD-L1 expression; (iii) tumor infiltrating lymphocyte level; and/or (iv) neoantigens, The biological sample is a liquid or solid tumor biopsy sample and may be, for example, tissue or blood (including blood derivatives such as plasma or serum) from the patient. It is preferred that the biological sample is obtained from the patient prior to the first administration of the first and the second components of the combination therapy treatment. In some embodiments, the biological sample is obtained from the patient prior to a first administration of the first or the second component of the combination therapy treatment. In accordance with further aspect of the present invention, a method is provided for identifying or predicting a clinical outcome of a patient to a medicament. The medicament comprises: (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor (or an antigen-binding fragment thereof) specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C). The polypeptide, nucleic acid molecule, T-cell or T-cell receptor (or antigen-binding fragment thereof) may also be as described in the sections “Polypeptides”, “Nucleic acid 13399613-3 molecules” or “T-cell receptor or T-cell” respectively or “Combination Therapy” above, provided that it comprises a feature as set out in (A) to (D) above. The method comprises the step evaluating an hTERT level in a biological sample obtained from a cancer patient at a time point subsequent to an administration of a medicament. The present inventors have surprisingly found that the hTERT level in the biological sample can be used to identify or predict the clinical outcome of a cancer patient to the medicament. Thus embodiments of the present invention provide a means for monitoring and/or predicting a clinical outcome of a patient in response to the administration of the polypeptide, nucleic acid molecule, T-cell or T-cell receptor (or antigen-binding fragment thereof). The present inventors have made the surprising realisation that, targeting hTERT with the polypeptide, nucleic acid molecule, T-cell or T-cell receptor (or antigen-binding fragment thereof) as set out in (A) to (D) above, results in different hTERT levels developing between clinical responders and clinical non-responders and that such differences can be used to identify and predict a clinical outcome of the patient. In accordance with a first embodiment of the method of the invention, a biopsy tissue sample is obtained from a cancer patient subsequent to a first administration of the medicament as set out in (A) to (D) above. In the first embodiment, the medicament comprises a cocktail of polypeptides comprising the sequences of SEQ ID NOS.1, 2 and 3. It is preferred that the biopsy tissue sample is taken between 10 days and 14 weeks subsequent to the first administration of the medicament. In some embodiments, the biopsy tissue sample is taken at 10 days or 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14 weeks subsequent to the first administration of the medicament. In a further embodiment, the biopsy tissue sample is taken at least 3, 6, 9, 12, 15, 18, 21 or 24 months subsequent to the first administration of the medicament. In one embodiment, the biopsy tissue sample is taken at 3, 6, 9, 12, 15, 18, 21 or 24 months after an initial treatment period. In one embodiment, the initial treatment period comprises the first 14 weeks of treatment. In the first embodiment, an mRNA level of hTERT is evaluated in the biopsy tissue sample by RNA sequencing. In a preferred embodiment, an mRNA level of hTERT is measured in terms of transcripts per million (TPM). Transcripts Per Million (TPM) is a 13399613-3 normalization method for RNA sequencing. It is to be understood as meaning that, for every 1,000,000 RNA molecules in the RNA sequencing sample, x came from hTERT. In the first embodiment, the evaluated mRNA level of hTERT is compared to a reference value obtained from a population of control subjects. In the first embodiment, the reference value is a threshold value. In the first embodiment, the threshold value is 0.3 TPM, preferably 0.33 TPM. When the evaluated mRNA level of hTERT is lower than the threshold value, then the cancer patient is identified or predicted to have a clinical response (i.e. to be a clinical responder). When the evaluated mRNA level of hTERT is higher than the threshold value, then the cancer patient is identified or predicted to have a clinical non-response (i.e. to be a clinical non-responder). In an alternative embodiment, a different threshold value is used. In some embodiments, the threshold value is 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.4, 0.5, 0.6, 0.7, 0.77, 0.8 or 0.9 TPM. In the first embodiment, the threshold value is calculated from data on the mRNA levels of hTERT in samples from subjects within a population of control subjects, the population of control subjects being a population of patients having a particular type of cancer. In one embodiment, the cancer is melanoma or metastatic malignant melanoma. However, it is to be understood that the population of control subjects is not limited to patients having melanoma or metastatic malignant melanoma. In alternative embodiments, the population of control subjects is a population of patients having any one or more of the cancers described herein in which the telomerase enzyme is expressed. Thus the population of control subjects, is some embodiments, is comprised of patients that have different types of cancer. As the telomerase enzyme is expressed in the majority of human cancers, the population of control subjects is not limited to patients having any one particular type of cancer. In the first embodiment, it is preferred that the threshold value is calculated using a Receiver Operating Characteristic (ROC) analysis based on the mRNA levels of hTERT (subsequent to administration of the medicament) and clinical data obtained from the population of control subjects. It is preferred that threshold value enables the cancer patient to be identified as having, or predicted to have, a clinical response or a clinical non-response (i.e. to be a clinical responder or a clinical non- responder) with high sensitivity and/or high specificity, more preferably high sensitivity and high specificity. In some embodiments the sensitivity and/or specificity is at least 70%, 75%, 80%, 85%, 90%, 95% or 100%. 13399613-3 In accordance with a second embodiment of the method of the invention, the evaluated hTERT level (as described above) is compared to a control hTERT level in a biological sample obtained from the cancer patient at a prior time point. In embodiments in which the evaluated hTERT level is an mRNA level of hTERT, the control hTERT level is also an mRNA level of hTERT. It is to be understood that the control hTERT level and the evaluated hTERT level are determined from first and second biological samples respectively that are obtained from the same patient but at different time points. The first time point is prior to the second time point. In some embodiments, the method of the present invention comprises the step of evaluating a control mRNA level of hTERT in a biopsy tissue sample obtained from the cancer patient by RNA sequencing. In some embodiments, the control hTERT level is a baseline hTERT level. In one embodiment, the baseline hTERT level is the hTERT level in a biological sample obtained from the cancer patient prior to the first administration of the medicament or within 24 hours of the first administration of the medicament. However, in alternative embodiments, the biological sample is obtained from the cancer patient within 2, 3, 4 or 5 days of the first administration of the medicament. The baseline hTERT level thus represents the level of hTERT in a biological sample obtained from the cancer patient before the medicament has been administered or before it has taken effect. In the second embodiment, when the evaluated mRNA level of hTERT is decreased relative to the baseline mRNA level of hTERT then the patient is identified as having, or is predicted to have, a clinical response. When the evaluated mRNA level of hTERT is the same as or is increased relative to the baseline level of hTERT then the patient is identified as having, or is predicted to have, a clinical non-response. Thus a decrease in the hTERT level over time in the cancer patient following treatment is indicative of the presence of a clinical response whereas the same level or an increase in the hTERT level over time in the cancer patient following treatment is indicative of the absence of a clinical response. In some embodiments, the cancer patient is identified as having, or is predicted to have, a clinical response if there is a statistically significant reduction in the mRNA level of hTERT between the evaluated level and the baseline level. In one embodiment, the cancer patient is identified as having, or is predicted to have, a clinical response when 13399613-3 the evaluated mRNA level of hTERT is decreased relative to the baseline mRNA level of hTERT by a log2(fold-change) that is equal to or less than -0.1, preferably equal to or less than -0.11. In one embodiment, the cancer patient is identified as having, or is predicted to have, a clinical response if the percentage change in the mRNA level of hTERT between the evaluated level and the baseline level is a reduction of at least 10%, preferably a reduction of at least 20%, more preferably a reduction of at least 25%. In some embodiments, the percentage change is a reduction of at least 28%, 28.4%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 150% or 200%. In some embodiments, the cancer patient is identified as having, or is predicted to have, a clinical non-response when the evaluated mRNA level of hTERT is similar or statistically the same as the baseline mRNA level of hTERT or when there is an increase, or a statistically significant increase in the mRNA level of hTERT between the evaluated level and the baseline level. In one embodiment, the cancer patient is identified as having, or is predicted to have, a clinical non-response when the evaluated hTERT level is increased relative to the baseline hTERT level by a log2(fold-change) that is equal to or greater than 0.03, preferably equal to or greater than 0.034. In one embodiment, the cancer patient is identified as having, or is predicted to have, a clinical non-response when the percentage change in the mRNA level of hTERT between the evaluated level and the baseline level is between 0% and an increase of at least 25%, preferably an increase of at least 50% or 100%, more preferably an increase of at least 130%. In some embodiments, the percentage change is an increase of at least 134%, 134.8%, 135%, 140%, 150%, 160%, 170%, 180%, 190%, 200%, 250%, 300%, 350% or 400%. In some embodiments, a delta hTERT value is calculated, which corresponds to the difference between the baseline hTERT level and the evaluated hTERT level (i.e. calculated delta hTERT value = baseline hTERT level – evaluated hTERT level). In such embodiments, the calculated delta hTERT value can be compared to a reference value obtained from a population of control subjects. In one embodiment, the reference value is a threshold value. In a preferred embodiment, the threshold value is a delta hTERT value of -0.1 TPM. When the calculated delta hTERT value is less than -0.1 TPM, then the cancer patient is identified or predicted to have a clinical response (i.e. to be a clinical responder). When the calculated delta hTERT value is greater than -0.1 TPM, then the cancer patient is identified or predicted to have a clinical non-response (i.e. to be a clinical non-responder). In an alternative embodiment, a different threshold value is 13399613-3 used. In some embodiments, the threshold value is -0.6, -0.5, -0.4, -0.3, -0.2, -0.12, 0.005 or 0.006. It is to be understood that a delta hTERT value of -0.1 or less means that the evaluated hTERT level is decreased by at least 0.1 TPM relative to the baseline hTERT level. This indicates that the patient is likely to have a clinical response. Conversely, a delta hTERT value of greater than -0.1 indicates that the patient is likely to have a clinical non- response. A delta hTERT value greater than -0.1 means that the evaluated hTERT level is decreased by less than 0.1 TPM (or is increased) relative to the baseline hTERT level. Thus as described above, a delta hTERT value of -0.1 is a threshold value, which is used to distinguish clinical responders from clinical non-responders. In one embodiment, the delta hTERT threshold value is calculated using a ROC analysis based on delta hTERT values and clinical data from a population of control subjects. It is preferred that delta hTERT threshold value enables the cancer patient to be identified as having, or predicted to have, a clinical response or a clinical non-response (i.e. to be a clinical responder or a clinical non-responder) with high sensitivity and/or high specificity, more preferably high sensitivity and high specificity. In some embodiments the sensitivity and/or specificity is at least 70%, 75%, 80%, 85%, 90%, 95% or 100%. In some embodiments, the population of control subjects is as defined above in relation to the first embodiment. In a third embodiment, the evaluated hTERT level is compared with the hTERT levels in a population of control subjects. If the control subjects are cancer patients, then the clinical outcomes of the control subjects have been identified or predicted. In one embodiment, the population of control subjects comprises or consists of clinical responders and/or healthy individuals. That is to say, the population includes patients who have been identified as, or predicted to be, clinical responders following a previous treatment for cancer and/or healthy individuals who have not been diagnosed with cancer. Such patients and/or healthy individuals are expected to have low hTERT levels. In an alternative embodiment, the population of control subjects comprises or consists of clinical non-responders. That is to say, the population includes patients who have been identified as, or predicted to be, clinical non-responders following a previous treatment for cancer. Such patients are expected to have high hTERT levels. The clinical outcome of the cancer patient in whom the evaluated hTERT level is measured is correlated with that observed in the population of control subjects when the 13399613-3 evaluated hTERT level also correlates with the hTERT levels observed in the population of control subjects. Thus in embodiments in which the population of control subjects comprises or consists of clinical responders and/or healthy individuals, then a cancer patient is identified as having, or predicted to have, a clinical response to the medicament when their evaluated hTERT level correlates with the hTERT levels in that population of control subjects. Conversely, in embodiments in which the population of control subjects comprises or consists of clinical non-responders, then a cancer patient is identified as having, or predicted to have, a clinical non-response to the medicament when their evaluated hTERT level correlates with the hTERT levels in that population of control subjects. In such embodiments, the term “correlates” refers to the evaluated hTERT level being similar to and/or statistically the same as the hTERT levels observed in the population of control subjects or to the evaluated hTERT level being similar to and/or statistically the same as an average hTERT level calculated from the hTERT levels of subjects within the population. In some embodiments, the tem “similar to and/or statistically the same as” refers to less than a 20% difference between two values, preferably less than a 15%, 10% or 5% difference. As discussed above, the population of control subjects may comprise cancer patients having one particular type of cancer. However, in alternative embodiments, the population may comprise cancer patients having different types of cancer. In a further embodiment, the evaluated hTERT level is at least a second evaluated hTERT level. That is to say, it is the hTERT level evaluated in at least a second biological sample obtained from the cancer patient at a time point subsequent to an administration of the medicament. In some embodiments, the clinical outcome of the cancer patient has been previously identified or predicted. Thus this second evaluated hTERT level enables the patient to be monitored over time. The at least second evaluated hTERT level post-administration can be compared to the reference value obtained from the population of control subjects (as described above) in order to confirm whether the patient is identified as having, or predicted to have, a continued clinical response or a continued clinical non-response to the medicament. In an alternative embodiment, the at least second evaluated hTERT level is compared with a control hTERT level in a biological sample obtained from the cancer patient at an earlier time point (e.g. a first evaluated hTERT level). 13399613-3 If the patient was previously identified as having, or predicted to have, a clinical response and the at least second evaluated hTERT level is the same as the control hTERT level (or is decreased relative to the control hTERT level), then the patient is continued to be identified as having, or predicted to have, a clinical response. However, if the reverse is found, this may indicate that the patient has changed from having a clinical response to having a clinical non-response; thus the patient is no longer identified as having, or predicted to have, a clinical response. If the patient was previously identified as having, or predicted to have, a clinical non-response and the at least second evaluated hTERT level is the same as the control hTERT level (or is increased relative to the control hTERT level), then the patient is continued to be identified as having, or predicted to have, a clinical non-response. However, if the reverse is found, this may indicate that the patient has changed from having a clinical non-response to having a clinical response; thus the patient is no longer identified as having, or predicted to have, a clinical non-response. In the above embodiment, two or more hTERT levels are considered “the same as” each other if they are similar to and/or statistically the same as each other. In one embodiment, two or more hTERT levels are “the same as” each other if they are within 20% of each other, preferably within 15%, 10% or 5% of each other. That is to say, a second evaluated hTERT level is “the same as” a control hTERT level when there is a less than 20% difference between the two levels, preferably a less than 15%, 10% or 5% difference. In yet a further embodiment, the at least second evaluated hTERT level is a third, fourth, fifth, sixth, seventh, eighth, ninth, tenth or more evaluated hTERT level and the comparisons described above are performed in order to continue to monitor the progress of the patient over time. In the embodiments described above, a biopsy tissue sample (i.e. a solid sample) is obtained from the cancer patient. However, in other embodiments, the biological sample is a liquid sample, preferably a blood sample. The term “blood sample” also comprises samples of plasma, serum and other blood derivatives. In one embodiment, the liquid biopsy comprises tumor-derived entities such as circulating tumor cells, cell free or circulating tumor DNA and/or tumor extracellular vesicles (e.g. exosomes). In some embodiments, transcriptome analysis of tumor-derived entities, such as circulating tumor cells, in a liquid biopsy (e.g. a blood sample) is used in order to measure an hTERT level 13399613-3 (see, for example, Negishi, R. et al. Transcriptomic profiling of single circulating tumor cells provides insight into human metastatic gastric cancer. Commun Biol 5, 20 (2022), incorporated herein by reference). In the embodiments described above, the hTERT level that is evaluated in the biological sample obtained from the cancer patient is an mRNA level of hTERT. However, in other embodiments, an alternative measure of the hTERT level in the biological sample obtained from the cancer patient is provided. In one such embodiment, the hTERT level is a protein level of hTERT. In the embodiments described above, the medicament that has been administered to the cancer patient comprises a cocktail of polypeptides comprising the sequences of SEQ ID NOS.1, 2 and 3. In an alternative embodiment, the medicament comprises a cocktail of nucleic acid molecules which encode the polypeptides of SEQ ID NOS.1, 2 and 3. In a further embodiment, the medicament comprises a cocktail of different T-cell receptors that are specific for polypeptides consisting of the sequences of SEQ ID NOS.1, 2 and 3. In yet a further embodiment, the medicament comprises a cocktail of T-cells displaying the aforementioned T-cell receptors. However, it is to be understood that the medicament is not limited to the aforementioned cocktail and may comprise a polypeptide, a nucleic acid molecule, a T-cell or T-cell receptor (or antigen-binding fragment thereof) as described in the sections above, provided that: (A) the polypeptide comprises a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) the