Identification and validation of a novel signature as a diagnostic and prognostic biomarker in colorectal cancer.

ABSTRACT:

Background

Colorectal cancer (CRC) is one of the most common malignant neoplasms worldwide. Although marker genes associated with CRC have been identified previously, only a few have fulfilled the therapeutic demand. Therefore, based on differentially expressed genes (DEGs), this study aimed to establish a promising and valuable signature model to diagnose CRC and predict patient's prognosis.

Methods

The key genes were screened from DEGs to establish a multiscale embedded gene co-expression network, protein-protein interaction network, and survival analysis. A support vector machine (SVM) diagnostic model was constructed by a supervised classification algorithm. Univariate Cox analysis was performed to construct two prognostic signatures for overall survival and disease-free

SUBMITTER: Wang D 

PROVIDER: S-EPMC9628086 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature