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Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer
Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Tech Science Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10207953/ https://www.ncbi.nlm.nih.gov/pubmed/37304238 http://dx.doi.org/10.32604/or.2023.028548 |
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author | TANG, QINGLING ATIQ, WARDA MAHNOOR, SHAISTA ABDEL-MAKSOUD, MOSTAFA A. AUFY, MOHAMMED YAZ, HAMID ZHU, JIANYU |
author_facet | TANG, QINGLING ATIQ, WARDA MAHNOOR, SHAISTA ABDEL-MAKSOUD, MOSTAFA A. AUFY, MOHAMMED YAZ, HAMID ZHU, JIANYU |
author_sort | TANG, QINGLING |
collection | PubMed |
description | Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In this study, the differentially expressed genes (DEGs) were identified from an independent GSE69428 Gene Expression Omnibus (GEO) dataset between OC and control samples. The DEGs were processed to construct the protein-protein interaction (PPI) network using STRING. Later, hub genes were identified through Cytohubba analysis of the Cytoscape. Expression and survival profiling of the hub genes were validated using GEPIA, OncoDB, and GENT2. For exploring promoter methylation levels and genetic alterations in hub genes, MEXPRESS and cBioPortal were utilized, respectively. Moreover, DAVID, HPA, TIMER, CancerSEA, ENCORI, DrugBank, and GSCAlite were used for gene enrichment analysis, subcellular localization analysis, immune cell infiltration analysis, exploring correlations between hub genes and different diverse states, lncRNA-miRNA-mRNA co-regulatory network analysis, predicting hub gene-associated drugs, and conducting drug sensitivity analysis, respectively. In total, 8947 DEGs were found between OC and normal samples in GSE69428. After STRING and Cytohubba analysis, 4 hub genes including TTK (TTK Protein Kinase), (BUB1 mitotic checkpoint serine/threonine kinase B) BUB1B, (Nucleolar and spindle-associated protein 1) NUSAP1, and (ZW10 interacting kinetochore protein) ZWINT were selected as the hub genes. Further, it was validated that these 4 hub genes were significantly up-regulated in OC samples compared to normal controls, but overexpression of these genes was not associated with overall survival (OS). However, genetic alterations in those genes were found to be linked with OS and disease-free (DFS) survival. Moreover, this study also revealed some novel links between TTK, BUB1B, NUSAP1, and ZWINT overexpression and promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. Four hub genes, including TTK, BUB1B, NUSAP1, and ZWINT, were revealed as tumor-promotive factors in OC, having the potential to be utilized as novel biomarkers and therapeutic targets for OC management. |
format | Online Article Text |
id | pubmed-10207953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Tech Science Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-102079532023-06-10 Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer TANG, QINGLING ATIQ, WARDA MAHNOOR, SHAISTA ABDEL-MAKSOUD, MOSTAFA A. AUFY, MOHAMMED YAZ, HAMID ZHU, JIANYU Oncol Res Article Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In this study, the differentially expressed genes (DEGs) were identified from an independent GSE69428 Gene Expression Omnibus (GEO) dataset between OC and control samples. The DEGs were processed to construct the protein-protein interaction (PPI) network using STRING. Later, hub genes were identified through Cytohubba analysis of the Cytoscape. Expression and survival profiling of the hub genes were validated using GEPIA, OncoDB, and GENT2. For exploring promoter methylation levels and genetic alterations in hub genes, MEXPRESS and cBioPortal were utilized, respectively. Moreover, DAVID, HPA, TIMER, CancerSEA, ENCORI, DrugBank, and GSCAlite were used for gene enrichment analysis, subcellular localization analysis, immune cell infiltration analysis, exploring correlations between hub genes and different diverse states, lncRNA-miRNA-mRNA co-regulatory network analysis, predicting hub gene-associated drugs, and conducting drug sensitivity analysis, respectively. In total, 8947 DEGs were found between OC and normal samples in GSE69428. After STRING and Cytohubba analysis, 4 hub genes including TTK (TTK Protein Kinase), (BUB1 mitotic checkpoint serine/threonine kinase B) BUB1B, (Nucleolar and spindle-associated protein 1) NUSAP1, and (ZW10 interacting kinetochore protein) ZWINT were selected as the hub genes. Further, it was validated that these 4 hub genes were significantly up-regulated in OC samples compared to normal controls, but overexpression of these genes was not associated with overall survival (OS). However, genetic alterations in those genes were found to be linked with OS and disease-free (DFS) survival. Moreover, this study also revealed some novel links between TTK, BUB1B, NUSAP1, and ZWINT overexpression and promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. Four hub genes, including TTK, BUB1B, NUSAP1, and ZWINT, were revealed as tumor-promotive factors in OC, having the potential to be utilized as novel biomarkers and therapeutic targets for OC management. Tech Science Press 2023-04-10 /pmc/articles/PMC10207953/ /pubmed/37304238 http://dx.doi.org/10.32604/or.2023.028548 Text en © 2023 Tang et al. https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Article TANG, QINGLING ATIQ, WARDA MAHNOOR, SHAISTA ABDEL-MAKSOUD, MOSTAFA A. AUFY, MOHAMMED YAZ, HAMID ZHU, JIANYU Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer |
title | Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer |
title_full | Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer |
title_fullStr | Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer |
title_full_unstemmed | Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer |
title_short | Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer |
title_sort | comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10207953/ https://www.ncbi.nlm.nih.gov/pubmed/37304238 http://dx.doi.org/10.32604/or.2023.028548 |
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