nucleic acid molecule comprises a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) the T-cell receptor is specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) the T-cell displays a T-cell receptor as defined in (C). In yet a further embodiment, the medicament has been administered to the cancer patient simultaneously, separately or sequentially with an immune checkpoint inhibitor 13399613-3 as described in the sections above. It is preferred that the immune checkpoint inhibitor is a PD-1/PD-L1 immune checkpoint inhibitor and/or a CTLA-4 immune checkpoint inhibitor. The method of the invention is suitable for use with samples obtained from a patient suffering from any type of cancer in which the telomerase enzyme is activated. As discussed above, the telomerase enzyme is activated in the majority of human cancers thus the method of the invention is not limited to any one particular type of cancer. Patient Group In one aspect of the present invention there is provided a method of treating cancer in a patient in need of treatment wherein the patient is selected from a defined patient group. The patient group is defined by patients within the group having a level of biomarker selected from the following: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) tumor infiltrating lymphocyte level; and/or (iv) neoantigens, where the level of one or more of (i) to (iv) is determined to be “low”. This patient group has been identified as being particularly responsive to the combination therapy described above. That is to say, on average the patient group has a higher prevalence of complete response and a longer median overall survival than the general patient population for the cancer type to which the patient is subject. A member of this patient group may be identified by obtaining a biological sample from the patient and determining the level of one or more of (i) to (iv), as described above, to be low in the biological sample. However, it is not essential that this step be performed in order to carry out treatment. In another aspect of the present invention, there is provided a method of treating cancer in a patient in need of treatment wherein the patient is selected from a defined patient group. The patient group is defined by patients within the group having being identified as having, or predicted to have, clinical response to a previous treatment comprising administration of: 13399613-3 (A) a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (B) a nucleic acid molecule comprising a nucleotide sequence encoding a polypeptide comprising a region of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the region; (C) a T-cell receptor specific for a polypeptide consisting of at least 12 amino acids of hTERT or a sequence having at least 80% sequence identity to the polypeptide; or (D) a T-cell displaying the T-cell receptor as defined in (C). In a further embodiment, the previous treatment comprises administration of an immune checkpoint inhibitor, simultaneously, separately or sequentially with the polypeptide, the nucleic acid molecule, the T-cell receptor or the T-cell as defined above. A member of this patient group may be identified by obtaining a biological sample from the patient, evaluating an hTERT level in the biological sample and finding it to be negatively associated with a clinical response. That is to say, the patient may be identified as having a low hTERT level or a decrease in hTERT levels. However, it is not essential that this step be performed in order to carry out treatment. Biomarker One or more biomarkers are relevant to aspects of the present invention. The level of one or more of the biomarkers is determined in some aspects of the invention in order to identify a subject who is suitable for to receive the combination therapy. In particular, the level of one or the biomarkers is determined to be “low” in patients identified to be suitable to receive the combination therapy. In other aspects of the invention, the combination therapy is used for the treatment of a patient who is a member of a patient group whose levels of one or more of the biomarkers is “low”. The biomarker is one or more selected from the following: (i) tumor mutational burden; (ii) PD-L1 expression; (iii) tumor infiltrating lymphocyte level; and/or (iv) neoantigens. 13399613-3 Where the level of one or more of (i) to (iv) is determined to be “low” the cancer patient from whom the biological samples obtained is identified as a subject to whom the combination therapy is to be administered or characterises the patient group to whom the combination therapy is administered. That is to say that the patient is identified as a patient who is more likely to receive a clinical benefit from the combination therapy or is more likely to receive a higher clinical benefit than the general patient population for the cancer type to which the patient is subject. In some embodiments, the level of the biomarker (i) to (iv) is determined to be “low” if equal to or less than the 50 ^th , 40 ^th , 30 ^th , 20 ^th , 10 ^th , 5 ^th or 1 ^st percentile of a cancer patient population. In some embodiments, the level of biomarker (i) in a patient is determined to be “low” if the tumor mutational burden in the biological sample obtained from the patient is equal to or less than 400, 300, 200, 100, 75, 50, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6.6, 6, 5, 4, 3, 2, 1, 0.1 or 0.001 somatic mutations per megabase (mut/Mb). Preferably, the term “low” as used herein in relation to the level of TMB refers to a level that is equal to or less than 30, 25, 20, 10, 9, 8, 7, 6, 6.6, 5, 4, 3 or 2 mut/Mb, most preferably equal to or less than 10 mut/Mb. In some embodiments, the level of biomarker (ii) (i.e. tumor cell PD-L1 expression) is determined to be “low” if the tumor proportional score (TPS) for the patient is equal to or less than 60%, 50%, 40%, 30%, 20%, 10%, 5% or 1%. Preferably, a TPS that is equal to or less than 1%. More preferably, a TPS that is less than 1%. In one embodiment, the level of biomarker (ii) is determined to be “low” if PD-L1 staining of equal to or less than 60%, 50%, 40%, 30%, 25%, 20%, 10%, 5% or 1% of tumor cells is observed in the biological sample from the patient. Preferably PD-L1 staining of equal to or less than 1% of tumor cells. More, preferably PD-L1 staining of less than 1% of tumor cells. Alternatively, the level of biomarker (ii) is determined to be “low” if equal to or less than 60%, 50%, 40%, 30%, 20%, 10%, 5% or 1% of immune cells, preferably tumor infiltrating lymphocytes, express PD-L1 in the biological sample obtained from the patient. Preferably, equal to or less than 10%, 5% or 1% of immune cells expressing PD-L1. More preferably, equal to or less than 10%, 5% or 1% of tumor infiltrating lymphocytes expressing PD-L1. In one embodiment, the level of biomarker (ii) is determined to be “low” if PD-L1 stained tumor-infiltrating immune cells covering equal to or less than 60%, 13399613-3 50%, 40%, 30%, 25%, 20%, 10%, 5% or 1% of the tumor area are observed in the biological sample obtained from the patient. Preferably, PD-L1 stained tumor-infiltrating immune cells covering equal to or less than 10%, 5% or 1% of the tumor area. In a further alternative, the level of biomarker (ii) is determined to be “low” if the TPS is below 50%, 40%, 30%, 25%, 20%, 10%, 5% or 1% in the biological sample obtained from the patient. In a further alternative, the level of biomarker (ii) is determined to be low if a combined positive score (CPS) is equal to or less than 60%, 50%, 40%, 30%, 25%, 20%, 15%, 10%, 5% or 1% in the biological sample obtained from the patient. Preferably a CPS that is equal to or less than 20% or 10%. In some embodiments, the level of biomarker (ii) is determined to be “low” if two or more of these requirements are met. In some embodiments, the level of biomarker (iii) is determined by measuring the level of the tumor infiltrating lymphocyte density. In particular, in some embodiments, the level of biomarker (iii) is determined to be “low” if the tumor infiltrating lymphocyte density in the biological sample obtained from the patient is equal to or less than the 50 ^th , 40 ^th , 30 ^th , 20 ^th , 10 ^th , 5 ^th or 1 ^st percentile of a cancer patient population. In some alternative embodiments, the tumor infiltrating lymphocyte density is specifically the CD8 + T-cell density. In these embodiments, it is preferred that the level of the biomarker is determined to be “low” when there is equal to or less than a CD8+ T-cell density of 2000, 1900, 1800, 1700, 1600, 1500, 1400, 1300, 1200, 1100, 1000, 900, 886, 885, 880, 870, 860, 850, 700, 600, 500, 400, 350, 341, 300, 250, 200, 150, 125, 116, 100, 90, 80, 78, 75 or 70 count/mm ² in the biological sample obtained from the patient. It is preferred that the level of biomarker (iii) is determined to be “low” when the CD8+ T-cell density is equal to or less than 1000, 900, 886, 885, 880, 870, 860, 850 or 800 counts/mm ² , more preferably equal to or less than 900 or 850 counts/mm ² in the biological sample obtained from the patient. In some embodiments, the level of biomarker (iv) is determined to be “low” if the number of predicted neoantigens in the biological sample obtained from the patient is equal to or less than 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1. It is preferred that the number of predicted neoantigens in the biological sample obtained from the patient is equal to or less than 1. In some embodiments, the level of the biomarker (i) to (iv) is determined to be “low” if it is below a threshold value. In some embodiments, the threshold value is calculated from 13399613-3 data on the level of the biomarker in subjects within a population of control subjects. In a preferred embodiment, the threshold value is calculated using a Receiver Operating Characteristic (ROC) analysis based on the level of the biomarker and the clinical data obtained from a population of control subjects. In one embodiment, a ROC analysis is performed using GraphPad Prism 9.4.1 software (San Diego, California, USA) and the Wilson/Brown method. In a preferred embodiment, the threshold value enables the identification or prediction of a clinical outcome, and therefore suitability to receive the combination therapy, with high sensitivity and/or high specificity, more preferably high sensitivity and high specificity. In some embodiments the sensitivity and/or specificity is at least 70%, 75%, 80%, 85%, 90%, 95% or 100%. In one embodiment, the threshold value for biomarker (i) to (iv) is measured in a unit as described above. In some embodiments, the