Tumor Frameshift Mutation Proportion Predicts Response to Immunotherapy in Mismatch Repair-Deficient Prostate Cancer

Abstract

Background: Genomic biomarkers that predict response to anti-PD1 therapy in prostate cancer are needed. Frameshift mutations are predicted to generate more neoantigens than missense mutations; therefore, we hypothesized that the number or proportion of tumor frameshift mutations would correlate with response to anti-PD1 therapy in prostate cancer.

Methods: To enrich for response to anti-PD1 therapy, we assembled a multicenter cohort of 65 men with mismatch repair-deficient (dMMR) prostate cancer. Patient characteristics and outcomes were determined by retrospective chart review. Clinical somatic DNA sequencing was used to determine tumor mutational burden (TMB), frameshift mutation burden, and frameshift mutation proportion (FSP), which were correlated to outcomes on anti-PD1 treatment. We subsequently used data from a clinical trial of pembrolizumab in patients with nonprostatic dMMR cancers of various histologies as a biomarker validation cohort.

Results: Nineteen of 65 patients with dMMR metastatic castration-resistant prostate cancer were treated with anti-PD1 therapy. The PSA₅₀ response rate was 65%, and the median progression-free survival (PFS) was 24 (95% confidence interval 16-54) weeks. Tumor FSP, more than overall TMB, correlated most strongly with prolonged PFS and overall survival (OS) on anti-PD1 treatment and with density of CD8+ tumor-infiltrating lymphocytes. High FSP similarly identified patients with longer PFS as well as OS on anti-PD1 therapy in a validation cohort.

Conclusion: Tumor FSP correlated with prolonged efficacy of anti-PD1 treatment among patients with dMMR cancers and may represent a new biomarker of immune checkpoint inhibitor sensitivity.

Implications for practice: Given the modest efficacy of immune checkpoint inhibition (ICI) in unselected patients with advanced prostate cancer, biomarkers of ICI sensitivity are needed. To facilitate biomarker discovery, a cohort of patients with DNA mismatch repair-deficient (dMMR) prostate cancer was assembled, as these patients are enriched for responses to ICI. A high response rate to anti-PD1 therapy in these patients was observed; however, these responses were not durable in most patients. Notably, tumor frameshift mutation proportion (FSP) was identified as a novel biomarker that was associated with prolonged response to anti-PD1 therapy in this cohort. This finding was validated in a separate cohort of patients with nonprostatic dMMR cancers of various primary histologies. This works suggests that FSP predicts response to anti-PD1 therapy in dMMR cancers, which should be validated prospectively in larger independent cohorts.

Keywords: Biomarkers; Immunotherapy; Mismatch repair deficiency; Prostate cancer.

Figure 1

Efficacy of anti‐PD1 therapy for patients with mismatch repair‐deficient prostate cancer. (A): Waterfall plot of best PSA response to anti‐PD1 therapy. PSA₅₀ is shown with a dotted line. Responses greater than 100% are truncated at 100%. (B): Clinical and/or radiographic PFS to anti‐PD1 therapy is shown as a Kaplan‐Meier curve (solid line) with 95% confidence intervals shown with dotted lines. Abbreviations: PSA, prostate‐specific antigen; PSA₅₀, 50% decline in PSA; PFS, progression‐free survival.

Figure 2

FSP positively correlated with PFS on anti‐PD1 therapy. Correlation of TMB (A), FSB (B), and FSP (C) with PFS on anti‐PD1 therapy among patients with mismatch repair‐deficient prostate cancer who had progressed or died on anti‐PD1. PFS (D) and OS (E) on anti‐PD1 therapy stratified by optimal FSP cutoff are shown as Kaplan‐Meier curves. (F): Waterfall plot of best PSA response to anti‐PD1 therapy color‐coded by FSP. Fifty percent decrease in PSA (PSA₅₀) is shown with a dotted line. Responses greater than 100% are truncated at 100%. Abbreviations: CI, confidence interval; FSB, frameshift mutation burden; FSP, frameshift mutation proportion; mut/Mb, mutations per megabase; OS, overall survival; PFS, progression‐free survival; PSA, prostate‐specific antigen; TMB, tumor mutational burden.

Figure 3

Correlation of genomic markers with CD8+ TIL density and PD‐L1 expression among a separate cohort of prostate cancers with MSH2 protein loss. Correlation of TMB (A), FSB (B), and FSP (C) to CD8+ TIL density. TMB (D), FSB (E), and FSP (F) among tumors with and without PD‐L1 expression determined by immunohistochemistry. Abbreviations: FSB, frameshift mutation burden; FSP, frameshift mutation proportion; mut/Mb, mutations per megabase; TIL, tumor‐infiltrating lymphocyte; TMB, tumor mutational burden.

Figure 4

FSP positively correlated with PFS and OS on anti‐PD1 therapy in a separate cohort of mismatch repair‐deficient tumors of varying primary origin. (A): PFS on anti‐PD1 stratified by median TMB, FSB, and FSP are shown as Kaplan‐Meier curves. (B): OS after initiation of anti‐PD1 stratified by median TMB, FSB, and FSP. Abbreviations: CI, confidence interval; FSB, frameshift mutation burden; FSP, frameshift mutation proportion; ND, not determined; OS, overall survival; PFS, progression‐free survival; TMB, tumor mutational burden.

Figure 5

Relationship of FSP with markers of genomic instability. (A): Correlation of FSP with TMB among patients with mismatch repair‐deficient (dMMR) prostate cancer. TMB (B), FSB (C), and FSP (D) stratified by microsatellite instability status among patients with dMMR prostate cancer. Abbreviations: FSB, frameshift mutation burden; FSP, frameshift mutation proportion; MSI‐I/H, microsatellite instability–intermediate/high; MSS, microsatellite stable; mut/Mb, mutations per megabase; TMB, tumor mutational burden.