Construction of an immune-related prognostic model and potential drugs screening for esophageal cancer based on bioinformatics analyses and network pharmacology.

ABSTRACT:

Background

Esophageal cancer (ESCA) is a highly invasive malignant tumor with poor prognosis. This study aimed to discover a generalized and high-sensitivity immune prognostic signature that could stratify ESCA patients and predict their overall survival, and to discover potential therapeutic drugs by the connectivity map.

Methods

The key gene modules significantly related to clinical traits (survival time and state) of ESCA patients were selected by weighted gene coexpression network analysis (WCGNA), then the univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a 15-immune-related gene prognostic signature.

Results

The immune-related risk model was related to clinical and pathologic factors and remaine

SUBMITTER: Qi P 

PROVIDER: S-EPMC11131936 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature