List of Collaborating Institutions
California Institute of Technology
University of California, Los Angeles
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Cellular transitions between two distinct states are fundamental to many steps of carcinogenesis and tumor progression. Such transitions are broadly studied, but general models have been historically limited to qualitative descriptions. This contrasts with phase transitions in physical systems, such as the transition between ferro- and paramagnetic states, which are well characterized within the context of the physico-chemical laws, and can be partially understood, in a predictive capacity, using simple, precise models such as the Ising model. Such models are based upon a system of interacting lattice sites. A parameter (e.g. temperature) is varied, and the fluctuations of the lattice sites are analyzed as the system approaches and passes through a critical point. These models are largely independent of many details of the specific system under study; the critical system-specific details are captured in the interactions between the lattice sites. Nevertheless, they can yield specific predictions that can, in principle, be experimentally verified, such as increased fluctuations in the vicinity of the critical point, and the loss of one or more degrees of freedom at the critical point. Ising-like in silico models have guided theoretical studies of transitions in various gene or protein regulatory networks, although resultant predictions can be challenging to experimentally test.
We seek a potentially general approach where the experimental input is a statistically large number of single cell measurements, with many analytes quantitatively measured from each cell. From this data we capture the fluctuations and thereby determine the correlations of many analytes. In an Ising model analogy, such measurements define the site interactions. These inputs permit straightforward theoretic models for resolving cellular steady states, transitions between steady states, and for making testable predictions. Studies of the chemically-induced-carcinogenesis transition are provided as preliminary data/proof of concept. For Aim 1 we develop a picture of cancer cell steady states using integrated metabolic and proteomic single cell assays. In Aims 2 and 3 we expand this approach to two apparent cellular transitions associated with cancer drug resistance: the adaptation of heterogeneous brain cancers to certain targeted inhibitors, and a drug-induced cellular de-differentiation observed in melanomas (and other tumors) in response to immunotherapy and targeted inhibitors. All aims are joint experiment/theory aims. Aims 2-3 involve in vivo testing of predictions.
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Dr. James Heath, PhD.
Dr. James Heath is the PI of this PS-OP. He is the Gilloon Professor of Chemistry at Caltech, co-director of Parker Institute for Cancer Immunotherapy at UCLA, and director of Institute for Systems Biology. He received his Ph.D. from Rice University in 1988. The Heath lab works on fundamental problems at the interface of the chemical, physical, biological and biomedical sciences, with focus areas of molecular biotechnologies, and oncology. The biological/biomedical research is relatively new (past 10 years), as my previous research history was in the areas of nanomaterials, solid-state physics, and nano/molecular electronics.
Dr. Wei Wei, PhD.
Dr. Wei Wei is the PI of this PS-OP. He is an Assistant Professor in the Department of Molecular and Medical Pharmacology at UCLA School of Medicine. He received his Ph.D. from Caltech in 2014. The Wei lab works on developing and employing a unique suite of single cell tools to cultivate new understanding and address significant questions in cancer research. Specifically, 1) Develop multi-omics single cell tools for interrogating the heterogeneous tumor cells and immune cells at multiple bimolecular levels. 2) Information theoretical and computational approaches for dissecting the high-dimensional single cell data with a particular focus on resolving tumor heterogeneity and dynamics of the signal transduction network for anticipating therapy resistance and identifying effective combination therapies. 3) Isolation, molecular characterization, and neoantigen identification of rare tumor cells in body fluids for cancer diagnosis and immunotherapy.
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Dr. Antoni Ribas
Dr. Antoni Ribas is a co-investigator of this PS-OP. He is a Professor of Medicine, Surgery and Molecular and Medical Pharmacology, and director of Parker Institute for Cancer Immunotherapy at UCLA. The Ribas lab has focused on the understating of melanoma biology and how it interacts with the immune system, with the main goal of clinical translation. We have conducted a series of investigator-initiated and industry-sponsored clinical trials, most of which have been focused on the treatment of metastatic melanoma and have involved laboratory-based correlates of mechanism of action and antitumor activity. These clinical trials have included dendritic cell-based vaccines, adoptive cell transfer with T cell receptor (TCR) engineered lymphocytes, anti-CTLA4 antibodies, anti-PD-1 antibodies, BRAF-targeted therapies and nanoparticle-siRNA. The major focus has been in understanding how best to treat melanoma using tumor immunotherapy and targeted therapies based on the understanding of the biological principles governing their antitumor activity.
Dr. Raphael Levine
Dr. Raphael Levine is a co-investigator of this PS-OP. He is a Distinguished Professor of Chemistry and Biochemistry at UCLA, member of NAS and AAAS, and recipient of Wolf Prize in Chemistry. He is a theorist interested in the role of energy in the chemical and biological change. His work on the selectivity of energy consumption and specificity of energy disposal in elementary chemical reactions led to the introduction of surprisal analysis. Since then this analysis has been employed in many areas of science including nuclear physics, image recognition and intensification and aeronautical, chemical and biomolecular engineering. Dr. Levine is often considered as one of the fathers of the field of molecular reaction dynamics. Dr. Levine will apply surprisal analysis to discuss biological transitions as characterized through measurements on single cells.
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