Abstract B234: Large scale analysis of miRNA expresion and in silico prediction of regulatory networks in thyroid cancer progression.
Authors: Geraldo Murilo V. , Kimura Edna T. 
Published: August 2014

Introduction: Papillary thyroid carcinoma (PTC) is a well differentiated tumor that accounts for more than 80% of the thyroid cancer cases. Although PTC presents good prognosis, about 5% of the cases present a more aggressive behavior, evolving to poorly differentiated thyroid carcinoma (PDTC) and becoming refractory to chemo and radioiodine therapy. Recent studies indicate a positive correlation between the more aggressive PTC phenotype and the point mutation in B-RAF proto-oncogene BRAFT1799A. microRNAs (miRNAs), small non-coding RNAs involved in post-transcriptional gene regulation, emerged as promising molecular markers and targets for cancer therapy, including for PTC. However, the role of miRNAs in PTC progression remains unclear, particularly regarding to the dedifferentiation observed in the more aggressive PTCs.

Materials: Transgenic FVB/N mice with thyroid-targeted expression of the oncogene BRAFT1799A, Tg-BRAF mice, which present locally invasive well-differentiated PTC at 5 weeks, and areas of poorly differentiated thyroid cancer after 12 weeks. Human thyroid cell lines N-Thy-ORI (normal), TPC-1 and BCPAP (PTC) and KTC-2 (PDTC).

Results: To identify differentially expressed miRNAs related to loss of differentiation during progression of PTC, we performed large scale analysis of miRNA expression of thyroid glands extracted from Tg-BRAF mice with 1, 5, 12 and 30 weeks, and of 4 human thyroid cell lines presenting different degrees of differentiation. Experimental validation of 8 de-regulated miRNAs genes (5 up- and 3 down-regulated) confirmed the expression pattern observed in large scale analysis. Based on the hypothesis that these miRNAs could cooperate to regulate the same mRNA targets, we used in silico approaches and publicly available GEO-datasets from normal thyroid tissue, well and poorly differentiated thyroid carcinoma, to generate two regulatory networks of predicted targets of the differentially expressed miRNAs during PTC progression. Interestingly, Kegg orthology analysis of the resulting regulatory networks revealed that the subset of up-regulated miRNAs negatively regulates the PI3K-AKT signaling pathway, by repressing its downstream targets BCL2 and CREB1. On the other hand, the regulatory network regulated by under-expressed miRNAs potentially regulates RNA splicing and transport by regulating the RNA binding protein RBM8A. Additionally the MAPK and TGF-beta signaling pathways, important mediators of epithelial-to-mesenchymal transition and cell survival, respectively, are potentially regulated by under-expressed miRNAs by targeting TGF-beta receptor 2 and RAF1.

Conclusion: Our large scale analysis followed by an in silico approach identified a potential regulatory network of post-transcriptional regulation that could explain the aggressive behavior of this subtype of PTC. Moreover, the further investigation of the disrupted regulatory networks in PTC, as well as the modulation of miRNA genes, could open up perspectives for the development of new therapeutic strategies for aggressive PTC.

Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B234.

Citation Format: Murilo V. Geraldo, Edna T. Kimura. Large scale analysis of miRNA expresion and in silico prediction of regulatory networks in thyroid cancer progression. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B234.