WO2024156006A2 - Targeting mhc-i antigen presentation modulators for immunotherapy for cancer and autoimmune disorders - Google Patents

Abstract

Provided are compositions, methods and modified cells that are used for prophylaxis or treatment of cancer or autoimmune disorders. The compositions, methods and modified cells involve modulating expression of genes or the function of proteins that are encoded by the genes. The genes and proteins are related to expression and function of major histocompatibility complex (MHC)-I and/or peptide-MHC-I (pMHC-I).

Description

TARGETING MHC-I ANTIGEN PRESENTATION MODULATORS FOR IMMUNOTHERAPY FOR CANCER AND AUTOIMMUNE DISORDERS

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. provisional application no. 63/440,209, filed January' 20, 2023, the entire disclosure of which is incorporated herein by reference.

SEQUENCE LISTING STATEMENT

The instant application contains a Sequence Listing which is submitted in .xml format and is hereby incorporated by reference in its entirety⁷. Said .xml file is named “058636_00673_ST26.xml”, was created on January 22, 2024, and is 606,199 bytes in size.

BACKGROUND

Advances in immune checkpoint blockade (ICB) immunotherapy have reshaped the cancer treatment landscape (Sharpe and Pauken, 2018). Anti-PD-l/PD-Ll (collectively shortened to PD) therapy has been the best example demonstrating durable clinical responses with mild adverse effects across many different tumor types, by targeting general immune- evasion mechanism in the tumor microenvironment (TME) to potently repair tumor-specific T cell immunity⁷ (Sanmamed and Chen, 2018; Wang et al., 2017). The successes of anti-PD therapy are generally thought to arise from “inflamed"’ tumors with abundant tumor-specific CD8⁺ T cell responses, which are needed to effectively mount a cytotoxic response that eliminates tumor cells. However, many tumors are immunologically “cold” and lack significant T cell infiltration, resulting in a large subset of patients not responding to anti-PD therapy or developing acquired resistance. These results emphasize the need to identify new therapeutic strategies beyond the PD pathway for cold tumors that not only boost the activity, but also the specificity and quantity of CD8 T cells.

The major histocompatibility' complex class I (MHC-I, also referred to as human leukocyte antigens (HLA) in human) antigen presentation (AP) pathway determines the specificity of CD8⁺ T cells, and is essential for their activation and proliferation. Myeloid cells, as professional antigen presentation cells (APCs), and some tumor cells are capable of processing self or tumor antigens to form stable peptide-MHC-I (pMHC-I) complexes on the cell surface, which engage CD8⁺ T cells through antigen-specific T cell receptor (TCR) and triggers CD8⁺ T cell responses. Genetic mutations and deletions in genes involved in various components of the antigen presentation machinery' (APM), such as MHC-1 and Beta-2 microglobulin (B2m) (pMHC-I complex) (Rooney et al., 2015; Shukla et al., 2015), calreticulin (Arshad and Cresswell, 2018; Nangalia et al., 2013) and tapasin (Shionoya et al.. 2017; Sokol et al., 2015) (MHC-I peptide loading), CITA (also known as NLRC5) (Yoshihama et al., 2016) and IRF2 (Kriegsman et al., 2019) (MHC class I transcription activator), and JAK1/JAK2 (MHC-I induction through interferon-signaling pathway) (Schroder et al., 2004; Shin et al., 2017) have been implicated in tumor progression, as well as the resistance to immune checkpoint blockade (Nowicki et al., 2018; Shin et al., 2017). These examples, however, likely do not represent the general mechanisms leading to low immunogenicity in most tumors. Further, re-introducing or over-expressing these factors specifically in the TME may be difficult as a therapeutic strategy.

In addition to the reduction of APM essential factors, tumors may actively escape cytotoxic CD8 T cell response through inhibiting AP, a typical immune evasion mechanism seen in many viral infections but poorly studied in cancers. Viruses can produce a number of viral factors that actively inhibit various steps of MHC-I AP pathways, including a subset that directly associates with membrane-associated MHC-I. For instance, the murine cytomegalovirus (MCMV) protein GP48/M06 and the SARS-CoV-2 protein ORF7A has been shown to directly interact with the a chain of MHC-I and destabilize its association with B2M, resulting in low levels of viral antigen presentation (Arshad et al., 2022; Sgourakis et al., 2015). Additionally, the Epstein-Barr Virus G-protein-coupled receptor BILF1 contributes to viral immune evasion by specifically targeting MHC-I internalization and degradation (Zuo et al., 2009). However, endogenous AP inhibition mechanisms in immune homeostasis and cancers remain largely unknown. A few recent studies have suggested that autophagy or cholesterol-regulating soluble protein PCSK9 can mediate MHC-I degradation or disrupt MHC-I recycling, respectively, in the context of solid tumors (Liu et al., 2020; Yamamoto et al.. 2020). Transcription/epigenetic repressors TRAF3 and EZH2, as well as thymidylate synthase (also required for DNA replication and repair), were identified as MHC-I inhibitors by CRISPR screens on regulators of MHC-I expression (Burr et al., 2019; Dersh et al., 2021; Gu et al., 2021). How ever, these examples are likely not specific for MHC-I modulation as they have many other important cellular functions. Their precise roles in regulating tumor antigenic pMHC-I are still unclear. Together with the emerging evidence suggesting low' and variable percentage of tumor-reactive T cells in the TME (Scheper et al., 2019), there is an increasing need to identify more cancer-specific AP regulation mechanisms, which could be used as specific targets to increase the quality and quantity of tumor-specific CDS T cells. Further, acute myeloid leukemia (AML), an aggressive clonal hematopoietic neoplasm, is the malignant counterpart of myeloid progenitor cells with a poor clinical outcome (15-30% five-year overall survival) (Burnett et al., 1998; Ries LAG; Thein et al.. 2013). Its low mutation burden (Jimbu et al., 2021) and the lack of leukemia-specific CD8⁺ T cells may explain why the majority of AML patients do not respond well to current immunotherapy (Daver et al., 2021; Isidori et al., 2021; Sehgal et al., 2015). It has also been shown that the antigen presentation machinery (APM) genes are dysregulated in AML and further downregulated upon conventional therapies (Davidson-Moncada et al., 2018; Hoves et al.. 2009). Therefore, to treat AML. as well as other types of cancer and ‘"cold’⁷ tumors, there is an ongoing need to develop new' strategies to increase immunogenicity and increase anti-tumor immunity. Additionally, APM and related mechanisms participate in the development and progression of autoimmune diseases, for which new' treatment approaches are needed. The present disclosure is pertinent to these and other needs.

BRIEF SUMMARY

This disclosure provides compositions, methods, and modified cells for use in prophylaxis or therapy for cancer or autoimmune diseases. The method comprises modulating major histocompatibility complex (MHC)-I and/or peptide-MHC-I (pMHC-I) gene expression or function of proteins encoded by the genes. Genes that are involved in a membrane-associated antigen presentation inhibitory axis that involve MHC-I, pMHC-I, and both, are identified in this disclosure. Representative and non-limiting examples of the genes include SIJS 6. TMEM127, WWP2. STUB1, w LRPlO.

In one embodiment the disclosure provides for decreasing the expression of at least one described gene, or inhibiting the function of a protein encoded by at least one described gene. This approach can be used for prophylaxis or therapy for any type of cancer. In embodiments the cancer is resistant to an immune therapy, such as immune checkpoint inhibition.

In one embodiment the disclosure provides for increasing the expression of at least one described gene, or enhancing the function of a protein encoded by at least one described gene. This approach can be used for prophylaxis or therapy of autoimmune disorders.

The disclosure includes isolated cells that are modified such that expression of a described gene is changed, relative to expression of the same gene in unmodified cells.

The disclosure includes isolated cells that are modified such that function of a protein encoded by a described gene is changed, relative to function of the protein in unmodified cells. This disclosure includes use of the described modified cells in adoptive immunotherapies.

In embodiments cells that are modified according to the disclosure may be any cells that express MHC-I. In non-limiting embodiments the cells are macrophages, dendritic cells, natural killer (NK) cells, T cells which are optionally 0 or y5 T cells, or cancer cells. In embodiments a modified cell may express a chimeric antigen cell receptor (CAR). The CAR may be targeted to any antigen expressed by cancer cells, or cells that are involved in an autoimmune disorder.

The cells can be modified using a variety of approaches, which include use of therapeutic or prophylactic polynucleotides such as RNAi agents (e.g., shRNA/siRNA), antisense oligonucleotides, DNA editing systems, small drug molecules, peptide agents, antibodies and antibody derivatives, and the like.

In an embodiment the disclosure provides for diagnosis or prognosis for an individual who has or may be susceptible to developing cancer or an autoimmune disorder. The method includes determining gene or protein expression from the genes identified herein, and comparing the expression to a control value. The control value can be obtained from one or a series of individuals who do not have cancer or an autoimmune disorder, depending on the particular condition being analyzed. Based on a diagnosis or prognosis, the individual can be treated according to the methods of this disclosure.

BRIEF DESCRIPTION OF THE FIGURES

Figure 1. Systematic identification of antigen-specific AP inhibitors in AML using pMHC-I-guided CRISPR screens. (A) Schematic outline of the generation of antigen-specific AP reporters and the pMHC-I-guided genome-wide CRISPR/Cas9 loss-of- function screens in both human and mouse AML cell lines. (B and C) Waterfall plot depicting the selected positive and negative AP regulators identified in the human (HLA- A2:AFP, B) and mouse (H-2K^b:0VA, C) antigen-specific AP screens. Green: novel negative AP regulators, blue: published negative MHC-I regulators, orange: known positive AP regulators. (D and E) Frequency histograms on the log fold changes of the negative control guides (top), and selected regulators in the human (D) and mouse (E) antigen-specific AP screens. Green: novel negative AP regulators, blue: published negative MHC-I regulators, orange: known positive AP regulators. (F) Heatmap showing the surface levels of HLA- A2: AFP or H-2K^b:0VA and the expression levels of AFP or OVA antigen (denoted by the BFP level) in human or mouse reporters, respectively, transduced with the indicated sgRNAs targeting the selected candidates. The mean values from three biological replicates for each sgRNA were used to plot the heatmap. (G) Venn diagram of the common negative AP regulators in the human HLA-A2:AFP screen (log fold change > 0.5, p < 0.05) and the mouse H-2K^b:OVA screen (log fold change > 2, p < 0.05). (H) STRING protein-protein interaction (PPI) network of the 78 common negative AP regulators as defined in (G). The minimum required interaction score was set to 0.4. k-means clustering was applied. Bubble size denoted the combined log fold changes in both screens and the thickness of lines denoted the STRING PPI score/confidence.

Figure 2. Profiling functional AP inhibitors via in vivo screen. (A) Waterfall plot depicting the selected positive and negative MHC-I regulators identified in the human pan- HLA (HLA-ABC) screen. Green: novel negative MHC-I regulators, blue: published negative MHC-I regulators, orange: known positive MHC-I regulators. (B) Frequency histograms of the log2 fold changes of the negative control guides (top), and selected genes in the human pan-HLA screen. Green: novel negative MHC-I regulators, blue: published negative MHC-I regulators, orange: known positive MHC-I regulators. (C) Three-dimensional plot demonstrating the significantly selected hits from all three screens. Top-ranked negative regulators (green) and positive regulators (orange) are highlighted. (D) Venn diagram of the negative regulators in the human antigen-specific AP screen (log fold change > 0.5, p < 0.05), the human pan-HLA screen (log fold change > 0.5, p < 0.05) and the mouse antigen-specific AP screen (log fold change > 2, p < 0.05). The 44 common negative AP regulators that modulate both pMHC-I and MHC-I levels are listed below in order of their enrichment score. (E) Enrichment analyses comparing the 44 gene set, and the 34 gene set that mainly modulate pMHC-I in different categories of biological functions defined in Fig. 1H (top 4 groups) and proportion of putative surface proteins (bottom group). (F) Waterfall plot depicting the 44 (green) and 34 (orange) negative AP regulators identified in (D). Putative surface proteins are highlighted in red. (G) Schematic outline of the functional in vivo focused screens in the mouse AML cell line C1498. (H) Scatter plots showing the non-cssentiality of each candidate identified by in vitro cell growth (Y -axis) and the in vivo CTL selectivity of each targeted gene identified by comparison of tumors from Isotype versus anti-CD8 mAb-treated mice (X- axis). The 44 common negative AP regulators were highlighted in red, and the known MHC-I regulators were highlighted in blue. (I) Heatmaps showing the log fold changes of the 44 common negative AP regulators in the indicated screens.

