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A team of biological scientists, chemists, computer scientists, and statisticians from Carnegie Mellon and Dickinson College has received $3.5 million from the Pennsylvania Department of Health to identify new cancer subtypes, leading to improved medical diagnostics and possible new treatments. The support comes from Pennsylvania's tobacco settlement funds earmarked for research. This project was one of four multi-million dollar grants awarded by the Department of Health this fiscal year. For more information, see the related press release List of projects and investigators: Integrated Protein Informatics for Cancer Research Principal Investigator: Richard D. McCullough, Chemistry,
Carnegie Mellon Overview: Cancer is caused by defects in cellular processes, especially in regulation of cell division. These defects are caused by mutations in the genes in cells of our tissues and organs. These mutations alter the amounts and types of proteins present in the cells, resulting in changes in cellular properties, including uncontrolled cell division and unregulated cell movements resulting in metastasis of tumor cells. We propose to measure changes in levels and amounts of proteins in normal and cancer cells using very sensitive techniques developed at Carnegie Mellon. Projects 2 and 3 will use different methods to determine changes in protein behavior, while Project 4 will analyzes changes in RNA metabolism that may give rise to these aberrations. Project 5 is designed to rapidly determine the structure of possible causative proteins once they are identified in Projects 2, 3 and 4. Project 1 uses computational methods to analyze all of these changes simultaneously to determine whether any of them are correlated with each other or with drug sensitivities, to allow useful predictions. Project 6 uses computers to systematically identify and collect observations published in previous years that may be helpful in these and other studies. Through these sensitive and comprehensive experimental and computational methods, we will 1) develop methods to identify new cancer subtypes, 2) develop new methods for rapid diagnosis, 3) develop predictive models of drug response and clinical outcomes, 4) generate hypotheses about causation for further investigation, and 5) identify possible targets for drug discovery and possible new treatments. Project 1: Project 2: Project 3: Project 4: Project 5: Project 6:
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