Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Pharmacogenomic profiling of Akt in helper T cell activation

ABSTRACT: 1) identify, at the genome-wide level, the genes that are differentially expressed in activated Th cells, with or without Akt inhibition and 2) conduct bioinformatics analyses to identify the pathways and possible mechanisms involved. First identify the differentially expressed genes at 2,6 and 12h time points after TCR stimulation compared with 0h time point in the absence of Akti1/2 and presence of Akti1/2 , then identify differentially expressed gene sets that were dependent on Akt among the three different time point groups . There are duplicate samples for each time point.

ORGANISM(S): Mus musculus

SUBMITTER: Jing Cheng

PROVIDER: E-GEOD-45221 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Mammary gland involution represents one of the most dramatic examples of programmed cell death/apoptosis and tissue regression during development, yet large gaps still exist in the understanding of the mechanisms involved, and the key factors that trigger involution, are not yet identified. With the focus on identifying ânovelâ genes associated with mammary gland regression, we used microarray analysis to examine differentially expressed genes during early mammary gland involution in the mouse. We believe that such analysis may facilitate the identification of genes that report on proliferative changes in the breast, particularly with regards to growth arrest and growth inhibition. We further reasoned that genes that inhibit mammary gland proliferation might have relevance to breast tumorigenesis since cancer is generally associated with a defect in apoptosis and cell growth arrest. Gene expression from day 0 (D0) of involution was compared to day 1 (D1, 24 hr post weaning) to identify genes exhibiting differential expression. A total of 5,826 genes were identified as being differentially expressed. Changes in gene expression were confirmed by quantitative real time PCR analysis of 21 randomly selected genes. Following the selection of a number of highly regulated mouse genes within this cohort, database searches were then employed to identify genes associated with human tumorigenesis. With an ultimate goal being the identification of genes, which under normal physiological conditions, inhibit breast proliferation, and therefore have the potential to impact on the clinical management of breast cancer, we further examined their relevance to human tumorigenesis. Among genes identified as having human homologues, and with previously established links to human tumorigenesis, were several known genes among the top 200 differentially expressed genes including EGF, EGFR, TGFÃ2, PTHLH, IGFBP1, that were down regulated. Upregulated known genes included ANNEXIN A1 and A3, THYMOSIN BETA 10, IGFBP5, LIF, BID, BCL2, JUN, KIT, and CLAUDIN 1. CLAUDIN 1 was the most highly upregulated gene in our dataset. Moreover, we identified a number of genes not previously implicated or not well characterized in human breast cancer including ANGPTL4, SLC34A2, GOS2, STEAP, SOX4, TNFRSF12A and SAA2. The expression levels of these genes in human breast cancer were confirmed in breast cancer cell lines and breast tumor tissues. For some of these genes, expression was consistently down regulated in a small panel of human breast tumor specimens. We believe that these genes now warrant further investigation to determine their relevance to human breast tumorigenesis and their potential utility as therapeutic targets for human breast cancer. This pilot study was used to demonstrate proof of principle that through the analysis of gene expression during mammary gland involution, it may be indeed possible to identify ânovelâ genes relevant to the growth arrest in the mammary gland and relevant to human breast cancer. Experiment Overall Design: Pooled RNA from D0 mice and from D1 mice, (five mice per time point), was compared for differential gene expression by microarray analysis conducted by Paradigm Array Labs (Research Triangle Park, North Carolina, USA). The Affymetrix GeneChip Mouse Genome 430 Plus 2.0 Array (Affymetrix, Santa Clara CA. USA) was used. The array contained 45,100 probe sets (The Affymetrix probe-set identificator) and represented 39,000 transcripts. The Affymetrix Statistical Algorithms, implemented in the Affymetrix Microarray Suite 5.0 software, were used in the expression analysis of GeneChip probe arrays.

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Pharmacogenomic profiling of Akt in helper T cell activation

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