Figure 3. SUSD6 depletion enhances AP and promotes CD8⁺ T cell-mediated AML immunity. (A and B) Representative histogram (left) and bar plot (right) showing the surface levels of HLA-A2:AFP (A) or HLA-A2 (B) in human THP-1-Cas9-AFP-BFP cells transduced with the indicated sgRNAs. (n=3). (C- and D) Representative histogram (left) and bar plot (right) showing the surface levels of H-2K^b:0VA (C) or H-2K^b (D) in mouse RN2- Cas9-OVA-BFP cells transduced with the indicated sgRNAs. (n=3). (E) Schematic of the T cell activation assay: sgRNA-transduced RN2-Cas9-OVA-BFP cells were fixed and incubated with B3Z T cell hybridoma. followed by ELISA to quantify IL-2 secretion. (F) Bar plot showing the IL-2 secreted by B3Z T cell hybridoma incubated with RN2-Cas9-OVA- BFP cells transduced with the indicated sgRNA (n=3). (G) Schematic of the mouse T cell killing assay: sgRNA-transduced RN2-Cas9-OVA-BFP cells were co-cultured with OT-I T cells, which recognize the H-2K^b:0VA molecules presented by the RN2-Cas9-OVA-BFP cells. (H) Bar plot showing the percentages of sgRNA-transduced RN2-Cas9-OVA-BFP cells killed by the OT-I T cells described in (G). (n=3). (I) Schematic of the human T cell killing assay: THP-1-Cas9 cells were co-cultured with human primary T cells transduced with the anti-NY-ESO-1 TCR, which recognizes the SLLMWITQC peptide derived from NY-ESO-1, presented by HLA-A*02:01 on the THP-1-Cas9 cells. (J) Bar plot showing the percentages of sgRNA-transduced NY-ESO-l-expressing THP-1-Cas9 cells killed by the NY-ESO-1 TCR-T cells described in (I). (n=3). (K) Schematic of the in vivo experiments performed to validate the function of SUSD6 in a mouse syngeneic AML model. (L and M) Quantification of the tumor volumes (L) and Kaplan-Meier survival curves (M) of mice transplanted with Cl 498- Cas9 tumor cells transduced with the indicated sgRNAs as described in (K). (n=4 for sgNT and n=6 for sgSusd6). (O and P) Quantification of the tumor volumes (O) and Kaplan-Meier survival curves (P) of CD8⁺ T cell-depleted mice transplanted with C1498-Cas9 tumor cells transduced with the indicated sgRNAs. (n=5 for sgNT and n=6 for sgSusd6). (R) Violin plot of SUSD6 (KIAA0247) mRNA expression levels in normal HSPCs (HSC, MPP. CMP, GMP, MEP, early promyelocyte, and late promyelocyte), MDS cells, and AML cells with different karyotypes from patient samples. HSPCs, hematopoietic stem and progenitor cells; HSC, hematopoietic stem cell; MPP, multipotent progenitor; CMP, common myeloid progenitor; GMP, granulocyte-monocyte progenitor; MEP, megakaryocyte-erythrocyte progenitor; MDS, myelodysplastic syndromes. Data were obtained from BloodSpot (Bagger et al., 2016). (S) Survival of AML patients with high (red line) or low (blue line) expression of SUSD6 in the TCGA-AML cohort. (T) Pearson correlation of SUSD6 expression levels in AML cells and T cell activation signature (CD3E, GZMB, CX3CR1, FGFBP2, PRF1) in CD8⁺ T cells from bone marrow immuno-microenvironments from AML patients. Data were generated by single-cell RNA-seq. Data are presented as the mean ± SEM. *, p< 0.05; **, p< 0.01; and ***, p< 0.001 by two-tailed unpaired Student's /-test (A-D, F, H, and J), two-way ANOVA for the last time point (L and O). or Log-rank Mantel-Cox test (M and P). Data are presented as the mean ± SEM. ns, not significant: *, p< 0.05, **, p< 0.01; and ***, p< 0.001 by oneway ANOVA (E), two-tailed unpaired Student’s /-test (F-H, and J), or two-way ANOVA for the last time point (K).

Figure 4. SUSD6 suppresses AP and facilitates solid tumor-associated immunoevasion. (A and B) Quantification of the tumor volumes (A) and Kaplan-Meier survival curves (B) of mice transplanted with B16F10-OVA cells transduced with the indicated shRNAs as described in Fig. 10D. (n=5 for shRen, n=10 for shSusd6). (C and D) Quantification of the tumor volumes (C) and Kaplan-Meier survival curves (D) of mice transplanted with CT26 cells transduced with the indicated shRNAs as described in Fig. 10D. (n=4 for shRen, n=6 for shSusd6). (E and F) Quantification of the tumor volumes (E) and Kaplan-Meier survival curves (F) of CD8⁺ T cell-depleted mice transplanted with B16F10- OVA cells transduced with the indicated shRNAs. (n=5). (G and H) Quantification of the tumor volumes (G) and Kaplan-Meier survival curves (H) of CD8⁺ T cell-depleted mice transplanted with CT26 cells transduced with the indicated shRNAs. (n=7). (I) Representative image of the B16F10-OVA tumors transduced with the indicated shRNAs. Tumors were isolated for further analyses (J-Q) at day 15 after tumor cell transplantation. (J and K) Weights (J) and tumor cell numbers (K) of the B16F10-OVA tumors transduced with the indicated shRNAs. (n=9). (L) Median fluorescence index (MFI) of surface H-2K^b/H-2D^b in Bl 6F10-OVA tumors transduced with the indicated shRNAs. (n=9). (M) Bar plot of a quantitative estimation of CD8⁺ T cells normalized by tumor cell in control and SUSD6- knockout B16F10-OVA tumors, as determined by flow cytometry. (n=9). (N-Q) Representative flow cytometry plots (N and P) or quantification (O and Q) of IFN-y and Granzyme B production in CD8⁺ T cells infiltrated into the B16F10-QVA tumors transduced with the indicated shRNAs. (n=8). Data are presented as the mean ± SEM. ns, not significant; *, p< 0.05; **, p< 0.01; and ***, p< 0.001 by two-tailed unpaired Student’s /-test (J-M and O-Q), two-way ANOVA for the last time point (A, C. E, and G), or Log-rank Mantel-Cox test (B. D, F. and H).

Figure 5. SUSD6 targets MHC-I for lysosomal degradation. (A) Western blot analysis of HLA-A and B2m THP1 cells transduced with sgRosa or sgSUSD6. Representative western blots are shown on the left, and protein band quantitation is shown on the right (the expression values from sgSUSD6 was normalized to sgRosa, n=5). (B and C) Internalization of surface HLA-A2 in THP1 with and without sgSUSD6 knockout. Schematic of experiment design was shown in (B), and representative surface HLA-A2 quantification by flow cytometry was shown in (C) (n=3). (D-F) Time course study of surface HLA-A2 expression on THP1 cells with or without SUSD6 knockout and Cycloheximide (CHX, D), Bafilomycin Al (BafAl, E), or Epoxomicin (Epox, F) treatment (n=3). (G) Representative confocal images showing the subcellular localization of HLA-A2 in 293T cells with or without SUSD6 overexpression. Scale bar: 5pM. Data are presented as the mean ± SEM. ns. not significant; ***, p<0.001 by two-tailed paired Student’s /-test (A) or two-way ANOVA for the last time point (C-F).

Figure 6. Targeting the SUSD6/TMEM127/WWP2 complex for potential therapeutic restoration of AP-mediated immune surveillance. (A) mRNA co-expression analysis of TMEM127 (left) and WWP2 (right) with SUSD6 in AML. Data were obtained from the TCGA database. (B) Immuno-precipitation using anti-FLAG antibody or anti-HA antibody in 293T cells transduced with SUSD6-FLAG, TMEM127-HA, and WWP2-V5. IP, immunoprecipitation; IB, immunoblotting. (C) Schematic (left) of the split-luciferase experiments and the normalized relative luminescence units (RLU) (right) to demonstrate the interaction among HLA-A2, SUSD6 and TMEM127 in 293T cells by co-transfection of indicated small NanoBit- (smBit) or large NanoBit- (IgBit) tagged proteins (n=6). (D) Tripartite Split-GFP analysis of the HLA-A2/SUSD6/TMEM127 complex, where GFP signal can only be generated when three subunits of GFP come in proximity. Representative confocal images showing co-localization of the HLA-A2/SUSD6/TMEM127 complex w ith CD107A⁺ lysosomes in 293T cells co-transduced with GFP-TlO-tagged HLA-A2, GFP1-9- tagged SUSD6, and GFP-T11 -tagged TMEM127. 293T cells transduced with HLA-A2-T10 served as the negative control. Scale bar: 5pM. (E) Schematic (left) of the split-luciferase experiments and the normalized relative luminescence units (RLU) (right) to demonstrate the interaction between WWP2 and SUSD6 or TMEM127 in 293T cells by co-transfection of indicated small Bit- (smBit) or large Bit- (IgBit) tagged proteins (n=6). (F) Schematic (left) of the split-luciferase experiments and the normalized relative luminescence units (RLU) (right) to demonstrate the interaction between WWP2 and HLA-A2, in the presence of TMEM127 and/or SUSD6, in 293T cells by co-transfection of indicated small Bit- (smBit) or large Bit- (IgBit) tagged proteins (n=5). (G) Expression of STW gene signature in AML (red) and normal tissue (green). Data were obtained from the TCGA database and analyzed by GEPIA2. (H) Association of high or low STW gene signature with overall survival of AML patients in the TCGA database by SurvivalGenie. (I-L) Tumor growth (I and K) and Kaplan- Meier survival (J and L) curves of mice transplanted with C1498-Cas9-GFP cells transduced with the indicated sgRNAs without (I and J) or with (K and L) CD8⁺ T cell depletion. (For I and J: n=4 for sgNT and n=6 for sgTmeml27, for K and L: n=7). (M-P) Tumor growth (M and O) and Kaplan-Meier survival (N and P) curves of mice transplanted with B16F10-OVA cells transduced with the indicated shRNAs without (M and N) or with (O and P) CD8⁺ T cell depletion. (For M and N: n=4 for shRen and n=10 for shTmeml27, for O and P: n=7). Data are presented as the mean ± SEM. ns, not significant; *. p< 0.05; **, p< 0.01; and ***. p< 0.001 by one-way ANOVA (C and E), two-tailed unpaired Student’s t-test (F), two-way ANOVA for the last time point (I, K, M, and O), or Log-rank Mantel-Cox test (J, L, N, and P).

Figure 7. Genome-wide CRISPR screens of antigen-specific AP in human and mouse cell lines. Related to Figure 1. (A) Antigen presentation machinery (AMP) scores among various cancer types calculated as described (Wang et al., 2019). Data were derived from the TCGA database. (B) Flow-cytometric analysis of the human THP-1 AP reporter cell line (THP-1 -Cas9-AFP-BFP) on the levels of antigen and antigen-specific AP. (C) Flowcytometric analysis of the mouse RN2 AP reporter cell line (RN2-Cas9-OVA-BFP) on the levels of antigen and antigen-specific AP. (D) Venn diagram of the common positive AP regulators in the human HLA-A2:AFP screen (log fold change < -0.5, p < 0.05) and the mouse H-2K^b:OVA screen (log fold change < -2, p < 0.05). (E) STRING protein-protein interaction network of the 105 commonly selected hits defined in (C-D). The minimum required interaction score was set to 0.4. k-means clustering was applied. Bubble size denoted the combined log fold changes in both screens and the thickness of lines denoted the STRING PPI score/confidence.

Figure 8. Analyses of in vitro CRISPR screens. Related to Figure 2. (A) Schematic outline of the pan-HLA screen in OVA-expressing human THP-1 cells. (B) Venn diagram of the positive AP regulators in the human antigen-specific AP screen (log fold change < -0.5, p < 0.05), the human pan-AP screen (log fold change < -0.5, p < 0.05) and the mouse antigenspecific AP screen (log fold change < -2, p < 0.05). The 21 common positive AP regulators that modulate both pMHC-I and MHC-I were listed in order of their enrichment score. (C) Gene Ontology analysis of the 21 common positive AP regulators from all three screens. (D) Gene Ontology' analysis of the 84 positive AP regulators predominantly modulate pMHC-I as defined in (B). (E) Gene Ontology analysis of the 44 common negative AP regulators from all three screens. (F) Gene Ontology analysis of the 34 negative AP regulators predominantly modulate pMHC-I as defined in Fig. 2D. (G) Violin plots comparing the log fold changes of the HLA-A2:AFP screen for the candidates from the 44 gene set with those from the 34 gene set. *, p< 0.05 by two-tailed unpaired Student's t-test.

Figure 9. SUSD6 is a plasma membrane protein that potently inhibits AP in AML. Related to Figure 3. (A) Schematic of the topological domains of human SUSD6. (B) Representative flow cytometry surface staining of KASUMI-1 cells transduced with Vector control, FLAG-SUSD6 (FLAG tag fused in the N-terminal of SUSD6). and SUSD6-FLAG (FLAG tag fused in the intracellular C-terminal of SUSD6) by an anti-FLAG antibody. (C and D) Western blots of SUSD6 protein levels from Cas9-expressing THP1 whole cell lysates (C) and RN2 whole cell lysates (D) transduced with the indicated sgRNA. (E) Bar plots showing the surface HLA-ABC (left) and HLA-A2 (right) levels rescued by overexpressing the SUSD6 coding sequence (CDS) in SUSD6-deficient THP-1 cells examined by flow cytometry. (n=3). (F and G) Flow cytometric analysis of surface HLA- ABC and HLA-Bw6 levels in Cas9-expressing MV4-11 (F) and KASUMI-1 (G) transduced with the indicated sgRNAs. (n=3 for sgRosa, n=6 for sgSUSD6). (H) Bar plots showing the surface levels of HLA-A2:AFP (left) and HLA-ABC (right) examined by flow cytometry’ in THP-1 -Cas9-AFP-BFP cells transduced with the indicated sgRNAs with or without IFN-y treatment (0.5 ng/ml). (n=6). (I) Western blots of SUSD6 protein levels of whole cell lysates from C1498-Cas9-GFP cells transduced with the indicated sgRNAs (Blue arrow, Susd6 band; orange arrow, non-specific band). (J) Flow cytometric analysis of surface H-2K^b/H-2D^b level in C1498-Cas9-GFP cells transduced with the indicated sgRNAs. (n=3). (K) In vitro cell growth of C1498-Cas9-GFP transduced with the indicated shRNAs as described in Fig. 3K. (n=8)

Figure 10. SUSD6 is a general cancer-associated AP inhibitor. Related to Figure 4. (A) SUSD6 mRNA relative levels in normal human tissues (grey) and immune subsets (blue) from BioGPS database (Su et al., 2004; Wu et al., 2013). (B) SUSD6 mRNA relative levels in human cancers (red) and corresponding normal tissues (green). CHOL, Cholangiocarcinoma; GBM, Glioblastoma multiforme; LAML, Acute Myeloid Leukemia; LGG, Brain Lower Grade Glioma; PAAD, Pancreatic adenocarcinoma. Data were obtained from the TCGA database. (C) Normalized MFI of surface H-2K^b/H-2D^b and H-2K^d/D^d in Cas9-expressing tumor cell lines transduced with the indicated sgRNAs by flow cytometry. (n=3). (D) Schematic outline of the mouse models for in vivo studies to validate the function of Susd6 using syngeneic solid tumor cell lines. (E and G) Western blot data of Susd6 protein levels in B16F10-OVA cells (E) or CT26 cells (G) transduced with the indicated shRNAs.. (F and H) Relative Susd6 mRNA levels in B16F10-OVA cells (F) or CT26 cells (H) transduced with the indicated shRNAs. Expression data were generated by real-time PCR and were normalized to the shRen control (n=3). (I) Flow cytometric analysis of surface H-2K^b/H-2D^b level in B16F10-OVA cells transduced with the indicated shRNAs. (n=3). (J) Flow cytometric analysis of surface H-2K^d/H-2D^d level in CT26 cells transduced with the indicated shRNAs. (n=3). (K and L) In vitro cell grow th of B16F10-OVA (K) and CT26 (L) transduced with the indicated shRNAs. (n=4). Data are presented as the mean ± SEM. ns, not significant; *, p< 0.05; **, p< 0.01; and ***, p< 0.001 by two-tailed unpaired Student’s t-test (C. F, H. I, and J) or two-way ANOVA for the last time point (K and L).

