MicroRNA-based classifiers for diagnosis of oral cavity squamous cell carcinoma in tissue and plasma

Publication date: August 2018

Source: Oral Oncology, Volume 83

Author(s): Nicklas Juel Pedersen, David Hebbelstrup Jensen, Giedrius Lelkaitis, Katalin Kiss, Birgitte Wittenborg Charabi, Henrik Ullum, Lena Specht, Ane Yde Schmidt, Finn Cilius Nielsen, Christian von Buchwald

Abstract

Background

MicroRNAs (miRNAs) hold promise as diagnostic cancer biomarkers. Here we aimed to define the miRNome in oral squamous cell carcinoma (OSCC) and normal oral mucosa (NOM), and to identify and validate new diagnostic miRNAs and miRNA combinations in formalin-fixed paraffin-embedded (FFPE) tissue samples and plasma samples.

Methods

We performed next-generation miRNA sequencing in FFPE tissue samples of OSCC (n = 80) and NOM (n = 8). Our findings were validated by quantitative polymerase chain reaction (qPCR) analysis of OSCC (n = 195) and NOM (n = 103) FFPE tissue samples, and plasma samples from OSCC patients (n = 55) and healthy persons (n = 18).

Results

The OSCC miRNome included 567 miRNAs, 66 of which were differentially expressed between OSCC and NOM. Using qPCR data, we constructed receiver operating curves to classify patients as NOM or OSCC based on miRNA combinations. The area under the curve was of 0.92 from FFPE tissue (miR-204-5p, miR-370, miR-1307, miR-193b-3p, and miR-144-5p), and 1.0 from plasma samples (miR-30a-5p and miR-769-5p). Model calibration and discrimination were evaluated using 10-fold cross-validation.

Conclusions

Analysis of the miRNome from many OSCC cases improves our knowledge of the importance of individual miRNAs and their predictive potential in OSCC. We successfully identified miRNA classifiers in FFPE OSCC tissue and plasma with a high discriminatory ability between OSCC and NOM. The proposed combination of miR-30a-5p and miR-769-5p in plasma from OSCC patients could serve as a minimal invasive biomarker for diagnosis and control of T-site recurrences.

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