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pmid:33402836

Bioinformatics Analysis of Key Genes and Pathways of Cervical Cancer.

Huan Chen · Xi Wang · Huanhuan Jia · Yin Tao · Hong Zhou · Mingyuan Wang · Xin Wang · Xiaoling Fang

OncoTargets and therapy · 2020 doi:10.2147/OTT.S281533

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:33402836
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science-record
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2026-11-01T15:41:21Z
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2026-11-01T21:24:27Z
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paper object · 10 fields
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title
Bioinformatics Analysis of Key Genes and Pathways of Cervical Cancer.
doi
10.2147/OTT.S281533
pmid
33402836
authors array · 8 items
[0]
Huan Chen
[1]
Xi Wang
[2]
Huanhuan Jia
[3]
Yin Tao
[4]
Hong Zhou
[5]
Mingyuan Wang
[6]
Xin Wang
[7]
Xiaoling Fang
journal
OncoTargets and therapy
year
2020
abstract
BACKGROUND AND OBJECTIVE: Globally, cervical cancer (CC) is the fourth most common cancer affecting women. Although effective screening reduces its incidence, it remains one of the most serious cancers threatening the health of women. Therefore, the purpose of this study is to find new genes that can be used as potential biomarkers for the prognosis of CC. METHODS AND RESULTS: After downloading three datasets such as GSE6791, GSE63678, and GSE63514 from the Gene Expression Omnibus (GEO), we combined the expression matrixes and analyzed them to obtain the differential expressed genes (DEGs). Next, using the STRING website, we performed the protein interaction network analysis. Subsequently, hub genes were screened using the R and Cytoscape software. Then, the expression difference and survival analyses of the hub genes were confirmed using GIPIA. Here, we established that the KNTC1 gene was correlated to the overall survival prognosis of CC. Besides, the expression of the KNTC1 gene in the GSE63514 dataset was significantly different from that of the normal cervix, cervical pre-cancerous lesions, and CC. Consequently, immunohistochemistry analysis showed that the results have a definite diagnostic value. CONCLUSION: The KNTC1 gene could be linked with the pathophysiology of CC and maybe one of the early diagnostic markers for the diagnosis of cervical pre-cancerous lesions.
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Next, we compared the expression profiles of normal, LSIL (CIN I), HSIL (CIN II, III), and CC samples using the Wilcox test.
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sections[15] "Validation of Hub Genes" paragraph 2
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Next, we compared the expression profiles of normal, LSIL (CIN I), HSIL (CIN II, III), and CC samples using the Wilcox test.
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Here, we downloaded and analyzed three already established microarray datasets such as19 GSE6791,20 GSE63678,21 GSE63514 from the GEO database.
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sections[1] "Introduction" paragraph 4
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Here, we downloaded and analyzed three already established microarray datasets such as19 GSE6791,20 GSE63678,21 GSE63514 from the GEO database.
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Here, we downloaded and analyzed three already established microarray datasets such as19 GSE6791,20 GSE63678,21 GSE63514 from the GEO database.
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Gene expression analysis of cervical cancer progression
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Here, we downloaded and analyzed three already established microarray datasets such as19 GSE6791,20 GSE63678,21 GSE63514 from the GEO database.
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Expression data from Vulvar, Cervical, Endometrial Carcinoma tissue
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Here, we downloaded and analyzed three already established microarray datasets such as19 GSE6791,20 GSE63678,21 GSE63514 from the GEO database.
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title
Gene Expression Profiles of HPV-Positive and -Negative Head/Neck and Cervical Cancers
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Next, we compared the expression profiles of normal, LSIL (CIN I), HSIL (CIN II, III), and CC samples using the Wilcox test.
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Here, we downloaded and analyzed three already established microarray datasets such as19 GSE6791,20 GSE63678,21 GSE63514 from the GEO database.
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pre-cancerous lesions, and CC. Consequently, immunohistochemistry analysis showed that the results have a defi
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Complete file
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Therefore, the purpose of this study is to find new genes that can be used as potential biomarkers for the prognosis of CC.\nMETHODS AND RESULTS: After downloading three datasets such as GSE6791, GSE63678, and GSE63514 from the Gene Expression Omnibus (GEO), we combined the expression matrixes and analyzed them to obtain the differential expressed genes (DEGs). Next, using the STRING website, we performed the protein interaction network analysis. Subsequently, hub genes were screened using the R and Cytoscape software. Then, the expression difference and survival analyses of the hub genes were confirmed using GIPIA. Here, we established that the KNTC1 gene was correlated to the overall survival prognosis of CC. Besides, the expression of the KNTC1 gene in the GSE63514 dataset was significantly different from that of the normal cervix, cervical pre-cancerous lesions, and CC. 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