A dual interest in mathematics and medicine led me, via a Master in Electrical Engineering with medicine/biology courses, to the field of Bioinformatics. My PhD work was centered around large-scale data integration and development of predictive machine learning algorithms for cancer. In 2010, I further pursued my research interests as a postdoctoral fellow at Lawrence Berkeley Lab and the University of California, San Francisco, in the labs of Joe Gray and Laura van ’t Veer. Advanced analytics approaches led me to identify a DNA-repair deficiency signature for prediction of response to PARP inhibition that retrospectively validated in the I-SPY2 breast cancer trial.
Keen to pursue research in an agile environment with impact on patient care, I joined Genentech in 2012 and initially worked on tumor metabolism programs. Since 2014, I have been focused on translational research for breast and lung cancer, with major emphasis on exploiting cancer heterogeneity to enhance our understanding of biology, identify therapeutic vulnerabilities, and inform clinical development. This work is enabled through close collaboration with scientists in Research Molecular Oncology and Oncology Biomarker Development.
Cell Metab. 2018 Sep 4;28(3):383-399.e9.
My research is focused on exploiting cancer heterogeneity to enhance our understanding of biology, identify therapeutic vulnerabilities, and inform clinical development. Some examples: (i) Holistic profiling of HER2+ breast cancer exposed therapeutic opportunities for combining anti-HER2 therapy with anti-androgen agents in breast cancer, and highlighted the potential for broader pan-cancer therapeutic use of HER2 inhibitors. (ii) An in vitro derived and in vivo validated gene expression signature for response prediction to GLS1 inhibition enhanced our mechanistic understanding of glutamine metabolism dependency in cancer. (iii) Metabolomic profiling of pancreatic ductal adenocarcinoma revealed three subtypes with distinct dependencies on glycolysis, lipogenesis and redox pathways, with in vivo confirmation for compounds in clinical development. (iv) Genomic characterization of genetically engineered mouse models of human lung and pancreatic cancer revealed acquired genetic heterogeneity that impacts selective pressure of therapy.
My team at large pursues basic research on disease-related cellular signaling, focuses on target discovery and validation, explores the mechanism of action of drugs, characterizes resistance mechanisms, studies crosstalk between tumor cells and their surroundings, and identifies predictive and prognostic biomarkers, in the oncology field. We thus pretty much touch every phase in drug development, from basic research, translational research, to phase 3 trials. This is enabled through collaboration with Research Molecular Oncology, Research Physiological Chemistry, and Oncology Biomarker Development in Development Sciences.