CKS2 and RMI2 are two prognostic biomarkers of lung adenocarcinoma

Abstract

Background Lung adenocarcinoma (ACA) is the most common subtype of non-small-cell lung cancer. About 70%–80% patients are diagnosed at an advanced stage; therefore, the survival rate is poor. It is urgent to discover accurate markers that can differentiate the late stages of lung ACA from the early stages. With the development of biochips, researchers are able to efficiently screen large amounts of biological analytes for multiple purposes. Methods Our team downloaded GSE75037 and GSE32863 from the Gene Expression Omnibus (GEO) database. Next, we utilized GEO’s online tool, GEO2R, to analyze the differentially expressed genes (DEGs) between stage I and stage II–IV lung ACA. The using the Cytoscape software was used to analyze the DEGs and the protein-protein interaction (PPI) network was further constructed. The function of the DEGs were further analyzed by cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) online tools. We validated these results in 72 pairs human samples. Results We identified 109 co-DEGs, most of which were involved in either proliferation, S phase of mitotic cell cycle, regulation of exit from mitosis, DNA replication initiation, DNA replication, and chromosome segregation. Utilizing cBioPortal and University of California Santa Cruz databases, we further confirmed 35 hub genes. Two of these genes, encoding CDC28 protein kinase regulatory subunit 2 (CKS2) and RecQ-mediated genome instability 2 (RMI2), were upregulated in lung ACA compared with adjacent normal tissues. The Kaplan–Meier curves revealed upregulation of CKS2 and RMI2 are associated with worse survival. Using CMap analysis, we discovered 10 small molecular compounds that reversed the altered DEGs, the top five are phenoxybenzamine, adiphenine, resveratrol, and trifluoperazine. We also evaluated 72 pairs resected samples, results revealed that upregulation of CKS2 and RMI2 in lung ACA were associated with larger tumor size. Our results allow the deeper recognizing of the mechanisms of the progression of lung ACA, and may indicate potential therapeutic strategies for the therapy of lung ACA.