Quantitative Analysis of Discoidin Domain Receptor 2 Signalling Networks

Interactions between cells and their surrounding matrix play critical roles in health and disease, yet our understanding of their cellular signalling networks are still incomplete. The discoidin domain receptors (DDRs) regulate cellular responses to collagen (the most abundant matrix component in the body) and are critical for tissue organization and development. Its importance in biological function is reflected in DDR signalling defects which lead to diseases such as osteoarthritis and atherosclerosis. Here we propose to use cutting-edge analytical tools and mathematical modelling approaches to establish how cells employ DDR2 (discoidin domain receptor 2) to interpret signals from collagen and translate these cues into cell behaviour such as growth. The research will be conducted in three phases. The first phase will involve the use of a sensitive analytical approach known as mass spectrometry to comprehensively map DDR2 signalling changes upon exposure to the collagen. In the second phase, the mass spectrometric data will be used to build a mathematical model that will provide mechanistic insights into specific DDR2 signaling proteins that control cell growth. These new insights will be tested in the final phase of the project by expression or elimination of the identified signalling proteins and relating changes in signaling to cellular growth. These proposed studies will allow us to fully understand the role of DDR2 signalling in cell-matrix interactions.

Cells receive a variety of environmental stimuli from the surrounding extracellular matrix (ECM). Collagen is the most abundant ECM protein and exerts profound effects on cellular behaviour. The discoidin domain receptors (DDRs) are receptor tyrosine kinases that engage collagen and initiate signalling networks that drive cellular responses such as proliferation, migration and invasion. However, the mechanisms by which these receptors mediate each of these processes are currently unknown. To address this deficiency and gain new insights into collagen-induced signalling, we propose to assess the biological effects of DDR2 (discoidin domain receptor 2) signalling through a combination of mass spectrometry (MS), chemical biology and mathematical modelling. The proposed research will encompass 3 aims. In the first aim, quantitative phosphoproteomics by mass spectrometry and chemical biology will be used to build a high-resolution map of DDR2 signalling networks and direct substrates. In the second aim, mathematical modelling (partial least squares regression) will be used to correlate DDR2 phosphorylation profiles with biological responses (cell growth, cell ceycle progression and MMP secretion). In the final aim of the project, we will validate the model predictions by measuring the DDR2 signalling network and cellular phenotypes upon perturbation (exogenous protein expression and RNA interference) of prioritised candidates. These proposed studies will allow us to gain a mechanistic understanding of the role of DDR2 signalling in cell-matrix interactions.

The research outcomes arising from this proposal will contribute to the following areas. 1. The development of an integrated approach to therapeutics research in the biopharmaceutical and bioprocess industry. The advent of high-throughput approaches has led to a massive amount of molecular data being generated in the pharmaceutical and biomedical industries. One of the major challenges facing the industry is to prioritize candidates from these large datasets. There are a number of major pharmaceutical companies that have R&D departments dedicated to systems biology and mathematical modelling with the aim of designing better drugs. An example is Merrimack Pharmaceuticals in the United States who have successfully used mathematical modelling to develop new compounds against cancer. It is envisioned that this approach of combining systems measurements such as proteomics together with modelling will lead to the growth of a new integrated approach to therapeutics research. Specifically, the mathematical model that has arisen from the research can be used to design and optimize therapeutics for collagen-associated diseases such as osteoarthritis and atherosclerosis. The bioprocessing industry has a long history of employing engineering approaches to optimize industrial processes. However, much of this work has focused on disciplines such as metabolic engineering and biochemical engineering. Little work has been done in utilizing our understanding of cellular signalling networks for bioreactor design and optimization. An example is the development of stem cell bioreactors. Extracellular matrix components such as collagen are important in maintaining the viability of stem cells but are very costly. Identifying the signalling pathways activated by these factors will open the door to engineering cells that may be capable of optimal growth even in the presence of reduced collagen levels. 2. Commercialization of research. The phosphoproteins that are validated in aim three of the proposal will serve as possible targets for commercial development and intellectual property. Specifically, targets that are identified to decrease matrix metalloprotease secretion may be used as alternatives to the current MMP inhibitors that have thus far failed clinical trials. 3. Public awareness and engagement. It is an important goal of the Institute of Cancer Research to engage the community to raise the public's awareness of science. This will be done through the public relations department of the institute and will include press releases upon publication of research data, meeting with the public through charity events and seminars that educate the public and its relationship to society.