threshold value for biomarker (i) is measured in mutations per megabase (mut/Mb). In some embodiments, the threshold value for biomarker (ii) is measured as a tumor proportional score (TPS), a percentage of immune cells expressing PD-L1 or a percentage of the tumor area covered by PD-L1 stained immune cells, or a combined positive score (CPS). In some embodiments, the threshold value for biomarker (iii) is measured as a CD8+ T-cell density (counts/mm ² ). In some embodiments, the threshold value for biomarker (iv) is measured as a number of predicted neoantigens. In some embodiments, the population of control subjects from which the threshold value is calculated is a group of individuals from which data on the level of the biomarker is evaluated. In one embodiment, the population of control subjects is a population of cancer patients. That is to say, a group of patients who have been diagnosed with cancer. In one embodiment, the population of cancer patients is a group of patients who have been diagnosed with a particular type of cancer (e.g. malignant melanoma, mesothelioma, head and neck cancer, ovarian cancer, non-small cell lung cancer). In one embodiment, the population of cancer patients is a sample of individuals (e.g. at least 10, 20 or 50 randomly selected individuals) who have been diagnosed with a particular type of cancer and who are taken to be representative of the wider patient population. In one embodiment, the population of cancer patients is a cohort of patients who are undergoing study or treatment. In a further embodiment, the population of control subjects comprises patients that have been diagnosed with different types of cancer. In one embodiment, the population of control subjects is a population of patients having any one or more of the cancers described herein in which the telomerase enzyme 13399613-3 is expressed. As the telomerase enzyme is expressed in the majority of human cancers, the population of control subjects is not limited to patients having any one particular type of cancer. In some embodiments, the patient is excluded from treatment with the PD-1/PD-L1 immune checkpoint inhibitor when administered as a monotherapy. That is to say, the biomarker or biomarkers in the patient are at levels for which the PD-1/PD-L1 immune checkpoint inhibitor does not have regulatory approval when administered alone. In some embodiments, the patient is excluded from treatment with the PD-1/PD-L1 immune checkpoint inhibitor and/or the CTLA-4 immune checkpoint inhibitor when administered as a monotherapy. That is to say, the biomarker or biomarkers in the patient are at levels for which the PD-1/PD-L1 immune checkpoint inhibitor and/or the CTLA-4 immune checkpoint inhibitor do not have regulatory approval when administered alone. Cancer Indication The present invention is not limited to any particular cancer indication. Aspects of the present invention are, in principle, applicable across all cancer indications where PD- 1/PD-L1 and/or CTLA-4 inhibitors can be used. Such cancer indications include the following: breast cancer, prostate cancer, pancreatic cancer, colorectal cancer, lung cancer, bladder cancer, malignant melanoma, leukaemias, lymphomas, ovarian cancer, cervical cancer, head and neck cancer, malignant mesothelioma and biliary tract carcinomas. In preferred embodiments, the cancer indication is one for which high tumor mutational burden, PD-L1 expression or tumor infiltrating lymphocyte levels is a patient selection criterion such as cervical cancer, triple negative breast cancer, head and neck cancer, esophageal cancer and urothelial cancer. As examples of such a selection criterion, nivolumab and pembrolizumab are each approved for treatment of patients with lung cancer who have >50% (Europe) or >1% (USA) PD-L1 expression levels on tumor cells. Similarly, atezolizumab is approved for treatment of patients with urothelial carcinoma who have PD-L1 stained tumor-infiltrating immune cells [IC] covering ≥ 5% of the tumor area. Mechanism of Action Without wishing to be bound by theory, it is believed that the biomarkers identified herein correlate with more effective combination therapy treatment and it is believed that a 13399613-3 patient group defined herein is particularly responsive to the combination therapy treatment for the following reasons. The first component of the combination therapy treatment (e.g. the polypeptide described above) induces a T cell response directed against the respective tumor-associated antigen (TAA). The following discussion will refer to the preferred tumor-associated antigen of human telomerase reverse transcriptase (hTERT) but it is to be appreciated that the rationale also applies to other tumor-associated antigens in a corresponding manner. hTERT is a non-mutated antigen, with an expression pattern limited to rapidly proliferating tissues, stem cells, and cancer cells. hTERT is activated in 85-90% of all cancers, and serves as a promising antigen for immunotherapy due to its expression throughout the tumorigenesis and across otherwise heterogenous cancer lesions. Prior art immunotherapy (i.e. checkpoint inhibitor monotherapy) relies on spontaneously primed anti-tumor T cell responses for clinical efficacy. This is evidenced by the association between clinical response and: i) TMB high (Kim JY, Kronbichler A, Eisenhut M, Hong SH, van der Vliet HJ, Kang J, et al. Tumor Mutational Burden and Efficacy of Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis. Cancers (Basel).2019;11(11)), ii) PD-L1 positive (Taube JM, Klein A, Brahmer JR, Xu H, Pan X, Kim JH, et al. Association of PD-1, PD-1 Ligands, and Other Features of the Tumor Immune Microenvironment with Response to Anti–PD-1 Therapy. Clinical Cancer Research.2014;20(19):5064-74), and iii) tumor-infiltrating lymphocytes (TIL)-high ( Uryvaev A, Passhak M, Hershkovits D, Sabo E, Bar-Sela G. The role of tumor-infiltrating lymphocytes (TILs) as a predictive biomarker of response to anti-PD1 therapy in patients with metastatic non-small cell lung cancer or metastatic melanoma. Medical Oncology. 2018;35(3):25) tumors. TMB serves as a marker for how different from healthy cells the tumor appears to the immune system. TMB-high tumors frequently harbor immunogenic mutated peptides (neoantigens) that can be recognized by a patient’s T cells, and subsequently released from the immune checkpoints by checkpoint inhibitors. Various studies have observed 13399613-3 a correlation between higher TMB and improved clinical response to immune checkpoint inhibitor therapy, details of which are provided below. Marabelle et al. 2020 reported that high tissue TMB (tTMB) in various solid tumors correlated with a response to pembrolizumab monotherapy. Patients were defined as having tTMB-high status using a threshold of ≥10 mut/Mb (Marabelle A et al.: Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open- label, phase 2 KEYNOTE-158 study. Lancet Oncol.2020 Oct;21(10):1353-1365). Hamid et al. 2019 reported that clinical activity of the PD-L1 inhibitor atezolizumab in patients with metastatic melanoma was higher in TMB-high patients than in TMB-low patients. A TMB cutoff of 16 mut/Mb was used to define the TMB-high or low patients (Hamid O et al.: Clinical Activity, and Biological Correlates of Response in Patients with Metastatic Melanoma: Results from a Phase I Trial of Atezolizumab. Clin Cancer Res. 2019 Oct 15;25(20):6061-6072). Johnson et al. 2016 reported a retrospective cohort study of patients with metastatic melanoma treated with anti–PD-1 (nivolumab or pembrolizumab) or anti–PD-L1 (atezolizumab) antibodies. Patients were divided into high (>23.1 mutations/MB), intermediate (3.3–23.1 mutations/MB), and low (<3.3 mutations/MB) mutation load groups. Using these thresholds, superior objective response rates (ORR) were observed in the high mutational load group, followed by intermediate and low groups (Johnson DB et al.: Targeted Next Generation Sequencing Identifies Markers of Response to PD-1 Blockade. Cancer Immunol Res.2016 Nov;4(11):959-967). Balar et al. reported that tumor mutational load was significantly higher in patients with locally advanced and metastatic urothelial carcinoma who responded to the anti-PD-L1 antibody atezolizumab than in non-responders (Balar AV et al.: Atezolizumab as first- line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial. Lancet. 2017 Jan 7;389(10064):67-76). Chae et al.2019 reported that high-TMB was associated with significantly longer overall survival in non-small cell lung cancer patients treated with PD-1/PD-L1 immune 13399613-3 checkpoint therapies. TMB was calculated in mutations per megabase pair and the following categories were determined: very low (0-1), low (2-5), intermediate (6-14), high intermediate (15-19), high (20-34), and very high (35 and above) (Chae YK et al.: Association of Tumor Mutational Burden With DNA Repair Mutations and Response to Anti-PD-1/PD-L1 Therapy in Non-Small-Cell Lung Cancer. Clin Lung Cancer. 2019 Mar;20(2):88-96.e6). Wang et al.2019 reported that TMB-high patients with gastric cancer treated with the PD-1 antibody toripalimab showed significantly superior overall survival than those who were TMB-low. TMB was determined by analyzing somatic mutations per mega-base (Mb). A cutoff of the top 20% of the TMB (12 mutations/Mb) was selected as defining a tumor as TMB-high. Patients with TMB <12 mutations/Mb were defined as TMB-low (Wang F et al.: Safety, efficacy and tumor mutational burden as a biomarker of overall survival benefit in chemo-refractory gastric cancer treated with toripalimab, a PD-1 antibody in phase Ib/II clinical trial NCT02915432. Ann Oncol.2019 Sep 1;30(9):1479- 1486). A meta-analysis reported in Kim et al. 2019, which integrated more than 5000 patient data with various advanced cancer types, indicated a 47% risk reduction for death and a 48% risk reduction for disease progression in patients with high compared to low TMB undergoing immune checkpoint inhibitor treatment (Kim JY et al.: Tumor Mutational Burden and Efficacy of Immune Checkpoint Inhibitors: A Systematic Review and Meta- Analysis. Cancers (Basel).2019 Nov 15;11(11):1798). PD-L1 is a marker that is expressed by tumor cells to restrict the effector functions of T cells specific for tumor antigens. PD-L1 is upregulated on cancer cells in response to inflammatory cytokines released by T cells during an ongoing immune response. Thus, the presence of PD-L1 on tumor cells reflect the existence of anti-tumor T cell responses. Patients with PD-L1 positive tumors are more likely to achieve clinical efficacy from checkpoint inhibition. This has been observed