PURPOSE: Current immunohistochemical (IHC)-based definitions of luminal A and B breast cancers are imperfect when compared with multigene expression-based assays. In this study, we sought to improve the IHC subtyping by examining the pathologic and gene expression characteristics of genomically defined luminal A and B subtypes. PATIENTS AND METHODS: Gene expression and pathologic features were collected from primary tumors across five independent cohorts: British Columbia Cancer Agency (BCCA) tamoxifen-treated only, Grupo Español de Investigación en Cáncer de Mama 9906 trial, BCCA no systemic treatment cohort, PAM50 microarray training data set, and a combined publicly available microarray data set. Optimal cutoffs of percentage of progesterone receptor (PR) -positive tumor cells to predict survival were derived and independently tested. Multivariable Cox models were used to test the prognostic significance. RESULTS: Clinicopathologic comparisons among luminal A and B subtypes consistently identified higher rates of PR positivity, human epidermal growth factor receptor 2 (HER2) negativity, and histologic grade 1 in luminal A tumors. Quantitative PR gene and protein expression were also found to be significantly higher in luminal A tumors. An empiric cutoff of more than 20% of PR-positive tumor cells was statistically chosen and proved significant for predicting survival differences within IHC-defined luminal A tumors independently of endocrine therapy administration. Finally, no additional prognostic value within hormonal receptor (HR) -positive/HER2-negative disease was observed with the use of the IHC4 score when intrinsic IHC-based subtypes were used that included the more than 20% PR-positive tumor cells and vice versa. CONCLUSION: Semiquantitative IHC expression of PR adds prognostic value within the current IHC-based luminal A definition by improving the identification of good outcome breast cancers. The new proposed IHC-based definition of luminal A tumors is HR positive/HER2 negative/Ki-67 less than 14%, and PR more than 20%.
PURPOSE: Current immunohistochemical (IHC)-based definitions of luminal A and B breast cancers are imperfect when compared with multigene expression-based assays. In this study, we sought to improve the IHC subtyping by examining the pathologic and gene expression characteristics of genomically defined luminal A and B subtypes. PATIENTS AND METHODS: Gene expression and pathologic features were collected from primary tumors across five independent cohorts: British Columbia Cancer Agency (BCCA) tamoxifen-treated only, Grupo Español de Investigación en Cáncer de Mama 9906 trial, BCCA no systemic treatment cohort, PAM50 microarray training data set, and a combined publicly available microarray data set. Optimal cutoffs of percentage of progesterone receptor (PR) -positive tumor cells to predict survival were derived and independently tested. Multivariable Cox models were used to test the prognostic significance. RESULTS: Clinicopathologic comparisons among luminal A and B subtypes consistently identified higher rates of PR positivity, humanepidermal growth factor receptor 2 (HER2) negativity, and histologic grade 1 in luminal A tumors. Quantitative PR gene and protein expression were also found to be significantly higher in luminal A tumors. An empiric cutoff of more than 20% of PR-positive tumor cells was statistically chosen and proved significant for predicting survival differences within IHC-defined luminal A tumors independently of endocrine therapy administration. Finally, no additional prognostic value within hormonal receptor (HR) -positive/HER2-negative disease was observed with the use of the IHC4 score when intrinsic IHC-based subtypes were used that included the more than 20% PR-positive tumor cells and vice versa. CONCLUSION: Semiquantitative IHC expression of PR adds prognostic value within the current IHC-based luminal A definition by improving the identification of good outcome breast cancers. The new proposed IHC-based definition of luminal A tumors is HR positive/HER2 negative/Ki-67 less than 14%, and PR more than 20%.
Authors: Giuseppe Viale; Meredith M Regan; Eugenio Maiorano; Mauro G Mastropasqua; Patrizia Dell'Orto; Birgitte Bruun Rasmussen; Johnny Raffoul; Patrick Neven; Zsolt Orosz; Stephen Braye; Christian Ohlschlegel; Beat Thürlimann; Richard D Gelber; Monica Castiglione-Gertsch; Karen N Price; Aron Goldhirsch; Barry A Gusterson; Alan S Coates Journal: J Clin Oncol Date: 2007-08-06 Impact factor: 44.544
Authors: Soonmyung Paik; Gong Tang; Steven Shak; Chungyeul Kim; Joffre Baker; Wanseop Kim; Maureen Cronin; Frederick L Baehner; Drew Watson; John Bryant; Joseph P Costantino; Charles E Geyer; D Lawrence Wickerham; Norman Wolmark Journal: J Clin Oncol Date: 2006-05-23 Impact factor: 44.544
Authors: Daniel S Oh; Melissa A Troester; Jerry Usary; Zhiyuan Hu; Xiaping He; Cheng Fan; Junyuan Wu; Lisa A Carey; Charles M Perou Journal: J Clin Oncol Date: 2006-02-27 Impact factor: 44.544
Authors: Victor R Grann; Andrea B Troxel; Naseem J Zojwalla; Judith S Jacobson; Dawn Hershman; Alfred I Neugut Journal: Cancer Date: 2005-06-01 Impact factor: 6.860
Authors: C M Perou; T Sørlie; M B Eisen; M van de Rijn; S S Jeffrey; C A Rees; J R Pollack; D T Ross; H Johnsen; L A Akslen; O Fluge; A Pergamenschikov; C Williams; S X Zhu; P E Lønning; A L Børresen-Dale; P O Brown; D Botstein Journal: Nature Date: 2000-08-17 Impact factor: 49.962
Authors: Syed K Mohsin; Heidi Weiss; Thomas Havighurst; Gary M Clark; Melora Berardo; Le D Roanh; Ta V To; Zhang Qian; Zho Qian; Richard R Love; D Craig Allred Journal: Mod Pathol Date: 2004-12 Impact factor: 7.842
Authors: Einas M Yousef; Daniela Furrer; David L Laperriere; Muhammad R Tahir; Sylvie Mader; Caroline Diorio; Louis A Gaboury Journal: Mod Pathol Date: 2017-01-13 Impact factor: 7.842
Authors: Nadia Howlader; Sean F Altekruse; Christopher I Li; Vivien W Chen; Christina A Clarke; Lynn A G Ries; Kathleen A Cronin Journal: J Natl Cancer Inst Date: 2014-04-28 Impact factor: 13.506
Authors: Carol Sweeney; Philip S Bernard; Rachel E Factor; Marilyn L Kwan; Laurel A Habel; Charles P Quesenberry; Kaylynn Shakespear; Erin K Weltzien; Inge J Stijleman; Carole A Davis; Mark T W Ebbert; Adrienne Castillo; Lawrence H Kushi; Bette J Caan Journal: Cancer Epidemiol Biomarkers Prev Date: 2014-02-12 Impact factor: 4.254
Authors: Bette J Caan; Carol Sweeney; Laurel A Habel; Marilyn L Kwan; Candyce H Kroenke; Erin K Weltzien; Charles P Quesenberry; Adrienne Castillo; Rachel E Factor; Lawrence H Kushi; Philip S Bernard Journal: Cancer Epidemiol Biomarkers Prev Date: 2014-02-12 Impact factor: 4.254