Xiao Dayong, Dong Siyuan, Yang Shize, Liu Zhenghua
Department of Thoracic Surgery, The People's Hospital of Wanning, Wanning, Hainan, China.
Department of Thoracic Surgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.
PeerJ. 2020 Oct 7;8:e10126. doi: 10.7717/peerj.10126. eCollection 2020.
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.
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.
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.
肺腺癌（ACA）是非小细胞肺癌最常见的亚型。约70%-80%的患者在晚期被诊断出来，因此生存率较低。迫切需要发现能够区分肺ACA晚期和早期的准确标志物。随着生物芯片的发展，研究人员能够高效地筛选大量生物分析物以用于多种目的。
我们的团队从基因表达综合数据库（GEO）下载了GSE75037和GSE32863。接下来，我们利用GEO的在线工具GEO2R分析I期和II-IV期肺ACA之间的差异表达基因（DEG）。使用Cytoscape软件分析DEG并进一步构建蛋白质-蛋白质相互作用（PPI）网络。通过cBioPortal和基因表达谱交互分析（GEPIA）在线工具进一步分析DEG的功能。我们在72对人类样本中验证了这些结果。
我们鉴定出109个共DEG，其中大多数参与增殖、有丝分裂细胞周期的S期、有丝分裂退出的调节、DNA复制起始、DNA复制和染色体分离。利用cBioPortal和加利福尼亚大学圣克鲁兹分校数据库，我们进一步确认了35个核心基因。与相邻正常组织相比，其中两个基因，即编码细胞周期蛋白依赖性激酶28调节亚基2（CKS2）和RecQ介导的基因组不稳定性2（RMI2）的基因在肺ACA中上调。Kaplan-Meier曲线显示CKS2和RMI2的上调与较差的生存率相关。使用CMap分析，我们发现了10种可逆转DEG改变的小分子化合物，排名前五的是酚苄明、阿地芬宁、白藜芦醇和三氟拉嗪。我们还评估了72对切除样本，结果显示肺ACA中CKS2和RMI2的上调与更大的肿瘤大小相关。我们的结果有助于更深入地认识肺ACA进展的机制，并可能为肺ACA的治疗指明潜在的治疗策略。