Figure 11. SUSD6 regulates MHC-I level through post-translational mechanisms. Related to Figure 5. (A) RT-qPCR analysis of genes involved in antigen processing and presentation upon SUSD6 knockout in THP1 cells. (n=3). (B) Flow cytometry plots showing the parentages of OP-Puro labeled THP-1 cells with or without SUSD6 knockout. (C) Quantification of the proportion of OP-Puro⁺ (as an indicator of active translation) cells (left) and the MFIs of the OP-Pure signals in the OP-Pure⁺ THP- 1 cells (right) with or without SUSD6 knockout. (n=3 for sgRosa, n=6 for sgSUSD6). (D) Schematic of the mechanism of regulation of surface MHC-I by Cycloheximide (CHX), Bafilomycin Al (BafAl), and Epoxomicin (Epox). Data are presented as the mean ± SEM. In C, ns, not significant by two- tailed unpaired Student’s t-test.

Figure 12. The SUSD6/TMEM127/WWP2 complex is a potential therapeutic target for the restoration of tumor AP. Related to Figure 6. (A and B) mRNA coexpression analysis of TMEM127 (A) and WWP2 (B) with SUSD6 in COAD and LIHC tumors. COAD, Colon adenocarcinoma; LIHC; Liver hepatocellular carcinoma. (C) Immunoprecipitation using anti-FLAG or anti-HA antibodies in 293T cells transduced with SUSD6- FLAG and TMEM127-HA. Grp94 (an ER lumen protein), PDL1 (a membrane protein), and p-actin (a cytosolic protein) served as negative controls. (D and E) Detection of GFP signal in 293T cells transduced with the indicated genes and treated with or without BafAl by flow cytometry. Representative flow cytometry plots are shown in (D) and quantification is shown in (E). (n=3). (F) Immuno-precipitation using the anti-Ubiquitin antibody in THP1 cells transduced with the indicated shRNA. Black arrow, unspecific band; right brackets; ubiquitinated HLA-A. (G) Flow cytometry analysis of surface HLA-A2 expression in THP1- Cas9 cells transduced with the indicated sgRNA. (n=3). (H) Immuno-precipitation using anti- FLAG antibody in 293T cells transduced with SUSD6-FLAG and STUB1-V5 (blue words), or TMEM127-FLAG and STUB1-V5 (orange w^?ords). (I) Expression of STW gene signature in pancreatic ductal adenocarcinoma (PAAD) (red) and relevant normal tissue (green). Data were obtained from TCGA database and analyzed by GEPIA2. (J) Association of high or low STW gene signature with overall survival of PAAD patients in the TCGA database by SurvivalGenie. (K-O) Western blot (K, L, N) and RT-qPCR (M, O) to validate Tmeml27 knockdown efficiency in C1498-Cas9 (K), B16F10-OVA (L-M), and CT26 (N-O). (For M: n=3, for O: n=3 for shRen and n=4 for shTmeml27). (P) Knocking down Tmeml27 enhanced tumor antigen presentation in C1498-Cas9 cells (left), B16F10-OVA cells (middle), and CT26 cells (right). (n=3 for all conditions). (Q) In vitro growth of C1498-Cas9 cells (left), B16F10-OVA cells (middle) and CT26 cells (right) transduced with the indicated sgRNAs or shRNAs. (For C1498-Cas9-GFP: n=3 for sgNT and n=6 for sgTmeml27, for B16F10-OVA: n=6, for CT26: n=3). (R-U) Tumor growth (R and T) and Kaplan-Meier survival (S and U) curves from mice transplanted with CT26 cells transduced with the indicated shRNA with (R and S) or without (T and U) CD8⁺ T cell depletion. (For R and S: n=4 for shRen and n=5 for shTmeml27, for T and U: n=7). Data are presented as the mean ± SEM. ns. not significant; *, p< 0.05; and ***, p< 0.001 by two-way ANOVA (E), one-way ANOVA (G), two-tailed unpaired Student's /-test (M. O, and P), two-way ANOVA for the last time point (Q, R, and T), or Log-rank Mantel-Cox test (S and U). In (C), (F), and (H), IP, immunoprecipitation; IB, immunoblotting.

Figure 13. Graph showing that SUSD6 and TMEM127 are upregulated in the hematopoietic lineages and expression of SUSD6 and TMEM127 in normal human tissues .

Figure 14. Tmeml27 ablation enhances MHC-I expression in vivo. (A-D) Flow cytometry of surface MHC-I (H2-Kb/H2-Db) in myeloid cells isolated from bone marrow (A), lymph node (B), or spleen (C) of WT or Tmeml27 KO mice. (D) Percentages of different lymphoid lineages in the spleens of WT or TMEM127 KO mice.

Figure 15. Targeting positive or negative antigen presentation modulators in CAR macrophages to restore tumor antigen presentation. Schematics of targeting MHC-I antigen presentation positive or negative regulators to enhance MHC-I antigen presentation in the CAR macrophage for better control of tumors.

Figure 16. Data showing SUD6 and TMEM127 regulate MHC-1 expression in professional APCs. (A-B). Flow cytometry of surface MHC-I (H2-K^h/H2-D^b) in APCs isolated from the spleens of WT, Susd6 (KO) (A) or Tmeml24 KO (B) mice. (C-D) Flow cytometry analysis of lymphocytes isolated from WT. Susd6 (KO) (C) or Tmeml27 (KO) mice spleens. (E-F) representative dot plots of CD4+ and CD8+ (F) T cells from isolated WT or TMEM127 KO mice spleens. Figure 17. Cartoon representation illustrating non-limiting differences between wild ty pe cells (left), and modified cells (right), where SUSD6 and TMEM127 expression has been repressed. The effects on MHC-I processes and on T cell responses are depicted.

DETAILED DESCRIPTION

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 invention belongs.

Throughout this application, the use of the singular form encompasses the plural form and vice versa. For example, “a", or “an” also includes a plurality of the referenced items, unless otherwise indicated.

Where a range of values is provided in this disclosure, it should be understood that each intervening value, and all intervening ranges, between the upper and lower limit of that range is also included, unless clearly indicated otherwise. The upper and lower limits from within the broad range may independently be included in the smaller ranges encompassed within the disclosure.

When values are expressed as approximations, by the use of the antecedent “about” and “approximately” it will be understood that the particular value forms another embodiment. The term “about” and “approximately” in relation to a numerical value encompasses variations of +/-10%, +/- 5%, or +/- 1%.

The disclosure includes all polynucleotides and amino acid sequences described herein. All polynucleotides described herein include complementary sequences. All DNA sequences described herein include RNA sequences that are the same as the DNA sequences, except for the T to U substitution, and all complementary RNA sequences. The sequences of all polynucleotides and proteins that are referenced by way of a database are incorporated herein as the sequences exist in the database as of the effective filing date of this patent application.

The disclosure provides novel methodologies to enhance MHC-I antigen presentation with for use with cancer immunotherapy and autoimmune disorders. In an embodiment the disclosure provides for genetic modulation of cancer by genetically modifying the cells to overexpress or under express certain genes as further described herein.

In one embodiment the disclosure provides a method comprising modifying a cell by modulating MHC-I and/or peptide-MHC-I (pMHC-I) expression and/or function of the cell by modulating expression of at least one gene that is a component of a membrane-associated antigen inhibitory axis within the cell, or by contacting the cell with an agent that is targeted to at least one protein encoded by said at least one gene to inhibit function of the protein. Enhancing protein function is also encompassed by the disclosure, such as for use with autoimmune disorders.

In embodiments representative and non-limiting examples of genes that can be modulated (along with modulating the proteins the encode) include SUSD6. TMEM127, LRP10. WWP2 and STUB1. The disclosure is not limited to these genes. In embodiments, the described genes are selected from Table A, which provides accession numbers for the proteins encoded by the genes. In embodiments a method of the disclosure comprises decreasing expression of at least one gene or inhibiting the function of a protein encoded by said at least one gene to thereby increase the MHC-I expression or function, the pMHC-I expression or function, or a combination thereof. For this purpose at least one gene is selected from the group of genes of column 3) and column 4) of Table A.

The disclosure also includes increasing expression of at least one gene to thereby increase the MHC-I and/or pMHC-I expression and/or function. For this purpose at least one gene is selected from group of genes of column 1) and column 2) of Table A.

The disclosure includes modified cells that are genetically modified as discussed above. Non-limiting examples of cells that can be modified are discussed further below. In certain embodiments the modified cell is an antigen presenting cell, a cancer cell, a macrophage, a dendritic cell, an a[3 or

T cell or a natural killer (NK) cell. In a non-limiting embodiment the cell that is modified is a macrophage. The macrophage (or other immune cells described herein) may be a chimeric antigen receptor (CAR) expressing cell, wherein the CAR is targeted to specific antigens, including but not necessarily limited to cancer antigens. A non-limiting and representative CAR macrophage and targeting of it is shown in the accompanying figures.

The disclosure also provides a method for prophylaxis or treatment of a condition for an individual in need thereof. The individual may be in need of prophylaxis or treatment of cancer or an autoimmune disease. In general, the disclosure includes the proviso that for autoimmune diseases, the method involves reducing MHC-I expression.

In embodiments, the disclosure provides a method that comprises: i) administering to the individual at least one agent that inhibits expression of at least one gene that is selected from the group of genes of column 3) and column 4) of Table A, or administering to the individual an agent that is targeted to at least one protein encoded by said at least one gene; or ii) administering to the individual at least one agent that increases expression of at least one gene that is selected from the group of genes of column 1) and column 2) of Table A; or iii) administering to the individual modified cells that have been modified to increase expression of at least one gene selected from the genes of Table A, column 1 and column 2; or iv) administering to the individual modified cells that have been modified to decrease expression of at least one gene selected from the genes of Table A, columns 3) and 4); or v) administering any combination of i). ii), iii) and iv).

In embodiments the disclosure provides a method compnsing administering modified cells to the individual, and wherein the modified cells optionally comprise macrophages, and wherein the macrophages optionally express CAR.

The method is suitable for prophylaxis or therapy of any type of cancer as described further below. In embodiments, the cancer is resistant to immune checkpoint inhibitor therapy, such as anti-PD-l/PD-Ll, anti-CTLA-4, or anti-LAG-3 therapy. For use with cancer, the disclosure also provides for improving CD8⁺ T cell immunity against the cancer.

As discussed above and below, the disclosure also provides a method for prophylaxis or therapy of an autoimmune disorder. The method comprises administering to an individual in need thereof at least one agent that promotes expression of at least one selected from the group of genes of column 3) and column 4) of Table A, or administering at least one agent that promotes function of a protein encoded by said at least one gene. Representative and non-limiting examples of such genes include SUSD6, TMEM127, LRP 10, WWP2 and STUB1.

Isolated cells produced by the described method are also included.

In embodiments, the disclosure provides for increasing or decreasing expression of one or more genes described herein, including but not necessarily limited to those described in Table A.

Expression of any gene or modulating the function of any protein encoded by any gene described herein can include increase in expression or an increase of function, or a decrease of expression or a decrease in function, and all combinations of increase and decreases.

Increasing expression of any described gene can be achieved using approaches that will be apparent to those skilled in the art when given the benefit of the present disclosure. In embodiments, increased expression of a gene can be achieved by inserting a promoter such that is operably linked to the described gene, and wherein the promoter increases transcription of the gene relative to expression of the gene from the endogenous promoter. In embodiments, the promoter is constitutively active. In embodiments, the promoter is a strong promoter that is functional in human cells. In embodiments the promoter may be an inducible promoter. In embodiments the promoter may be selectively expresses in only certain cell types or stages of development. In embodiments, the promoter may replace the endogenous promoter. In another embodiment increasing expression of a gene can be achieved by inserting additional copies of the gene into the described cells. The additional copies may be under the control of an endogenous promoter or an engineered promoter. In additional embodiments one or more enhancer elements may be inserted into a chromosome such that transcription and translation of a described gene is increased within modified cells relative to transcription or translation in unmodified cells.

In embodiments, any RNAi-based approaches can be used such that the expression or translation of an mRNA encoding any described gene is inhibited. In embodiments, inhibiting the expression of a described and/or a described protein is achieved using an RNA interference (RNAi)-mediated approach. In this regard, in non-limiting embodiments, RNAi- mediated silencing is performed. In embodiments, this is achieved by delivery of any suitable RNAi agent. In embodiments, an siRNA-based approach is used. This can be performed by introducing and/or expressing one or more suitable short hairpin RNAs (shRNA) in the cells. shRNA is an RNA molecule that contains a sense strand, antisense strand, and a short loop sequence between the sense and antisense fragments. shRNA is exported into the cytoplasm where it is processed by dicer into short interfering RNA (siRNA). siRNA are 21-23 nucleotide double-stranded RNA molecules that are recognized by the RNA-induced silencing complex (RISC). Once incorporated into RISC, siRNA facilitate cleavage and degradation of targeted mRNA. Thus, for use in RNAi mediated silencing or down regulation of gene expression as described herein, siRNA, shRNA, or miRNA can be used. In alternative embodiments, a functional RNA. such as a ribozyme is used. In embodiments, the ribozyme comprises a hammerhead ribozyme, a hairpin ribozyme, or a Hepatitis Delta Virus ribozyme. In related embodiments, a microRNA (miRNA) adapted to target the relevant mRNA can be used. In embodiments, the RNAi agent may be modified to improve its efficacy, such as by being resistant to nuclease digestion.

Any therapeutic or prophylactic polynucleotide described herein may comprise DNA or RNA. The DNA or RNA may be modified or unmodified. In embodiments, antisense- oligonucleotides (AS Os) can be used. In embodiments, a modified polynucleotide comprises modified nucleotides and/or modified nucleotide linkages. The nucleotides may be nucleotide analogs. Modified nucleotides that can be used are known in the art, such as those described in Metelev VG, Oretskaya TS. Modified Oligonucleotides: New Structures, New' Properties, and New' Spheres of Application. Russ J Bioorg Chem. 2021;47(2):339-343. doi: 10. 1134/S1068162021020175. Epub 2021 Apr 2 , the disclosure of which is incorporated herein by reference. The nucleotides or nucleotide analogs may be linked by phosphodiester linkages or by a synthetic linkage, i.e., a linkage other than a phosphodiester linkage. Nonlimiting examples of linkages that can be used include phosphodi ester, alkylphosphonate, phosphorothioate, phosphorodithioate, phosphate ester, alkylphosphonothioate, phosphoramidate, carbamate, carbonate, morpholino, phosphate triester, acetamidate, carboxymethyl ester, or combinations thereof. Polynucleotides that comprise DNA/RNA hybrids are included.

In an embodiment, a prophylactic or therapeutic agent, such as RNA or other described polynucleotides, is provided in combination with any suitable nucleic acid delivery' agent, non-limiting examples of which are described in Mitchell, M.J., et al.. Nat Rev Drug Discov. 20, 101-124 (2021), the description of which is incorporated herein by reference. In non-limiting embodiments a polynucleotide of this disclosure is combined with one or more unilamellar and/or multilamellar vesicular structures such as liposomes or lipid nanoparticles, cationic polymers, lipoplexes, polyplexes, or inorganic nanoparticles. Any delivery agent described herein may comprise polyethylene glycol (PEG) and thus may be PEGylated.

In embodiments a chromosome within a cell is modified to decrease expression of a described gene. In embodiments, a genome of one or more cells as described herein may be modified to disrupt or delete a described gene. This approach can be performed using any designer nuclease. In embodiments, the nuclease is a RNA-guided CRISPR nuclease. A variety of suitable CRISPR nucleases (e.g., Cas nucleases) are known in the art. In specific and non-limiting embodiments, the Cas comprises a Cas9, such as Streptococcus pyogenes (SpCas9). Derivatives of Cas9 are known in the art and may also be used. Such derivatives may be, for example, smaller enzymes than Cas9, and/or have different proto adjacent motif (PAM) requirements. In a non-limiting embodiments, the Cas enzyme may be Cas 12a, also known as Cpfl, or SpCas9-HFl, or HypaCas9. In embodiments a Cas3 enzyme or a transposon coupled to a nuclease may be used.

In embodiments, a nuclease may be administered directly to the cells. For example, a Cas protein and suitable guide RNA(s) may be administered to the cells as ribonucleoproteins (RNPs) using any suitable technique. Alternatively, the Cas protein may be introduced into the cells separately from the guide RNAs. In embodiments, a viral expression vector may be used to introduce sequences encoding one or more of the described nucleases and/or related effector complex proteins into the cells. In embodiments, and adeno viral vector or adeno- associated viral vector may be used. As an alternative to a Cas system, a zinc finger nuclease, or a transcription activator-like effector nuclease (TALEN), or a transposon-based DNA editing system can be used to modify cells as described herein.

In embodiments, the disclosure provides for inhibiting the function of a protein encoded by a described gene is inhibited. In embodiments the function of a protein is inhibited using one or more binding partners. The binding partner may be any form of an antibody that specifically binds to a described protein, including but not limited to an intact antibody, a bispecific antibody, a multispecific antibody, an antigen-binding (Fab) fragment, an Fab’ fragment, an (Fab’)2 fragment, an Fd, an Fv, a single domain fragment or single monomeric variable antibody domain, a single-chain Diabody (scDb), a single-chain variable fragment (scFv), a CrossMab format, a tri-specific binding partner, a DARPin, an affibody, or an affimer. In embodiments the function of a described protein may be inhibited using a peptide or small molecule drug. In embodiments, the individual in need of modified cells or other agents described herein has been diagnosed with or is suspected of having cancer. In embodiments, the cancer is a solid tumor or a hematologic malignancy. In embodiments, the cancer is renal cell carcinoma, breast cancer, prostate cancer, pancreatic cancer, lung cancer, liver cancer, ovarian cancer, cervical cancer, colon cancer, esophageal cancer, glioma, glioblastoma or another brain cancer, stomach cancer, bladder cancer, testicular cancer, head and neck cancer, melanoma or another skin cancer, any sarcoma, including but not limited to fibrosarcoma, angiosarcoma, osteosarcoma, and rhabdomyosarcoma, and any blood cancer, including all types of leukemia, lymphoma, and myeloma.

In embodiments, an effective amount of an agent described herein is administered to an individual in need thereof. "‘Agents⁷’ as used herein include but are not necessarily limited RNAi agents, gene editing systems, binding partners, small molecule drugs, and modified cells. Modified cells of this disclosure may be any cell type. In embodiments the cells are hematopoietic stem cells or other lymphoid progenitor cells. In embodiments, the cells are lymphocytes. In some examples the lymphocytes are T cells, natural killer (NK), natural killer T cells (NKTs), macrophages, or dendritic cells. In certain examples a cell of this disclosure is also modified such that it expresses a chimeric antigen receptor (CAR). Modified cells of this disclosure may be used as, for example, for adoptive immunotherapy. In embodiments one or more agents described herein may be combined with other agents that are intended for prophylaxis or treatment of a disorder, such as chemotherapeutic agents, checkpoint inhibitors, antibody-drug conjugates, radiation, surgical interventions, and the like.

In one embodiment, expression of a protein described herein can be increased by providing to cells an mRNA encoding the protein, or an expression vector encoding the protein. In embodiments, the disclosure includes administering mRNA to cells to overexpress MHC-I inhibitors for autoimmune purposes, or overexpress MHC-II activators for cancer purposes.

In embodiments, an effective amount is an amount that reduces one or more signs or symptoms of a disease and/or reduces the severity of the disease. An effective amount may also inhibit or prevent the onset of a disease or a disease relapse. A precise dosage can be selected by the individual physician in view of the patient to be treated. Dosage and administration can be adjusted to provide sufficient levels of binding partner to maintain the desired effect. Additional factors that may be taken into account include the severity and type of the disease state, age, weight, and gender of the patient, desired duration of treatment, method of administration, time and frequency of administration, drug combination(s), reaction sensitivities, and/or tolerance/response to therapy. In embodiments, a described method is used for treatment of so-called immunologically ‘'cold’’ tumors, i.e., tumors that involve insufficient CD8+ T cell immunity due to low MHC-I expression or low mutation burden. Thus, in embodiments, a described method increases cytotoxic T cell, or other T cell, infiltration into a tumor. In embodiments, a described method potentiates another therapy, including but not necessarily limited to an immunological anti-cancer therapy. In embodiments, a described method exhibits a synergistic anti-cancer response.

In embodiments, the individual in need of prophylaxis or treatment as described herein has been diagnosed with or is suspected of having cancer. In embodiments, the cancer is a solid tumor or a hematologic malignancy. In embodiments, the cancer is renal cell carcinoma, breast cancer, prostate cancer, pancreatic cancer, lung cancer, liver cancer, ovarian cancer, cervical cancer, colon cancer, esophageal cancer, glioma, glioblastoma or another brain cancer, stomach cancer, bladder cancer, testicular cancer, head and neck cancer, melanoma or another skin cancer, any sarcoma, including but not limited to fibrosarcoma, angiosarcoma, osteosarcoma, and rhabdomyosarcoma, and any blood cancer, including all types of leukemia, lymphoma, and myeloma. In a non-limiting embodiment the individual has acute myeloid leukemia (AML).

In embodiments, the individual in need of prophylaxis or treatment as described herein has been diagnosed with or is suspected of having an autoimmune disease. In embodiments, the autoimmune disease is any of systemic lupus erythematosus, rheumatoid arthritis, chronic inflammation, celiac disease, Crohn’s disease, colitis, diabetes mellitus ty pe 1, inflammatory' bowel disease, autoimmune encephalitis, eosinophilic fasciitis, eosinophilic gastroenteritis, eosinophilic esophagitis, multiple sclerosis (MS), including but not limited to Relapsing-Remitting MS, Secondary-Progressive MS, Primary-Progressive MS, and Progressive-Relapsing MS, or gastritis, Graves’ disease, hypogammaglobulinemia, idiopathic inflammatory' demyelinating diseases, thrombocytopenic purpura, my asthenia gravis, pernicious anemia, psoriasis, Sjogren's syndrome, ulcerative colitis, graft versus host disease (GVHD) or any autoimmune disease that is characterized by type II, III or IV hypersensitivity, Polymyalgia rheumatic, Addison’s disease, Behcet’s disease, scleroderma (systemic sclerosis), Autoimmune pancreatitis, Autoimmune hemolytic anemia, Hypoparathyroidism, Guillain-Barre syndrome, Reactive arthritis, or Sarcoidosis. In embodiments, the individual has been diagnosed with or is suspected of one or a combination of primary-progressive multiple sclerosis (PPMS), relapsing-remitting MS (RRMS), secondary -progressive MS (SPMS), or progressive-relapsing MS (PRMS).

In embodiments, an individual is diagnosed or a prognosis is made for the individual based on expression of the described genes as determined from a biological sample from the individual. The biological sample can be analyzed using any suitable technique, such as immunoassays for proteins, and sequencing for nucleic acid analysis. Results from analyzing the sample can be compared to any suitable control, such as a value obtained for expression of the same gene or genes from an individual who does not have cancer, or has cancer that is susceptible or not susceptible to immune checkpoint inhibition, or does not have an autoimmune disease.

As discussed herein, and as illustrated by the accompanying figures, aspects of the disclosure include non-limiting demonstrations that SUSD6 depletion enhances AP and promotes CD8+ T cell-mediated acute AML treatment, that SUSD6 is a plasma membrane protein that potently inhibits AP in AML, that SUSD6 suppresses AP and facilitates solid tumor-associated immuno-evasion, SUSD6 is a general cancer-associated AP inhibitor, that targeting the SUSD6/TMEM127/WWP2 complex may be used for therapeutic restoration of AP-mediated immune surveillance, that TMEM127 ablation enhances MHC-I expression in vivo, and that targeting SUSD6 and TMEM127 restores tumor antigen presentation. As also described herein, the disclosure includes modifying WWP2, STUB1, and/or LRP10 expression. LRP10 has been shown to suppresses IL7R. limiting CD8+ T cell homeostatic expansion and anti-tumor immunity (see, for example, https://doi.org/10.1101/2023.12.08.570738, the disclosure of which is incorporated herein by reference).

In view of the foregoing, the present disclosure relates to the Examples below.

With respect to the Examples, to systematically identify general and tumor-associated MHC-I antigen presentation inhibitors, we performed pMHC-I-guided CRISPR screens in both human and mouse AML cell lines. We started with AML given its poor immunogenicity and the fact that it represents the malignant counterpart of myeloid progenitors which can differentiate into professional APC, with mechanisms that can be potentially extended to other cancer types. Through these screens, we constructed positive and negative regulator ' networks of pMHC-I modulation and compared the role of these novel regulators in the simultaneous modulation of MHC-I expression. We identified a membrane-associated AP inhibitory axis that involves Sushi Domain Containing 6 (SUSD6, KIAA0247) and Transmembrane Protein 127 (TMEM127), which together recruit the E3 ligase WWP2 for MHC-I lysosomal degradation. Without intending to be constrained by any particular interpretation, it is considered that host membrane molecule(s) that can directly engage and inhibit MHC-I or pMHC-I expression by targeting described genes or their proteins has not been suggested before. TMEM127, a proposed 4-transmembrane protein (Flores et al., 2020) which is involved in susceptibility to rare neuroendocrine tumors (Qin et al., 2010), has been suggested as a Nedd4-family E3 ligase adaptor that degrades MHC-II in the presence of an Salmonella effector protein, SteD (Alix et al., 2020); while SUSD6, a single-pass transmembrane protein, has no know n immunological functions. We characterized the function and mechanism of the SUSD6-TMEM127-WWP2 inhibitory' axis in modulating both pMHC-I and MHC-I presentation, as w ell as its suppressive role in the modulation of tumor immunity in both AML and solid cancers. The disclosure therefore reveals a new class of tumor-associated immune-evasion mechanisms that target AP. The disclosure supports use of the described composition and methods as membrane-associated targets for nextgeneration cancer immunotherapies.

Example 1 pMHC-I-Guided CRISPR/Cas9 Screens Reveal Key AP Regulatory Networks in AML To systematically identify cancer-associated key regulators for MHC-I AP, we first engineered antigen-specific AP reporters in cell lines of AML, an APC precursor-derived tumor with low APM score compared to other major tumor types (Fig. 7A). Specifically, we engineered the Cas9-expressing THP-1. a well-characterized MLL-AF9+ TP53^mut NRAS^G12D HLA-A*02:01+ human AML cell line, to express a truncated alpha-fetoprotein (AFP) tumor antigen fused together with a blue fluorescence protein (BFP) through a 2A self-cleaving peptide, which served as a quantitative reporter of AFP antigen expression (Fig. 1A). To evaluate antigen-specific pMHC-I AP in this reporter system, we used a unique fully-human antibody (clone ET1402L1) which binds an immunogenic AFP 158-166 peptide complexed with HLA-A*02:01 (HLA-A*02:01:AFPi58-i66, hereafter referred to as HLA-A2:AFP) (Liu et al., 2017). We observed a positive correlation between the surface level of HLA-A2:AFP and AFP antigen expression as indicated by BFP intensity (Fig. 7B), validating the robustness of our system to quantitatively monitor AP triggered by a specified antigen. Using the same strategy', we then generated another reporter using RN2, an MLL-AF9+ Nras^G12D H-2K^b+ mouse AML cell line (Shi et al., 2015; Zuber et al., 2011) and chicken ovalbumin (OVA) as a model antigen (Fig. 1A). We observed a stronger positive correlation between OVA antigen expression, as measured by BFP intensity, and the surface level of pMHC-I complex (H- 2K^b:OVA₂57-264, hereafter referred to as H-2K^b:0VA), indicated by a specific mAb (Fig. 7C).

Using our engineered antigen-specific AP reporter cell lines, we then performed genome-scale CRISPR/Cas9 loss-of-function screens to search for key pMHC-I regulators. These human and mouse AP reporter cell lines were transduced with either the Brunello sgRNA library or the Brie library (Doench et al., 2016). respectively. Cells were then sorted on the basis of high or low pMHC-I expression on the surface of these reporter lines by flow cytometry, and individual sgRNA read counts were then evaluated by deep sequencing (Fig. 1A). Our strategy' allowed us to pinpoint positive and negative regulators for pMHC-I in both human and mouse leukemia cells which were previously unknown (Fig. 1B-E). We then selected dozens of top candidates in both screens (either common or species-specific) and validated their abilities to specifically regulate antigen-specific AP (Fig. IF). While the majority⁷ of these gene candidates were found to specifically modulate pMHC-I AP levels, some of them (e.g., ICMT. TSC2) appeared to affect AP by simultaneously modulating antigen levels (Fig. IF).

Integrating both human and mouse cell line screens, we successfully identified 105 evolutionarily-conserved common positive AP regulators that were negatively selected during these two screens, whose loss was found to reduce both HLA-A2:AFP and H- 2K^b:OVA surface presentation (Fig. 7D, and Fig. 1B-E). The majority of these canonical and essential factors for antigen processing and presentation (e g., B2M, TAPI , TAP2, TAPBP, NLRC5) appeared in our screens (Fig. 1B-E). STRING protein-protein interaction network analysis further identified dozens of novel molecules involved in transcription, RNA processing. mTOR signaling, and mitochondria function that can positively regulate pMHC-I presentation (Fig. 7E). Interestingly, mTOR signaling was reported to have impacts on MHC-I immunopeptidome (Caron et al., 2011), while mitochondrial dynamics and genomic integrity' have been linked to neoantigen generation and pMHC-I expression (Lei et al., 2022; Mardis, 2019; Prota et al., 2022). On the flip side, 78 genes were identified as common negative AP regulators (Fig. 1G). Network analysis suggested that these genes have strong interplays with protein ubiquitination, vesicle trafficking or transport, as well as DNA metabolic processes or cell cycle (Fig. 1H). Together, our pMHC-I reporter-based CRISPR screens systematically revealed critical regulators of AP that were conserved in both human and mouse cancer cells. To test whether the effect on surface pMHC-I of these common AP regulators could be explained simply by the modulation of general MHC-I/HLA, we also performed an additional CRISPR screen to dissect factors that affect surface pan-HLA level in the Cas9- expressing THP-1 AML cells (Fig. 8A). Integrating our antigen-specific pMHC-I AP and pan-HLA screens, we identified 21 out of 105 positive regulators as genes positively modulating both pMHC-I and MHC-I (Fig. 2A-2C, Fig. 8B). The majority of them are known canonical antigen presentation mediators (Fig. 8C), including NLRC5, TAPI, TAP2. TAPBP and B2M, as well as recently identified positive regulators for MHC-I expression (SUGT1) (Dersh et al., 2021) or glycosphingolipid-related MHC-I antibody /TCR recognition (SPPL3) (Jongsma et al.. 2021) (Fig.lB-E, Fig. 2A-2B). Interestingly, 84 out of 105 positive AP regulators from our screens were associated with pMHC-I modulation, but not MHC-I (Fig. 8B), these genes are strongly enriched in biological processes that control transcription, RNA processing, translation and mitochondria function (Fig. 8D). Moreover, there were few overlaps between these 21 common positive AP/MHC-I regulators from our screens and the recently reported positive MHC-I regulators in lymphoma (only SUGT1, SRSF6, MOGS, and the canonical AP factors) (Dersh et al., 2021) (Fig. 8B). These results collectively suggest some differential regulatory mechanisms of pMHC-I versus MHC-I which requires detailed characterization and might be related to diverse biological processes or different cell ty pes.

Although they appeared in low rank or even in different direction in our pMHC-I screens (Fig.lB-E), we validated several recently identified negative regulators for glycosphingolipid-related MHC-I antibody /TCR recognition (e g., UGCG, SLC35A2, B3GNT5) (Jongsma et al., 2021) as top gene candidates in our pan-HLA screen. Surprisingly, EZH2 (Burr et al., 2019; Dersh et al., 2021) and TRAF3 (Gu et al., 2021) were not top hits (Fig. 2A and 2B). These data clearly suggest that these genes have a differential effect on modulating surface pMHC-I and MHC-I. Therefore, we categorized these 78 negative AP regulators into two groups based on their ability⁷ with (the 44 gene set) or without (group 2, the 34 gene set) affecting pan-HLA levels (Fig. 2D). When directly comparing these two groups, we found that negative AP regulators from the 44 gene set were more enriched in pathways that control the functions of protein trafficking organelles, including ER. Golgi, and endosome, while the negative AP regulators from the 34 gene set tended to regulate protein ubiquitination, DNA metabolic processes and cell cycle-related processes (Fig. 2E, 8E-F). Our analysis also revealed that 44 gene set had a larger portion of membrane proteins (SUSD6. TMEM127, LRP10, PDCD10. CHIC2, and TM9SF3) in the 44 gene set compared to the 34 gene set (Fig. 2E and 2F), with SUSD6 and TMEM127 serving as top two gene candidates in the HLA-A2: AFP screen (Fig. 2F). Moreover, the AP regulators from the 44 gene set were, in general, stronger modulators of the antigen-specific AP in AML cells (Fig. 2F and 8G) Given the fact that MHC-I is also a membrane protein, it is possible that these membrane proteins provide more direct mechanistic links to MHC-I and/or pMHC-I downregulation. Those 34 regulators mainly affecting pMHC-I but not MHC-I and are included in the disclosure, which provides additional characterization of the 44 negative AP/MHC-I regulators for the Examples that follow.

Example 2

Integration of in vivo Screens Identifies Functional AP Inhibitors

Dysregulation of the AP pathway has been connected to the failure of ICB treatment and poor clinical outcomes in certain cancers, including AML (Castro et al., 2019; Isidori et al.. 2021; Nangaha et al., 2013; Shin et al., 2017; Zaretsky et al., 2016). Further, enhancing AP is believed to increase tumor immunogenicity (Burr et al., 2019; Gu et al., 2021; Liu et al., 2020; Yamamoto et al., 2020), which opens the door to exciting and clinically relevant work. To further validate the immune regulator}' function of our 44 common AP inhibitors, particularly in the context of tumors and T cell immunity, we performed in vivo CRISPR screens in a syngeneic murine AML model (C 1498) (Au - Mopin et al., 2016), using a focused 11 bran- containing sgRNAs targeting these molecules as well as several published MHC-I regulators (e g., Traf3, Ezh2, Pcsk9) (Burr et al., 2019; Griffin et al., 2021; Gu et al., 2021; Liu et al., 2020; Manguso et al.. 2017). sgRN A- transduced AML cells were transplanted into either CD8⁺ T cell-depleted mice or immune-competent mice, while a portion of the cells was cultured in vitro to assess the essentiality of each candidate and to affect internal tumor growth (Fig. 2G). At 15 days after tumor cell inoculation, we observed that a large majority of the 44 common AP repressors came up as hits that enhanced CD8⁺ T cell-dependent immunosurveillance, including top-ranked candidates SUSD6, TMEM127. LRP10, WWP2 and STUB1 (Fig. 2H-I). Notably, we did not observe a significant correlation between loss of cell-intrinsic fitness and disadvantage under immune-selection, suggesting a strong selection for cell-extrinsic factors that modulate immunosurveillance in this screen setting (Fig. 2H and 21). Collectively, our comprehensive screens systematically identified functional AP inhibitors in AML. Example 3

SUSD6 Loss Enhances AP and Facilities T Cell-Mediated Immunosurveillance in AML and solid cancers.

Among the evolutionally-conserved common negative AP regulators, we are particularly interested in SUSD6, given the fact that: 1) it is one of the top hits in all AP screens (Fig. 2D) as well as the in vivo screen (Fig. 2H), and. 2) it represents a single transmembrane protein with our validated expression on the cell surface (Fig. 9A and 9B), which may provide a mechanistic link on regulating membrane-associated pMHC-I and MHC-I. Next, we validated the ability /capacity of SUSD6 sgRNA in enhancing both antigenspecific AP and HLA/MHC-I expression in both human and mouse AML lines by flow cytometry (Fig. 3A-D) In this experiment, we selected sgRNAs for human or mouse SUSD6 and confirmed their knockdown capacity by western blot (Fig. 9C and 9D). Moreover, overexpression of the SUSD6 fully reversed the HLA-enhancing phenoty pe of the SUSD6- deficient cells (Fig. 9E). In addition, we confirmed the AP inhibitory effect of SUSD6 in two additional human AML cell lines (MV4-11 and KASUMI-1) with different driver mutations (Fig. 9F and 9G), as well as in the context of interferon treatment (Fig. 9H). Taken together, our findings reveal a functional role of the membrane protein SUSD6 in suppressing pMHC-I AP as well as MHC-I expression.

Considering MHC-I AP is one of the major dominants that control CD8¹ T cell activation and function (Dockree et al., 2017; Peaper and Cresswell, 2008), we then tested whether SUSD6 ablation could benefit CD8⁺ T cell responses. By co-culturing the H- 2K^b:OVA-specific B3Z CD T cell hybridoma (Karttunen and Shastri, 1991) with RN2- Cas9-OVA-BFP mouse AML cells, we confirmed that SUSD6 loss in the AML cells potentiated T cell activation measured by IL-2 secretion (Fig. 3E and 3F). In line with this, SUSD6-deficient RN2-OVA cells were more susceptible to OT-I T cell-mediated killing in a co-culture assay (Fig. 3G and 3H). Similarly, we observed that SUSD6-deficient human THP-1 AML cells, which were conditioned by the hypo-methylating agent, Azacytidine, to induce NY-ESO-1 antigen expression, also were more susceptible to killing by human peripheral T cells engineered to express a NY-ESO-1 specific TCR that recognizes the NY- ESO-1 SLLMWITQC peptide-HLA-A*02:01 complex (Fig. 31 and 3J).

We next examined the function of SUSD6 in the control of AML by using a previously established mouse syngeneic model (Au - Mopin et al., 2016). SUSD6- or nontargeting sgRNAs-transduced Cas9-expressing C1498 AML cells were sorted, expanded and transplanted into immune-competent recipients or maintained in vitro (Fig. 3K). Knockout efficiency and the MHC-I-enhancing effect upon SUSD6 ablation were confirmed before transplantation (Fig. 91 and 9J). Although SUSD6 loss did not impair cell fitness and growth in in vitro culture (Fig. 9K), a significant delay in leukemia progression in mice was observed (Fig. 3L), which correlated with prolonged survival (Fig. 3M). Notably, the AML- suppressive activity of SUSD6 ablation was totally dependent on CD8⁺ T cells (Fig. 30 and 3P), suggesting SUSD6 plays a critical role in controlling AML immunogenicity and T cell immunity. To further establish the clinical significance of SUSD6 in AML, we analyzed the BloodSpot database and found significantly higher expression of SUSD6 in myelodysplastic syndromes (MDS) and AML compared to normal hematopoietic stem and progenitor cells (HSPCs) (Fig. 3R). Moreover. SUSD6 expression was correlated with complex karyotype in AML (Fig. 3R). Survival analysis also suggested that high expression of SUSD6 associated with poor clinical outcomes in AML patients (Fig. 3S). Our in-house single-cell RNA-seq profiling of the bone marrow immune-microenvironments in AML patients further revealed that the levels of SUSD6 expression in AML cells were negatively correlated with the T cell activation signature (CD3E, GZMB. CX3CR1, FGFBP2. PRF1) in CD8⁺ T cells within the bone marrow immune-microenvironments (Fig. 3T). Collectively, the disclosure shows that SUSD6 suppresses AML AP and intrinsic immunogenicity to facilitate AML-associated immune-evasion.

