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Identification of novel candidate genes and small molecule drugs in ovarian cancer by bioinformatics strategy.

作者信息

Wei Min, Bai Xuefei, Dong Qiaomei

机构信息

Department of Obstetrics and Gynecology, The First Hospital of Lanzhou University, Lanzhou, China.

The First Clinical Medical College of Lanzhou University, Lanzhou, China.

出版信息

Transl Cancer Res. 2022 Jun;11(6):1630-1643. doi: 10.21037/tcr-21-2890.


DOI:10.21037/tcr-21-2890
PMID:35836518
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9273707/
Abstract

BACKGROUND: Ovarian cancer (OC) is the most lethal type of malignancies in the female reproductive system. This study aimed to identify novel biomarkers and potential small molecule drugs in OC by integrating two expression profile datasets. METHODS: GSE18520 and GSE14407 from the Gene Expression Omnibus (GEO) database were selected and the overlapped differentially expressed genes (DEGs) were detected. The Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis were performed to establish the protein-protein interaction (PPI) network of DEGs and identified the hub genes. Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine database and The Human Protein Atlas (HPA) were used to validate the expression of the identified hub genes. The prognostic value of these hub genes were evaluated by the Kaplan Meier plotter online tool. The expression of NCAPG was further explored by immunohistochemistry in our OC tissues. Moreover, CMap database was used to look for prospective small compounds with therapeutic efficacy based on OC RNA-seq. RESULTS: A total of 433 DEGs were identified. The DEGs were mainly enriched in negative regulation of transcription and pathways in cancer. A PPI network was constructed with 344 nodes and 1,596 interactions. The top ten module genes were chosen as hub genes. Among which, survival analysis showed that patients with high expression of and had poorer survival results than those with low expression. These six genes were all overexpressed in OC tissue by means of bioinformatics analysis. In our clinical patients, the expression rate of NCAPG in OC tissues was significantly higher than that in benign serous ovarian cystadenoma and borderline serous ovarian cystadenoma tissues. Meanwhile, several small molecules with potential therapeutic efficacy against OC were identified in our study. CONCLUSIONS: By means of bioinformatics analysis, we identified six real hub genes and indicated a group of candidate small molecule drugs as adjunctive agents for OC. They could be the potential novel biomarkers for the diagnosis and promising therapeutic targets of OC.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/dd88cd900354/tcr-11-06-1630-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/2228dea490fe/tcr-11-06-1630-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/86d69d319912/tcr-11-06-1630-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/7feb6946e478/tcr-11-06-1630-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/6a78f63d0ac9/tcr-11-06-1630-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/531b3539d551/tcr-11-06-1630-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/be864693caac/tcr-11-06-1630-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/3fb1ac9ecce1/tcr-11-06-1630-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/dd88cd900354/tcr-11-06-1630-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/2228dea490fe/tcr-11-06-1630-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/86d69d319912/tcr-11-06-1630-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/7feb6946e478/tcr-11-06-1630-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/6a78f63d0ac9/tcr-11-06-1630-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/531b3539d551/tcr-11-06-1630-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/be864693caac/tcr-11-06-1630-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/3fb1ac9ecce1/tcr-11-06-1630-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/77e9/9273707/dd88cd900354/tcr-11-06-1630-f8.jpg

相似文献

[1]
Identification of novel candidate genes and small molecule drugs in ovarian cancer by bioinformatics strategy.

Transl Cancer Res. 2022-6

[2]
Integrated bioinformatics analysis for the screening of hub genes and therapeutic drugs in ovarian cancer.

J Ovarian Res. 2020-1-27

[3]
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[4]
Prognostic values and prospective pathway signaling of MicroRNA-182 in ovarian cancer: a study based on gene expression omnibus (GEO) and bioinformatics analysis.

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[5]
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Pathol Res Pract. 2019-2-28

[6]
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[7]
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Transl Cancer Res. 2022-5

[8]
Elevated mRNA Expression Levels of NCAPG are Associated with Poor Prognosis in Ovarian Cancer.

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[9]
Prospective pathway signaling and prognostic values of MicroRNA-9 in ovarian cancer based on gene expression omnibus (GEO): a bioinformatics analysis.

J Ovarian Res. 2021-2-9

[10]
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Biochem Biophys Res Commun. 2024-11-12

引用本文的文献

[1]
The role and therapeutic value of NUSAP1 in human cancers.

J Transl Med. 2025-7-2

[2]
Bioinformatics Based Drug Repurposing Approach for Breast and Gynecological Cancers: Genes Address Common Hub Genes and Drugs.

Eur J Breast Health. 2025-1-1

[3]
Proteomic analysis of ascitic extracellular vesicles describes tumour microenvironment and predicts patient survival in ovarian cancer.

J Extracell Vesicles. 2024-3

[4]
cAMP-Dependent Signaling and Ovarian Cancer.

Cells. 2022-11-29

本文引用的文献

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Int J Mol Sci. 2019-2-22

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CA Cancer J Clin. 2019-1-8

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