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DOI 10.1002/jcla.23233

Медицинская библиотека · Journal of clinical laboratory analysis · 2020

Circulating miRNAs as diagnostic biomarkers for multiple myeloma and monoclonal gammopathy of undetermined significance.

Li Jia, Zhang Man, Wang Chengbin

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Аннотация

BACKGROUND

Multiple myeloma (MM) is still an incurable hematological malignancy evolved from asymptomatic monoclonal gammopathy of undetermined significance (MGUS). New evidence suggests that circulating microRNAs (miRNAs) can serve as stable diagnostic biomarkers for MM and MUGS.

METHODS

Serum miRNAs in MM patients, MUGS patients, and healthy controls (HC) were performed by Agilent Bioanalyzer 2100. MicroRNAs in MM detected as promising biomarkers were validated by using quantitative real-time PCR (qRT-PCR). Receiver operator characteristic (ROC) curve and multivariate logistic analysis were used to evaluate the diagnostic value of miRNAs for MM and MUGS.

RESULTS

In microarray analysis, the top ten differential expressed miRNAs in MM included miR-134-5p, miR-107, miR-15a-5p, miR-5159-3p, miR-1914-3p, miR-4723-3p, miR-5588-3p, miR-6893-3p, miR-7106-3p, and miR-6722-5p. Three up-regulated miRNAs (miR-134-5p, miR-107, and miR-15a-5p) were further validated. The elevated expression levels of miR-134-5p, miR-107, and miR-15a-5p in qRT-PCR were increased consistent with microarray analysis. These miRNAs distinguished MM and MUGS from HC significantly. Multivariate logistic analysis showed combination miR-107, miR-15a-5p with Hb, the AUC was 0.954 (95% CI: 0.890-1.000), sensitivity of 91.3%, and specificity of 93.7% for distinguishing MM from MUGS.

CONCLUSIONS

These data demonstrate that miR-134-5p, miR-107, and miR-15a-5p are potential diagnostic biomarkers in MM and MUGS. Moreover, the combination miR-107 and miR-15a-5p with Hb can distinguish MM from MUGS.

Для цитирования: Li Jia, Zhang Man, Wang Chengbin. Circulating miRNAs as diagnostic biomarkers for multiple myeloma and monoclonal gammopathy of undetermined significance.. Journal of clinical laboratory analysis. 2020. DOI: 10.1002/jcla.23233.

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