The SUSD6 gene is primarily enriched in cells of the immune system, particularly the myeloid cell subsets and NK cells, with modest or low expression in most human organs, based on the BIOGPS database (Fig. 10A). In addition to AML, SUSD6 was found to be significantly amplified in a series of human solid cancers, such as pancreatic cancer (PAAD), glioblastoma (GBM), and brain lower grade glioma (LGG) (Fig.lOB). Therefore, we tested if our findings on SUSD6 could be extended beyond AML to models of solid tumors, as aberrant AP had been suggested in many cancer types. We first confirmed that SUSD6 ablation by sgRNAs enhanced MHC-I expression in multiple solid tumor cell lines (B16F10- OVA, CMT167, KPC, MC38, CT26, EMT6) (Fig. IOC). Two representative solid tumor lines (B16F10-OVA and CT26) with distinct genetic backgrounds were then selected to further validate the in vivo function of SUSD6 in facilitating tumor-associated immune- evasion (Fig. 10D) Both selected cell lines demonstrated potent and consistent knock-down efficiencies and MHC-I-boosting effects upon SUSD6-targ eting shRNA transduction (Fig. 10E-J). Consistent with our AML data, ablation of SUSD6 in both solid tumor lines delayed tumor progression and improved animal survival (Fig. 4A-D) without dampening internal cell fitness when cultured in vitro (Fig. 10K and 1OL). In addition, depletion of CD8⁺ T cells using completely impaired the tumor-suppressive function of SUSD6 ablation in both models, confirming that the effect is CD8⁺ T cell dependent (Fig. 4E-H). In line with the delayed grow th of SUSD6-deficient B16F10-OVA in vivo, we observed a significantly lower tumor burden measured by a reduced size, w eight and cell number per tumor when SUSD6 was ablated (Fig. 4I-K). Moreover, ex vivo analysis of tumor cells suggested that the MHC-I- enhancing effect upon SUSD6 ablation was sustainable, even after weeks of shRNA targeting (Fig. 4L) Consistent with CD8⁺ T cell dependency in this model, flow-cytometry analyses confirmed significant increases of CD8⁺ T cells in the TME (Fig. 4M). Furthermore, the tumor-infiltrating CD8⁺ T cells in the SUSD6-deficient tumors had an increased effector function compared to those from the WT tumors, as measured by their capacities to secret both granzyme B and interferon-y (Fig. 4N-Q). Altogether, these data indicate that SUSD6 overexpression is a potential general mechanism of AP inhibition and T cell evasion in both leukemia and solid tumors.

Example 4

SUSD6 and TMEM127 complex Targets MHC-I for Lysosomal Degradation through Direct Interaction and Recruitment of E3 Ligases

To investigate the underlying mechanisms by which SUSD6 affects antigen presentation, we first performed RT-qPCR experiments in THP1 cells with and without SUSD6 ablation. These experiments revealed that SUSD6 did not affect MHC-I transcription (Fig. HA) However, silencing SUSD6 resulted in a substantial increase in the total amount of MHC-I protein (Fig. 5A) without affecting global translation by OP-Puro analysis (Liu et al., 2012) (Fig. 11B and 11C). Thus, analyzed whether SUSD6 could affect MHC-I in a post- translational fashion. Indeed, the internalization assay revealed that SUSD6 destabilized surface MHC-I/HLA (Fig. 5B and 5C). These data were further supported by the fact that depletion of SUSD6 slowed the reduction of surface HLA-A2 over a 24-hour time course in the presence of a translation inhibitor, cycloheximide (CHX) (Fig. 5D and HD). Moreover, substantial increase in surface HLA-A2 of WT cells was observed when lysosome inhibitor Bafilomycin Al (BafAl) was applied (Fig. HD), suggesting that lysosomal degradation was the major route for surface HLA degradation (Fig. 5E). However, such increase was not observed for SUSD6-knockout cells, indicating that SUSD6 is involved in and upstream of the lysosomal degradation of surface HLA (Fig. 5E). On the contrary, no significant increase in surface HLA-A was observed for WT or SUSD6 knockout cells when proteasomal degradation was inhibited by epoxomicin (Epox) (Fig. 11D and 5F), highlighting that SUSD6 was not involved in the proteasomal degradation of surface MHC-I. The overexpression of SUSD6 in 293T cells led to a significant reduction in HLA-A2 surface localization but an increase in lysosomal localization (Fig. 5G). Together these data strongly indicate that SUSD6 targets surface HLA for lysosomal degradation.

TMEM127 and WWP2, two other top hits discovered by our screens (Fig. 1 and 2), have been previously reported to be involved in protein ubiquitination and degradation (Alix et al., 2020). The expression of both genes is highly correlated with SUSD6 expression in AML and solid tumors (Fig. 6A and 12A-B). Together, these data suggest that TMEM127 and WWP2 may co-operate with SUSD6 for the degradation of surface MHC-I. Indeed, coimmunoprecipitation (CoIP) experiments revealed that SUSD6 and TMEM127 could simultaneously and specifically form a complex with HLA molecules (Fig. 6B), but not with irrelevant molecules (Fig. 12C). To further validate this data, we employed a split-luciferase system (Dixon et al., 2016), and detected the direct interaction between HLA, SUSD6, and TMEM127 (Fig. 6C). Additionally, we confirmed the simultaneous interaction between these three molecules via a tripartite split-GFP system (Cabantous et al., 2013; Foglieni et al., 2017), where the GFP signal could only be detected when these molecules were in close proximity (Fig. 6D and Fig. 12D). Notably, the primary localization of HLA changed from the plasma membrane to the lysosome when SUSD6 and TMEM127 were overexpressed (Fig. 6D). Furthermore, the percentage of the split-GFP⁺ cells was significantly increased upon BafAl treatment only in cells that expressed both SUSD6 and TMEM127 but not those expressing SUSD6 and control CD86 protein, confirming the SUSD6/TMEM127/HLA complex was targeted for lysosomal degradation (Fig 12D and 12E).

Previous studies showed that WWP2, an E3 ligase, could be recruited by TMEM127 to ubiquitinate surface MHC-II in the presence of a bacteria effector protein (Alix et al., 2020). We conducted Co-IP experiments and discovered that WWP2 could be pulled dow n in conjunction with SUSD6 or TMEM127 (Fig. 6B). Split luciferase analysis revealed the direct interaction between WWP2 and SUSD6 or the c-terminal intracellular tail of TMEM127 (Fig. 6E). Interestingly, WWP2 did not interact with HLA directly, it requires the presence of both SUSD6 and TMEM127 to associate with HLA (Fig. 6E and 6F), implying that SUSD6 and TMEM127 cooperate to recruit WWP2 to the vicinity of the HLA molecules. Further, knocking down SUSD6 by shRNA resulted in a decrease in HLA ubiquitination (Fig. 12F). However, knocking out WWP2 alone did not increase the surface HLA level as much as targeting SUSD6 or TMEM127 (Fig. 12G), indicating that additional E3 ligases may be involved in the ubiquitination of HLA. Another E3 ubiquitin ligase, STUB1, which was also identified in our screen (Fig.lB-E and 2D) and previously shown to affect surface MHC-I through down regulating IFNGR1 (Ng et al., 2022), could be pulled down together with SUSD6 or TMEM127 (Fig. 12H).

In summary’, the Examples above demonstrate that SUSD6 and TMEM127 simultaneously interact with the HLA molecule. E3 ligases, such as WWP2 and STUB1. may be recruited during the interaction to ubiquitinate plasma membrane HLA for lysosomal degradation.

Example 5

Targeting TMEM127 in the SUSD6/TMEM127/WWP2 Complex Restores Tumor AP and Controls Tumor Growth

Given the highly correlated expression of SUSD6, 7MEM127, and IFWP2 (STW) genes in various tumor types (Fig. 6A and Fig. 12A and 12B), we explored the clinical relevance of STW gene signature using the TCGA database. We found that STW gene signatures were significantly upregulated in AML (Fig. 6G) and PAAD (Fig. 121). which were negatively correlated with patient survival (Fig. 6H and Fig. 12J). Since SUSD6, TMEM127, and WWP2 w ork together to mediate surface HLA lysosomal degradation, we tested whether tumor AP could be restored by targeting the STW complex instead of SUSD6 itself. As a proof of concept, we have show n that knocking down SUSD6 in AML (C1498) or solid tumors (B16F10-OVA and CT26) enhanced tumor AP, delayed tumor growth, and extended animal survival (Fig. 3 and 4). Additionally, knocking down TMEM127 also resulted in a similar phenotype in these tumor models (Fig. 61, 6J, 6M, 6N, 12K-12P, 12R and 12S) without impairing the tumor fitness in vitro (Fig. 12Q). The in vivo effect of TMEM127 ablation was also CD8⁺ T cell-dependent (Fig. 6K, 6L, 60, 6P, 12T and 12U), recapitulating what we have observed in the Susd6-deficient tumor (Fig. 3 and 4). Taken together, our in vitro and in vivo examples collectively demonstrate restoration of tumor AP and enhanced immune surveillance by targeting the STW membrane-associated AP inhibitory axis.

Discussion of Examples This disclosure is believed to present the first genome-wide CRISPR screens that systematically identify regulators that: 1) directly control the actual specific-antigen-pMHC- I-complex; 2) are evolutionarily-conserved in both human and mouse systems; and 3) are largely shared by AML and by solid cancers. The results are different from recent studies that focus on MHC-I expression screens and/or a particular tumor type (Burr et al., 2019; Dersh et al., 2021; Gu et al.. 2021; Jongsma et al., 2021). In this disclosure, we identify an inhibitory axis involving a membrane-associated complex that is able to recruit the WWP2 E3 ligase for MHC-I lysosomal degradation. Further, we found that the MHC-I degradation occurs specifically upon engagement of SUSD6 and TMEM127. We showed that ablation of SUSD6 or TMEM127 in leukemia, as well as various solid cancers, profoundly enhanced AP and reduced tumor growth in a CD8⁺ T cell-dependent manner. We also found that the STW gene signature is negatively correlated with cancer survival. The disclosure thus reveals a membrane-associated AP inhibitory axis with strong tumor relevance that is expected to be suitable for immunotherapy of both acute leukemia and solid cancers.

Based on our screening results, we identified 105 positive and 78 negative regulators for pMHC-I modulation. We also constructed a negative AP regulatory network for pMHC-I modulation.

Among these 44 negative AP regulators, SUSD6, TMEM127 and WWP2 and STUB1 stood out due to 1) their top-ranked function in both pMHC-I and MHC-I inhibition; 2) their lack of effect on cancer cell intrinsic growth; 3) an in vivo CRISPR screen related to AML- specific CD8⁺ T cell immunity’. TMEM127 and SUSD6 are membrane proteins, WWP2 (Chen et al., 2009; Xu et al., 2009) and STUB1 (Ballinger Carol et al., 1999; Jiang et al., 2001) are E3 ligases known to play a role in ubiquitin-mediated protein degradation. It is established that many viruses use membrane-associated viral factors to directly hijack MHC-I expression, which include single-pass immunoglobulin-like proteins GP48 (Sgourakis et al., 2015) or ORF7a (SARS-CoV-2) (Arshad et al., 2022), and multiple transmembrane GPCR BILF1 (EBV) (Zuo et al., 2009). SUSD6 and TMEM127 also are a single-pass and a four- pass transmembrane protein, respectively, and the function of both on pMHC-I or MHC-I negative regulation were validated by a senes of in vitro and in vivo studies. We also found both molecules could directly engage with MHC-I to form a tri-molecular complex interacting with each other as indicated by our co-IP and split-luciferase studies. Therefore, without intending to be bound by any particular theory', it is considered that at least SUSD6 and TMEM127 comprise a new class of host membrane molecule(s) that directly bind to and inhibit MHC-I and pMHC-I surface expression. TMEM127 has been suggested as an adaptor for WWP2 E3 ligase, which was validated by our split-luciferase studies. However, we also identified a much stronger interaction between SUSD6 and WWP2, and both TMEM127 and SUSD6 are required for the interaction between HLA and WWP2. Other than WWP2, we also found STUB1 can engage with TMEM127 and SUSD6. Therefore, it is considered that TMEM127 and SUSD6 served as a “regulasome” at the membrane level, to bridge some E3 ligases to the proximity’ of MHC-I for its degradation. Other E3 ligases were not selected out from our screens except WWP2. STUB!, and UHRF1, suggesting a degree of E3 ligase specificity.

The role that SUSD6 and TMEM127 play in modulating pMHC-I or MHC-I appears to be consistent across cancer subtypes, as indicated by our data involving a series of AML or solid cancer cell lines. SUSD6 mRNA is only expressed in immune subsets from healthy donors, however, it can be overexpressed in both AML and several solid cancers, with unclear induction mechanisms. We found a strong correlation among TMEM127, SUSD6 and WWP2 in multiple cancer types. Other than cancer cells, the disclosure also includes modulating SUSD6-TMEM127-WWP2 axis in the control of other cells, particularly the professional antigen presenting cells, as cross-priming of tumor-specific T cells by dendritic cells in the tumor-draining lymph node is generally considered as the initiation step of the anti-tumor immune response (Sanchez-Paul ete et al., 2017).

E3 ligase WWP2 associates with SUSD6, TMEM127, and pMHC-I. USP7. a cancer- associated deubiquitinase (Zhang et al., 2020), also were identified by the described screens. The data clearly establish SUSD6-TMEM127-WWP2 as an inhibitory axis for MHC-I antigen presentation and CD8⁺ T cell tumor immunity. The disclosure also supports lysosomal degradation as a key mechanism of MHC-I immune evasion mediated by the SUSD6-TMEM127-WWP2 axis.

The disclosure also indicates that the SUSD6-TMEM127-WWP2 axis as a cancer- associated immune evasion mechanism as a therapeutic target for “cold” tumors that involve insufficient CD8⁺ T cell immunity due to low MHC-I expression or low mutation burden, particularly in cancers with high-expression of these molecule(s). Therapeutic targeting of these molecules, such as antibodies against SUSD6 or TMEM127 to disrupt the SUSD6- TMEM127-MHC-I tri-molecular axis, intra-tumoral delivery of shRNA encapsulating nanoparticles, and small molecule inhibitors to E3 ligases, are thus encompassed by the disclosure to enhance MHC-I antigen presentation and CD8⁺ T cell immunity. Example 6

Methods

KEY RESOURCES TABLE

EXPERIMENTAL MODEL AND SUBJECT DETAILS

Cell lines

HEK293T cells (ATCC, CRL-3216, RRID: CVCL 0063, Female), MC38 (Kerafast; ENH204-FP, RRID: CVCL B288, Female), B16F10-OVA, KPC (Sun et al., 2021)), CMT167 (ECACC, 10032302, RRID: CVCL 2405, Female). EMT6 (ATCC, CRL-2755, RRID: CVCL 1923, Female), and CT26.WT (ATCC, CRL-2638, RRID: CVCL 7256) were cultured in complete Dulbecco’s Modified Eagle Medium (DMEM), supplemented with 10% heat-inactivated fetal bovine serum (FBS), 2 mM L-Glutamine. IX Penicillin/Streptomycin, 1 mM Sodium Pyruvate, and 20 mM HEPES. THP-1 cells (ATCC, TIB-202, RRID: CVCL_0006, Male), RN2 cells (Shi et al., 2015)), C1498 (ATCC, TIB-49, RRID: CVCL_3494, Female) were cultured in RPMI 1640 medium supplemented with 10% FBS, 2 mM L-Glutamine, 20 mM HEPES, and IX Penicillin/Streptomycin. All cells were maintained at 37°C and in a 5% CO2 atmosphere. All the cell lines were determined negative for mycoplasma using the LookOut Mycoplasma PCR Detection Kit (Sigma). Cells were used for experiments within 15 to 20 passages from thawing. The H-2K^b:OVA-specific B3Z hybridoma cells were cultured at 37 °C and 5% CO2 in RPMI-1640, supplemented with 10% FBS, 25 mM HEPES, 1 mM sodium pyruvate, lx Pen/Strep, and 50 pM 0-ME.

