Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma

Abstract

Immune checkpoint inhibitors targeting the programmed cell death 1 receptor (PD-1) improve survival in a subset of patients with clear cell renal cell carcinoma (ccRCC). To identify genomic alterations in ccRCC that correlate with response to anti-PD-1 monotherapy, we performed whole-exome sequencing of metastatic ccRCC from 35 patients. We found that clinical benefit was associated with loss-of-function mutations in the PBRM1 gene (P = 0.012), which encodes a subunit of the PBAF switch-sucrose nonfermentable (SWI/SNF) chromatin remodeling complex. We confirmed this finding in an independent validation cohort of 63 ccRCC patients treated with PD-1 or PD-L1 (PD-1 ligand) blockade therapy alone or in combination with anti-CTLA-4 (cytotoxic T lymphocyte-associated protein 4) therapies (P = 0.0071). Gene-expression analysis of PBAF-deficient ccRCC cell lines and PBRM1-deficient tumors revealed altered transcriptional output in JAK-STAT (Janus kinase-signal transducers and activators of transcription), hypoxia, and immune signaling pathways. PBRM1 loss in ccRCC may alter global tumor-cell expression profiles to influence responsiveness to immune checkpoint therapy.

Fig. 1. Cohort consolidation and clinical characteristics of the discovery cohort

(A) Sample inclusion/exclusion criteria and computational workflow. (B) Clinical stratification by degree of objective change in tumor burden (y-axis) and duration of progression-free survival (x-axis). One patient (RCC_99) not shown due to lack of tumor response data. *Patient RCC_50 was classified as clinical benefit despite PFS<6 months because there was continued tumor shrinkage after an initial period of minor tumor progression (see fig. S2). (C) Mutation burden in the discovery cohort by response group. (D) Ratio of subclonal to clonal mutations, as estimated by ABSOLUTE, by response group. ns = not significant. Abbreviations: CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease.

Fig. 2. Analysis of tumor genome features in discovery cohort reveals a correlation between PBRM1 LOF mutations and clinical benefit from anti-PD-1 therapy

(A) Mutations in the discovery cohort. Patients are ordered by response category, with tumor mutation burden in decreasing order within each response category. Shown are the genes that were recurrently mutated at a significant frequency, as assessed by MutSig2CV analysis (table S1E). CNA = copy number alteration. (B) Enrichment of truncating mutations in tumors from patients in the CB vs. NCB groups. Red dashed line denotes q<0.1 (Fisher’s exact test). Mutations in genes above the black dotted line are enriched in tumors of patients with CB from anti-PD-1 therapy and mutations in genes below the line are enriched in tumors of patients with NCB. (C) Kaplan-Meier curve comparing overall survival of patients treated with anti-PD-1 therapy whose tumors did or did not harbor LOF mutations in PBRM1. See also fig. S5 for Kaplan-Meier curve comparing progression-free survival of these patients. (D) Spider plot showing objective decrease in tumor burden in PBRM1-LOF (blue) vs. PBRM1-intact (yellow) tumors. Three patients with early progression on anti-PD-1 therapy and truncating mutations in PBRM1 (dark blue) had long and/or censored OS.

Fig. 3. PBRM1 LOF mutations correlate with clinical benefit in a validation cohort of ccRCC patients treated with immune checkpoint inhibitors

(A) Selection of the validation cohort. (B) Clinical outcomes in the validation cohort. Ten patients without post-treatment re-staging scans (eight with clinical PD, two with SD, and one with PR) as well as 14 patients with targeted panel sequencing are not shown. (C) Proportion of tumors harboring PBRM1 LOF mutations in patients in the CB vs. NCB groups. Error bars are S.E. *Fisher’s exact p<0.05. (D) Truncating alterations in PBRM1 and response to anti-PD-(L)1 therapies by sample. Colored boxes indicate samples with truncating mutations in PBRM1 while gray denotes samples without PBRM1 truncating mutations. Missense LOF denotes a missense mutation detected by targeted sequencing that was confirmed to be LOF by PBRM1 immunohistochemistry (see Supplemental Methods).

Fig. 4. PBRM1 mutational status in ccRCC influences immune gene expression

(A) GSEA was performed on PBAF-deficient (A704^{BAF180−/−} and A704^{BAF180wt, BRG1−/−}) vs. PBAF-proficient (A704^BAF180wt) kidney cancer cell lines using both Hallmark and corresponding Founder gene sets. GSEA enrichment plot shown for the KEGG cytokine-cytokine receptor interaction gene set in A704^{BAF180−/−} vs. A704^BAF180wt (PBRM1 null vs. wildtype). Enrichment plot is similar for A704^{BAF180wt, BRG1−/−} vs. A704^BAF180wt (BRG1 null vs. wildtype); see table S4. (B) GSEA was also performed on RNA-seq from pre-treatment tumors in the discovery and validation cohorts of this study (n = 18 PBRM1-LOF vs. n = 14 PBRM1-intact) using the Hallmark gene sets. Enrichment plots show increased expression of the hypoxia and IL6/JAK-STAT3 gene sets in the PBRM1-LOF tumors.