Molecular signature of eutopic endometrium in endometriosis based on the multi-omics integrative synthesis
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Molecular signature of eutopic endometrium in endometriosis based on the multi-omics integrative synthesis Erika Prašnikar 1 & Jure Knez 2 & Borut Kovačič 1 & Tanja Kunej 3 Received: 26 February 2020 / Accepted: 14 May 2020 # The Author(s) 2020
Abstract Purpose To synthesise data from genome-wide studies reporting molecular signature of eutopic endometrium through the phases of the menstrual cycle in endometriosis. Methods Extraction of data from publications reporting genetic signatures characterising endometrium associated with endometriosis. The nomenclature of extracted differentially expressed transcripts and proteins was adopted according to the HUGO Gene Nomenclature Committee (HGNC). Loci were further sorted according to the different phases of the menstrual cycle, i.e. menstrual (M), proliferative (P), secretory (S), early-secretory (ES), mid-secretory (MS), late-secretory (LS), and not specified (N/S) if the endometrial dating was not available. Enrichment analysis was performed using the DAVID bioinformatics tool. Results Altered molecular changes were reported by 21 studies, including 13 performed at the transcriptomic, 6 at proteomic, and 2 at epigenomic level. Extracted data resulted in a catalogue of total 670 genetic causes with available 591 official gene symbols, i.e. M = 3, P = 188, S = 81, ES = 82, MS = 173, LS = 36, and N/S = 28. Enriched pathways included oestrogen signalling pathway, extracellular matrix organization, and endothelial cell chemotaxis. Our study revealed that knowledge of endometrium biology in endometriosis is fragmented due to heterogeneity of published data. However, 15 genes reported as dysregulated by at least two studies within the same phase and 33 significantly enriched GO-BP terms/KEGG pathways associated with different phases of the menstrual cycle were identified. Conclusions A multi-omics insight into molecular patterns underlying endometriosis could contribute towards identification of endometrial pathological mechanisms that impact fertility capacities of women with endometriosis. Keywords Endometriosis . Expression signature . Gene set enrichment analysis (GSEA) . Genome-wide study . Multi-omics data integration
Abbreviations ASRM American Society for Reproductive Medicine Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10815-020-01833-3) contains supplementary material, which is available to authorized users. * Borut Kovačič [email protected] * Tanja Kunej [email protected] 1
Department of Reproductive Medicine and Gynecological Endocrinology, University Medical Centre Maribor, 2000 Maribor, Slovenia
2
Department of Gynecological and Breast Oncology, University Medical Centre Maribor, 2000 Maribor, Slovenia
3
Biotechnical Faculty, Department of Animal Science, University of Ljubljana, 1000 Ljubljana, Slovenia
GSEA HGNC NCBI DAVID KEGG GO mRNA lncRNA sncRNA snoRNA miRNA M P S ES MS
Gene set enrichment analysis HUGO Gene Nomenclature Committee National Centre for Biotechnol
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