Volume 7 Supplement 1
Gene expression profiles and molecular classification to predict distant metastasis and tamoxifen-resistant breast cancer
© BioMed Central 2005
Published: 27 May 2005
Genome-wide measures of gene expression can identify patterns of gene activity that subclassify tumours and might provide better means than are currently available for individual risk assessment in patients with primary breast cancer and for prediction of tamoxifen resistance.
We analyzed, with Affymetrix Human U133a GeneChips, the expression of 22,000 transcripts from total RNA of frozen tumour samples from 286 lymph node negative (LNN) patients who had not received adjuvant systemic treatment. In a separate second study conducted in 112 estrogen receptor (ER)-positive primary breast carcinomas from patients with metastatic disease and clearly defined types of response to first-line treatment with tamoxifen, a 18,000 human cDNA microarray was used to discover gene expression profiles predictive of tamoxifen resistance.
In the first single-center study, in a training set of 115 tumors (80 ER+ and 35 ER- tumors) we identified a 76-gene signature (60 genes for ER+ and 16 for ER-) for predicting the occurrence of distant metastasis within 5 years. This signature was successfully validated with 93% sensitivity in an independent test set of 171 LNN patients as a whole, irrespective of age or ER status. The 76-gene profile was strongly predictive of those patients who will develop a distant metastasis within 5 years or will remain recurrence free during that period (hazard ratio [HR] 5.67; P < 0.00002) and in multivariate analysis when corrected for traditional prognostic factors including grade (HR 5.55; P < 0.00003). Analogously, the 76-gene expression profile strongly predicted overall survival (HR 8.62; P < 0.00002). The 76-gene profile was also a strong prognostic factor in the subgroup of 79 patients with a tumor size ranging from 10 to 20 mm (HR 14.1; P < 0.00003) and in 84 premenopausal patients (HR 9.60; P < 0.0002) and 87 postmenopausal patients (HR 4.04; P = 0.0017). In the subgroup of 42 ER- patients in the validation set, even a profile of only 16 genes appeared to have a strong prognostic value (HR 8.74; P = 0.012). Recently, our 76-gene expression signature was successfully validated in a separate multicenter European study of 180 patients from four institutions (Nijmegen, Munich, Bari, Ljubljana) (HR 7.41; P < 0.0001) with similar sensitivity and specificity.
In the second study, conducted in 112 patients with metastatic disease, using a training set of 46 breast cancers 81 genes were found to be differentially expressed between tamoxifen-responsive and -resistant tumors. From the 81 genes, a predictive signature of 44 genes was extracted and validated in an independent set of 66 tumors. This 44-gene signature is significantly superior (odds ratio [OR] 3.16; P = 0.03) to traditional predictive factors in univariate analysis and significantly related to longer progression-free survival in univariate as well as in multivariate analyses (P = 0.03). The predictive value of the 44-gene signature was recently confirmed in an extended series of 280 patients with advanced disease.
In the first study, the identified 76-gene signature provides a powerful tool for identification of patients at high or low risk for distant recurrence or death due to breast cancer, allowing clinicians to adapt choices of adjuvant systemic therapy. In the second study, the 44-gene signature predicts tamoxifen resistance more accurately than do traditional predictive factors. Interestingly, in a third study DNA methylation status also appeared to be useful in predicting tamoxifen resistance.
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