(4ap) Systems Biology Approaches for Cancer Diagnostics and Therapeutics | AIChE

(4ap) Systems Biology Approaches for Cancer Diagnostics and Therapeutics

Authors 

Graham, N. A. - Presenter, California Institute of Technology



New measurement technologies have transformed biology from a qualitative, descriptive field into a quantitative, multiparameter science. This transition has enabled the development of integrated, systems models of disease that bridge traditional biology and quantitative sciences including chemical engineering. I am passionate about harnessing the power of quantitative systems approaches to uncover novel biology in order to design new diagnostics and therapeutics, with a particular focus on cancer.

My graduate research at Caltech focused on crosstalk within biomolecular signaling networks, particularly between soluble and insoluble microenvironmental cues such as peptide ligands (eg, EGF) and intercellular contact (eg, cadherins). This research provided a foundation in quantitative cellular biology and shaped my interest in how cancer cells deregulate physiological signals to achieve pathological behavior. 

For my postdoctoral research, I joined the Department of Molecular and Medical Pharmacology at UCLA to study translational and systems approaches to cancer diagnostics and therapeutics. Here, I will present three studies from my postdoctoral research: i) a systems analysis of positive feedback in signal transduction networks that underlies cancer cell death following metabolic perturbations; ii) development and application of a novel bioinformatic approach (self-organizing maps) to analyze single-cell, multiparameter data from microfluidic measurements of brain tumor biopsies; and iii) phospho-proteomic analysis of mouse and human prostate cancer tissues to predict therapeutic treatment modalities.

My future research program will synthesize my training in both engineering and biology. I will build a highly collaborative research program that integrates genomic, proteomic and metabolomic data to build predictive, systems models of disease. In collaboration with physician scientists and clinicians, I will generate and integrate quantitative biological data to uncover novel biological mechanisms with translational relevance. My training in chemical engineering, biological sciences and bioinformatics has positioned me at the forefront of the interdisciplinary field of cancer systems biology, where I will play a central role in discovering novel cancer biology that can be exploited for both diagnostics and therapeutics.

PhD: California Institute of Technology (2007), Dept of Chemical Engineering, Advisor Anand R. Asthagiri

Postdoc: University of California, Los Angeles, David Geffen School of Medicine, Dept of Molecular and Medical Pharmacology, Advisor Thomas G. Graeber