Identification of natural killer cell associated subtyping and gene signature to predict prognosis and drug sensitivity of lung adenocarcinoma.

ABSTRACT: Introduction: This research explored the immune characteristics of natural killer (NK) cells in lung adenocarcinoma (LUAD) and their predictive role on patient survival and immunotherapy response. Material and methods: Molecular subtyping of LUAD samples was performed by evaluating NK cell-associated pathways and genes in The Cancer Genome Atlas (TCGA) dataset using consistent clustering. 12 programmed cell death (PCD) patterns were acquired from previous study. Riskscore prognostic models were constructed using Least absolute shrinkage and selection operator (Lasso) and Cox regression. The model stability was validated in Gene Expression Omnibus database (GEO). Results: We classified LUAD into three different molecular subgroups based on NK cell-related genes, with th

SUBMITTER: Zhang D 

PROVIDER: S-EPMC10119412 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature