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Background  The microbiome has been shown to affect the response to Immune Checkpoint Inhibitors (ICIs) in a small number of cancers and in preclinical models. Here, we sought to broadly survey cancers to identify those in which the microbiome may play a prognostic role using retrospective analyses of patients with advanced cancer treated with ICIs.    Methods  We conducted a retrospective analysis of 690 patients who received ICI therapy for advanced cancer. We used a literature review to define a causal model for the relationship between medications, the microbiome, and ICI response to guide the abstraction of electronic health records. Medications with precedent for changes to the microbiome included antibiotics, corticosteroids, proton pump inhibitors, histamine receptor blockers, non-steroid anti-inflammatories and statins. We tested the effect of medication timing on overall survival (OS) and evaluated the robustness of medication effects in each cancer. Finally, we compared the size of the effect observed for different classes of antibiotics to taxa that have been correlated to ICI response using a literature review of culture-based antibiotic susceptibilities.    Results  Of the medications assessed, only antibiotics and corticosteroids significantly associated with shorter OS. The hazard ratios (HRs) for antibiotics and corticosteroids were highest near the start of ICI treatment but remained significant when given prior to ICI. Antibiotics and corticosteroids remained significantly associated with OS even when controlling for multiple factors such as Eastern Cooperative Oncology Group performance status, Charlson Comorbidity Index score, and stage. When grouping antibiotics by class, β-lactams showed the strongest association with OS across all tested cancers.    Conclusions  The timing and strength of the correlations with antibiotics and corticosteroids after controlling for confounding factors are consistent with the microbiome involvement with the response to ICIs across several cancers.

bmc cancer

Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications