Developing metabolic gene signatures to predict intrahepatic cholangiocarcinoma prognosis and mining a miRNA regulatory network.

ABSTRACT:

Background

Metabolic disturbance is closely correlated with intrahepatic cholangiocarcinoma (IHCC), and we aimed to identify metabolic gene marker for the prognosis of IHCC.

Methods

We obtained expression and clinical data from 141 patients with IHCC from public databases. Prognostic metabolic genes were selected using univariate Cox regression analysis. Unsupervised cluster analysis was applied to identify IHCC subtypes, and CIBERSORT was used for immune infiltration analysis of different subtypes. Then, the metabolic gene signature was screened using multivariate Cox regression analysis and the LASSO algorithm. The prognostic potential and regulatory network of the metabolic gene signature were further investigated.

Results

We screened 228 prognosis-related metaboli

SUBMITTER: Ran X 

PROVIDER: S-EPMC8761474 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature