Open AccessOptimization of prediction methods for risk assessment of pathogenic germline variants in the Japanese population
Author(s) -
Senda Noriko,
KawaguchiSakita Nobuko,
Kawashima Masahiro,
InagakiKawata Yukiko,
Yoshida Kenichi,
Takada Masahiro,
Kataoka Masako,
Torii Masae,
Nishimura Tomomi,
Kawaguchi Kosuke,
Suzuki Eiji,
Kataoka Yuki,
Matsumoto Yoshiaki,
Yoshibayashi Hiroshi,
Yamagami Kazuhiko,
Tsuyuki Shigeru,
Takahara Sachiko,
Yamauchi Akira,
Shinkura Nobuhiko,
Kato Hironori,
Moriguchi Yoshio,
Okamura Ryuji,
Kan Norimichi,
Suwa Hirofumi,
Sakata Shingo,
Mashima Susumu,
Yotsumoto Fumiaki,
Tachibana Tsuyoshi,
Tanaka Mitsuru,
Togashi Kaori,
Haga Hironori,
Yamada Takahiro,
Kosugi Shinji,
Inamoto Takashi,
Sugimoto Masahiro,
Ogawa Seishi,
Toi Masakazu
Publication year - 2021
Publication title -
cancer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 141
eISSN - 1349-7006
pISSN - 1347-9032
DOI - 10.1111/cas.14986
Subject(s) - palb2 , medicine , breast cancer , oncology , confidence interval , family history , ovarian cancer , cancer , population , germline , germline mutation , gynecology , gene , genetics , mutation , biology , environmental health
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.