Background: Endometriosis is a common gynaecological disease and there is no reliable non-invasive biomarker for its unknown pathogenesis. TRF is differentially expressed in a variety of cancers and is a new non-invasive biomarker. The aim of this study was to reveal the full landscape of tRF expression profile in endometriosis using PANDORA-seq, which will provide strong target support for early diagnosis and treatment.
Methods: PANDORA-seq was used to detect the eutopic and ectopic endometrial tissues of 4 patients with ovarian endometriosis and 4 normal endometrial tissues in the control group, and qRT-PCR was performed to verify. The target genes of DEtRF were predicted by TargetScan and miRanda, and the potential functions of differential tRFs were studied by bioinformatics such as Gene Ontology (GO) and Kycrto Encyclopedia of Genes and Genomes (KEGG), so as to further elucidate the pathogenesis of endometriosis.
Results: Under the screening conditions of |Fold Change| ≥ 2 and Padj < 0.05, a total of 13 common differentially expressed tRFs were identified when comparing the disease groups, defined as endometriosis-affected eutopic endometrial tissue (EU) and ectopic endometrial tissue (EC), with the control group consisting of eutopic endometrial tissue from normal uteri (EN). Eleven DEtRFs target genes were highly enriched in endometriosis-related signalling pathways, such as MAPK, Ras, p53 and mitophagy-related pathways.
Conclusion: Differentially expressed tRF may be involved in the development of endometriosis by regulating target genes in MAPK and autophagy signalling pathways. DEtRF is expected to be a new non-invasive biomarker for endometriosis.
Keywords: Bioinformatics; PANDORA-seq; biomarker; endometriosis; noncoding RNAs; tRNA-derived fragments.