Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study
Background: Uterine corpus endometrial carcinoma (UCEC), derived from the endometrium, is the most common type of endometrial malignasis. This gynecological malignancy is very common all over the world, especially in developed countries and shows a potentially rising trend correlated with the increa...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Biochemistry and Biophysics Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405580824002243 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850173365823733760 |
|---|---|
| author | Mahsa Ejlalidiz Ameneh Mehri-Ghahfarrokhi Mohammadreza Saberiyan |
| author_facet | Mahsa Ejlalidiz Ameneh Mehri-Ghahfarrokhi Mohammadreza Saberiyan |
| author_sort | Mahsa Ejlalidiz |
| collection | DOAJ |
| description | Background: Uterine corpus endometrial carcinoma (UCEC), derived from the endometrium, is the most common type of endometrial malignasis. This gynecological malignancy is very common all over the world, especially in developed countries and shows a potentially rising trend correlated with the increase in obese women. Methods: Differentially Expressed Genes (DEGs) analysis was conducted on GSE7305 and GSE25628 datasets from the Gene Expression Omnibus (GEO). DEGs were identified using GEO2R (adjusted p-value <0.05, |logFC| > 1). Pathway analysis employed KEGG and Gene Ontology databases, while protein-protein interactions were analyzed using Cytoscape and Gephi. GEPIA was used for target gene validation. Results: We have identified 304 common DEGs and 78 hub genes using GEO and PPI analysis, respectively. The GO and KEGG pathways analysis revealed enrichment of DEGs in extracellular matrix structural constituent, extracellular space, cell adhesion, and ECM-receptor interaction. GEPIA analysis identified three genes, ENG, GNG4, and ECT2, whose expression significantly differed between normal and tumor samples. Conclusion: This analysis study identified the hub genes and associated pathways involved in the pathogenesis of UCEC. The identified hub genes exhibit remarkable potential as diagnostic biomarkers, providing a significant opportunity for early diagnosis and more effective therapeutic approaches for UCEC. |
| format | Article |
| id | doaj-art-93c68d6f54c7477e97d46db8b823e2e5 |
| institution | OA Journals |
| issn | 2405-5808 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Biochemistry and Biophysics Reports |
| spelling | doaj-art-93c68d6f54c7477e97d46db8b823e2e52025-08-20T02:19:51ZengElsevierBiochemistry and Biophysics Reports2405-58082024-12-014010186010.1016/j.bbrep.2024.101860Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico studyMahsa Ejlalidiz0Ameneh Mehri-Ghahfarrokhi1Mohammadreza Saberiyan2Medical Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, IranClinical Research Developmental Unit, Hajar Hospital, Shahrekord University of Medical Sciences, Shahrekord, IranDepartment of Medical Genetics, School of Medical Sciences, Hormozgan University of Medical Sciences, Bandar Abbas, Iran; Corresponding author. Department of Medical Genetics, School of Medical Sciences, Hormozgan University of Medical Sciences, Bandar Abbas, P.O.Box: 7919693116, Iran.Background: Uterine corpus endometrial carcinoma (UCEC), derived from the endometrium, is the most common type of endometrial malignasis. This gynecological malignancy is very common all over the world, especially in developed countries and shows a potentially rising trend correlated with the increase in obese women. Methods: Differentially Expressed Genes (DEGs) analysis was conducted on GSE7305 and GSE25628 datasets from the Gene Expression Omnibus (GEO). DEGs were identified using GEO2R (adjusted p-value <0.05, |logFC| > 1). Pathway analysis employed KEGG and Gene Ontology databases, while protein-protein interactions were analyzed using Cytoscape and Gephi. GEPIA was used for target gene validation. Results: We have identified 304 common DEGs and 78 hub genes using GEO and PPI analysis, respectively. The GO and KEGG pathways analysis revealed enrichment of DEGs in extracellular matrix structural constituent, extracellular space, cell adhesion, and ECM-receptor interaction. GEPIA analysis identified three genes, ENG, GNG4, and ECT2, whose expression significantly differed between normal and tumor samples. Conclusion: This analysis study identified the hub genes and associated pathways involved in the pathogenesis of UCEC. The identified hub genes exhibit remarkable potential as diagnostic biomarkers, providing a significant opportunity for early diagnosis and more effective therapeutic approaches for UCEC.http://www.sciencedirect.com/science/article/pii/S2405580824002243EndometriosisUCECPPI networkDiagnostic biomarkers |
| spellingShingle | Mahsa Ejlalidiz Ameneh Mehri-Ghahfarrokhi Mohammadreza Saberiyan Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study Biochemistry and Biophysics Reports Endometriosis UCEC PPI network Diagnostic biomarkers |
| title | Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study |
| title_full | Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study |
| title_fullStr | Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study |
| title_full_unstemmed | Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study |
| title_short | Identification of hub genes and pathways in Uterine corpus endometrial carcinoma (UCEC): A comprehensive in silico study |
| title_sort | identification of hub genes and pathways in uterine corpus endometrial carcinoma ucec a comprehensive in silico study |
| topic | Endometriosis UCEC PPI network Diagnostic biomarkers |
| url | http://www.sciencedirect.com/science/article/pii/S2405580824002243 |
| work_keys_str_mv | AT mahsaejlalidiz identificationofhubgenesandpathwaysinuterinecorpusendometrialcarcinomaucecacomprehensiveinsilicostudy AT amenehmehrighahfarrokhi identificationofhubgenesandpathwaysinuterinecorpusendometrialcarcinomaucecacomprehensiveinsilicostudy AT mohammadrezasaberiyan identificationofhubgenesandpathwaysinuterinecorpusendometrialcarcinomaucecacomprehensiveinsilicostudy |