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Purpose: While immune checkpoint inhibitors (ICIs) have revolutionized the treatment of cancer by producing durable anti-tumor 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 analytical 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 re-analyzed 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 response (R) or nonresponse (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.
Fyza Y Shaikh
Cynthia L Sears
Fyza Y Shaikh,James R White,Joell J Gills,Taiki Hakozaki,Corentin Richard,Bertrand Routy,Yusuke Okuma,Mykhaylo Usyk,Abhishek Pandey,Jeffrey S Weber,Jiyoung Ahn,Evan J Lipson,Jarushka Naidoo,Drew M Pardoll,Cynthia L Sears