Identification Target Genes for Potential Biomarkers in Endometriosis from Transcriptomics Database
This study analyzed transcriptomic data from three endometriosis datasets to identify 339 differentially expressed genes, highlighting pathways involved in cell proliferation and angiogenesis, and proposing ten genes as potential biomarkers.
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The paper analyzed three publicly available endometriosis transcriptomic datasets (GSE7307, GSE23339, and GSE25628) from the GEO database to identify differentially expressed genes and underlying pathways. After intersecting DEGs across datasets, the authors reported 339 genes and found enrichment for processes such as epithelial cell proliferation and angiogenesis, with components involving lysosomal lumen and extracellular matrix, and molecular functions including Wnt-activated receptor activity and low-density lipoprotein particle binding. Ten genes (TAGLN, C7, TCF21, GATA6, GPC3, FZD7, TCEAL2, KLF2, FMO1, and HOXC6) were proposed as candidate biomarker targets. This paper is centrally about endometriosis — it derives candidate biomarker genes and enriched pathways from transcriptomic data.
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- last seen: 2026-06-10T17:14:06.276822+00:00