Immune Landscape and a Promising Immune Prognostic Model Associated with TP53 in Early-stage Lung Adenocarcinoma

Overview

Journal Cancer Med

Specialty Oncology

Date 2020 Dec 14

PMID 33314730

Citations 17

Authors

Chengde Wu

Xiang Rao

Wei Lin

Affiliations

Soon will be listed here.

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 ) and TP53 wild-type (TP53 ) 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 and TP53 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.

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References

Chiu D, Tse A, Xu I, Cui J, Lai R, Li L . Hypoxia inducible factor HIF-1 promotes myeloid-derived suppressor cells accumulation through ENTPD2/CD39L1 in hepatocellular carcinoma. Nat Commun. 2017; 8(1):517. PMC: 5593860. DOI: 10.1038/s41467-017-00530-7. View

Siegel R, Miller K, Jemal A . Cancer statistics, 2020. CA Cancer J Clin. 2020; 70(1):7-30. DOI: 10.3322/caac.21590. View

Gordon-Weeks A, Lim S, Yuzhalin A, Jones K, Muschel R . Macrophage migration inhibitory factor: a key cytokine and therapeutic target in colon cancer. Cytokine Growth Factor Rev. 2015; 26(4):451-61. DOI: 10.1016/j.cytogfr.2015.03.002. View

Dong Z, Zhang J, Liu S, Su J, Zhang C, Xie Z . EGFR mutation correlates with uninflamed phenotype and weak immunogenicity, causing impaired response to PD-1 blockade in non-small cell lung cancer. Oncoimmunology. 2017; 6(11):e1356145. PMC: 5674946. DOI: 10.1080/2162402X.2017.1356145. View

Xu J, Zhang C, Wang X, Zhai L, Ma Y, Mao Y . Integrative Proteomic Characterization of Human Lung Adenocarcinoma. Cell. 2020; 182(1):245-261.e17. DOI: 10.1016/j.cell.2020.05.043. View

Dong Z, Zhong W, Zhang X, Su J, Xie Z, Liu S . Potential Predictive Value of and Mutation Status for Response to PD-1 Blockade Immunotherapy in Lung Adenocarcinoma. Clin Cancer Res. 2017; 23(12):3012-3024. DOI: 10.1158/1078-0432.CCR-16-2554. View

Coudray N, Ocampo P, Sakellaropoulos T, Narula N, Snuderl M, Fenyo D . Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning. Nat Med. 2018; 24(10):1559-1567. PMC: 9847512. DOI: 10.1038/s41591-018-0177-5. View

Wong W, Griesman J, Feng Z . Imputing genotypes using regularized generalized linear regression models. Stat Appl Genet Mol Biol. 2014; 13(5):519-29. DOI: 10.1515/sagmb-2012-0044. View

McGranahan N, Rosenthal R, Hiley C, Rowan A, Watkins T, Wilson G . Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution. Cell. 2017; 171(6):1259-1271.e11. PMC: 5720478. DOI: 10.1016/j.cell.2017.10.001. View

10.

Jager B, Klatt D, Plappert L, Golpon H, Lienenklaus S, Barbosa P . CXCR4/MIF axis amplifies tumor growth and epithelial-mesenchymal interaction in non-small cell lung cancer. Cell Signal. 2020; 73:109672. DOI: 10.1016/j.cellsig.2020.109672. View

11.

Bao X, Shi R, Zhao T, Wang Y . Immune landscape and a novel immunotherapy-related gene signature associated with clinical outcome in early-stage lung adenocarcinoma. J Mol Med (Berl). 2020; 98(6):805-818. PMC: 7297823. DOI: 10.1007/s00109-020-01908-9. View

12.

Zhou B, Flodby P, Luo J, Castillo D, Liu Y, Yu F . Claudin-18-mediated YAP activity regulates lung stem and progenitor cell homeostasis and tumorigenesis. J Clin Invest. 2018; 128(3):970-984. PMC: 5824875. DOI: 10.1172/JCI90429. View

13.

Zhang Z, Xie H, Chen P, Cao P . Development and Identification of a Nomogram Prognostic Model for Patients with Primary Clear Cell Carcinoma of the Liver. Med Sci Monit. 2020; 26:e919789. PMC: 6996864. DOI: 10.12659/MSM.919789. View

14.

Kurebayashi Y, Emoto K, Hayashi Y, Kamiyama I, Ohtsuka T, Asamura H . Comprehensive Immune Profiling of Lung Adenocarcinomas Reveals Four Immunosubtypes with Plasma Cell Subtype a Negative Indicator. Cancer Immunol Res. 2016; 4(3):234-47. DOI: 10.1158/2326-6066.CIR-15-0214. View

15.

Wu P, Zheng Y, Wang Y, Wang Y, Liang N . Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma. J Transl Med. 2020; 18(1):380. PMC: 7542703. DOI: 10.1186/s12967-020-02545-z. View

16.

Rizvi N, Hellmann M, Snyder A, Kvistborg P, Makarov V, Havel J . Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015; 348(6230):124-8. PMC: 4993154. DOI: 10.1126/science.aaa1348. View

17.

Kadara H, Choi M, Zhang J, Parra E, Rodriguez-Canales J, Gaffney S . Whole-exome sequencing and immune profiling of early-stage lung adenocarcinoma with fully annotated clinical follow-up. Ann Oncol. 2016; 28(1):75-82. PMC: 5982809. DOI: 10.1093/annonc/mdw436. View

18.

He R, Zuo S . A Robust 8-Gene Prognostic Signature for Early-Stage Non-small Cell Lung Cancer. Front Oncol. 2019; 9:693. PMC: 6684755. DOI: 10.3389/fonc.2019.00693. View

19.

Heagerty P, Zheng Y . Survival model predictive accuracy and ROC curves. Biometrics. 2005; 61(1):92-105. DOI: 10.1111/j.0006-341X.2005.030814.x. View

20.

Kamimura A, Kamachi M, Nishihira J, Ogura S, Isobe H, Dosaka-Akita H . Intracellular distribution of macrophage migration inhibitory factor predicts the prognosis of patients with adenocarcinoma of the lung. Cancer. 2000; 89(2):334-41. View