Open AccessDifferential expression of mi RNAs in the serum of patients with high‐risk oral lesions
Author(s) -
MacLellan Sara Ann,
Lawson James,
Baik Jonathan,
Guillaud Martial,
Poh Catherine FangYeu,
Garnis Cathie
Publication year - 2012
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.17
Subject(s) - rna , microrna , medicine , cancer , disease , long non coding rna , downregulation and upregulation , area under the curve , gastroenterology , oncology , cancer research , biology , gene , genetics
Oral cancer is one of the most commonly diagnosed cancers worldwide. Disease is often diagnosed at later stages, which is associated with a poor 5‐year survival rate and a high rate of local recurrence. Micro RNA s (mi RNA s), a group of small, noncoding RNA s, can be isolated from blood serum samples and have demonstrated utility as biomarkers in multiple cancer types. The aim of this study was to examine the expression profiles of circulating mi RNA s in the serum of patients with high‐risk oral lesions ( HRL s; oral cancer or carcinoma in situ) and to explore their utility as potential oral cancer biomarkers. Global serum mi RNA profiles were generated using quantitative PCR method from 1) patients diagnosed with HRL s and undergoing intent‐to‐cure surgical treatment ( N = 30) and 2) a demographically matched, noncancer control group ( N = 26). We next honed our list of serum mi RNA s associated with disease by reducing the effects of interpatient variability; we compared serum mi RNA profiles from samples taken both before and after tumor resections ( N = 10). Based on these analyses, fifteen mi RNA s were significantly upregulated and five were significantly downregulated based on presence of disease (minimum fold‐change >2 in at least 50% of samples, P < 0.05, permutation). Five of these mi RNA s (miR‐16, let‐7b, miR‐338‐3p, miR‐223, and miR‐29a) yielded an area under the ROC curve ( AUC ) >0.8, suggesting utility as noninvasive biomarkers for detection of oral cancer or high‐grade lesions. Combining these serum mi RNA profiles with other screening techniques could greatly improve the sensitivity in oral cancer detection.