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    Normal colon epithelium: a dataset for the analysis of gene expression and alternative splicing events in colon disease.

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    Authors
    Mojica, Wilfrido
    Hawthorn, Lesleyann
    Issue Date
    2010-02-18
    URI
    http://hdl.handle.net/10675.2/68
    
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    Abstract
    BACKGROUND: Studies using microarray analysis of colorectal cancer have been generally beleaguered by the lack of a normal cell population of the same lineage as the tumor cell. One of the main objectives of this study was to generate a reference gene expression data set for normal colonic epithelium which can be used in comparisons with diseased tissues, as well as to provide a dataset that could be used as a baseline for studies in alternative splicing. RESULTS: We present a dependable expression reference data set for non-neoplastic colonic epithelial cells. An enriched population of fresh colon epithelial cells were obtained from non-neoplastic, colectomy specimens and analyzed using Affymetrix GeneChip EXON 1.0 ST arrays. For demonstration purposes, we have compared the data derived from these cells to a publically available set of tumor and matched normal colon data. This analysis allowed an assessment of global gene expression alterations and demonstrated that adjacent normal tissues, with a high degree of cellular heterogeneity, are not always representative of normal cells for comparison to tumors which arise from the colon epithelium. We also examined alternative splicing events in tumors compared to normal colon epithelial cells. CONCLUSIONS: The findings from this study represent the first comprehensive expression profile for non-neoplastic colonic epithelial cells reported. Our analysis of splice variants illustrate that this is a very labor intensive procedure, requiring vigilant examination of the data. It is projected that the contribution of this set of data derived from pure colonic epithelial cells will enhance studies in colon-related disease and offer a vital baseline for studies aimed at elucidating the mechanisms of alternative splicing.
    Citation
    BMC Genomics. 2010 Jan 4; 11:5
    ae974a485f413a2113503eed53cd6c53
    10.1186/1471-2164-11-5
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    Georgia Cancer Center: Faculty Research and Presentations

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