Clare Yu, Ph.D. & Juliana “Julie” Wortman

Funded in Collaboration with Stand Up To Cancer (SU2C)

The goal of an exciting new form of immunotherapy is to get the immune system to kill cancer cells. When killer T cells arrive to kill tumor cells, some cancer cells are able to prevent this attack by inserting a protein that acts like a “key” (e.g., a PD1 ligand where ‘PD’ stands for Programmed Death) into a “keyhole” (e.g., a PD1 receptor) on the killer T cell.  Anti-PD1 immunotherapy drugs like nivolumab and pembrolizumab block the keyholes and prevent cancer cells from turning off the killer T cells. Such immunotherapy drugs are particularly effective when killer T cells have infiltrated the tumor. The goal of our project is to understand what features of the microenvironment of the tumor enhance the infiltration of killer T cells into the tumor. The tumor microenvironment, which includes cells, protein structures (like collagen fibers) made by some of these cells, blood vessels, and lymph vessels, typically provides a supporting environment for the tumor to grow. However, changes to the tumor microenvironment can inhibit the growth of the tumor and even lead to its demise. We will carefully characterize the spatial arrangements of the different types of cells and structures in the breast cancer tumor microenvironment in an effort to determine what enhances infiltration by killer T cells. Knowing this could lead to more effective immunotherapy.

Steven Altschuler, Ph.D. & Xiaoxiao Sun, Ph.D.

Funded in Collaboration With Stand Up To Cancer (SU2C)

One of the foremost challenges to cancer treatment is the emergence of drug resistance.  Adding complexity to this problem is the realization that both the initial as well as the emergent drug-resistant cancer population can be in highly heterogeneous epigenetic and genetic states and from populations of very different sizes.  This heterogeneity makes it difficult to predict which cells will survive drug treatment and which drug-resistance mechanism will emerge, repopulate the cancer cell population and ultimately cause relapse.  Our goal is to better understand which cellular subpopulations are predisposed to initially survive targeted therapy, how diverse these subpopulations are from one another, and combination therapies would best target these subpopulations.  To accomplish this, we will make use of novel high-throughput assays for drug treatment, genomic and image analysis and mathematical analysis of cellular heterogenity and evolution.  These studies will address questions that are central to the fields of cancer biology, modeling, and cancer therapeutics, and allow us to test novel therapeutic approaches that can then be rapidly translated to the clinical context.

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