Cell lines transduced with lentiviral MSCV-Cas9-2A-Blast were selected with blasticidin (InvivoGen) 48 hrs after transduction. All transfections were performed in HEK293T cells using Lipofectamine3000 (Invitrogen) reagent at 4:2:3 ratios of sgRNA construct: pVSVG: pPax2 in OPTI-MEM solution. Viral supernatant was collected 48 hrs and 72 hrs post-transfection. Spin infections were performed at 32°C at 1,500 RCF for 30 min with polybrene reagent (1 :2000 dilution) (Fisher Scientific). For SUSD6/ TMEM127/ WWP2/ STUB1 overexpression, a cassette containing human-codon-optimized FLAG/HA/V5-tagged SUSD6/ TMEM127/ WWP2/ STUB1 CDSs followed by ires-EGFP- P2A-PURO, T2A-mCherry, T2A-BFP, or T2A-URFP were cloned into the lentiviral vector pCDH-EFl s. Lentivirus were generated using HEK293T, and spin infections were performed to transduce AML cells. For generating the split-GFP system, codon-optimized SUSD6- GFP(l-9)-V5, HLA-A2-B2M-T10-HA and TMEM127-T11-FLAG were cloned into the lentiviral vector pCDH-EFls. Lentivirus were generated using HEK293T, and spin infections were performed to transduce HEK293T cells.

Animals

C57BL/6J (000664), BALB/cJ (000651), Cas9-GFP (024858), OT-I (003831) were produced using breeders bought from the Jackson Laboratory⁷. Mice w ere bred and maintained in individually ventilated cages and fed with autoclaved food and sterile water at NYU School of Medicine Animal Facility. All animal experiments were performed in accordance with protocols approved by the New⁷ York University Institutional Animal Care and Use Committee (IACUC, ID: IA16-00008 TR1 and PROT0201900147), according to national and institutional guidelines. Surface antigen-guided Genome-wide CRISPR Screens

THP-1-Cas9-AFP-BFP and RN2-Cas9-cOVA-BFP cells were transduced with the Brunello sgRNA library or Brie sgRNA library virus (Doench et al., 2016), respectively, at a low MOI (~0.3). On day 2 post-transduction, GFP⁺ percentage was assessed to determine infection efficiency and sgRNA coverage (~l,000X). Then, puromycin (1 (ig/ml) was added for 5 days to select infected (GFP⁺) cells. After selection, viable infected cells were isolated by Histopaque 1077 (Sigma Aldrich) and grown without antibiotics. On day 12 posttransduction of the genome-wide libraries, THP-1-Cas9-AFP-BFP and RN2-Cas9-OVA-BFP cells were stained with human TruStain Fcblock (BioLegend #422302, dilution 1:200) and mouse TruStain Fcblock (BioLegend #101320, dilution 1:200), respectively, for 10 mins at room temperature and then subsequently stained the THP-1-Cas9-AFP-BFP cells for APC- ET1402L1 (Liu et al., 2017) or APC-HLA-ABC (BioLegend #31 1410, dilution 1 :200), and stained the RN2-Cas9-cOVA-BFP cells for APC-H-2K^b:OVA (BioLegend #141606, dilution 1 :200), for 40 mins at 4°C followed by flow cytometry⁷ gating on high and low 10% of the population. 3-5 million cells were collected for each sorted population followed by genomic DNA (gDNA) extraction using the QIAGEN DNA kit (#51306) according to manufacturer’s protocol. For library construction, gDNA was amplified for 25 cycles using EX-Taq (Takara) and primer pairs that contain barcodes. PCR products were size-selected using AMPure XP beads (Beckman Coulter). Barcoded libraries were then sequenced using the Next-Seq instrument (single-end, 80 cycles). The LFCs of each screen were calculated by the average Iog2 fold change (Highl 0% / Low 1 %) of all sgRNAs targeting a given gene. We plotted the LFCs of selected sgRNAs using non-targeting control as background. The plots were generated with R package ggplot2 (version 3.3.6).

Focused in vivo CRISPR screens

C1498-Cas9-GFP or B16F10-OVA-Cas9-GFP cells were transduced with a focused library containing sgRNAs targeting the 44 common AP repressors and several published controls. Transduced cells sorted by FACS then expanded for 6 days before being injected in either CD8⁺ T cell-depleted mice or immune-competent Cas9-GFP mice. A portion of the cells was cultured in vitro to assess the essentiality⁷ of each candidate. Transplanted cancer cells were then collected on day 15. gDNA was extracted for library preparation and sgRNA representations were evaluated using the Next-Seq instrument (single-end, 80 cycles). The LFCs of immune selection w ere calculated by⁷ the average log2 fold change (Isotype / anti- CD8) of all sgRNAs targeting a given gene, while the essentialities were calculated by the average log2 fold change (Day 9 /Day 3) of all sgRNAs targeting a given gene.

Validation of screen candidates

THP-1-Cas9-AFP-BFP and RN2-Cas9-OVA-BFP cells were transduced with indicated sgRNAs, harvested on day 4 and day 8, followed by washing with FACS buffer (PBS + 2% FBS). Human TruStain FcX™ (BioLegend #422302, dilution 1 : 100) or mouse TruStain FcX™ (BioLegend #101320, dilution 1 : 100) was used for Fc receptor blocking at room temperature for 15 min. THP-1-Cas9-AFP-BFP cells were then stained using the following fluorescently labeled antibodies: APC-ET1402L1 (Liu et al., 2017), PE-HLA-ABC (BioLegend #311406, dilution 1: 100), PerCP/Cy5.5-CD147 (BioLegend # 306220, dilution 1 : 100) and APC/Cy7-HLA-A2 (BioLegend #343310, dilution 1 : 100) for 40 mins at 4 °C, while RN2-Cas9-cOVA-BFP cells were stained with: APC-H-2K^b:OVA (BioLegend #141606. dilution 1 : 100), PE-H-2K^b (BioLegend #116508, dilution 1 : 100) and APC-CD98 (BioLegend #128212, dilution 1 : 100) for 40 mins at 4 °C. Data were acquired on a BD LSRFortessa™ Cell Analyzer or BD ® LSR II Flow Cytometer and analyzed by the FlowJo software.

Intracellular staining for flow cytometry

Intracellular staining was performed using the eBioscience™ Intracellular Fixation & Permeabilization Buffer Set (Invitrogen. Cat# 88-8824-00) following the manufacture’s protocol.

Surface HLA internalization

THP-1-Cas9 cells were transduced with indicated sgRNAs and cultured for 8 days. Cells were then stained for purified antibodies against human HLA-A2 (BioLegend #343302, dilution 1 : 100) for 40 mins at 4 °C. Cells were then incubated at 37 °C for the indicated time before putting on ice and staining for APC Goat anti-mouse IgG (BioLegend # 405308, dilution 1 : 100) for 30 mins on ice. DAPI (Sigma Aldrich #D9542-1MG) was used to exclude dead cells. Data were acquired on a BD LSRFortessa™ Cell Analyzer and analyzed by the FlowJo software.

T cell activity assay by B3Z T cell hybridoma co-culture

RN2-Cas9-OVA cells were transduced with indicated sgRNA, sorted and expanded for 8 days, followed by co-culturing with B3Z T cell hybridoma as described previously (Lu et al., 2018). Briefly, 10⁵ transduced RN2-Cas9-OVA cells were fixed in 1% paraformaldehyde at 37 °C for 10 min. followed by incubation with 200 mM glycine (dissolved in PBS, pH 7.5) at 37 °C for 5 min to stop the fixation. Cells were then washed three times with B3Z medium. A total of 5 x 10⁴ B3Z T cell hybridoma cells were added per well and cultured for 10 h at 37 °C. The supernatant was harvested and secreted IL-2 was then measured by ELISA following the manufacturer’s protocol (BD Biosciences #555148).

OT-I T cell killing assay

RN2-Cas9-OVA-BFP cells were transduced with indicated sgRNA. sorted and expanded for 8 days followed by co-culturing with OT-I C8⁺ T cells. Briefly. 50.000 sgRNA- transduced RN2-Cas9-OVA-BFP cells were seeded into each well of a 96-well U-bottom plate together with 4,000 CD8⁺ T cells freshly isolated from the lymph nodes of OT-I mice or C57BL/6J mice in RPMI-1640, supplemented with 10% FBS, 25 mM HEPES, 1 mM sodium pyruvate, lx Pen/Strep, lOng/ml murine IL2 (PeproTech) and 50 pm -ME. Flow cytometric analyses were applied to assess viable cell numbers for the tumor cells using AccuCheck counting beads (Invitrogen) at 44 hours post-co-culture. DAPI (Sigma Aldrich #D9542- 1MG) was used to exclude dead cells. “% OT-I T cell killing” was calculated as 1 - (cell # in the OT-I group/cell # in the C57BL/6J group).

NY-ESO-1 TCR-T cell killing assay

Human CD8⁺ T cells were purchased from STEMCELL Technologies. Cells were thawed and cultured at 1,000,000 cells/mL in RPMI-1640, supplemented with 20% FBS. 25 mM HEPES, 1 mM sodium pyruvate, lx Pen/Strep, lx NEAA, lOng/ml human IL2 (PeproTech) and 50 pm |3-ME. Dynabeads™ Human T-Activator CD3/CD28 were added to stimulate T cells. After 48 hours of activation. T cells were lentivirally transduced with the NY-ESO-1 TCR-T construct to generate NY-ESO-1 TCR-T cells. T cells were then rested for 3 days without Dynabeads before setting up the co-culture system.

For setting up the co-culture assay, THP-1-Cas9-AFP-BFP cells were transduced with indicated sgRNA, sorted and expanded for 8 days, then induced with Azacitidine (5 pM) for 3 days, followed by co-culturing with NY-ESO-1 TCR-T cells. Briefly, 50.000 sgRNA- transduced THP-1-Cas9-AFP-BFP cells w ere seeded into each well of a 96-well U-bottom plate together with 2,500 non-transduced human CD8⁺ T cells or human NY-ESO-1 TCR-T cells generated as described in RPMI-1640, supplemented with 20% FBS, 25 mM HEPES, 1 mM sodium pyruvate, lx Pen/Strep, lx NEAA, lOng/ml human IL2 (PeproTech) and 50 pm P-ME. Flow cytometric analyses were applied to assess viable cell numbers for the tumor cells using AccuCheck counting beads (Invitrogen) at 96 hours post-co-culture. DAPI (Sigma Aldrich #D9542-1MG) was used to exclude dead cells. “% NY-ESO-1 T cell killing” was calculated as 1 - (cell # in the NY-ESO-1 T cell group/cell # in the non-transduced group).

OP-Puro assay

THP-1-Cas9 cells were transduced with indicated sgRNA. On day 8 posttransduction, cells were harvested and the Click-iT Plus OPP Alexa Fluor 647 Protein Synthesis Assay Kit was used to assess the global translation following the manufacture's protocol.

Tumor inoculation and dissection

For tumor inoculation, 1.000,000-1,500.000 cancer cells (C1498-Cas9-GFP, B16F10- OVA, CT26) were subcutaneously injected into the C57BL/6J or BALB/cJ mice. Tumor sizes were measured every three days.

For tumor dissection. B16F10-OVA tumors were isolated on day 15 post-inoculation. Tumors were subjected to image and weight upon harvest. Liberase™ TM (7.7 pg/ml, Roche) and DNase I (100 pg/ml. Invitrogen) were then used to digest the tumor chunks. Single-cell suspensions were generated by smashing the digested tumor chunks through 70 pm strainers (BD Biosciences). Tumor cells were then subjected to flow cytometric analyses.

For measuring the tumor-infiltrating lymphocytes (TILs), mouse TruStain FcX™ (BioLegend #101320, dilution 1: 100) was used for Fc receptor blocking at room temperature for 15 min. TILs were then stained using the following fluorescently labeled antibodies: BV605-CD3E (BD Biosciences #563004, dilution 1 :200), PE-B220 (BD Biosciences #553090. dilution 1:200), PerCP/Cy5.5-NKl. l (BioLegend #108728. dilution 1 :200), PE/Cy7-CD4 (BioLegend #100422, dilution 1 :200). APC-CD8 (Thermo Fisher Scientific #17-0081-82, dilution 1:200), APC/Cy7-CD45.2 (BioLegend #109824, dilution 1 :200) for 40 mins at 4 °C. DAPI (Sigma Aldrich #D9542-1MG) was used to exclude dead cells. Data were acquired on a BD LSRFortessa™ Cell Analyzer or BD ® LSR II Flow Cytometer and analyzed by the FlowJo software.

