Predicting angiogenic receptor trafficking and signaling via computational systems biology

Angiogenesis is defined as the growth of new blood vessels from preexisting vessels. Systematic regulation of angiogenesis could lead to new treatments of vascular diseases and cancer. As such, vascular endothelial growth factor (VEGF), a potent angiogenic growth factor, offers a promising therapeutic target. Despite this promise, VEGF targeted therapies are not clinically effective for many pathologies, such as breast cancer. Thus, a better understanding of the VEGF network for regulating angiogenesis, along with identifying key nodes controlling angiogenesis within this network, are necessary to provide effective VEGF therapeutics. Systems biology, defined as applying experiment and computational modeling to understand a biological system, can readily define this VEGF-angiogenesis network. In this dissertation, I provide an overview of how computational systems biology has been used to provide basic biological insights into angiogenesis, explore anti-angiogenic therapeutic options for cancer, and pro-angiogenic therapeutic options for vascular disease. Using systems biology, I have previously predicted that VEGFR1 acts as a predictive biomarker of anti-VEGF efficacy in breast cancer. Particularly, tumor endothelial cell subpopulations exhibiting high VEGFR1 levels result in ineffective anti-VEGF treatment. These high VEGFR1 subpopulations are characterized by a high amount of VEGF-VEGFR1 complex formation, and subsequently high VEGF-VEGFR1 internalization. The high VEGF-VEGFR1 complex formation implies a possible VEGFR1 signaling role beyond its classically defined decoy status. In this dissertation, I introduce a computational approach that accurately predicts the cell response elicited via VEGFR1 signaling. I show that VEGFR1 promotes cell migration through PLCγ and PI3K pathways, and promotes cell proliferation through a PLCγ pathway. These results provide new biological insight into VEGFR1 signaling and angiogenesis while offering a system for directing angiogenesis. Cell subpopulations expressing high VEGFR1 levels are characterized by a large amount of VEGF-VEGFR1 internalization. Thus, endocytosis may regulate VEGFR1 signaling; indeed, intracellular-based receptor signaling has recently emerged as a key component in mediating cell responses for receptor tyrosine kinases (RTKs). However, how endocytosis fundamentally mediates signaling for any RTK remains poorly defined. Understanding how endocytosis fundamentally directs intracellular receptor signaling requires receptor-specific endocytosis mechanisms to be delineated. This delineation requires identifying the signaling mechanisms common to all receptor types. To this end, I conduct a computational meta-analysis predicting endocytic compartment signaling across eight RTKs, and identify their common signaling mechanisms. I find that endocytic vesicles are the primary cell signaling compartment; over 43% total receptor phosphorylation occurs within the endocytic vesicle compartment for all eight RTKs. Conversely, all RTKs exhibit low membrane-based receptor signaling, exhibiting < 1% total receptor phosphorylation. Mechanistically, this high RTK phosphorylation within endocytic vesicles may be attributed to their low volume, which facilitates an enriched ligand concentration. The late endosome and nucleus are also important contributors to receptor signaling, where 26% and 18% average receptor phosphorylation occurs, respectively. Furthermore, nuclear translocation requires late endosomal transport; blocking receptor trafficking from late endosomes to the nucleus reduces nuclear signaling 96%. These findings can be applied to understand specific RTK signaling functions in terms of cell response, and optimize RTK therapeutics targeting endocytic pathways. Overall, I reveal the role of VEGFR1 and its signaling mechanisms, which is essential information to the field of angiogenesis. This information advances angiogenesis therapeutics by identifying the VEGF-VEGFR1 signaling axis as an essential target. I identify the primary adapters that can be targeted to critically regulate VEGF-VEGFR1 signaling, and endocytic compartmentalization that can be targeted for tuning receptor signaling. Furthermore, the computational techniques I develop advance the field of systems biology by delineating the signal-to-response of receptor signaling, improving receptor investigation by allowing adapter phosphorylation and cell responses to be quantified simultaneously, in addition to compartmentalized receptor signaling. These computational techniques improve disease treatment by allowing optimal receptor signaling targets to be identified quickly. Additionally, unknown receptor signaling can be mapped from adapter phosphorylation to cell response. These computational techniques can be integrated into multiscale computational models to provide clinically relevant, patient-specific platforms for directing disease treatment