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BRCA1和BRCA2突变状态的精细组织病理学预测指标:来自BCAC、CIMBA和ENIGMA联盟的乳腺癌特征大规模分析

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

作者信息

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

出版信息

Breast Cancer Res. 2014 Dec 23;16(6):3419. doi: 10.1186/s13058-014-0474-y.

Abstract

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.

摘要

引言

BRCA1或BRCA2种系突变携带者中浸润性乳腺癌的组织病理学特征分布与无已知突变个体不同。因此,组织病理学特征可用于突变预测,包括通过统计建模评估临床意义不确定的BRCA1或BRCA2变异的致病性。我们分析了由BRCA1/2修饰因子研究联盟(CIMBA)和乳腺癌协会联盟(BCAC)积累的大型病理学数据集,以重新评估BRCA1和BRCA2突变状态的组织病理学预测指标,并为统计建模提供可靠的似然比(LR)估计值。

方法

纳入研究/中心的选择标准是有70岁以下诊断的浸润性乳腺癌的雌激素受体(ER)状态或分级数据。该数据集包括4477名BRCA1突变携带者、2565名BRCA2突变携带者和47565例BCAC乳腺癌病例。使用Mantel-Haenszel方法得出按组织病理学标志物分层的各国突变状态可能性估计值。

结果

ER阳性表型对BRCA1突变状态具有负向预测作用,与分级无关(LR为0.08至0.90)。ER阴性3级组织病理学特征在50岁及以上女性中对BRCA1突变阳性状态的预测性更强(LR = 4.13(3.70至4.62)),而在50岁以下女性中(LR = 3.16(2.96至3.37))。对于BRCA2,ER阳性3级表型无论年龄大小对突变阳性状态均有适度预测作用(LR = 1.7倍),而ER阴性3级特征在50岁及以上女性中对突变阳性状态有适度预测作用(LR = 1.54(1.27至1.88))。三阴型肿瘤状态在50岁以下女性(LR = 3.73(3.43至4.05))和50岁及以上女性(LR = 4.41(3.86至5.04))中对BRCA1突变状态具有高度预测性,在50岁及以上女性中对BRCA2突变阳性状态有适度预测作用(LR = 1.79(1.42至2.24))。

结论

这些结果完善了通过常用的组织病理学特征预测BRCA1和BRCA2突变状态的似然比估计值。诊断年龄是大多数分析中的一个重要变量,对于BRCA2突变携带者的预测,分级比ER状态更具信息量。这些估计值将改善BRCA1和BRCA2变异分类,并为患者的突变检测和临床管理提供参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b26/4352262/bac37d7f73b2/13058_2014_474_Fig1_HTML.jpg

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