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

Clin Cancer Res. 2021 May 1;27(9):2571-2583. doi: 10.1158/1078-0432.CCR-20-4834. Epub 2021 Feb 16.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacteria / classification
  • Bacteria / genetics
  • Biomarkers*
  • Computational Biology* / methods
  • Gastrointestinal Microbiome
  • Genome, Bacterial
  • Humans
  • Immune Checkpoint Inhibitors / pharmacology*
  • Immune Checkpoint Inhibitors / therapeutic use
  • Metagenomics / methods
  • Microbiota / drug effects*
  • Microbiota / genetics
  • RNA, Ribosomal, 16S
  • ROC Curve
  • Reproducibility of Results
  • Whole Genome Sequencing

Substances

  • Biomarkers
  • Immune Checkpoint Inhibitors
  • RNA, Ribosomal, 16S