AUTOIMMUNE AND INFLAMMATORY DISEASES

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims benefit of U.S. Provisional Application No. 63/381 ,974, filed November 2, 2022, which is hereby incorporated herein by reference in its entirety.

BACKGROUND

Systemic lupus erythematosus (SLE) is a complex, heterogenous autoimmune disease that impacts millions of people worldwide. Treatment options are currently limited to immunosuppressive drugs and belimumab to control widespread inflammation and tissue damage. Patients with SLE exhibit an assortment of T cell dysfunctions including impaired mitochondrial function, reduced regulatory T cell (Treg) suppressive capacity, high metabolic activity, oxidative stress, and expansion of pathogenic Th1-like Th17 cells. Therefore, some goals for improved therapeutic options for lupus include restoring homeostasis to T cell subsets, restoring mitochondrial health, normalizing T cell metabolism, and boosting Treg function.

T cell subsets such as Thl , Th17 and Treg cells have unique metabolic phenotypes and requirements that offer metabolic targets to manipulate T cell populations. Given these opportunities, it is not surprising that metabolic targeting has been applied to T cells in the setting of SLE. Simultaneous inhibition of glycolysis and mitochondrial function reduced T cell-mediated inflammation in two mouse models of lupus. These approaches, however, may be overly broad and have failed to rescue both mitochondrial dysfunction and T cell subset homeostasis.

SUMMARY

As disclosed herein, micronutrients such as iron can regulate both cellular metabolism and mitochondrial reactive oxygen species (ROS) and may offer targeted opportunities for metabolic immunotherapy. Although iron is required for many cellular functions, too much unbound (labile) iron, can induce cellular damage via oxidative stress, mitochondrial damage, and ferroptosis. The transferrin receptor, CD71 , is the primary iron receptor for immune cells and binds to transferrin (Tf)-bound iron to facilitate iron internalization. Iron flux and CD71 expression are particularly important for T cell activation. Missense mutations in the gene for CD71 , TFRC, result in combined immunodeficiency (CID) with defective T cell proliferation. Low serum iron levels can also impede the primary CD8 T cell response to vaccinations. Low iron decreased mitochondrial polarization and mTORCI signaling, highlighting the link between iron flux, mitochondrial function, and metabolic programming in T cells. Importantly, regulation of iron metabolism also appears to differ among T cell subsets as Th1 cells are reported to be more sensitive to iron depletion than Th2 cells.

Around 50% of SLE patients are considered anemic with approximately 35% of anemic patients having iron deficiency anemia (IDA). Despite this, a clinical study found that CD4 T cells isolated from patients contained higher intracellular iron levels than controls, and dietary iron may aggravate lupus symptoms in patients. In lupus-prone mice, administration of hepcidin to lower serum iron levels reduced renal iron accumulation and pro-inflammatory cytokine production from macrophages while also reducing CD4 T cell infiltration to the kidney. Increased iron levels may therefore contribute to oxidative stress and mitochondrial dysfunction in lupus T cells. As disclosed herein, lupus-prone mice and SLE patient T cells have elevated CD71 and that targeting this iron receptor can normalize T cell function to reduce Th1 cells while promoting Treg and reducing autoimmune pathology.

Therefore, disclosed herein is a method for treating an autoimmune and/or inflammatory disease in a subject that involves administering to the subject a therapeutically effective amount of a composition comprising an antibody that inhibits binding of CD71 (transferrin receptor) to transferrin-bound iron, either directly or by stimulating internalization of the receptor, or an antigen-binding fragment thereof to ultimately reduce iron influx.

Also disclosed are bispecific antibodies that bind CD71 and at least one T cell antigen, such as CD3, CD4, or CD8.

Also disclosed is a method for increasing Treg function and proliferation in a subject that involves administering to the subject a therapeutically effective amount of a composition comprising an antibody that inhibits binding of CD71 (transferrin receptor) to transferrin-bound iron, or an antigen-binding fragment thereof. Increasing Treg function may also include primary immunodeficiencies such as immune dysregulation, polyendocrinopathy, enteropathy, X-linked (IPEX) syndrome or other immunological disorders characterized by a loss of Treg function.

Also disclosed is a method that involves assaying a sample from a subject for CD71 expression on Th 17 cells, detecting elevated CD71 expression on T cells, and administering to the subject a therapeutically effective amount of a composition comprising an antibody that inhibits binding of CD71 (transferrin receptor) to transferrin- bound iron, or an antigen-binding fragment thereof.

Also disclosed is a method that involves assaying a sample from a subject for Th17 and Treg populations, detecting a low Th17/Treg ratio, and administering to the subject a therapeutically effective amount of a composition comprising an antibody that inhibits binding of CD71 (transferrin receptor) to transferrin-bound iron, or an antigenbinding fragment thereof.

In some embodiments, the subject has an autoimmune or inflammatory disease. For example, the autoimmune disease can be but is not limited to Systemic Lupus Erythematosus (SLE). In some embodiments, the inflammatory disease comprises multiple sclerosis (MS), rheumatoid arthritis (RA), irritable bowel disease (IBD), type 1 diabetes, or graft-versus-host-disease (GvHD). In some embodiments, the subject is the recipient of an organ transplantation.

The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIGs. 1A to

FIGs. 1 A tp 11 show transferrin receptor is conditionally essential for effector T cells and iTregs. FIG. 1A shows Naive CD4 T cells from Cas9-transgenic mice were stimulated and skewed into T _H 1 (left) or iT _reg (right) cells. Cells were transduced with a retroviral library of gRNAs specific for genes in iron metabolism or nontargeting controls. MAGeCK analysis was used to determine gRNA depletion and enrichment in T cell cultures over 7 days. Results are representative of two independent screens. FIG. 1 B shows CD71 expression at 5 days after differentiation of activated TH1 and iT _reg cultures. FIG. 1C shows intracellular ferrous iron in TH1 cells and iT _reg s measured by BioTracker iron staining. FIG. 1 D shows CD71 expression at 72 hours and 6 days after activation with a representative plot (left). FIG. 1 E shows T cell pellets from 72 hours after activation were subjected to ICP-MS to determine total (2+ and 3+) intracellular iron concentrations. “Unstim” represents T cells that were left unstimulated, and “Media” is a control for iron content in the cell culture medium only, ppb, parts per billion. FIG. 1 F shows Tfrc mRNAwas quantified in activated T cells by qRT-PCR. FIG. 1G shows Irp2 protein levels were quantified by immunoblot in activated CD4 T cells and normalized to the actin loading control. FIG. 1 H shows whole-cell lysates from ex vivo purified CD4 T cells were examined for Hfe expression by immunoblot. FIG. 11 shows activated CD4 T cells from control or SLE1 .2.3 mice were treated with transferrin protein for 0, 10 min, 30 min, or 2 hours to stimulate CD71 endosomal trafficking. Confocal microscopy was used to quantify the percentage of cells that contained CD71+ recycling endosomes by Rab8 colocalization with CD71 (right). Each data point is from an individual biological replicate where data from three technical replicates were averaged. Representative images from *20 magnification at the 2-hour time point are shown. Scale bars, 50 pm. (B to H) Student’s unpaired two-tailed t test. (I) Two-way ANOVA. ns, not significant.

FIGs. 2A to 2I show CD71 blockade normalizes T cell activation and mTORCI in SLE1.2.3 T cells. FIG. 2A shows CD69 expression was determined by flow cytometry 24 hours after activation in T cell cultures. FIG. 2B shows CD44 expression determined by flow cytometry 72 hours after activation. FIG. 2C shows T cell cultures restimulated on day 5 after activation with PMA/ionomycin to quantify the percentage of IL-2+ CD4 T cells. FIG. 2D shows IL-2 mRNA was quantified on day 4 of activation by qRT-PCR. FIG. 2E shows cell culture supernatants collected on day 4 of activation, and IL-2 concentrations were determined by ELISA. Values were then normalized to viable cell counts. FIG. 2F shows T cell cultures on day 5 of stimulation were analyzed by intracellular flow cytometry for p-S6. Results are from two independent experiments. FIG. 2G shows forward scatter (FSC) and side scatter (SSC) were measured in T cell cultures. FIG. 2H shows CD4 T cells activated for 24 hours and then treated with antibodies or nM rapamycin (rapa) for 2 days. IL-7 cells were left unstimulated as a control group. CD71 was measured by flow cytometry, and (I) CellTrace Violet (CTV) staining was used to calculate the division index. FIGs. 2A, 2B, and 2D to 2I - one-way ANOVA with Sidak’s multiple comparisons test. FIG. 2C - Paired ANOVA with Sidak’s multiple comparisons test. Results are from three experiments combined.

FIGs. 3A to 3H show CD71 blockade restores metabolic and mitochondrial function in SLE1 .2.3 T cells. FIGs. 3A and 3B show MitoTracker Green (FIG. 3A) and MitoSOX Red (FIG. 3B) staining measured by flow cytometry on day 5 after activation. FIG. 3C shows T cell cultures were processed for EM. A minimum of 100 mitochondria were analyzed in each sample group to quantify mitochondrial area (right). Scale bars, 1 pm (at 2700x) and 400 nm (at 6500x). FIG. 3D shows extracellular flux analysis on day 5 after activation. Representative oxygen consumption rate (OCR) during a Mito Stress Test is shown. Cells were treated with dimethyl sulfoxide (DMSO) or CPX for 4 hours. FIG. 3E shows representative Mito Stress Test for T cells activated with isotype control or anti-CD71. Maximal respiration (FIG. 3F) and proton leak (FIG. 3G) were quantified from Mito Stress Test (FIG. 3E). R/A, rotenone and antimycin A. FIG. 3H shows an ATP rate assay was performed with CD4 T cells as activated in FIG. 3E to quantify mitochondrial (left) versus glycolytic (right) ATP production. FIGs. 3A, 3B, and 3E to 3H - One-way ANOVA with Sidak’s multiple comparisons test. FIGs. 3C and 3D - Paired ANOVA.

FIGs. 4A to 4I show CD71 blockade differentially affects T cell subsets. FIG. 4A shows RNA sequencing results of TH17 differentiated cultures from either healthy control or SLE1.2.3 mice. IL-17 signaling and TH17 differentiation gene expression is shown in a heatmap by Iog2 fold change (Log2FC). Data are normalized to controls. FIG. 4B shows iron metabolism genes in TH17 cultures from control or SLE1 .2.3 samples. P values on plots are the adjusted P values determined by DESeq2 analysis. FIG. 4C shows CD71 expression on day 3 of activation in TH 17 cells or iTregs treated with isotype control, anti-CD71 , CPX, or iron supplementation. FIG. 4D shows iTreg and TH1 cultures ± CD71 blockade analyzed for Foxp3 expression on day 5 after activation. FIG. 4E shows iTreg cultures analyzed for IL-2 production by flow cytometry. FIG. 4F shows Naive T cells subjected to iTreg differentiation for 3 days. Supernatants were analyzed for IL-10 by ELISA and normalized to cell number. FIG. 4G shows Naive CD4 T cells isolated from SLE1.2.3 and control mice. Day 4 cells were restimulated as in FIG. 4C to determine the percentage of IL-10+ T cells. FIG. 4H shows c-MAF expression in Foxp3+ iTregs. FIG. 4I shows Naive T cells from Cas9 transgenic mice were differentiated into iTreg cultures for 2 days and transduced with a gRNA targeting Tfrc or a nontargeting control (NTC). Transduced cells (Thy1.1 +) were analyzed for Foxp3 expression (left) and p-S6 (right) by flow cytometry 5 days later. FIGs. 4C, 4D, and 4H - Two-way ANOVA with Dunnett’s multiple comparisons test. FIG. 4G - One-way ANOVA with Sidak’s multiple comparisons test. FIG. 4I - Paired ANOVA. FIG. 4E and 4F - Paired Student’s t test. FIG. 4I - Unpaired two-tailed Student’s t test. FPKM, fragments per kilobase of transcript per million mapped fragments.

FIGs. 5A to 5K show CD71 blockade reduces autoimmunity and pathology in SLE1.2.3 mice. FIG. 5A shows SLE1.2.3 mice or age-matched B6 controls were treated twice per week with an isotype control or anti-CD71 for 4 weeks, n = 4. FIG. 5B shows anti-dsDNA antibodies were measured in serum before the treatment regimen. The dotted line represents the cutoff value for inclusion criteria. FIG. 5C shows end point serum levels of anti-dsDNA Ig antibodies. FIG. 5D shows splenomegaly measured by spleen-to-body mass ratio at study end point. FIG. 5E shows CD4 T cells isolated from the spleen and LNs by negative selection, and cell counts were determined by automated cell counter. FIG. 5F shows CD4 T cells as described in FIG. 5E were stained for CD44 and examined by flow cytometry. FIGs. 5G and 5H show pathological assessment of inflammation in the kidney (FIG. 5G) and liver (FIG. 5H) scored semi- quantitatively from H&E-stained tissue sections. Arrows indicate infiltrates of lymphocytes and plasma cells. Scale bars, 200 pm (large) and 20 pm (insets). FIG. 51 shows end point sera measured for IL-10 concentrations. Assay limit of detection was 0.000531 . FIG. 5J shows CD4 T cells from spleens and LNs stimulated with PMA/ionomycin. IL-10+ CD4 T cells were quantified by flow cytometry. (K) The percentage of CD25+ Foxp3+ cells within total CD4 T cells was determined by flow cytometry at the study end point. All experiments were n = 3. One-way ANOVA with Sidak’s multiple comparisons test was used to determine significance of all plots.

FIGs. 6A to 6K show CD71 expression on T cells is required to drive SLE. Splenocytes fromCD4“Cre“ Tfrc ^fl/fl or Cre ⁺ Tfrcfl ! mice were transferred into bm12 recipient mice to induce SLE. Sham mice received a control PBS injection with no cells. FIG. 6A shows sera from days 3, 8, and 14 after transfer measured for anti-dsDNA IgG antibodies. Cre“ recipients, Cre ⁺ recipients; sham recipients. FIG. 6B shows TFH cell frequency as a percentage of total CD4 T cells in peripheral blood and GO B cell frequency as a percentage of CD19+ B cells in peripheral blood. FIG. 6C shows spleen weights measured on day 14 study end point. FIG. 6D shows day 14 splenocytes analyzed for GO B cell frequency and plasma cell frequency as a percentage of CD19+ B cells. FIG. 6E shows mean fluorescence intensity (MFI) of CD71 on CD4 T cells in the spleen. FIG. 6F shows frequency of TFH cells in the spleen and IGOS expression on all CD4 T cells in the spleen. FIG. 6G shows CD44 expression MFI on CD4 T cells in the spleen and MITOTRACKER Green staining. FIG. 6H shows CD71 MFI on CD4 T cells from the LNs. FIG. 6I shows TFH frequency and IGOS expression within CD4 T cells from the LN. FIG. 6J shows BIOTRACKER (2+) labile iron dye staining in CD4 T cells. FIG. 6K shows lymphocytes were isolated from the kidneys on day 14. Percentage of lymphocyte layer that were CD4 T cells (left) and CD71 expression on CD4 T cells (right). FIG. 6A - two-tailed Student’s t test. FIGs. 6B to 6K- Oneway ANOVA with Sidak’s multiple comparisons test.

FIGs. 7A to 7J show CD71 expression correlates with cells in patients with SLE. FIG. 7A shows Naive human T cells activated for 5 days under non-differentiating conditions (T _H 0) or TH17 conditions. Fe measured by ICP-MS and normalized to sulfur (S) for protein content. Paired Student’s t test. FIG. 7B shows PBMCs isolated from healthy donors (Control) and patients with SLE (SLE). Percentage of T _H 17 cells in CD4 T cell compartment compared with CD71 expression on bulk CD4 T cells. Controls, black; SLE. Pearson correlation was used to determine r value and statistical significance. FIG. 7C shows CD71 expression on bulk CD4 T cells. FIG. 7D shows percentage of CD4 T cells defined as T _H 17 cells. FIG. 7E shows CD71 expression on TH17 cells. FIGs. 7F to 7H shows flow cytometry data from patients with SLEDAI scores of 3 or less compared with those with scores of 4 or higher. FIG. 7I shows maximal respiration determined from MITOSTRESS Test assay on days 4 to 5 after activation. FIG. 7J shows IL-10 concentrations in day 3 supernatants measured by ELISA. FIG. 7C to 7H - Student’s two-tailed t test. FIG. 7I and 7J - Paired Student’s t test.

FIGs. 8A to 8C show iron metabolism is dysregulated in patients with SLE. FIGs. 8A and 8B show two published RNA-sequencing datasets examined for gene expression in a subset of iron metabolism genes from patient PBMCs (FIG. 7A) or CD4 T cells (FIG. 7B). FPKM= fragment per kilobase pair per million. FIG. 7C shows circulating HFE was measured in serum from patients with SLE or sex-matched healthy controls by ELISA. P values were determined by student’s t-test, two-tailed.

FIG. 9 shows SLE1 .2.3 T cells have altered T cell activation. Naive T cells were isolated from SLE1.2.3 mice or age matched healthy control and stimulated with splenocytes + anti-CD3. Activation markers CD69, CD25, CD44, and CD62L were measured by flow cytometry at 24h and 72h post-activation. Significance was determined by student’s two-tailed t-test, representative of 3 independent experiments.

FIGs. 10A to 10C show anti-CD71 treatment causes transferrin receptor internalization and lowered intracellular iron. FIG. 10A shows Naive T cells activated in the presence of an isotype control antibody or CD71 blocking antibody. Surface CD71 expression was measured by flow cytometry at 24h post-activation. FIG. 10B show T cells activated for 24h and then treated with isotype control or anti-CD71 antibody for one hour. All cells were fixed, then fixed cells were either permeabilized ‘Perm’ or not permeabilized ‘Fix’ before adding secondary antibody conjugated to AlexaFluor488 (AF488). FIG. 10C shows labile iron in T cell cultures activated as in FIG. 10A was measured with BioTracker Red dye at 72h post-activation, representative plot shown (right). Similar results were obtained in 3 independent experiments.

FIGs. 11A to 11h show CD71 blockade causes death in Th1 cells and inhibits Th17 cell differentiation. FIG. 11A shows cell death measured by AnnexinV and propidium iodide (PI) staining in flow cytometry. A representative plot of Th1 cells is shown (left). FIG. 11 B shows T cell cultures as in FIG. 11 A analyzed for phosphorylated H2AX as an indicator of DNA damage. FIGs. 11C and 11 D show Th 17 cultures restimulated with PMA/ionomycin on day 5 to determine the percentage of IL-17a+ cells (FIG. 11C) or lL-2+ cells (FIG. 11 D) with flow cytometry. FIG. 11 E show naive CD4 T cells from SLE1.2.3 mice or B6 controls treated with either anti-CD71 or CPX. IL-17+ cells determined as in FIG. 110. FIG. 11 F shows T cells from control mice activated in the presence of different cytokine conditions or left unstimulated + IL-7 as a control. The percentage of CD71+ cells (left) and CD71 intensity (right) was quantified on days 1 , 3, and 5 post-activation by flow cytometry. FIG. 11G shows T cell cultures as described in FIG. 11 F analyzed for percentages of CD25+ cells (left) and the intensity of CD25 (right). FIG. 11 H shows samples as in FIGs. 11 F, 11 G plotted based on their relative CD71 and CD25 geometric MFI (gMFI) values. FIGs. 11 A, 11 B, 11 E - One-way ANOVA with Sidak’s multiple comparisons test (c,d) Student’s two-tailed t-test.

FIGs. 12A to 111 show in vivo CD71-blockade in SLE1.2.3 mice. FIGs. 12A and 12B show endpoint serum analyzed for anti-nuclear antibodies (ANA), and anti-histone IgG antibodies (FIG. 12B). FIG. 12C show percentages of B cells within splenocyte population were quantified by double positive CD19 and B220. (N=3 experiments) FIGs. 12D to 12F show complete blood count (CBC) results for hemoglobin (FIG. 12D), hematocrit (HOT) (FIG. 12E), and red blood cell (RBC) (FIG. 12F) counts. Normal ranges from B6 mice are indicated by the dotted lines. FIG. 12G shows endpoint CD4 T cells subjected to flow cytometry to determine CD69 expression. FIGs. 12HI and 121 show spleens and lymph nodes examined for T follicular regulatory (Tfr) (FIG. 12H) and T follicular helper (Tfh) cell frequencies (FIG. 121) at the study endpoint. All statistical tests were one-way ANOVA with Sidak’s multiple comparisons test.

FIGs. 13A to 13E show supporting SLE patient data. FIG. 13A shows gating strategy for PBMC flow cytometry experiments, showing identification of Th 17 subset. FIG. 13B show CD69 and CD44 expression on bulk CD4 T cells from PBMC samples. Student’s t-test. FIG. 13C shows SLE patient CD71 expression on CD4 T cells compared to hemoglobin levels. FIG. 13D shows Biotracker Red labile iron staining on day 3 post-activation. One-way ANOVA with Sidak’s multiple comparisons test. FIG. 13E shows representative activation marker staining on day 3 post-activation +/- CD71 blockade. Similar results were obtained in at least 6 independent experiments.

DETAILED DESCRIPTION

Before the present disclosure is described in greater detail, it is to be understood that this disclosure is not limited to particular embodiments described, and as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be limited only by the appended claims.

Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the disclosure. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges and are also encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present disclosure, the preferred methods and materials are now described.

All publications and patents cited in this specification are herein incorporated by reference as if each individual publication or patent were specifically and individually indicated to be incorporated by reference and are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited. The citation of any publication is for its disclosure prior to the filing date and should not be construed as an admission that the present disclosure is not entitled to antedate such publication by virtue of prior disclosure. Further, the dates of publication provided could be different from the actual publication dates that may need to be independently confirmed. As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present disclosure. Any recited method can be carried out in the order of events recited or in any other order that is logically possible.

Embodiments of the present disclosure will employ, unless otherwise indicated, techniques of chemistry, biology, and the like, which are within the skill of the art.

The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to perform the methods and use the probes disclosed and claimed herein. Efforts have been made to ensure accuracy with respect to numbers (e.g., amounts, temperature, etc.), but some errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, temperature is in °C, and pressure is at or near atmospheric. Standard temperature and pressure are defined as 20 °C and 1 atmosphere.

Before the embodiments of the present disclosure are described in detail, it is to be understood that, unless otherwise indicated, the present disclosure is not limited to particular materials, reagents, reaction materials, manufacturing processes, or the like, as such can vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only, and is not intended to be limiting. It is also possible in the present disclosure that steps can be executed in different sequence where this is logically possible.

It must be noted that, as used in the specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.

The term “amino acid sequence” refers to a list of abbreviations, letters, characters or words representing amino acid residues. The amino acid abbreviations used herein are conventional one letter codes for the amino acids and are expressed as follows: A, alanine; B, asparagine or aspartic acid; C, cysteine; D aspartic acid; E, glutamate, glutamic acid; F, phenylalanine; G, glycine; H histidine; I isoleucine; K, lysine; L, leucine; M, methionine; N, asparagine; P, proline; Q, glutamine; R, arginine; S, serine; T, threonine; V, valine; W, tryptophan; Y, tyrosine; Z, glutamine or glutamic acid.

The term “antibody” refers to an immunoglobulin, derivatives thereof which maintain specific binding ability, and proteins having a binding domain which is homologous or largely homologous to an immunoglobulin binding domain. These proteins may be derived from natural sources, or partly or wholly synthetically produced. An antibody may be monoclonal or polyclonal. The antibody may be a member of any immunoglobulin class from any species, including any of the human classes: IgG, IgM , IgA, IgD, and I g E. In exemplary embodiments, antibodies used with the methods and compositions described herein are derivatives of the IgG class. In addition to intact immunoglobulin molecules, also included in the term “antibodies” are fragments or polymers of those immunoglobulin molecules, and human or humanized versions of immunoglobulin molecules that selectively bind the target antigen.

The term “antibody fragment” refers to any derivative of an antibody which is less than full-length. In exemplary embodiments, the antibody fragment retains at least a significant portion of the full-length antibody's specific binding ability. Examples of antibody fragments include, but are not limited to, Fab, Fab', F(ab')2, scFv, Fv, dsFv diabody, Fc, and Fd fragments. The antibody fragment may be produced by any means. For instance, the antibody fragment may be enzymatically or chemically produced by fragmentation of an intact antibody, it may be recombinantly produced from a gene encoding the partial antibody sequence, or it may be wholly or partially synthetically produced. The antibody fragment may optionally be a single chain antibody fragment. Alternatively, the fragment may comprise multiple chains which are linked together, for instance, by disulfide linkages. The fragment may also optionally be a multimolecular complex. A functional antibody fragment will typically comprise at least about 50 amino acids and more typically will comprise at least about 200 amino acids.

The term “antigen binding site” refers to a region of an antibody that specifically binds an epitope on an antigen.

The term “carrier” means a compound, composition, substance, or structure that, when in combination with a compound or composition, aids or facilitates preparation, storage, administration, delivery, effectiveness, selectivity, or any other feature of the compound or composition for its intended use or purpose. For example, a carrier can be selected to minimize any degradation of the active ingredient and to minimize any adverse side effects in the subject.

The term “chimeric molecule” refers to a single molecule created by joining two or more molecules that exist separately in their native state. The single, chimeric molecule has the desired functionality of all of its constituent molecules. One type of chimeric molecules is a fusion protein. The term “engineered antibody” refers to a recombinant molecule that comprises at least an antibody fragment comprising an antigen binding site derived from the variable domain of the heavy chain and/or light chain of an antibody and may optionally comprise the entire or part of the variable and/or constant domains of an antibody from any of the Ig classes (for example IgA, IgD, IgE, IgG, IgM and IgY).

The term “epitope” refers to the region of an antigen to which an antibody binds preferentially and specifically. A monoclonal antibody binds preferentially to a single specific epitope of a molecule that can be molecularly defined. In the present invention, multiple epitopes can be recognized by a multispecific antibody such as a bi-specific antibody that specifically bind CD71 on T cells.

The term “fusion protein” refers to a polypeptide formed by the joining of two or more polypeptides through a peptide bond formed between the amino terminus of one polypeptide and the carboxyl terminus of another polypeptide. The fusion protein can be formed by the chemical coupling of the constituent polypeptides or it can be expressed as a single polypeptide from nucleic acid sequence encoding the single contiguous fusion protein. A single chain fusion protein is a fusion protein having a single contiguous polypeptide backbone. Fusion proteins can be prepared using conventional techniques in molecular biology to join the two genes in frame into a single nucleic acid, and then expressing the nucleic acid in an appropriate host cell under conditions in which the fusion protein is produced.

The term “Fab fragment” refers to a fragment of an antibody comprising an antigen-binding site generated by cleavage of the antibody with the enzyme papain, which cuts at the hinge region N-terminally to the inter-H-chain disulfide bond and generates two Fab fragments from one antibody molecule.

The term “F(ab')2 fragment” refers to a fragment of an antibody containing two antigen-binding sites, generated by cleavage of the antibody molecule with the enzyme pepsin which cuts at the hinge region C-terminally to the inter-H-chain disulfide bond.

The term “Fc fragment” refers to the fragment of an antibody comprising the constant domain of its heavy chain.

The term “Fv fragment” refers to the fragment of an antibody comprising the variable domains of its heavy chain and light chain.

“Gene construct” refers to a nucleic acid, such as a vector, plasmid, viral genome or the like which includes a “coding sequence” for a polypeptide or which is otherwise transcribable to a biologically active RNA (e.g., antisense, decoy, ribozyme, etc), may be transfected into cells, e.g. in certain embodiments mammalian cells, and may cause expression of the coding sequence in cells transfected with the construct. The gene construct may include one or more regulatory elements operably linked to the coding sequence, as well as intronic sequences, polyadenylation sites, origins of replication, marker genes, etc.

