Comprehensive analysis of an autophagy-related prognostic model for predicting survival based on TCGA and ICGC database in hepatocellular carcinoma patients.

ABSTRACT:

Background

There is accumulating evidence that autophagic activity is crucial to the development of hepatocellular carcinoma (HCC). Thus, we sought to develop a predictive model based on autophagy-related genes (ARGs) to forecast the prognosis of HCC patients.

Methods

Based on expression data from The Cancer Genome Atlas (TCGA) and ARGs from Human Autophagy Database (HADb), the differentially expressed ARGs were screened. The prognosis-related ARGs were identified using a univariate Cox regression analysis. Using multivariate Cox regression analysis, a prognostic model was developed. To assess the predictive value of the model, receiver operating characteristic (ROC) curve, Kaplan-Meier curve, and multivariable Cox regression analyses were conducted. A data cohort gathered i

SUBMITTER: An LN 

PROVIDER: S-EPMC9830320 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature