Improving the Prognosis of Colon Cancer through Knowledge-Based Clinical-Molecular Integrated Analysis.

ABSTRACT:

Background

Colon cancer has high morbidity and mortality rates among cancers. Existing clinical staging systems cannot accurately assess the prognostic risk of colon cancer patients. This study was aimed at improving the prognostic performance of the colon cancer clinical staging system through knowledge-based clinical-molecular integrated analysis.

Methods

374 samples from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) dataset were used as the discovery set. 98 samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset were used as the validation set. After converting gene expression data into pathway dysregulation scores (PDSs), the random survival forest and Cox model were used to identify the best prognostic supplementary factors. The corresp

SUBMITTER: Tong D 

PROVIDER: S-EPMC8051523 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature