Multilayer OMIC data in medullary thyroid carcinoma identifies the STAT3 pathway as a potential therapeutic target in RETM918T tumors

Abstract

Purpose: Medullary thyroid carcinoma (MTC) is a rare disease with few genetic drivers, and the etiology specific to each known susceptibility mutation remains unknown. Exploiting multilayer genomic data, we focused our interest on the role of aberrant DNA methylation in MTC development.Experimental Design: We performed genome-wide DNA methylation profiling assessing more than 27,000 CpGs in the largest MTC series reported to date, comprising 48 molecularly characterized tumors. mRNA and miRNA expression data were available for 33 and 31 tumors, respectively. Two human MTC cell lines and 101 paraffin-embedded MTCs were used for validation.Results: The most distinctive methylome was observed for RETM918T-related tumors. Integration of methylation data with mRNA and miRNA expression data identified genes negatively regulated by promoter methylation. These in silico findings were confirmed in vitro for PLCB2, DKK4, MMP20, and miR-10a, -30a, and -200c. The mutation-specific aberrant methylation of PLCB2, DKK4, and MMP20 was validated in 25 independent MTCs by bisulfite pyrosequencing. The methylome and transcriptome data underscored JAK/Stat pathway involvement in RETM918T MTCs. Immunostaining [immunohistochemistry (IHC)] for the active form of signaling effector STAT3 was performed in a series of 101 MTCs. As expected, positive IHC was associated with RETM918T-bearing tumors (P < 0.02). Pharmacologic inhibition of STAT3 activity increased the sensitivity to vandetanib of the RETM918T-positive MTC cell line, MZ-CRC-1.Conclusions: Multilayer OMIC data analysis uncovered methylation hallmarks in genetically defined MTCs and revealed JAK/Stat signaling effector STAT3 as a potential therapeutic target for the treatment of RETM918T MTCs.

This work was supported by the Fondo de Investigaciones Sanitarias (FIS) project PI14/00240 and the Comunidad de Madrid (Grant S2011/BMD-2328 TIRONET) to MR. LI-P is supported by the Centro de Investigacion Biomédica en Red de Enfermedades Raras (CIBERER). VM was supported by a predoctoral fellowship from the "la Caixa"/CNIO international PhD programme. CM-C is supported by a postdoctoral fellowship from the Fundación AECC.