CTLA-4 immune checkpoint blockade is clinically effective in a subset of patients with metastatic melanoma. We identify a subcluster of MAGE-A cancer-germline antigens, located within a narrow 75 kb region of chromosome Xq28, that predicts resistance uniquely to blockade of CTLA-4, but not PD-1. We validate this gene expression signature in an independent anti-CTLA-4-treated cohort and show its specificity to the CTLA-4 pathway with two independent anti-PD-1-treated cohorts. Autophagy, a process critical for optimal anti-cancer immunity, has previously been shown to be suppressed by the MAGE-TRIM28 ubiquitin ligase in vitro. We now show that the expression of the key autophagosome component LC3B and other activators of autophagy are negatively associated with MAGE-A protein levels in human melanomas, including samples from patients with resistance to CTLA-4 blockade. Our findings implicate autophagy suppression in resistance to CTLA-4 blockade in melanoma, suggesting exploitation of autophagy induction for potential therapeutic synergy with CTLA-4 inhibitors.

While several investigators have identified genomic markers of clinical outcome to CTLA-4 blockade (), discovery of robust transcriptional signatures for response to immune checkpoint therapy has been limited by small sample sizes and lack of validation cohorts. Along with important genomic markers that have highlighted resistance pathways common to various checkpoint inhibitors (), discovery of biomarkers specific to a given immune checkpoint may illuminate the processes distinguishing these inhibitory pathways. To interrogate and identify transcriptional determinants of clinical outcome specific to CTLA-4 blockade in advanced melanoma, we analyzed RNA sequencing (RNA-seq) data from 146 melanoma biopsies representing patients from three previously reported clinical studies comprising four clinical treatment cohorts () as well as both transcriptomic and DNA methylation data from The Cancer Genome Atlas (TCGA) (). These analyses allowed us to discover an unexpected role for cancer-germline antigens in primary resistance to CTLA-4 but not PD-1 blockade and to conduct studies implicating the involvement of autophagy dysregulation in clinical outcome to ipilimumab, setting the stage for future investigations in larger, prospective trials.

Antibodies targeting the cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) pathway in advanced melanoma have yielded lasting clinical responses in a subset of patients (). Combining CTLA-4 blockade with antagonists of an alternative immune checkpoint pathway, the programmed death (PD-1) pathway, increases response rates in metastatic melanoma compared with either agent alone and suggests the potential benefit of combining CTLA-4 blockade with other immunotherapeutics (). However, robust determinants of response and resistance to CTLA-4 blockade remain elusive, hindering efforts to rationally incorporate it in combinatorial strategies and to precisely pair it with patients most likely to respond.

In order to directly explore the association of MAGE-A protein levels and autophagy, we used an available subset of melanoma samples on the TMA (n = 58) for staining with microtubule-associated protein 1A/1B-light chain 3 (LC3A/B), a well-established marker of autophagosomal membranes (). MAGE-Atumors were commonly LC3B-expressing (71%, 34 of 48) compared to MAGE-Atumors (20%, 2 of 10, Fisher’s test, p = 0.004), indicating an in vivo attenuation of autophagy in samples with high MAGE-A levels ( Figure 4 E). Finally, IF staining of the clinical samples from the discovery cohort for expression of HMGB1 and MAGE-A proteins revealed ubiquitous expression of HMGB1 protein in 3 of 3 MAGE-Atumors and absent HMGB1 expression in 2 of 2 MAGE-Atumors and the MAGE-AA375 human xenograft ( Figure 4 F). Taken together, these results suggest that the MAGE-A proteins are associated with suppression of autophagy in vivo in melanoma, potentially disrupting the development of optimal anticancer immunity and driving primary resistance to CTLA-4 blockade ( Figure 4 G).

