MSRD 2016 Sample Abstract Your abstract MUST be in the following format: 1. Font: Arial. Size 10 2. TITLE must be CAPITALIZED and bolded 3. Author names should be written as 1st initial followed by period, and then Last Name (ex: Jane Jaime Doe J. J. Doe) 4. Superscripts must be used to indicate affiliations 5. Name of presenting student should be bolded 6. Abstract must have the following headings CAPITALIZED and bolded: INTRODUCTION (or BACKGROUND), OBJECTIVE, METHODS, RESULTS, and CONCLUSION (or DISCUSSION). If you believe your research is best presented in an unstructured abstract format you may submit an unstructured abstract as long as it meets the rest of the criteria. 7. Maximum characters (with spaces): 2250 (this includes the title, author names and affiliations, subheadings from point 6 above, and the research) 8. Save the document in WORD format, titled: “Last name, First name – MSRD 2016 Abstract” 9. You MUST write inside the box provided only MASS SPECTROMETRY-BASED PHOSPHOLIPIDOMICS OF ONCOLYTIC VIRUSINFECTED LEUKEMIA CELLS M. Atkins1,2, C. Canez2, J. Hajjar3, G. Waghray3, H. Atkins3, and J. C. Smith2 1MD/PhD Program, University of Toronto, Toronto, Ontario, Canada 2Department of Chemistry, Carleton University, Ottawa, Ontario, Canada and 4Centre for Innovation in Cancer Therapeutics, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada BACKGROUND/PURPOSE: Oncolytic viruses (OVs) are effective therapeutic agents that selectively target cancer cells. However, many of the molecular mechanisms of infection remain unresolved. Understanding the cellular response to infection will inform the design of sensitizers that improve OV efficacy. Lipid signaling and cellular metabolism have recently emerged as targets of non-OV infection to expand cell membranes, alter membrane curvature and fluidity and act as signaling molecules, but their role in OV infection is unknown. We examine the cellular response to two OVs, VSV and a corresponding mutant, VSV-Δ51M in leukemic cells. OBJECTIVES: We seek to understand early lipid regulation of cancer cells to OV infection. METHODS: Our online liquid chromatography-mass spectrometry approach identified 168 phosphatidylcholine (PC) lipids using a positive ion mode precursor ion scan for m/z 184. Moreover, a negative ion mode precursor ion scan for m/z 168 was used to discriminate sphingomyelin (SM) from PC. RESULTS: SMs are unchanged in the early cellular response to OV infection. In contrast, PCs are dysregulated in the early cellular response to OV infection. Low m/z PCs are down-regulated and high m/z PCs are up-regulated, which suggests OV infection targets the conversion of lysophosphatidylcholine (LPC) lipids to diacylphosphatidylcholine (DPC) lipids. We have identified LPCAT2 as a potential target of OV infection that regulates lipid metabolism. CONCLUSIONS: Our LC-MS approach suggests the early cellular response to OV infection is not mediated through SMs, but DPCs are up-regulated at the expense of LPCs soon after OV infection. We next seek to understand the subcellular regulation of phospholipids, which will facilitate the identification of candidate protein regulators.