RESUMO
PURPOSE: Medullary thyroid carcinoma (MTC) presents a distinct biological context from other thyroid cancers due to its specific cellular origin. This heterogeneous and rare tumor has a high prevalence of advanced diseases, making it crucial to address the limited therapeutic options and enhance complex clinical management. Given the high clinical accessibility of methylation information, we construct the largest MTC methylation cohort to date. EXPERIMENTAL DESIGN: Seventy-eight fresh-frozen MTC samples constituted our methylation cohort. The comprehensive study process incorporated machine learning, statistical analysis, and in vitro experiments. RESULTS: Our study pioneered the identification of a three-class clustering system for risk stratification, exhibiting pronounced epigenomic heterogeneity. The elevated overall methylation status in MTC-B, combined with the "mutual exclusivity" of hypomethylated sites displayed by MTC-A and MTC-C, distinctively characterized the MTC-specific methylation pattern. Integrating with the transcriptome, we further depicted the features of these three clusters to scrutinize biological properties. Several MTC-specific aberrant DNA methylation events were emphasized in our study. NNAT expression was found to be notably reduced in poor-prognostic MTC-C, with its promoter region overlapping with an upregulated differentially methylated region. In vitro experiments further affirmed NNAT's therapeutic potential. Moreover, we built an elastic-net logistic regression model with a relatively high AUC encompassing 68 probes, intended for future validation and systematic clinical application. CONCLUSIONS: Conducting research on diseases with low incidence poses significant challenges, and we provide a robust resource and comprehensive research framework to assist in ongoing MTC case inclusion and facilitate in-depth dissection of its molecular biological features.
