In silico annotation of follicular thyroid neoplasm associated metabolic pathways and involved biomarkers: An aid to diagnosis

Abstract

The follicular thyroid neoplasm (FTN) is like an unsolved puzzle at some stage in preoperative diagnosis. Usually, for preliminary characterization of thyroid lesions, clinicians depend much on fine-needle aspiration cytology (FNAC). However, in the case of FTN, FNAC cannot distinguish between benign and malignant entities, as both are exhibiting predominant follicular architecture. Cytological/ architectural/ or cellular criteria alone is not enough to differentiate Follicular adenoma (FA), Follicular thyroid carcinoma (FTC), Follicular variant of papillary thyroid carcinoma (FVPTC) together with Non-Invasive Follicular variant of Papillary Thyroid Carcinoma (NIFTP), Encapsulated FVPTC (EFVPTC) and well-differentiated neoplasm of uncertain malignant potential. Thus, the genetic analysis can be used as a novel diagnostic approach that should be applied with the traditional method for easy diagnosis of follicular thyroid neoplasm, which reduces the risk of unnecessary surgeries. This present study tried to explore the current genetic assessment of FTN through review of the genetics of FTN studied from 2009 to 2019 which showed the characterization of differential gene expression in these follicular neoplasms some extent. Also, pathway analysis has potentially implemented to minimize the diagnosis dilemma. In addition to the previously identified pathways and associated target genes, some novel endocrine cancer-related pathways with putative target genes of FTN have been remoted from characterizing tumor with follicular pattern. The observed genes might be considered as diagnostic biomarker in the respective FTN associated metabolic pathways.