Abstract SY25-03: Targeting the RAS signal transduction network in cancer cells

Abstract

Abstract Activating mutations of the RAS family of oncogenes are among the most frequent aberrations found in cancer. In addition, signals from receptor tyrosine kinases as well as mutations down-stream of RAS, such as BRAF or PIK3CA, lead to abnormal activation of the RAS signal transduction network in cancer cells. Since the RAS proteins are considered “undruggable”, a variety of agents has been developed targeting down-stream effectors of RAS that are being tested clinically. In addition, inhibitors of receptor tyrosine kinases have demonstrated clinical activity in a variety of diseases. However, the anti-tumor efficacy of these agents is strongly dependent on the molecular context in target cells. Thus, identification of cancer subtypes with particular sensitivity to perturbation of individual network components is pivotal for further development of such compounds. Furthermore, it has become clear that oncogenic molecular networks are complex in structure and dynamic behavior, thus mediating resistance to targeted therapeutics in cancer cells to treatment with such inhibitors through unpredicted mechanisms. In particular feedback and feed-forward mechanisms appear to be relevant. For example, feedback-activation of the PI3 kinase pathways upon inhibition of mTOR has been demonstrated to be clinically relevant. Therefore, capturing molecular responses to targeted agents in cancer cells comprehensively is important, in particular for the rational development of drug combinations aiming at preventing cancer cells from mounting molecular “escape” responses following inhibition of key network components. The availability of advanced genomic and proteomic technologies has facilitated capturing complex molecular responses to molecular perturbations at the systems level. We have employed such an approach to characterize network responses to molecular agents targeting RAS effector pathways. Basal-type breast cancer cells were found to be particularly susceptible to growth-inhibition by small-molecule MEK inhibitors. Furthermore, we discovered a negative feedback loop between the MEK and PI3 kinase pathways resulting in activation of AKT in response to inhibition of MEK in an EGFR-dependent fashion. While these findings were made initially in models of breast cancer, we have recently been able to demonstrate that they also apply to pancreatic cancer cell lines and xenograft tumors derived from these cell lines in nude mice. Comprehensive data on molecular responses can be utilized for the development of mathematical models describing the interaction of signal transduction network components. Such models, in particular mechanistic dynamical simulation and inferential data mining approaches, are promising tools for in silico experimentation with the goal of predicting cellular consequences of molecular perturbations. We are employing Bayesian network inference models aiming at reconstructing molecular interactions within the RAS signal transduction network. Initial simulations revealed novel, MEK-dependent, regulators of the cell cycle. Such approach could identify novel interactions of molecular networks as candidate targets for combination therapies. Citation Format: W. Michael Korn. Targeting the RAS signal transduction network in cancer cells [abstract]. In: Proceedings of the AACR 101st Annual Meeting 2010; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr SY25-03