Immune checkpoint blockade (ICB) targeting PD-1 and CTLA-4 shows unpredictable responses across cancers. This study used deep shotgun metagenomic sequencing of baseline fecal samples (n=106 discovery cohort) from a phase 2 trial of combination ICB (ipilimumab and nivolumab) in patients with diverse rare cancers. Strain-resolved microbial abundances improved machine learning predictions of ICB response and 12-month progression-free survival compared to species-level analysis or clinical factors. A meta-analysis of six studies (n=364 validation cohort) showed cross-cancer validity of strain-response signatures only with concordant ICB regimens, suggesting microbiome diagnostics/therapeutics should be tailored to the ICB regimen, not cancer type.
Publisher
Nature Medicine
Published On
Mar 01, 2024
Authors
Ashray Gunjur, Yan Shao, Timothy Rozday, Oliver Klein, Andre Mu, Bastiaan W. Haak, Ben Markman, Damien Kee, Matteo S. Carlino, Craig Underhill, Sophia Frentzas, Michael Michael, Bo Gao, Jodie Palmer, Jonathan Cebon, Andreas Behren, David J. Adams, Trevor D. Lawley
Tags
Immune checkpoint blockade
microbiome
metagenomic sequencing
predictive analysis
rare cancers
machine learning
ICB regimens
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