Long Non-Coding RNAs as Determinants of Thyroid Cancer Phenotypes: Investigating Differential Gene Expression Patterns and Novel Biomarker Discovery.

Thyroid Cancer (TC) is the most common endocrine malignancy, with increasing incidence globally. Papillary thyroid cancer (PTC), a differentiated form of TC, accounts for approximately 90% of TC and occurs predominantly in women of childbearing age. Although responsive to current treatments, recurrence of PTC by middle age is common and is much more refractive to treatment. Undifferentiated TC, particularly anaplastic thyroid cancer (ATC), is the most aggressive TC subtype, characterized by it being resistant and unresponsive to all therapeutic and surgical interventions. Further, ATC is one of the most aggressive and lethal malignancies across all cancer types. Despite the differences in therapeutic needs in differentiated vs. undifferentiated TC subtypes, there is a critical unmet need for the identification of molecular biomarkers that can aid in early diagnosis, prognosis, and actionable therapeutic targets for intervention. Advances in the field of cancer genomics have enabled for the elucidation of differential gene expression patterns between tumors and healthy tissue. A novel category of molecules, known as non-coding RNAs, can themselves be differentially expressed, and extensively contribute to the up- and downregulation of protein coding genes, serving as master orchestrators of regulated and dysregulated gene expression patterns. These non-coding RNAs have been identified for their roles in driving carcinogenic patterns at various stages of tumor development and have become attractive targets for study. The identification of specific genes that are differentially expressed can give insight into mechanisms that drive carcinogenic patterns, filling the gaps of deciphering molecular and cellular processes that modulate TC subtypes, outside of well-known driver mutations.

Dysregulated Expression Patterns of Circular RNAs in Cancer: Uncovering Molecular Mechanisms and Biomarker Potential.

Circular RNAs (circRNAs) are stable, enclosed, non-coding RNA molecules with dynamic regulatory propensity. Their biogenesis involves a back-splicing process, forming a highly stable and operational RNA molecule. Dysregulated circRNA expression can drive carcinogenic and tumorigenic transformation through the orchestration of epigenetic modifications via extensive RNA and protein-binding domains. These multi-ranged functional capabilities have unveiled extensive identification of previously unknown molecular and cellular patterns of cancer cells. Reliable circRNA expression patterns can aid in early disease detection and provide criteria for genome-specific personalized medicine. Studies described in this review have revealed the novelty of circRNAs and their biological ss as prognostic and diagnostic biomarkers.

Interactome of Long Non-Coding RNAs: Transcriptomic Expression Patterns and Shaping Cancer Cell Phenotypes.

RNA biology has gained extensive recognition in the last two decades due to the identification of novel transcriptomic elements and molecular functions. Cancer arises, in part, due to the accumulation of mutations that greatly contribute to genomic instability. However, the identification of differential gene expression patterns of wild-type loci has exceeded the boundaries of mutational study and has significantly contributed to the identification of molecular mechanisms that drive carcinogenic transformation. Non-coding RNA molecules have provided a novel avenue of exploration, providing additional routes for evaluating genomic and epigenomic regulation. Of particular focus, long non-coding RNA molecule expression has been demonstrated to govern and direct cellular activity, thus evidencing a correlation between aberrant long non-coding RNA expression and the pathological transformation of cells. lncRNA classification, structure, function, and therapeutic utilization have expanded cancer studies and molecular targeting, and understanding the lncRNA interactome aids in defining the unique transcriptomic signatures of cancer cell phenotypes.