Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma

Willy Hugo, Jesse M Zaretsky, Lu Sun, Chunying Song, Blanca Homet Moreno, Siwen Hu-Lieskovan, Beata Berent-Maoz, Jia Pang, Bartosz Chmielowski, Grace Cherry, Elizabeth Seja, Shirley Lomeli, Xiangju Kong, Mark C Kelley, Jeffrey A Sosman, Douglas B Johnson, Antoni Ribas, Roger S Lo, Willy Hugo, Jesse M Zaretsky, Lu Sun, Chunying Song, Blanca Homet Moreno, Siwen Hu-Lieskovan, Beata Berent-Maoz, Jia Pang, Bartosz Chmielowski, Grace Cherry, Elizabeth Seja, Shirley Lomeli, Xiangju Kong, Mark C Kelley, Jeffrey A Sosman, Douglas B Johnson, Antoni Ribas, Roger S Lo

Abstract

PD-1 immune checkpoint blockade provides significant clinical benefits for melanoma patients. We analyzed the somatic mutanomes and transcriptomes of pretreatment melanoma biopsies to identify factors that may influence innate sensitivity or resistance to anti-PD-1 therapy. We find that overall high mutational loads associate with improved survival, and tumors from responding patients are enriched for mutations in the DNA repair gene BRCA2. Innately resistant tumors display a transcriptional signature (referred to as the IPRES, or innate anti-PD-1 resistance), indicating concurrent up-expression of genes involved in the regulation of mesenchymal transition, cell adhesion, extracellular matrix remodeling, angiogenesis, and wound healing. Notably, mitogen-activated protein kinase (MAPK)-targeted therapy (MAPK inhibitor) induces similar signatures in melanoma, suggesting that a non-genomic form of MAPK inhibitor resistance mediates cross-resistance to anti-PD-1 therapy. Validation of the IPRES in other independent tumor cohorts defines a transcriptomic subset across distinct types of advanced cancer. These findings suggest that attenuating the biological processes that underlie IPRES may improve anti-PD-1 response in melanoma and other cancer types.

Copyright © 2016 Elsevier Inc. All rights reserved.

Figures

Figure 1. Mutational Correlates of Innate Sensitivity…
Figure 1. Mutational Correlates of Innate Sensitivity to Anti-PD-1 Therapy
(A) Overall survival of anti-PD-1-treated patients whose melanoma tumors harbored high (top third) versus low (bottom third) mutational (somatic nsSNVs) loads. P values, log-rank test. (B) Overall survival of anti-PD-1-treated melanoma patients whose pretreatment tumors responded (n=20) or did not respond (n=17). P value, log-rank test. (C) Total number of nsSNVs detected in anti-PD-1 responding and non-responding melanoma tumors harboring high (above the respective group's median) or low (below the group median) mutational loads. P value, log-rank test. (D) Overall survival of anti-PD-1-treated melanoma patients whose pretreatment tumors responded or did not respond and harboring high (above the group median) or low (below the group median) mutational loads. P value, log-rank test. (E) Recurrent exomic alterations (nsSNVs and small insertion/deletions or INDELs) in pretreatment tumors of responding versus non-responding patients on anti-PD-1 therapy. Copy number alterations were annotated for the same gene as a reference. Top, mutations of melanoma signature genes. Middle, mutations recurrent in responding versus non-responding tumors (recurrence in 25% in one group and at most one occurrence in the opposite group, Fisher exact test, FDR-corrected P≤0.05 on enrichment against the background mutation frequency). Bottom, the total nsSNV load of each melanoma tumor. (F) Schematics of impact of non-synonymous missense and nonsense mutations in the BRCA2 protein and its domains. (G) Total number of nsSNVs detected in melanomas with or without BRCA2 non-synonymous mutations. P value, Mann Whitney test. See also Table S1 and Figure S1.
Figure 2. Transcriptomic Signatures of Innate Resistance…
Figure 2. Transcriptomic Signatures of Innate Resistance to Anti-PD-1 Therapy
(A) (Top) Heatmap showing differentially expressed genes in the pretreatment tumors derived from patients who responded versus who did not respond to anti-PD-1 treatment (gene expression with inter-quartile range (IQR) ≥ 2; median fold-change (FC) difference ≥ 2; Mann-Whitney P ≤ 0.05). (Middle) mRNA expression levels of genes with hypothetical roles in modulating response patterns to anti-PD-1 therapy. (Bottom) Overall number of nsSNVs, HLA class 1 and 2 neoepitopes (predicted). (B) mRNA levels of genes (which control tumor cell mesenchymal transition, tumor angiogenesis and macrophage and monocyte chemotaxis) that were differentially expressed between the responding versus non-responding pretreatment tumors. P values, Mann Whitney test. (C) GO enrichment of genes that were expressed higher in the responding tumors. (D) Heatmap showing the Gene Set Variance Analysis (GSVA) scores of gene signatures differentially enriched in the responding versus non-responding pre-anti-PD-1 tumors (absolute median GSVA score difference ≥ 10%, FDR-corrected Welch t-test p≤0.25 or nominal Welch t-test p≤0.1). For comparison, enrichment scores of interferon signatures are also displayed. (E) Overall survival of anti-PD-1-treated melanoma patients with presence (n=10) or absence (n=16) of co-enriched Innate Anti-PD-1 RESistance (IPRES) signatures. P value, log-rank test. See also Table S2 and Figure S2.
Figure 3. Co-enrichment of Innate Anti-PD-1 Resistance-associated…
Figure 3. Co-enrichment of Innate Anti-PD-1 Resistance-associated Signatures Defines a Transcriptomic Subset in Melanoma and Multiple Cancers
(A) Heatmap showing GSVA scores of IPRES signatures across four independent RNASeq data sets derived from metastatic melanoma. Cohort 1, pretreatment (anti-PD-1) tumors; cohort 2, pretreatment (anti-CTLA-4) tumors; cohort 3, pretreatment (MAPKi) tumors; cohort 4, TCGA cutaneous melanoma (metastatic only). (B) Heatmap showing GSVA scores of IPRIM signatures across TCGA RNASeq data sets (metastatic melanoma or SKCM, lung adenocarcinoma or LUAD, colon adenocarcinoma or COAD, kidney clear cell carcinoma or KIRC, and pancreatic adenocarcinoma or PAAD). See also Figure S3.

Source: PubMed

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