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Updated: Sep 9, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Microbiome meets immunotherapy: unlocking the hidden predictors of immune checkpoint inhibitors
Lihaoyun Huang1,2, Yu Li2, Chunyan Zhang2
1Department of Oncology, Zhujiang Hospital, Southern Medical University; Donghai County People's Hospital (Affiliated Kangda College of Nanjing Medical University), Lianyungang, China.
Abstract:
Immune checkpoint inhibitors (ICIs) have revolutionized cancer immunotherapy, with the microbiome significantly influencing treatment outcomes. Analysis of 4663 studies (2014.01-2024.10) identified 71 eligible randomized controlled trials (RCTs) and cohort studies (41 viral, 30 bacterial). Analyses included subgroup assessments by cancer type, microbial taxa, and ICI regimens. Among 4663 identified studies, 71 met inclusion criteria (41 viral, 30 bacterial). Viral status, particularly hepatitis B virus (HBV) and human papillomavirus (HPV), significantly associated with ORR and DCR. Bacterial enrichment correlated with improved survival in hepatobiliary (OS: HR = 4.33, 95%CI: 2.20-8.50) and lung cancers (PFS: HR = 1.70, 95%CI: 1.04-2.78). Multi-microbiome models demonstrated superior outcome prediction, with microbial diversity correlating with improved PFS (HR = 0.64, 95%CI: 0.42-0.98). Viral status showed cancer-specific associations with SAEs. The microbiome serves as a valuable predictor of ICI outcomes. Future studies should emphasize large-scale RCTs, standardized assessment methods, and host-microbiome interactions.
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