We also considered the results of a recent in vitro ubiquitination screen of >9,000 recombinant proteins to identify protein targets of the MAGE-TRIM28 complex (). In addition to known targets such as AMPK, high-mobility group box 1 (HMGB1), a protein with well-described roles in both autophagy and immunogenic cell death that is required for dendritic cell-mediated priming of an adaptive immune response (), was identified as a lead target ( Figure 4 B). To investigate whether HMGB1 was a potential target of the MAGE-TRIM28 complex in melanoma tumors in vivo, we enumerated on a cell-by-cell basis the relative expression of HMGB1 and MAGE-A in tumor sections of a tissue microarray (TMA) comprising 100 samples (9 benign nevi tumors, 91 primary and metastatic melanomas) through immunofluorescence (IF) staining. We found that the fraction of HMGB1-positive cells was comparable in MAGE-Acells from both benign nevi and malignant tumors but was significantly reduced in MAGE-Acells (26% and 31% versus 8%, Chi-square test p < 2.2 × 10 Figure 4 C). We also observed mutual exclusivity of HMGB1 and MAGE-A proteins within the same tumor ( Figure 4 D).

We hypothesized that autophagy would be suppressed in human melanomas with elevated MAGE-A protein levels to mediate MAGE-A-driven primary resistance to CTLA-4 blockade, and hence sought to investigate whether CRMA expression was negatively associated with markers of autophagy. To explore this hypothesis, we first evaluated the potential targets of the MAGE-TRIM28 complex by examining the list of proteins negatively correlated with CRMA proteins in human melanomas from The Cancer Protein Atlas (TCPA) (see STAR Methods for details). In this unbiased analysis, the only significantly downregulated protein in tumors with high expression of the CRMA locus was 14-3-3 protein zeta (14-3-3ζ), a known activator of autophagy that acts through the AMPK pathway () ( Figure 4 A, t test, p = 0.0002, false discovery rate [FDR] = 0.05).

(F) Immunofluorescence staining for MAGE-A and HMGB1 shows mutual exclusion in five patient samples from the discovery cohort in addition to a human xenograft melanoma. Magnification ×400.

(E) A higher proportion of MAGE- tumors are positive for LC3B, a marker of autophagy, by IHC staining compared to MAGE + tumors in the melanoma TMA (p = 0.004) (top). Examples of LC3B + and LC3B − tumors, magnification ×400 (bottom).

(D) Examples from the TMA of mutually exclusive expression of MAGE-A and HMGB1 in cells from the same tumor. Magnification ×200.

(C) Immunofluorescence staining (IF) for MAGE-A and HMGB1 in a melanoma tissue microarray (TMA) shows a negative association between the two proteins in individual cells.

(B) In vitro screen for MAGE-TRIM28 ubiquitination substrates identifies HMGB1 (p = 0.04). AMPKα1 was used as a positive control (). Data represented as mean ± SD.

Although MAGE proteins have often been studied as immunotherapeutic targets bound to HLA molecules on the cell surface (), recent studies have attributed them with key oncogenic capacities. Critical to the oncogenic functions of MAGEs may be their ability to bind to and potentiate the activity of various E3 ubiquitin ligases (). MAGEA2, MAGEA3, and MAGEA6 all share specific binding to the TRIM28 ubiquitin ligase (). Extensive, in vitro mechanistic characterization of diverse cancer cell lines has revealed autophagy to be a prime target of the MAGE-TRIM28 complex (). Several other studies have demonstrated the potential for autophagy to induce potent immune responses by cytokine-mediated priming of antigen-specific interferon (IFN)-ɣ-producing T cells () and stimulation of immunogenic cell death (). A role for MAGE-A genes in autophagy regulation in vivo in human tumors, however, has not been previously demonstrated.

Because the CTLA-4 and PD-1 pathways drive markedly different immunobiologic processes, we hypothesized that transcriptional signatures of clinical outcomes to their antagonists would be unique to each pathway. Indeed, when we interrogated pre-treatment CRMA expression in a recently reported set of transcriptomic data from pre-PD-1 blockade treated melanomas, we found none of these genes to associate with clinical outcome to PD-1 blockade, suggesting the specificity of the CRMA signature to ipilimumab outcome ( Figure 3 E) (). We confirmed similar results in an analysis of transcriptome data from an independent nivolumab-treated cohort in a parallel arm of the CheckMate 064 trial ( Figure 3 F; Table S1 ; see STAR Methods for details), further supporting the notion that the CRMA signature is predictive for CTLA-4 blockade rather than prognostic of aggressive natural history. Collectively, these results are consistent with the notion that the CTLA-4 and PD-1 pathways occupy biologically and clinically distinct niches.

