Sahar Madani, Irine Gotsiridze
Cancer has long been a complex and puzzling disease for humans to understand. It is primarily caused by the mutation of two groups of genes known as oncogenes and tumor suppressor genes (TSGs). Certain inherited medical conditions can increase the risk of developing more common forms of thyroid cancer associated with these genes. Uncommon genetic conditions have also been linked to higher rates of thyroid cancer. The genes associated with thyroid cancer are an ideal model for investigating the effects of selection at different stages of thyroid cancer.
A study is currently underway to identify patterns of positive selection in seven highly mutated genes associated with thyroid cancer through a detailed phylogenetic analysis. The nucleotide sequences for these genes were obtained from the Ref Seq database at the National Center for Biotechnology Information (NCBI) and aligned using the Muscle software. The best-fit model for nucleotide substitution was chosen using JMODELTEST, and the corresponding phylogenetic trees were constructed using PAML. The CODMEL software was used to calculate the non-synonymous to synonymous ratio and to select the most plausible evolutionary model for each gene.
The results of the analysis revealed that three genes (BDP1, TG, and TNN) showed strong signatures for positive selection, with p-values of 8.49E-18, 0.002, and 1.75E-87, respectively. The study is ongoing, and the analysis will be extended to the non-coding part to increase the evidence of positive selection on these genes. The aim is to better understand the evolutionary history of thyroid cancer-related genes, enrich the evidence data for the positively selected sites, and improve our understanding of the functionalities of these proteins, domains, and motifs. This could potentially provide valuable insights into drug-targeting sites.