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Determination of novel biomarkers and pathways shared by colorectal cancer and endometrial cancer via comprehensive bioinformatics analysis
- Source :
- Informatics in Medicine Unlocked, Vol 20, Iss , Pp 100376- (2020)
- Publication Year :
- 2020
- Publisher :
- Elsevier, 2020.
-
Abstract
- Background: Endometrial cancer (EC) is a common female genital tract malignancy of women, and colorectal cancer (CRC) is one of its risk factors. However, the mutual genes and molecular pathways shared by these two diseases have not yet been ascertained. Objectives: In the present study, we aimed to reveal candidate biomarkers and molecular interactions between CRC and EC to understand the common disease mechanism. Materials and methods: We performed differential analysis of CRC and EC microarray data by employing limma to reveal differentially expressed genes (DEGs). Then, we used mutual DEGs between these diseases to obtain significant biological processes and pathways by performing enrichment analyses. In addition, to reveal candidate biomarkers and regulatory transcripts, we analyzed different networks using bioinformatics tools. Results: We identified 286 overlapped DEGs between CRC and EC transcriptomes datasets. Enrichment analysis of these aberrantly expressed genes revealed that they were significantly enriched in cancer pathways signaling. Based on topological analysis of the PPI network, we revealed 11 hub proteins including JUN, MYC, FOS, EGR1, LEF1, CDC42, CTGF, ADAM10, CYR61, FOXA1, and UBE2I. We also identified seven significant transcription factors (TFs) namely FOXC1, GATA2, YY1, E2F1, CREB1, HINFP, and FOXL1 and five miRNAs including hsa-miR-124-3p, hsa-miR-106b-5p, hsa-miR-501-3p, hsa-miR-29b-3p, and hsa-miR-145-5p that regulate expressions of the DEGs. Conclusion: We have identified novel biomarkers and molecular pathways shared by CRC and EC that will help to understand underlying common molecular mechanisms and to develop potential therapeutics.
Details
- Language :
- English
- ISSN :
- 23529148
- Volume :
- 20
- Issue :
- 100376-
- Database :
- Directory of Open Access Journals
- Journal :
- Informatics in Medicine Unlocked
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.1ecf70e45c3544a8bf11e35086663925
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.imu.2020.100376