in a number of previous studies, as detailed below. A randomized phase 3 study of non-small-cell lung cancer patients (NSCLC) who received pembrolizumab observed a relationship between high tumor PD-L1 expression and greater efficacy of pembrolizumab. It was concluded that pembrolizumab was a 13399613-3 reasonable treatment option for patients with PD-L1-expressing tumors (having a tumor proportion score of 1% or greater) (Mok TSK et al.: Pembrolizumab versus chemotherapy for previously untreated, PD-L1-expressing, locally advanced or metastatic non-small-cell lung cancer (KEYNOTE-042): a randomised, open-label, controlled, phase 3 trial. Lancet.2019 May 4;393(10183):1819-1830). A further study of NSCLC patients who had been treated with nivolumab observed that 5-year overall survival rates were higher in patients with tumor PD-L1 expression of ≥1% compared with those having tumor PD-L1 expression of <1% (Borghaei H et al.: Five-Year Outcomes From the Randomized, Phase III Trials CheckMate 017 and 057: Nivolumab Versus Docetaxel in Previously Treated Non-Small-Cell Lung Cancer. J Clin Oncol.2021 Mar 1;39(7):723-733). A randomized phase 3 study of patients with advanced head and neck squamous cell carcinomas (HNSCCs) treated with pembrolizumab observed that PD-L1 expression level associated with an overall survival benefit over chemotherapy; pembrolizumab alone significantly prolonged overall survival (OS) compared with cetuximab- chemotherapy in patients with PD-L1 combined positive score (CPS) ≥ 20 (hazard ratio [HR], 0.61; 95% CI, 0.45 to 0.83) and CPS ≥ 1 (HR, 0.78; 95% CI, 0.64 to 0.96) (Harrington KJ et al.: Pembrolizumab With or Without Chemotherapy in Recurrent or Metastatic Head and Neck Squamous Cell Carcinoma: Updated Results of the Phase III KEYNOTE-048 Study. J Clin Oncol. 2023 Feb 1;41(4):790-802). In addition, a randomized phase III KEYNOTE-181 study of pembrolizumab versus chemotherapy in advanced esophageal cancer observed that overall survival was prolonged with pembrolizumab versus chemotherapy for patients with a PD-L1 combined positive score (CPS) ≥ 10 (Kojima T et al.: Randomized Phase III KEYNOTE-181 Study of Pembrolizumab Versus Chemotherapy in Advanced Esophageal Cancer. J Clin Oncol. 2020 Dec 10;38(35):4138-4148). TIL is also a marker for tumor immunogenicity and predictive of clinical efficacy from checkpoint inhibition. The presence of few TILs suggests a lack of tumor immunogenicity, which would reduce the expected clinical efficacy of checkpoint inhibition. In a study of the expression of CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs) in patients with melanoma treated with anti-PD-1 immunotherapy, an association was found between CD8+/CD4+ TILs ratio and response to anti-PD-1 treatment. Ratios of CD8+/CD4+ lower than 2 predicted lack of response to treatment, while CD8+/CD4+ ratios higher than 2.7 13399613-3 had an 81.3% response rate. In addition, it was reported that the presence of more than 1900/mm ² of CD8+ lymphocytes in the melanoma tumor predicted a 90% response to therapy. An association was also observed between CD8+/CD4+ TILs ratio and response to anti-PD-1 treatment patients with metastatic NSCLC. Furthermore, a significant relationship between infiltration of the NSCLC tumor by CD8+ TILs and response to immunotherapy was observed. Tumors with a CD8+ lymphocyte count under 886/mm ² showed low response rates but tumors with a CD8+ lymphocyte count in the range of 886-1899/mm ² showed a high response rate (Uryvaev A et al.: The role of tumor-infiltrating lymphocytes (TILs) as a predictive biomarker of response to anti-PD- 1 therapy in patients with metastatic non-small cell lung cancer or metastatic melanoma. Medical Oncology 2018, 35:25). In a further study of melanoma patients who received anti-PD-1 immunotherapy, it was observed that the response group was associated with significantly higher numbers of CD8+ T cells at both the invasive margin and the tumor centre when compared to the progression group (Tumeh PC et al.: PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 2014 Nov 27;515(7528):568-71). Therefore, the prevailing view from the prior art is that patients with tumors that are characterized as TMB-high, PD-L1 positive and TIL-high respond better to immune checkpoint inhibitor monotherapy. Indeed, the regulatory approval of checkpoint inhibitors for cancer indications is usually limited to patients with high levels of relevant biomarkers. For example, nivolumab and pembrolizumab are each approved for treatment of patients with lung cancer who have ≥50% (Europe) or ≥1% (USA) PD-L1 expression levels on tumor cells. Similarly, atezolizumab is approved for treatment of patients with urothelial carcinoma who have PD-L1 stained tumor-infiltrating immune cells [IC] covering ≥ 5% of the tumor area. TMB-low tumors, PD-L1 negative tumors and TIL-low tumors are generally less immunogenic and consequently immune checkpoint inhibitor monotherapy has relatively reduced clinical efficacy. The observation made by the present inventors, that a combination therapy of a tumor-associated antigen vaccine and an anti-PD-1/PD-L1 immune checkpoint inhibitor produced durable clinical responses in patients whose biopsies were characterised as TMB-low (and/or having low numbers of predicted neoantigens), PD-L1-low and few TILs, was therefore particularly unexpected. 13399613-3 Without wishing to be bound by theory, it is believed that low levels of the biomarkers identified herein (tumor mutational burden, PD-L1 expression, tumor infiltrating lymphocyte level, and/or number of predicted neoantigens) correlate with more effective combination therapy treatment and a patient group defined herein is particularly responsive to the combination therapy treatment because the first component of the combination therapy treatment (e.g. the polypeptide described above) induces a T cell response directed against the respective tumor-associated antigen (TAA). In doing so, it is believed that the combination therapy treatment extends clinical efficacy to patients who might otherwise not have benefited from immune checkpoint inhibitor monotherapy. As described above, TMB-low tumors are generally less immunogenic, and the checkpoint inhibitors have relatively reduced clinical efficacy. As the first component of the treatment described above induces an anti-tumor T cell response directed at a non- mutated antigen, these T cells may elicit a clinically meaningful anti-tumor immune response also in TMB-low tumors when combined with a checkpoint inhibitor. PD-L1 negative tumors are less immunogenic, and the first component of the treatment, as described above, may introduce the necessary anti-tumor T cell response to promote clinical responses when combined with checkpoint inhibition. Furthermore, the first component of the treatment, as described above, which aims to increase the breadth of the anti-tumor T cell response, may promote infiltration of CD8 T cells to the tumor microenvironment. Thus, the added benefit of administration of the first component of the treatment to checkpoint inhibition may be relatively greater in patients with biopsies characterized by few TILs. Thus in patients having low levels of the biomarkers defined herein (tumor mutational burden, PD-L1 expression, tumor infiltrating lymphocyte level, and/or number of predicted neoantigens), the clinical efficacy of the combination therapy treatment is unexpectedly high as compared with the clinical efficacy that would have been expected in the patients had they been treated with immune checkpoint inhibitor monotherapy. 13399613-3 Examples Hereinafter, the invention will be specifically described with reference to the Examples. However, these Examples do not limit the technical scope of the invention. Example 1: Durable objective responses were observed in patients with metastatic malignant melanoma who were administered the polypeptides of SEQ ID NOS.1, 2 and 3 in combination with a PD-1/PD-L1 immune checkpoint inhibitor Clinical trial design: The clinical trial was a phase I, open-label, multicentre study investigating the tolerability and efficacy of a vaccine comprising a cocktail of polypeptides having the sequences of SEQ ID NOS.1, 2 and 3 in first-line metastatic malignant melanoma patients planned for treatment with the anti-PD-1 antibody pembrolizumab. The dataset from the study included only first-line patients. Treatment regimen: In cohort 1 of the clinical trial, 20 patients were given pembrolizumab (200 mg) every 3 weeks (Q3W) according to the package label and the vaccine comprising the cocktail of polypeptides of SEQ ID NOS.1, 2 and 3 (300 μg) was given with GM-CSF (37.5 μg) as an adjuvant. The vaccination regimen with the cocktail of polypeptides of SEQ ID NOS. 1, 2 and 3 was eight intradermal injections over a course of 3 months. In cohort 2 of the clinical trial, 10 patients were given pembrolizumab (200 mg) every 3 weeks (Q3W) according to the package label and the vaccine comprising the cocktail of polypeptides of SEQ ID NOS.1, 2 and 3 (300 μg) was given with GM-CSF (75 μg) as an adjuvant. The vaccination regimen with the cocktail of polypeptides of SEQ ID NOS.1, 2 and 3 was eight intradermal injections over a course of 3 months. Results and Discussion: Referring to Figure 1, of the 30 patients included in cohort 1 and 2 of the clinical trial, 10 patients had a complete response (33.3%), 7 patients had a partial response (23.3%), 2 patients had stable disease (6.7%) and 11 patients had confirmed/unconfirmed progressive disease (36.75). This corresponds to an objective response rate (i.e. the 13399613-3 proportion of patients with a complete response or a partial response to treatment according to iRECIST criteria) of 56.7%. With a median follow-up time of 29.0 months (range 6.7 - 42.4), the median PFS was 18.9 months (95% CI, 3.5 - no estimate), and the median OS was not reached (Figures 7A and 7B). The one- and two-year survival rates were 86.7% and 73.3%, respectively. The ORR per iRECIST was 56.7% (95% CI, 37.4 - 74.5%). Most objective responses were durable and persisted for up to 2 years (Figures 7C and Figure 8). The median duration of response (DOR) was not reached, and only 3 of the 17 patients with a clinical response had progressed at the time of reporting (Figure 7C). Two patients with iPR progressed after 8.3 and 12.7 months in response, respectively, and one patient achieving an iCR progressed after 15.9 months in response. Therefore, the combination of a vaccine comprising a cocktail of polypeptides having the sequences of SEQ ID NOS.1, 2 and 3 with the PD-1/PD-L1 immune checkpoint