Therapeutically Increasing MHC-I Expression Potentiates Immune Checkpoint Blockade

Abstract

Immune checkpoint blockade (ICB) therapy revolutionized cancer treatment, but many patients with impaired MHC-I expression remain refractory. Here, we combined FACS-based genome-wide CRISPR screens with a data-mining approach to identify drugs that can upregulate MHC-I without inducing PD-L1. CRISPR screening identified TRAF3, a suppressor of the NFκB pathway, as a negative regulator of MHC-I but not PD-L1. The Traf3-knockout gene expression signature is associated with better survival in ICB-naïve patients with cancer and better ICB response. We then screened for drugs with similar transcriptional effects as this signature and identified Second Mitochondria-derived Activator of Caspase (SMAC) mimetics. We experimentally validated that the SMAC mimetic birinapant upregulates MHC-I, sensitizes cancer cells to T cell-dependent killing, and adds to ICB efficacy. Our findings provide preclinical rationale for treating tumors expressing low MHC-I expression with SMAC mimetics to enhance sensitivity to immunotherapy. The approach used in this study can be generalized to identify other drugs that enhance immunotherapy efficacy. SIGNIFICANCE: MHC-I loss or downregulation in cancer cells is a major mechanism of resistance to T cell-based immunotherapies. Our study reveals that birinapant may be used for patients with low baseline MHC-I to enhance ICB response. This represents promising immunotherapy opportunities given the biosafety profile of birinapant from multiple clinical trials.This article is highlighted in the In This Issue feature, p. 1307.

Figure 1.. CRISPR screens identify novel regulators of MHC-I.

(A) Workflow of using CRISPR screens to identify the positive or negative regulators of MHC-I and/or PD-L1. We transduced B16F10 mouse melanoma cells with an in-house-designed genome-wide sgRNA library, expanded the transduced cells, and stimulated the cells with 0.1ng/ml (low dose) or 10ng/ml IFNg (high dose) for different levels of MHC-I/PD-L1 induction. We then performed FACS to isolate the MHC-I^hiPD-L1^hi, MHC-I^hiPD-L1^lo, MHC-I^loPD-L1^hi, and MHC-I^loPD-L1^lo sub-populations. We amplified and sequenced the gRNAs in these sub-populations as well as the bulk pre-sorting population to identify genes that were enriched in each sorted sub-population. MHC-I and/or PD-L1 regulators are expected to be enriched in the sub-populations as indicated. (B) Titration of IFNγ concentration to test its effect on MHC-I and PD-L1 expression. Histogram of H2-K^b and PD-L1 levels assessed by flow cytometry following two-day treatment with different concentrations of IFNγ. (C) CRISPR screen reveals known and novel candidate regulators of MHC-I and/or PD-L1. Ranked dot plots of gene enrichment in each sorted sub-population compared to the unsorted population are shown. The X axis shows the rank of each gene, and the Y axis shows the log2 enrichment of sgRNAs for each gene in the indicated sub-population compared to the unsorted population. (D) Immunoblot of B16F10 cells with indicated genotypes shows good efficiency of Traf3 knockout or overexpression. (E-F) Validation of TRAF3 as a negative regulator of MHC-I with IFNγ induction. B16F10 cells transduced with control sgRNA or sgTraf3 were cultured for 48 hours, with IFNγ concentrations as indicated, and then assessed on their MHC-I and PD-L1 levels. (E) Typical histogram of H2-K^b and PD-L1 FACS plot of control or Traf3-deficient B16F10 cells in each treatment condition. (F) Quantification of median fluorescence intensity (MFI) of H2-K^b or PD-L1 from (E). Values are normalized to the sgControl group with vehicle treatment. (**P < 0.01, ***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test comparing sgTraf3 and sgControl in each condition). (G-H) Validation of TRAF3 as a negative regulator of MHC-I with type-I IFN induction. B16F10 cells transduced with control sgRNA or sgTraf3 were cultured for 48 hours with treatment as indicated, and then assessed on their MHC-I and PD-L1 levels. 500U/ml IFNα or IFNβ was used. (G) Typical histogram of H2-K^b and PD-L1 FACS plot of control or Traf3-deficient B16F10 cells in each treatment condition. (H) Quantification of MFI of H2-K^b or PD-L1 from (G). Values are normalized to the sgControl group with vehicle treatment. (**P < 0.01, ***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test comparing sgTraf3 and sgControl in each condition).

Figure 2.. TRAF3 deficiency upregulates MHC-I through NF-κB.

(A) RNA-seq of B16F10 cells transduced with sgControl or sgTraf3 shows upregulation of MHC-I-related genes in the absence of Traf3. Heatmap of differential expression of genes induced by TRAF3 deficiency with IFNγ treatment. (B) GSEA enrichment analysis of upregulated pathways (GO biological pathway) in sgTraf3 cells compared to sgControl cells with IFNγ treatment. Multiple pathways, such as antigen presentation and NF-kB signaling, were upregulated by the deletion of Traf3. (C) ATAC-seq of Traf3-normal or -deficient B16F10 cells revealed that TRAF3 deficiency leads to higher chromatin accessibility near genes encoding components of the MHC-I complex. (D) Cistrome-GO analysis of the more accessible regions in sgTraf3 compared to sgControl cells with IFNγ treatment. (E) Cistrome toolkit analysis of ATAC-seq data revealed that DNA-binding sites of RELA were more open in the Traf3-deficient cells. (F) Enrichment of motifs in the accessible chromatin regions specific to Traf3-deficient cells. The top enriched motifs (RELA) is shown. (G) Typical immunoblot of NF-κB signaling components in Traf3-normal or -deficient B16F10 cells in response to IFNγ induction. B16F10 cells transduced with sgControl or sgTraf3 were induced by 1ng/ml IFNγ for 0, 0.5, or 24 hours, and then harvested for immunoblot. Data from 1 typical experiment out of 3 biological replicates is shown. (H) Quantification of immunoblot signals from panel (G) based with 3 biological replicates. TRAF3 deletion leads to upregulated NF-kB signaling. (I-J) B16F10 cells transduced with control sgRNA or sgTraf3 were treated with vehicle control, IFNγ (1ng/ml), and/or TPCA-1 (1μM) for 48 hours, and then assessed on their MHC-I and PD-L1 levels. (I) Typical histogram of H2-K^b and PD-L1 FACS plot of control or Traf3-deficient B16F10 cells in each treatment condition. (J) Quantification of MFI of H2-K^b or PD-L1 from (I). Values are normalized to sgControl group with vehicle treatment. (***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test comparing IFNγ and IFNγ+TPCA groups).

Figure 3.. TRAF3 deletion sensitizes cancer cells to T-cell-driven cytotoxicity.

(A) Workflow of testing the role of TRAF3 in regulating the response of cancer cells to T-cell-driven cytotoxicity through in vitro co-culture. Traf3-normal or -deficient B16F10 cells were cultured with antigen-specific CD8⁺ T cells (Pmel-1 or OT-I) for 1–3 days. Cell number and cell surface MHC-I/PD-L1 expression were quantified by FACS. (B-C) Relative B16F10 cell number after co-culture with (B) OT-I T cells or (C) Pmel-1 T cells at different E:T ratios revealed a higher sensitivity of Traf3-deficient B16F10 cells to T-cell-mediated cytotoxicity. For co-culture with Pmel-1 T cells, B16F10 cells were pre-treated with 1ng/ml IFNγ for 12 hours prior to the co-culture. The bar plots present the relative cell number in each group, normalized to the cell number in the sgControl group in each E:T condition. Mean ± s.d. and individual replicate values are shown for each group. (**P < 0.01, ***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test comparing sgTraf3 and sgControl in each condition). (D) Relative MFI of H2-K^b or PD-L1 of B16F10 cells co-cultured with OT-I T cells. Values are normalized to the sgControl group in E:T = 0.25 condition. Mean ± s.d. and individual replicate values are shown for each group. (**P < 0.01, ***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test comparing sgTraf3 and sgControl in each condition). (E) Relative B16F10 cell number after co-culture with Pmel-1 T cells at different E:T ratios revealed a lower sensitivity of Traf3-overexpressing B16F10 cells to T-cell-mediated cytotoxicity. The bar plots present the relative cell number in each group, normalized to the cell number in the pEF1α group in each E:T condition. Mean ± s.d. and individual replicate values are shown for each group. (**P < 0.01, ***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test comparing pEF1α-Traf3 and pEF1α in each condition). (F) Workflow of testing the role of TRAF3 in modulating the ICB response in vivo. 4×10⁵ B16F10 cells (Traf3-normal or -deficient) were transplanted subcutaneously into syngeneic recipient mice. Starting on Day 6 post-transplantation, we treated the recipients with control IgG or combination ICB every 3rd day for a total of 4 doses. We monitored tumor size and recipient survival. (G) Longitudinal tumor size of sgControl or sgTraf3 tumors treated by control IgG or ICB. Mean ± s.e.m. is shown for each group at each time point. (**P < 0.01, ***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test comparing sgTraf3 and sgControl in each condition). (H) Kaplan-Meier curves of recipients of sgControl or sgTraf3 tumors treated by control IgG or ICB. The sgTraf3 cohort with ICB treatment survived significantly longer than the other groups. (**P < 0.01; Log-rank test with Benjamini-Hochberg adjustment of multiple comparisons).

