Signal Transduction

Modeling signal transduction of receptor tyrosine kinases.

One aspect of my work has focused on understanding how the proteomic makeup of a cell drives the response to growth factors that are part of the microenvironment. Using high throughput fixed-cell microscopy I have examined the signaling responses in a small panel of breast cancer cell lines and used both statistical analysis and ODE modeling to identify the protein determinants that drive signaling as well as understanding novel aspects of the signal transduction pathways.

Through a collaboration with Steve Wiley and Wei-Jun Qian at the PNNL we are using high-sensitivity quantitative SRM proteomics to look specifically at the feedback regulators of the MAPK pathway that gives rise to cell type-specific response kinetics following EGF or HGF treatment. We are also attempting to expand this work to the PI3K/AKT signaling axis to identify proteomic and genetic differences in the signal transduction pathways that lead to altered responses to therapeutic drugs.

With the help of Ben Gyori and Will Chen, members of the Modeling and Informatics Group at the Laboratory of Systems Pharmacology, we are exploring if this data can be directly incorporated into the DARPA - Big Mechanism effort that seeks to create a detailed RAS signaling model by automated literature mining.


Shi, T, M Niepel, JE McDermott, Y Gao, CD Nicora, WB Chrisler, LM Markillie, et al. “Conservation of protein abundance patterns reveals the regulatory architecture of the EGFR-MAPK pathway.” Science Signaling 9, no. 436 (2016): 1–14.

Chen, WW, M Niepel, and PK Sorger. “Classic and contemporary approaches to modeling biochemical reactions.” Genes & Development 24, no. 17 (2010): 1861 - 1875.