Identification and validation of a novel prognostic model of inflammation-related gene signature of lung adenocarcinoma.

ABSTRACT: Previous literatures have suggested the importance of inflammatory response during lung adenocarcinoma (LUAD) development. This study aimed at exploring the inflammation-related genes and developing a prognostic signature for predicting the prognosis of LUAD. Survival‑associated inflammation-related genes were identified by univariate Cox regression analysis in the dataset of The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) penalized Cox regression model was used to derive a risk signature which is significantly negatively correlated with OS and divide samples into high-, medium- and low-risk group. Univariate and multivariate Cox analyses suggested that the level of risk group was an independent prognostic factor of the overall survival (OS). Tim

SUBMITTER: Luo D 

PROVIDER: S-EPMC9427773 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature