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Verification of candidate microRNA markers for parathyroid carcinoma

Overview of attention for article published in Endocrine, February 2018
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Title
Verification of candidate microRNA markers for parathyroid carcinoma
Published in
Endocrine, February 2018
DOI 10.1007/s12020-018-1551-2
Pubmed ID
Authors

Ya Hu, Xiang Zhang, Ming Cui, Zhe Su, Mengyi Wang, Quan Liao, Yupei Zhao

Abstract

Parathyroid carcinoma (PCa) is a rare endocrine malignancy with poor prognosis and is often difficult to accurately diagnose both before and after surgery. Dysregulated microRNA (miRNA) levels have been identified in PCa using a limited number of samples. The aim of the present study was to verify a group of miRNA markers in a new series of samples to explore their potential significance in PCa diagnosis. A total of 58 tissue samples, including 17 PCa lesions and 41 sporadic parathyroid adenomas (PAds), were obtained from 56 primary hyperparathyroidism (pHPT) patients. Candidate miRNAs (miR-139-5p, miR-155-5p, miR-222-3p, miR-26b-5p, miR-296-5p, miR-30b-5p, miR-372-3p, miR-503-5p, miR-517c-3p, miR-7-5p, and miR-126-5p) were quantified by TaqMan real-time quantitative PCR assays. Up-regulated miR-222 (p = 0.041) levels and down-regulated miR-139 (p = 0.003), miR-30b (p < 0.001), miR-517c (p = 0.038), and miR-126* (p = 0.002) levels were found in PCa relative to PAd. Binary logistic regression analysis showed that miR-139 and miR-30b were the best diagnostic markers. The combination of miR-139 and miR-30b yielded an area under the receiver operating characteristic curve of 0.888. Additionally, serum calcium (rs = -0.518, p < 0.001), intact parathyroid hormone (iPTH) (rs = -0.495, p < 0.001), and alkaline phosphatase (ALP) (rs = -0.523, p < 0.001) levels were negatively correlated with miR-30b levels. miR-139, miR-222, miR-30b, miR-517c, and miR-126* were differentially expressed between PCa and PAd. The combined analysis of miR-139 and miR-30b may be used as a potential diagnostic strategy for distinguishing PCa from PAd.

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The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Postgraduate 2 20%
Student > Doctoral Student 1 10%
Other 1 10%
Researcher 1 10%
Student > Master 1 10%
Other 0 0%
Unknown 4 40%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 10%
Medicine and Dentistry 1 10%
Engineering 1 10%
Unknown 7 70%