Construction of a prognostic model via WGCNA combined with the LASSO algorithm for stomach adenocarcinoma patients.

ABSTRACT:

Objective

This study aimed to identify prognostic signatures to predict the prognosis of patients with stomach adenocarcinoma (STAD), which is necessary to improve poor prognosis and offer possible treatment strategies for STAD patients.

Methods

The overlapping genes between the key model genes that were screened by the weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) whose expression was different with significance between normal and tumor tissues were extracted to serve as co-expression genes. Then, enrichment analysis was performed on these genes. Furthermore, the least absolute shrinkage and selection operator (LASSO) regression was performed to screen the hub genes among overlapping genes. Finally, we constructed a model to

SUBMITTER: Huang ZD 

PROVIDER: S-EPMC11335515 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature