Charles M. Perou, PhD

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.