Unknown

Dataset Information

Identification of a metabolic-related gene signature predicting the overall survival for patients with stomach adenocarcinoma.


ABSTRACT:

Background

The reprogramming of energy metabolism and consistently altered metabolic genes are new features of cancer, and their prognostic roles remain to be further studied in stomach adenocarcinoma (STAD).

Methods

Messenger RNA (mRNA) expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) and the GSE84437 databases from the Gene Expression Omnibus (GEO) database. A univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model established a novel metabolic signature based on TCGA. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy.

Results

A novel metabolic-related signature (in

SUBMITTER: Nie Y 

PROVIDER: S-EPMC7877239 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

altmetric image

Publications

Sorry, this publication's infomation has not been loaded in the Indexer, please go directly to PUBMED or Altmetric.

Similar Datasets