Open Access

ARTICLE

Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer

QINGLING TANG¹, WARDA ATIQ², SHAISTA MAHNOOR², MOSTAFA A. ABDEL-MAKSOUD³, MOHAMMED AUFY⁴, HAMID YAZ^3,*, JIANYU ZHU^5,*

1Department of Gynecology and Obstetrics, Shanghai Songjiang District Jiuting Hospital, Shanghai, 20000, China
2 Department of Medicine, Fatima Jinnah Medical University, Lahore, 42000, Pakistan
3 Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia
4 Department of Pharmaceutical Sciences, Division of Pharmacology and Toxicology, University of Vienna, Vienna, 1010, Austria
5 Department of Trauma Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China

* Corresponding Authors: HAMID YAZ. Email: ; JIANYU ZHU. Email:

Oncology Research 2023, 31(2), 141-156. https://doi.org/10.32604/or.2023.028548

Received 24 December 2022; Accepted 02 February 2023; Issue published 10 April 2023

Abstract

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.

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Keywords

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