Mathematical Biology Seminar
Friday, November 1, 2019, 1:30pm, 235 Physics
James Alvarez (Duke University, Pharmacology and Cancer Biology)
Adaptation and selection during residual disease and tumor recurrence
Abstract:
Tumor recurrence following therapy is the leading cause of death in many cancer types, including some of the most common epithelial tumors such as breast and prostate cancer. Many breast tumors recur more than 5 years after initial surgery and treatment, and recurrences as long as 20 years following therapy have been documented. This has led to the suggestion that a population of tumor cells – referred to as minimal residual disease – can survive treatment and persist in a dormant, clinically undetectable state for years or even decades. These dormant residual cells are the likely reservoir for disease recurrence. Because recurrent breast cancer is generally incurable, developing strategies to forestall recurrence by therapeutically targeting residual cells during the dormant stage is of paramount importance. While recent work in this area has focused on specific pathways that promote the survival and recurrence of dormant cells, several fundamental questions about dormancy have not yet been addressed: How does the clonal composition of tumors change during dormancy and recurrence? Is tumor recurrence driven by the selection of a subset of dormant residual cells? Do dormant tumor cells undergo adaptive changes that allow them to recur? Because primary breast tumors are be heterogeneous, harboring different subclones of (epi)genetically distinct cells, it is likely that dormancy and recurrence are accompanied by profound changes in the clonal composition of tumors. However, the clonal dynamics of these processes has not been examined, due in part to the difficulty in studying dormant residual disease in humans. We are using a validated mouse model of breast cancer dormancy and recurrence to study clonal evolution during residual disease and recurrence. To do this, we are taking a cellular barcoding approach, which allows us to directly assess, on a single-cell level, how the clonal composition of tumors changes during dormancy and recurrence. Importantly, combining barcoding with this genetically engineered mouse model can provide novel insights that could not be found using other approaches.

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