Screening and Identification of Key Genes for Clinical Benefit of Immunotherapy on Lung Adenocarcinoma Based on TCGA Database

Abstract

Objective To identify key biomarkers for predicting the response to immunotherapy and elucidate the possible underlying mechanism in lung adenocarcinoma based on whole-genome sequencing. Methods Data set of MSKCC (Science 2015) with lung adenocarcinoma from TCGA database were downloaded. According to the duration time of response to immunotherapy, two groups were divided: durable clinical benefit (DCB) group and non-durable clinical benefit (Non-DCB) group. The differences in gene mutation spectrum between the two groups were analyzed. The key genes and underlying biological functions of immunotherapy for lung adenocarcinoma were further analyzed. Results There were differences in gene mutation spectrum between the DCB group and the Non-DCB group. In the DCB group, these key genes were mainly involved in Ca signaling pathway, Rap1 and PI3K-AKT pathways. The top 6 hub genes (KRAS, PPP2CB, CDC20, DYNC1I2, BRCA1 and AKAP9) were screened using the PPI network analysis. CDC20 and BRCA1 were associated with the prognosis of lung adenocarcinoma patients. Conclusion The hub genes involved in the DCB group might be important to guide the classification of immune signature and improve precision immunotherapy for lung adenocarcinoma. In addition, CDC20 and BRCA1 might be potential therapeutic targets for immunotherapy of lung adenocarcinoma.

Keywords

• lung cancer
• immunotherapy
• biomarkers
• tcga
• bioinformatics analysis