To investigate any bias resulting from inclusion of patients with stable disease, we removed patients with stable disease from the expression analysis and re-classified the cohort into patients with objective responses (complete [CR] or partial response [PR]) and to those with PD. A differential expression analysis of CRMA genes between these groups confirmed the association of CRMA expression with primary resistance (median 99-fold increase, range 37–196; maximum p value = 0.073; Figure S3 F), leading us to ask whether there is any prognostic value to the signature. We then demonstrated that CRMA expression did not discriminate overall survival in the untreated TCGA melanoma cohort ( Figure 3 D). These findings support the predictive, rather than prognostic, nature of the CRMA signature for CTLA-4 blockade. Taken together, these data suggest CRMA expression as a transcriptomic determinant of clinical outcome to CTLA-4 blockade.

Within the full cohort from, a Kaplan-Meier analysis of overall survival on ipilimumab therapy demonstrated that samples with high CRMA expression had poorer overall and progression-free survival than those with low CRMA expression (log-rank p = 0.007 and p = 0.006, respectively, n = 40) ( Figures 3 A and S3 D). Similarly, detectable MAGE-A protein expression associated with inferior overall and progression-free survival on ipilimumab therapy (log-rank p = 0.011 and p = 0.032, respectively, n = 55) ( Figures 3 B and S3 E). In a multivariable analysis of these 40 patients that included evaluation of neoantigen load, CRMA expression emerged as the sole independent risk factor for poor outcome after ipilimumab therapy (Cox proportional-hazards model, p = 0.018; Figure 3 C).

(F) Boxplots of RNA-seq expression values for each MAGEA gene in the CRMA locus within no PD (green; n = 23) and PD (yellow; n = 14) tumors from anti-PD-1 cohort 2 ().

(E) Boxplots of RNA-seq expression values for each MAGEA gene in the CRMA locus within no PD (light green; n = 15) and PD (dark green; n=13) tumors from anti-PD-1 cohort 1().

(A and B) Kaplan-Meier overall survival analysis comparing patients from discovery cohort classified by (A) expression of genes within the CRMA locus (median split) or (B) expression of MAGE-A protein.

In addition to the CRMA cluster, we also found increased expression of additional CGAs in NB samples, although none were as highly expressed as those at the CRMA locus ( Table S2 ). Moreover, CGAs previously described to elicit humoral and cellular responses linked to clinical outcome, such as NY-ESO-1 (), were not differentially expressed, nor were melanoma differentiation antigens (e.g., TYR, TYRP1, PMEL, and MLANA) ( Figure S3 A). Additional gene families upregulated in NB samples included those related to epithelial-to-mesenchymal transition () (i.e., CLDN1, CLDN2, EGF, EYA1, FGF2, SNAI1, WNT3) and embryonic development (HOXA2, HOXA3, HOXA5, HOXD10, HOXD11, HOXD13) ( Table S2 ). Moreover, multiple subunits of the GABA-A receptor, which has been implicated in mediating suppression of inflammatory macrophages and anti-tumor T cells, were also enriched in NB samples (fold change: 2.7–110; 6 of 19 family members, hypergeometric test, p < 5.7 × 10) (). Recent work has also implicated GABRA3, a GABA-A receptor subunit, in mediating cancer invasion and metastasis, potentially through increasing stem cell populations (). Consistent with previous reports, immune subsets were found to be significantly upregulated only in CB transcriptomes ( Figures S3 B and S3C). Altogether, the primary resistance phenotype to CTLA-4 blockade appears to be marked by CRMA overexpression and may comprise epigenomic dysregulation coupled with activation of additional programs including EMT, embryonic development, and invasion.

(F) Boxplots depicting the individual RNA-seq expression value for each MAGEA and CSAG gene within this locus in the discovery cohort stratified by CR/PR and PD status ().

(D and E) CRMA gene and MAGE-A protein expression correlate with progression-free survival after CTLA-4 blockade. Progression-free survival analyses comparing patients from the discovery cohort classified by (D) CRMA gene expression or (E) MAGE-A protein expression.

