Integration of DNA- and RNA- based methods for prediction of response and survival after neoadjuvant chemotherapy for breast cancer

• Applicant: Dr. Bruno Valentin Sinn
• Subject Area: Pathology
• Term: from 2013 to 2015
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 236050770

Breast cancer is the most common cancer in women and accounts for 14% of cancer deaths among women. Therapy decision is based on the evaluation of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) expression. The current understanding of breast cancer biology is based on seminal gene expression studies that led to the definition of different intrinsic phenotypes. The concept of molecular subtyping for therapy decision was recently included in the St. Gallen recommendations for breast cancer management. However, there is no standardized protocol and the method using ER, PR and HER2 immunohistochemistry in combination with the proliferation marker ki67 as surrogate markers for intrinsic subtypes may be subject to technical and analytical problems of immunohistochemistry. Whereas standard approaches serve well for selecting patients for endocrine or anti-HER2 treatment, in many instances it is not clear if a patient will benefit from chemotherapy. There is clinical need for new predictive tests for selecting patients for chemotherapy.Whole-genome analyses are now powerful, cost-effective and fast enough to refine the view on cancer biology beyond the classical gene-expression studies. Data from current studies revealed new insights to breast cancer biology and emphasize a promising new approach to handle with the diversity of this disease. While most of these studies are aiming at the definition of new breast cancer subtypes for a better understanding of breast cancer biology and to find new targetable molecular alterations, the proposed project is focused on using new technologies to answer defined clinical problems, i.e. the prediction of therapy success and survival following neoadjuvant chemotherapy.The project is focused on transcriptome analyses using RNA-sequencing, a deep-sequencing technology that deciphers the transcriptome of a given sample at single-base resolution to examine transcriptional and post-transcriptional elements. These data will be integrated with results from DNA-sequencing and gene expression studies to define subgroups with resistance/response to neoadjuvant chemotherapy. The in-house biobank of the MD Anderson Cancer Center consists of a large, well-characterized collection of formalin-fixed paraffin-embedded and matched fresh-frozen pre-treatment core biopsies from breast cancer patients treated with neoadjuvant chemotherapy. A finding study will be performed using high-quality RNA and DNA from fresh-frozen samples and a subsequent transfer to FFPE tissue. The overall objective is to define molecular markers for prediction of clinical outcome and to develop molecular diagnostic tools that help clinical decision-making in breast cancer. This is the first attempt to define predictive and prognostic breast cancer subgroups based on RNA-sequencing. The results will contribute to improve and individualize clinical decision-making in breast cancer treatment.

• DFG Programme: Research Fellowships
• International Connection: USA
• Host: Professor Dr. W. Fraser Symmans