Open Access Open Badges Research article

Rare, evolutionarily unlikely missense substitutions in CHEK2 contribute to breast cancer susceptibility: results from a breast cancer family registry case-control mutation-screening study

Florence Le Calvez-Kelm1, Fabienne Lesueur1, Francesca Damiola1, Maxime Vallée1, Catherine Voegele1, Davit Babikyan2, Geoffroy Durand1, Nathalie Forey1, Sandrine McKay-Chopin1, Nivonirina Robinot1, Tù Nguyen-Dumont1, Alun Thomas3, Graham B Byrnes1, Breast Cancer Family Registry456, John L Hopper4, Melissa C Southey7, Irene L Andrulis5, Esther M John68 and Sean V Tavtigian9*

Author Affiliations

1 International Agency for Research on Cancer, 150 Cours Albert Thomas, Lyon CEDEX 08, F-69372, France

2 Laboratory of Cancer Genetics, Center of Medical Genetics and Primary Health Care, 4 Tigran Mets Avenue, Yerevan 375010, Armenia

3 Department of Internal Medicine, University of Utah School of Medicine, 391 Chipeta Way, Suite D, Salt Lake City, UT 84108, USA

4 Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, The University of Melbourne, 723 Swanston Street, Melbourne, Victoria 3010, Australia

5 Cancer Care Ontario, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Department of Molecular Genetics, University of Toronto, 60 Murray Street, Toronto, ON M5T 3L9, Canada

6 Cancer Prevention Institute of California, 2201 Walnut Avenue, Suite 300, Fremont, CA 94538, USA

7 Department of Pathology, The University of Melbourne, Medical Building 181, Melbourne, Victoria 3010, Australia

8 Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305, USA

9 Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, 2000 Circle of Hope, Salt Lake City, UT 84112, USA

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Breast Cancer Research 2011, 13:R6  doi:10.1186/bcr2810

Published: 18 January 2011



Both protein-truncating variants and some missense substitutions in CHEK2 confer increased risk of breast cancer. However, no large-scale study has used full open reading frame mutation screening to assess the contribution of rare missense substitutions in CHEK2 to breast cancer risk. This absence has been due in part to a lack of validated statistical methods for summarizing risk attributable to large numbers of individually rare missense substitutions.


Previously, we adapted an in silico assessment of missense substitutions used for analysis of unclassified missense substitutions in BRCA1 and BRCA2 to the problem of assessing candidate genes using rare missense substitution data observed in case-control mutation-screening studies. The method involves stratifying rare missense substitutions observed in cases and/or controls into a series of grades ordered a priori from least to most likely to be evolutionarily deleterious, followed by a logistic regression test for trends to compare the frequency distributions of the graded missense substitutions in cases versus controls. Here we used this approach to analyze CHEK2 mutation-screening data from a population-based series of 1,303 female breast cancer patients and 1,109 unaffected female controls.


We found evidence of risk associated with rare, evolutionarily unlikely CHEK2 missense substitutions. Additional findings were that (1) the risk estimate for the most severe grade of CHEK2 missense substitutions (denoted C65) is approximately equivalent to that of CHEK2 protein-truncating variants; (2) the population attributable fraction and the familial relative risk explained by the pool of rare missense substitutions were similar to those explained by the pool of protein-truncating variants; and (3) post hoc power calculations implied that scaling up case-control mutation screening to examine entire biochemical pathways would require roughly 2,000 cases and controls to achieve acceptable statistical power.


This study shows that CHEK2 harbors many rare sequence variants that confer increased risk of breast cancer and that a substantial proportion of these are missense substitutions. The study validates our analytic approach to rare missense substitutions and provides a method to combine data from protein-truncating variants and rare missense substitutions into a one degree of freedom per gene test.