Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach
Ovarian cancer is the eighth-most common cancer in women and has the highest rate of death among all gynecological malignancies in the Western world. Increasing evidence shows that miRNAs are connected to the progression of ovarian cancer. In the current study, we focus on the identification of miRN...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Biology |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-7737/12/2/192 |
| _version_ | 1797622281016442880 |
|---|---|
| author | Anam Beg Rafat Parveen Hassan Fouad M. E. Yahia Azza S. Hassanein |
| author_facet | Anam Beg Rafat Parveen Hassan Fouad M. E. Yahia Azza S. Hassanein |
| author_sort | Anam Beg |
| collection | DOAJ |
| description | Ovarian cancer is the eighth-most common cancer in women and has the highest rate of death among all gynecological malignancies in the Western world. Increasing evidence shows that miRNAs are connected to the progression of ovarian cancer. In the current study, we focus on the identification of miRNA and its associated genes that are responsible for the early prognosis of patients with ovarian cancer. The microarray dataset GSE119055 used in this study was retrieved via the publicly available GEO database by NCBI for the analysis of DEGs. The miRNA GSE119055 dataset includes six ovarian carcinoma samples along with three healthy/primary samples. In our study, DEM analysis of ovarian carcinoma and healthy subjects was performed using R Software to transform and normalize all transcriptomic data along with packages from Bioconductor. Results: We identified miRNA and its associated hub genes from the samples of ovarian cancer. We discovered the top five upregulated miRNAs (hsa-miR-130b-3p, hsa-miR-18a-5p, hsa-miR-182-5p, hsa-miR-187-3p, and hsa-miR-378a-3p) and the top five downregulated miRNAs (hsa-miR-501-3p, hsa-miR-4324, hsa-miR-500a-3p, hsa-miR-1271-5p, and hsa-miR-660-5p) from the network and their associated genes, which include seven common genes (SCN2A, BCL2, MAF, ZNF532, CADM1, ELAVL2, and ESRRG) that were considered hub genes for the downregulated network. Similarly, for upregulated miRNAs we found two hub genes (PRKACB and TAOK1). |
| first_indexed | 2024-03-11T09:07:59Z |
| format | Article |
| id | doaj.art-61aba41d92ae45baa888ac783db6cecf |
| institution | Directory Open Access Journal |
| issn | 2079-7737 |
| language | English |
| last_indexed | 2024-03-11T09:07:59Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biology |
| spelling | doaj.art-61aba41d92ae45baa888ac783db6cecf2023-11-16T19:12:54ZengMDPI AGBiology2079-77372023-01-0112219210.3390/biology12020192Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico ApproachAnam Beg0Rafat Parveen1Hassan Fouad2M. E. Yahia3Azza S. Hassanein4Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, IndiaDepartment of Computer Science, Jamia Millia Islamia, New Delhi 110025, IndiaApplied Medical Science Department, CC, King Saud University, Riyadh 11433, Saudi ArabiaFaculty of Engineering and Natural Sciences, International University of Sarajevo, Hrasnička Cesta 15, Ilidža, 71210 Sarajevo, Bosnia and HerzegovinaBiomedical Engineering Department, Faculty of Engineering, Helwan University, Cairo 11792, EgyptOvarian cancer is the eighth-most common cancer in women and has the highest rate of death among all gynecological malignancies in the Western world. Increasing evidence shows that miRNAs are connected to the progression of ovarian cancer. In the current study, we focus on the identification of miRNA and its associated genes that are responsible for the early prognosis of patients with ovarian cancer. The microarray dataset GSE119055 used in this study was retrieved via the publicly available GEO database by NCBI for the analysis of DEGs. The miRNA GSE119055 dataset includes six ovarian carcinoma samples along with three healthy/primary samples. In our study, DEM analysis of ovarian carcinoma and healthy subjects was performed using R Software to transform and normalize all transcriptomic data along with packages from Bioconductor. Results: We identified miRNA and its associated hub genes from the samples of ovarian cancer. We discovered the top five upregulated miRNAs (hsa-miR-130b-3p, hsa-miR-18a-5p, hsa-miR-182-5p, hsa-miR-187-3p, and hsa-miR-378a-3p) and the top five downregulated miRNAs (hsa-miR-501-3p, hsa-miR-4324, hsa-miR-500a-3p, hsa-miR-1271-5p, and hsa-miR-660-5p) from the network and their associated genes, which include seven common genes (SCN2A, BCL2, MAF, ZNF532, CADM1, ELAVL2, and ESRRG) that were considered hub genes for the downregulated network. Similarly, for upregulated miRNAs we found two hub genes (PRKACB and TAOK1).https://www.mdpi.com/2079-7737/12/2/192ovarian cancerDEMsmiRNA–mRNA networkmodule |
| spellingShingle | Anam Beg Rafat Parveen Hassan Fouad M. E. Yahia Azza S. Hassanein Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach Biology ovarian cancer DEMs miRNA–mRNA network module |
| title | Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach |
| title_full | Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach |
| title_fullStr | Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach |
| title_full_unstemmed | Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach |
| title_short | Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach |
| title_sort | identification of driver genes and mirnas in ovarian cancer through an integrated in silico approach |
| topic | ovarian cancer DEMs miRNA–mRNA network module |
| url | https://www.mdpi.com/2079-7737/12/2/192 |
| work_keys_str_mv | AT anambeg identificationofdrivergenesandmirnasinovariancancerthroughanintegratedinsilicoapproach AT rafatparveen identificationofdrivergenesandmirnasinovariancancerthroughanintegratedinsilicoapproach AT hassanfouad identificationofdrivergenesandmirnasinovariancancerthroughanintegratedinsilicoapproach AT meyahia identificationofdrivergenesandmirnasinovariancancerthroughanintegratedinsilicoapproach AT azzashassanein identificationofdrivergenesandmirnasinovariancancerthroughanintegratedinsilicoapproach |