Biomarker identification of medullary thyroid carcinoma from gene expression profiles considering without-treatment and with-treatment studies-A bioinformatics approach.

Abstract

Medullary thyroid carcinoma (MTC) is a neuroendocrine tumor derived from parafollicular thyroid gland cells. In both hereditary MTC and sporadic forms, genetic changes result in fundamental changes, and prognosis and mutational status are highly correlated. In this work, biomarker genes (DEGs and DEmiRNAs) for MTC will be computationally identified in order to help in their diagnosis and treatment. The gene expression profiles of two different types of studies, namely without-treatment (wo-trt) and with-treatment (w-trt), are considered for discovering biomarkers. The datasets were retrieved from the GEO database, and the DEGs and DEmiRNAs were analyzed using ExpressAnalyst and GEO2R. The functional analysis of DEGs and DEmiRNAs was performed, and most of the pathways enriched related to thyroid oncological pathways such as MAPK pathway,mTOR pathway, and PI3K-AKT Signaling pathway. Through this conclusion, the RET gene was upregulated wo-trt; the dinaciclib treatment RET gene was down-regulated computationally. To optimize the therapeutic targeting of RET, greater research into the mechanisms regulating RET transcription is necessary.