Skip to main content

 The conceptual framework for the Breast Program is that the distinct biology of the intrinsic subtypes of breast cancer mandate that investigations into etiology, biology, and treatment must not focus upon breast cancer as a disease entity but on subtype-specific lesions or on pathways and molecules mindful that biologic approaches effective in one subset of tumors may be irrelevant in others. We believe that the “low hanging fruit” of single agent biologic therapy has been picked with ER and HER2 targeting; further advances in endocrine resistance, HER2 resistance, and other subtypes will likely require combinatorial approaches and a systems philosophy.

Based on this framework, Program faculty have outlined several strategic areas for research emphasis:

Integrating molecular subtypes into epidemiology and microenvironment

Once one recognizes that breast cancer is not one disease but a family of diseases, it no longer makes sense to ask “what causes breast cancer?” It is likely that gene:gene and gene:environment causes of breast cancer vary by subtype. Our population-based studies, which are among the largest ever performed and systematically oversample young and African-American women, are predicated on the hypotheses that there will be specific predisposition to individual breast cancer subtypes including potential subtype specific associations with defined allelic variants in DNA repair genes, oxidative and hormonal metabolism, and proliferation genes. In addition, we also believe that there will be subtype-specific microenvironmental influences.

Technological advances in imaging and analysis

uilding upon the UNC Nanotechnology Center of Excellence, Biomedical Research Imaging Facility, and our Bioinformatics Core, we are able to provide the translational and clinical mechanisms for testing improved breast imaging and irradiation techniques such as the carbon nanotube-based designs, imaging advances for dynamic MRI and digital tomosynthesis, analysis of microscopic images and of high dimensional datasets as are generated by imaging studies.

Genomic Analyses of Tumors and Normal Breast Tissues

Building upon our history DNA microarray findings, new and additional genomic profiling studies will be performed primarily using RNA-sequencing and DNA-sequencing that are focused primarily upon identifying biomarkers predictive of chemotherapy responsiveness, and markers predictive of new biological agents like kinase inhibitors and PARP inhibitors. These studies will also transition to newer genomic technologies include NexGen sequencing approaches that will quantitate gene expression and simultaneously sequence the entire transcriptome, thus providing a level of detail never achieved before when using DNA microarrays>

Mouse models

We have genetically engineered, or obtained, mouse models representing many of the intrinsic subtypes of breast cancer; in addition we also have patient-derived xenografts as well. These defined models are being used to test combinations and novel agents in the Mouse Phase I Unit (see Molecular Therapeutics). The mouse studies are designed to either mirror or inform human clinical trials

Tissue-based discovery, translation, and clinical research program

Our Program begins with strong integration of laboratory and clinical scientists fostered by an interdisciplinary structure and collaborative environment. We believe that translational research must be bidirectional, meaning embedded correlative studies in clinical trials and tumor/tissue resources being used for basic research questions. Our clinical trials uniformly include correlative endpoints and are either subtype-specific or stratified in analysis. In addition, based upon strong Inter-SPORE and Inter-Center relationships, and the roles several Program members have in national cooperative groups, we are examining tissues from a variety of prospective clinical trials to answer questions about subtype-specificity in response to defined cytotoxic and biologic therapies. We are proud of a track record of taking bench findings and testing them in clinical trials with predefined correlative