| Literature DB >> 28017893 |
Paola Todeschini1, Elisa Salviato2, Lara Paracchini3, Manuela Ferracin4, Marco Petrillo5, Laura Zanotti6, Germana Tognon7, Angela Gambino8, Enrica Calura2, Giulia Caratti3, Paolo Martini2, Luca Beltrame3, Lorenzo Maragoni2, Daniela Gallo5, Franco E Odicino8, Enrico Sartori8, Giovanni Scambia5, Massimo Negrini9, Antonella Ravaggi6, Maurizio D'Incalci10, Sergio Marchini3, Eliana Bignotti7, Chiara Romualdi2.
Abstract
High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecologic neoplasm, with five-year survival rate below 30%. Early disease detection is of utmost importance to improve HGSOC cure rate. Sera from 168 HGSOC patients and 65 healthy controls were gathered together from two independent collections and stratified into a training set, for miRNA marker identification, and a validation set, for data validation. An innovative statistical approach for microarray data normalization was developed to identify differentially expressed miRNAs. Signature validation in both the training and validation sets was performed by quantitative Real Time PCR (RT-qPCR). In both the training and validation sets, miR-1246, miR-595 and miR-2278 emerged significantly over expressed in the sera of HGSOC patients compared to healthy controls. Receiver Operating Characteristic curve analysis revealed miR-1246 as the best diagnostic biomarker, with a sensitivity of 87%, a specificity of 77% and an accuracy of 84%. This study is the first step in the identification of circulating miRNAs with diagnostic relevance for HGSOC. According to its specificity and sensitivity, circulating miR-1246 levels are worthy to be further investigated as potential diagnostic biomarker for HGSOC.Entities:
Keywords: Diagnosis; High-grade serous ovarian carcinoma; Microarray; Serum miRNA; Tumor marker
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Year: 2016 PMID: 28017893 DOI: 10.1016/j.canlet.2016.12.017
Source DB: PubMed Journal: Cancer Lett ISSN: 0304-3835 Impact factor: 8.679