The human body has a tremendous capacity for healing, but the ability of cells to grow, regenerate tissues, and recruit new blood vessels may also be misused during cancer progression. In many common cancers, especially breast cancer, the ability of tumors to express a set of 512 genes seen normally in a model of wound response is a powerful and accurate predictor of subsequent metastasis and death. The prognostic information of the 512 gene """"""""wound signature"""""""" was independent of and more informative than traditional clinical and pathologic risk factors. The wound signature was also independent of previously identified prognostic signatures and molecular markers. However, the large number of genes involved renders the wound signature difficult to implement in daily clinical practice. The central goal of this proposal is to develop technologies that will greatly simplify the diagnosis of the wound signature. We propose to develop two technologies toward this end. First, we will develop a method to diagnose the wound signature based on detecting DNA amplification of its two regulator genes. Our recent discovery that the wound signature is a consequence of amplification of two key growth regulator genes predicts that measuring the regulator genes will be sufficient to diagnose the wound signature and to prognosticate patient outcome. Second, we will develop a novel gene picking algorithm and RNA amplification technology that can reproduce the prognostic power of the wound signature by measuring only a small fraction of gene transcripts from tumor samples. At the end of the funding period, we envision the capacity to diagnose the wound signature from standard formalin-fixed, paraffin embedded tumor sections. ? ? Breast cancer is the second most common cause of cancer death for women in the United States. These deaths are most often caused by the spread of breast cancer to other sites of the body, a process that involves genes normally reserved for wound healing. Improved technology to identify the wound response genes in breast cancer will improve the risk assessment of breast cancer patients and better guide patients to appropriate therapies. ? ? ?
