Department of Gynecology and Obstetrics, Shaoxing People's Hospital, Shaoxing Hospital, Zhejiang University School of Medicine, Shaoxing, China.
Biomed Res Int. 2021 Mar 3;2021:6663367. doi: 10.1155/2021/6663367. eCollection 2021.
Cervical cancer is a common malignant tumor of women. Using integrated bioinformatics, this study identified key disease-causing genes in cervical cancer that may provide effective biomarkers or therapeutic targets for early diagnosis and treatment.
We used high-throughput sequencing data from the Gene Expression Omnibus (GEO) to identify new cervical cancer biomarkers. The GSE63678 dataset was downloaded. The data was analyzed via bioinformatics methods, and 61 differentially expressed genes were obtained. These differential genes were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments analyses. GO analysis demonstrated that the basic biological functions of differential genes were mostly regulating cell division, mitotic nuclear division, and immune response. Analysis of the KEGG pathway showed the primary involved in the cell cycle, p53 signaling pathway, and cytokine-cytokine receptor interactions. Using TCGA database to query differential expression of differential genes in cervical cancer, the gene was found to be highly expressed. analysis of protein interactions using the STRING database revealed that interacts with many proteins. These findings were then validated with immunohistochemistry and qRt-PCR to confirm that is highly expressed in cervical cancer tissues. Cell function tests demonstrated that inhibition of expression could inhibit the proliferation and migration of cervical cancer HeLa and SiHa cells and promote apoptosis.
With comprehensive bioinformatics combined with clinical and cellular function analysis, is important to the development of cervical cancer. Targeting of this biomarker may improve the early diagnosis and treatment of cervical cancer.
宫颈癌是女性常见的恶性肿瘤之一。本研究通过整合生物信息学方法，鉴定了宫颈癌的关键致病基因，这些基因可能为宫颈癌的早期诊断和治疗提供有效的生物标志物或治疗靶点。
我们使用来自基因表达综合数据库（GEO）的高通量测序数据来鉴定新的宫颈癌生物标志物。下载 GSE63678 数据集。通过生物信息学方法进行数据分析，获得 61 个差异表达基因。对这些差异基因进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路富集分析。GO 分析表明，差异基因的基本生物学功能主要是调节细胞分裂、有丝分裂核分裂和免疫反应。KEGG 通路分析表明，这些差异基因主要参与细胞周期、p53 信号通路和细胞因子-细胞因子受体相互作用。使用 TCGA 数据库查询宫颈癌中差异基因的差异表达，发现 基因高表达。使用 STRING 数据库进行蛋白质相互作用分析表明， 与许多蛋白质相互作用。然后通过免疫组织化学和 qRt-PCR 进行验证，证实 在宫颈癌组织中高表达。细胞功能试验表明，抑制 表达可抑制宫颈癌 HeLa 和 SiHa 细胞的增殖和迁移，促进细胞凋亡。
通过综合生物信息学结合临床和细胞功能分析， 对宫颈癌的发展至关重要。针对该生物标志物可能提高宫颈癌的早期诊断和治疗效果。
