University of North Carolina Chapel Hill, North Carolina
May Goldman Shaw Distinguished Professor of Molecular Oncology Research Professor of Genetics & Pathology Lineberger Comprehensive Cancer Center
Using cutting-edge sequencing technologies and artificial intelligence to better understand the complexity of breast cancer and improve personalized medicine.
The goal of personalized medicine is to find the right therapy for each patient, based on the unique features driving that individual’s tumor growth. Tumors can vary widely between patients for several reasons: inherited genetic differences, mutations and genetic changes that develop during a patient’s lifetime, or the composition of the tumor microenvironment—the cells, structures, and molecules that surround a tumor and affect its progression. All contribute to the tumor’s susceptibility to therapies. Dr. Perou and his team employ a sequencing technology that analyzes genetic information from individual cells (single cell sequencing). This allows for more precise characterization of all cells, including immune cells that infiltrate the tumor, and provides a picture of which cells are present. Dr. Perou’s long-term goal is to improve therapies and the accuracy of prognoses.
Dr. Perou is known for developing assays which identify breast cancer subtypes, and that information is converted into a “risk score” that guides a patient’s clinical care. However, this risk score currently only applies to patients whose tumors are ER-positive and HER2-negative. Previous studies from Dr. Perou’s group established a set of genetic signatures from immune cells that could be used in prognostic risk scores for other subtypes of breast cancer, namely HER-positive and triple-negative (TNBC). The team recently analyzed 400 TNBC tumor samples from patients treated with multi-agent neoadjuvant chemotherapy. The results showed that the best genomic predictors of successful treatment response are immune cell features. B cells and T cells in particular predicted both a higher likelihood of tumor shrinkage and longer patient survival times. These data are now being used to develop a multi-feature genomic prognosis tool for early-stage TNBC.
In the coming year, Dr. Perou will continue to focus on tumor-immune cell interactions and investigate the role of the immune system in late-stage metastatic cancers where immunity seems to be diminished. Dr. Perou and his team are developing complex breast cancer models for the evaluation of immunity in the metastatic process. They will then use these models to evaluate the next generation of cancer immunotherapies and develop computational models to predict tumor response to therapy.
The goal of a physician is to find the right medicine for the right patient, based on the unique features driving that individual’s tumor growth. –Dr. Perou
Dr. Perou is a member of the Lineberger Comprehensive Cancer Center at UNC, and the Scientific Director of the UNC Bioinformatics Core. He received his PhD in Cellular and Molecular Biology from the Department of Pathology at the University of Utah (1996) where he cloned the human Chediak-Higashi Syndrome gene. He next performed his postdoctoral training in the laboratory of David Botstein at Stanford University (1997-2000) where he began his genomic studies of human tumors using DNA microarrays. These genomic analyses resulted in the identification of novel subtypes of human breast tumors that predict patient survival times and response to therapy. Dr. Perou’s laboratory at UNC is focused on using genomics, genetics, and laboratory models to decipher the underlying biology of the molecular subtypes of breast cancer. He then uses this biological information to develop novel therapeutic strategies that are specifically targeted against each of these distinct subtypes of breast cancer.
2003
The Susan Hertog Award
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