© The Author 2006. Published by Oxford University Press.
ARTICLE |
Gene Expression Profiling in Breast Cancer: Understanding the Molecular Basis of Histologic Grade To Improve Prognosis
Affiliations of authors: Functional Genomics and Translational Research Unit (CS, SL, BH-K, CD), Translational Research and Medical Oncology Unit (CS, CD, DL, FC, MP), Jules Bordet Institute, Machine Learning Group (BH-K), Université Libre de Bruxelles, Brussels, Belgium; National Center of Competence in Research Molecular Oncology, Swiss Institute of Experimental Cancer Research (PW, PF, MD), Swiss Institute of Bioinformatics (PW, PF, VP, MD), CH-1066 Epalinges, Switzerland; Molecular Oncology Laboratory and Molecular Angiogenesis Laboratory, Cancer Research UK and the Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK (AH, SF); Cancer Center Karolinska, Karolinska University Hospital, Stockholm, Sweden (JS, JB); Department of Pathology, Uppsala University Hospital, Uppsala, Sweden (HN); Division of Diagnostic Oncology (HP, MJVdV), Division of Radiation Oncology (DN), The Netherlands Cancer Institute, Amsterdam, The Netherlands; International Drug Development Institute, Brussels, Belgium (MB)
Correspondence to: Christos Sotiriou, MD, PhD, Translational Research Unit, Jules Bordet Institute, 121 Blvd de Waterloo, 1000 Brussels, Belgium (e-mail:christos.sotiriou{at}bordet.be).
Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%–60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profiles of breast cancers and whether such profiles could be used to improve histologic grading. Methods: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)–positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan–Meier analysis. All statistical tests were two-sided. Results: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1–3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P<.001, log-rank test). Conclusions: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value.
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