Integrative nomogram model based on anoikis-related genes enhances prognostic evaluation in colorectal cancer.

ABSTRACT:

Background

Revealing the role of anoikis resistance plays in CRC is significant for CRC diagnosis and treatment. This study integrated the CRC anoikis-related key genes (CRC-AKGs) and established a novel model for improving the efficiency and accuracy of the prognostic evaluation of CRC.

Methods

CRC-ARGs were screened out by performing differential expression and univariate Cox analysis. CRC-AKGs were obtained through the LASSO machine learning algorithm and the LASSO Risk-Score was constructed to build a nomogram clinical prediction model combined with the clinical predictors. In parallel, this work developed a web-based dynamic nomogram to facilitate the generalization and practical application of our model.

Results

We identified 10 CRC-AKGs and a risk-related progn

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC11261108 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature