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Identification of Potent Novel Biomarkers of Uterine Leiomyoma Through DEGs Screening and Networking.


 Background: Uterine leiomyomas is a benign lesion arising in myometrium of the uterus. Various risk factors like stress, obesity, hormonal imbalance are involved in the progression of the uterine leiomyomas. Despite the significant research, the potential biomarkers related to uterine leiomyomas are yet to be discovered. Methods: The present study deals with searching the common potent markers of Uterine Leiomyoma (ULM) that was responsible for their pathogenicity. The microarray dataset (GSEID: GSE30673) was fetched through Gene Expression Omnibus database. Comparing with normal myometrium samples, Principal Component Analysis (PCA) and heat map were constructed to obtain differential expressed genes (DEGs) for ULM. Common DEGs were obtained through Venny software v 2.1.0. Significant enriched pathways and ontological study for DEGs were also performed through online Database for Annotation, Visualization and Integrated Discovery tool. Based upon STRING v 10.5, protein- protein interaction network was constructed in order to predict functional interactions among proteins. Results: 176 of total DEGs with 101 overexpressed and 75 under expressed genes were screened out with their official gene symbol. 2 DEGs were found as common genes in OMIM and Gene Cards.Only 9 DEGs were found to have combined score > 0.4 and hence included in interaction network. The present study revealed EGF, FYN, VCAN, TRIP13, FBXW7 as up-regulated genes and GATA2, JAG1, TLR3, APOL1 as down-regulated genes found to be expressed in samples with ULM disease. KEGG pathway enrichment analysis for DEGs revealed Focal adhesion, ECM-receptor interaction, long-term depression and Retinol metabolism are major pathways which have been enriched for these DEGs. Conclusion: We conclude that TRIP13 and TLR3 might be the novel biomarkers related to ULM disease which were revealed through our findings. The present study provides us a new perspective to detect the potent biomarkers responsible for ULM and further in vitro and in vivo experiments needed to be performed to verify the results.