sábado, 26 de mayo de 2018

Predicting the presence of oral squamous cell carcinoma using commonly dysregulated microRNA in oral swirls. - PubMed - NCBI

2018 May 15. pii: canprevres.0409.2017. doi: 10.1158/1940-6207.CAPR-17-0409. [Epub ahead of print]

Predicting the presence of oral squamous cell carcinoma using commonly dysregulated microRNA in oral swirls.

Yap T1, Koo K2, Cheng L3, Vella LJ4, Hill AF3, Reynolds EC5, Nastri AL6, Cirillo N7, Seers CA8, McCullough M5.

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Abstract

Oral swirls are a noninvasive, rapidly collected source of salivary microRNA potentially useful in the early detection of disease states, particularly oral squamous cell carcinoma (OSCC). The aim of this study was to predict the presence of oral squamous cell carcinoma using a panel of OSCC-related dysregulated microRNA found in oral swirls, identified jointly in data from formalin-fixed paraffin embedded (FFPE) and fresh frozen specimens. Next generation sequencing (NGS) was used to determine microRNA fold changes in FFPE OSCC specimens relative to histologically normal epithelium. This data was placed with NGS of fresh frozen tissue data of The Cancer Genome Atlas database (TCGA) to select a panel of commonly dysregulated microRNA. This panel was then analyzed by RT-qPCR in RNA extracted from oral swirls collected from 30 patients with OSCC and 30 controls. Upregulation of miR-31, miR-21 and downregulation of miR-99a, let-7c, miR-125b and miR-100 was found between OSCC and controls in both FFPE and fresh frozen samples. These microRNA were studied in a training set of 15 OSCC vs 15 control oral swirls to develop a dysregulation score (AUC 0.95 (95% CI, 0.88-1.03)) and classification tree. A test cohort of 15 OSCC vs 15 control oral swirls yielded a dysregulation score AUC of 0.86 (95% CI, 0.79-1.00) with the classification tree identifying 100% (15/15) of OSCC and 67% (10/15) of controls. This study debuts the use of OSCC-associated microRNA, commonly dysregulated in both FFPE and frozen specimens, in oral swirls to indicate presence of OSCC with high accuracy.