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Functional Genomics Core

$232,403P01FY2015AINIH

University Of Pittsburgh At Pittsburgh, Pittsburgh PA

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Abstract

CORE SUMMARY The overall goal of this PPG application is to compare and contrast the mechanisms by which the inhibitory receptors PD1 and LAG3 operate on T cells in the context of tolerance and autoimmunity, cancer, and chronic infection. One major approach to be used throughout the studies is the application of genome-wide transcriptional profiling. The purpose of this Functional Genomics and Computational Biology Core is to manage, analyze and integrate these datasets and define key genes and pathways involved in immunoregulation by PD1 and/or LAG3. This Core will also apply network-based computational approaches to define centrally important ?hub? genes, biological pathways and cellular networks regulated by PD1 and/or LAG3. Thus, Core C will apply integrated computational and bioinformatics approaches to define biological effects of PD1 and LAG3 in autoimmune, antitumor and antiviral T cells. The three Aims are: AIM 1: To host, normalize, pre-process and provide expression profiling analysis of individual transcriptional profiling datasets. This Aim will provide data hosting, a uniform set of approaches to quality control and normalize genome-wide transcriptional datasets as well as Project-specific analysis of transcriptional differences. Datasets for autoreactive and exhausted CD4+ T cells, Treg involved in autoimmunity and tumor responses, and antiviral and antitumor exhausted CD8+ T cells where PD1 and LAG3 have been disrupted will be generated and integrated to obtain information about genes and pathways controlled by PD1 and LAG3. AIM 2: To integrate analysis of transcriptional datasets and use network-based computational modeling to define centrally important pathways involved in the biology of PD1 and/or LAG3. First, this Aim will integrate transcriptional datasets from different Projects to define common and unique features of the PD1 and LAG3 pathways in autoimmunity, cancer, and chronic infection. Second, we will use Weighted Gene Co-expression Network Analysis (WGCNA) to define centrally important ?hub? genes and pathways involved in PD1 and LAG3 function and synergy. AIM 3: To generate and validate retroviral approaches to directly test predictions from functional genomic analyses. This Aim will generate and validate retroviruses (RV) on the MigR1 or related backbones to allow overexpression (or knockdown) of genes of interest in CD4+ or CD8+ T cells involved in autoimmunity or responses to tumors or chronic viral infection. This approach will lead to a high degree of synergy within the PPG and help to a focus efforts on centrally important genes and pathways.

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