Mega- and meta-analyses of fecal metagenomic studies assessing response to immune checkpoint inhibitors

Purpose Gut microbiota have been associated with response to immune checkpoint inhibitors (ICI) including anti-PD-1 and anti-CTLA-4 antibodies. However, inter-study difference in design, patient cohorts and data analysis pose challenges to identifying species consistently associated with response to ICI or lack thereof. Experimental Design We uniformly processed and analyzed data from three studies of microbial metagenomes in cancer immunotherapy response (four distinct data sets) to identify species consistently associated with response or non-response (n=190 patient samples). Metagenomic data were processed and analyzed using Metaphlan v2.0. Meta- and mega-analyses were performed using a two-part modelling approach of species present in at least 20% of samples to account for both prevalence and relative abundance differences between responders/non-responders. Results Meta- and mega-analyses identified five species that were concordantly significantly different between responders and non-responders. Amongst them, Bacteroides thetaiotaomicron and Clostridium bolteae relative abundance (RA) were independently predictive of non-response to immunotherapy when data sets were combined and analyzed using mega-analyses (AUC 0.59 95% CI 0.51-0.68 and AUC 0.61 95% CI 0.52-0.69, respectively). Conclusions Meta- and mega-analysis of published metagenomic studies identified bacterial species both positively and negatively associated with immunotherapy responsiveness across four published cohorts. ### Competing Interest Statement AAH, BC, PS, MW, VR, WX, BAC, have no conflicts to report. AS has received compensation from: Merck, Bristol-Myers Squibb, Novartis, Oncorus, Janssen; and grant/research support from: Novartis, Bristol-Myers Squibb, Symphogen AstraZeneca/Medimmune, Merck, Bayer, Surface Oncology, Northern Biologics, Janssen Oncology/Johnson & Johnson, Roche, Regeneron, Alkermes, Array Biopharma/Pfizer, GSK.