Eswaran Sangavi, Padavu Mythili, Kumar Dileep, Kabekkodu Shama Prasada
Department of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India.
Poona College of Pharmacy, Bharati Vidyapeeth (Deemed to be) University, Pune, Maharashtra, 411038, India.
Curr Pharm Des. 2023;29(25):2018-2032. doi: 10.2174/1381612829666230816100623.
Critical issues in the therapeutic management of cervical cancer (CC) include therapy resistance and treatment failure. The development of therapy resistance is a multifaceted, progressive process, including genetic and epigenetic abnormalities. The present study aimed to identify genes that may contribute to therapy resistance in CC.
We have created an extensive list of the genes in cancer that are therapy-resistant using a text-mining approach. The list was compared with the TCGA-CESC dataset to identify the differentially expressed therapy resistance genes (DETRGs) in CC. We used online resources (UALCAN, DNMIVD, cBio- Portal, HCMDB, OncoDB, ShinyGO, HPA, KM Plotter, TIMER, and DGIdb) to determine the potential association between methylation and expression of therapy resistance genes with the prognosis and clinical outcomes in CC.
The systematic analysis identified 71 out of 91 DETRGs showed aberrant DNA methylation. The overlapping analysis identified 25 genes to show an inverse correlation between methylation and expression. Further, differential expression or methylation could be helpful in CC staging, HPV association, prediction of metastasis and prognosis. The study identified seven driver genes in CC. The PPIN identifies ten hub genes (HGs) associated with CC staging, cancer hallmarks, and prognosis to affect long-term survival.
Our thorough investigation uncovered several novel genes and pathways that might contribute to therapy resistance in CC. The genes identified in our study may serve as a biomarker, prognostic indicator, and therapeutic target in CC.
宫颈癌（CC）治疗管理中的关键问题包括治疗耐药性和治疗失败。治疗耐药性的发展是一个多方面的渐进过程，包括遗传和表观遗传异常。本研究旨在确定可能导致CC治疗耐药性的基因。
我们使用文本挖掘方法创建了一份癌症中具有治疗耐药性的基因的详尽列表。将该列表与TCGA-CESC数据集进行比较，以识别CC中差异表达的治疗耐药基因（DETRG）。我们使用在线资源（UALCAN、DNMIVD、cBio-Portal、HCMDB、OncoDB、ShinyGO、HPA、KM Plotter、TIMER和DGIdb）来确定治疗耐药基因的甲基化与表达之间与CC预后和临床结果的潜在关联。
系统分析确定91个DETRG中有71个显示出异常的DNA甲基化。重叠分析确定25个基因在甲基化与表达之间呈负相关。此外，差异表达或甲基化可能有助于CC分期、HPV关联、转移预测和预后。该研究确定了CC中的七个驱动基因。蛋白质-蛋白质相互作用网络（PPIN）确定了十个与CC分期、癌症特征和预后相关的枢纽基因（HG），以影响长期生存。
我们的深入研究发现了几个可能导致CC治疗耐药性的新基因和途径。我们研究中确定的基因可能作为CC的生物标志物、预后指标和治疗靶点。
