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Predicting Response to First-line Trastuzumab: eTag Analysis of Primary Breast Tumor Predictive Factors, and Metastatic Serum Biomarker Analysis
Background: Metastatic breast cancer patients are currently selected for trastuzumab (Herceptin) treatment by positive testing for HER-2/neu IHC 3+ / FISH amplification from the primary breast tumor, but less than 40 % of these patients will respond to first-line metastatic treatment with trastuzumab monotherapy, and most patients who do respond will unfortunately progress within a year with acquired resistance. The rapid development of novel treatments for HER-2/neu-positive breast cancer has created a critical need for more effective biomarkers from the primary breast tumors and from metastatic serum to predict response to first-line trastuzumab therapy. Hypothesis: Successful identification of novel, effective surrogate predictive biomarkers of metastatic breast cancer patient response to first-line trastuzumab will maximize the effectiveness of the growing choice of novel HER-2/neu therapies for individual patients. Specific Aims: 1) Determine the ability of HER family total, homo- and heterodimers, and AKT /TSC dimers assayed using eTag analysis of an international retrospective consortium primary breast tumor bank to predict patient response to first-line trastuzumab-containing therapy. 2) Determine the ability of serum EGFR, IGF-IR, uPA, TIMP-1, and endoglin assayed from an international consortium retrospective pretreatment and serial metastatic serum bank to predict patient response to first-line trastuzumab-containing therapy. Study Design: Primary breast cancer FFPE sections derived from a retrospective international study consortium (chaired by the PI) comprising over 300 metastatic breast cancer patients will be subjected to HER family pathway eTag analysis and correlated with computerized clinical outcome to first-line trastuzumab therapy. Matching serial serum from these patients will also be analyzed using ELISA assays for the proven serum biomarkers EGFR, IGF-IR, uPA, TIMP-1, and endoglin; combined with known serum HER-2/neu data, and computerized correlative analysis conducted to maximize the biomarker combinations for prediction of optimal patient response to first-line trastuzumab-containing therapy. Potential Outcomes/Benefits: Successful identification of effective biomarkers from eTag primary tumor analysis and from ELISA metastatic serum analysis to predict trastuzumab response will maximize the evidence-based use of surrogate molecular markers for patient selection for novel HER-2/neu-targeted therapies.
About 25 % of breast cancer patients have a specific cancer called HER-2/neu-positive. HER-2/neu is a breast cancer cell surface receptor that is amplified hundreds of times compared to normal cells and is a hallmark sign of a more aggressive cancer. Trastuzumab (Herceptin) is the newer monoclonal antibody treatment for this specific type of breast cancer, and it acts by specifically binding to this HER-2/neu receptor and inhibiting its activation and subsequent aggressive tumor growth and spreading (metastatic) behavior, much like a key fits only one of many locks. Why do only 40% of metastatic HER-2/neu-positive breast cancer patients have a good response to this Herceptin treatment alone? The answer to this question is still largely unknown, but some mechanisms are being discovered, such as the tumor cell removing the outside antibody binding portion and therefore not binding the trastuzumab, or by circumventing the binding system by activating the HER-2/neu cancer cell using other mechanisms either on the surface or inside of the cell (alternative activation) and therefore rendering the Herceptin antibody useless to stop this alternative tumor cell activation. What can be done to better identify the 40 % of patients whose breast cancer cell aggressiveness will be slowed down using the trastuzumab treatment, and to select the other 60 % of patients who will not respond and might be better treated using the newer agents being developed against HER-2/neu ?positive breast cancers? This is the critical question to be answered as soon as possible. We propose to do this by measuring the amounts of novel predictive biomarkers in both the primary breast cancer tumor (novel eTag technology) and in the blood serum samples (conventional ELISA technology) taken before and during the time this group of breast cancer patients first receive Herceptin therapy to treat the distant metastasis of their breast cancer. Once the best combinations of these predictive biomarkers are optimized using computerized statistical analysis, we then propose that this best biomarker combination be used to select those patients ahead of time who would be most likely to respond to Herceptin treatment, and also to select those patients who will not respond and who could then be changed to newer, more effective therapies to attack the HER-2/neu target at different points. We have already identified a large group of over 300 patients by teaming with an international consortium of participating oncologists (chaired by the PI) from a previous project measuring serum HER-2/neu. The patients? breast tumor tissue and serum biomarker data will be combined with their known response to Herceptin therapy to generate the large database that is critical for determining individualized selection of the best HER-2/neu therapy choice for future patients.