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September 19, 2025Open MedicineOpen Access

A machine learning-based prognostic model integrating mRNA stemness index, hypoxia, and glycolysis‑related biomarkers for colorectal cancer

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Authors

DLDan LiuMZM. ZhangYNYing Nie

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Overview

Cox-prognostic model predicts survival in colorectal cancer patients by integrating hypoxia and biomarkers, indicating potential clinical utility.

Key Points

  • The prognostic model demonstrates high accuracy in predicting survival among colorectal cancer patients based on biomarkers and indices.
  • Using data from TCGA, analysis revealed distinct clusters of CRC patients, where one cluster had worse outcomes based on hypoxia and glycolysis-related genes.
  • Employing methods like gene co-expression and LASSO regression, the model effectively identifies high-risk individuals for immunotherapy response.
  • Creating a five-gene nomogram, the prognosis assessment proved reliable in guiding treatment decisions through decision curve analysis.

Cite This Study

Liu et al. (2025) studied this question.

synapsesocial.com/papers/68d435ed713b0b5dfea75ec0https://doi.org/10.1515/med-2025-1247
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