Abstract

Breast cancer is one of the most common cancers among the women around the world. Several genes are known to be responsible for conferring the susceptibility to breast cancer. Among them, TP53 is one of the major genetic risk factor which is known to be mutated in many of the breast tumor types. TP53 mutations in breast cancer are known to be related to a poor prognosis and chemo resistance. This renders them as a promising molecular target for the treatment of breast cancer. In this study, we present a computational based screening and molecular dynamic simulation of breast cancer associated deleterious non-synonymous single nucleotide polymorphisms in TP53. We have predicted three deleterious coding non-synonymous single nucleotide polymorphisms rs11540654 (R110P), rs17849781 (P278A) and rs28934874 (P151T) in TP53 with a phenotype in breast tumors using computational tools SIFT, Polyphen-2 and MutDB. We have performed molecular dynamics simulations to study the structural and dynamic effects of these TP53 mutations in comparison to the wild-type protein. Results from our simulations revealed a detailed consequence of the mutations on the p53 DNA-binding core domain that may provide insight for therapeutic approaches in breast cancer.

Highlights

  • One of the common malignancies and leading causes of cancer death faced by women around the world is breast cancer

  • We have focused on the nonsynonymous coding SNPs (nSNPs) in the coding region of TP53 gene having an impact on breast cancer phenotype

  • We have explored the possible relationship between genetic mutation and phenotypic variation using different computational algorithm tools Sorting Tolerant From Intolerant’ (SIFT), PolyPhen-2 and Mutdb for prioritizing the deleterious breast cancer associated nSNPs from dbSNP datasets

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Summary

Introduction

One of the common malignancies and leading causes of cancer death faced by women around the world is breast cancer. Some of the common risk factors for breast cancer can be broadly categorized into two types i.e., genetic and non genetic. Among these two risk factors, genetic risk factors constitute 5–10% of the breast cancer cases. Studies showed that fifty one variants in 40 genes are significantly associated with breast cancer risk and among them variants in six genes i.e., BRCA1, BRCA2, TP53, PTEN, STK11 and CDH1 show strong association whereas variants in four genes i.e., ATM, CHEK2, BRIP1, PALB2 show moderate association and approximately 20 variants in other genes show weak association [3,4]

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