Prognostic Classifier Based on Genome-Wide DNA Methylation Profiling in Well-Differentiated Thyroid Tumors

Mariana Bisarro Dos Reis, Mateus Camargo Barros-Filho, Fábio Albuquerque Marchi, Caroline Moraes Beltrami, Hellen Kuasne, Clóvis Antônio Lopes Pinto, Srikant Ambatipudi, Zdenko Herceg, Luiz Paulo Kowalski, Silvia Regina Rogatto

Research output: Contribution to journalArticle (Academic Journal)peer-review

42 Citations (Scopus)
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Context: Even though the majority of well-differentiated thyroid carcinoma (WDTC) is indolent, a number of cases display an aggressive behavior. Cumulative evidence suggests that the deregulation of DNA methylation has the potential to point out molecular markers associated with worse prognosis.

Objective: To identify a prognostic epigenetic signature in thyroid cancer.

Design: Genome-wide DNA methylation assays (450k platform, Illumina) were performed in a cohort of 50 nonneoplastic thyroid tissues (NTs), 17 benign thyroid lesions (BTLs), and 74 thyroid carcinomas (60 papillary, 8 follicular, 2 Hürthle cell, 1 poorly differentiated, and 3 anaplastic). A prognostic classifier for WDTC was developed via diagonal linear discriminant analysis. The results were compared with The Cancer Genome Atlas (TCGA) database.

Results: A specific epigenetic profile was detected according to each histological subtype. BTLs and follicular carcinomas showed a greater number of methylated CpG in comparison with NTs, whereas hypomethylation was predominant in papillary and undifferentiated carcinomas. A prognostic classifier based on 21 DNA methylation probes was able to predict poor outcome in patients with WDTC (sensitivity 63%, specificity 92% for internal data; sensitivity 64%, specificity 88% for TCGA data). High-risk score based on the classifier was considered an independent factor of poor outcome (Cox regression, P < 0.001).

Conclusions: The methylation profile of thyroid lesions exhibited a specific signature according to the histological subtype. A meaningful algorithm composed of 21 probes was capable of predicting the recurrence in WDTC.

Original languageEnglish
Pages (from-to)4089-4099
Number of pages11
JournalJournal of Clinical Endocrinology and Metabolism
Issue number11
Publication statusPublished - 1 Nov 2017

Structured keywords

  • ICEP


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