(C) Immune gene sets enriched in CB and NB tumors showing p value of enrichment (signed according to whether the gene set was enriched in NB (+) or CB (-) tumors). Dashed line represents p = 0.05.

(A) Heatmap showing relative gene expression of NB-enriched biological categories (see Table S2 ) along with lack of enrichment of NY-ESO-1 and melanoma differentiation antigens. Annotations of gender, purity and RECIST response included.

We further investigated DNA methylation patterns associated with CRMA expression by querying methylation data from TCGA melanoma samples. Differential methylation analysis of 485,577 probes between samples with high (n = 116) and low expression (n = 117) of the CRMA locus (see STAR Methods for details) revealed 47 probes relatively hypermethylated in the “CRMA-high” group compared to 65,467 in the “CRMA-low” group ( Figure 2 C, top). These 65,467 probes mapped across the genome, suggesting global hypomethylation in melanoma samples with high CRMA expression ( Figure S2 C). Gene set enrichment analysis for genes corresponding to these 65,467 probes using PANTHER () revealed four pathways as significantly demethylated in the CRMA-high melanoma TCGA group ( Figure 2 C, bottom). Of these, cadherin signaling and Wnt pathway signaling were also two of only three PANTHER pathways enriched in genes upregulated in NB samples (Bonferroni adjusted p < 0.01 and p < 0.05, respectively), further implicating epigenomic dysregulation in primary resistance to anti-CTLA-4 therapy.

To investigate potential mechanisms underlying the transcriptional enrichment of CRMA genes in resistant tumors, we analyzed copy-number variation and DNA methylation at this locus in the clinical trial samples. We observed no copy-number alterations of this region based on analysis of matched whole-exome sequencing (WES) data ( Figure S2 A; see STAR Methods for details). On the other hand, locus-specific methylation analysis of the MAGEA3 and MAGEA6 promoters revealed decreased DNA methylation throughout these promoters in NB samples ( Figure 2 B; p = 3 × 10) and a slight to moderate decrease in unique methylation sites within the gene bodies of MAGEA6, MAGEA3, and MAGEA12 ( Figure S2 B), consistent with known epigenetic regulation of CRMA genes ().

(B) Bisulfite PCR of unique methylation sites within the gene bodies of MAGEA3/A6/A12 genes highlights a slight to moderate decrease in methylation in NB patients (n = 4, orange) versus CB patients (n = 4, blue). The position of 3 PCR amplicons are highlighted, and the plots highlight the mean methylation for each CpG within the amplicon region.

(A) Copy number analysis of CRMA region in CB/NB patients. Neither the locus average of copy ratios, nor copy ratios on individual targets showed a statistically significant germline or somatic variation between the two groups at 5% level.

To define the transcriptome-wide effects of CRMA expression, we analyzed RNA-seq data from 465 melanomas from TCGA (). Genes overexpressed in NB samples overlapped with genes positively associated with CRMA expression in TCGA melanomas (p < 2.2 × 10) but not with genes negatively associated with CRMA expression ( Figure 2 A; Tables S3 and S4 ; see STAR Methods ). These results suggest that primary resistance to ipilumumab is associated with transcriptional programs inherent to high CRMA-expressing tumors.

(C) Volcano plot of differentially methylated probes (FDR = 0.05) across the genome between CRMA-low and CRMA-high expression groups in the TCGA melanoma cohort. Table shows PANTHER pathways () enriched in genes corresponding to 65,467 probes relatively hypomethylated in the CRMA-high group. Highlighted in red are two of only three PANTHER pathways enriched in NB samples.

(B) Methylation of MAGEA3 and MAGEA6 promoters in NB patients (orange; n = 3) compared to CB patients (blue; n = 3) as validated by bisulfite PCR. The plot highlights the local regression (solid line) of the mean methylation for every CpG (dots) along the MAGEA3 and MAGEA6 promoters in CB versus NB patients. The SD is indicated by the shaded area. Both promoter sequences are identical within the analyzed amplicon span.