The term “identity” refers to sequence identity between two nucleic acid molecules or polypeptides. Identity can be determined by comparing a position in each sequence which may be aligned for purposes of comparison. When a position in the compared sequence is occupied by the same base, then the molecules are identical at that position. A degree of similarity or identity between nucleic acid or amino acid sequences is a function of the number of identical or matching nucleotides at positions shared by the nucleic acid sequences. Various alignment algorithms and/or programs may be used to calculate the identity between two sequences, including FASTA, or BLAST which are available as a part of the GCG sequence analysis package (University of Wisconsin, Madison, Wis.), and can be used with, e.g., default setting. For example, polypeptides having at least 70%, 85%, 90%, 95%, 98% or 99% identity to specific polypeptides described herein and preferably exhibiting substantially the same functions, as well as polynucleotide encoding such polypeptides, are contemplated. Unless otherwise indicated a similarity score will be based on use of BLOSUM62. When BLASTP is used, the percent similarity is based on the BLASTP positives score and the percent sequence identity is based on the BLASTP identities score. BLASTP “Identities” shows the number and fraction of total residues in the high scoring sequence pairs which are identical; and BLASTP “Positives” shows the number and fraction of residues for which the alignment scores have positive values and which are similar to each other. Amino acid sequences having these degrees of identity or similarity or any intermediate degree of identity of similarity to the amino acid sequences disclosed herein are contemplated and encompassed by this disclosure. The polynucleotide sequences of similar polypeptides are deduced using the genetic code and may be obtained by conventional means, in particular by reverse translating its amino acid sequence using the genetic code.

The term “linker” is art-recognized and refers to a molecule or group of molecules connecting two compounds, such as two polypeptides. The linker may be comprised of a single linking molecule or may comprise a linking molecule and a spacer molecule, intended to separate the linking molecule and a compound by a specific distance. The term “nucleic acid” refers to a natural or synthetic molecule comprising a single nucleotide or two or more nucleotides linked by a phosphate group at the 3’ position of one nucleotide to the 5’ end of another nucleotide. The nucleic acid is not limited by length, and thus the nucleic acid can include deoxyribonucleic acid (DNA) or ribonucleic acid (RNA).

The term “operably linked to” refers to the functional relationship of a nucleic acid with another nucleic acid sequence. Promoters, enhancers, transcriptional and translational stop sites, and other signal sequences are examples of nucleic acid sequences operably linked to other sequences. For example, operable linkage of DNA to a transcriptional control element refers to the physical and functional relationship between the DNA and promoter such that the transcription of such DNA is initiated from the promoter by an RNA polymerase that specifically recognizes, binds to and transcribes the DNA.

The terms “peptide,” “protein,” and “polypeptide” are used interchangeably to refer to a natural or synthetic molecule comprising two or more amino acids linked by the carboxyl group of one amino acid to the alpha amino group of another.

The term “pharmaceutically acceptable” refers to those compounds, materials, compositions, and/or dosage forms which are, within the scope of sound medical judgment, suitable for use in contact with the tissues of human beings and animals without excessive toxicity, irritation, allergic response, or other problems or complications commensurate with a reasonable benefit/risk ratio.

The terms “polypeptide fragment” or “fragment”, when used in reference to a particular polypeptide, refers to a polypeptide in which amino acid residues are deleted as compared to the reference polypeptide itself, but where the remaining amino acid sequence is usually identical to that of the reference polypeptide. Such deletions may occur at the amino-terminus or carboxy-terminus of the reference polypeptide, or alternatively both. Fragments typically are at least about 5, 6, 8 or 10 amino acids long, at least about 14 amino acids long, at least about 20, 30, 40 or 50 amino acids long, at least about 75 amino acids long, or at least about 100, 150, 200, 300, 500 or more amino acids long. A fragment can retain one or more of the biological activities of the reference polypeptide. In various embodiments, a fragment may comprise an enzymatic activity and/or an interaction site of the reference polypeptide. In another embodiment, a fragment may have immunogenic properties. The term “protein domain” refers to a portion of a protein, portions of a protein, or an entire protein showing structural integrity; this determination may be based on amino acid composition of a portion of a protein, portions of a protein, or the entire protein.

The term “single chain variable fragment or scFv” refers to an Fv fragment in which the heavy chain domain and the light chain domain are linked. One or more scFv fragments may be linked to other antibody fragments (such as the constant domain of a heavy chain or a light chain) to form antibody constructs having one or more antigen recognition sites.

A “spacer” as used herein refers to a peptide that joins the proteins comprising a fusion protein. Generally a spacer has no specific biological activity other than to join the proteins or to preserve some minimum distance or other spatial relationship between them. However, the constituent amino acids of a spacer may be selected to influence some property of the molecule such as the folding, net charge, or hydrophobicity of the molecule.

The term “specifically binds”, as used herein, when referring to a polypeptide (including antibodies) or receptor, refers to a binding reaction which is determinative of the presence of the protein or polypeptide or receptor in a heterogeneous population of proteins and other biologies. Thus, under designated conditions (e.g. immunoassay conditions in the case of an antibody), a specified ligand or antibody “specifically binds” to its particular “target” (e.g. an antibody specifically binds to an endothelial antigen) when it does not bind in a significant amount to other proteins present in the sample or to other proteins to which the ligand or antibody may come in contact in an organism. Generally, a first molecule that “specifically binds” a second molecule has an affinity constant (Ka) greater than about 10 ⁵ M ^-1 (e.g., 10 ⁶ M ^-1 , 10 ⁷ M ^-1 , 10 ⁸ M ^-1 , 10 ⁹ M ^-1 , 1O ¹⁰ M ^-1 , 10 ¹¹ M ^-1 , and 10 ¹² M ^-1 or more) with that second molecule.

The term “specifically deliver” as used herein refers to the preferential association of a molecule with a cell or tissue bearing a particular target molecule or marker and not to cells or tissues lacking that target molecule. It is, of course, recognized that a certain degree of non-specific interaction may occur between a molecule and a non- target cell or tissue. Nevertheless, specific delivery, may be distinguished as mediated through specific recognition of the target molecule. Typically specific delivery results in a much stronger association between the delivered molecule and cells bearing the target molecule than between the delivered molecule and cells lacking the target molecule. The term “subject” refers to any individual who is the target of administration or treatment. The subject can be a vertebrate, for example, a mammal. Thus, the subject can be a human or veterinary patient. The term “patient” refers to a subject under the treatment of a clinician, e.g., physician.

The term “therapeutically effective” refers to the amount of the composition used is of sufficient quantity to ameliorate one or more causes or symptoms of a disease or disorder. Such amelioration only requires a reduction or alteration, not necessarily elimination.

The terms “transformation” and “transfection” mean the introduction of a nucleic acid, e.g., an expression vector, into a recipient cell including introduction of a nucleic acid to the chromosomal DNA of said cell.

The term “treatment” refers to the medical management of a patient with the intent to cure, ameliorate, stabilize, or prevent a disease, pathological condition, or disorder. This term includes active treatment, that is, treatment directed specifically toward the improvement of a disease, pathological condition, or disorder, and also includes causal treatment, that is, treatment directed toward removal of the cause of the associated disease, pathological condition, or disorder. In addition, this term includes palliative treatment, that is, treatment designed for the relief of symptoms rather than the curing of the disease, pathological condition, or disorder; preventative treatment, that is, treatment directed to minimizing or partially or completely inhibiting the development of the associated disease, pathological condition, or disorder; and supportive treatment, that is, treatment employed to supplement another specific therapy directed toward the improvement of the associated disease, pathological condition, or disorder.

The term “variant” refers to an amino acid or peptide sequence having conservative amino acid substitutions, non-conservative amino acid subsitutions (i.e. a degenerate variant), substitutions within the wobble position of each codon (i.e. DNA and RNA) encoding an amino acid, amino acids added to the C-terminus of a peptide, or a peptide having 60%, 70%, 80%, 90%, 95%, 96%, 97%, 98%, 99% sequence identity to a reference sequence.

The term “vector” refers to a nucleic acid sequence capable of transporting into a cell another nucleic acid to which the vector sequence has been linked. The term “expression vector” includes any vector, (e.g., a plasmid, cosmid or phage chromosome) containing a gene construct in a form suitable for expression by a cell (e.g., linked to a transcriptional control element). Anti-CD71 Blocking Antibody

Disclosed herein are compositions and methods for treating lupus using antibodies that block the binding of CD71 (transferrin receptor, TfR1) to transferrin- bound iron. These antibodies are referred to herein as “CD71 blocking antibodies” which are known in the art.

It is generally accepted that transferrin receptor antibodies can reduce the uptake of iron into the cell (Kemp, Iron deprivation and cancer: a view beginning with studies of monoclonal antibodies against the transferrin receptor, Histol Histopathol 12, 291-296, (1997)). This can be achieved by blocking the interaction of the transferrin receptor with iron-charged transferrin or by altering the dynamics of transferrin receptor cycling and cell surface presentation.

For example, the murine anti-human TfR1 IgA antibody 42/6 blocks transferrin (Tf) binding through steric hindrance and downregulates surface TfR1, decreasing iron uptake. 42/6 was shown to be cytotoxic to both normal and malignant myeloid cells at similar levels in vitro. Other murine antibodies targeting human TfR1 include A24 (lgG2b), E2.3 (lgG1), and A27.15 (lgG1).

CD71 blocking antibodies are also disclosed in U.S. Patent No. 8,187,594, which is incorporated by reference in its entirety for the teaching of these antibodies.

Anti-CD71 antibodies are also described in U.S. Patent No. 8,734,799, which is incorporated by reference in its entirety for the teaching of these antibodies.

Anti-CD71 antibodies are also described in U.S. Patent No. 8,409,573, which is incorporated by reference in its entirety for the teaching of these antibodies.

Anti-CD71 antibodies are also described in WO2016179257A2, which is incorporated by reference in its entirety for the teaching of these antibodies.

Antibodies that can be used in the disclosed compositions and methods include whole immunoglobulin (i.e., an intact antibody) of any class, fragments thereof, and synthetic proteins containing at least the antigen binding variable domain of an antibody. The variable domains differ in sequence among antibodies and are used in the binding and specificity of each particular antibody for its particular antigen. However, the variability is not usually evenly distributed through the variable domains of antibodies. It is typically concentrated in three segments called complementarity determining regions (CDRs) or hypervariable regions both in the light chain and the heavy chain variable domains. The more highly conserved portions of the variable domains are called the framework (FR). The variable domains of native heavy and light chains each comprise four FR regions, largely adopting a beta-sheet configuration, connected by three CDRs, which form loops connecting, and in some cases forming part of, the beta-sheet structure. The CDRs in each chain are held together in close proximity by the FR regions and, with the CDRs from the other chain, contribute to the formation of the antigen binding site of antibodies.

Transgenic animals (e.g., mice) that are capable, upon immunization, of producing a full repertoire of human antibodies in the absence of endogenous immunoglobulin production can be employed. For example, it has been described that the homozygous deletion of the antibody heavy chain joining region (J(H)) gene in chimeric and germ-line mutant mice results in complete inhibition of endogenous antibody production. Transfer of the human germ-line immunoglobulin gene array in such germ-line mutant mice will result in the production of human antibodies upon antigen challenge (see, e.g., Jakobovits et al., Proc. Natl. Acad. Sci. USA, 90:2551-255 (1993); Jakobovits et al., Nature, 362:255-258 (1993); Bruggemann et al., Year in Immuno., 7:33 (1993)). Human antibodies can also be produced in phage display libraries (Hoogenboom et al., J. Mol. Biol., 227:381 (1991); Marks et al., J. Mol. Biol., 222:581 (1991)). The techniques of Cote et al. and Boerner et al. are also available for the preparation of human monoclonal antibodies (Cole et al., Monoclonal Antibodies and Cancer Therapy, Alan R. Liss, p. 77 (1985); Boerner et al., J. Immunol., 147(1):86-95 (1991)).

Optionally, the antibodies are generated in other species and “humanized” for administration in humans. Humanized forms of non-human (e.g., murine) antibodies are chimeric immunoglobulins, immunoglobulin chains or fragments thereof (such as Fv, Fab, Fab', F(ab’)2, or other antigen-binding subsequences of antibodies) which contain minimal sequence derived from non-human immunoglobulin. Humanized antibodies include human immunoglobulins (recipient antibody) in which residues from a complementarity determining region (CDR) of the recipient antibody are replaced by residues from a CDR of a non-human species (donor antibody) such as mouse, rat or rabbit having the desired specificity, affinity and capacity. In some instances, Fv framework residues of the human immunoglobulin are replaced by corresponding non- human residues. Humanized antibodies may also comprise residues that are found neither in the recipient antibody nor in the imported CDR or framework sequences. In general, the humanized antibody will comprise substantially all of at least one, and typically two, variable domains, in which all or substantially all of the CDR regions correspond to those of a non-human immunoglobulin and all or substantially all of the FR regions are those of a human immunoglobulin consensus sequence. The humanized antibody optimally also will comprise at least a portion of an immunoglobulin constant region (Fc), typically that of a human immunoglobulin (Jones et al., Nature, 321 :522-525 (1986); Riechmann et al., Nature, 332:323-327 (1988); and Presta, Curr. Op. Struct. Biol., 2:593-596 (1992))

Methods for humanizing non-human antibodies are well known in the art. Generally, a humanized antibody has one or more amino acid residues introduced into it from a source that is non-human. These non-human amino acid residues are often referred to as “import” residues, which are typically taken from an “import” variable domain. Antibody humanization techniques generally involve the use of recombinant DNA technology to manipulate the DNA sequence encoding one or more polypeptide chains of an antibody molecule. Humanization can be essentially performed following the method of Winter and co-workers (Jones et al., Nature, 321 :522-525 (1986); Riechmann et al., Nature, 332:323-327 (1988); Verhoeyen et al., Science, 239:1534- 1536 (1988)), by substituting rodent CDRs or CDR sequences for the corresponding sequences of a human antibody. Accordingly, a humanized form of a non human antibody (or a fragment thereof) is a chimeric antibody or fragment (U.S. Pat. No. 4,816,567), wherein substantially less than an intact human variable domain has been substituted by the corresponding sequence from a non-human species. In practice, humanized antibodies are typically human antibodies in which some CDR residues and possibly some FR residues are substituted by residues from analogous sites in rodent antibodies.

Also disclosed are fragments of antibodies which have bioactivity. The fragments, whether attached to other sequences or not, include insertions, deletions, substitutions, or other selected modifications of particular regions or specific amino acids residues, provided the activity of the fragment is not significantly altered or impaired compared to the non-modified antibody or antibody fragment.

