Ontology highlight
ABSTRACT: Background
The acidic microenvironment (AME), like hypoxia, inflammation, or immunoreaction, is a hallmark of the tumor microenvironment (TME). This work aimed to develop a prediction signature dependent on AME-associated lncRNAs in order to predict the prognosis of LC individuals.Methods
We downloaded RNA-seq information and the corresponding clinical and predictive data from The Cancer Genome Atlas (TCGA) dataset and conducted univariate and multivariate Cox regression analyses to identify AME-associated lncRNAs for the construction of a prediction signature The Kaplan-Meier technique was utilized to determine the overall survival (OS) rate of the high (H)-risk and low (L)-risk groups. Using gene set enrichment analysis (GSEA) the functional variations between the H- and
SUBMITTER: Jiang P
PROVIDER: S-EPMC9660327 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature