Optimization of prediction methods for risk assessment of pathogenic germline variants in the Japanese population

Noriko Senda, Nobuko Kawaguchi-Sakita, Masahiro Kawashima, Yukiko Inagaki-Kawata, Kenichi Yoshida, Masahiro Takada, Masako Kataoka, Masae Torii, Tomomi Nishimura, Kosuke Kawaguchi, Eiji Suzuki, Yuki Kataoka, Yoshiaki Matsumoto, Hiroshi Yoshibayashi, Kazuhiko Yamagami, Shigeru Tsuyuki, Sachiko Takahara, Akira Yamauchi, Nobuhiko Shinkura, Hironori KatoYoshio Moriguchi, Ryuji Okamura, Norimichi Kan, Hirofumi Suwa, Shingo Sakata, Susumu Mashima, Fumiaki Yotsumoto, Tsuyoshi Tachibana, Mitsuru Tanaka, Kaori Togashi, Hironori Haga, Takahiro Yamada, Shinji Kosugi, Takashi Inamoto, Masahiro Sugimoto, Seishi Ogawa, Masakazu Toi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Predicting pathogenic germline variants (PGVs) in breast cancer patients is important for selecting optimal therapeutics and implementing risk reduction strategies. However, PGV risk factors and the performance of prediction methods in the Japanese population remain unclear. We investigated clinicopathological risk factors using the Tyrer-Cuzick (TC) breast cancer risk evaluation tool to predict BRCA PGVs in unselected Japanese breast cancer patients (n = 1,995). Eleven breast cancer susceptibility genes were analyzed using target-capture sequencing in a previous study; the PGV prevalence in BRCA1, BRCA2, and PALB2 was 0.75%, 3.1%, and 0.45%, respectively. Significant associations were found between the presence of BRCA PGVs and early disease onset, number of familial cancer cases (up to third-degree relatives), triple-negative breast cancer patients under the age of 60, and ovarian cancer history (all P <.0001). In total, 816 patients (40.9%) satisfied the National Comprehensive Cancer Network (NCCN) guidelines for recommending multigene testing. The sensitivity and specificity of the NCCN criteria for discriminating PGV carriers from noncarriers were 71.3% and 60.7%, respectively. The TC model showed good discrimination for predicting BRCA PGVs (area under the curve, 0.75; 95% confidence interval, 0.69-0.81). Furthermore, use of the TC model with an optimized cutoff of TC score ≥0.16% in addition to the NCCN guidelines improved the predictive efficiency for high-risk groups (sensitivity, 77.2%; specificity, 54.8%; about 11 genes). Given the influence of ethnic differences on prediction, we consider that further studies are warranted to elucidate the role of environmental and genetic factors for realizing precise prediction.

Original languageEnglish
Pages (from-to)3338-3348
Number of pages11
JournalCancer science
Volume112
Issue number8
DOIs
Publication statusPublished - 2021 Aug
Externally publishedYes

Keywords

  • BRCA
  • Tyrer-Cuzick model
  • breast cancer
  • pathogenic germline variant
  • risk factor

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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