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317702

Identification of Ovarian Cancer Using in Silico-Based Analysis of the Downregulated Expressed miRNAs

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Last updated: 03 Jan 2025

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Abstract

               Ovarian cancer (OC) is one of the top global reasons of death among women with high prevalence. Ovarian cancer can be categorized into epithelial, non-epithelial, and metastatic types. Animal models such as mice are intensively utilized to investigate the molecular mechanism controlling cancer development in the human beings. Recently, several approaches have been extremely studied to control ovarian cancer at the transcriptional or post-transcriptional levels using small RNAs molecules including microRNAs. These molecules have played a key role in the growth of malignant tumour of ovary including cellular proliferation and metastasis. We carried out a meta-analysis of previously published miRNA expression datasets (two human datasets GSE83693 and GSE119055) and one mouse GSE98391 to identify the downregulated miRNA and its target genes with biological processes and pathways. Meta-analysis of miRNA datasets showed that miR-378a-3p, miR-378a -5p and miR-378c are commonly downregulated miRNAs among the three databases in cancerous samples in comparison to normal samples. A total of 405 common gene targets for miR-378a-3p, -5p and miR-378c were identified using miRWALK. Enrichment analysis revealed that miRNAs target genes were predominantly linked to protein binding as well as in Ras signalling pathways. In addition, multiple hub miRNA target genes in the PPI network provided poor prognosis for the patients with OC including FLT1, its level was closely relevant to ovarian cancer. Overall, these investigations exhibited that the defined miRNAs and their target genes could be exploited as biomarkers to identify ovarian malignancies and achieve an early effective therapy.

DOI

10.21608/eajbsc.2023.317702

Keywords

ovarian cancer, miRNAs, in silico-based analysis

Authors

First Name

Bushra

Last Name

Mohammed

MiddleName

T.

Affiliation

Department of Pathology and Microbiology, College of Veterinary Medicine, University of Duhok, Iraq

Email

bushrat.mohammed@uod.ac

City

Duhok

Orcid

0000-0002-0621-1103

First Name

Sherzad

Last Name

Mustafa

MiddleName

I.

Affiliation

Department of Pathology and Microbiology, College of Veterinary Medicine, University of Duhok, Iraq

Email

sherzad.mustafa@uod.ac

City

Iraq

Orcid

/0000-0002-7782-875X

First Name

Bayar

Last Name

Zeebaree

MiddleName

K.

Affiliation

Department of Medicine and Surgery, College of Veterinary Medicine, University of Duhok, Iraq

Email

-

City

Iraq

Orcid

-

Volume

15

Article Issue

2

Related Issue

42345

Issue Date

2023-12-01

Receive Date

2023-08-03

Publish Date

2023-09-23

Page Start

309

Page End

323

Print ISSN

2090-0767

Online ISSN

2090-083X

Link

https://eajbsc.journals.ekb.eg/article_317702.html

Detail API

https://eajbsc.journals.ekb.eg/service?article_code=317702

Order

317,702

Type

Original Article

Type Code

673

Publication Type

Journal

Publication Title

Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology

Publication Link

https://eajbsc.journals.ekb.eg/

MainTitle

Identification of Ovarian Cancer Using in Silico-Based Analysis of the Downregulated Expressed miRNAs

Details

Type

Article

Created At

24 Dec 2024