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MicroRNA Expression Profile in Endometriosis and Endometriosis-Associated Ovarian Cancer-Systematic Review
Maria Szubert1,2, Iwona Gabriel3, Aleksander Rycerz1,4
1Department of Surgical and Oncologic Gynecology, 1st Department of Gynecology and Obstetrics, Medical University of Lodz, 251 Pomorska Street, 92-213 Lodz, Poland.
A distinct microRNA (miRNA) profile cannot yet differentiate endometriosis from endometriosis-associated ovarian cancer due to insufficient comparable raw data. Further research using standardized methods like next-generation sequencing is needed to establish a prognostic miRNA signature.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Endometriosis-associated ovarian cancer (EAOC) likely originates from endometriosis foci.
- MicroRNAs (miRNAs) are implicated in the carcinogenesis of EAOC.
- A distinct miRNA profile could potentially link endometriosis and EAOC and predict cancer development.
Purpose of the Study:
- To determine if a specific miRNA profile is associated with endometriosis and EAOC.
- To investigate the potential causal relationship between endometriosis and EAOC through miRNA expression.
- To assess the clinical utility of miRNA profiles for prognosing carcinogenesis in endometriosis.
Main Methods:
- Systematic literature search (PubMed, Cochrane, Medline) following PRISMA guidelines.
- Inclusion criteria: studies evaluating miRNA expression in both endometriosis and EAOC under identical conditions.
- Quality assessment using Newcastle-Ottawa Scale and ROBINS-I tool.
Main Results:
- Analysis of 13 studies (608 patients, >1000 miRNAs) revealed high heterogeneity.
- A meta-analysis was not feasible due to inconsistent methodologies and lack of raw data.
- No distinct miRNA profile could be established to differentiate between endometriosis and EAOC.
Conclusions:
- Insufficient comparable raw miRNA expression data exists to differentiate endometriosis from EAOC.
- High heterogeneity in reference gene sets prevents cross-study comparison of miRNA expression.
- Next-generation sequencing (NGS) is recommended for future studies to overcome standardization issues.
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