In-Silico Characterization of Human Her2 Gene to Predict the Breast Cancer Associated Biomarkers

Abstract

HER2 gene hyperactivation is responsible for the incidence of invasive breast cancer (BC). It leads to over expression of HER2 receptors in breast cells resulting in abnormal receptor dimerization and signal transduction cascade initiation. It ultimately causes uncontrolled proliferation of breast cells. Therefore, this is the most susceptible target gene for BC treatment. HER2 gene transcript with accession ID ENST00000269571.10 was selected for association analysis in present study. A total of ten single nucleotide polymorphisms (SNPs) of gene were analyzed using in-silico tools like CELLO, PROTPARAM, SOPMA, and SWISSMODEL. These tools helped in determining the effect of variants on sub-cellular localization, physiochemical properties, and secondary (2D) and tertiary (3D) structures of mutated proteins. Variants rs1249755832, rs769703068, rs1567913219, and rs1213602748 altered the localization of mutated proteins. SNPs rs1213602748, rs769703068, and rs1249755832 considerably changed the isoelectric point (pI), extinction coefficient, instability index, aliphatic index, and GRAVY. Variant rs769703068 caused a change in all four properties of the 2D structure, i.e., alpha helix, extended strand, beta-turn, and random coil. Polymorphisms that caused a significant deviation in 3D configuration were rs769703068, rs144434331, and rs146177313. These variants can be recommended as biomarkers for HER2+ BC cell diagnosis.