| Literature DB >> 28251903 |
Whijae Roh1,2, Pei-Ling Chen1,3, Alexandre Reuben4, Christine N Spencer1, Peter A Prieto4, John P Miller5, Vancheswaran Gopalakrishnan4, Feng Wang1, Zachary A Cooper1,4, Sangeetha M Reddy6, Curtis Gumbs1, Latasha Little1, Qing Chang1, Wei-Shen Chen1,3, Khalida Wani7, Mariana Petaccia De Macedo7,8, Eveline Chen7, Jacob L Austin-Breneman4, Hong Jiang4, Jason Roszik1,9, Michael T Tetzlaff3, Michael A Davies9, Jeffrey E Gershenwald4, Hussein Tawbi9, Alexander J Lazar4,7, Patrick Hwu9, Wen-Jen Hwu9, Adi Diab9, Isabella C Glitza9, Sapna P Patel9, Scott E Woodman9, Rodabe N Amaria9, Victor G Prieto3, Jianhua Hu10, Padmanee Sharma11,12, James P Allison11, Lynda Chin13, Jianhua Zhang14, Jennifer A Wargo15,4, P Andrew Futreal15.
Abstract
Immune checkpoint blockade produces clinical benefit in many patients. However, better biomarkers of response are still needed, and mechanisms of resistance remain incompletely understood. To address this, we recently studied a cohort of melanoma patients treated with sequential checkpoint blockade against cytotoxic T lymphocyte antigen-4 (CTLA-4) followed by programmed death receptor-1 (PD-1) and identified immune markers of response and resistance. Building on these studies, we performed deep molecular profiling including T cell receptor sequencing and whole-exome sequencing within the same cohort and demonstrated that a more clonal T cell repertoire was predictive of response to PD-1 but not CTLA-4 blockade. Analysis of CNAs identified a higher burden of copy number loss in nonresponders to CTLA-4 and PD-1 blockade and found that it was associated with decreased expression of genes in immune-related pathways. The effect of mutational load and burden of copy number loss on response was nonredundant, suggesting the potential utility of a combinatorial biomarker to optimize patient care with checkpoint blockade therapy.Entities:
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Year: 2017 PMID: 28251903 PMCID: PMC5819607 DOI: 10.1126/scitranslmed.aah3560
Source DB: PubMed Journal: Sci Transl Med ISSN: 1946-6234 Impact factor: 17.956