Analysis of 30 putative BRCA1 splicing mutations in hereditary breast and ovarian cancer families identifies exonic splice site mutations that escape in silico prediction

对遗传性乳腺癌和卵巢癌家族中 30 个假定的 BRCA1 剪接突变进行分析,确定了无法通过计算机预测的外显子剪接位点突变

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作者:Barbara Wappenschmidt, Alexandra A Becker, Jan Hauke, Ute Weber, Stefanie Engert, Juliane Köhler, Karin Kast, Norbert Arnold, Kerstin Rhiem, Eric Hahnen, Alfons Meindl, Rita K Schmutzler

Abstract

Screening for pathogenic mutations in breast and ovarian cancer genes such as BRCA1/2, CHEK2 and RAD51C is common practice for individuals from high-risk families. However, test results may be ambiguous due to the presence of unclassified variants (UCV) in the concurrent absence of clearly cancer-predisposing mutations. Especially the presence of intronic or exonic variants within these genes that possibly affect proper pre-mRNA processing poses a challenge as their functional implications are not immediately apparent. Therefore, it appears necessary to characterize potential splicing UCV and to develop appropriate classification tools. We investigated 30 distinct BRCA1 variants, both intronic and exonic, regarding their spliceogenic potential by commonly used in silico prediction algorithms (HSF, MaxEntScan) along with in vitro transcript analyses. A total of 25 variants were identified spliceogenic, either causing/enhancing exon skipping or activation of cryptic splice sites, or both. Except from a single intronic variant causing minor effects on BRCA1 pre-mRNA processing in our analyses, 23 out of 24 intronic variants were correctly predicted by MaxEntScan, while HSF was less accurate in this cohort. Among the 6 exonic variants analyzed, 4 severely impair correct pre-mRNA processing, while the remaining two have partial effects. In contrast to the intronic alterations investigated, only half of the spliceogenic exonic variants were correctly predicted by HSF and/or MaxEntScan. These data support the idea that exonic splicing mutations are commonly disease-causing and concurrently prone to escape in silico prediction, hence necessitating experimental in vitro splicing analysis.

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