The Potential Use of Salivary miRNAs as Promising Biomarkers for Detection of Cancer: A Meta-Analysis.
BACKGROUND
Accumulating evidence has demonstrated that microRNAs (miRNAs) could serve as promising molecular biomarkers for cancer detection. This study aims to systematically assess the diagnostic performance of salivary miRNAs in detection of cancer through a comprehensive meta-analysis.


METHODS
Eligible studies were identified using PubMed and other computerized databases up to October 31, 2015, supplemented by a manual search of references from retrieved articles. The pooled sensitivity, specificity, and other measurements of accuracy of salivary miRNAs in the diagnosis of cancer were analyzed using the bivariate binomial mixed model.


RESULTS
Seventeen studies from 8 articles with 694 subjects were included in this meta-analysis. All studies have a relatively high score of quality assessment. The overall sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) of salivary miRNAs in detection of cancer were 0.77 (95% confidence intervals [CI]: 0.69-0.84), 0.77 (95%CI: 0.65-0.88), 3.37 (95%CI: 2.26-5.02), 0.29 (95%CI: 0.23-0.38), and 11.41 (95%CI: 7.35-17.73), respectively. The AUC was 0.84 (95%CI: 0.80-0.87). Moreover, both whole saliva and saliva supernatant could be used as sources of clinical specimens for miRNAs detection.


CONCLUSIONS
Our meta-analysis demonstrated that salivary miRNAs may serve as potential noninvasive biomarkers for cancer detection. The findings need to be confirmed with further research before it can be applied in the clinic.
Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China.
Yuanjie
Y
Ding
Department of Cancer Epidemiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.
Qing
Q
Ma
Department of Epidemiology and Health Statistics, School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, China.
Fen
F
Liu
Department of Molecular Physiology and Biophysics, Holden Comprehensive Cancer Center, University of Iowa Carver College of Medicine, Iowa City, IA, United States of America.
Lei
L
Zhao
Department of Cancer Epidemiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.
Wenqiang
W
Wei
D014408:Biomarkers, Tumor / Q000032:analysis; D006801:Humans; D016013:Likelihood Functions; D035683:MicroRNAs / Q000032:analysis*; D009369:Neoplasms / Q000175:diagnosis*; D016017:Odds Ratio; D012463:Saliva / Q000737:chemistry*; D012680:Sensitivity and Specificity
D014408:Biomarkers, Tumor; D035683:MicroRNAs