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01.12.2018 | Research article | Ausgabe 1/2018 Open Access

BMC Cancer 1/2018

Serum microRNA signatures and metabolomics have high diagnostic value in gastric cancer

Zeitschrift:
BMC Cancer > Ausgabe 1/2018
Autoren:
Hai-Ning Liu, Hao Wu, Yu-Jen Tseng, Yan-Jie Chen, Dan-Ying Zhang, Lin Zhu, Ling Dong, Xi-Zhong Shen, Tao-Tao Liu
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12885-018-4343-4) contains supplementary material, which is available to authorized users.

Abstract

Background

Many novel diagnostic biomarkers have been developed for gastric cancer (GC) recently. We chose two methods with high diagnostic value, the detection of serum microRNAs and metabolomics based on gas chromatography/mass spectrometry (GC/MS), and aimed to establish appropriate models.

Methods

We reviewed the diagnostic accuracies of all microRNAs identified by previous diagnostic tests. Then appropriate microRNAs and their combinations were validated the diagnostic value. We included 80 patients with GC and 82 healthy controls (HCs) and detected the expression of the microRNAs. GC/MS analysis was conducted, and we used three multivariate statistical analyses to establish diagnostic models. The concentrations of carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA19–9) were detected for comparison with the novel models.

Results

Sixty-seven published studies and 70 microRNAs were finally included in the systematic review. MiR-18a, miR-19a, miR-21, miR-92a, miR-199a and miR-421 were chosen to further validate their diagnostic efficiencies. Five of those microRNAs in GC patients had significantly different expression. The combination of miR-19a and miR-92a had the highest area under the curve (AUC) at 0.850 with a sensitivity of 91.3% and a specificity of 61.0%. The GC/MS analysis performed an excellent diagnostic value and the AUC reached 1.0.

Conclusion

There is a good potential for microRNAs and GC/MS analysis as new diagnostic methods in view of their high diagnostic value compared with traditional biomarkers.
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