Identification and validation in a novel quantification system of the glutamine metabolism patterns for the prediction of prognosis and therapy response in hepatocellular carcinoma.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) has one of the highest mortality rates worldwide. Abnormal glutamine metabolism (GM) has been reported to be involved in HCC progression. The current study sought to examine the predictive value of GM in HCC patient's prognosis and therapy response.

Methods

The RNA-sequencing data and clinical information of HCC samples were obtained from The Cancer Genome Atlas (TCGA) database (N=377) and Gene Expression Omnibus (GEO) database (N=242). By analyzing a data set from TCGA, we showed that the GM landscape of HCC patients was developed based on the non-negative matrix factorization (NMF) algorithm. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analyses were used to construc

SUBMITTER: Jin S 

PROVIDER: S-EPMC9660061 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature