Journal
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Volume 20, Issue 10, Pages -Publisher
MDPI
DOI: 10.3390/ijms20102536
Keywords
papillary thyroid cancer; genetic and epigenetic network; next-generation sequencing (NGS) data; carcinogenic biomarkers; genetic and epigenetic drug targets; drug data mining
Funding
- Ministry of Science and Technology [MOST 107-2221-E-007-112-MY3]
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Thyroid cancer is the most common endocrine cancer. Particularly, papillary thyroid cancer (PTC) accounts for the highest proportion of thyroid cancer. Up to now, there are few researches discussing the pathogenesis and progression mechanisms of PTC from the viewpoint of systems biology approaches. In this study, first we constructed the candidate genetic and epigenetic network (GEN) consisting of candidate protein-protein interaction network (PPIN) and candidate gene regulatory network (GRN) by big database mining. Secondly, system identification and system order detection methods were applied to prune candidate GEN via next-generation sequencing (NGS) and DNA methylation profiles to obtain the real GEN. After that, we extracted core GENs from real GENs by the principal network projection (PNP) method. To investigate the pathogenic and progression mechanisms in each stage of PTC, core GEN was denoted in respect of KEGG pathways. Finally, by comparing two successive core signaling pathways of PTC, we not only shed light on the causes of PTC progression, but also identified essential biomarkers with specific gene expression signature. Moreover, based on the identified gene expression signature, we suggested potential candidate drugs to prevent the progression of PTC with querying Connectivity Map (CMap).
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