Title
Common miRNAs, candidate genes and their interaction network across four subtypes of epithelial ovarian cancer
Authors
Rinki Singh & Anup Som*
Affiliation
Centre of Bioinformatics, Institute of Interdisciplinary Studies, University of Allahabad, Prayagraj – 211002, India
Rinki Singh – Email: au.rinki.bio@gmail.com; Anup Som – E-mail: som.anup@gmail.com; *Corresponding author
Article Type
Research Article
Date
Received June 20, 2021; Revised August 30, 2021; Accepted August 30, 2021, Published August 31, 2021
Abstract
Epithelial ovarian cancer (EOC) is
categorized into four major histological subtypes such as clear cell
carcinoma (CCC), endometrioid carcinoma (EC), mucinous carcinoma
(MC), and serous carcinoma (SC). Heterogeneity of the EOC leads to
different clinical outcomes of the disease, although all the
subtypes are originated from the same layer of tissue. Therefore, it
is of interest to identify the common candidate genes, miRNA and
their interaction network in four the subtypes of EOC. A comparative
gene expression analysis identified 248 common differentially
expressed genes (DEGs) in the four subtypes of EOC. Identified
common DEGs were found to be enriched in cancer specific pathways. A
protein-protein interaction (PPI) network of the common DEGs were
constructed, and subsequent module and survival analyses identified
seven key candidate genes (CCNB1, CENPM, CEP55, RACGAP1, TPX2,
UBE2C, and ZWINT). We also documented 10 key candidate miRNAs
(hsa-mir-16-5p, hsa-mir-23b-3p, hsa-mir-34a-5p, hsa-mir-103a-3p,
hsa-mir-107, hsamir-
124-3p, hsa-mir-129-2-3p, hsa-mir-147a, hsa-mir-205-5p, and
hsa-mir-195-5p) linked to the candidate genes. These derived data
find application in the understanding of EOC.
Keywords
Epithelial ovarian cancer, Differential gene expression, Biomarkers, Gene ontology, Survival analysis, miRNA-mRNA network
Citation
Singh & Som, Bioinformation 17(8): 748-759 (2021)
Edited by
P Kangueane
ISSN
0973-2063
Publisher
License
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
