Circulating miRNAs and Multivariate Biomarker Signatures in Ovarian Cancer: A Systematic Review
6 affiliations
- 1Department of Life Sciences, School of Life and Health Sciences, University of Nicosia, Nicosia 2417, Cyprus
- 2Non-Coding RNA Research Laboratory, School of Life and Health Sciences, University of Nicosia, Nicosia 2417, Cyprus
- 3Instituto Português de Oncologia de Lisboa Francisco Gentil, 1099-023 Lisbon, Portugal
- 4Institute of Communication and Computer Systems, National Technical University of Athens, Zografos Campus, 15780 Athens, Greece
- 5School of Chemical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
- 6Department of Surgery and Cancer, Imperial College London, London W12 0NN, UK
Abstract
Ovarian cancer (OC) is the most lethal gynecological malignancy, largely because non-specific symptoms contribute to advanced-stage diagnosis and poor prognosis, underscoring the need for improved non-invasive biomarkers. Circulating microRNAs (c-miRNAs) have emerged as promising candidates for OC detection, risk stratification, prognosis, and treatment monitoring. This systematic review, prospectively registered in PROSPERO (CRD420251230898), evaluated the diagnostic and prognostic performance of c-miRNAs and miRNA-based multivariate signatures. MEDLINE/PubMed, Scopus, and CENTRAL were searched from inception to 30 May 2026. Eligible studies assessed c-miRNAs in serum, plasma, whole blood, or extracellular vesicle fractions from women with confirmed or suspected OC including studies using prediagnostic samples from women subsequently diagnosed with OC. Records were screened, data extracted, and risk of bias evaluated according to the type of result using QUADAS-2 for diagnostic accuracy, QUIPS for prognostic-factor associations, and PROBAST for multivariable prediction models. Of 697 records identified, 91 publications met the inclusion criteria. Most studies used case–control or observational designs and analysed serum or plasma samples. Single c-miRNAs generally showed moderate diagnostic accuracy, whereas multivariate miRNA panels and multimodal models incorporating CA-125 or HE4 generally reported higher AUC values, including in some early-stage cohorts. Frequently reported candidates included members of the miR-200 family, miR-21, miR-1246, miR-125b, miR-145, miR-205, and miR-130a. Prognostic studies associated c-miRNAs with survival, recurrence, treatment response, and chemoresistance, although findings were more heterogeneous than diagnostic findings. Risk-of-bias concerns were common, particularly for patient selection in diagnostic studies, confounding in prognostic-factor analyses, and statistical analysis in prediction-model studies. Overall, c-miRNAs represent promising non-invasive biomarkers for OC, particularly when integrated into multivariate or multimodal models. However, methodological heterogeneity, small cohort sizes, limited external validation, and inconsistent reporting currently restrict clinical translation. Future studies should prioritize standardized pre-analytical and analytical workflows, adequately powered prospective cohorts, and independent multicenter validation.
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BibTeX
@article{ayache2026circulating,
title = {{Circulating miRNAs and Multivariate Biomarker Signatures in Ovarian Cancer: A Systematic Review}},
author = {Karen Ayache and Ana Vieira and Sofia Fragoso and Siobhan Brushett and Ioannis Gallos and Pushpa Patel and Jonathan Krell and Paula Cunnea and Dimitra Dionysiou and Fátima Vaz and Paula M. Mendes and Myrtani Pieri and Christos Papaneophytou},
journal = {International Journal of Molecular Sciences},
year = {2026},
month = oct,
doi = {10.3390/ijms27198823},
url = {https://www.mdpi.com/1422-0067/27/19/8823},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Circulating miRNAs and Multivariate Biomarker Signatures in Ovarian Cancer: A Systematic Review
AU - Karen Ayache
AU - Ana Vieira
AU - Sofia Fragoso
AU - Siobhan Brushett
AU - Ioannis Gallos
AU - Pushpa Patel
AU - Jonathan Krell
AU - Paula Cunnea
AU - Dimitra Dionysiou
AU - Fátima Vaz
AU - Paula M. Mendes
AU - Myrtani Pieri
AU - Christos Papaneophytou
PY - 2026
DA - 2026/10/02
JO - International Journal of Molecular Sciences
DO - 10.3390/ijms27198823
UR - https://www.mdpi.com/1422-0067/27/19/8823
AB - Ovarian cancer (OC) is the most lethal gynecological malignancy, largely because non-specific symptoms contribute to advanced-stage diagnosis and poor prognosis, underscoring the need for improved non-invasive biomarkers. Circulating microRNAs (c-miRNAs) have emerged as promising candidates for OC detection, risk stratification, prognosis, and treatment monitoring. This systematic review, prospectively registered in PROSPERO (CRD420251230898), evaluated the diagnostic and prognostic performance of c-miRNAs and miRNA-based multivariate signatures. MEDLINE/PubMed, Scopus, and CENTRAL were searched from inception to 30 May 2026. Eligible studies assessed c-miRNAs in serum, plasma, whole blood, or extracellular vesicle fractions from women with confirmed or suspected OC including studies using prediagnostic samples from women subsequently diagnosed with OC. Records were screened, data extracted, and risk of bias evaluated according to the type of result using QUADAS-2 for diagnostic accuracy, QUIPS for prognostic-factor associations, and PROBAST for multivariable prediction models. Of 697 records identified, 91 publications met the inclusion criteria. Most studies used case–control or observational designs and analysed serum or plasma samples. Single c-miRNAs generally showed moderate diagnostic accuracy, whereas multivariate miRNA panels and multimodal models incorporating CA-125 or HE4 generally reported higher AUC values, including in some early-stage cohorts. Frequently reported candidates included members of the miR-200 family, miR-21, miR-1246, miR-125b, miR-145, miR-205, and miR-130a. Prognostic studies associated c-miRNAs with survival, recurrence, treatment response, and chemoresistance, although findings were more heterogeneous than diagnostic findings. Risk-of-bias concerns were common, particularly for patient selection in diagnostic studies, confounding in prognostic-factor analyses, and statistical analysis in prediction-model studies. Overall, c-miRNAs represent promising non-invasive biomarkers for OC, particularly when integrated into multivariate or multimodal models. However, methodological heterogeneity, small cohort sizes, limited external validation, and inconsistent reporting currently restrict clinical translation. Future studies should prioritize standardized pre-analytical and analytical workflows, adequately powered prospective cohorts, and independent multicenter validation.
SN - 1422-0067
ER -