Mathematical Model of Parotid Acinar Differentiation

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DESCRIPTION (provided by applicant): This application is in response to NOT-OD-09-058, titled "NIH Announces the Availability of Recovery Act Funds for Competitive Revision Applications." This Competitive Revision application proposes an additional Specific Aim for the original R01 project. The long term goal of our project is to define the development of signaling networks that induce differentiation of cells into mature salivary serous acinar cells. Millions of patients suffer loss of salivary gland function due to Sjogren's syndrome or radiation therapy. Understanding the differentiation of salivary cells is a necessary step to enable the restoration of diseased or destroyed parotid salivary tissue. Our overall hypothesis for the parent project is that a mathematical model can identify key regulatory pathways that control parotid acinar cell differentiation. The goal of the existing project is to develop IPA-based mathematical and statistical models that will identify gene networks which cause terminal differentiation of parotid acinar cells. The dynamical mathematical models will serve to generate hypotheses which will be reiteratively tested, and the model will be repeatedly refined by the incorporation of new data. Both Affymetrix microarrays and miRNA arrays are being used to create biological networks with Ingenuity Pathway Analysis, and Genespring programs. These networks are used to create coupled Ordinary Differential Equation (ODE) models to describe the process of differentiation. A difficulty in any biological modeling project is finding the appropriate networks. Specific Aim #1R for this Competitive Revision proposes to develop an unbiased statistical approach to derive genetic networks from array data. The approach is based on recently developed methods for genetic network discovery based on algebraic analysis of the statistically significant interactions in the mathematical network without the need of precisely fitting all the model parameters. This novel method is based on two recent publications by the Co-PI, Dr. Rempala where it is shown to be highly robust against misclassification and capable of correctly identify the network from noisy and incomplete data. The new modeling component will be supported by generating additional microarray results to use for training and validation, as well as RT-PCR and transfection studies to validate the derived network. The additional statistical and biological results will add a new dimension to the original project, and will speed progress in defining the molecular pathways that drive cytodifferentiation of parotid acinar cells. In addition, the unbiased statistical approach to discovering biological networks will be applicable to study of other tissues and pathologies. PUBLIC HEALTH RELEVANCE: The overall goal of this research is to define the molecular mechanisms which control differentiation of cells into secretory salivary acinar cells. This addresses the needs of millions of Americans who suffer from salivary gland dysfunction due to Sj"gren's Syndrome, radiation therapy, or xerostomia due to essential medications. This research is a necessary foundation for developing new technologies such as gene transfer therapy and biologics for treating or alleviating the oral symptoms of xerostomia.