About

• Mentorship Training Completions:
• 

• Department Affiliations:
• Genetics

• Other UNC PhD Program Affiliations:
• Genetics and Molecular Biology; Bioinformatics and Computational Biology; Pathobiology and Translational Science

Breast cancer is a prevalent disease with known clinical and molecular diversity. To address these challenges, my research team uses a multidisciplinary approach based upon genomics, genetics, cancer biology, bioinformatics, epidemiology, and clinical research to improve the outcomes of cancer patients. A major contribution of mine has been the discovery of the intrinsic subtypes of breast cancer. We demonstrated that breast cancers can be divided into at least five molecular subtypes using the “PAM50” assay, with my lab focusing particular attention on the Basal-like subtype, which represents ~80% of Triple Negative Breast Cancers. In addition, we have translated these molecular classifications into the human population; specifically, by using the Carolina Breast Cancer Study (CBCS), we have found that young African American (AA) women are diagnosed with Basal-like Breast Cancers approximately twice as often as their Caucasian counterparts. These results provide a partial explanation of the racial outcomes disparity in the USA between AAs and Caucasians; however, additional studies are needed and are an emphasis of our ongoing research.

Our main research focus includes identifying the drivers of metastatic disease, determining the role of the adaptive immune system in breast tumor progression, and improving therapeutic targeting of TNBC/Basal-like tumors. We use a multitude of experimental and computational approaches, including RNA-sequencing (RNAseq), single-cell approaches, proteomics, DNA exome and whole genome sequencing, cell culture, and mouse models. We use these approaches to discover the causative events of each molecular subtype in human tumors and then model these events in cell lines and mouse models where we can investigate tumor biology and immune system interactions. All of these genomic studies generate large volumes of data, and thus a significant portion of my lab is devoted to computational approaches to use these multi-omics data to develop statistical predictors of tumor responsiveness and long-term patient outcomes.

I am currently a Professor in the Department of Genetics, and have been a faculty member at UNC-Chapel Hill since 2000. I am also the Co-Director of the Computational Medicine Program, Faculty Director of the LCCC Bioinformatics Group, and Co-Director of the LCCC Breast Cancer Research Program. I am a member of the AACR, ASCO, the ALLIANCE Breast Committee, and the Translational Breast Cancer Research Consortium. My lab has received support from the NIH/NCI, Susan G. Komen, V Foundation for Cancer Research, and Breast Cancer Research Foundation. I have also co-founded three genomics-based biotechnology companies that are bringing new genomic tests into clinical care.

I actively strive to foster a diverse work environment, including people from different cultures and training backgrounds (i.e., biologists, geneticists, bioinformaticians, statisticians, oncologists, surgical oncologists, pathologists, and others). I am actively seeking new graduate students, medical fellows, and postdoctoral fellows, and have opportunities available for both experimentalists and computational scientists.

My Research

Human carcinomas show great diversity in their morphologies, clinical histories and responsiveness to therapy. This wide tumor diversity poses the main challenge for the effective treatment of cancer patients. The focus of my lab is to characterize the biological diversity of human tumors using genomics, genetics, and cell biology, and then to use this information to develop improved treatments that are specific for each tumor subtype and for each patient. A significant contribution of ours towards the goal of personalized medicine has been in the genomic characterization of human breast tumors, which identified the Intrinsic Subtypes of Breast Cancer. These Intrinsic Subtypes are predictive of relapse-free survival, overall survival and responsiveness to chemotherapy and some molecularly targeted agents.

We study many human solid tumor disease types using multiple experimental approaches including RNA-sequencing (RNA-seq), DNA exome sequencing, Whole Genome Sequencing (WGS), cell/tissue culturing, and Proteomics, with a particular focus on the Basal-like/Triple Negative Breast Cancer subtype. In addition, we are mimicking these human tumor alterations in Genetically Engineered Mouse Models, and using established primary tumor Patient-Derived Xenografts (PDXs), to investigate the efficacy of new drugs and new drug combinations. All of these genomic and genetic studies generate large volumes of data; thus, a significant portion of my lab is devoted to using genomic data and a systems biology approach to create computational predictors of complex cancer phenotypes, which will ultimately be applied in the clinic.

My lab utilizes a multi-disciplinary team spanning cancer biology, genomics, genetics, bioinformatics, statistics, systems biology, and the clinical treatment of cancer patients. In addition to our experimental approaches, we are also developing novel computational approaches and algorithms that will predict patient survival and complex phenotypes including tumor responsiveness to a variety of novel drugs. Some of our assays are already used in the clinic and we have more in development. I am actively seeking new graduate students, medical fellows, and postdocs and have opportunities available for both experimental and computational scientists.