Dataset Information

Altered Serum MicroRNA Profile May Serve as an Auxiliary Tool for Discriminating Aggressive Thyroid Carcinoma from Nonaggressive Thyroid Cancer and Benign Thyroid Nodules.

ABSTRACT: Thyroid cancers are the most common malignancy of the endocrine system; however, there is no reliable blood biomarkers for thyroid cancer diagnosis and even for aggressive and nonaggressive thyroid cancers as well as benign nodule discrimination. The present study is aimed at evaluating whether circulating microRNA (miRNA) can differentiate aggressive and nonaggressive thyroid cancer from benign thyroid nodules. In this study, we performed a multiphase, case-control study to screen serum miRNA expression profile in 100 patients with papillary thyroid cancer (PTC), 15 patients with aggressive medullary thyroid carcinoma (MTC), 91 patients with benign nodules, and 89 healthy controls using TaqMan low-density array followed by extensive reverse transcription quantitative real-time PCR validation. The results showed that the serum levels of miR-222-3p, miR-17-5p, and miR-451a were markedly increased, while miR-146a-5p, miR-132-3p, and miR-183-3p were significantly decreased in the PTC and benign nodule groups compared with the control group. There was no difference in the miRNA expression profile between the PTC group and the benign nodule group. Nevertheless, the serum levels of miR-222-3p and miR-17-5p were significantly increased in the MTC group than the benign nodule and control group. Moreover, receiver operating characteristic curve analyses demonstrated that the 2 miRNAs and their panel can accurately discriminate MTC from the benign nodule group and healthy controls. These findings indicated that the altered circulating miRNAs may discriminate PTC and benign thyroid nodules from controls, and serum miR-222-3p and miR-17-5p have the potential to serve as auxiliary tools for diagnosing more aggressive thyroid carcinomas, such as MTC.

SUBMITTER: Zhang A

PROVIDER: S-EPMC6766139 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Altered Serum MicroRNA Profile May Serve as an Auxiliary Tool for Discriminating Aggressive Thyroid Carcinoma from Nonaggressive Thyroid Cancer and Benign Thyroid Nodules.

Zhang Aisen A Wang Cheng C Lu Hui H Chen Xi X Ba Yi Y Zhang Chunni C Zhang Chen-Yu CY

Disease markers 20190916

Thyroid cancers are the most common malignancy of the endocrine system; however, there is no reliable blood biomarkers for thyroid cancer diagnosis and even for aggressive and nonaggressive thyroid cancers as well as benign nodule discrimination. The present study is aimed at evaluating whether circulating microRNA (miRNA) can differentiate aggressive and nonaggressive thyroid cancer from benign thyroid nodules. In this study, we performed a multiphase, case-control study to screen serum miRNA e ...[more]

PMID: 31636734

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Project description:BACKGROUND: Novel biomarkers are urgently needed to distinguish between benign and malignant thyroid nodules and detect thyroid cancer in the early stage. The associations between serum IgG N-glycosylation and thyroid cancer risk have been revealed. We aimed to explore the potential of IgG N-glycan traits as biomarkers in the differential diagnosis of thyroid cancer.METHODS: Plasma IgG N-glycome analysis was applied to a discovery cohort followed by independent validation. IgG N-glycan profiles were obtained using a robust quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. IgG N-glycans were relatively quantified, and classification performance was evaluated based on directly detected and derived glycan traits.RESULTS: Four directly detected glycans were significantly changed in thyroid cancer patients compared to that in non-cancer controls. Derived glycan traits and a classification glycol-panel were generated based on the directly detected glycan traits. In the discovery cohort, derived trait BN (bisecting type neutral N-glycans) and the glyco-panel showed potential in distinguishing between thyroid cancer and non-cancer controls with AUCs of 0.920 and 0.917, respectively. The diagnostic potential was further validated. Derived trait BN and the glycol-panel displayed “accurate” performance (AUC>0.8) in discriminating thyroid cancer from benign thyroid nodules and healthy controls in the validation cohort. Meanwhile, derived trait BN and the glycol-panel also showed diagnostic potential in detecting early-stage thyroid cancer.CONCLUSIONS: IgG N-glycome analysis revealed N-glycomic differences that allow classification of thyroid cancer from non-cancer controls. Our results suggested that derived trait BN and the classification glyco-panel rather than single N-glycans may serve as candidate biomarkers for further validation.

Project description:Background A dynamic artificial intelligence (AI) ultrasonic intelligent assistant diagnosis system (dynamic AI) is a joint application of AI technology and medical imaging, which can conduct real-time synchronous dynamic analysis of nodules from multiple sectional views with different angles. This study explored the diagnostic value of dynamic AI for benign and malignant thyroid nodules in patients with Hashimoto thyroiditis (HT) and its significance in guiding surgical treatment strategies. Methods Data of 487 patients (154 with and 333 without HT) with 829 thyroid nodules who underwent surgery were collected. Differentiation of benign and malignant nodules was performed using dynamic AI, and diagnostic effects (specificity, sensitivity, negative predictive value, positive predictive value, accuracy, misdiagnosis rate and missed diagnosis rate) was assessed. Differences in diagnostic efficacy were compared among AI, preoperative ultrasound based on the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS), and fine needle aspiration cytology (FNAC) diagnoses. Results The accuracy, specificity and sensitivity of dynamic AI reached 88.06%, 80.19%, and 90.68%, respectively; besides, there was consistency with postoperative pathological consequences (κ=0.690; P<0.001). The diagnostic efficacy of dynamic AI was equivalent between patients with and without HT, and there were no significant differences in sensitivity, specificity, accuracy, positive predictive value, negative predictive value, missed diagnosis rate, and misdiagnosis rate. In patients with HT, dynamic AI had significantly higher specificity and a lower misdiagnosis rate than did preoperative ultrasound based on the ACR TI-RADS (P<0.05). Compared with FNAC diagnosis, dynamic AI had a significantly higher sensitivity and a lower missed diagnosis rate (P<0.05). Conclusions Dynamic AI possessed an elevated diagnostic worth of malignant and benign thyroid nodules in patients with HT, which can provide a new method and valuable information for the diagnosis and development of management strategy of patients.

Dataset Information

Altered Serum MicroRNA Profile May Serve as an Auxiliary Tool for Discriminating Aggressive Thyroid Carcinoma from Nonaggressive Thyroid Cancer and Benign Thyroid Nodules.

Publications

Altered Serum MicroRNA Profile May Serve as an Auxiliary Tool for Discriminating Aggressive Thyroid Carcinoma from Nonaggressive Thyroid Cancer and Benign Thyroid Nodules.

Similar Datasets

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