Techniques can also be adapted for the production of single-chain antibodies specific to an antigenic protein of the present disclosure. Methods for the production of single-chain antibodies are well known to those of skill in the art. A single chain antibody can be created by fusing together the variable domains of the heavy and light chains using a short peptide linker, thereby reconstituting an antigen binding site on a single molecule. Single-chain antibody variable fragments (scFvs) in which the C-terminus of one variable domain is tethered to the N-terminus of the other variable domain via a 15 to 25 amino acid peptide or linker have been developed without significantly disrupting antigen binding or specificity of the binding. The linker is chosen to permit the heavy chain and light chain to bind together in their proper conformational orientation.

Pharmaceutical composition

Also disclosed is a pharmaceutical composition comprising a disclosed antibody in a pharmaceutically acceptable carrier. Pharmaceutical carriers are known to those skilled in the art. These most typically would be standard carriers for administration of drugs to humans, including solutions such as sterile water, saline, and buffered solutions at physiological pH. For example, suitable carriers and their formulations are described in Remington: The Science and Practice of Pharmacy (21 ed.) ed. PP. Gerbino, Lippincott Williams & Wilkins, Philadelphia, PA. 2005. Typically, an appropriate amount of a pharmaceutically-acceptable salt is used in the formulation to render the formulation isotonic. Examples of the pharmaceutically-acceptable carrier include, but are not limited to, saline, Ringer's solution and dextrose solution. The pH of the solution is preferably from about 5 to about 8, and more preferably from about 7 to about 7.5. The solution should be RNAse free. Further carriers include sustained release preparations such as semipermeable matrices of solid hydrophobic polymers containing the antibody, which matrices are in the form of shaped articles, e.g., films, liposomes or microparticles. It will be apparent to those persons skilled in the art that certain carriers may be more preferable depending upon, for instance, the route of administration and concentration of composition being administered.

Pharmaceutical compositions may include carriers, thickeners, diluents, buffers, preservatives, surface active agents and the like in addition to the molecule of choice. Pharmaceutical compositions may also include one or more active ingredients such as antimicrobial agents, anti-inflammatory agents, anesthetics, and the like.

Preparations for parenteral administration include sterile aqueous or nonaqueous solutions, suspensions, and emulsions. Examples of non-aqueous solvents are propylene glycol, polyethylene glycol, vegetable oils such as olive oil, and injectable organic esters such as ethyl oleate. Aqueous carriers include water, alcoholic/aqueous solutions, emulsions or suspensions, including saline and buffered media. Parenteral vehicles include sodium chloride solution, Ringer's dextrose, dextrose and sodium chloride, lactated Ringer's, or fixed oils. Intravenous vehicles include fluid and nutrient replenishers, electrolyte replenishers (such as those based on Ringer's dextrose), and the like. Preservatives and other additives may also be present such as, for example, antimicrobials, anti-oxidants, chelating agents, and inert gases and the like.

Some of the compositions may potentially be administered as a pharmaceutically acceptable acid- or base- addition salt, formed by reaction with inorganic acids such as hydrochloric acid, hydrobromic acid, perchloric acid, nitric acid, thiocyanic acid, sulfuric acid, and phosphoric acid, and organic acids such as formic acid, acetic acid, propionic acid, glycolic acid, lactic acid, pyruvic acid, oxalic acid, malonic acid, succinic acid, maleic acid, and fumaric acid, or by reaction with an inorganic base such as sodium hydroxide, ammonium hydroxide, potassium hydroxide, and organic bases such as mono-, di-, trialkyl and aryl amines and substituted ethanolamines.

Nucleic Acids and Vectors

Also disclosed are polynucleotides and polynucleotide vectors encoding the disclosed CD71 -specific antibodies. Nucleic acid sequences encoding the disclosed antibodies, and regions thereof, can be obtained using recombinant methods known in the art, such as, for example by screening libraries from cells expressing the gene, by deriving the gene from a vector known to include the same, or by isolating directly from cells and tissues containing the same, using standard techniques. Alternatively, the gene of interest can be produced synthetically, rather than cloned.

Expression of nucleic acids encoding antibodies is typically achieved by operably linking a nucleic acid encoding the antibody to a promoter, and incorporating the construct into an expression vector. Typical cloning vectors contain transcription and translation terminators, initiation sequences, and promoters useful for regulation of the expression of the desired nucleic acid sequence.

The disclosed nucleic acid can be cloned into a number of types of vectors. For example, the nucleic acid can be cloned into a vector including, but not limited to a plasmid, a phagemid, a phage derivative, an animal virus, and a cosmid. Vectors of particular interest include expression vectors, replication vectors, probe generation vectors, and sequencing vectors.

Further, the expression vector may be provided to a cell in the form of a viral vector. Viral vector technology is well known in the art and is described, for example, in Sambrook et al. (2001, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory, New York), and in other virology and molecular biology manuals. Viruses, which are useful as vectors include, but are not limited to, retroviruses, adenoviruses, adeno-associated viruses, herpes viruses, and lentiviruses. In general, a suitable vector contains an origin of replication functional in at least one organism, a promoter sequence, convenient restriction endonuclease sites, and one or more selectable markers. In some embodimens, the polynucleotide vectors are lentiviral or retroviral vectors.

A number of viral based systems have been developed for gene transfer into mammalian cells. For example, retroviruses provide a convenient platform for gene delivery systems. A selected gene can be inserted into a vector and packaged in retroviral particles using techniques known in the art. The recombinant virus can then be isolated and delivered to cells of the subject either in vivo or ex vivo.

One example of a suitable promoter is the immediate early cytomegalovirus (CMV) promoter sequence. This promoter sequence is a strong constitutive promoter sequence capable of driving high levels of expression of any polynucleotide sequence operatively linked thereto. Another example of a suitable promoter is Elongation Growth Factor-1 a (EF-1a). However, other constitutive promoter sequences may also be used, including, but not limited to the simian virus 40 (SV40) early promoter, MND (myeloproliferative sarcoma virus) promoter, mouse mammary tumor virus (MMTV), human immunodeficiency virus (HIV) long terminal repeat (LTR) promoter, MoMuLV promoter, an avian leukemia virus promoter, an Epstein-Barr virus immediate early promoter, a Rous sarcoma virus promoter, as well as human gene promoters such as, but not limited to, the actin promoter, the myosin promoter, the hemoglobin promoter, and the creatine kinase promoter. The promoter can alternatively be an inducible promoter. Examples of inducible promoters include, but are not limited to a metallothionine promoter, a glucocorticoid promoter, a progesterone promoter, and a tetracycline promoter.

Additional promoter elements, e.g., enhancers, regulate the frequency of transcriptional initiation. Typically, these are located in the region 30-110 bp upstream of the start site, although a number of promoters have recently been shown to contain functional elements downstream of the start site as well. The spacing between promoter elements frequently is flexible, so that promoter function is preserved when elements are inverted or moved relative to one another.

In order to assess the expression of an antibody or portions thereof, the expression vector to be introduced into a cell can also contain either a selectable marker gene or a reporter gene or both to facilitate identification and selection of expressing cells from the population of cells sought to be transfected or infected through viral vectors. In other aspects, the selectable marker may be carried on a separate piece of DNA and used in a co-transfection procedure. Both selectable markers and reporter genes may be flanked with appropriate regulatory sequences to enable expression in the host cells. Useful selectable markers include, for example, antibiotic-resistance genes.

Reporter genes are used for identifying potentially transfected cells and for evaluating the functionality of regulatory sequences. In general, a reporter gene is a gene that is not present in or expressed by the recipient organism or tissue and that encodes a polypeptide whose expression is manifested by some easily detectable property, e g., enzymatic activity. Expression of the reporter gene is assayed at a suitable time after the DNA has been introduced into the recipient cells. Suitable reporter genes may include genes encoding luciferase, beta-galactosidase, chloramphenicol acetyl transferase, secreted alkaline phosphatase, or the green fluorescent protein gene. Suitable expression systems are well known and may be prepared using known techniques or obtained commercially. In general, the construct with the minimal 5' flanking region showing the highest level of expression of reporter gene is identified as the promoter. Such promoter regions may be linked to a reporter gene and used to evaluate agents for the ability to modulate promoter-driven transcription.

Methods of introducing and expressing genes into a cell are known in the art. In the context of an expression vector, the vector can be readily introduced into a host cell, e.g., mammalian, bacterial, yeast, or insect cell by any method in the art. For example, the expression vector can be transferred into a host cell by physical, chemical, or biological means.

Physical methods for introducing a polynucleotide into a host cell include calcium phosphate precipitation, lipofection, particle bombardment, microinjection, electroporation, and the like. Methods for producing cells comprising vectors and/or exogenous nucleic acids are well-known in the art. See, for example, Sambrook et al. (2001 , Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory, New York).

Biological methods for introducing a polynucleotide of interest into a host cell include the use of DNA and RNA vectors. Viral vectors, and especially retroviral vectors, have become the most widely used method for inserting genes into mammalian, e.g., human cells.

Chemical means for introducing a polynucleotide into a host cell include colloidal dispersion systems, such as macromolecule complexes, nanocapsules, microspheres, beads, and lipid-based systems including oil-in-water emulsions, micelles, mixed micelles, and liposomes. An exemplary colloidal system for use as a delivery vehicle in vitro and in vivo is a liposome (e.g., an artificial membrane vesicle).

In the case where a non-viral delivery system is utilized, an exemplary delivery vehicle is a liposome. In another aspect, the nucleic acid may be associated with a lipid. The nucleic acid associated with a lipid may be encapsulated in the aqueous interior of a liposome, interspersed within the lipid bilayer of a liposome, attached to a liposome via a linking molecule that is associated with both the liposome and the oligonucleotide, entrapped in a liposome, complexed with a liposome, dispersed in a solution containing a lipid, mixed with a lipid, combined with a lipid, contained as a suspension in a lipid, contained or complexed with a micelle, or otherwise associated with a lipid. Lipid, lipid/DNA or lipid/expression vector associated compositions are not limited to any particular structure in solution. For example, they may be present in a bilayer structure, as micelles, or with a “collapsed” structure. They may also simply be interspersed in a solution, possibly forming aggregates that are not uniform in size or shape. Lipids are fatty substances which may be naturally occurring or synthetic lipids. For example, lipids include the fatty droplets that naturally occur in the cytoplasm as well as the class of compounds which contain long-chain aliphatic hydrocarbons and their derivatives, such as fatty acids, alcohols, amines, amino alcohols, and aldehydes. Lipids suitable for use can be obtained from commercial sources. For example, dimyristyl phosphatidylcholine (“DMPC”) can be obtained from Sigma, St. Louis, Mo.; dicetyl phosphate (“DCP”) can be obtained from K & K Laboratories (Plainview, N.Y.); cholesterol (“Choi”) can be obtained from Calbiochem-Behring; dimyristyl phosphatidylglycerol (“DM PG”) and other lipids may be obtained from Avanti Polar Lipids, Inc, (Birmingham, Ala.).

Methods of Treatment

The disclosed compositions, including pharmaceutical composition, may be administered in a number of ways depending on whether local or systemic treatment is desired, and on the area to be treated. For example, the disclosed compositions can be administered intravenously, intraperitoneally, intramuscularly, subcutaneously, intracavity, or transdermally. The compositions may be administered orally, parenterally (e.g., intravenously), by intramuscular injection, by intraperitoneal injection, transdermally, extracorporeally, ophthalmically, vaginally, rectally, intranasally, topically or the like, including topical intranasal administration or administration by inhalant. Parenteral administration of the composition, if used, is generally characterized by injection. Injectables can be prepared in conventional forms, either as liquid solutions or suspensions, solid forms suitable for solution of suspension in liquid prior to injection, or as emulsions. A revised approach for parenteral administration involves use of a slow release or sustained release system such that a constant dosage is maintained.

The exact amount of the compositions required will vary from subject to subject, depending on the species, age, weight and general condition of the subject, the severity of the allergic disorder being treated, the particular nucleic acid or vector used, its mode of administration and the like. Thus, it is not possible to specify an exact amount for every composition. However, an appropriate amount can be determined by one of ordinary skill in the art using only routine experimentation given the teachings herein. For example, effective dosages and schedules for administering the compositions may be determined empirically, and making such determinations is within the skill in the art. The dosage ranges for the administration of the compositions are those large enough to produce the desired effect in which the symptoms disorder are affected. The dosage should not be so large as to cause adverse side effects, such as unwanted crossreactions, anaphylactic reactions, and the like. Generally, the dosage will vary with the age, condition, sex and extent of the disease in the patient, route of administration, or whether other drugs are included in the regimen, and can be determined by one of skill in the art. The dosage can be adjusted by the individual physician in the event of any counterindications. Dosage can vary, and can be administered in one or more dose administrations daily, for one or several days. Guidance can be found in the literature for appropriate dosages for given classes of pharmaceutical products. A typical daily dosage of the disclosed composition used alone might range from about 1 pg/kg to up to 100 mg/kg of body weight or more per day, depending on the factors mentioned above.

In some embodiments, the molecule is administered in a dose equivalent to parenteral administration of about 0.1 ng to about 100 g per kg of body weight, about 10 ng to about 50 g per kg of body weight, about 100 ng to about 1 g per kg of body weight, from about 1 pg to about 100 mg per kg of body weight, from about 1 pg to about 50 mg per kg of body weight, from about 1 mg to about 500 mg per kg of body weight; and from about 1 mg to about 50 mg per kg of body weight. Alternatively, the amount of molecule containing lenalidomide administered to achieve a therapeutic effective dose is about 0.1 ng, 1 ng, 10 ng, 100 ng, 1 pg, 10 pg, 100 pg, 1 mg, 2 mg, 3 mg, 4 mg, 5 mg, 6 mg, 7 mg, 8 mg, 9 mg, 10 mg, 11 mg, 12 mg, 13 mg, 14 mg, 15 mg, 16 mg, 17 mg, 18 mg, 19 mg, 20 mg, 30 mg, 40 mg, 50 mg, 60 mg, 70 mg, 80 mg, 90 mg, 100 mg, 500 mg per kg of body weight or greater.

