Department of Obstetrics & Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Shenyang, China.
Cancer Biother Radiopharm. 2022 Sep;37(7):569-579. doi: 10.1089/cbr.2020.4249. Epub 2021 Mar 31.
As one of the three malignant genital tumors, mortality in women with ovarian cancer is consistently high worldwide. It is of great importance to find prognostic markers for diagnosis and treatment of ovarian cancer. In this study, the authors utilized the bioinformatics analysis to identify the potential key genes to reveal the potential mechanism for ovarian cancer. The authors used the gene expression profile (GSE14407) to perform differentially expressed gene (DEG) analysis and the weighted gene co-expression network analysis. They selected the key module and performed the gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for the genes in the hub module. Then they screened the key genes in the hub module, and further validated their expression level. A total of 3124 DEGs were detected after differential gene expression analysis; of these, 433 were upregulated genes and 2691 were downregulated genes. The authors selected the brown module that is significantly associated with the gene expression. Then they selected 30 hub genes from the protein-protein interaction network. The authors identified the PDZ binding kinase () as the prognosis-associated hub gene whose expression was significantly high in the ovarian cancer tissue. The bioinformatics analysis for the DEGs could be important to understand the pathogenesis for ovarian cancer. In this study, is identified as a potential marker that might improve the understanding of the molecular mechanism and the diagnosis level for ovarian cancer.
作为三大恶性生殖系统肿瘤之一，全球范围内卵巢癌患者的死亡率一直居高不下。寻找用于卵巢癌诊断和治疗的预后标志物非常重要。在本研究中，作者利用生物信息学分析来识别潜在的关键基因，以揭示卵巢癌的潜在机制。
作者使用基因表达谱（GSE14407）进行差异表达基因（DEG）分析和加权基因共表达网络分析。他们选择关键模块，并对枢纽模块中的基因进行基因本体（GO）注释和京都基因与基因组百科全书（KEGG）通路富集分析。然后，他们筛选了枢纽模块中的关键基因，并进一步验证了其表达水平。
通过差异基因表达分析共检测到 3124 个 DEG；其中，上调基因 433 个，下调基因 2691 个。作者选择与基因表达显著相关的棕色模块。然后，他们从蛋白质-蛋白质相互作用网络中选择了 30 个枢纽基因。作者鉴定出 PDZ 结合激酶（）作为与卵巢癌组织中表达显著升高相关的预后相关枢纽基因。
对 DEG 的生物信息学分析对于理解卵巢癌的发病机制可能很重要。在本研究中，确定为一种潜在的标志物，可能有助于提高对卵巢癌分子机制和诊断水平的认识。
