Effects of gut microbiota on immune checkpoint inhibitors in multi-cancer and as microbial biomarkers for predicting therapeutic response

Yufeng Lin; Mingxu Xie; Harry Cheuk-Hay Lau; Ruijie Zeng; Ruyi Zhang; Luyao Wang; Qing Li; Yiwei Wang; Danyu Chen; Lanping Jiang; William Damsky; Jun Yu

doi:10.1016/j.medj.2024.10.007

Effects of gut microbiota on immune checkpoint inhibitors in multi-cancer and as microbial biomarkers for predicting therapeutic response

Med. 2024 Nov 7:100530. doi: 10.1016/j.medj.2024.10.007. Online ahead of print.

Authors

Affiliations

¹ Institute of Digestive Disease, Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, CUHK Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong SAR, China.
² Institute of Digestive Disease, Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, CUHK Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong SAR, China; Department of Anaesthesia and Intensive Care, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China.
³ Department of Dermatology, Yale School of Medicine, Yale University, New Haven, CT, USA.
⁴ Institute of Digestive Disease, Department of Medicine and Therapeutics, State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, CUHK Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong SAR, China. Electronic address: [email protected].

PMID: 39515321
DOI: 10.1016/j.medj.2024.10.007

Abstract

Background: Gut bacteria are related to immune checkpoint inhibitors (ICIs). However, there is inconsistency in ICI-associated species, while the role of non-bacterial microbes in immunotherapy remains elusive. Here, we evaluated the association of trans-kingdom microbes with ICIs by multi-cohort multi-cancer analyses.

Methods: We retrieved fecal metagenomes from 1,359 ICI recipients with four different cancers (metastatic melanoma [MM], non-small cell lung carcinoma [NSCLC], renal cell cancer [RCC], and hepatocellular carcinoma) from 12 published datasets. Microbiota composition was analyzed using the Wilcoxon rank test. The performance of microbial biomarkers in predicting ICI response was assessed by random forest. Key responder-associated microbes were functionally examined in vitro and in mice.

Findings: Trans-kingdom gut microbiota (bacteria, eukaryotes, viruses, and archaea) was significantly different between ICI responders and non-responders in multi-cancer. Bacteria (Faecalibacterium prausnitzii, Coprococcus comes) and eukaryotes (Nemania serpens, Hyphopichia pseudoburtonii) were consistently enriched in responders of ≥2 cancer types or from ≥3 cohorts, contrasting with the depleted bacterium Hungatella hathewayi. Responder-associated species in each cancer were revealed, such as F. prausnitzii in MM and 6 species in NSCLC. These signature species influenced ICI efficacy by modulating CD8⁺ T cell activity in vitro and in mice. Moreover, bacterial and eukaryotic biomarkers showed great performance in predicting ICI response in patients from discovery and two validation cohorts (MM: area under the receiver operating characteristic curve [AUROC] = 72.27%-80.19%; NSCLC: AUROC = 72.70%-87.98%; RCC: AUROC = 83.33%-89.58%).

Conclusions: This study identified trans-kingdom microbial signatures associated with ICI in multi-cancer and specific cancer types. Trans-kingdom microbial biomarkers are potential predictors of ICI response in patients with cancer.

Funding: Funding information is shown in the acknowledgments.

Keywords: Pre-clinical research.