Ayna Duran Gizem
Department of Biomedical Engineering, Faculty of Engineering, İzmir University of Economics, İzmir, Turkey.
Eur J Breast Health. 2025 Jan 1;21(1):63-73. doi: 10.4274/ejbh.galenos.2024.2024-11-2.
The prevalence of breast cancer and gynaecological cancers is high, and these cancer types can occur consecutively as secondary cancers. The aim of our study is to determine the genes commonly expressed in these cancers and to identify the common hub genes and drug components.
Gene intensity values of breast cancer, gynaecological cancers such as cervical, ovarian and endometrial cancers were used from the Gene Expression Omnibus database Affymetrix Human Genome U133 Plus 2.0 Array project. Using the linear modelling method included in the R LIMMA package, genes that differ between healthy individuals and cancer patients were identified. Hub genes were determined using cytoHubba in Cytoscape program. "ShinyGo 0.80" tool was used to determine the disease-specific biological KEGG pathways. Drug.MATADOR from the ShinyGo 0.80 tool was used to predict drug-target relationships.
The RecQ Like Helicase 4 and genes were found to be similarly expressed in breast cancer and gynaecological cancers. Upon KEGG pathway analyses with hub genes, Drug.MATADOR analysis with hub genes related to cancer related pathways was performed. We have determined these gene/drug interactions: NBN (targeted by Hydroxyurea), EP300 (targeted by Acetylcarnitine) and MAPK14 (targeted by Salicylate and Dibutyryl cyclic AMP).
The drugs associated with hub genes determined in our study are not routinely used in cancer treatment. Our study offers the opportunity to identify the target genes of drugs used in breast and gynaecological cancers with the drug repurposing approach.
乳腺癌和妇科癌症的患病率很高,并且这些癌症类型可作为继发性癌症连续发生。我们研究的目的是确定这些癌症中共同表达的基因,并识别共同的枢纽基因和药物成分。
使用基因表达综合数据库Affymetrix人类基因组U133 Plus 2.0阵列项目中乳腺癌、妇科癌症(如宫颈癌、卵巢癌和子宫内膜癌)的基因强度值。使用R LIMMA软件包中包含的线性建模方法,确定健康个体和癌症患者之间存在差异的基因。使用Cytoscape程序中的cytoHubba确定枢纽基因。使用“ShinyGo 0.80”工具确定疾病特异性的生物KEGG通路。使用ShinyGo 0.80工具中的Drug.MATADOR预测药物-靶点关系。
发现类RecQ解旋酶4基因在乳腺癌和妇科癌症中表达相似。在用枢纽基因进行KEGG通路分析后,对与癌症相关通路相关的枢纽基因进行了Drug.MATADOR分析。我们确定了这些基因/药物相互作用:NBN(由羟基脲靶向)、EP300(由乙酰肉碱靶向)和MAPK14(由水杨酸盐和二丁酰环磷腺苷靶向)。
我们研究中确定的与枢纽基因相关的药物在癌症治疗中并非常规使用。我们的研究提供了一个机会,通过药物重新利用方法来识别用于乳腺癌和妇科癌症治疗的药物的靶基因。