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Defining The Clinical And Functional Role Of An Extracellular Matrix Gene Cluster In Therapy Failure
Scientific abstract There is a clinical need to identify individual patients who will benefit or fail from endocrine therapy, both for patients with primary breast cancer, who may be cured by adjuvant therapy, and for patients with advanced disease. We have recently published a set of 81 genes predictive for the response to the anti-estrogen tamoxifen. For this, we used whole genome gene expression profiling of estrogen receptor–positive (ER+) primary breast tumors from patients with advanced disease. A 44-gene signature was extracted which is superior to traditional predictive factors and significantly related with a longer progression-free-survival (PFS). Based on Receiver Operator Characteristic (ROC) analysis for type of response and Spearman correlation analysis for PFS, 22 genes were validated with quantitative RT-PCR (qRT-PCR) assays on a larger set of 253 tumors. In this larger cohort 14 genes retained significance. Interestingly, 5 of these genes belong to a cluster of 6 genes -originally identified in our 81-gene profile to be- related to extracellular matrix (ECM) activities. In this ECM-cluster, TIMP3, COL1A1 and SPARC had been identified as myo-epithelial cell markers. Furthermore, three ECM-genes have been reported to be upregulated by estrogens but are downregulated in HER2-transfected cells. We hypothesize that overexpression of genes of the ECM-cluster causes endocrine therapy resistance and that this might identify tumors of myo-epithelial origin, which are related with an aggressive phenotype and poorer prognosis. It is our goal to determine the clinical and functional importance of the ECM-cluster and to ascertain how overexpression of its genes may be detrimental to the beneficial effects of endocrine therapy. To unravel the clinical significance, ECM-cluster expression will be measured by qRT-PCR and imunohistochemistry in primary breast tumors from clearly defined subsets of patients with known disease outcome, therapy response, and histopathology. The functional role of this cluster will be characterized in cell-based systems by siRNA and gene transfection (down- and upregulation, respectively) to determine its role in drug responsiveness. Furthermore, the efficacy of modulators to target ECM-genes in breast tumor cells will be assessed. The outcome of this study provides evidence for the relevance of the ECM-cluster in therapy failure that could improve diagnosis and provide new targets for treatment.
Breast cancer becomes life threatening when tumor cells metastasise, i.e. spread across the body. Although the cure rates have improved due to earlier detection and improved treatment modalities, there still is a considerable number of affected women that suffer from its morbidity and/or die from the disease. About three quarters of breast tumors express the estrogen receptor, which is an important target for treatment. In primary and metastatic breast cancer the anti-estrogen tamoxifen is widely used as treatment. This drug interferes with the growth stimulating effects of the female sex steroid hormone estrogen, thus blocking tumor growth. Unfortunately, half of the patients do not respond at start of treatment. To identify patients who will benefit from tamoxifen therapy we have generated a predictive gene signature using whole genome gene expression profiling. We have recently published a set of 81 genes predictive for the response to tamoxifen therapy in patients with metastatic disease. We validated 22 genes in a larger set of 253 tumors and 14 of these genes correlate significantly with anti-hormone therapy failure. Interestingly, 5 genes belong to a cluster of 6 genes, originally identified in our 81-gene profile, that are related to extracellular matrix (ECM) activities. In this ECM-cluster, the genes TIMP3, COL1A1 and SPARC have been identified as myo-epithelial cell markers. We aim to elucidate the clinical and functional relevance of the ECM-cluster in relation with therapy response and to identify tumors of myo-epithelial origin. Understanding the biology of the ECM-cluster in relation with therapy resistance could lead to an increased therapy response. A better identification of myo-epithelial tumors, which have been reported to be of a more aggressive phenotype and of poorer prognosis, will result in better diagnostic tests. T he outcome of this study will determine the relevance of the ECM-gene cluster in therapy failure and could help to improve diagnosis and therapy modalities.