Abstract 3358: Epigenetic signatures associated with patient outcome in thyroid carcinoma

Abstract

BACKGROUND: Thyroid cancer (TC) is the most frequent endocrine neoplasia composed essentially by well-differentiated tumors (90%). These tumors generally are indolent and the patients show a favorable outcome. However, a set of TC patients presents aggressive outcome. Global deregulation of DNA methylation has been described as involved in thyroid cancer (TC) development. In this study, DNA methylation profile was performed aiming to identify a prognostic signature in TC. PATIENTS AND METHODS: The methylation profile of 50 non-neoplastic thyroid tissues (NT), 17 benign thyroid lesions and 74 TC (60 papillary, 8 follicular, 2 Hürthle cell, 1 poorly differentiated and 3 anaplastic thyroid carcinomas) were investigated using the Methylation 450 Human Infinium®BeadChip platform (Illumina). The data were normalized and analyzed using SVA, wateRmelon and LIMMA packages. The threshold delta beta of 0.2 and adjusted p-value <0.05 were used to identify differentially methylated probes among the histological subtypes. The delta beta of 0.1 and adjusted p-value <0.05 were used in the prognostic features analysis in WDTC (well differentiated thyroid cancer) cases. An epigenetic classifier according to WDTC was identified using diagonal linear discriminant analysis. The results were compared with The Cancer Genome Atlas (TCGA) database. RESULTS: Methylation analyses revealed a specific epigenetic profile according to the histological subtypes. A global hypermethylation was observed in benign lesions and follicular carcinomas, while papillary and undifferentiated carcinomas were widely hypomethylated compared with NT. An epigenetic signature comprising 21 probes differentially methylated (delta beta 0.1) was able to predict poor outcome in WDTC patients. This classifier reveled 63% of sensitivity and 92% of specificity, which was confirmed by TCGA database (64% of sensitivity and 88% of specificity). Using the established signature, we were able to confirm the involvement of poor prognosis markers with high-risk scores (multivariable analysis; P<0.001). CONCLUSION: Thyroid tumors showed different methylation profile according to the histological subtypes. Genes regulated by methylation in TC and associated with the tumor development were identified and confirmed by TCGA. In addition, a meaningful algorithm was designed and confirmed as capable to predict recurrence in WDTC. FINANCIAL SUPPORT: FAPESP (2015/20548-5) and National Institute of Science and Technology in Oncogenomics (FAPESP 2008/57887-9 and CNPq 573589/08-9), CNPq (302606/2011-4). Note: This abstract was not presented at the meeting. Citation Format: Mariana Bisarro dos Reis, Caroline Moraes Beltrami, Mateus Camargo Barros-Filho, Fabio Albuquerque Marchi, Hellen Kuasne, Skirant Ambatipudi, Zdenko Herceg, Luiz Paulo Kowalski, Silvia Regina Rogatto. Epigenetic signatures associated with patient outcome in thyroid carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3358. doi:10.1158/1538-7445.AM2017-3358