Integrated analysis of purine metabolism assists in predicting prognosis and treatment decisions for patients with lung adenocarcinoma.

ABSTRACT

The incidence of lung cancer, especially lung adenocarcinoma (LUAD), has recently increased. Targeted therapy and immunotherapy combined with conventional treatment have shown surprising benefits in enhancing the LUAD patient's prognosis. For the purpose of guiding treatment planning and the prognosis of LUAD, more research is required. The particular aim of this work was to establish a purine metabolism scoring (PMS) model for the purpose of individually forecasting treatment outcomes and overall survival for patients who have LUAD. Clinical and whole genome data were obtained from the TCGA-LUAD cohort via "UCSC". The 25 driver purine metabolism-related prognostic genes were determined founded on univariate Cox regression. Then PMS was developed through stepwise LASSO Cox regression. Survival analysis indicated that patients who have PMS experienced worse outcomes. We validated the PGM2 effect on lung adenocarcinoma malignancy in in vitro experiments. Univariate as well as multivariate Cox regression suggested that PMS was an independent prognostic indicator for LUAD patients, which was confirmed in subgroup analysis. Functional assay demonstrated that immune response as well as cytotoxicity pathways have a connection with lower PMS, and patients who have low PMS possess an active immune microenvironment. Moreover, the LUAD patients who have low PMS showed greater sensitivity to immunotherapy, targeted therapy, as well as chemotherapy. Knockdown of PGM2 was discovered to decrease the proliferation, invasion, as well as migration of lung adenocarcinoma cells in an in vitro assay. Pertaining to this particular research, we created a PMS model and conducted a thorough analysis of purine metabolism in LUAD in order to determine prognosis and offer recommendations for treatment. This finding offered a fresh concept for the clinical management of LUAD and novel therapy protocols.