A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors.

Autor:	Shaikh FY; The Bloomberg-Kimmel Institute of Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, Maryland.; Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland., White JR; Resphera Biosciences, Baltimore, Maryland., Gills JJ; The Bloomberg-Kimmel Institute of Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, Maryland.; Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland., Hakozaki T; Department of Thoracic Oncology and Respiratory Medicine, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Bunkyo City, Tokyo, Japan., Richard C; University of Montreal Research Center (CRCHUM), Montreal, Quebec., Routy B; University of Montreal Research Center (CRCHUM), Montreal, Quebec., Okuma Y; Department of Thoracic Oncology and Respiratory Medicine, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital, Bunkyo City, Tokyo, Japan.; Department of Thoracic Oncology, National Cancer Center Hospital, Chuo City, Tokyo, Japan., Usyk M; Department of Population Health, NYU School of Medicine, New York, New York., Pandey A; Department of Medicine, NYU School of Medicine, New York, New York., Weber JS; Department of Medicine, NYU School of Medicine, New York, New York., Ahn J; Department of Population Health, NYU School of Medicine, New York, New York., Lipson EJ; The Bloomberg-Kimmel Institute of Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, Maryland.; Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland., Naidoo J; The Bloomberg-Kimmel Institute of Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, Maryland.; Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland., Pardoll DM; The Bloomberg-Kimmel Institute of Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, Maryland.; Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland.; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland., Sears CL; The Bloomberg-Kimmel Institute of Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, Maryland. csears@jhmi.edu.; Departments of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland.; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Jazyk:	angličtina
Zdroj:	Clinical cancer research : an official journal of the American Association for Cancer Research [Clin Cancer Res] 2021 May 01; Vol. 27 (9), pp. 2571-2583. Date of Electronic Publication: 2021 Feb 16.
DOI:	10.1158/1078-0432.CCR-20-4834
Abstrakt:	Purpose: While immune checkpoint inhibitors (ICI) have revolutionized the treatment of cancer by producing durable antitumor responses, only 10%-30% of treated patients respond and the ability to predict clinical benefit remains elusive. Several studies, small in size and using variable analytic methods, suggest the gut microbiome may be a novel, modifiable biomarker for tumor response rates, but the specific bacteria or bacterial communities putatively impacting ICI responses have been inconsistent across the studied populations. Experimental Design: We have reanalyzed the available raw 16S rRNA amplicon and metagenomic sequencing data across five recently published ICI studies ( n = 303 unique patients) using a uniform computational approach. Results: Herein, we identify novel bacterial signals associated with clinical responders (R) or nonresponders (NR) and develop an integrated microbiome prediction index. Unexpectedly, the NR-associated integrated index shows the strongest and most consistent signal using a random effects model and in a sensitivity and specificity analysis ( P < 0.01). We subsequently tested the integrated index using validation cohorts across three distinct and diverse cancers ( n = 105). Conclusions: Our analysis highlights the development of biomarkers for nonresponse, rather than response, in predicting ICI outcomes and suggests a new approach to identify patients who would benefit from microbiome-based interventions to improve response rates. (©2021 American Association for Cancer Research.)
Databáze:	MEDLINE
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