For measuring MHC-I expression on tumor cells, mouse TruStain FcX™ (BioLegend #101320, dilution 1 : 100) was used for Fc receptor blocking at room temperature for 15 min. Tumor cells were then stained using the following fluorescently labeled antibodies: PE/Cy7- H2-K^b/D^b (BioLegend #114616, dilution 1:200), APC-CD98-APC (BioLegend #128212, dilution 1 :200) for 40 mins at 4 °C. DAPI (Sigma Aldrich #D9542-1MG) was used to exclude dead cells. Data were acquired on a BD LSRFortessa™ Cell Analyzer or BD ® LSR II Flow Cytometer and analyzed by the FlowJo software.

Construction of the Split-GFP system

The tripartite split-GFP system (Foglieni et al., 2017) was adapted to detect the HLA- A2 / SUSD6 / TMEM127 complex. Briefly, HLA-A2 was fused to the tenth (T10) P-strand of GFP at its C-terminal (HLA-A2-T10), while TMEM127 was fused to the eleventh (T11) - strand of GFP at its C-terminal (TMEM127-T11). SUSD6 was fused to the first to ninth P- strand of GFP (GFP 1-9) at its C-terminal (SUSD6-GFP1-9). 293T cells were transduced with either the HLA-A2-T10 alone or the combination of HLA-A2-T10, TMEM127-T11 and SUSD6-GFP1-9. Transduced cells were sorted and expanded before proceeding to immunofluorescence staining.

Immunofluorescence Staining

Sorted HLA-A2-T10, TMEM127-T11 and SUSD6-GFP1-9- transduced 293T and HLA-A2-T10-transduced cells were seeded onto Poly-L-Lysine (Sigma) precoated coverslips and cultured overnight. Cells were washed with PBS, then fixed with 4% (vol/vol) paraformaldehyde for 10 min at room temperature. Cells were then permeabilized with 0.5% Triton X-100 and blocked with 1% BSA in Tris-Buffered Saline and Tween 20 (TBST). Coverslips were stained overnight at 4 °C with PE-anti-huCD107a (Miltenyi. 130-111-621, dilution 1 : 100) and APC-anti-HA (BioLegend #901523, dilution 1 : 100) diluted in blocking buffer. After washing, coverslips were mounted with 10 pl of SlowFade Glass Soft-set antifade mountant (Invitrogen) onto slides. Slides were analyzed on a Zeiss 880 confocal microscope. For the split-GFP experiments, slides were analyzed with the AiryScan setting on a Zeiss 880 confocal microscope (microscopynotes.com/880/airyscan/index.html). ImageJ software was used to analyze the data.

RNA extraction and quantitative PCR

Total RNA was extracted from cells using a commercially available RNA extraction Kit (QIAGEN). Reverse transcription was performed with a High-Capacity RT kit (Applied Biosystems). Quantitative PCR (qPCR) was performed using the CFX96 Touch Real-Time PCR Detection System (Bio-Rad) with a 20 pL reaction, composed of 100 ng of cDNA, 10 pL Power SYBR Green master mix (Applied Biosystems), and 250 nM of each forward and reverse primer. Surface HLA-A2 kinetics assay

To determine the involvement of SUSD6 and TMEM127 in the degradation of surface MHC-I molecule, THP1-Cas9 cells transduced with sgNT, sgSUSD6, or sgTMEM127 were treated with 20 pg/ml Cycloheximide (CHX, Sigma) to inhibit protein biosynthesis, 20pM Bafilomycin Al (BafAl, Sigma) to inhibit lysosomal degradation, or 1 pM Epoxomicin (Epox, APExBIo) to inhibit proteasomal degradation, at 37 °C for 0 h, 3 h, 6 h. 9 h, 12 h, and 24 h. Cells were then stained and checked by flow cytometry by using the following antibodies: human TruStain FcX™ (BioLegend #422302, dilution 1: 100), APC/Cy7-HLA- A2 (BioLegend #343310, dilution 1 :100) and PerCP/Cy5.5-CD147 (BioLegend #306220, dilution 1 : 100). DAPI (Sigma Aldrich #D9542-1MG) was used to exclude dead cells. Data were acquired on a BD LSRFortessa™ Cell Analyzer or BD ® LSR II Flow Cytometer and analyzed by the FlowJo software.

Western blot

Cas9-expressing THP1 and RN2 cells were transduced with indicated sgRNA. B16F10-OVA and CT26 cells were transduced with indicated shRNA for silencing the targeted genes. Cells were lysed at 7-10 days post-transduction and the lysates were harvested for western blot using the following antibodies: from Abeam (Waltham, MA): rabbit anti- HLA-A antibody (ab52922, dilution 1 : 2,000) and rabbit anti-beta 2 Microglobulin antibody (ab75853, dilution 1:2,000); from Invitrogen (Waltham, MA): rabbit anti-KIAA0247 antibody (PA5-56481, 1:500); from Bethyl Laboratories (Montgomery, TX): rabbit anti- TMEM127 antibody (A303-450A. dilution 1 : 1,000); from BioLegend (San Diego, CA): Direct-Blot™ HRP anti-[3-actin antibody (664804, dilution 1 : 10,000); and from Enzo Life Sciences (Farmingdale, NY): rat anti-Grp94 antibody (ADI-SPA-850-F, dilution 1 :2,000).

For Co-immunoprecipitation samples, the following antibodies were used: from BioLegend (San Diego, CA): Direct-Blot™ HRP anti-V5-tag Antibody (680603. dilution 1 :2,000). Direct-Blot™ HRP anti-FLAG Tag Antibody (637311, 1:2.000), Direct-Blot™ HRP anti-HA. l 1 Epitope Tag Antibody (901519, dilution 1 :2,500), Direct-Blot™ HRP anti- P-actin antibody (664804, dilution 1: 10,000), and Direct-Blot™ HRP anti-Ubiquitin Antibody (646303, dilution 1:2,000); from Abeam (Waltham. MA): rabbit anti-HLA-A antibody (ab52922, dilution 1:2,000); from Enzo Life Sciences (Farmingdale, NY): rat anti- Grp94 antibody (ADI-SPA-850-F, dilution 1:2,000); and from Proteintech (Rosemont, IL): rabbit anti-PD-Ll antibody (17952-1-AP, dilution 1:500). Co-immunoprecipitation ( Co-IP)

293T cells were lentivirally transduced to express SUSD6-FLAG. TMEM 127-HA. and/or WWP2-V5. 4-7 days post-transduction, cells were treated with 20uM Bafilomycin Al (Sigma) for 6 hours to inhibit lysosomal degradation and subsequently cross-linked by DSP (Sigma) to stabilize transient molecular interactions following the manufacture’s protocol. Cells were then lysed in TBS (20mM Tris-HCl, 150mM NaCl, pH 7.6) supplemented with 2mM CaCh, 1% digitonin (Sigma), and protease inhibitor cocktail (Roche) for 1 hour at 4 °C. Cell lysate was pre-cleared with Protein G beads (Invitrogen) for 1 hour at 4 °C. Antibody was added to the pre-cleared lysate and incubated at 4 °C for overnight. Protein G beads were then added for immunoprecipitation and incubated at 4 °C for 3 h. Following that, beads were washed three times with lysis buffer and twice with TBS. After boiling the beads in Laemmli Sample Buffer containing 2-Mercaptoethanol (Sigma), the supernatant was used for the western blot.

Split-luciferase assay

293T cells were transfected in a 384-well plate with indicated IgBit- or smBit-tagged HLA-A, SUSD6, TMEM127, or WWP2 for 18 to 24 h. Media was then changed to Opti-Men (Gibco), and Nano-Gio® Live Cell Assay System (Promega) was added to each well following the manufacture’s protocol. Luminescence was detected and quantified using an EnSpire plate reader (PerkinElmer).

Gene Ontology Analyses

Gene Ontology (GO) analyses were performed for genes that were positively or negatively selected in the screen using R package clusterProfiler (3.10.0). Enrichment scores were then plotted with R package ggplot2 (version 3.3.6).

Enrichment Score

Fisher exact test was used to calculate the enrichment scores (odd ratios) of the 5 functional gene sets (defined in Fig. 1H plus the putative surface proteins) among the 44 gene set or the 34 gene set using the whole genome as background.

Statistical analysis of non-scRI\’Aseq data

Two-tailed student’s West, one-way ANOVA, or two-way ANOVA were applied for statistical analysis in GraphPad Prism. P values were calculated and reported as follows: ns, not significant; *, p < 0.05; **, p < 0.01; ***, p < 0.001. The error bars in each figure represented standard error of the mean (SEM). n referred to the number of independent experiment unless specified.

The following table provides single guide RNA (sgRNA) target sequences used to perform experiments discussed above:

The following tables provides sequences comprised by shRNA constructs which were used to produce data described in this disclosure. The sequences include their RNA equivalents (U substituted for T), RNA sequences transcribed from each sequence, complementary' DNA and RNA sequences, and reverse complementary DNA and RNA sequences:

The following table provides 97-mer sequences comprised by shRNA constructs which were used to produce data described in this disclosure. shRNA constructs (produces as RNA) table

The following table provides siRNA sequences derived from the shRNA constructs: siRNA constructs table

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. It is intended that the specification and examples be considered as exemplary only. References. This reference listing is not an indication that any reference is material to patentability.

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Claims

What is claimed is:

1 . A method for modulating major histocompatibility complex (MHC)-I and/or peptide- MHC-I (pMHC-I) expression or function by cells for use in prophylaxis or therapy of cancer or an autoimmune disorder, the method comprising modifying the cells by changing expression inhibiting the function of a protein encoded by at least one gene that is a component of an MHC-I modulator within the cells, and wherein the at least one gene is SUSD6, TMEM127, WWP2, STUB1, mLRPlO.

2. The method of claim 1, comprising changing the expression of the at least one gene.

3. The method of claim 2, wherein the cells that are modified are antigen presenting cells.

4. The method of claim 2, wherein the cells that are modified are macrophages, dendritic cells, natural killer (NK) cells, T cells which are optionally af> or y5 T cells, cancer cells, or a combination thereof.

5. The method of claim 2, wherein the cells that are modified comprise macrophages, dendritic cells, natural killer cells or T cells, that are modified to express a chimeric antigen receptor (CAR).

6. The method of claim 2, comprising decreasing expression of the at least one gene, and wherein the cells that are modified are capable of participating in a prophylactic or therapeutic anti-cancer response when the cells are present in an individual who has the cancer or is at risk for developing the cancer, and wherein optionally the cancer is resistant to immune checkpoint inhibition.

7. The method of claim 2, comprising increasing expression of the at least one gene, and wherein the cells that are modified are capable of participating in a prophylactic or therapeutic response for an autoimmune disease when the cells are present an individual in who has the autoimmune disease or is at risk for developing the autoimmune disease.

8. The method of claim 2, wherein the changing the expression of the at least one gene comprises modifying DNA in the cells comprising the gene to reduce its expression, or delivering to the cells an agent that inhibits expression of the gene but does not modify the DNA of the cells.

9. The method of claim 8, comprising administering to the cells a clustered regularly interspaced short palindromic repeats (CRISPR) system that modifies the DNA.

10. The method of claim 8, comprising administering to the cells a polynucleotide or oligonucleotide that inhibits expression of a protein encoded by the at least one gene and/or participates in degradation of an mRNA transcribed from the at least one gene.

11. The method of claim 10, wherein the at least one gene is SUSD6 or TMEM127.

12. The method of claim 11, wherein the cells that are modified are capable of participating in a prophylactic or therapeutic anti-cancer response when the cells are present in an individual who has the cancer or is at risk for developing the cancer.

13. A method for prophylaxis or treatment of a condition for an individual in need thereof, the method comprising administering to the individual an agent that changes expression or inhibits the function of a protein encoded by at least one gene that is a component of an MHC-I modulator within the cells, and wherein the at least one gene is SUSD6, TMEM127, WWP2, STUB1. ovLRPlO.

14. The method of claim 13, comprising changing the expression of the at least one gene.

15. The method of claim 13, wherein changing the expression of the at least one gene comprises reducing the expression.

16. The method of claim 15, wherein the individual is need of treatment for cancer.

17. The method of claim 13, wherein changing the expression of the at least one gene comprises increasing the expression.

18. The method of claim 17, wherein the individual is need of treatment for an autoimmune disease.

19. A method for prophylaxis or treatment of a condition for an individual in need thereof, the method comprising administering to the individual modified cells that are modified such that expression of at least one gene that is a component of an MHC-I modulator within the cells is changed, and wherein the at least one gene is SUSD6, TMEM127, WWP2, STUB1, wLRPlO.

20. The method of claim 19, wherein the cells that are modified are macrophages, dendritic cells, natural killer (NK) cells, T cells which are optionally a0 or y5 T cells, cancer cells, or a combination thereof.

21. The method of claim 19, wherein the cells that are modified comprise macrophages that are modified to express a chimeric antigen receptor (CAR).

22. The method of claim 19, wherein expression of the at least one gene is reduced.

23. The method of claim 22, wherein the individual has a cancer, and wherein optionally the cancer is resistant to immune checkpoint inhibition.

24. The method of claim 19, wherein expression of the at least one gene is increased.

25. The method of claim 19, wherein the individual is need of treatment for an autoimmune disease.

26. A method comprising identifying an individual in need of treatment for cancer or an autoimmune disease, the method comprising determining expression of one or more of SUSD6, TMEM 127, WWP2, STUB1, or LRP10 that is different from a control value of expression of SUSD6, TMEM127, WWP2, STUB1, or LRP10, said control value being obtained from one or more individuals who do not have the cancer or the autoimmune disease, respectively.

27. The method of claim 26, further comprising determining that the individual is in need of treatment for the cancer, and administering to the individual: i) an agent that inhibits the expression of SUSD6, TMEM127. WWP2. STUB1, or LRP10, or ii) modified cells that are modified such that expression at SUSD6, TMEM127, WWP2, STUB1, ovLRPlO is reduced.

28. The method of claim 26, further comprising determining that the individual is in need of treatment for the autoimmune disease, and modifying cells that are either present in the individual or are administered to the individual, wherein the cells are modified such that expression of SUSD6, TMEM127, WWP2. STUB1, or LRP10 is increased.

29. Modified cells produced according to any one of claims 1-12.