title: Identification and Evaluation of Serum MicroRNA-29 Family for Glioma Screening.
abstract: Glioma is one of the most common primary central nervous system tumors with high mortality and poor 5-year survival rate. Current diagnostic methods for glioma were either invasive or expensive. MicroRNAs (miRNAs) are small non-coding RNAs which play an important part in the regulation of gene expression. Considering the fact that miRNAs are stable in serum, plasma, urine, and other body fluids, they show great promises to be convenient and non-invasive biomarkers for cancers. This study aimed at evaluating the availability of serum microRNA-29 (miR-29) family in screening of glioma. A meta-analysis was also performed to assess the predictive value of miR-29 family in multi-cancer screening. Serum samples were collected from 83 glioma patients at different stages and 69 healthy controls. RNA was extracted and the relative expression of serum miR-29 was acquired by qRT-PCR and calculated by Cycle threshold (Ct) with microRNA-24 as an internal control. In the meta-analysis, studies concerning the predictive value of miR-29 family in cancer were retrieved. The predictive value of serum miR-29 family for glioma was moderate (AUC = 0.74). But the predictive value of serum miR-29 family in high-graded glioma detection was sufficient (AUC = 0.81). Also, serum miR-29 family might not be applicable in early-stage glioma detection (AUC = 0.66). A high predictive value of miR-29 family in multi-cancer detection was observed from meta-analysis (AUC = 0.83). This study manifested that serum miR-29 family could be applied as a biomarker for high-graded glioma screening, but the sensitivity and specificity for low-graded glioma detection might not be sufficient. A meta-analysis concerning the predictive value of miR-29 family in multi-cancer detection concluded that miR-29 family might be a sufficient universal biomarker for cancer.
authors.affiliation: The Affiliated Drum Tower Hospital, Medical School, Nanjing University, Hankou Road 22#, Nanjing, Jiangsu, 210093, China.
authors.forename: Junhua
authors.initials: J
authors.lastname: Wu
authors.affiliation: School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China.
authors.forename: Liwen
authors.initials: L
authors.lastname: Li
authors.affiliation: The Affiliated Drum Tower Hospital, Medical School, Nanjing University, Hankou Road 22#, Nanjing, Jiangsu, 210093, China. chunpingjiang@yeah.net.
authors.forename: Chunping
authors.initials: C
authors.lastname: Jiang
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000097:blood*; D001932:Brain Neoplasms / Q000097:blood*; D016022:Case-Control Studies; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D005909:Glioblastoma / Q000097:blood; D005910:Glioma / Q000097:blood* / Q000473:pathology; D006801:Humans; D008297:Male; D035683:MicroRNAs / Q000097:blood*; D008875:Middle Aged; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D012372:ROC Curve; D012307:Risk Factors; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; C532045:MIRN29a microRNA, human; D035683:MicroRNAs
keywords: Glioma; Meta-analysis; MicroRNA-29 family; Screening; Serum