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Background <p>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.</p> Methods <p>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 <i>vivo</i> assays.</p> Results <p>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.</p> Conclusion <p>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.</p>

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Establishment of a microbial abundance prognostic model for colorectal cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月10日

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  • Jie Lin,
  • Zhi Ling,
  • Wenbin Fan,
  • Qinyun Cai,
  • Jingjing Yang,
  • Mingyang Tao,
  • Huaijuan Guo,
  • Ying Wang,
  • Xuebing Yan,
  • Changsong Yang

摘要

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.