Management of breast cancer patients would clearly be optimized if clinicians had a molecular fingerprint of a patient's tumor at the time of diagnosis that would accurately predict recurrence and treatment response. Therefore, goal of this continuing project is to identify clinically useful biomarkers that will add to existing factors already validated by our group to provide this fingerprint, and to then apply appropriate statistical methodology for their incorporation into indices that can be used in routine patient management. During the present project period we have examined more than 20 potential prognostic markers, including p53, HER-2, S-phase fraction, and our new cell cycle protein mitosin. We have also compared the major factor integration techniques, contributed to the statistical technology for factor evaluation, provided the first demonstration that HER-2 may be associated with CMF resistance, and developed a basic but powerful index for identifying patients at very high risk of recurrence for aggressive adjuvant treatment. To achieve our overall goal, we now propose: (1) To create prognostic indices for patients with primary breast cancer, by: a) using nine commonly available factors to create an index of extremely low recurrence risk, b) validating new proliferation markers including mitosin and Ki67 to replace flow cytometric S-phase in this index, c) expanding this index by including promising newer markers of proliferation, differentiation, and metastatic potential, and D) expanding our index of very high recurrence risk by including additional commonly available factors and promising newer markers; and (2) To evaluate standard and investigational biomarkers for their ability to predict response to adjuvant CMF and to adjuvant tamoxifen, using tissues from two large randomized controlled treatment trails with long clinical follow-up.
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