Refined histopathological predictors of BRCA1 and BRCA2 mutation status: a large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia.

Authors:
Amanda B Spurdle
Amanda B Spurdle
QIMR Berghofer Medical Research Institute
Brisbane City | Australia
Fergus J Couch
Fergus J Couch
Mayo Clinic
Phoenix | United States
Michael T Parsons
Michael T Parsons
QIMR Berghofer Medical Research Institute
Lesley McGuffog
Lesley McGuffog
United Kingdom
Daniel Barrowdale
Daniel Barrowdale
University of Cambridge
United Kingdom
Manjeet K Bolla
Manjeet K Bolla
University of Cambridge
United Kingdom
Qin Wang
Qin Wang
University of Cambridge
United Kingdom
Sue Healey
Sue Healey
QIMR Berghofer Medical Research Institute
Brisbane City | Australia
Rita Schmutzler Barbara Wappenschmidt Kerstin Rhiem Eric Hahnen Christoph Engel Alfons Meindl Nina Ditsch Norbert Arnold Hansjoerg Plendl Dieter Niederacher Christian Sutter Shan Wang-Gohrke Doris Steinemann Sabine Preisler-Adams Karin Kast Raymonda Varon-Mateeva Steve Ellis Debra Frost Radka Platte Jo Perkins D Gareth Evans Louise Izatt Ros Eeles Julian Adlard Rosemarie Davidson Trevor Cole Giulietta Scuvera Siranoush Manoukian Bernardo Bonanni Frederique Mariette Stefano Fortuzzi Alessandra Viel Barbara Pasini Laura Papi Liliana Varesco Rosemary Balleine Katherine L Nathanson Susan M Domchek Kenneth Offitt Anna Jakubowska Noralane Lindor Mads Thomassen Uffe Birk Jensen Johanna Rantala Åke Borg Irene L Andrulis Alexander Miron Thomas V O Hansen Trinidad Caldes Susan L Neuhausen Amanda E Toland Heli Nevanlinna Marco Montagna Judy Garber Andrew K Godwin Ana Osorio Rachel E Factor Mary B Terry Timothy R Rebbeck Beth Y Karlan Melissa Southey Muhammad Usman Rashid Nadine Tung Paul D P Pharoah Fiona M Blows Alison M Dunning Elena Provenzano Per Hall Kamila Czene Marjanka K Schmidt Annegien Broeks Sten Cornelissen Senno Verhoef Peter A Fasching Matthias W Beckmann Arif B Ekici Dennis J Slamon Stig E Bojesen Børge G Nordestgaard Sune F Nielsen Henrik Flyger Jenny Chang-Claude Dieter Flesch-Janys Anja Rudolph Petra Seibold Kristiina Aittomäki Taru A Muranen Päivi Heikkilä Carl Blomqvist Jonine Figueroa Stephen J Chanock Louise Brinton Jolanta Lissowska Janet E Olson Vernon S Pankratz Esther M John Alice S Whittemore Dee W West Ute Hamann Diana Torres Hans Ulrich Ulmer Thomas Rüdiger Peter Devilee Robert A E M Tollenaar Caroline Seynaeve Christi J Van Asperen Diana M Eccles William J Tapper Lorraine Durcan Louise Jones Julian Peto Isabel dos-Santos-Silva Olivia Fletcher Nichola Johnson Miriam Dwek Ruth Swann Anita L Bane Gord Glendon Anna M Mulligan Graham G Giles Roger L Milne Laura Baglietto Catriona McLean Jane Carpenter Christine Clarke Rodney Scott Hiltrud Brauch Thomas Brüning Yon-Dschun Ko Angela Cox Simon S Cross Malcolm W R Reed Jan Lubinski Katarzyna Jaworska-Bieniek Katarzyna Durda Jacek Gronwald Thilo Dörk Natalia Bogdanova Tjoung-Won Park-Simon Peter Hillemanns Christopher A Haiman Brian E Henderson Fredrick Schumacher Loic Le Marchand Barbara Burwinkel Frederik Marme Harald Surovy Rongxi Yang Hoda Anton-Culver Argyrios Ziogas Maartje J Hooning J Margriet Collée John W M Martens Madeleine M A Tilanus-Linthorst Hermann Brenner Aida Karina Dieffenbach Volke Arndt Christa Stegmaier Robert Winqvist Katri Pylkäs Arja Jukkola-Vuorinen Mervi Grip Annika Lindblom Sara Margolin Vijai Joseph Mark Robson Rohini Rau-Murthy Anna González-Neira José Ignacio Arias Pilar Zamora Javier Benítez Arto Mannermaa Vesa Kataja Veli-Matti Kosma Jaana M Hartikainen Paolo Peterlongo Daniela Zaffaroni Monica Barile Fabio Capra Paolo Radice Soo H Teo Douglas F Easton Antonis C Antoniou Georgia Chenevix-Trench David E Goldgar

Breast Cancer Res 2014 Dec 23;16(6):3419. Epub 2014 Dec 23.

Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling.

Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the likelihood of mutation status by histopathological markers were derived using a Mantel-Haenszel approach.

Results: ER-positive phenotype negatively predicted BRCA1 mutation status, irrespective of grade (LRs from 0.08 to 0.90). ER-negative grade 3 histopathology was more predictive of positive BRCA1 mutation status in women 50 years or older (LR = 4.13 (3.70 to 4.62)) versus younger than 50 years (LR = 3.16 (2.96 to 3.37)). For BRCA2, ER-positive grade 3 phenotype modestly predicted positive mutation status irrespective of age (LR = 1.7-fold), whereas ER-negative grade 3 features modestly predicted positive mutation status at 50 years or older (LR = 1.54 (1.27 to 1.88)). Triple-negative tumor status was highly predictive of BRCA1 mutation status for women younger than 50 years (LR = 3.73 (3.43 to 4.05)) and 50 years or older (LR = 4.41 (3.86 to 5.04)), and modestly predictive of positive BRCA2 mutation status in women 50 years or older (LR = 1.79 (1.42 to 2.24)).

Conclusions: These results refine likelihood-ratio estimates for predicting BRCA1 and BRCA2 mutation status by using commonly measured histopathological features. Age at diagnosis is an important variable for most analyses, and grade is more informative than ER status for BRCA2 mutation carrier prediction. The estimates will improve BRCA1 and BRCA2 variant classification and inform patient mutation testing and clinical management.

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http://dx.doi.org/10.1186/s13058-014-0474-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4352262PMC

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December 2014
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