Mechanistic Characterization of RTK Signaling Networks Using Phosphoproteomic Approaches

Cancer is a complex disease, which often stems from aberrant gene expression and protein signaling. In order to improve development of novel therapeutics, underlying mechanisms employed by malignant cells to maintain their function need to be deeply understood. The field of phosphoproteomics has advanced over the past few decades to allow analysis of phosphorylated proteins with increased sensitivity and accuracy. Using these methods in combination with a systematic mutational strategy that evaluates the network effects of loss of phosphorylatable tyrosines that the protein of interest seemingly depends on, allows for an unbiased mechanistic characterization of the signaling network. When implemented with various computational tools, these data can provide a predictive model that can inform future targeting strategies in disease. Here, I present an overview of the value phosphoproteomics adds to cancer research, and the insights we can gain when combined with Y-to-F mutational approaches to gain mechanistic understanding underlying protein function. We successfully applied these approaches in characterizing EGFR, a protein often dysregulated in cancer. Furthermore, we experimentally evaluated the use of fluorophores such as GFP in these signaling studies. We also applied these approaches in other settings, when evaluating function of AXL, another RTK that has been associated with acquired resistance to EGFR-targeting tyrosine kinase inhibitors. We applied phosphoproteomic analysis to explore the regulation of EGFR by phosphatase PTPRJ as a potential indirect mechanism of modulation. Beyond cancer, we applied our phosphoproteomic approach to validate a novel biomarker in Alzheimer’s disease. Together, these findings highlight how these approaches can result in invaluable mechanistic insight that can propel future drug development efforts.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Biological Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Gerritsen, Jacqueline S.

Advisor dc:contributor.advisor

• White, Forest M.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/153468

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/153468