Figure 4.. Traf3-knockout signature is correlated with higher MHC-I in primary patient samples.

(A-C) Traf3 knockout signature is positively correlated with (A) MHC-I expression, (B) CD8⁺ T cell infiltration, and (C) patient survival in the TCGA SKCM dataset. PCC: Pearson correlation coefficient. (D) TIDE-predicted ICB responders showed higher Traf3-knockout signature values in the TCGA SKCM dataset. (E) Expression of MHC-I component or related genes in MHC-I-high or -low samples. (F) GSEA of differentially expressed genes in MHC-I-high versus MHC-I-low samples. (G) MHC-I-high samples show higher expression of genes involved in antigen presentation, NF-κB signaling, TNF signaling, and Toll-like receptor pathways. (H) Traf3-knockout signature score in MHC-I-high or MHC-I-low RNA-seq samples. (I) H3K27ac ChIP-seq results for the HLA-A/B/C loci in MHC-I-high or MHC-I-low samples. (J) Top 200 genes with the higher regulatory potential value in MHC-I-high versus MHC-I-low H3K27ac ChIP-seq samples. (K) Traf3-knockout signature score of H3-K27ac ChIP-seq regulatory potential values in MHC-I-high or -low samples. (L) Cistrome-GO enrichment analysis of H3K27ac ChIP-seq peaks with stronger signal in MHC-I-high compared to MHC-I-low samples.

Figure 5.. Traf3-knockout signature is correlated with better response to ICB.

(A-D) Traf3 knockout signature is positively correlated with (A) MHC-I expression, (B) intratumoral CTL infiltration, (C) ICB response, and (D) overall survival and progression-free survival in patients treated by anti-PD-1 or combined anti-PD-1 and anti-CTLA-4 in the Gide et al. (71) study in melanoma. (E-H) Traf3 knockout signature is positively correlated with (E) MHC-I expression, (F) intratumoral CTL infiltration, (G) ICB response, and (H) overall survival and progression-free survival in patients treated by anti-PD-1 or combined anti-PD-1 and anti-CTLA-4 in the Mariathasan et al. (72) study in urothelial carcinoma. (I) Traf3 knockout signature is positively correlated with MHC-I expression and cytotoxic T cell infiltration and negatively correlated with survival hazard in most ICB treatment clinical trials.

Figure 6.. Birinapant can specifically upregulate MHC-I and add to the efficacy of ICB treatment.

(A) Heatmap of the regulation of transcription of MHC-I components and PD-L1/PD-L2 in each drug treatment condition. Data are ordered by the magnitude of MHC-I regulation from the most upregulated (left) to the most downregulated (right). (B) Characterization of each drug treatment for effect on MHC-I expression and Traf3-knockout signature value. (C) Flow cytometry of B16F10 cells treated by IFNg and/or different concentrations of the SMAC mimetic birinapant (Bir). Typical histograms of H2-K^b and PD-L1 levels in each condition are shown. (D) The relative MFI of samples in (C). Mean ± s.d. is shown for each group. Values are normalized to the mean MFI at 0ng/ml IFNγ 0μM birinapant. (E) Relative B16F10 cell number after co-culture with OT-I T cells at different E:T ratios revealed a higher sensitivity of B16F10 cells to T-cell-mediated cytotoxicity under birinapant treatment. The bar plots present the relative cell number in each group, normalized to the cell number in the vehicle treatment group in each E:T condition. Mean ± s.d. and individual replicate values are shown for each group. (***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test). (F) Relative MFI of H2-K^b or PD-L1 of B16F10 cells co-cultured with OT-I T cells. Values are normalized to the vehicle treatment group in E:T = 0.25 condition. Mean ± s.d. and individual replicate values are shown for each group. (***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test comparing vehicle and SMAC treatment groups in each condition). (G) Longitudinal tumor size of tumors under different treatments. Mean ± s.e.m. is shown for each group at each time point. (**P < 0.01, ***P < 0.001; Two-way ANOVA with Benjamini-Hochberg post test). (H) GSEA of the bulk tumor RNA-seq data evaluating the gene sets that were upregulated in response to SMAC mimetic. (I) Quantification of Traf3 knockout signature in each treatment group revealed a trend toward upregulation in response to birinapant treatment.