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Multicenter Study
. 2022 Mar 1;8(3):e216744.
doi: 10.1001/jamaoncol.2021.6744. Epub 2022 Mar 17.

Pathology of Tumors Associated With Pathogenic Germline Variants in 9 Breast Cancer Susceptibility Genes

Breast Cancer Association Consortium; Nasim Mavaddat  1 , Leila Dorling  1 , Sara Carvalho  1 , Jamie Allen  1 , Anna González-Neira  2 , Renske Keeman  3 , Manjeet K Bolla  1 , Joe Dennis  1 , Qin Wang  1 , Thomas U Ahearn  4 , Irene L Andrulis  5   6 , Matthias W Beckmann  7 , Sabine Behrens  8 , Javier Benitez  2   9 , Marina Bermisheva  10 , Carl Blomqvist  11 , Natalia V Bogdanova  12   13   14 , Stig E Bojesen  15   16   17 , Ignacio Briceno  18 , Thomas Brüning  19 , Nicola J Camp  20 , Archie Campbell  21   22 , Jose E Castelao  23 , Jenny Chang-Claude  8   24 , Stephen J Chanock  4 , Georgia Chenevix-Trench  25 , Hans Christiansen  12 , Kamila Czene  26 , Thilo Dörk  13 , Mikael Eriksson  26 , D Gareth Evans  27   28 , Peter A Fasching  7   29 , Jonine D Figueroa  22   30 , Henrik Flyger  31 , Marike Gabrielson  26 , Manuela Gago-Dominguez  32   33 , Jürgen Geisler  34   35 , Graham G Giles  36   37   38 , Pascal Guénel  39 , Andreas Hadjisavvas  40   41 , Eric Hahnen  42   43 , Per Hall  26   44 , Ute Hamann  45 , Jaana M Hartikainen  46   47 , Mikael Hartman  48   49   50 , Reiner Hoppe  51   52 , Anthony Howell  53 , Anna Jakubowska  54   55 , Audrey Jung  8 , Elza K Khusnutdinova  10   56 , Vessela N Kristensen  57   58 , Jingmei Li  49   59 , Swee Ho Lim  60   61 , Annika Lindblom  62   63 , Maria A Loizidou  40   41 , Artitaya Lophatananon  64 , Jan Lubinski  54 , Michael J Madsen  20 , Arto Mannermaa  46   47   65 , Mehdi Manoochehri  45 , Sara Margolin  44   66 , Dimitrios Mavroudis  67 , Roger L Milne  36   37   38 , Nur Aishah Mohd Taib  68 , Anna Morra  3 , Kenneth Muir  64 , Nadia Obi  69 , Ana Osorio  2   70 , Tjoung-Won Park-Simon  13 , Paolo Peterlongo  71 , Paolo Radice  72 , Emmanouil Saloustros  73 , Elinor J Sawyer  74 , Rita K Schmutzler  42   43   75 , Mitul Shah  76 , Xueling Sim  48 , Melissa C Southey  36   38   77 , Heather Thorne  78   79 , Ian Tomlinson  80   81 , Diana Torres  45   82 , Thérèse Truong  39 , Cheng Har Yip  68   83 , Amanda B Spurdle  25 , Maaike P G Vreeswijk  84 , Alison M Dunning  76 , Montserrat García-Closas  4 , Paul D P Pharoah  1   76 , Anders Kvist  85 , Taru A Muranen  86 , Heli Nevanlinna  86 , Soo Hwang Teo  68   87 , Peter Devilee  84   88 , Marjanka K Schmidt  3   89 , Douglas F Easton  1   76
Affiliations
Multicenter Study

Pathology of Tumors Associated With Pathogenic Germline Variants in 9 Breast Cancer Susceptibility Genes

Breast Cancer Association Consortium et al. JAMA Oncol. .

Abstract

Importance: Rare germline genetic variants in several genes are associated with increased breast cancer (BC) risk, but their precise contributions to different disease subtypes are unclear. This information is relevant to guidelines for gene panel testing and risk prediction.

Objective: To characterize tumors associated with BC susceptibility genes in large-scale population- or hospital-based studies.

Design, setting, and participants: The multicenter, international case-control analysis of the BRIDGES study included 42 680 patients and 46 387 control participants, comprising women aged 18 to 79 years who were sampled independently of family history from 38 studies. Studies were conducted between 1991 and 2016. Sequencing and analysis took place between 2016 and 2021.

Exposures: Protein-truncating variants and likely pathogenic missense variants in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53.

Main outcomes and measures: The intrinsic-like BC subtypes as defined by estrogen receptor, progesterone receptor, and ERBB2 (formerly known as HER2) status, and tumor grade; morphology; size; stage; lymph node involvement; subtype-specific odds ratios (ORs) for carrying protein-truncating variants and pathogenic missense variants in the 9 BC susceptibility genes.

Results: The mean (SD) ages at interview (control participants) and diagnosis (cases) were 55.1 (11.9) and 55.8 (10.6) years, respectively; all participants were of European or East Asian ethnicity. There was substantial heterogeneity in the distribution of intrinsic subtypes by gene. RAD51C, RAD51D, and BARD1 variants were associated mainly with triple-negative disease (OR, 6.19 [95% CI, 3.17-12.12]; OR, 6.19 [95% CI, 2.99-12.79]; and OR, 10.05 [95% CI, 5.27-19.19], respectively). CHEK2 variants were associated with all subtypes (with ORs ranging from 2.21-3.17) except for triple-negative disease. For ATM variants, the association was strongest for the hormone receptor (HR)+ERBB2- high-grade subtype (OR, 4.99; 95% CI, 3.68-6.76). BRCA1 was associated with increased risk of all subtypes, but the ORs varied widely, being highest for triple-negative disease (OR, 55.32; 95% CI, 40.51-75.55). BRCA2 and PALB2 variants were also associated with triple-negative disease. TP53 variants were most strongly associated with HR+ERBB2+ and HR-ERBB2+ subtypes. Tumors occurring in pathogenic variant carriers were of higher grade. For most genes and subtypes, a decline in ORs was observed with increasing age. Together, the 9 genes were associated with 27.3% of all triple-negative tumors in women 40 years or younger.

Conclusions and relevance: The results of this case-control study suggest that variants in the 9 BC risk genes differ substantially in their associated pathology but are generally associated with triple-negative and/or high-grade disease. Knowing the age and tumor subtype distributions associated with individual BC genes can potentially aid guidelines for gene panel testing, risk prediction, and variant classification and guide targeted screening strategies.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Mavaddat reported grants from the University of Cambridge, European Union Horizon 2020, Wellcome Trust, Genome Canada, Canadian Institutes of Health Research, and National Cancer Institute during the conduct of the study. Dr Allen reported grants from EU Horizons 2020 during the conduct of the study. Dr Bolla reported grants from Cancer Research UK and the National Institutes of Health (NIH) during the conduct of the study. Dr Andrulis reported grants from NIH during the conduct of the study. Dr Briceno reported grants from Universidad de la Sabana during the conduct of the study. Dr Fasching reported personal fees from Roche, Lilly, Novartis, Pierre Fabre, Gilead, Seagen, Eisai, Daiichi Sankyo, AstraZeneca, Merck Sharp & Dohme, and Pfizer and grants from Cepheid and BioNtech during the conduct of the study. Dr Giles reported grants from National Health and Medical Research Council during the conduct of the study. Dr Hahnen reported personal fees from AstraZeneca outside the submitted work. Dr Hartikainen reported grants from Cancer Foundation Finland during the conduct of the study. Ms Morra reported being paid by an EU grant during the conduct of the study. Dr Park-Simon reported being a recipient of the Claudia von Schilling Stiftung Award during the conduct of the study. Dr Schmutzler reported grants from German Cancer Aid during the conduct of the study. Dr Southey reported grants from National Health and Medical Research Council (NHMRC) (Australia) during the conduct of the study. Dr Spurdle reported grants from the NHMRC during the conduct of the study. Dr Pharoah reported grants from Cancer Research UK during the conduct of the study. Dr Kvist reported grants from European Union Horizon 2020 research and innovation program BRIDGES during the conduct of the study. Dr Nevanlinna reported grants from Helsinki University Hospital, Sigrid Juselius Foundation, and Cancer Foundation Finland during the conduct of the study as well as honorarium from AstraZeneca outside the submitted work. Dr Camp reported grants from the University of Utah, Huntsman Cancer Foundation, and the National Cancer Institute. Dr Schmidt reported grants from EU during the conduct of the study. Dr Easton reported grants from the European Commission and Wellcome Trust outside the submitted work. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Association Odds Ratios (ORs) for Protein-Truncating Variant Carrier Status in Breast Cancer Susceptibility Genes BRCA1, BRCA2, ATM, and CHEK2 and Intrinsic Subtypes of Breast Cancer
Multiple Imputation by Chained Equations imputation was conducted as described in the Methods and intrinsic subtypes constructed for each imputed data set. Multinomial logistic regression was conducted with intrinsic subtypes as the outcome variable, adjusting by age at diagnosis/interview and country, and the results of these analyses were pooled. These results are also shown in eTable 4 in Supplement 2. HR indicates hormone receptor.
Figure 2.
Figure 2.. Association Odds Ratios (ORs) for Protein-Truncating Variant Carrier Status in Breast Cancer Susceptibility Genes PALB2, BARD1, RAD51C, and RAD51D and Intrinsic Subtypes of Breast Cancer
Multiple Imputation by Chained Equations imputation was conducted as described in the Methods and intrinsic subtypes constructed for each imputed data set. Multinomial logistic regression was conducted with intrinsic subtypes as the outcome variable, adjusting by age at diagnosis/interview and country, and the results of these analyses were pooled. These results are also shown in eTable 4 in Supplement 2. HR indicates hormone receptor; NA, not applicable.
Figure 3.
Figure 3.. Estimates of Cumulative Risks of Breast Cancer by Age and Hormone Receptor (HR)–Positive Subtype for Protein-Truncating Variants in 8 Breast Cancer Susceptibility Genes
Age-, gene-, and subtype-specific cumulative risks were calculated as described in the Methods and eMethods in Supplement 1. Baseline incidence rates were derived from UK breast cancer incidence rates for 2016 (https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/breast-cancer/incidence-invasive).
Figure 4.
Figure 4.. Estimates of Cumulative Risks of Breast Cancer by Age and Hormone Receptor (HR)–Negative Subtype for Protein-Truncating Variants in 8 Breast Cancer Susceptibility Genes
Age-, gene-, and subtype-specific cumulative risks were calculated as described in the Methods and eMethods in Supplement 1. Baseline incidence rates were derived from UK breast cancer incidence rates for 2016 (https://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/breast-cancer/incidence-invasive).
See this image and copyright information in PMC

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