To assess protein-level expression of the CRMA genes in relationship to clinical response, we performed immunohistochemistry (IHC) using a MAGE-A antibody (clone 6C1) broadly reactive for gene products from the MAGE-A family (i.e., recognizing MAGEA1, MAGEA2, MAGEA3, MAGEA4, MAGEA6, MAGEA10, and MAGEA12) on 55 melanoma samples from the original discovery cohort (). Forty-eight of these 55 patients could be unambiguously classified into CB and NB cohorts (see STAR Methods ). Consistent with the RNA-seq analysis, the NB cohort (n = 33) comprised a higher proportion of MAGE-Atumors compared to the CB cohort (n = 15) ( Figures 1 E and 1F, 76% versus 40%, p = 0.024), further confirming the strong association of baseline transcript and protein expression of a specific cluster of MAGE-A genes with primary resistance to ipilimumab.

While our discovery cohort was generated from formalin-fixed samples from an observational, retrospective study, we could validate our findings in an independent RNA-seq dataset generated from cryopreserved tumors from a prospective, randomized trial using pre-treatment patient samples derived from the CheckMate 064 trial (). This cohort comprised 41 patients, divided into “progressive disease” (PD; n = 12) or “no progressive disease” (no PD; n = 29) groups (see STAR Methods for details). Again, the CRMA genes were among the most significantly upregulated genes ( Figure 1 C). Because overall survival data attributable to ipilimumab monotherapy was not available given the subsequent administration of nivolumab, we re-classified our discovery cohort based on response assessments used for the CheckMate 064 trial with PD and no PD groups. RNA-seq expression values from the validation cohort were available for 5 of 8 genes in the CRMA locus (MAGEA3, MAGEA2, MAGEA2B, MAGEA12, and MAGEA6), and we observed consistent increases in all of these genes in patients with PD in both discovery (median 57-fold increase, range 24–159; maximum p value = 0.075) and validation cohorts (median 108-fold increase, range 5–236; maximum p value = 0.044; Figures 1 C, 1D, S1 E, and S1F).

We performed several confirmatory assessments to evaluate the validity of the CRMA signature. First, we ruled out potential sequencing-related artifacts by confirming expression of the CRMA genes in the original tumor RNA from the discovery set by gene-specific real-time qPCR ( Figure S1 B). Second, we found similar tumor purity estimates in both patient groups (see STAR Methods ), suggesting that relative enrichment of cancer cells in the NB group was unlikely to explain our finding ( Figure 1 A, inset). Finally, given the signature’s genomic localization to the X chromosome and potential modification by DNA damaging agents, we ensured that neither gender nor prior exposure to cytotoxic therapy (i.e., dacarbazine/temozolomide) was associated with clinical outcome ( Figures S1 C and S1D).

From a previously reported cohort of 110 melanoma patients treated with ipilimumab, we analyzed the 40 with associated tumor-derived RNA-seq data from pre-therapy samples (). Thirty-five of these 40 patients could be unambiguously classified into the clinical benefit (CB) and no benefit (NB) designations maintained from the original report (see STAR Methods ). A differential gene expression analysis comparing NB (n = 22) and CB (n = 13) groups identified 457 genes upregulated in NB samples ( Figure 1 A; Tables S1 and S2 ). Strikingly, 7 of the top 12 genes overexpressed in NB samples were clustered within a 75 kb region of chromosome Xq28 (median 67-fold increase, range 34–188; Figure 1 B, top). An additional gene, MAGEA3, was also located within this narrow genomic region and was similarly upregulated in NB samples (24-fold increase). All 8 genes (MAGEA3, CSAG3, CSAG2, MAGEA2, MAGEA2B, CSAG1, MAGEA12, MAGEA6) encoded cancer-germline antigens (CGAs), a large family of genes notable for their restricted expression in testis and placenta during normal development but re-expression across many tumor types. These 8 genes constitute one of four subclusters within the MAGE-A family and are coordinately regulated, independent of the other three MAGE-A subclusters (). 16 of 22 NB samples showed upregulation of at least one of these 8 CGAs, which we refer to as “anti-CTLA-4 resistance associated MAGE-A (CRMA)” genes, compared to only 2 of 13 CB samples (Fisher’s exact test, p = 0.002; Figure S1 A).

