Herbert Levine, Ph.D. & Xuefei Li, Ph.D.

Funded in Collaboration with Stand Up To Cancer (SU2C)

Clinical oncology has entered an era of personalized molecular diagnosis and targeted therapy. This means treatments are tailored to each patient based her tumor’s histopathological and genetic characteristics. Such personalized treatment often involves a combination of multiple active agents to treat one tumor. In estrogen receptor positive (ER+) breast cancers, the three most promising classes of treatments are hormonal therapy, PI3K pathway inhibitors and cell cycle inhibitors.

Although patients derive benefit from such treatment, for most of the advanced ER+ breast cancers, the tumors respond initially but then stop responding, which is called “resistance” to therapy. Unfortunately, this resistance results in death in most cases of advanced breast cancer. Treating these cases requires developing novel therapeutic strategies to overcome the resistance based on an understanding of the mechanisms of resistance.

In this project, we leverage the leading edge technology of high-throughput whole-genome screening to discover mechanisms of resistance to each of three classes of drugs and all of their combinations. We also characterize the identified genes and their function in a variety of breast cancer cell types and mouse models. The knowledge of resistance to treatment obtained through this project will guide our effort to design more effective combinational therapeutics to overcome resistance. Ultimately, this work will be translated to benefit most of the patients with ER+ breast cancers.

Location: Rice University - Texas
Proposal: Computational Modeling of the Tumor Microenvironment
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