Definition of clinically distinct molecular subtypes in estrogen receptor-positive breast carcinomas through genomic grade.

PURPOSE A number of microarray studies have reported distinct molecular profiles of breast cancers (BC), such as basal-like, ErbB2-like, and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER) -positive subtypes has been inconsistent. Therefore, refinement of their molecular definition is needed. MATERIALS AND METHODS We have previously reported a gene expression grade index (GGI), which defines histologic grade based on gene expression profiles. Using this algorithm, we assigned ER-positive BC to either high-or low-genomic grade subgroups and compared these with previously reported ER-positive molecular classifications. As further validation, we classified 666 ER-positive samples into subtypes and assessed their clinical outcome. RESULTS Two ER-positive molecular subgroups (high and low genomic grade) could be defined using the GGI. Despite tracking a single biologic pathway, these were highly comparable to the previously described luminal A and B classification and significantly correlated to the risk groups produced using the 21-gene recurrence score. The two subtypes were associated with statistically distinct clinical outcome in both systemically untreated and tamoxifen-treated populations. CONCLUSION The use of genomic grade can identify two clinically distinct ER-positive molecular subtypes in a simple and highly reproducible manner across multiple data sets. This study emphasizes the important role of proliferation-related genes in predicting prognosis in ER-positive BC.

[1]  I. Ellis,et al.  Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. , 2002, Histopathology.

[2]  Robert Gray,et al.  Flexible Methods for Analyzing Survival Data Using Splines, with Applications to Breast Cancer Prognosis , 1992 .

[3]  R. Sutherland,et al.  Inducible overexpression of cyclin D1 in breast cancer cells reverses the growth-inhibitory effects of antiestrogens. , 1997, Clinical cancer research : an official journal of the American Association for Cancer Research.

[4]  T. Lumley,et al.  Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker , 2000, Biometrics.

[5]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[6]  P. Grambsch,et al.  Modeling Survival Data: Extending the Cox Model , 2000 .

[7]  R. Tibshirani,et al.  Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[9]  Z. Valenta,et al.  Estimation of the survival function for Gray's piecewise‐constant time‐varying coefficients model , 2002, Statistics in medicine.

[10]  Yudong D. He,et al.  A Gene-Expression Signature as a Predictor of Survival in Breast Cancer , 2002 .

[11]  Philip M. Long,et al.  Breast cancer classification and prognosis based on gene expression profiles from a population-based study , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[12]  J. Cuzick,et al.  Anastrozole alone or in combination with tamoxifen versus tamoxifen alone for adjuvant treatment of postmenopausal women with early‐stage breast cancer , 2003, Cancer.

[13]  R. Tibshirani,et al.  Repeated observation of breast tumor subtypes in independent gene expression data sets , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[14]  E. Perez,et al.  A randomized trial of letrozole in postmenopausal women after five years of tamoxifen therapy for early-stage breast cancer. , 2004, The New England journal of medicine.

[15]  M. Cronin,et al.  A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. , 2004, The New England journal of medicine.

[16]  C. Davies Switching to exemestane after 2-3 years of adjuvant tamoxifen prolongs disease-free survival, but not overall survival, in postmenopausal women surviving primary breast cancer, compared with continuous tamoxifen. , 2004, Cancer treatment reviews.

[17]  Wei Wang,et al.  A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. , 2004, Cancer cell.

[18]  P. Lønning,et al.  Cognitive ability in childhood and cognitive decline in mid-life: longitudinal birth cohort study , 2003, BMJ : British Medical Journal.

[19]  Therese Sørlie,et al.  Molecular portraits of breast cancer: tumour subtypes as distinct disease entities. , 2004, European journal of cancer.

[20]  Yudong D. He,et al.  A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients. , 2005, Cancer research.

[21]  Howard Y. Chang,et al.  Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[22]  Prediction of early distant relapses on tamoxifen in early-stage breast cancer (BC): A potential tool for adjuvant aromatase inhibitor (AI) tailoring , 2005 .

[23]  J. Forbes,et al.  A comparison of letrozole and tamoxifen in postmenopausal women with early breast cancer. , 2005, The New England journal of medicine.

[24]  Y Wang,et al.  Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials , 2005, The Lancet.

[25]  J. Foekens,et al.  Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer , 2005, The Lancet.

[26]  佐治 重衡,et al.  What's going on 乳癌 A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Ma XJ, Wang Z, Ryan PD, Isakoff SJ, Barmettler A, Fuller A, et al. Cancer Cell. 2004;5:607-16. PMID:15193263--術後補助療法におけるタモキシフェンへの反応性は2つの遺伝子レベルの測定によって予測しうることを示した論文 , 2005 .

[27]  Michael Gnant,et al.  Switching of postmenopausal women with endocrine-responsive early breast cancer to anastrozole after 2 years' adjuvant tamoxifen: combined results of ABCSG trial 8 and ARNO 95 trial , 2005, The Lancet.

[28]  Chiara Benedetto,et al.  Switching to anastrozole versus continued tamoxifen treatment of early breast cancer: preliminary results of the Italian Tamoxifen Anastrozole Trial. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[29]  Zhiyuan Hu,et al.  Estrogen-regulated genes predict survival in hormone receptor-positive breast cancers. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[30]  A. Nobel,et al.  The molecular portraits of breast tumors are conserved across microarray platforms , 2006, BMC Genomics.

[31]  M. J. van de Vijver,et al.  Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. , 2006, Journal of the National Cancer Institute.

[32]  A. Nobel,et al.  Concordance among Gene-Expression – Based Predictors for Breast Cancer , 2011 .