Gene mutations are a source of genetic instability which fuels the progression of cancer. Mutations in and are considered as major drivers in the progression of breast cancer and their detection indispensable for devising therapeutic and management approaches. The current study aims to identify novel pathogenic and recurrent mutations in and in Pakhtun population from the Khyber Pakhtunkhwa. To determine the and pathogenic mutation prevalence in Pakhtun population from KP, whole exome sequencing of 19 patients along with 6 normal FFPE embedded blocks were performed. The pathogenicity of the mutations were determined and they were further correlated with different hormonal, sociogenetic and clinicopathological features. We obtained a total of 10 mutations (5 somatic and 5 germline) in while 27 mutations (24 somatic and 3 germline) for . Five and seventeen pathogenic or deleterious mutations were identified in and respectively by examining the mutational spectrum through SIFT, PolyPhen-2 and Mutation Taster. Among the SNVs, were identified as mutations of the interaction sites as predicted by the deep algorithm based ISPRED-SEQ prediction tool. SAAFEQ-SEQ web-based algorithm was used to calculate the changes in free energy and effect of SNVs on protein stability. All SNVs were found to have a destabilizing effect on the protein. ConSurf database was used to determine the evolutionary conservation scores and nature of the mutated residues. Gromacs 4.5 was used for the molecular simulations. Ramachandran plots were generated using procheck server. STRING and GeneMania was used for prediction of the gene interactions. The highest number of mutations ( 7/10, 70 %) were on exon 9 and (, 11/27; 40 %) were on exon 11. 40 % and 60 % of the mutations were associated Grade 2 and Grade 3 tumors respectively. The present study reveals unique and mutations in Pakhtun population. We further suggest sequencing of the large cohorts for further characterizing the pathogenic mutations.

中文翻译：

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巴基斯坦开伯尔-普赫图赫瓦省 (KP) 普赫图族乳腺癌患者 BRCA1 和 BRCA2 基因突变谱的初步研究

基因突变是遗传不稳定性的根源，会加速癌症的进展。突变被认为是乳腺癌进展的主要驱动因素，其检测对于设计治疗和管理方法必不可少。目前的研究旨在鉴定开伯尔-普赫图赫瓦省普赫图族群中的新致病性和复发性突变。为了确定来自 KP 的 Pakhtun 人群的致病性突变患病率，对 19 名患者以及 6 个正常 FFPE 嵌入块进行了全外显子组测序。突变的致病性已被确定，并进一步与不同的激素、社会遗传学和临床病理学特征相关。我们总共获得了 10 个突变（5 个体细胞和 5 个种系），而 27 个突变（24 个体细胞和 3 个种系）。通过 SIFT、PolyPhen-2 和 Mutation Taster 检查突变谱，分别鉴定出 5 种和 17 种致病或有害突变。在 SNV 中，根据基于深度算法的 ISPRED-SEQ 预测工具的预测，被鉴定为相互作用位点的突变。 SAAFEQ-SEQ 基于网络的算法用于计算自由能的变化以及 SNV 对蛋白质稳定性的影响。所有 SNV 均被发现对蛋白质具有不稳定作用。 ConSurf 数据库用于确定进化保守分数和突变残基的性质。 Gromacs 4.5 用于分子模拟。 Ramachandran 图是使用 procheck 服务器生成的。 STRING 和 GeneMania 用于预测基因相互作用。最高数量的突变 (7/10, 70%) 位于外显子 9 上，(11/27; 40%) 位于外显子 11 上。40% 和 60% 的突变分别与 2 级和 3 级肿瘤相关。本研究揭示了 Pakhtun 人群的独特突变。我们进一步建议对大群体进行测序，以进一步表征致病突变。