inhibitor pembrolizumab produces durable objective responses in patients with metastatic malignant melanoma. Example 2: Durable clinical responses were observed in metastatic malignant melanoma patients with baseline tumor biopsies characterised as tumor mutational burden (TMB)- low and having a lower number of predicted neoantigens Materials and Methods: Tumor biopsies, one formalin-fixed, paraffin-embedded (FFPE) and two snap frozen, were collected at baseline and at the end of the treatment regimen as set out in Example 1. DNA was extracted from whole-blood to allow annotation of somatic variants. DNA for whole-exome sequencing and the TMB calculation was extracted from snap-frozen biopsies from 17 patients at baseline. Tumor mutational burden (TMB) calculation: DNA degradation and potential contamination was tested using Agarose Gel Electrophoresis. DNA concentration was measured using Qubit® DNA Assay Kit in Qubit® 4.0 Flurometer (Life Technologies, CA, USA). Human genomic DNA was physically fragmented and prepared as libraries containing duel-indexed sequencing barcodes. The pre-capture libraries were enriched using SureSelect Human AII Exon 13399613-3 V6 capture baits (Agilent Technologies) for coding regions and splice junction sites of 20,000 human genes. The post-capture libraries were sequenced on a NovaSeq 6000 instrument (Illumina). The sequence data were analyzed using a custom-developed bioinformatics pipeline which aligns sequence data to the human genome (GRCh37/UCSC hg19), to perform variant calls and annotation. The pipeline performs QC analysis of the sequence data to ensure the quality of the reported sequencing data. The TMB was calculated using the number of mutations with a variant allelic frequency above 5% per megabase. TMB- low can be defined as equal to or less than 10 mutations (with a variant allelic frequency above 5%) per megabase. Predicted neoantigen calculation: The neoantigen prediction was performed using a proprietary platform developed by NEC Oncoimmunity AS (Oslo, Norway). The predicted neoantigens are a result of looking at which mutations (based whole-exome sequencing of DNA) are expressed (confirmed by RNA sequencing) and evaluated as sufficiently different from a normal counterpart, and with good binding properties to patient-specific HLA type so are thereby expected to be recognized by the patients’ immune system. The method is described in Malone B. et al., Sci Rep.2020 Dec 23;10(1):22375 (incorporated herein by reference). The artificial intelligence (AI) prediction platform used for immunogenic neoantigen prediction was the NEC Immune Profiler (NIP). The NIP software predicted each of the key determinants of antigen presentation (AP) for each somatic mutation, by predicting the potential of all tumor-specific mutated peptides to be efficiently presented by each of the patients Class I HLA-A and -B alleles. Thus the AP score reflects the features and likelihood of a somatic mutation being recognized by a T cell. This includes metrics such as RNA expression levels of the mutated antigen, the “distance from self” (i.e. how different does the mutation make the peptide antigen), and how well do the mutated peptide fit with the patients’ HLA alleles. A cut-off of 0.6 or 0.7 is considered relevant based on the feedback from NEC Oncoimmunity (with 0.7 being a stricter cut-off). A cut off of 0.6 was used in the present analysis. 13399613-3 Results and Discussion: Referring to Figure 2A, among the clinical “Responders (R)” (i.e. those patients with a complete response or a partial response to treatment; n=8) the median TMB was 3.0 mutations/megabase (mut/Mb) (range 1.3-55.2) as compared to a median TMB of 10.7 mut/Mb (range 2.1-48.2) in the clinical “Non-Responders (NR)” (i.e. those patients with stable disease or confirmed/unconfirmed progressive disease following treatment; n=9). Thus the median TMB for the responders was lower than that of the non-responders (although the difference was not statistically significant as determined by a statistical test (Mann-Whitney); p value 0,2459). The baseline overall median TMB was 6.6 mutations/Mb (range, 1.3-55.2). Further details of the baseline TMB values are set out in Table 2A. Table 2A: Baseline TMB (mut/Mb) A threshold of 10 mut/Mb was applied to the data in Table 2A to produce the analysis set out in Table 2B. This threshold has been used in previous clinical studies (see, for example, Marabelle et al., 2020). Therefore, low TMB was defined as ≤10 mut/Mb and high TMB was defined as >10 mut/Mb. Table 2B: Numbers of responders and non-responders having low or high TMB (based on a threshold of 10 mut/Mb) 13399613-3 The objective response rate (ORR) for the low TMB population was 66.7% (6/9 patients). The ORR for the high TMB population was 25% (2/8 patients). The ORR for the sampled population was 47.1% (8/17 patients). This analysis shows that clinical responses were observed at a similar (high) rate in patients with low baseline TMB levels, as compared to the overall sampled population in the study. This was unexpected as previous studies have reported that lower TMB levels correlate with poorer responses to checkpoint inhibition monotherapy. Thus, the addition of a vaccine comprising the cocktail of polypeptides of SEQ ID NOS.1, 2 and 3 to the checkpoint inhibition extended clinical efficacy to patients with TMB-low tumors. Referring to Figure 2B, among clinical responders (i.e. those patients with a complete response or a partial response to treatment; n=7) the median number of predicted neoantigens was lower as compared to a median number of predicted neoantigens in clinical non-responders (i.e. those patients with stable disease or confirmed/unconfirmed progressive disease following treatment; n=9). The baseline overall median number of predicted neoantigens was 1.5 (range, 0-21). Clinical responders exhibited a median number of neoantigens of 0.0 vs.2.0, p value 0.638, for non-responders. A threshold of 1 predicted neoantigen was applied to the data in Figure 2B. This analysis is set out in Table 2C below. Therefore, low predicted neoantigen was defined as ≤1 predicted neoantigen and high predicted neoantigen was defined as >1 predicted neoantigen. Table 2C: Numbers of responders and non-responders having low or high predicted neoantigen (based on a threshold of 1 predicted neoantigen) The ORR for the low predicted neoantigen population was 50% (4/8 patients). The ORR for the high predicted neoantigen population was 37.5% (3/8 patients). The ORR for the sampled population was 43.8% (7/16 patients). 13399613-3 This analysis shows that clinical responses were observed at a similar (high) rate in patients with low predicted neoantigen levels, as compared to the overall sampled population in the study. This was unexpected as lower predicted neoantigen levels are thought to correlate with poorer responses with checkpoint inhibition monotherapy. Thus, the addition of a vaccine comprising the cocktail of polypeptides of SEQ ID NOS. 1, 2 and 3 to the checkpoint inhibition extended clinical efficacy to patients with tumors having low predicted neoantigen levels. Therefore, both the median TMB and the median number of predicted neoantigens in baseline tumor biopsies from patients with durable clinical responses were lower than those from patients who were clinical non-responders. Furthermore, patients having TMB-low tumors (equal to or less than 10 mut/Mb) at baseline or having low predicted neoantigen levels (equal to or less than 1 predicted neoantigen) exhibited unexpectedly high clinical response rates following treatment with a vaccine comprising the cocktail of polypeptides of SEQ ID NOS. 1, 2 and 3 in combination with a PD-1 immune checkpoint inhibitor. were observed in metastatic malignant melanoma characterised as PD-L1-low Materials and Methods – PD-L1 staining: FFPE baseline biopsies were assessed using the PD-L1 IHC 22C3 pharmDx antibody for Autostainer Link 48 (Agilent). Biopsies were considered evaluable if at least 100 viable tumor cells were present. PD-L1 was considered for partial or complete cell membrane staining of tumor cells that is perceived distinct from cytoplasmic staining. Cytoplasmic staining was considered non-specific and excluded. Samples were considered PD-L1 positive with a tumor proportion score (TPS) of ≥1%. The TPS was calculated according to the formula: TPS = (number of positive PD-L1 tumor cells/total number of viable tumor cells) x 100. Sample quality and positivity evaluation was performed by an experienced pathologist. Results and Discussion: Referring to Figure 3A, the objective responses of all patients in cohort 1 and 2 of the clinical trial are shown (as detailed in Example 1). Referring to Figure 3B, the objective 13399613-3 responses of patients with PD-L1-low tumors (i.e. having <1% PD-L1 positive tumor cells; n=14) are shown. Referring to Figure 3C, the objective responses of patients with non PD-L1-low tumors (i.e. having ≥1% PD-L1 positive tumor cells; n=8) are shown. In patients with PD-L1-low tumors, 8 clinical responses were observed out of 14 patients, corresponding to an objective response rate (according to the iRECIST criteria) of 57.1%. However, in patients with non PD-L1-low tumors, only 4 clinical responses were observed out of 8 patients, corresponding to an objective response rate (according to the iRECIST criteria) of 50.0%. Therefore, the objective response rate (i.e. those patients with a complete response and a partial response to treatment according to the iRECIST criteria) is higher in patients with tumor biopsies characterised as PD-L1-low. Example 4: Durable clinical responses were observed in metastatic malignant melanoma patients with tumor biopsies characterised as having few tumor infiltrating lymphocytes (TILs) Materials and Methods – TILs staining FFPE biopsies were used for multiplex immunofluorescence staining. For the TILs calculation, baseline biopsies from 15 patients were assessed. These results are shown in Table 3A. Subsequently, baseline biopsies from a further 9 patients were assessed. The complete data are shown in Table 3B. Biopsy Sections (4 µm thick) were stained using a custom-based 8-color IHC kit (Akoya Biosciences, Marlborough, MA, USA) and the fully automated Leica Bond RXm (Leica Biosystems, Buffalo Grove, IL, USA). The slides were deparaffinized, rehydrated, and rinsed with distilled H2O. Antigen retrieval and removal of antibodies from the previous cycles were performed by boiling at 95 °C at pH 9 (first cycle) or pH 6 (all remaining cycles). For multiplex immunofluorescence staining, a panel of immune markers was developed using antibodies against CD4 (rabbit/EPR6855, Abcam, 1:80) and CD8α (mouse/144B, Invitrogen/MA5-13,473, 1:100). A cocktail of two antibodies was used to identify the melanoma cells: anti-Sox10 (rabbit/EP268-1, Akoya, ready to use) and anti-S100 (mouse/4C4.9, Akoya, ready to use). Staining was developed using amplification HRP- polymer systems and Opal fluorophore dyes. To visualize the cell nuclei, the tissue was stained with 4′,6-diamidino-2-phenylindole (Spectral DAPI, Akoya). The slides were 13399613-3 mounted with Prolong Diamond Antifade Mountant (Thermo Fisher, Waltham, MA, USA) and imaged at × 20 magnification using the Vectra® Polaris™ Automated Quantitative Pathology Imaging System (Akoya Biosciences, Marlborough, MA, USA). Each image was manually reviewed and curated by a pathologist to exclude artifacts and staining defects. Results and Discussion The results of the TIL analysis are presented in Table 3A. Table 3A shows the data from 15 patients. Subsequent data were then collected from a further 9 patient baseline biopsies and the complete dataset from 24 patients is shown in Table 3B. Table 3A: CD8+ T-cell density (counts/mm ² ) in Responders (R) and Non-Responders R NR All Median 116,1248 51,1701 78,31741 M ⁱⁿ 16,15595 3,068537 3,068537 M ^ax 341,2032 326,7513 341,2032 Table 3B: Complete data of CD8+ T-cell density (counts/mm ² ) in responders and non- responders CD8+ cells Responders Non-Responders Counts/mm2 (iCR + iPR) (iSD+iCPD/UPD) 41,1 3,2 36,4 94,2 113,4 34,0 16,7 550,2 69,3 507,4 331,2 0,1 96,3 61,2 180,0 382,8 52,1 5,6 110,0 98,1 1264,1 802,3 170,6 301,8 Min 16,7 0 Max 1264,1 802,3 Median 110,0 94,2 13399613-3 A threshold of 850 counts/mm ² was applied to the data in Figure 3B. A threshold of 850 counts/mm ² is expected to be clinically relevant based on previous studies (e.g. Uryvaev A et al., 2018). This analysis is set out in Table 3C below. Therefore, low TIL was defined as ≤850 counts/mm ² and high TIL was defined as >850 counts/mm ² . Table 3C: Numbers of responders and non-responders having low or high TIL levels (based on a threshold of 850 counts/mm ² ) The ORR for the low TIL population was 52.2% (12/23 patients). The ORR for the sampled population was 54.2% (13/24 patients). There was no difference in baseline levels of CD8+ cells in clinical responders and non- responders (median 110.0 vs 94.2, Mann Whitney p-value 0.69) (Table 3B). The density of CD8+ T-cells in both responders and non-responders was considered low. Thus the level of this biomarker was similar between responders and non-responders. Based on previous studies of immune checkpoint inhibitor monotherapy, patients having a low density of CD8+ T-cells would be expected to have reduced responses to therapy. However, in this study durable clinical responses to the combination therapy were nevertheless observed in patients with baseline tumor biopsies that were characterised as having fewer (low) TILs. In particular, the data in Table 3C show that clinical responses were observed at a similar rate in patients with low baseline TIL levels as compared to the overall sampled population. This was unexpected as previous reports have indicated that higher CD8+ T-cell levels correlate with a clinical response to checkpoint inhibitor monotherapy. Thus, the addition of a vaccine comprising the cocktail of polypeptides of SEQ ID NOS.1, 2 and 3 to the checkpoint inhibition extended clinical efficacy to patients with tumors having low baseline TIL levels. 13399613-3 Example 5: IFN-γ gene signature data Materials and Methods: IFN-γ gene signature data was obtained as per the method set out in Ayers M. et al., J Clin Invest.2017 Aug 1;127(8):2930-2940 (incorporated herein by reference). Results and Discussion: The interferon-gamma signature is defined as the expression levels of a validated 18- gene list (as set out in Ayers M. et al.2017). Referring to Figure 4, the “row z-score” is shown whereby the RNA expression levels at baseline (TPM / transcripts per million) were normalized for each gene across patients who were administered the polypeptides of SEQ ID NOS.1, 2 and 3 in combination with pembrolizumab. The heatmap of Figure 4 shows whether these genes are expressed higher by some patients compared to others (and not absolute expression values). Patients with iCR or iPR were not found to be enriched for this signature, and that these genes were evenly expressed across the different response categories. Furthermore, referring to Figure 5, it was shown that RNA expression of hTERT was detected in in all except two biopsies (patients 004-0007 and 004-0010), and the baseline hTERT expression level was evenly distributed between the different response categories. Example 6: Anti-hTERT immune responses were detected in patients with metastatic malignant melanoma who were administered the polypeptides of SEQ ID NOS.1, 2 and 3 in combination with a PD-1/PD-L1 immune checkpoint inhibitor Materials and Methods The immune response specific to the vaccine comprising a cocktail of polypeptides having the sequences of SEQ ID NOS.1, 2 and 3 (the “UV1” vaccine) was measured in peripheral blood mononuclear cells (PBMCs) of the patients included in the clinical trial as described under Example 1. PBMCs were prepared from whole blood samples (BD Vacutainer CPT ^TM Cell Preparation tubes) and collected at baseline, four times during the UV1 vaccination period, and four times during the follow-up period (30 days and 3, 6, and 9 months after the last UV1 vaccination). At the start of the study (July 2018), centrifuged CPT vacutainers were shipped to a US central laboratory for isolation and cryopreservation. The procedure was changed in April 2020, after which the samples 13399613-3 were isolated and cryopreserved at each site before being shipped to the central laboratory for storage. All samples were sent to Norway for immune response analysis. The UV1-specific T-cell response was measured by proliferation assay ( ³ H-Thymidine incorporation) as previously described (e.g. Ellingsen EB et al., Journal for ImmunoTherapy of Cancer 10:e004345, 2022, incorporated herein by reference). Briefly, thawed PBMCs were stimulated with UV1 peptides (SEQ ID NO.2: peptide 725; hTERT 691-705 (RTFVLRVRAQDPPPE), SEQ ID NO.1: peptide 719-20; hTERT 660- 689 (ALFSVLNYERARRPGLLGASVLGLDDIHRA), SEQ ID NO.3: peptide 728; hTERT 651-665 (AERLTSRVKALFSVL) (Corden Pharma, Switzerland)) at a concentration of 10 µM for each peptide. On day three, IL-2 (20U/ml) and IL-7 (5ng/ml) were added. After 10-14 days, the T-cells were re-stimulated with peptide-loaded autologous irradiated antigen-presenting cells (APCs), and proliferation was determined by ³ H-Thymidine incorporation assay, with all conditions tested in triplicates. The stimulation index (SI), which is the ratio of the mean counts in wells with T-cells stimulated with or without UV1 peptides, was calculated. If the SI at any timepoint was ≥3 for any of the three UV1 peptides or a mix, the patient was considered an immune responder. Patients with a UV1-specific T-cell response at baseline (SI ≥ 3) required a doubling of the SI in at least one post-vaccination sample or an increase in the number of peptides recognized to be defined as vaccine responders. Staphylococcus aureus enterotoxin C3 (SEC3) was used as a positive control to determine immunocompetence. IR-evaluable samples had an SEC3 SI ≥10. Results Referring to Figures 9A and 9B, the detection of anti-hTERT immune responses in 10 patients is shown. The median highest stimulation index (SI) in immune responders was 6.8 (range: 3.3-46.0) and the median time to first immune response was 25.3 weeks (range: 7.6-53.6). Discussion Vaccine-induced immune responses were assessed using a standard proliferation assay. This assay requires high-quality peripheral blood mononuclear cells for 10-12 days of in vitro culture. Unfortunately, the quality of these samples was affected by processing at different US sites and trans-Atlantic shipping, before being assayed in Norway. While results from a phase I melanoma trial with UV1 in combination with 13399613-3 ipilimumab showed a median time to the first immune response of 4 weeks (Ellingsen EB et al., Journal for ImmunoTherapy of Cancer 10:e004345, 2022, incorporated herein by reference), immune responses detected in this example were first documented in samples from later time points. In particular, Ellingsen EB et al., 2022 reports a median time to a measurable immune response of 4, 5 and 10 weeks for trials of UV1 in combination with ipilimumab in malignant melanoma, non-small cell lung cancer and prostate cancer respectively and 6.5 weeks (range, 1–40) for all studies combined (Figure 1C of Ellingsen EB et al., 2022, incorporated herein by reference). The late appearance is likely due to the laboratory and shipment adjustments that were implemented during the study, which increased the quality of subsequent samples. of hTERT decreased in clinical and increased in clinical non- Materials and Methods The expression levels of hTERT (the target antigen) as well as the expression levels of genes related to T-cell function and activation, cytokine activity and immune checkpoint molecules were assessed at baseline and week 14 of treatment by sequencing tumor biopsy-derived RNA. Tumor biopsies, one formalin-fixed paraffin-embedded (FFPE) sample, and two snap- frozen samples were collected at baseline and at the end of UV1 treatment (corresponding to week 14 after the first administration of UV1). RNA was extracted from the snap-frozen biopsies (Novogene, Cambridge, United Kingdom). The RNA samples were processed using the TruSeq Stranded Total RNA Library Prep kit (Illumina) using 500 ng as starting material. RNA sequencing was performed using the NovaSeq 6000 instrument (Illumina). The percentage change in hTERT expression (TPM) was calculated by dividing the delta hTERT value (delta hTERT value = baseline hTERT level – measured hTERT level) by the baseline value. For statistical analysis on the change in hTERT expression, differentially expressed genes (DEGs) analysis were performed on kallisto abundance files imported by tximport and analyzed with Deseq2 (v1.38.1) and R (v4.2.2). The pairing of the samples (coming from the same patient) was included in the design formula. To improve fold change estimation, shrinkage was performed using apeglm method. 13399613-3 Results Referring to Figure 10, a relative increase in gene expression across the categories of genes relating to T cell function and activation, cytokine activity, and immune checkpoint molecules was observed in both clinical responders and clinical non-responders, indicating an impact of the combination therapy in nearly all patients, despite the apparent lack of objective responses in the clinical non-responders. Notably, the relative RNA expression of hTERT (Figure 10, “Target antigen”) decreased in clinical responders (Figure 10, see “Responders”) and increased in clinical non-responders (Figure 10, “Non-Responders”). The mean percentage change in hTERT expression (TPM) between baseline and week 14 of treatment was -28.4% (range: -100% to 372,8%) in the clinical responders. Among the clinical responders, it should be noted that there was only one patient with an increase in hTERT expression and this was from a 0.01 to 0.04 TPM. The mean percentage change in hTERT expression (TPM) between baseline and week 14 of treatment was 134.8% (range: 0% to 277.3%) in the clinical non-responders. Statistical analysis (as set out under the Material and Methods above) on the change in hTERT expression indicated that among the clinical responders, the log2(fold change) in hTERT expression was -0.11 (p-value <0.001). Among the clinical non-responders, the log2(fold change) in hTERT expression was 0.034 (p-value 0.113). Thus the relative decrease in hTERT expression in the clinical responders was highly significant. Conclusions A relative decrease in hTERT expression was observed in the clinical responders between baseline and week 14 of treatment whereas a relative increase in hTERT expression was observed in the clinical non-responders over the same time period. The relative decrease in hTERT expression in the clinical responders was found to be highly significant by statistical analysis. Example 8: Receiver operating characteristic (ROC) analysis on the difference in hTERT expression levels between baseline and week 14 of treatment among clinical responders and clinical non-responders 13399613-3 Background A ROC analysis can be used to determine the cut-off value that gives the optimal trade- off between clinical sensitivity and sensitivity of a given diagnostic/prognostic test. In addition, the area under a ROC curve (AUC) is a measure of the quality of a diagnostic/prognostic test. In relation to diagnostic/prognostic tests, sensitivity (the true positive rate) can be defined as the ability of a test to correctly identify patients with a disease, whereas specificity (the true negative rate) can be defined as the ability of a test to correctly identify people without the disease. An ideal test would be one with both high sensitivity (i.e. having a low false negative rate) and high specificity (i.e. having a low false positive rate). Methods A ROC analysis was run on the difference in hTERT mRNA expression levels between baseline and week 14 of treatment among clinical responders (n=7) and clinical non- responders (n=6). The analysis was performed using GraphPad Prism 9.4.1 software (San Diego, California, USA) and the Wilson/Brown method. The difference in hTERT mRNA expression levels between baseline and week 14 of treatment is also referred to as the “delta” value. Results Referring to Figure 11, the ROC analysis shows that the AUC was 0.9524 (95% CI, 0.84 to 1.00, p value 0.0066). An AUC higher than 0.9 is considered very good. Tables 4 and 5 show the different thresholds in the delta that can be set (i.e. as a cut-off value for a test) and the respective sensitivity and specificity levels. A delta of less than -0.1 (i.e. an absolute reduction in transcripts per million (TPM) of 0.1 or greater) provides a good tradeoff between sensitivity and specificity. That is to say, if the delta hTERT level (i.e. the difference between the hTERT mRNA expression level at baseline and week 14 of treatment) of a cancer patient was less than -0.1, this would indicate with high sensitivity and specificity that the cancer patient is likely to be a clinical responder. 13399613-3 Table 4: Delta thresholds and their respective sensitivity and specificity levels for values higher than each threshold 13399613-3 Table 5: Delta thresholds and their respective sensitivity and specificity levels for values lower than each threshold Conclusions The ROC analysis demonstrates the delta hTERT value (e.g. the difference between the hTERT level at baseline and week 14 of treatment) can be used to identify clinical responders and non-responders. In this example, the ROC analysis demonstrated that a threshold of -0.1 TPM identified clinical responders from clinical non-responders with high sensitivity and specificity. Example 9: ROC analysis of hTERT expression levels post-treatment Methods A ROC analysis was run on the hTERT mRNA expression level data from week 14 of treatment (raw transcripts per million (TPM) from the week 14 biopsies). The analysis was performed using GraphPad Prism 9.4.1 software (San Diego, California, USA) and 13399613-3 the Wilson/Brown method. A ROC curve was produced (Figure 12) and the different possible thresholds are set out in Tables 6 and 7. Results Referring to Figure 12, the ROC analysis shows that the AUC was 0.867 (95% CI, 0.62 – 1.0) with a p-value of 0.023. An AUC higher than 0.8 is considered good. Tables 6 and 7 show the different thresholds in the post-treatment values that can be set (i.e. as a cut-off for a test) and the respective sensitivity and specificity levels. A threshold of >0.33 TPM maintained a high specificity. That is to say, if the post-treatment level of hTERT of a cancer patient was greater than 0.33 TPM, this would be considered high and would indicate that the cancer patient is likely to be a clinical non-responder. Conversely, if the post-treatment level of hTERT of a cancer patient was less than 0.33 TPM, this would be considered low and would indicate that the cancer patient is likely to be a clinical responder. Table 6: Thresholds (TPM) and their respective sensitivity and specificity for predicting non-response 13399613-3 Table 7: Thresholds (TPM) and their respective sensitivity and specificity for predicting response Conclusions The ROC analysis demonstrates that a post-treatment hTERT level alone can be used to identify clinical responders and non-responders. In this example, the ROC analysis demonstrated that a threshold of 0.33 TPM identified clinical responders from clinical non-responders with high sensitivity and specificity. Example 10: hTERT levels at week 14 of treatment can predict whether a cancer patient will respond or progress at a future time point Background The data set from the clinical trial as described in Example 1 was analysed to assess how the biopsy time point at which the level of hTERT was measured (week 14 of treatment) corresponded to the time point of response or progression in clinical responders and clinical non-responders respectively. 13399613-3 Results Referring to Figure 13A, the percent change in tumor size from baseline for each patient is shown, together with whether the hTERT level at week 14 was above or below the threshold value of 0.33 TPM. Although most responses/progressions occurred around a similar time point as the biopsy harvesting (i.e. week 14 of treatment), certain patients experienced responses/progressions at later time points (see the continued lines after the stars on Figure 13A). The mean time from biopsy harvesting to partial or complete response was 38.1 days (range -8 to 110) in the clinical responders (n=7). The mean time from biopsy harvesting to progression was 58.1 days (range -9 to 188) in the clinical non-responders (n=7). Figure 13B further analyses a subset of patients exhibiting stable disease at week 14 of treatment and shows the percent change in tumor size from baseline for each of these patients, together with the hTERT level (TPM) measured at week 14. Notably, those patients who had an hTERT level above the threshold of 0.33 TPM at week 14 went on to develop progressive disease whereas those patients who had an hTERT level below the threshold of 0.33 TPM at week 14 went on the develop a partial response or a complete response. Thus although the patients all appeared to have stable disease at week 14 based on the percent change in tumor size, the hTERT level measured at this time point could predict whether the patient would respond or progress at a future time point. Conclusions This analysis demonstrates that, in certain patients, measuring the hTERT level at week 14 of treatment and comparing the level to a threshold value (in this example, 0.33 TPM) can predict whether the patient will respond or progress at a future time point. Example 11: Analysis of the relative RNA expression of various genes in clinical responders and clinical non-responders The relative change in RNA expression levels of hTERT (the target antigen) between baseline and week 14 of treatment in clinical responders and clinical non-responders was compared to other genes, including the tumor-associated antigen NY-ESO-1 (CTAG1B). Materials and Methods are as described in Example 7. EP3230498 reported that intratumoral RNA levels of CD276, CTAG1B, DSG2, EGFR, SLC2A1 and TSLP from 13399613-3 pre-treatment tumor samples negatively correlated with an anti-tumor response to a PD- 1 antagonist. Results Referring to Figure 14, the percentage change in RNA expression (TPM) between baseline and week 14 of treatment is shown for clinical responders and clinical non- responders for each gene analysed. Samples with 0 TPM at baseline but a detectable post-treatment level were uncalculable and marked with an “X” in Figure 14. Referring to Figure 15, the log2 (fold-change) in RNA expression (TPM) between baseline and week 14 of treatment is shown for clinical responders and clinical non-responders for each gene analysed. The log2(fold change) was uncalculable if the RNA expression unit (TPM) was zero in either the baseline or the post-treatment sample; such samples are marked with an “X” in Figure 15. As described in Example 7 above, the relative RNA expression of hTERT decreased in clinical responders and increased in clinical non- responders. However, no particular correlations were observed between the other genes analysed and a clinical response or a clinical non-response to treatment. Conclusions The relative decreased in hTERT expression in the clinical responders between baseline and week 14 of treatment and the relative increase in hTERT expression in the clinical non-responders over the same time period was not observed for other genes, including the tumor-associated antigen NY-ESO-1. This substantiates the relevance of evaluating hTERT levels to identify or predict the clinical outcome of a cancer patient who has received a vaccine targeting hTERT. 13399613-3

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