Using Ultra‐Deep miRNA sequencing for identification of possible new biomarkers in endometriosis patients

Endometriosis seems to be a precursor of epithelial ovarian cancer, especially clear cell and endometrioid adenocarcinomas. The features shared by endometriosis and cancer include the ability to evade apoptosis, the stem cell‐like ability and angiogenic potential. As such characteristics are encoded by the cell's genetic constitution; acquired mutations are responsible for the malignant transformation of endometriosis. So, a number of differences between endometriosis and cancer are found at the molecular level and miRNAs are recognized as key regulators of gene expression. Besides, aberrant expression of these small RNAs has been linked to human disease, including those related to estrogen‐dependent gynecological disorders and cancer. Total RNA of 09 type IV endometriosis patients, as well as, 07 normal endometrioid tissue was extracted, enriched for small RNAs and used for microRNA expression analysis on SOLiD4 sequencer. Sequences were mapped against the miRBase using CLC Genomics Workbench 6.0.1. An average of 5 million reads per sample was mapped on known miRNAs. After mapping and normalization of reads, we used EdgeR to identify differently expressed miRNAs, those with p<0.01 and FDR < 0.05. With this methodology we could obtain differentially expressed miRNAs between the samples which indicates that this approach is feasible for new biomarkers search.