Qingwei Wang1, Weiping Zheng1. 1. Department of Gynecology and Obstetrics, Shaoxing People's Hospital, Shaoxing Hospital, Zhejiang University School of Medicine, Shaoxing, China.
Abstract
BACKGROUND: 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. RESULTS: 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 CDC7 gene was found to be highly expressed. In silico analysis of protein interactions using the STRING database revealed that CDC7 interacts with many proteins. These findings were then validated in vitro with immunohistochemistry and qRt-PCR to confirm that CDC7 is highly expressed in cervical cancer tissues. Cell function tests demonstrated that inhibition of CDC7 expression could inhibit the proliferation and migration of cervical cancer HeLa and SiHa cells and promote apoptosis. CONCLUSION: With comprehensive bioinformatics combined with clinical and cellular function analysis, CDC7 is important to the development of cervical cancer. Targeting of this biomarker may improve the early diagnosis and treatment of cervical cancer.
BACKGROUND: 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. RESULTS: 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 CDC7 gene was found to be highly expressed. In silico analysis of protein interactions using the STRING database revealed that CDC7 interacts with many proteins. These findings were then validated in vitro with immunohistochemistry and qRt-PCR to confirm that CDC7 is highly expressed in cervical cancer tissues. Cell function tests demonstrated that inhibition of CDC7 expression could inhibit the proliferation and migration of cervical cancer HeLa and SiHa cells and promote apoptosis. CONCLUSION: With comprehensive bioinformatics combined with clinical and cellular function analysis, CDC7 is important to the development of cervical cancer. Targeting of this biomarker may improve the early diagnosis and treatment of cervical cancer.
Authors: Nathaniel Melling; Johanna Muth; Ronald Simon; Carsten Bokemeyer; Luigi Terracciano; Guido Sauter; Jakob Robert Izbicki; Andreas Holger Marx Journal: Diagn Pathol Date: 2015-07-25 Impact factor: 2.644
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