Exon splicing analysis of intronic variants in multigene cancer panel testing for hereditary breast/ovarian cancer

Jin Sun Ryu, Hye Young Lee, Eun Hae Cho, Kyong Ah Yoon, Min Kyeong Kim, Jungnam Joo, Eun Sook Lee, Han Sung Kang, Seeyoun Lee, Dong Ock Lee, Myong Cheol Lim, Sun Young Kong

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8 Citations (Scopus)

Abstract

The use of multigene panel testing for patients with a predisposition to breast/ovarian cancer is increasing as the identification of variants is useful for diagnosis and disease management. We identified pathogenic and likely pathogenic (P/LP) variants of high-and moderate-risk genes using a 23-gene germline cancer panel in 518 patients with hereditary breast and ovarian cancers (HBOC). The frequency of P/LP variants was 12.4% (64/518) for high- and moderate-penetrant genes, namely, BRCA2 (5.6%), BRCA1 (3.3%), CHEK2 (1.2%), MUTYH (0.8%), PALB2 (0.8%), MLH1 (0.4%), ATM (0.4%), BRIP1 (0.4%), TP53 (0.2%), and PMS2 (0.2%). Five patients possessed two P/LP variants in BRCA1/2 and other genes. We also compared the results from in silico splicing predictive tools and exon splicing patterns from patient samples by analyzing RT-PCR product sequences in six P/LP intronic variants and two intronic variants of unknown significance (VUS). Altered transcriptional fragments were detected for P/LP intronic variants in BRCA1, BRIP1, CHEK2, PARB2, and PMS2. Notably, we identified an in-frame deletion of the BRCA1 C-terminal (BRCT) domain by exon skipping in BRCA1 c.5152+6T>C—as known VUS—indicating a risk for HBOC. Thus, exon splicing analysis can improve the identification of veiled intronic variants that would aid decision making and determination of hereditary cancer risk.

Original languageEnglish
Pages (from-to)3912-3925
Number of pages14
JournalCancer Science
Volume111
Issue number10
DOIs
Publication statusPublished - 2020 Oct 1

Bibliographical note

Publisher Copyright:
© 2020 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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