BACKGROUND: Women who have germline mutations in the BRCA1 gene are at substantially increased lifetime risk of developing breast and ovarian cancer but are otherwise normal. Currently, early age of onset of cancer and a strong family history are relied upon as the chief clues as to who should be offered genetic testing. Certain morphologic and immunohistochemical features are overrepresented in BRCA1-associated breast cancers but these differences have not been incorporated into the current selection criteria for genetic testing. DESIGN: Each of the 4 pathologists studied 30 known cases of BRCA1- and BRCA2-associated breast cancer from kConFab families. After reviewing the literature, we agreed on a semiquantitative scoring system for estimating the chances of presence of an underlying BRCA1 mutation, based on the number of the reported prototypic features present. After a time lag of 12 months, we each examined a series of 62 deidentified cases of breast cancer, inclusive of cases of BRCA1-associated breast cancer and controls. The controls included cases of BRCA2-associated breast cancer and sporadic cases. RESULTS: Our predictions had a sensitivity of 92%, specificity of 86%, positive predictive value of 61%, and negative predictive value of 98%. For comparison the sensitivity of currently used selection criteria are in the range of 25% to 30%. CONCLUSION: The inclusion of morphologic and immunohistochemical features of breast cancers in algorithms to predict the likelihood of presence of germline mutations in the BRCA1 gene improves the accuracy of the selection process.
BACKGROUND:Women who have germline mutations in the BRCA1 gene are at substantially increased lifetime risk of developing breast and ovarian cancer but are otherwise normal. Currently, early age of onset of cancer and a strong family history are relied upon as the chief clues as to who should be offered genetic testing. Certain morphologic and immunohistochemical features are overrepresented in BRCA1-associated breast cancers but these differences have not been incorporated into the current selection criteria for genetic testing. DESIGN: Each of the 4 pathologists studied 30 known cases of BRCA1- and BRCA2-associated breast cancer from kConFab families. After reviewing the literature, we agreed on a semiquantitative scoring system for estimating the chances of presence of an underlying BRCA1 mutation, based on the number of the reported prototypic features present. After a time lag of 12 months, we each examined a series of 62 deidentified cases of breast cancer, inclusive of cases of BRCA1-associated breast cancer and controls. The controls included cases of BRCA2-associated breast cancer and sporadic cases. RESULTS: Our predictions had a sensitivity of 92%, specificity of 86%, positive predictive value of 61%, and negative predictive value of 98%. For comparison the sensitivity of currently used selection criteria are in the range of 25% to 30%. CONCLUSION: The inclusion of morphologic and immunohistochemical features of breast cancers in algorithms to predict the likelihood of presence of germline mutations in the BRCA1 gene improves the accuracy of the selection process.
Authors: Mika Fujiwara; Valerie A McGuire; Anna Felberg; Weiva Sieh; Alice S Whittemore; Teri A Longacre Journal: Am J Surg Pathol Date: 2012-08 Impact factor: 6.394
Authors: Anna Marie Mulligan; Dushanthi Pinnaduwage; Anita L Bane; Shelley B Bull; Frances P O'Malley; Irene L Andrulis Journal: Cancer Date: 2010-11-02 Impact factor: 6.860
Authors: Yujing J Heng; Susan C Lester; Gary Mk Tse; Rachel E Factor; Kimberly H Allison; Laura C Collins; Yunn-Yi Chen; Kristin C Jensen; Nicole B Johnson; Jong Cheol Jeong; Rahi Punjabi; Sandra J Shin; Kamaljeet Singh; Gregor Krings; David A Eberhard; Puay Hoon Tan; Konstanty Korski; Frederic M Waldman; David A Gutman; Melinda Sanders; Jorge S Reis-Filho; Sydney R Flanagan; Deena Ma Gendoo; Gregory M Chen; Benjamin Haibe-Kains; Giovanni Ciriello; Katherine A Hoadley; Charles M Perou; Andrew H Beck Journal: J Pathol Date: 2016-12-29 Impact factor: 7.996
Authors: R Andrés; I Pajares; J Balmaña; G Llort; T Ramón Y Cajal; I Chirivella; E Aguirre; L Robles; E Lastra; P Pérez-Segura; N Bosch; C Yagüe; E Lerma; J Godino; M D Miramar; M Moros; P Astier; B Saez; M J Vidal; A Arcusa; S Ramón y Cajal; M T Calvo; A Tres Journal: Clin Transl Oncol Date: 2013-08-27 Impact factor: 3.405
Authors: S R Young; Robert T Pilarski; Talia Donenberg; Charles Shapiro; Lyn S Hammond; Judith Miller; Karen A Brooks; Stephanie Cohen; Beverly Tenenholz; Damini Desai; Inuk Zandvakili; Robert Royer; Song Li; Steven A Narod Journal: BMC Cancer Date: 2009-03-19 Impact factor: 4.430