Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma.

ABSTRACT: Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune inf

SUBMITTER: Chen Y 

PROVIDER: S-EPMC9918018 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature