A Comprehensive Analysis of Programmed Cell Death-Associated Genes for Tumor Microenvironment Evaluation Promotes Precise Immunotherapy in Patients with Lung Adenocarcinoma.

J Pers Med

Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Department of Medical Oncology, Breast Tumor Center, Phase I Clinical Trial Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China.

Published: March 2023

Immune checkpoint inhibitors (ICIs) represent a new hot spot in tumor therapy. Programmed cell death has an important role in the prognosis. We explore a programmed cell death gene prognostic model associated with survival and immunotherapy prediction via computational algorithms. Patient details were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. We used LASSO algorithm and multiple-cox regression to establish a programmed cell death-associated gene prognostic model. Further, we explored whether this model could evaluate the sensitivity of patients to anti-PD-1/PD-L1. In total, 1342 patients were included. We constructed a programmed cell death model in TCGA cohorts, and the overall survival (OS) was significantly different between the high- and low-risk score groups (HR 2.70; 95% CI 1.94-3.75; < 0.0001; 3-year OS AUC 0.71). Specifically, this model was associated with immunotherapy progression-free survival benefit in the validation cohort (HR 2.42; 95% CI 1.59-3.68; = 0.015; 12-month AUC 0.87). We suggest that the programmed cell death model could provide guidance for immunotherapy in LUAD patients.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10058589PMC
http://dx.doi.org/10.3390/jpm13030476DOI Listing

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