Identification of Prognostic Signature and Gliclazide as Candidate Drugs in Lung Adenocarcinoma

Yang Cheng; Kezuo Hou; Yizhe Wang; Yang Chen; Xueying Zheng; Jianfei Qi; Bowen Yang; Shiying Tang; Xu Han; Dongyao Shi; Ximing Wang; Yunpeng Liu; Xuejun Hu; Xiaofang Che

doi:10.3389/fonc.2021.665276

Identification of Prognostic Signature and Gliclazide as Candidate Drugs in Lung Adenocarcinoma

Front Oncol. 2021 Jun 24:11:665276. doi: 10.3389/fonc.2021.665276. eCollection 2021.

Authors

Yang Cheng¹, Kezuo Hou^{2

3

4}, Yizhe Wang¹, Yang Chen¹, Xueying Zheng^{2

3

4}, Jianfei Qi⁵, Bowen Yang^{2

3

4}, Shiying Tang^{2

3

4}, Xu Han^{2

3

4}, Dongyao Shi¹, Ximing Wang¹, Yunpeng Liu^{2

3

4}, Xuejun Hu¹, Xiaofang Che^{2

3

4}

Affiliations

¹ Department of Respiratory and Infectious Disease of Geriatrics, The First Hospital of China Medical University, Shenyang, China.
² Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, China.
³ Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, China.
⁴ Liaoning Province Clinical Research Center for Cancer, The First Hospital of China Medical University, Shenyang, China.
⁵ Marlene and Stewart Greenebaum Comprehensive Cancer Center, University of Maryland, Baltimore, MD, United States.

Abstract

Background: Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, with high incidence and mortality. To improve the curative effect and prolong the survival of patients, it is necessary to find new biomarkers to accurately predict the prognosis of patients and explore new strategy to treat high-risk LUAD.

Methods: A comprehensive genome-wide profiling analysis was conducted using a retrospective pool of LUAD patient data from the previous datasets of Gene Expression Omnibus (GEO) including GSE18842, GSE19188, GSE40791 and GSE50081 and The Cancer Genome Atlas (TCGA). Differential gene analysis and Cox proportional hazard model were used to identify differentially expressed genes with survival significance as candidate prognostic genes. The Kaplan-Meier with log-rank test was used to assess survival difference. A risk score model was developed and validated using TCGA-LUAD and GSE50081. Additionally, The Connectivity Map (CMAP) was used to predict drugs for the treatment of LUAD. The anti-cancer effect and mechanism of its candidate drugs were studied in LUAD cell lines.

Results: We identified a 5-gene signature (KIF20A, KLF4, KRT6A, LIFR and RGS13). Risk Score (RS) based on 5-gene signature was significantly associated with overall survival (OS). Nomogram combining RS with clinical pathology parameters could potently predict the prognosis of patients with LUAD. Moreover, gliclazide was identified as a candidate drug for the treatment of high-RS LUAD. Finally, gliclazide was shown to induce cell cycle arrest and apoptosis in LUAD cells possibly by targeting CCNB1, CCNB2, CDK1 and AURKA.

Conclusion: This study identified a 5-gene signature that can predict the prognosis of patients with LUAD, and Gliclazide as a potential therapeutic drug for LUAD. It provides a new direction for the prognosis and treatment of patients with LUAD.

Keywords: drug repositioning; gliclazide; lung adenocarcinoma; prognosis; signature.