The disclosed antibodies may be administered either alone, or as a pharmaceutical composition in combination with diluents and/or with other components such as IL-2, IL-15, or other cytokines or cell populations. Briefly, pharmaceutical compositions may comprise a target cell population as described herein, in combination with one or more pharmaceutically or physiologically acceptable carriers, diluents or excipients. Such compositions may comprise buffers such as neutral buffered saline, phosphate buffered saline and the like; carbohydrates such as glucose, mannose, sucrose or dextrans, mannitol; proteins; polypeptides or amino acids such as glycine; antioxidants; chelating agents such as EDTA or glutathione; adjuvants (e.g., aluminum hydroxide); and preservatives. Compositions for use in the disclosed methods are in some embodimetns formulated for intravenous administration. Pharmaceutical compositions may be administered in any manner appropriate treat MM. The quantity and frequency of administration will be determined by such factors as the condition of the patient, and the severity of the patient's disease, although appropriate dosages may be determined by clinical trials.

The administration of the disclosed compositions may be carried out in any convenient manner, including by injection, transfusion, or implantation. The compositions described herein may be administered to a patient subcutaneously, intradermally, intratumorally, intranodally, intramedullary, intramuscularly, by intravenous (i.v.) injection, or intraperitoneally. In some embodiments, the disclosed compositions are administered to a patient by intradermal or subcutaneous injection. In some embodiments, the disclosed compositions are administered by i.v. injection. The compositions may also be injected directly into a tumor, lymph node, or site of infection.

A number of embodiments of the invention have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the invention. Accordingly, other embodiments are within the scope of the following claims. EXAMPLES

Example 1: Elevated transferrin receptor impairs T cell metabolism and function in systemic lupus erythematosus

Results

CD71 is conditionally essential for effector T cells but suppresses iT _reg s

Iron metabolism may offer novel therapeutic targets with the potential to regulate T cell differentiation and mitigate mitochondrial oxidative stress; unbiased approaches have not been used to establish the essential iron regulatory genes in T cells. We therefore designed a custom pooled library of CRISPR-Cas9 guide RNAs (gRNAs) targeting genes in iron metabolism to determine genes that are important for T cell differentiation. Naive T cells from Cas9 transgenic mice were retrovirally transduced to express the pool of gRNAs, and cells were differentiated into T _H 1 cells and iT _reg s in physiologically relevant human plasma-like medium (HPLM). gRNA frequencies were determined by sequencing, and guide frequencies in the resultant populations were compared with the starting pool to establish whether a given gene deletion reduced or increased T cell fitness and accumulation. CRISPR disruption of most genes had a modest or no effect, but deletion of Slc25a37 (mitoferrin-1) and Tfrc (transferrin receptor, CD71) was detrimental and led to fitness disadvantages for T _H 1 cells (Fig. 1 A). Conversely, deletion of Tfrc provided a strong fitness advantage to iT _re gs. TH1 cultures expressed higher levels of CD71 than iT _reg cultures (Fig. 1 B) and contained more intracellular iron (Fig. 1C). Tfrc thus conditionally affects T cell subsets and is essential for inflammatory T cells.

Iron metabolism is dysregulated in T cells from patients with SLE

Iron metabolism in immune cells is subject to tight regulation through systemic and cellular mechanisms to support multiple cellular functions and oxidative stress. Given reported metabolic defects in SLE T cells, we determined whether dysregulated iron handling was apparent in patients with SLE in published RNA sequencing and human genome array datasets. In both SLE total peripheral blood mononuclear cells (PBMCs) and purified CD4 T cells, expression of TFRC was significantly higher in patients with SLE than healthy individuals (Figs. 8A and 8B). SLC11A2, which encodes for the divalent metal transporter 1, was increased in PBMCs, but not in CD4 T cells. Six-transmembrane epithelial antigen of prostate 3 (STEAP3) expression, an endosomal ferrireductase, was modestly increased in CD4 T cells from patients with SLE but not PBMC samples. Hemochromatosis (HFE), a regulator of iron homeostasis and CD71 iron uptake, was significantly increased in both PBMC and CD4 T cell samples from patients with SLE. HFE can bind to CD71 and reduce its affinity for transferrin-bound iron but may also enhance iron uptake when associated with 2-microglobulin by promoting endosomal recycling of CD71 to the plasma membrane. Concentrations of HFE in serum were significantly elevated in patients with SLE compared with healthy controls (Fig. 8C). Collectively, these studies suggest that CD71 is dysregulated and may contribute to the elevated iron concentrations and dysfunction previously measured in T cells from patients with SLE.

T cells from lupus-prone mice have altered activation and kinetics of CD71 induction

T cell receptor activation is often impaired in T cells from patients with SLE (36, 37), and iron uptake is associated with T cell activation. To better understand the regulation of iron metabolism in SLE, we examined the triple congenic mouse model of lupus-prone mice (referred to as SLE1.2.3), which closely mimics human disease. Naive CD4 T cells were isolated from female SLE1.2.3 mice or healthy age-matched control mice and stimulated to measure activation over time. T cells from SLE1.2.3 mice induced significantly lower levels of activation markers CD25 and CD69, and downregulation of CD62L was delayed (Fig. 9A). In contrast, CD44 was significantly higher in activated SLE1.2.3 T cells compared with controls (Fig. 9A), as has been reported in T cells from patients with SLE.

Cell surface CD71 , also considered an activation marker of T cells, was significantly higher in SLE T cells than controls and remained elevated long after initial stimulation (Fig. 1 D). Increased and prolonged expression was associated with elevated intracellular iron concentrations in SLE1.2.3 T cells (Fig. 1 E). Therefore, both the elevated intracellular iron and altered T cell activation phenotypes and CD71 expression were altered in consistent fashions between the SLE1.2.3 mouse model and phenotypes demonstrated by T cells from patients with SLE. Although protein levels of CD71 were higher in SLE1.2.3 T cells, transcripts of Tfrc were significantly lower than controls (Fig. 1 F), suggesting posttranscriptional regulation. Translation of Tfrc is known to be regulated by the RNA binding protein iron-regulatory protein 2 (Irp2). I rp2 is subject to proteasomal degradation in the presence of iron, but in low iron states, the protein is stabilized, binds to iron-responsive elements (IREs) in Tfrc mRNAs, and stabilizes the transcript (41). Consistent with higher concentrations of iron in SLE1 .2.3 T cells (Fig. 1 E), Irp2 protein was reduced when normalized to p-actin (Fig. 1G). Hfe expression was increased in SLE1.2.3 T cells (Fig. 1 H), which may influence the recycling rate of CD71 (35).

To investigate endosomal recycling of CD71 in SLE1.2.3 T cells, we stimulated CD71 internalization in activated T cells with transferrin protein. Using Ras-related protein Rab8 as a marker of recycling endosomes, we quantified colocalization of CD71 and Rab8 at each time point (Fig. 11). Control T cells demonstrated peak colocalization after 30 min of transferrin stimulation and returned to baseline levels by 2 hours. By contrast, SLE1.2.3 T cells increased colocalization over time, with the highest signal at 2 hours that was significantly higher than that of control T cells. These data suggest that altered or increased recycling contributes to the increased surface levels of CD71 in SLE1.2.3 T cells.

CD71 blockade reduces intracellular iron and normalizes SLE T cell activation in vitro

Anti-CD71 antibodies have been reported to bind CD71 to block association with transferrin-iron complexes and stimulate receptor internalization without iron uptake. Consistent with receptor blockade and/or internalization, cell surface CD71 expression decreased as observed by flow cytometry in activated T cells treated with CD71 -blocking antibody compared with the isotype control (Fig. 10A). Because flow cytometric detection of cell surface CD71 could have been hindered by the presence of the CD71- blocking antibody, however, internalization was specifically tested by treatment of activated T cells with anti-CD71 or the isotype control antibody for 1 hour, followed by a secondary antibody. T cells were either permeabilized or non-permeabilized before adding the secondary, allowing the measurement of internalized versus cell surface- associated blocking antibody. There was significant internalization of the receptor/anti- CD71 complex (Fig. 10B). This correlated with a significant decrease in intracellular labile iron, confirming the role of the blocking antibody in reducing intracellular iron loads (Fig. 10C).

Because CD71 expression and iron flux are important for T cell activation, we tested whether anti-CD71 would prevent T cell activation. CD69 up-regulation was restored to SLE1.2.3 T cells treated with anti-CD71 , whereas control T cells were unaffected (Fig. 2A). Conversely, CD44 overexpression in SLE1.2.3 T cells was reduced to control levels by anti-CD71 treatments (Fig. 2B). T cells in patients with SLE have a well-documented deficiency in IL-2 production. The percentage of IL-2-producing T cells was increased in SLE1.2.3 T cells activated with anti-CD71 but not control T cells (Fig. 2C). Furthermore, IL-2 transcription was significantly boosted in SLE1.2.3 T cells and modestly increased in control T cells (Fig. 2D). Overall, IL-2 secretion was defective in SLE1 .2.3 T cells compared with controls but significantly improved by anti-CD71 on a per-cell basis (Fig. 2E). Together, these data show that targeting CD71 correlates with lower intracellular iron and can normalize altered T cell activation phenotypes demonstrated by SLE T cells.

CD71 blockade restores mTORCI signaling and mitochondrial function in SLE- prone T cells

To determine the mechanism by which targeting CD71 targeting may rescue functional abnormalities in SLE T cells, we tested CD71 regulation of mTORCI . High levels of mTORCI have been reported in SLE T cells and can be detrimental to Tregs. mTORCI integrates the status of multiple cell nutrient and metabolic conditions with cell signaling to phosphorylate targets such as p70S6 kinase and promote anabolic metabolism. mTORCI activity as indicated by phospho-S6 (p-S6) trended higher in SLE1.2.3 T cells and was significantly reversed with anti-CD71 (Fig. 2F). These findings are consistent with other results that iron chelation suppresses mTORCI activation. mTORCI broadly regulates anabolic metabolism, so the effects of CD71 blockade reduced T cell size, which was normalized in SLE1.2.3 T cells with anti-CD71 when measured by flow cytometric forward light scatter (Fig. 2G). To test whether mTORCI signaling regulates CD71 expression, T cells were activated for 24 hours and then treated with rapamycin to inhibit mTORCI . mTORCI inhibition did not significantly affect CD71 expression (Fig. 2H), whereas both anti-CD71 and rapamycin significantly lowered cell proliferation (Fig. 2I). Therefore, CD71 and iron metabolism predominately regulates mTORCI signaling in T cells, although mTORCI may contribute a minimal role to CD71 expression.

Altered mitochondrial metabolism and low ATP production is a well-documented phenotype of T cells in SLE (50); thus, we investigated the effects of anti-CD71 on mitochondrial function. Mitochondrial matrix protein mass indicated by MITOTRACKER Green was reduced in SLE1.2.3 T cells relative to control T cells (Fig. 3A). Anti-CD71 treatment resulted in a further decrease in mitochondrial mass in both control and SLE1.2.3 T cells. CD71 blockade also resulted in a large decrease in MITOROS in both control and SLE1.2.3 T cells (Fig. 3B). Therefore, manipulations of iron metabolism affect some mitochondrial features in T cells independently of disease status. The ultrastructure of the mitochondria was next analyzed by electron microscopy (EM). Mitochondrial cross-sectional area (referred to hereby as mitochondrial area) was determined by measuring the area of mitochondrial membranes and revealed that SLE1.2.3 T cell mitochondrial size was significantly smaller than controls (Fig. 3C). Anti- CD71 treatment in control cells reduced mitochondrial area but did not change the overall morphology of the mitochondria. In contrast, anti-CD71 treatment of SLE1.2.3 T cells caused a marked change in morphology from small dense mitochondria to larger areas with reduced electron density that was comparable to control T cells. Despite changes in mitochondrial area, the total mitochondrial area fraction of cells was not affected by disease status or treatment type (Fig. 3C) to indicate that the average proportion of the cell that was occupied by mitochondria did not change and only the immediate size of individual mitochondria was distinctly affected. The increase in mitochondrial area in anti-CD71-treated SLE1.2.3 T cells with an invariant area fraction suggests that the cells have fewer but larger and less dense mitochondria, consistent with the observed reduction in MITOTRACKER staining that detects cardiolipin in mitochondrial membranes.

To test whether anti-CD71 affected mitochondrial respiration in SLE1.2.3 T cells, we conducted extracellular flux analyses. All T cells required some level of iron for mitochondrial function because T cells incubated with the cell-permeable iron chelator ciclopirox (CPX) had decreased basal and maximal mitochondrial respiration regardless of disease status (Fig. 3D). However, respiration of T cells was differentially affected by anti-CD71 in SLE1.2.3 T cells versus controls (Fig. 3E). Whereas control T cells had slightly increased maximal respiration with CD71 blockade, respiration was significantly decreased in SLE1.2.3 T cells (Fig. 3F). SLE1.2.3 T cells had a significantly higher mitochondrial proton leak, a measure of electron transport efficiency across the mitochondrial membrane outside of ATP synthase and mitochondrial quality, than control cells (Fig. 3G). Proton leak was restored in SLE1.2.3 T cells, however, to levels of controls by anti-CD71 . Anti-CD71 treatments led to a significant boost in ATP production specifically from the mitochondria and not from glycolysis (Fig. 3H). Together, these data demonstrate a morphological and functional effect of CD71 blockade on SLE1.2.3 T cells that improves efficiency of respiration and mitochondrial ATP production.

CD71 differentially affects T cell subsets

CRISPR-0as9 screening indicated that Tfrc was conditionally essential for T _H 1 but not iT _re g _S (Fig. 1A). Therefore, we tested whether anti-CD71 exerted distinct impacts on different CD4 T cell subsets. Naive T cells from control mice were activated with CD71 blockade or an isotype control during differentiation for TH1 and TH17 cells and iTregs. Anti-CD71 treatment led to increased apoptotic cell death in TH1 cultures, consistent with a positive role for CD71 in TH1 cells, but had limited or no effect on iTreg or T _H 17 cultures (Fig. 11A). Mechanistically, this increased apoptosis was associated with extensive DNAdamage as indicated by phosphorylation of H2A histone family member X (H2AX), a hallmark of double-stranded breaks (Fig. 11 B).

