Establishment of a microbial abundance prognostic model for colorectal cancer

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Authors: Jie Lin, Zhi Ling, Wenbin Fan, Qinyun Cai, Jingjing Yang, Mingyang Tao, Huaijuan Guo, Ying Wang, Xuebing Yan, Changsong Yang
Cited by: 0
References: 71

Abstract

BACKGROUND: Previous studies have demonstrated a close association between gut microbiota and the onset and progression of colorectal cancer (CRC). However, the prognostic and therapeutic value of microbiota in CRC remains controversial. This study integrates multiomics approaches to investigate the prognostic and therapeutic implications of microbiota in CRC. METHODS: A CRC microbial abundance prognostic model (MAPM) was constructed utilizing bioinformatics approaches to evaluate its prognostic value. The relationship between MAPM and the clinical characteristics of CRC, as well as the immune microenvironment, was analyzed. Furthermore, key prognostic genes associated with the MAPM were identified and validated in vitro and in vivo assays. RESULTS: The MAPM comprised 12 microbes and effectively stratified the prognosis of CRC patients. The risk score of this model exhibits a close association with the immune infiltration of CRC. Remarkably, HSF4, identified as a key gene from the MAPM, is found to be overexpressed in the tumor tissues, and its high expression independently predicts poor prognosis in CRC patients. Knockdown of HSF4 significantly inhibits the proliferation, colony formation, migration, and invasion of CRC cells in vitro, as well as the growth of xenografts in nude mice. CONCLUSION: A MAPM is established to predict the prognosis of CRC patients, further highlighting the potential of detecting the microbiome in clinical practice. Moreover, HSF4, as a prognostic gene from the MAPM, is a promising drug target for CRC treatment.

Fields of Study & Subjects

Ferroptosis and cancer prognosis Gut microbiota and health Cancer Immunotherapy and Biomarkers

Publication details

Journal / source
BMC Cancer
Volume
26
Issue
1
Pages
197–197
Publication date
10 January 2026
Language
EN