Immune landscape and a promising immune prognostic model associated with TP53 in early‐stage lung adenocarcinoma. (12th December 2020)

• Record Type: Journal Article
• Authors: Wu, Chengde; Rao, Xiang; Lin, Wei
• Is Part Of: Cancer medicine. Volume 10:Number 3(2021)
• Page Start: 806
• Page End: 823
• Publication Date: 2020-12-12
• Subjects: CIBERSORT -- early‐stage lung adenocarcinoma -- immune prognostic model -- prognosis -- TP53; 616.994005
• DOI: 10.1002/cam4.3655
• Languages: English
• ISSNs: 2045-7634

Abstract

Abstract: Purpose: TP53 mutation, one of the most frequent mutations in early‐stage lung adenocarcinoma (LUAD), triggers a series of alterations in the immune landscape, progression, and clinical outcome of early‐stage LUAD. Our study was designed to unravel the effects of TP53 mutation on the immunophenotype of early‐stage LUAD and formulate a TP53‐associated immune prognostic model (IPM) that can estimate prognosis in early‐stage LUAD patients. Materials and methods: Immune‐associated differentially expressed genes (DEGs) between TP53 mutated (TP53 MUT ) and TP53 wild‐type (TP53 WT ) early‐stage LUAD were comprehensively analyzed. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis identified the prognostic immune‐associated DEGs. We constructed and validated an IPM based on the TCGA and a meta‐GEO composed of GSE72094, GSE42127, and GSE31210, respectively. The CIBERSORT algorithm was analyzed for assessing the percentage of immune cell types. A nomogram model was established for clinical application. Results: TP53 mutation occurred in approximately 50.00% of LUAD patients, stimulating a weakened immune response in early‐stage LUAD. Sixty‐seven immune‐associated DEGs were determined between TP53 WT and TP53 MUT cohort. An IPM consisting of two prognostic immune‐associated DEGs (risk score = 0.098 * ENTPD2 expression + 0.168 * MIF expression) was developed through 397 cases in the TCGA and further validated based on 623 patients in a meta‐GEO. The IPM stratified patients into low or high risk of undesirable survival and was identified as an independent prognostic indicator in multivariate analysis (HR = 2.09, 95% CI: 1.43–3.06, p < 0.001). Increased expressions of PD‐L1, CTLA‐4, and TIGIT were revealed in the high‐risk group. Prognostic nomogram incorporating the IPM and other clinicopathological parameters (TNM stage and age) achieved optimal predictive accuracy and clinical utility. Conclusion: The IPM based on TP53 status is a reliable and robust immune signature to identify early‐stage LUAD patients with high risk of unfavorable survival. Abstract : An immune prognostic model based on TP53 status is a hopeful biomarker to optimize the prognosis of early‐stage lung adenocarcinoma.