Definition of Clinically Distinct Molecular Subtypes in Estrogen Receptor–Positive Breast Carcinomas Through Genomic Grade
Top Cited Papers
- 1 April 2007
- journal article
- breast cancer
- Published by American Society of Clinical Oncology (ASCO) in Journal of Clinical Oncology
- Vol. 25 (10) , 1239-1246
- https://doi.org/10.1200/jco.2006.07.1522
Abstract
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.Keywords
This publication has 29 references indexed in Scilit:
- The molecular portraits of breast tumors are conserved across microarray platformsBMC Genomics, 2006
- Estrogen-Regulated Genes Predict Survival in Hormone Receptor–Positive Breast CancersJournal of Clinical Oncology, 2006
- Gene Expression Profiling in Breast Cancer: Understanding the Molecular Basis of Histologic Grade To Improve PrognosisJNCI Journal of the National Cancer Institute, 2006
- A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast CancerNew England Journal of Medicine, 2004
- Molecular portraits of breast cancer: tumour subtypes as distinct disease entitiesEuropean Journal Of Cancer, 2004
- Breast cancer classification and prognosis based on gene expression profiles from a population-based studyProceedings of the National Academy of Sciences, 2003
- Repeated observation of breast tumor subtypes in independent gene expression data setsProceedings of the National Academy of Sciences, 2003
- A Gene-Expression Signature as a Predictor of Survival in Breast CancerNew England Journal of Medicine, 2002
- Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implicationsProceedings of the National Academy of Sciences, 2001
- Molecular portraits of human breast tumoursNature, 2000