(F) Boxplots depicting the individual fold changes for each MAGEA gene within the CRMA locus are shown for patients with no PD or PD in the discovery cohort; p values using the Wilcoxon test.

(D) DTIC/temozolamide treatment history does not affect outcome after ipilimumab. Patients were included into “DTIC” group if DTIC or temozolamide were used as treatment at any time point prior to ipilimumab.

(B) RT-qPCR validation of CRMA genes using three different housekeeping genes: HPRT1 (top), GAPDH (middle) and PGK1 (bottom). P values using the Wilcoxon test and median fold changes are indicated.

(A) Heatmap showing relative expression of CRMA genes for CB and NB patients in the discovery cohort with annotations for gender, purity and RECIST response.

(C) Volcano plot depicting genes enriched in “no progressive disease” (no PD) and “progressive disease” (PD) groups at week 13 in the ipilimumab-nivolumab arm of the CheckMate 064 trial () (validation cohort).

(B) Top: 75 kb region within the CRMA locus containing the 8 CGAs is shown; CSAG3 and MAGEA2 are duplicated genes. Bottom: Boxplots depicting the individual RNA-seq expression value for each MAGEA and CSAG gene within this locus in the discovery cohort stratified by CB and NB status ().

(A) Volcano plot depicting genes enriched in CB and NB tumors (n = 457 and 326, respectively; fold change >2, one-sided Wilcoxon test p value < 0.05). Relative positions of CRMA and immune-related genes (pink) are shown. Inset: computational purity estimates by the ABSOLUTE algorithm are comparable between the CB and NB groups ().

Discussion

One possible explanation for our findings is that reduced CRMA expression in responding tumors is a manifestation of effective anti-MAGE-A immune activity. Responding melanoma samples are characterized by immune infiltrates that may have already selected against tumor cells expressing high levels of CRMA genes. However, we observed that other CGAs previously demonstrated to elicit cellular and humoral responses, such as NY-ESO-1, and various differentiation antigens, showed no evidence of selection in our analysis ( Figure S3 A). To our knowledge, this particular MAGE-A subfamily has not been shown to provoke stronger immune responses than other cancer-germline or melanoma-associated antigens; further investigation of in situ immune responses should be pursued to rule out this possibility.

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et al. Sequential administration of nivolumab and ipilimumab with a planned switch in patients with advanced melanoma (CheckMate 064): an open-label, randomised, phase 2 trial. The possibility that the CRMA genes mediate resistance uniquely to CTLA-4, and not PD-1, blockade through impairment of immune priming may be initially puzzling because immune effector function is usually thought to be contingent on previous T cell priming. However, other factors could explain why CRMA expression is a marker of resistance for anti-CTLA-4 but not anti-PD-1 therapy. Given the importance of autophagy for T cell priming, which is restrained by the CTLA-4 pathway, autophagy suppression by the MAGE-TRIM28 complex could directly explain the relevance of the MAGE-A signature to anti-CTLA-4 therapy. However, unlike the restricted expression of CTLA-4 to the T cell compartment, the promiscuous expression of PD-1 in various cell types contributes to diverse and heterogeneous mechanisms underlying responses to PD-1 pathway blockade—that operate through both cell-autonomous (i.e., melanoma cells expressing the PD-1 receptor and driven by intrinsic PD-1 pathway signaling) () and non-autonomous (e.g., reversal of T cell exhaustion) () processes. Furthermore, tumor biopsies (such as used in this study) provide only a snapshot in time; if MAGE-A gene expression has occurred later in tumor development after an anti-cancer effector immune response has already developed, then a PD-1 inhibitor may be able to exploit a pre-existing reservoir of intratumoral lymphocytes whereas a CTLA-4 inhibitor is still restrained by an upstream defect in priming. The classical assumption that effector immunity generally follows intact priming has been challenged by the results of the CheckMate 064 trial that found that patients treated with CTLA-4 blockade (priming manipulation) after PD-1 blockade (effector manipulation) had a significantly improved overall survival compared to the reverse sequence ().