Identification of genome-wide copy number variation-driven subtypes for the treatment and prognostic prediction of esophageal carcinoma.

ABSTRACT:

Background

Esophageal carcinoma (ESCA) is a frequently detected gastrointestinal cancer. Copy number variants (CNVs) have a dramatic impact on the screening, diagnosis and prognostic prediction of cancers. However, the mechanism of action of CNVs on ESCA occurrence and progression remains unclear.

Methods

ESCA samples from The Cancer Genome Atlas (TCGA) were typed by consensus clustering using CNV-associated genes. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to section gene modules closely related to the two clusters, and sub-networks were constructed as hub genes. In addition, seven prognosis-correlated genes were further screened and retained by multivariate Cox regression analysis to develop a prognostic assessment model. The ssGSEA algorithm assessed en

SUBMITTER: Zhao C 

PROVIDER: S-EPMC11462465 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature