A B cell-derived gene expression signature associates with an immunologically active tumor microenvironment and response to immune checkpoint blockade therapy. (2nd January 2019)

• Record Type: Journal Article
• Authors: Varn, Frederick S.; Wang, Yue; Cheng, Chao
• Is Part Of: Oncoimmunology. Volume 8:Number 1(2019)
• Publication Date: 2019-01-02
• Subjects: Immunotherapy -- genomics -- tumor immunology -- B cells -- immune checkpoint blockade -- gene signatures -- biomarkers; Tumors -- Immunological aspects -- Periodicals; Neoplasms -- therapy -- Periodicals; Immunotherapy -- Periodicals; 616.994
• DOI: 10.1080/2162402X.2018.1513440
• Languages: English
• ISSNs: 2162-402X

Abstract

ABSTRACT: Immune checkpoint inhibitors have shown great potential in treating solid tumors, inducing durable remission and prolonged survival time in responders. Despite their promise, a large fraction of patients remains unresponsive to these treatments highlighting the need for biomarkers that can predict patient sensitivity. Pre-treatment gene expression profiles for patients receiving immune checkpoint inhibitors have recently become available, establishing a new medium by which to discover biomarkers that predict therapy response. In this study, we mined for transcriptomic correlates of response by applying immune cell-derived gene expression signatures to publicly available datasets containing matched gene expression and response efficacy information. These datasets were comprised of urothelial carcinoma patients receiving anti-PD-L1 (n = 25), melanoma patients receiving anti-PD-1 (n = 28), and melanoma patients receiving anti-CTLA-4 (n = 42). We identified one signature, derived from a subpopulation of B cells, with scores that were significantly and reproducibly elevated in patients experiencing clinical benefit following therapy targeting the PD-1/PD-L1 axis and were additionally elevated in patients responsive to anti-CTLA-4 therapy. Multivariate models revealed that this signature was associated with response independent of other response-predictive biomarkers, including tumor mutation burden. Functional annotation of the signature revealed it to be associated with features indicative of an immunologically active microenvironment, including B and T cell activation as well as antigen presentation activity. The preliminary findings presented detail a transcriptomic signature associated with response to multiple checkpoint inhibitors and suggest novel biological associations that warrant further investigation.