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Pathogenicity assessment of variants for breast cancer susceptibility genes based on BRCAness of tumor sample

机译:基于肿瘤样本Brcaness的乳腺癌敏感基因变体的致病性评估

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摘要

Genes involved in the homologous recombination repair pathway—as exemplified by BRCA1, BRCA2, PALB2, ATM, and CHEK2—are frequently associated with hereditary breast and ovarian cancer syndrome. Germline mutations in the loci of these genes with loss of heterozygosity or additional somatic truncation at the WT allele lead to the development of breast cancers with characteristic clinicopathological features and prominent genomic features of homologous recombination deficiency, otherwise referred to as “BRCAness.” Although clinical genetic testing for these and other genes has increased the chances of identifying pathogenic variants, there has also been an increase in the prevalence of variants of uncertain significance, which poses a challenge to patient care because of the difficulties associated with making further clinical decisions. To overcome this challenge, we sought to develop a methodology to reclassify the pathogenicity of these unknown variants using statistical modeling of BRCAness. The model was developed with Lasso logistic regression by comparing 116 genomic attributes derived from 37 BRCA1/2 biallelic mutant and 32 homologous recombination‐quiescent breast cancer exomes. The model showed 95.8% and 86.7% accuracies in the training cohort and The Cancer Genome Atlas validation cohort, respectively. Through application of the model for variant reclassification of homologous recombination‐associated hereditary breast and ovarian cancer causal genes and further assessment with clinicopathological features, we finally identified one likely pathogenic and five likely benign variants. As such, the BRCAness model developed from the tumor exome was robust and provided a reasonable basis for variant reclassification.
机译:参与同源重组修复途径的基因 - 如BRCA1,BRCA2,PALB2,ATM和Chek2常用于遗传性乳腺癌和卵巢癌综合征。这些基因位点的种系突变随着WT等位基因的杂合子或另外的体细胞截短导致具有特征临床病理特征和同源重组缺乏的突出特征的乳腺癌的发育,否则被称为“BRCANESS”。虽然这些和其他基因的临床遗传测试增加了鉴定致病变异的可能性,但由于与进一步临床决策相关的困难,这也存在不确定意义的变异患病率的增加。 。为了克服这一挑战,我们试图制定一种方法来利用Brcaness的统计建模来重新分类这些未知变体的致病性。通过比较来自37 brca1 / 2双挠曲突变体和32种同源重组静脉乳腺癌突出的116个基因组属性,通过洛索逻辑回归开发了该模型。该模型分别在培训队列和癌症基因组地图集验证队列中显示出95.8%和86.7%的准确性。通过应用模型进行同源重组相关遗传性乳腺癌和卵巢癌因果基因的变异重新分类和进一步评估临床病理特征,我们最终确定了一种可能的致病和五种可能的良性变异。因此,从肿瘤外壳开发的BRCaness模型是稳健的,为变体重估提供了合理的基础。

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