Although anti-CD71 treatment did not affect the viability of T _H 17 cells, anti-CD71 interfered with their differentiation, in agreement with other recent work. The percentage of I L-17 ⁺ cells was significantly reduced compared with controls (Fig. 110). In contrast to previous studies that found a role for increased IL-2 to suppress T _H 17 cells, however, only a modest increase in the percentage of I L-2 ⁺ cells with anti-CD71 was observed (Fig. 11D), suggesting that additional mechanisms exist to inhibit T _H 17 differentiation during CD71 blockade. Anti-CD71 during activation also interfered with T _H 17 differentiation of SLE1.2.3 T cells (Fig. 11E). TH17 cells treated with the chelator CPX had a further reduction in IL-17 production in both control and SLE1.2.3 T cells. Therefore, both acute iron availability and/or iron loads during early T cell differentiation can regulate IL-17 production in SLE T cells.

T cell differentiation to functional subsets is largely driven by specific cytokines, which could regulate CD71 expression directly. We hypothesized that IL-6 would drive the highest expression of CD71 on activated T cells. To this end, T cells were differentiated in the presence of individual cytokines involved in T _H 1 , T _H 17, and T _reg differentiation with or without transforming growth factor-p (TGF-P). T cells activated in TGF-p alone failed to up-regulate CD71 after activation (Fig. 11 F). The percentage of CD71 ⁺ cells was similar under other conditions, whereas the intensity of CD71 expression was varied (Fig. 11 F). T cells activated in IL-2 or IL-6 had the highest CD71 intensity but, when combined with TGF-p, expressed less than a third of the amount. CD71 was regulated by cytokines independently of activation status because CD25 expression demonstrated a distinct pattern of regulation from that of CD71 (Fig. 11 G), with T cells activated with either IL-6 or TGF-p + IL-6 + IL-1 p + IL-23 having the highest CD25 intensity. T cell CD71 and CD25 split into two distinct expression trajectories based on the presence or absence of TGF-p (Fig. 11 H). Cultures without TGF-p had high CD71 and lower OD25 expression, and cultures with TGF-p expressed more CD25 and less CD71. T _H 17 cultures were subjected to RNA sequencing to determine whether SLE1.2.3 T cell gene expression profiles promoted enhanced TH17 differentiation and/or iron metabolism. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that SLE1.2.3 TH17 cells contained a gene expression profile more enriched for TH17 differentiation and IL-17 signaling than control T _H 17 T cells (Fig. 4A). T _H 17 cells from SLE1 .2.3 mice were also more pathogenic, as indicated by significant increases in Csf2, 116, and Ifng, which had a fold change of >165 in SLE1 .2.3 T cells. Gene ontology analysis of biological processes performed on significant genes revealed enrichments in both regulation of metal ion transport and divalent metal ion transport pathways. In addition, the most marked change among all gene expression as determined by DESeq2 analysis was the ferritin light chain, Ftl1 (Padj = 5.2 x 1O“ ¹¹¹ ; Fig. 4B). Despite decreased ferritin expression, SLE1 .2.3 T cells exhibited large increases in multiple iron handling genes, including Steap3, Slc11a1, and Glrx, an enzyme required for the biogenesis of iron-sulfur clusters. Two iron-binding lipoxygenases involved in fatty acid hydroperoxidase production (Aiox5 and Alox15) were also significantly increased in SLE1 .2.3 T cells (Fig. 4B). Using a newly compiled gene set of predicted IRE or I RE-like motifs in 3' untranslated region (3'-UTR) and 5’-UTR (52), we tested whether transcripts had global changes in IREs. SLE1.2.3 TH17 cells exhibited down-regulation in IRE motifs compared with control T _H 17 cells. Together, these data suggest that SLE1.2.3 T cells are transcriptionally more primed for T _H 17 differentiation and pathogenicity, have significant disruptions in key cellular iron handling genes, and suggest an altered transcriptional responsiveness to iron-based regulation by global mRNA IRE representation.

CD71 regulation in response to iron manipulation is distinct between TH 17 and iTregs

The effects of anti-CD71 and other cellular iron manipulations were next examined specifically on T _H 17 cells and iTregs. Because CD71 itself is regulated by ironresponsive proteins during T cell activation, we treated T cells with CPX or supplemented cultures with excess iron during differentiation to indirectly test whether iron-dependent regulation of CD71 could be dysregulated in SLE. Control CPX-treated TH17 cells had a decrease in CD71 expression, but CD71 was not significantly affected in SLE1.2.3 T cells (Fig. 40), suggesting that CD71 regulation may be less sensitive to intracellular iron concentrations in SLE1.2.3 T cells or that iron chelation had a smaller effect due to higher starting concentrations of iron. In both controls and SLE1.2.3 T cells, iron supplementation significantly decreased CD71 expression, in agreement with another study of T cells loaded with excess iron that also down-regulated CD71 potentially through IRP function. iT _reg s did not exhibit the same down-regulation of CD71 expression with iron supplementation (Fig. 40). This distinct regulation was unique to control iTregs because iT _reg s from SLE1 .2.3 mice did show a significant decrease in CD71 expression with iron supplementation to further support differential iron regulation in SLE T cells.

The effects of anti-CD71 were next examined specifically on iTregs. Consistent with enhanced iT _reg accumulation after CRISPR deletion of Tfrc (Fig. 1A), anti-CD71 significantly increased forkhead box P3 (Foxp3) expression in iTregs compared with the isotype control (Fig. 4D), although the overall percentage of Foxp3 ⁺ cells was unaffected. The percentage of iT _re gs producing IL-2 doubled, and the amount of IL-10 secreted into cell supernatants under iT _reg conditions was increased with anti-CD71 treatment (Figs. 4E and 4F). Naive T cells isolated and differentiated into iT _reg s produced significantly more IL- 10 with anti-CD71 treatment (Fig. 4G). This was accompanied by increased musculoaponeurotic fibrosarcoma (c-MAF) expression with anti-CD71 , a common feature for IL-10 production in T cells across subsets (Fig. 4H). To genetically test the role of Tfrc, we cloned single gRNAs to target Tfrc or a scramble nontargeting control sequence to delete CD71 during iT _reg differentiation (Fig. 4I). Transduced cells expressing CD90.1 (Thy 1.1) were analyzed for Foxp3 expression, which did not significantly change with Tfrc deletion, although iT _reg culture conditions promoted more than 90% of cells to express Foxp3. mTORCI activity was significantly decreased by Tfrc deletion in iT _reg s, as shown by less p-S6 (Fig. 41). These data show that CD71 blockade can modulate T cell differentiation to suppress effector T cells and boost Foxp3 expression and IL-10 production of iTregs.

CD71 blockade reduces pathology and autoimmunity in SLE1.2.3 mice

On the basis of the ability of CD71 blockade to improve the activation and mitochondrial functions of SLE1 .2.3 T cells, we tested whether this treatment could reduce in vivo markers of autoimmunity in lupus-prone mice. To this end, SLE1.2.3 females and age-matched controls were treated with isotype control or anti-CD71 antibody twice a week for 4 weeks (Fig. 5A). SLE1.2.3 mice with preestablished autoimmunity determined by anti-double-stranded DNA (dsDNA) immunoglobulin G (IgG) antibodies at the start of the treatment course were included in the study (Fig. 5B). By the end of the treatment course, anti-dsDNA antibodies in SLE1.2.3 mice treated with anti-CD71 were reduced compared with the isotype control group (Fig. 5C). Antinuclear antibodies (ANAs) and anti-histone antibodies also showed decreased trends (Fig. 12A and 12B). Splenomegaly was significantly reduced with anti-CD71 treatment (Fig. 5D), but total B cell numbers appeared unaffected (Fig. 120). However, spleens and lymph nodes (LNs) were harvested, and CD4 T cells were isolated, revealing a significant drop in CD4 T cell numbers in anti-CD71 -treated mice (Fig. 5E). Treatment was well tolerated, and no signs of anemia were detected by complete blood count analysis (Figs. 12D to 12F). Analysis of activation markers immediately ex vivo showed that SLE1.2.3 T cells exhibited much higher CD69 expression, which was not affected by the anti-CD71 treatments (Fig. 12G). There was, however, a rescue in the intensity of CD44 expression of the anti-CD71 -treated group in SLE1.2.3 T cells (Fig. 5F).

Kidneys and livers were next analyzed to assess SLE-associated pathology and determine whether CD71 blockade reduced tissue damage. Histopathologic assessment of inflammation was blindly scored with a semiquantitative inflammation scale in stained tissue sections. In the kidney, interstitial nephritis and glomerular loop thickening were evident in the kidneys of SLE1.2.3 mice that received isotype control antibody (Fig. 5G). These lesions were significantly reduced with anti-CD71 treatments. SLE1.2.3 mice also exhibited periportal infiltrates of lymphocytes and plasma cells in the liver (Fig. 5H) that were greatly reduced with anti-CD71 treatment.

Consistent with increased IL- 10 secretion from iT _reg cultures treated with anti- CD71 (Fig. 4H), there was a large increase of IL-10 in the sera of SLE1.2.3 mice with anti-CD71 treatments (Fig. 5I). Furthermore, the percentage of CD4 T cells producing IL- 10 was significantly increased (Fig. 5J), suggesting that CD71 targeting may rewire CD4 T cells in vivo to secrete IL-10. We hypothesized that Tregs may be a source of the IL-10 because our CRISPR screen and CD71 blockade in vitro were beneficial to iT _reg cultures (Fig. 1A). In agreement with this, natural T _reg frequency increased in SLE1.2.3 mice treated with anti-CD71 (Fig. 5K), but no changes in the frequency of T follicular regulatory (Tfr) cells were observed (Fig. 12H). TFH cells were expanded in SLE1 .2.3 mice, and anti-CD71 treatments boosted TFH frequency in control mice but not SLE1.2.3 mice (Fig. 121). Together, these data show that anti-CD71 treatments were well tolerated in vivo, reduced disease pathology, and supported Tregs. CD71 expression on T cells is required to drive autoimmunity in an inducible model of SLE

Although anti-CD71 treatments reduced autoimmunity in SLE1.2.3 mice, CD71 expression is not limited to T cells, and therefore, antibody treatments could have also affected other cell types. To address this, we used CD4 ^cre ;Tfrc ^fl/fl mice in the inducible bm12 model of SLE. Splenocytes from a C57BL/6 background are transferred into congenic bm12 recipient mice, which have a three-amino acid polymorphism in H2-Ab1, and autoimmunity develops within 14 days. We hypothesized that Cre+ recipients would not develop autoimmunity if CD71 expression on T cells is necessary for autoreactive T cells in SLE. By the 14-day end point, only Cre- recipients developed a significant detection of anti-dsDNA antibodies (Fig. 6A). By day 8 after transfer, a significant expansion of both TFH and germinal center (GC) B cells could be detected in peripheral blood compared with Cre+ recipients or sham control mice (Fig. 6B).

Spleens and LNs were removed from all recipient mice on day 14. Splenomegaly was significantly affected by CD71 status because the mass of Ore- recipient spleens was doubled compared with Cre ⁺ recipients or sham controls (Fig. 6C). Both GC B cells and plasma cells were expanded in the spleens of Cre- recipients compared with Cre+ (Fig. 6D). Examination of CD4 T cells in the spleen confirmed a significant loss of CD71 expression on T cells in Cre ⁺ recipients, although some CD71 expression was present because of their original T cell compartment (Fig. 6E). Cre- recipients demonstrated a significant expansion of TFH cells in the spleen and increased induced T cell costimulator (ICOS) expression on bulk CD4 T cells (Fig. 6F). These T cells also had higher expression of the activation marker CD44 compared with Cre+ or sham recipients (Fig. 6G). T cell phenotypes in the LNs were consistent with those demonstrated by splenocytes. Cre- recipients had significantly higher CD71 expression (Fig. 6H) and an expanded TFH population (Fig. 6I). CD71 deletion lessened iron accumulation in T cells in vivo (Fig. 6J). Although kidney damage does not occur by day 14 in this model, kidneys were removed to examine early detection of T cell autoreactivity. Lymphocytes purified from kidneys of Cre- recipients tended to have a higher frequency of CD4 T cells (Fig. 6K). Within the CD4 T cells in the kidney, Cre- recipients had significantly higher CD71 expression compared with Cre ⁺ recipients. Together, the bm12 inducible model of SLE supported the hypothesis that CD71 expression on T cells is required for SLE disease. CD71 expression on T cells corresponds to disease activity and increased TH 17 cells in patients with SLE

To test the regulation and role of CD71 and iron metabolism in human T cells, we activated naive T cells from three healthy donors under either undifferentiated THO conditions orT _H 17 conditions. T _H 17-skewed T cells from each donor contained significantly higher intracellular iron concentrations than T _H 0 cells (Fig. 7 A), consistent with the role for iron in T _H 17 differentiation in human T cells. Therefore, T cells from patients with SLE and healthy donors with no history of autoimmune conditions were collected to characterize the expression and role of CD71 (Table 1 and Fig. 13A). In both control and SLE patient samples, there was a notable correlation between the percentage of T _H 17 cells and the level of CD71 expression on all CD4 T cells (Fig. 7B), consistent with the relationship between CD71 expression and T _H 17 cell differentiation in humans. On average, CD71 expression was increased on CD4 T cells from patients with SLE compared with those of controls (Fig. 7C). Patients with SLE also had higher percentages of T _H 17 cells in their CD4 T cell compartment, and CD71 expression on these cells was elevated in many patients (Figs. 7D and 7E).

Despite increased CD71 and CD44 expression, CD69 did not significantly differ in patients with SLE compared with controls, suggesting that high CD71 was not a nonspecific effect of elevated T cell activation (Fig. 13B). Furthermore, although patients with SLE often develop anemia, CD71 expression on T cells correlated with hemoglobin levels (Fig. 13C), suggesting that anemia itself does not dictate CD4 T cell expression of CD71. Patients with high CD71 expression may represent a subset of SLE with more active disease and TH17 cell involvement. Although all patients were being treated with at least hydroxychloroquine and some with additional therapies (Table 1), SLE disease activity assessed by Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) scores showed a trend toward patients with worse disease to have higher CD71 expression on CD4 T cells (Fig. 7F), although there were no apparent differences in the frequency of T _H 17 cells (Fig. 7G). CD71 expression on T _H 17 cells, however, did significantly correlate with disease severity despite a limited sample size (Fig. 7H).

