Multi-analytical test based on serum miRNAs and proteins quantification for ovarian cancer early detection.

Autor: Cirillo PDR; Altamedica Center, Human Genetics Laboratories, Altamedica Main Center, Rome, Italy., Margiotti K; Altamedica Center, Human Genetics Laboratories, Altamedica Main Center, Rome, Italy., Fabiani M; Altamedica Center, Human Genetics Laboratories, Altamedica Main Center, Rome, Italy., Barros-Filho MC; Department of Head and Neck Surgery, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil., Sparacino D; Altamedica Center, Human Genetics Laboratories, Altamedica Main Center, Rome, Italy., Cima A; Altamedica Center, Human Genetics Laboratories, Altamedica Main Center, Rome, Italy., Longo SA; Altamedica Center, Human Genetics Laboratories, Altamedica Main Center, Rome, Italy., Cupellaro M; Altamedica, Department of Biochemistry, Altamedica Main Centre, Rome, Italy., Mesoraca A; Altamedica Center, Human Genetics Laboratories, Altamedica Main Center, Rome, Italy., Giorlandino C; Altamedica Center, Human Genetics Laboratories, Altamedica Main Center, Rome, Italy.; Altamedica, Department of Biochemistry, Altamedica Main Centre, Rome, Italy.; Altamedica, Department of Prenatal Diagnosis, Fetal-Maternal Medical Center, Rome, Italy.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2021 Aug 05; Vol. 16 (8), pp. e0255804. Date of Electronic Publication: 2021 Aug 05 (Print Publication: 2021).
DOI: 10.1371/journal.pone.0255804
Abstrakt: Advanced ovarian cancer is one of the most lethal gynecological tumor, mainly due to late diagnoses and acquired drug resistance. MicroRNAs (miRNAs) are small-non coding RNA acting as tumor suppressor/oncogenes differentially expressed in normal and epithelial ovarian cancer and has been recognized as a new class of tumor early detection biomarkers as they are released in blood fluids since tumor initiation process. Here, we evaluated by droplet digital PCR (ddPCR) circulating miRNAs in serum samples from healthy (N = 105) and untreated ovarian cancer patients (stages I to IV) (N = 72), grouped into a discovery/training and clinical validation set with the goal to identify the best classifier allowing the discrimination between earlier ovarian tumors from health controls women. The selection of 45 candidate miRNAs to be evaluated in the discovery set was based on miRNAs represented in ovarian cancer explorative commercial panels. We found six miRNAs showing increased levels in the blood of early or late-stage ovarian cancer groups compared to healthy controls. The serum levels of miR-320b and miR-141-3p were considered independent markers of malignancy in a multivariate logistic regression analysis. These markers were used to train diagnostic classifiers comprising miRNAs (miR-320b and miR-141-3p) and miRNAs combined with well-established ovarian cancer protein markers (miR-320b, miR-141-3p, CA-125 and HE4). The miRNA-based classifier was able to accurately discriminate early-stage ovarian cancer patients from health-controls in an independent sample set (Sensitivity = 80.0%, Specificity = 70.3%, AUC = 0.789). In addition, the integration of the serum proteins in the model markedly improved the performance (Sensitivity = 88.9%, Specificity = 100%, AUC = 1.000). A cross-study validation was carried out using four data series obtained from Gene Expression Omnibus (GEO), corroborating the performance of the miRNA-based classifier (AUCs ranging from 0.637 to 0.979). The clinical utility of the miRNA model should be validated in a prospective cohort in order to investigate their feasibility as an ovarian cancer early detection tool.
Competing Interests: PDRC, KM,MF,MCBF,DS,AC,SAL,MC, and AM are employed by Altamedica Medical centre, and CG is the scientific director of Altamedica Medical centre of Rome. There are no patents, products in development or market products to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Databáze: MEDLINE
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