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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., Biomarkers of immune checkpoint inhibition sensitivity are needed. This article reports on genomic biomarkers that may predict response to anti‐PD1 therapy in prostate cancer.

Background Early phase clinical trials evaluate the safety and efficacy of new treatments. The exclusion/inclusion criteria in these trials are usually rigorous and may exclude many patients seen in clinical practice. Our objective was to study the comorbidities limiting the participation of patients with breast, colorectal, or lung cancer in clinical trials. Materials and Methods We queried ClinicalTrials.gov on December 31, 2016. We reviewed the eligibility criteria of 1,103 trials. Logistic regression analyses were completed, and exclusion was studied as a binary variable. Results Out of 1,103 trials, 70 trials (6%) excluded patients >75 years of age, and 45% made no reference to age. Eighty-six percent of trials placed restrictions on patients with history of prior malignancies. Regarding central nervous system (CNS) metastasis, 416 trials (38%) excluded all patients with CNS metastasis, and 373 (34%) only allowed asymptomatic CNS metastasis. Regarding chronic viral infections, 347 trials (31%) excluded all patients with human immunodeficiency virus, and 228 trials (21%) excluded all patients with hepatitis B or C infection. On univariate analysis, chemotherapy trials were more likely to exclude patients with CNS metastasis and history of other malignancies than targeted therapy trials. Multivariate analysis demonstrated that industry-sponsored trials had higher odds of excluding patients with compromised liver function. Conclusion Many clinical trials excluded large segments of the population of patients with cancer. Frequent exclusion criteria included patients with CNS metastasis, history of prior malignancies, and chronic viral infections. The criteria for participation in some clinical trials may be overly restrictive and limit enrollment. Implications for Practice The results of this study revealed that most early phase clinic trials contain strict exclusion criteria, potentially excluding the patients who may be more likely to represent the population treated in clinical settings, leaving patients susceptible to unintended harm from inappropriate generalization of trial results. Careful liberalization of the inclusion/exclusion criteria in clinical trials will allow investigators to understand the benefits and drawbacks of the experimental drug for a broader population, and possibly improve recruitment of patients with cancer into clinical trials.