Molecular correlates of response to nivolumab at baseline and on treatment in patients with RCC

Abstract

Background: Nivolumab is an immune checkpoint inhibitor targeting the programmed death-1 receptor that improves survival in a subset of patients with clear cell renal cell carcinoma (ccRCC). In contrast to other tumor types that respond to immunotherapy, factors such as programmed death ligand-1 (PD-L1) status and tumor mutational burden show limited predictive utility in ccRCC. To address this gap, we report here the first molecular characterization of nivolumab response using paired index lesions, before and during treatment of metastatic ccRCC.

Methods: We analyzed gene expression and T-cell receptor (TCR) clonality using lesion-paired biopsies provided in the CheckMate 009 trial and integrated the results with their PD-L1/CD4/CD8 status, genomic mutation status and serum cytokine assays. Statistical tests included linear mixed models, logistic regression models, Fisher's exact test, and Kruskal-Wallis rank-sum test.

Results: We identified transcripts related to response, both at baseline and on therapy, including several that are amenable to peripheral bioassays or to therapeutic intervention. At both timepoints, response was positively associated with T-cell infiltration but not associated with TCR clonality, and some non-Responders were highly infiltrated. Lower baseline T-cell infiltration correlated with elevated transcription of Wnt/β-catenin signaling components and hypoxia-regulated genes, including the Treg chemoattractant CCL28. On treatment, analysis of the non-responding patients whose tumors were highly T-cell infiltrated suggests association of the RIG-I-MDA5 pathway in their nivolumab resistance. We also analyzed our data using previous transcriptional classifications of ccRCC and found they concordantly identified a molecular subtype that has enhanced nivolumab response but is sunitinib-resistant.

Conclusion: Our study describes molecular characteristics of response and resistance to nivolumab in patients with metastatic ccRCC, potentially impacting patient selection and first-line treatment decisions.

Trial registration number: NCT01358721.

Keywords: gene expression profiling; immunotherapy; kidney neoplasms; t-lymphocytes; tumor biomarkers.

Conflict of interest statement

Competing interests: PR-M, SDC, SP-C, PMS, RA, AMW, and MW-R were employees of Bristol Myers Squibb at the time of their contribution. TKC has served as a consultant/advisor for Pfizer, GlaxoSmithKline, Novartis, Merck, Bristol Myers Squibb, Bayer, Eisai, Roche, and Prometheus Labs, Inc, and has received institutional research funding from Pfizer, Novartis, GlaxoSmithKline, Bristol Myers Squibb, Merck, Exelixis, Roche, AstraZeneca, Peloton, and Tracon. MS has served as a consultant/advisor for Genentech-Roche, Bristol Myers Squibb, AstraZeneca/MedImmune, Pfizer, Novartis, Kyowa-Kirin, Amgen, Merus, Seattle Genetics, Immune Design, Prometheus, Anaeropharma, Astellas-Agensys, Immunova, Nektar, Neostem, Pierre-Fabre, Eli Lilly, Symphogen, Lion Biotechnologies, Amphivena, and Adaptive Biotechnologies.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1

Patient annotation and Response criterion. (A) Upper waterfall plot shows maximal percentage tumor burden reduction, available for 83 of the 91 treated patients. Reduction of ≥20% is indicated in gold. Lower waterfall plot shows maximal percentage reduction of the lesion that provided the baseline biopsy (index lesions, n=63). Reduction of ≥20% is indicated in gold. Sample annotation track shows ‘Response’ (Responders in gold), ‘RECIST BOR’ (CR and PR in dark gold/gold, SD in gray, PD in black), ‘Lesion Pair’, (baseline and day 28 biopsies from the same lesion in gold, n=59) and ‘Biopsy Site’ (lymph node metastatic site in gold). White indicates ‘no information’. *Patient 98. (B) Probability of progression-free survival stratified by Response status, estimated by the Kaplan-Meier method, for the 85 patients included in these analyses. BOR, best overall response; CR, complete response; PD, progressive disease; PR, partial response; RECIST, Response Evaluation Criteria in Solid Tumors; SD, stable disease.

Figure 2

Differential gene expression between Response groups at baseline. (A) Heat map panel shows z-score expression data for 93 genes meeting pabsent in melanoma 2; CPM, counts per million; CR, complete response; FFPE, formalin-fixed paraffin-embedded; GSEA, gene set enrichment analysis; IL, interleukin; IRIS, immune response in silico; PR, partial response; RECIST, Response Evaluation Criteria in Solid Tumors; RMA, robust multiarray average; TMM, trimmed mean of M-values; TKI, tyrosine kinase inhibitor.

Figure 3

Differential gene expression between Response groups at day 28. (A) Heat map panel shows z-score expression data for 779 genes meeting pT cell immunoreceptor with Ig and ITIM domains; TKI, tyrosine kinase inhibitor.

Figure 4

Differential change from baseline expression associated with Response. (A) Heat map panel shows the fold change for 189 genes with an expression change from baseline that differed between Response groups and was >1.25-fold in the Responder group (n=42 patients). Scale is −2-fold to +2-fold (blue to red). Waterfall plot shows maximal percentage reduction of the lesion that provided the expression data (n=29 matched index lesions). Lesions with reduction of ≥20% are indicated in gold. Sample annotation tracks show ‘Response’ (Responders in gold) and ‘Matched Lesion’ (baseline and day 28 biopsies from the same lesion in gold, n=33). Gene annotation track to the right of the heat map shows ‘IRIS’ immune-cell transcripts (lymphoid lineage in green, myeloid lineage in blue, expression in both lineages in gold). (B) Normalized enrichment score for GSEA evaluating Hallmark gene sets in the results for differential gene expression analyses of change on treatment in Responders. (C) RMA-normalized expression values for the IL-18 transcript in biopsies provided at baseline (n=56) and day 28 of nivolumab therapy (n=55). Data are grouped by Response status. Prior TKI therapy is indicated by circles, Naïve by diamonds. P values from Student’s t-test. (D) Serum levels (pg/mL) for the IL-18 protein in 84 patients who provided samples at baseline and day 21 of nivolumab treatment. Data are grouped by Response status. Prior TKI therapy is indicated by circles, Naïve by diamonds. P values from Student’s t-test. GSEA, gene set enrichment analysis; IL, interleukin; IRIS, immune response in silico; RMA, robust multiarray average; TKI, tyrosine kinase inhibitor.

Figure 5

Association with T-cell metrics at baseline. ‘CD3TCR Score’ indicates the composite score for T-cell receptor transcripts, calculated in 56 biopsies obtained from patients at baseline. The Responder group is indicated by gold plotting symbols, and the non-Responder group by black plotting symbols. Prior TKI therapy is indicated by circles, Naïve by diamonds. (A) Left panel: clonality of the T-cell repertoire in tumor biopsies at baseline (n=54, p value from unpaired t-test). Right panel: change in clonality at day 28 relative to baseline (n=51, p values from paired t-test). Data are grouped by Response status. (B) Expression values for the CCL28 transcript (left panel) and CA9 transcript (right panel), compared with CD3TCR score, in 56 patients at baseline. Adjusted p values are from limma (online supplemental table S7). (C) Normalized enrichment score for GSEA evaluating Hallmark gene sets in the results for differential gene expression analysis against CD3TCR score at baseline. (D) Heat map panel shows z-score expression data for the 11 transcripts from the gene set ‘ELVIDGE_HIF1A_TARGETS_DN’ that were associated with CD3TCR score. Scale is −1 to 1 (blue to red). Data are from 56 patients at baseline, sorted from low to high CD3TCR score (left to right). Sample annotation tracks show CD3TCR Score (blue to red indicates lowest to highest score in the 56 baseline biopsies), Response (Responders in gold), Prior Therapy (Naïve in gold), Biopsy site (Lymph node metastatic site in gold), VHL1 status (Mutant in gold, unknown in gray), and tumor PD-L1 category (Negative in white, Positive at any level in red, Unknown in gray). (E) Expression values for the CSNK1E, FZD3, LRP4, LRP5, LRP6 and PAK4 transcripts, versus CD3TCR score, in 56 patients at baseline. Adjusted p values are from limma (online supplemental table S7). GSEA, gene set enrichment analysis; PD-L1, programmed death ligand-1; RMA, robust multiarray average; VHL, von Hippel-Lindau.

Figure 6

Association between gene expression and Response in patients with high T-cell abundance at day 28. All data shown are from the 27 patients with above-median CD3TCR score at day 28. (A) Expression values for the CXCR4 (left panel) or CD40 (right panel) transcripts, in biopsies provided at day 28 of nivolumab treatment. Data are grouped by response status. Prior TKI therapy is indicated by circles, Naïve by diamonds. (B) Normalized enrichment score for GSEA evaluating Hallmark gene sets in the result for differential gene expression analyses at day 28 comparing response status. (C) Heat map panel shows z-score expression data at day 28 for the 20 transcripts from the Hallmark gene set ‘Interferon Gamma Response’ that were negatively associated with Response status (p

Figure 7

Association of gene expression classifiers with Response. (A) Heat map panel shows scores for the gene sets indicated, clustered by their similarity. Samples are ordered by maximal percentage tumor burden reduction for the 56 patients with baseline gene expression data, shown in the upper waterfall plot. Reduction of ≥20% is indicated in gold. Lower waterfall plot shows maximal percentage reduction of the lesion that provided the expression data (index lesions, n=42). Reduction of ≥20% is indicated in gold. Sample annotation tracks show Response (Responders in gold), PBRM1 status (truncating mutation in gold, wild type in black, unknown are blank), and predicted ccrcc-like subtype (ccrcc1-like as black, ccrcc2-like as red, ccrcc3-like as gray, and ccrcc4-like as gold). (B) Response rate in patient groups for each of the four ccrcc-like molecular subtypes. Error bars indicate 95% CI for the rate. P value is from Fisher’s exact test of ccrcc4-like versus ccrcc1/2/3-like. (C) Receiver operating characteristic curves summarizing predictive accuracy for gene set scores, ranging from TIS (AUC=72%) to IMmotion150 angiogenesis (AUC=33%). (D) ORs for Response given PBRM1 status, ccrcc4-like subtype, or gene set score. For the gene set scores, the OR compares the odds of response for the 25th versus the 75th percentile. For ccrcc4-like subtype and PBRM1 mutant status, the OR compares the odds of Response for ccrcc4-like versus ccrcc1/2/3-like and for mutant versus wild type, respectively. Panel displays log2 OR, centered on 0. OR and 95% CIs indicated to the left. (E) Data for 51 samples of ccRCC from public dataset E-MTAB-3267. Heat map panel shows z-score expression data for 93 genes for which baseline expression was associated with Response (p<0.01 and >1.5-fold difference) in CheckMate 009 (see figure 2A). Gene annotation track to the right of the heat map indicates the direction of differential expression in CheckMate 009, with red indicating transcripts that were higher at baseline in patients who then responded to nivolumab. Sample annotation tracks show the individual’s best response to subsequent therapy with sunitinib (PD indicated in black, SD in green, Clinical Benefit and PR in gold) and the ccrc subtype with ccrcc1, 2, and 3 in progressively darker shades of green and ccrcc4 in gold. Samples and transcripts are hierarchically clustered. AUC, area under the curve; ccrcc, clear cell renal cell carcinoma; OR, odds ratio; PD, progressive disease; PR, partial response; SD, stable disease; TIS, tumor inflammation signature.