Identification of Inflammatory Response-Related Gene Signature Associated With Immune Status and Prognosis of Lung Adenocarcinoma

Weijie Zou; Li Chen; Wenwen Mao; Su Hu; Yuanqing Liu; Chunhong Hu

doi:10.3389/fbioe.2021.772206

Identification of Inflammatory Response-Related Gene Signature Associated With Immune Status and Prognosis of Lung Adenocarcinoma

Front Bioeng Biotechnol. 2021 Nov 22:9:772206. doi: 10.3389/fbioe.2021.772206. eCollection 2021.

Authors

Weijie Zou^{1

2}, Li Chen³, Wenwen Mao^{1

2}, Su Hu^{1

2}, Yuanqing Liu^{1

2}, Chunhong Hu^{1

2}

Affiliations

¹ Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
² Institute of Medical Imaging of Soochow University, Suzhou, China.
³ Department of Interventional Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Abstract

Background: Lung adenocarcinoma (LUAD) is an exceedingly diverse disease, making prognostication difficult. Inflammatory responses in the tumor or the tumor microenvironment can alter prognosis in the process of the ongoing cross-talk between the host and the tumor. Nonetheless, Inflammatory response-related genes' prognostic significance in LUAD, on the other hand, has yet to be determined. Materials and Methods: The clinical data as well as the mRNA expression patterns of LUAD patients were obtained from a public dataset for this investigation. In the TCGA group, a multigene prognostic signature was built utilizing LASSO Cox analysis. Validation was executed on LUAD patients from the GEO cohort. The overall survival (OS) of low- and high-risk cohorts was compared utilizing the Kaplan-Meier analysis. The assessment of independent predictors of OS was carried out utilizing multivariate and univariate Cox analyses. The immune-associated pathway activity and immune cell infiltration score were computed utilizing single-sample gene set enrichment analysis. GO keywords and KEGG pathways were explored utilizing gene set enrichment analysis. Results: LASSO Cox regression analysis was employed to create an inflammatory response-related gene signature model. The high-risk cohort patients exhibited a considerably shorter OS as opposed to those in the low-risk cohort. The prognostic gene signature's predictive ability was demonstrated using receiver operating characteristic curve analysis. The risk score was found to be an independent predictor of OS using multivariate Cox analysis. The functional analysis illustrated that the immune status and cancer-related pathways for the two-risk cohorts were clearly different. The tumor stage and kind of immune infiltrate were found to be substantially linked with the risk score. Furthermore, the cancer cells' susceptibility to anti-tumor medication was substantially associated with the prognostic genes expression levels. Conclusion: In LUAD, a new signature made up of 8 inflammatory response-related genes may be utilized to forecast prognosis and influence immunological state. Inhibition of these genes could also be used as a treatment option.

Keywords: drug sensitivity; gene signature; immune status; inflammatory response; lung adenocarcinoma; tumor microenvironment.