BACKGROUND: Inhibition of programmed death-ligand 1 (PD-L1) with atezolizumab can induce durable clinical benefit (DCB) in patients with metastatic urothelial cancers, including complete remissions in patients with chemotherapy refractory disease. Although mutation load and PD-L1 immune cell (IC) staining have been associated with response, they lack sufficient sensitivity and specificity for clinical use. Thus, there is a need to evaluate the peripheral blood immune environment and to conduct detailed analyses of mutation load, predicted neoantigens, and immune cellular infiltration in tumors to enhance our understanding of the biologic underpinnings of response and resistance. METHODS AND FINDINGS: The goals of this study were to (1) evaluate the association of mutation load and predicted neoantigen load with therapeutic benefit and (2) determine whether intratumoral and peripheral blood T cell receptor (TCR) clonality inform clinical outcomes in urothelial carcinoma treated with atezolizumab. We hypothesized that an elevated mutation load in combination with T cell clonal dominance among intratumoral lymphocytes prior to treatment or among peripheral T cells after treatment would be associated with effective tumor control upon treatment with anti-PD-L1 therapy. We performed whole exome sequencing (WES), RNA sequencing (RNA-seq), and T cell receptor sequencing (TCR-seq) of pretreatment tumor samples as well as TCR-seq of matched, serially collected peripheral blood, collected before and after treatment with atezolizumab. These parameters were assessed for correlation with DCB (defined as progression-free survival [PFS] >6 months), PFS, and overall survival (OS), both alone and in the context of clinical and intratumoral parameters known to be predictive of survival in this disease state. Patients with DCB displayed a higher proportion of tumor-infiltrating T lymphocytes (TIL) (n = 24, Mann-Whitney p = 0.047). Pretreatment peripheral blood TCR clonality below the median was associated with improved PFS (n = 29, log-rank p = 0.048) and OS (n = 29, log-rank p = 0.011). Patients with DCB also demonstrated more substantial expansion of tumor-associated TCR clones in the peripheral blood 3 weeks after starting treatment (n = 22, Mann-Whitney p = 0.022). The combination of high pretreatment peripheral blood TCR clonality with elevated PD-L1 IC staining in tumor tissue was strongly associated with poor clinical outcomes (n = 10, hazard ratio (HR) (mean) = 89.88, HR (median) = 23.41, 95% CI [2.43, 506.94], p(HR > 1) = 0.0014). Marked variations in mutation loads were seen with different somatic variant calling methodologies, which, in turn, impacted associations with clinical outcomes. Missense mutation load, predicted neoantigen load, and expressed neoantigen load did not demonstrate significant association with DCB (n = 25, Mann-Whitney p = 0.22, n = 25, Mann-Whitney p = 0.55, and n = 25, Mann-Whitney p = 0.29, respectively). Instead, we found evidence of time-varying effects of somatic mutation load on PFS in this cohort (n = 25, p = 0.044). A limitation of our study is its small sample size (n = 29), a subset of the patients treated on IMvigor 210 (NCT02108652). Given the number of exploratory analyses performed, we intend for these results to be hypothesis-generating. CONCLUSIONS: These results demonstrate the complex nature of immune response to checkpoint blockade and the compelling need for greater interrogation and data integration of both host and tumor factors. Incorporating these variables in prospective studies will facilitate identification and treatment of resistant patients.

Author Info: (1) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. Department of Medicine, Weill Cornell Medical College, New York, N

Author Info: (1) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America. (2) Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. (3) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America. (4) Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. (5) Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. (6) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America. (7) Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. (8) Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. (9) Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. (10) Adaptive Biotechnologies, Seattle, Washington, United States of America. (11) Adaptive Biotechnologies, Seattle, Washington, United States of America. (12) Adaptive Biotechnologies, Seattle, Washington, United States of America. (13) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. (14) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. (15) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America. (16) Adaptive Biotechnologies, Seattle, Washington, United States of America. Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America. (17) Department of Pediatrics, Institute for Genomic Medicine, The Research Institute at Nationwide Children's Hospital, The Ohio State University College of Medicine, Columbus, Ohio, United States of America. (18) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. (19) Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America. (20) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. (21) Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America. Department of Medicine, Weill Cornell Medical College, New York, New York, United States of America.