Chaudhary Raushan Kumar, Khanal Pukar, Mateti Uday Venkat, Shastry C S, Shetty Jayarama
Department of Pharmacy Practice, NGSM Institute of Pharmaceutical Sciences (NGSMIPS), Nitte (Deemed to be University), Deralakatte, Mangaluru, Karnataka, 575018, India.
Department of Pharmacology, NGSM Institute of Pharmaceutical Sciences (NGSMIPS), Nitte (Deemed to be University), Deralakatte, Mangaluru, Karnataka, 575018, India.
J Genet Eng Biotechnol. 2023 Jan 30;21(1):9. doi: 10.1186/s43141-023-00468-y.
Cisplatin resistance is one of the major contributors to the poor survival rate among head and neck cancer (HNC) patients. Focusing on the protein-protein interaction rather than a single protein could provide a better understanding of drug resistance. Thus, this study aimed to identify hub genes in a complex network of cisplatin resistance associated genes in HNC chemotherapy via a series of bioinformatic tools.
The genes involved in cisplatin resistance were retrieved from the NCBI gene database using "head and neck cancer" and "cisplatin resistance" as key words. The human genes retrieved were analyzed for their interactions and enriched using the STRING database. The interaction between KEGG pathways and genes was visualized in Cytoscape 3.7.2. Further, the hub gene was identified using the Cytohubba plugin of Cytoscape and validated using UALCAN and Human Protein Atlas database. Validated genes were investigated for the drug-gene interaction using the DGIbd database.
Out of 137 genes obtained using key words, 133 were associated with cisplatin resistance in the human species. A total of 150 KEGG pathways, 82 cellular components, 123 molecular functions, and 1752 biological processes were modulated on enrichment analysis. Out of 37 hub genes, CCND1, AXL, CDKN2A, TERT, and EXH2 genes were found to have significant (p < 0.05) mRNA expression and effect on overall survival whereas protein expression was found to be positive for all the significant genes except TERT. Thus, they can be targeted with palbociclib, methotrexate, bortezomib and fluorouracil, sorafenib, dasatinib, carboplatin, paclitaxel, gemcitabine, imatinib, doxorubicin, and vorinostat.
As the pathogenesis of head and neck cancer is complex, targeting hub genes and associated pathways involved in cisplatin resistance could bring a milestone change in the drug discovery and management of drug resistance which might uplift overall survival among HNC patients.
顺铂耐药是导致头颈癌（HNC）患者生存率低下的主要因素之一。关注蛋白质-蛋白质相互作用而非单一蛋白质，可能会更好地理解耐药性。因此，本研究旨在通过一系列生物信息学工具，在HNC化疗中顺铂耐药相关基因的复杂网络中鉴定核心基因。
以“头颈癌”和“顺铂耐药”作为关键词，从NCBI基因数据库中检索参与顺铂耐药的基因。使用STRING数据库对检索到的人类基因进行相互作用分析和富集分析。在Cytoscape 3.7.2中可视化KEGG通路与基因之间的相互作用。此外，使用Cytoscape的Cytohubba插件鉴定核心基因，并使用UALCAN和人类蛋白质图谱数据库进行验证。使用DGIbd数据库研究验证基因的药物-基因相互作用。
在使用关键词获得的137个基因中，有133个与人类顺铂耐药相关。富集分析共调节了150条KEGG通路、82个细胞成分、123个分子功能和1752个生物学过程。在37个核心基因中，发现CCND1、AXL、CDKN2A、TERT和EXH2基因具有显著（p < 0.05）的mRNA表达并对总生存期有影响，而除TERT外，所有显著基因的蛋白质表达均为阳性。因此，它们可以用帕博西尼、甲氨蝶呤、硼替佐米和氟尿嘧啶、索拉非尼、达沙替尼、卡铂、紫杉醇、吉西他滨、伊马替尼、多柔比星和伏立诺他作为靶点。
由于头颈癌的发病机制复杂，靶向参与顺铂耐药的核心基因和相关通路可能会在药物发现和耐药性管理方面带来里程碑式的变化，这可能会提高HNC患者的总体生存率。
