Ma Jilei, Cai Xin, Kang Li, Chen Songfeng, Liu Hongjian
Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Department of Biotechnology and Food Engineering, Anyang Institute of Technology, Anyang, Henan 455000, PR China.
J Cancer. 2021 Jan 1;12(5):1307-1317. doi: 10.7150/jca.49702. eCollection 2021.
Melanoma is a pernicious skin cancer with high aggressiveness. This study aimed to identify potential novel biomarkers associated with the prognosis and pathogenesis of cutaneous melanoma and to explore new targeted drugs for melanoma. Two Gene Expression Omnibus (GEO) microarray datasets, GSE3189 and GSE7553 were combined to analyze the differentially expressed genes (DEGs). To better understand the DEGs in the melanoma pathogenesis, we performed gene enrichment analyses and established a protein-protein interaction network (PPI). The survival analyses for key genes were conducted based on the GEPIA platform. Finally, we mined the CMap database to explore potential small-molecule drugs to target the obtained DEGs. In short, we identified 500 DEGs between cutaneous melanoma samples and normal samples. The PPI network was established with 349 nodes and 1251 edges. Signaling pathway analysis showed that these genes play a vital role in ECM-receptor interactions, the PPAR signaling pathway and pathways in cancer. Eight DEGs with a relatively high degree of connectivity (CDC45, CENPF, DTL, FANCI, GINS2, HJURP, TPX2 and TRIP13) were selected as hub-genes that remarkably correlated to a poor survival rate. Based on 500 DEGs, 20 small-molecule drugs that potentially target genes with abnormal expression in cutaneous melanoma were obtained from the CMap database. Among these compounds, we found that menadione has the greatest therapeutic value for melanoma. : In conclusion, we identified the 8 candidate biomarkers and potential key signaling pathways in cutaneous melanoma through comprehensive microarray analyses. The identified candidate drugs have provided several directive significances for the synthesis medicine for melanoma.
黑色素瘤是一种具有高侵袭性的恶性皮肤癌。本研究旨在识别与皮肤黑色素瘤的预后和发病机制相关的潜在新型生物标志物,并探索黑色素瘤的新靶向药物。将两个基因表达综合数据库(GEO)微阵列数据集GSE3189和GSE7553合并,以分析差异表达基因(DEG)。为了更好地理解黑色素瘤发病机制中的DEG,我们进行了基因富集分析并建立了蛋白质-蛋白质相互作用网络(PPI)。基于GEPIA平台对关键基因进行生存分析。最后,我们挖掘了CMap数据库,以探索靶向所获得DEG的潜在小分子药物。简而言之,我们在皮肤黑色素瘤样本和正常样本之间识别出500个DEG。建立了具有349个节点和1251条边的PPI网络。信号通路分析表明,这些基因在细胞外基质-受体相互作用、过氧化物酶体增殖物激活受体(PPAR)信号通路和癌症相关通路中起着至关重要的作用。选择8个具有相对较高连接度的DEG(细胞分裂周期蛋白45(CDC45)、着丝粒蛋白F(CENPF)、DNA复制许可因子(DTL)、范可尼贫血互补组I(FANCI)、GINS复合体亚基2(GINS2)、组蛋白结合蛋白HJURP(HJURP)、微管蛋白聚合促进蛋白2(TPX2)和有丝分裂后期促进复合物亚基13(TRIP13))作为与低生存率显著相关的枢纽基因。基于500个DEG,从CMap数据库中获得了20种可能靶向皮肤黑色素瘤中异常表达基因的小分子药物。在这些化合物中,我们发现甲萘醌对黑色素瘤具有最大的治疗价值。总之,我们通过全面的微阵列分析,识别出皮肤黑色素瘤中的8个候选生物标志物和潜在的关键信号通路。所识别出的候选药物为黑色素瘤的合成药物提供了若干指导意义。