Targeting CD71 in T cells from patients with SLE increases IL-10 secretion

To test the effects of CD71 targeting in lupus patient T cell samples, we used a human-specific CD71 -blocking antibody, mirroring our previous tests with a murinespecific antibody in SLE1.2.3 mice. The antibody reduced iron uptake in activated T cells (Fig. 13D). In agreement with CD71 blockade in murine T cells, anti-CD71 did not interfere with activation of human T cell samples as measured by activation markers CD25 and CD44 (Fig. 13E). Extracellular flux analyses of mitochondrial respiration demonstrated a consistent drop in maximal respiration in control T cell samples (Fig. 7I), whereas T cells from patients with SLE had heterogeneous responses, and many showed increased maximal respiration. Despite heterogeneity, CD71 blockade led to a significant increase in IL-10 secretion from T cells from patients with SLE (Fig. 7J). Together, CD71 targeting in SLE patient T cell cultures appeared to regulate mitochondrial function and boost IL-10 production in a subset of samples.

Discussion

Iron metabolism has recently been recognized as a potential driver of disease in patients with SLE. Dietary iron can aggravate lupus symptoms, although it is unclear how iron influences immune cell function in the setting of lupus. Lowering serum iron in mouse models of lupus has shown promising reductions in autoimmune pathology, but these efforts have focused mainly on innate cells such as macrophages. Although iron has been implicated in T cell differentiation of some subsets (T _H 1 , T _H 2, and T _H 17), the mechanisms by which iron regulates T cell function have been limited despite a clear role for iron in anabolic and mitochondrial metabolism. Here, we show that targeting iron metabolism via CD71 can reduce disease manifestations of SLE through multiple mechanisms of T cell regulation. First, blocking CD71 lowered intracellular iron and modulated T cell activation in SLE T cells such that activation markers and IL-2 secretion were restored to normal. In SLE T cells, CD71 induction was heightened and remained elevated long after initial stimulus compared with controls. This elevated CD71 is likely driven by increased endosomal recycling to the plasma membrane that could increase accumulation of iron in SLE T cells despite the predisposition for patients with SLE to develop low serum iron. High levels of intracellular iron, in turn, altered mitochondrial respiration and quality control to reduce ATP production efficiency. The effects of CD71 blockade on mitochondrial health and ATP production were apparent only in SLE T cells, suggesting that mitochondria in SLE T cells may be sensitized to changes in iron levels caused by anti-CD71. Second, mTORCI was also regulated in a CD71-dependent manner. Elevated mTORCI activity can promote effector T cells, including TH17, suppress Treg function and stability, and may contribute to the finding of increased TH17 and decreased Tregs in patients with SLE.

Our study sheds light on iron biology in different T cell subsets and differentiation. iT _re gs thrived under CD71 -targeting conditions, whereas T _H 1 cultures were depleted because of increased levels of cell death. CD71 targeting was particularly beneficial to iTregs by increasing Foxp3 expression and lowering mTORCI, suggesting that they could have enhanced suppressive capacity or stability. Experiments treating cells with differential cytokine combinations highlight a potential role forTGF- to suppress CD71 expression during T cell activation, which could feed back on Tregs or suppress CD71 on nearby activated effector T cells. We also show that CD71 expression is associated with TH17 cell development in humans and that T _H 17 cells from patients with SLE express high levels of CD71. Because many patients with lupus exhibit pathogenic interferon-y (IFN-y), IL-17 double producing TH1* cells, one strategy for treating TH17- driven inflammation is to target metabolic regulators of the conversion of nonpathogenic T _H 17 cells to proinflammatory pathogenic T _H 17 cells. In support of this, iron-deficient mice failed to develop experimental autoimmune encephalomyelitis (EAE), and a CD4 T cell-specific deletion of Tfrc also failed to drive T _H 17 neuroinflammation via decreased granulocyte-macrophage colony-stimulating factor mRNA stability. CD71 blockade was previously shown to inhibit TH17 differentiation partly by increasing IL-2 secretion, but OUT TH17 cell cultures did not produce significantly more IL-2 upon anti-CD71 treatment. TH17 cultures from SLE-prone mice demonstrated a higher propensity for Tn17 cell differentiation, which was associated with altered expression of key iron metabolism genes. Regulators of iron metabolism may therefore reveal previously unknown regulators of T _H 17 cell pathogenicity, and together, these data demonstrate a strong association between sustained CD71 expression, iron accumulation, and development of a pathogenic T _H 17 program.

In vivo, CD71 blockade was well tolerated, significantly reduced autoantibodies, and prevented disease-specific pathology in the kidneys and liver. A notable finding was that blocking CD71 increased systemic IL-10 levels in the serum and IL-10-producing T cells. Although the physiologic significance of small changes in IL-10 is uncertain, an increased percentage of T cells producing IL-10 could have an enduring impact on inflammation in the T cell compartment. In addition, IL-10 is generally thought to have an antiinflammatory role; its role in SLE is controversial and has been associated with more active disease. This may reflect a compensation mechanism for increased systemic inflammation, although B cells in SLE mice treated with I L-10— blocking antibodies produced fewer autoantibodies. IL-10 was also linked to increased apoptosis of CD4 T cells from patients with SLE by inducing Fas cell surface receptor and Fas ligand (FasL) expression. However, recent work investigating the dual role of IL-10 in murine lupus showed that blocking the IL-10 receptor in vivo accelerated disease and immune dysregulation. Here, we found that SLE1.2.3 mice had a significant reduction in splenomegaly and autoantibody titers that correlated with increased systemic IL- 10 upon anti-CD71 treatment. Anti-CD71 appeared to act directly on T cells in vivo because frequencies of CD4 T cell secretion of IL-10 ex vivo were enhanced and Treg frequency was boosted.

Limitations of our study include a limited sample size of samples of patients with SLE further complicated by clinical treatment. Despite this, there appeared to be a subset of patients with SLE with high CD71 expression on TH17 cells, which correlated with a worse SLEDAI score. It is likely that anti-CD71 -induced changes in this population may be concealed in the bulk cultures analyzed here. The antibody blockade treatment used in SLE1.2.3 mice to induce CD71 internalization was well tolerated here and in previous studies, and no unintended anemia was observed. However, concentrations of iron in other tissues were not evaluated after treatment, and CD71 expression on other cell types must carefully be considered before targeting CD71 in humans. On the basis of these preliminary results, strategies such as bispecific antibodies that can target CD71 specifically on CD4 T cells could be a safer option for patients with SLE. In addition, given the benefits to Treg populations, CD71 targeting could also benefit patients who have a low TH17/Treg ratio by boosting Treg function and simultaneously depleting T _H 1* cells. Furthermore, other autoinflammatory T _H 17- driven diseases display iron deposits in affected tissues such as the central nervous system of patients with multiple sclerosis (MS) and the synovial fluid of patients with rheumatoid arthritis, suggesting that these findings may be relevant to inflammatory diseases beyond lupus.

Materials and Methods

Study design

For in vitro experiments, primary murine naive CD4 T cells were isolated from the spleens and LNs of female control C57BL/6 (JAX, #000664) or age-matched lupus- prone SLE1.2.3 mice (JAX, #007228) using the CD4 ⁺ CD62L ⁺ T cell isolation kit according to the manufacturer’s instructions (Miltenyi Biotec). CD62L-positive selection was routinely -98% in purity, as determined by flow cytometry. Cell cultures were activated in the presence of either anti-CD71 (BioLegend, 113821) or isotype control (lgG2a; BioLegend, 400543) at 2 pg/ml, and downstream experiments were performed between days 3 and 6 after activation. For in vivo anti-CD71 experiments, female control or age-matched SLE1.2.3 mice were treated with 200 g of CD71 -blocking antibody (clone R17217.1 ,3/TI B-219) or an isotype control antibody starting at 4 to 5 months of age (Bio X Cell). Treatment was administered twice a week via intraperitoneal injection for 4 weeks.

Mice

All experiments were performed at Vanderbilt University with Institutional Animal Care and Utilization Committee-approved protocols. Cages were maintained in a pathogen-free facility with ventilated cages and ad libitum food and water. At the time of euthanasia, a terminal blood draw was performed, and complete blood count analysis was obtained using the Forcyte (Oxford Science) hematology analyzer. Full gross examination and tissue collection were performed by a board-certified veterinary pathologist, and tissues were immersion-fixed in 10% neutral buffered formalin for about 3 days before routine processing and embedding in paraffin. Sections were cut at 5 pm and stained with hematoxylin and eosin (H&E) for analysis.

Tfrcf ^l/fl mice were purchased from the Jackson Laboratory (JAX, #028363) and bred with CD4 ^cre mice (JAX, #022071). For bm12 transfer experiments, splenocytes and LNs were isolated from Tfrc ^fl/fl homozygous mice that were either CD4 ^cre positive or negative. Flow cytometry confirmed that the percentage of CD4 T cells in the single-cell suspension was similar between Cre-negative and Cre-positive mice. About 30 x 10 ⁵ splenocytes were intraperitoneally injected into 11-week-old bm12 recipients (JAX, #001162), adjusting for CD4 T cell frequencies so that each mouse received the same number of T cells. Experiments were sex-matched such that male cells were transferred to male recipients and female donors were transferred into females. Serum samples were collected on days 3, 8, and 14 after transfer. Fourteen days after transfer was the end point of the study, at which time spleens, LNs, and kidneys were collected for flow cytometric analyses. Kidneys were placed in collagenase II (Sigma-Aldrich) in Hank’s balanced salt solution (HBSS) for 30 min at 37°C for digestion, processed through a 70- pm filter, and then subjected to a Percoll gradient to isolate the lymphocyte layer before flow cytometry.

Patient samples

Blood samples were obtained from patients with SLE, and control subjects were enrolled in the Inflammation, Cardiovascular Disease, and Autoimmunity in Rheumatic Diseases Study at the Vanderbilt University Medical Center. For inclusion in the study, all individuals were required to be 18 years of age or older. Patients required a rheumatologist diagnosis of SLE for inclusion, and all patients with SLE met the 1997 American College of Rheumatology revised classification criteria for SLE (72). Control subjects were excluded if they had an inflammatory autoimmune disease. The Vanderbilt University Medical Center Institutional Review Board approved the study (IRB no. 150544), and all individuals provided written informed consent. Clinical information was gathered via chart review by a rheumatologist. Peripheral blood was collected in heparincoated tubes. PBMCs were then isolated by Ficoll gradient separation, subjected to flow cytometry, and stored in liquid nitrogen.

Two panels of antibodies were run on patient PBMC samples. Flow cytometry was performed on freshly isolated PBMCs before long-term storage. All antibodies were purchased from BioLegend. The first panel was used to quantify CD71 and activation markers on bulk CD4 T cells [CD3-APC/Cy7 (clone HIT3a), CD4-PE/Cy7 (clone a161A1), CD25-BV605 (clone BC96), CD44-eFluor 450 (clone IM7), CD69-FITC (fluorescein isothiocyanate) (clone FN50), and CD71-APC (clone CY1G4)]. The second panel was used to quantify TH 17 cells and CD71 expression [CD3-APC/Cy7 (clone HIT3a), CD4-PE/Cy7 (clone a161A1), CXCR3-Pacific Blue (clone G025H7), CCR4- BV605 (clone L291 H4), CCR6-FITC (clone G034E3), and CD71-APC (clone CY1G4)]. Compensation was conducted using single-stain PBMC controls. A third panel was used to measure activation and memory status after activation: CD62L-Alexa Fluor 488 (clone DREG-56) and CD45RA-PECy5 (clone H1100) were used with the previous CD3, CD4, CD44, and CD71 antibodies.

For activation and culture of patient T cells, CD4 T cells were purified by negative selection using the human CD4 T Cell Isolation Kit (Miltenyi Biotec). Some samples were stored in liquid nitrogen before T cell isolations and functional assays were performed. T cells were activated with T cell activation/expansion CD2/3/28 beads at a ratio of 1:2 bead to cells (Miltenyi Biotec). Cultures were maintained in HPLM + 5% dialyzed fetal bovine serum (FBS; Sigma-Aldrich) and supplemented with recombinant human IL-2 (rhlL-2; 100 U/ml) from day 3 after activation. For CD71 blockade experiments, cells were activated in the presence of either anti-human CD71 (clone OKT9, Bio X Cell) or mouse IgG 1 isotype control (clone MOPC-21) at 2 pg/ml.

Cell cultures

Naive T cells were activated with irradiated splenocytes (irradiated at 30 gray) in the presence of anti-CD3 (1 pg/ml). Unstimulated controls were incubated with murine IL-27 (mlL-7) at 0.1 pg/ml. T cells were cultured at 37°C with 5% CO ₂ in RPMI 1640 supplemented with 10 mM Hepes, 25 M 2-mercaptoethanol, penicillin-streptomycin (100 U/ml), and 10% heat-inactivated FBS (Sigma-Aldrich). Cultures were supplemented with rhlL-2 (100 U/ml) from day 3 after activation. For differentiation of murine naive CD4 T cells, medium was supplemented with IL-12p70 (10 ng/ml), IL-2 (100 U/ml), anti-IL-4 (10 pg/ml), and anti-IFN-y (1 pg/ml) for THI cells or TGF- 1 (1.5 ng/ml), IL-2 (100 U/ml), anti-IL-4 (10 pg/ml), and anti-IFN-y (10 pg/ml) for iT _reg s. For TH17 cells, anti-IL-4 (10 pg/ml), anti-IFN-y (10 pg/ml), TGF- 1 (1 ng/ml), IL-23 (10 ng/ml), IL-6 (50 ng/ml), and IL-1 p (10 ng/ ml) were used. For human T cell differentiation, naive CD4 T cells were isolated using the Naive CD4 T Cell Isolation Kit II (Miltenyi Biotec). Human T cell TH17 cultures were activated with non-tissue culture-treated plates with plate-bound anti-CD3 (3 pg/ml), anti-CD28 (1 pg/ml), and anti-ICOS (1 pg/ml) antibodies. HPLM was supplemented with anti-IL-4 (2 pg/ml), anti-IFN-y (2 pg/ml), IL-23 (50 ng/ml), IL-1 (50 ng/ml), TGF-pi (5 ng/ml), IL-21 (25 ng/ml), and IL-6 (40 ng/ml). All cytokines were purchased from PeproTech except for I L-1 p (R&D Systems).

