Current Research in the Westbrook Lab

Translating oncogene-induced stress pathways into cancer therapies

The cancer community has largely studied the effects of oncogenes and tumor suppressors and how they contribute to the “pro-tumorigenic” hallmarks of cancer cells. However, it’s also become clear that oncogenes themselves induce a variety of stresses in cancer cells such as metabolic reprogramming, oxidative pressures, mitotic instability, and proteomic imbalance. These stress phenotypes can serve to antagonize tumor growth and survival. The idea that oncogenes confer a highly stressed state onto cancer cells predicts that strategies to exacerbate one or more of these oncogene-induced stresses could tilt this balance in favor of killing cancer cells. We are exploiting the idea of oncogene-induced stresses for therapeutic discovery by tackling several poorly understood questions:  (1) what are the molecular mechanisms by which prominent oncogenes (ex. Myc, Ras, etc.) induce these stresses? (2) how do cancer cells tolerate these stresses? and (3) are these stress support pathways different in normal and tumor cells? By using forward genetic approaches, we have made surprising discoveries about the endogenous cell pathways that are required to tolerate predominant oncogenic drivers like c-Myc (ex. Kessler et al, Science 2012; Hsu et al, Nature 2015). We are now extending these studies by elucidating the stress support pathways that enable cancer cells to tolerate other prominent drivers of breast cancer.

Identifying oncogene and tumor suppressor networks via functional genetic screens

With the explosion of genomic data emerging from TCGA, COSMIC, and other cancer genome initiatives, there are fundamental challenges in (1) discerning which mutant genes are critical cancer drivers, (2) discerning how these drivers are connected in genetic / signaling networks, and (3) finding key drivers that have not been uncovered by these genomic analyses. We are addressing these important questions by developing genetic screens in human and mouse systems for new tumor suppressors and oncogenes. Using novel genetic platforms, we are uncovering signaling networks that control tumor initiation and progression. For instance, a series of our genetic screens in breast cancer have uncovered an interconnected network of over 40 new tumor suppressor (PTPN12, REST, INPP4B, etc.) and oncogenes (PLK1, SCYL1, TEX14, etc.) with unappreciated roles in human cancer (ex. Sun et al., Cell 2011; Karlin et al, Cell Reports 2014). We are systematically applying genetic, cell biologic, and biochemical approaches to understand the functions of these gene networks in controlling breast cancer pathogenesis.

Repositioning anti-cancer therapies for triple-negative breast cancer (TNBC)

Breast cancer is a collection of diseases with heterogeneous molecular features and clinical behaviors. Among these disease subtypes, triple-negative breast cancer (TNBC) is the most aggressive, and the molecular determinants of TNBC are poorly understood. Recently, our group has discovered new tumor suppressor networks that are disrupted in more than 70 percent of TNBCs (Sun et al., Cell 2011; Nair et al., Nature Medicine 2018), with the tyrosine phosphatase PTPN12 acting as a core component of this network. Importantly, disruption of this tumor suppressor network leads to the concerted hyper-activation of a class of receptor tyrosine kinases. These kinases work together to drive TNBC and probably other cancers. Importantly, we have shown that pharmacologic inhibition of these collaborating kinases leads to tumor regression of primary TNBCs in vivo. We are currently dissecting the mechanism(s) by which these signaling pathways cooperate, and translating these discoveries into new clinical trials for TNBC patients at Baylor College of Medicine.

Understanding drug resistance in breast cancer

Targeted therapies have revolutionized cancer treatment. These new medicines antagonize the survival and progression of tumors by inhibiting cancer-driving oncogenes. However, despite the early success of these therapies, there is substantive heterogeneity in the initial and long-term response of tumors to these therapies. A major goal in our group is to discover the mechanisms governing how tumors respond to targeted therapies and translating these discoveries into better ways of predicting patient response. Using new genetic screening technologies, we have developed an approach to identify signaling networks that govern how cancer cells respond to targeted therapies. By using this approach, we are dissecting both the mechanisms of drug-action and pathways to resistance for agents that are in the clinic as well as drugs soon to be approved as new cancer therapies.