The search for predictive markers in the treatment of breast cancer patients
07 / 2009 - unknown
Breast cancer is the most frequently occurring cancer in women, with over a million of newly diagnosed cases worldwide each year. Since 70% of all breast tumors grow dependent on estrogen receptor alpha (ERalpha) activity, therapy is focused on inhibiting this hormone-activated transcription factor. Patients are commonly treated with tamoxifen or aromatase inhibitors, but resistance against these compounds occurs in 30-50% of the treated breast cancer patients. Finding classification criteria, by which the effectiveness of anti-hormonal medication can be determined may aid in optimal treatment selection. ERalpha can bind to over a 1000 genes in the genome of human breast cancer cells, including genes that are essential for tumor-growth. In aromatase inhibitor or tamoxifen resistant cells, ERalpha may associate to a specific set of genes that are essential and characteristic for the resistance-associated cell proliferation and tumor growth. In this research, we will search for the specific binding sites of active ERalpha under treatment-resistant conditions throughout the entire human genome. Activity of these genes will also be verified in treatment-resistant tumor samples, enabling the determination of gene activity directly in patient material. This way, we can find prediction criteria for the most optimal treatment for each individual breast cancer patient.