The Plat-E Retroviral Packaging Cell Line (American Type Culture Collection) was maintained at 37°C with 5% CO2 in Dulbecco’s modified Eagle’s medium supplemented with 10% FBS, penicillin-streptomycin (100 U/ml), puromycin (1 pg/ml), and blasticidin (10 pg/ml). Cell lines were tested for mycoplasma using the MycoProbe Mycoplasma Detection Kit (R&D Systems).

Flow cytometry

For intracellular and transcription factor stains, cells were first stained with viability dye ± cell surface antibodies, fixed and permeabilized, and then stained for intracellular proteins with the appropriate kits. Transcription factor staining consisted of the eBioscience Foxp3/Transcription Factor Staining Buffer Set. For cytokine stains, cells were restimulated with 12-myristate 13-acetate (PMA; 1 pg/ml) and ionomycin (750 ng/ml) in the presence of GOLGI PLUG and GOLGISTOP for 4 hours and then processed as other intracellular stains. Unstimulated cells served as a negative control. Antibodies for IL-10-producing T cells were as follows: CD4-e450 (clone GK1.5) and IL- 10-PE (clone JES5-16E3). For immunophenotyping panels, cells were pretreated with TruStain FcX PLUS before surface staining (BioLegend). B cells were quantified with B220-e450 (clone RA3-6B2) and CD19-APC (clone 6D5). Tregs and Tfr cells were quantified with CD4-PECy7, CD25-APC (clone PC61.5), Foxp3-e450 (clone FJK-16s), and Bcl-6-FITC (clone 7D1). Activation markers used were as follows: CD25-PE, CD44- PECy5 (clone IM7), CD69-FITC (clone H1.2F3), CD62L-APC (clone MEL-14), p-S6 (Ser235,236)-APC (clone cupk43k), and c-MAF-PE (BD, clone T54-853). For bm12 cytometry panels, gating strategies of plasma cells, GC B cells, and TFH cells followed previous methods (57). For TFH cells, CD4-SuperBright600 (Thermo Fisher Scientific, clone GK1.5), CXCR5-APC (clone L138D7), PD-1-PE (clone 29F.1A12), and ICOS- PECy5 (clone 15F9) were used. For B cells, CD19-APC (clone 6D5), CD138-BV605 (clone 281-2), GL-7-PE (clone GL7), and Fas-PerCPCy5.5 (clone SA367H8) were used.

For mitochondrial dyes, MITOTRACKER Green and MITOSOX Red (Thermo Fisher Scientific) were combined with cell surface CD4-e450 and CD71-APC antibody in complete medium at 37°C with 5% CO2 for 25 min. Labile iron staining was conducted with Bio-Tracker Far Red Labile 2+ Live Cell Dye (Millipore). Cells were first washed with HBSS and then stained for 30 min at 37°C with 5% CO ₂ in a 5 M solution of dye in HBSS. Unstimulated T cells and T cells with no dye were used as negative controls. All cells were coincubated with GHOSTREDDYE 780 (Cell Signaling Technology) along with mitochondrial dyes and gated on viable cells during analysis.

CRISPR-Cas9 screens

Details for library design and preparation were previously described. Briefly, gRNA sequences were chosen from the Brie library. Four gRNA sequences for each gene and five nontargeting controls, flanked by adapter sequences, were purchased as an oligo pool from Twist Bioscience. The iron metabolism library contained 55 total gene targets and 225 total gRNAs. The pMx-U6-gRNA-GFP vector was previously modified to express blue fluorescent protein in place of green fluorescent protein (GFP), and oligos were cloned into this vector using Gibson Assembly Master Mix. DNA was packaged into retrovirus after transfection of the Plat-E Retroviral Packaging Cell Line. Retroviral transduction of primary T cells was performed with RETRONECTIN-coated plates (Takara Bioscience). Naive T cells had been activated as described in the “Cell cultures” section for 2 days before transduction. CRISPR-Cas9 screens were conducted in HPLM and supplemented with rhlL-2 (100 U/ml) after transduction.

Collection and analysis of the gRNA frequencies over time followed the same methodology as previously described. At least 1000-fold representation of the library was maintained throughout the process of cell harvesting, amplification, and sequencing. FASTQ files were analyzed using the Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK v0.5.0.3) method to determine statistically significant gRNA enrichments or depletions. Enzyme-linked immunosorbent assays

Autoantibodies were measured with enzyme-linked immunosorbent assay (ELISA) kits purchased from Alpha Diagnostics: anti-histone total Ig, ANA total Ig, and anti-dsDNA total Ig. Serum was diluted 1 :500, and samples were run in technical duplicates. Optical density at 450 nm was measured on the CYTATION5 Imager. For cytokine measurements, serum was subjected to the LEGENDPLEX Mouse Inflammation Panel assay (BioLegend). Technical duplicates were averaged and compared with a standard curve according to the manufacturer’s protocol. IL-10 in human cell culture supernatants were measured using the LEGEND MAX Human IL-10 ELISA Kit (BioLegend). Technical duplicates were averaged and then normalized to the total number of live cells in each sample at the time of collection. Murine IL-2 concentrations were measured using the LEGEND MAX Mouse IL-2 ELISA Kit (BioLegend). Supernatants were diluted 1 :100, and absorbance values were normalized to the standard curve. HFE concentrations in patient sera were measured using the Human Hemochromatosis Protein (HFE) ELISA Kit (Abbexa, #abx387783).

Extracellular flux analyses

Extracellular flux analysis was performed with the SEAHORSE XFe96 Analyzer (Agilent). Plates were coated with Cell-Tak solution (Corning) for 30 min at room temperature before seeding the cells. A total of 150,000 viable cells were seeded per well, and a minimum of five technical replicates were seeded for each sample. Final cell counts of each well were acquired by bright-field imaging using a CYTATION5 imager for normalization. The glycolysis stress test was performed according to the Agilent protocol recommendations. The Mito Stress Test was performed with oligomycin A at 1.5 pM, carbonyl cyanide p-trifluoromethoxyphenylhydrazone (FCCP) at 1.5 pM, and rotenone/antimycin A at 0.5 pM final concentrations.

Confocal microscopy

Measurement of transferrin/CD71 internalization was adapted. CD4 T cells were activated for 3 days under T _H 0 conditions and then transferred into a 96-well U-bottom plate (150,000 cells per well). Cells were starved in phenol-red free RPMI 1640 with no serum for 45 min and then treated with mouse transferrin-horseradish peroxidase protein (0.01 mg/ml; Thermo Fisher Scientific, #31453) for the indicated time points. Cells were washed twice in phenol-red free RPMI 1640 and then transferred to poly-L- lysine-coated slides (Electron Microscopy Sciences) and rested for 15 min at 37°C with 5% CC ₂ for attachment. Samples were then immediately fixed with formalin (Sigma- Aldrich, HT501128) for 20 min at room temperature and permeabilized with 0.5% Triton X-100 for 10 min at room temperature. Samples were blocked for 1.5 hours with blocking solution [0.2% cold water fish gelatin + 0.5% bovine serum albumin in phosphate- buffered saline (PBS)] and stained with primary antibody in blocking solution overnight (anti-CD71, 2 pg/ml), washed three times for 10 min at room temperature, and then stained with secondary antibodies for 1 hour at room temperature. Secondary antibodies were as follows: goat anti-rat lgG2a-FITC (Invitrogen) 1 :1000 + Rab8-Alexa Fluor 594 (4 pg/ml; BioLegend). Images were taken at the Vanderbilt Cell Imaging Shared Resource Core using the Zeiss LSM 880 microscope at x20 magnification. At least three fields of view were captured for each biological sample for quantification of colocalization by the image calculator function on Fiji software.

RNA sequencing and quantitative reverse transcription polymerase chain reaction

Naive CD4 T cells were isolated from female healthy control or SLE1.2.3 mice and activated in T _H 17 conditions for 5 days. IL- 17a production was confirmed on day 5 by flow cytometry and was ~35 to 40% of cells in both the control or SLE1.2.3 cultures. Cells were washed with cold PBS, and RNA extraction was conducted with deoxyribonuclease treatment according to the RNeasy Plus Mini Kit (QIAGEN). mRNA enrichment and cDNA library preparation were performed using the stranded mRNA (polyadenylate-selected) library preparation kit. Sequencing was performed with paired- end 150 base pairs on the Illumina NovaSeq6000 targeting 50 million reads per sample (rps) at Vanderbilt University Medical Center’s Vanderbilt Technologies for Advanced Genomics core. Alignment percentages for all samples were above 99%. FASTQ analysis was conducted by Vanderbilt Technologies for Advanced Genomics Analysis and Research Design. Differential expression analysis criteria were as follows: fold change > 2 and false discovery rate < 0.05. Software versions were as follows: CUTADAPT v2.10, DESeq2 v1.24.0, WEBGESTALTR vO.4.4, FASTQC vO.11.9, STAR v2.7.3a, and featurecounts v2.0.0.

For quantitative reverse transcription polymerase chain reaction (qRT-PCR), RNA extraction was performed as described for RNA sequencing, and then, equal amounts of RNA for each sample were subjected to cDNA synthesis using the iScript cDNA Synthesis Kit (Bio-Rad). Tfrc transcripts were measured with primers with the same cycling conditions and instrumentation as previously described. Inductively coupled plasma mass spectrometry

To measure intracellular iron concentrations, equal cell numbers were determined and placed into metal-free 15-ml conicals (VWR). Cell pellets were washed twice with 10 ml of PBS and then stored at -80°C until downstream processing. Pellets were digested in 200 pl of Optima-grade nitric acid (Fisher) and 50 pl of Ultratrace-grade hydrogen peroxide (Sigma-Aldrich) and incubated overnight at 65°C. The next day, 2 ml of ultrapure-grade water (Invitrogen) were added before analysis.

Elemental quantification on acid-digested samples was performed using an Agilent 7700 inductively coupled plasma mass spectrometer (ICP-MS; Agilent, Santa Clara, CA) attached to a Teledyne CETAC Technologies ASX-560 autosampler (Teledyne CETAC Technologies, Omaha, NE). The following settings were fixed for the analysis: Cell Entrance = -40 V, Cell Exit = -60 V, Plate Bias = -60 V, OctP Bias = -18 V, and collision cell Helium Flow = 4.5 ml/min. Optimal voltages for Extract 2, Omega Bias, Omega Lens, OctP RF, and Deflect were determined empirically before each sample set was analyzed. Element calibration curves were generated using ARISTAR ICP Standard Mix (VWR, Radnor, PA). Samples were introduced by peristaltic pump with 0.5-mm-internal diameter tubing through a MicroMist borosilicate glass nebulizer (Agilent). Samples were initially up taken at 0.5 rps for 30 s, followed by 30 s at 0.1 rps to stabilize the signal. Samples were analyzed in Spectrum mode at 0.1 rps, collecting three points across each peak and performing three replicates of 100 sweeps for each element analyzed. Sampling probe and tubing were rinsed for 20 s at 0.5 rps with 2% nitric acid between every sample. Data were acquired and analyzed using the Agilent Mass HunterWorkstation Software version A.01.02.

Histology and immunohistochemistry

H&E sections were scored in a semiquantitative fashion by a pathologist. For liver sections, perivascular inflammatory cell infiltrates were scored on a scale from 0 to 3, where 0 represents no pathology; 1 represents mild, rare, few inflammatory cells; 2 represents multifocal to coalescing zones of inflammatory cells; and 3 represents severe, coalescing to diffuse inflammatory infiltrate. In the kidney sections, interstitial inflammation was scored using the same scoring system as described for the liver.

Immunoblot

Whole cell lysates were collected from T cell samples as described previously (75). Antibodies for immunoblot analysis were I rp2 (IREB2; Thermo Fisher Scientific, PA5-19158), HFE (Invitrogen, PA5-37364), and p-actin (Cell Signaling Technology, 3700S). Blots were incubated with IRDye anti-rabbit or anti-mouse secondary antibodies (LI-COR) and imaged using the Odyssey CLx instrument. Band intensity quantification was conducted with Studio Lite software (LI-OOR), and total protein signals were normalized to the p-actin signal for each sample.

Transmission EM

T cells were activated as described previously and supplemented with IL-2 on day 3. On day 5, cells were washed with warm PBS and then fixed in 2.5% glutaraldehyde in 0.1 M cacodylate for 1 hour at room temperature, followed by 24 hours at 4°C. After fixation, the cells were postfixed in 1 % OsO4 and en bloc stained with 1% uranyl acetate dehydrated in a graded ethanol series. Samples were gradually infiltrated with Quetol 651-based Spurr’s resin with propylene oxide as the transition solvent. The Spurr’s resin was polymerized at 60°C for 48 hours. Blocks were sectioned on a Leica UC7 ultramicrotome at 70-nm nominal thickness, and the samples were stained with 2% uranyl acetate and lead citrate. Transmission EM was performed using a Tecnai T12 operating at 100 kV with an AMT NANOSPRINT complementary metal-oxide semiconductor camera using AMT imaging software for single images and SerialEM for tiled datasets. Tiled datasets were reconstructed using the IMOD/ETomo software suite. Mitochondria quantification was done in Fiji by manually segmenting all mitochondria within cell cross sections from the tiled transmission EM datasets until at least 100 mitochondria were measured. Mitochondria area fraction was determined by summing the cross-sectional area of all mitochondria within a cell divided by the area of the entire cell.

Statistics

Statistical analyses were performed with GraphPad Prism software (v9). For all figures, statistically significant results are labeled as follows: *P < 0.05, **P < 0.01 , ***P < 0.001 , and ****P < 0.001. For a comparison of two groups, Student’s t test was performed. For more than two groups, one-way analysis of variance (ANOVA) was performed. Figures with data points connected by lines are indicative of paired analyses, whereas all other statistical tests were unpaired. In all figures, error bars represent means ± SD.

Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of skill in the art to which the disclosed invention belongs. Publications cited herein and the materials for which they are cited are specifically incorporated by reference.

Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Such equivalents are intended to be encompassed by the following claims.