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A novel saliva-based miRNA profile to diagnose and predict oral cancer

International Journal of Oral Science 2024年第1期16卷 97-109页

作者： jaikrishna balakittnen Chameera Ekanayake Weeramange Daniel F.Wallace Pascal H.G.Duijf Alexandre S.Cristino Gunter Hartel Roberto A.Barrero Touraj Taheri Liz Kenny Sarju Vasani Martin Batstone Omar Breik Chamindie Punyadeera Saliva&Liquid Biopsy Translational Laboratory Griffith Institute for Drug DiscoveryGriffith UniversityNathanQLDAustralia Department of Medical Laboratory Sciences Faculty of Allied Health SciencesUniversity of JaffnaJaffnaSri Lanka Menzies Health Institute Griffith UniversityGold CoastQLDAustralia School of Biomedical Sciences Faculty of HealthQueensland University of TechnologyBrisbaneQLDAustralia Centre for Cancer Biology Clinical and Health SciencesUniversity of South Australia&SA PathologyAdelaideSAAustralia Institute of Clinical Medicine Faculty of MedicineUniversity of OsloOsloNorway Department of Medical Genetics Oslo University HospitalOsloNorway Griffith Institute for Drug Discovery Griffith UniversityNathanQLDAustralia QIMR Berghofer Medical Research Institute Statistics UnitBrisbaneQLDAustralia School of Public Health The University of QueenslandBrisbaneQLDAustralia School of Nursing Queensland University of TechnologyBrisbaneQLDAustralia eResearch Research InfrastructureAcademic DivisionQueensland University of TechnologyBrisbaneQLDAustralia Department of Anatomical Pathology Royal Brisbane and Women’s HospitalHerstonQLDAustralia Faculty of Medicine The University of QueenslandBrisbaneQLDAustralia Royal Brisbane and Women’s Hospital Cancer Care ServicesHerstonQLDAustralia Department of Otolaryngology Royal Brisbane and Women’s HospitalHerstonQLDAustralia Department of Oral and Maxillofacial Surgery Royal Brisbane and Women’s HospitalHerstonQLDAustralia

Oral cancer (OC) is the most common form of head and neck cancer. Despite the high incidence and unfavourable patient outcomes, currently, there are no biomarkers for the early detection of OC. This study aims to discover, develop, and validate a novel saliva-based microRNA signature for early diagnosis and prediction of OC risk in oral potentially malignant disorders (OPMD).The Cancer Genome Atlas (TCGA) miRNA sequencing data and small RNA sequencing data of saliva samples were used to discover differentially expressed miRNAs. Identified miRNAs were validated in saliva samples of OC (n=50), OPMD (n=52), and controls(n=60) using quantitative real-time PCR. Eight differentially expressed miRNAs (miR-7-5p, miR-10b-5p, miR-182-5p, miR-215-5p,miR-431-5p, miR-486-3p, miR-3614-5p, and miR-4707-3p) were identified in the discovery phase and were validated. The efficiency of our eight-miRNA signature to discriminate OC and controls was:area under curve (AUC):0.954, sensitivity:86%, specificity:90%,positive predictive value (PPV):87.8%and negative predictive value (NPV):88.5%whereas between OC and OPMD was:AUC:0.911,sensitivity:90%, specificity:82.7%, PPV:74.2%and NPV:89.6%. We have developed a risk probability score to predict the presence or risk of OC in OPMD patients. We established a salivary miRNA signature that can aid in diagnosing and predicting OC,revolutionising the management of patients with OPMD. Together, our results shed new light on the management of OC by salivary miRNAs to the clinical utility of using miRNAs derived from saliva samples.

关键词： specificity salivary diagnosis

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