Exome Data Analysis in the Discovery of Variants Associated with Breast Cancer Metastasis and Their Implications on Protein Structure

Abstract

Understanding the correlation between heterogeneity in terms of genomic alterations and metastatic behavior is crucial in improving outcomes for breast cancer patients. Exome sequence that encode proteins generally encompasses around 2% of the genome, and is believed to harbor up to 85% of all disease causing variants. In this study, whole exome data from primary, metastatic and matched normal breast cancer samples submitted by Memorial Sloan Kettering Cancer Center (PRJNA273304) was deep dived using GATK pipeline, specifically Haplotypecaller was employed for variant calling and filtered using annovar. Impact of the identified mutations on the structure of the proteins was also analyzed. Variation in TOGARAM2, C3orf18, S100Z, MYH15, EPB41L4A, LARP1B, NAALADL2, OR2W3 and OR2AK2 were found in all nine primary and metastatic samples. None of these variants were previously reported to be associated with any disease conditions. Based on the structural availability of templates, MODELLER was utilized to build the three-dimensional structures of S100Z, MYH15, NAALADL2, OR2W3 and OR2AK2, and validated using the web based PROCHECK server. Lastly, molecular dynamics was carried out to evaluate the stability of the modeled proteins. Except OR2W3, all other mutant proteins exhibited significant RMSD deviation in the simulation studies substantiating the role of mutations. We conclude that the mutations identified can be useful in recognizing patients with breast cancer who are likely to develop remote metastases.