SplicerAV: a tool for mining microarray expression data for changes in RNA processing
<p>Abstract</p> <p>Background</p> <p>Over the past two decades more than fifty thousand unique clinical and biological samples have been assayed using the Affymetrix HG-U133 and HG-U95 GeneChip microarray platforms. This substantial repository has been used extensively...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2010-02-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/11/108 |
| _version_ | 1818835847499218944 |
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| author | Garcia-Blanco Mariano A Dewhirst Mark Dinan Michaela A Robinson Timothy J Pearson James L |
| author_facet | Garcia-Blanco Mariano A Dewhirst Mark Dinan Michaela A Robinson Timothy J Pearson James L |
| author_sort | Garcia-Blanco Mariano A |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>Over the past two decades more than fifty thousand unique clinical and biological samples have been assayed using the Affymetrix HG-U133 and HG-U95 GeneChip microarray platforms. This substantial repository has been used extensively to characterize changes in gene expression between biological samples, but has not been previously mined <it>en masse </it>for changes in mRNA processing. We explored the possibility of using HG-U133 microarray data to identify changes in alternative mRNA processing in several available archival datasets.</p> <p>Results</p> <p>Data from these and other gene expression microarrays can now be mined for changes in transcript isoform abundance using a program described here, SplicerAV. Using <it>in vivo </it>and <it>in vitro </it>breast cancer microarray datasets, SplicerAV was able to perform both gene and isoform specific expression profiling within the same microarray dataset. Our reanalysis of Affymetrix U133 plus 2.0 data generated by <it>in vitro </it>over-expression of HRAS, E2F3, beta-catenin (CTNNB1), SRC, and MYC identified several hundred oncogene-induced mRNA isoform changes, one of which recognized a previously unknown mechanism of <it>EGFR </it>family activation. Using clinical data, SplicerAV predicted 241 isoform changes between low and high grade breast tumors; with changes enriched among genes coding for guanyl-nucleotide exchange factors, metalloprotease inhibitors, and mRNA processing factors. Isoform changes in 15 genes were associated with aggressive cancer across the three breast cancer datasets.</p> <p>Conclusions</p> <p>Using SplicerAV, we identified several hundred previously uncharacterized isoform changes induced by <it>in vitro </it>oncogene over-expression and revealed a previously unknown mechanism of EGFR activation in human mammary epithelial cells. We analyzed Affymetrix GeneChip data from over 400 human breast tumors in three independent studies, making this the largest clinical dataset analyzed for <it>en masse </it>changes in alternative mRNA processing. The capacity to detect RNA isoform changes in archival microarray data using SplicerAV allowed us to carry out the first analysis of isoform specific mRNA changes directly associated with cancer survival.</p> |
| first_indexed | 2024-12-19T02:57:13Z |
| format | Article |
| id | doaj.art-d53787bfc0b64de289e562b2e54f57d3 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-19T02:57:13Z |
| publishDate | 2010-02-01 |
| publisher | BMC |
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| series | BMC Bioinformatics |
| spelling | doaj.art-d53787bfc0b64de289e562b2e54f57d32022-12-21T20:38:19ZengBMCBMC Bioinformatics1471-21052010-02-0111110810.1186/1471-2105-11-108SplicerAV: a tool for mining microarray expression data for changes in RNA processingGarcia-Blanco Mariano ADewhirst MarkDinan Michaela ARobinson Timothy JPearson James L<p>Abstract</p> <p>Background</p> <p>Over the past two decades more than fifty thousand unique clinical and biological samples have been assayed using the Affymetrix HG-U133 and HG-U95 GeneChip microarray platforms. This substantial repository has been used extensively to characterize changes in gene expression between biological samples, but has not been previously mined <it>en masse </it>for changes in mRNA processing. We explored the possibility of using HG-U133 microarray data to identify changes in alternative mRNA processing in several available archival datasets.</p> <p>Results</p> <p>Data from these and other gene expression microarrays can now be mined for changes in transcript isoform abundance using a program described here, SplicerAV. Using <it>in vivo </it>and <it>in vitro </it>breast cancer microarray datasets, SplicerAV was able to perform both gene and isoform specific expression profiling within the same microarray dataset. Our reanalysis of Affymetrix U133 plus 2.0 data generated by <it>in vitro </it>over-expression of HRAS, E2F3, beta-catenin (CTNNB1), SRC, and MYC identified several hundred oncogene-induced mRNA isoform changes, one of which recognized a previously unknown mechanism of <it>EGFR </it>family activation. Using clinical data, SplicerAV predicted 241 isoform changes between low and high grade breast tumors; with changes enriched among genes coding for guanyl-nucleotide exchange factors, metalloprotease inhibitors, and mRNA processing factors. Isoform changes in 15 genes were associated with aggressive cancer across the three breast cancer datasets.</p> <p>Conclusions</p> <p>Using SplicerAV, we identified several hundred previously uncharacterized isoform changes induced by <it>in vitro </it>oncogene over-expression and revealed a previously unknown mechanism of EGFR activation in human mammary epithelial cells. We analyzed Affymetrix GeneChip data from over 400 human breast tumors in three independent studies, making this the largest clinical dataset analyzed for <it>en masse </it>changes in alternative mRNA processing. The capacity to detect RNA isoform changes in archival microarray data using SplicerAV allowed us to carry out the first analysis of isoform specific mRNA changes directly associated with cancer survival.</p>http://www.biomedcentral.com/1471-2105/11/108 |
| spellingShingle | Garcia-Blanco Mariano A Dewhirst Mark Dinan Michaela A Robinson Timothy J Pearson James L SplicerAV: a tool for mining microarray expression data for changes in RNA processing BMC Bioinformatics |
| title | SplicerAV: a tool for mining microarray expression data for changes in RNA processing |
| title_full | SplicerAV: a tool for mining microarray expression data for changes in RNA processing |
| title_fullStr | SplicerAV: a tool for mining microarray expression data for changes in RNA processing |
| title_full_unstemmed | SplicerAV: a tool for mining microarray expression data for changes in RNA processing |
| title_short | SplicerAV: a tool for mining microarray expression data for changes in RNA processing |
| title_sort | splicerav a tool for mining microarray expression data for changes in rna processing |
| url | http://www.biomedcentral.com/1471-2105/11/108 |
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