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3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples

Gene expression microarrays are the most widely used technique for genome-wide expression profiling. However, microarrays do not perform well on formalin fixed paraffin embedded tissue (FFPET). Consequently, microarrays cannot be effectively utilized to perform gene expression profiling on the vast...

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Autores principales: Beck, Andrew H., Weng, Ziming, Witten, Daniela M., Zhu, Shirley, Foley, Joseph W., Lacroute, Phil, Smith, Cheryl L., Tibshirani, Robert, van de Rijn, Matt, Sidow, Arend, West, Robert B.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808244/
https://www.ncbi.nlm.nih.gov/pubmed/20098735
http://dx.doi.org/10.1371/journal.pone.0008768
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author Beck, Andrew H.
Weng, Ziming
Witten, Daniela M.
Zhu, Shirley
Foley, Joseph W.
Lacroute, Phil
Smith, Cheryl L.
Tibshirani, Robert
van de Rijn, Matt
Sidow, Arend
West, Robert B.
author_facet Beck, Andrew H.
Weng, Ziming
Witten, Daniela M.
Zhu, Shirley
Foley, Joseph W.
Lacroute, Phil
Smith, Cheryl L.
Tibshirani, Robert
van de Rijn, Matt
Sidow, Arend
West, Robert B.
author_sort Beck, Andrew H.
collection PubMed
description Gene expression microarrays are the most widely used technique for genome-wide expression profiling. However, microarrays do not perform well on formalin fixed paraffin embedded tissue (FFPET). Consequently, microarrays cannot be effectively utilized to perform gene expression profiling on the vast majority of archival tumor samples. To address this limitation of gene expression microarrays, we designed a novel procedure (3′-end sequencing for expression quantification (3SEQ)) for gene expression profiling from FFPET using next-generation sequencing. We performed gene expression profiling by 3SEQ and microarray on both frozen tissue and FFPET from two soft tissue tumors (desmoid type fibromatosis (DTF) and solitary fibrous tumor (SFT)) (total n = 23 samples, which were each profiled by at least one of the four platform-tissue preparation combinations). Analysis of 3SEQ data revealed many genes differentially expressed between the tumor types (FDR<0.01) on both the frozen tissue (∼9.6K genes) and FFPET (∼8.1K genes). Analysis of microarray data from frozen tissue revealed fewer differentially expressed genes (∼4.64K), and analysis of microarray data on FFPET revealed very few (69) differentially expressed genes. Functional gene set analysis of 3SEQ data from both frozen tissue and FFPET identified biological pathways known to be important in DTF and SFT pathogenesis and suggested several additional candidate oncogenic pathways in these tumors. These findings demonstrate that 3SEQ is an effective technique for gene expression profiling from archival tumor samples and may facilitate significant advances in translational cancer research.
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spelling pubmed-28082442010-01-21 3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples Beck, Andrew H. Weng, Ziming Witten, Daniela M. Zhu, Shirley Foley, Joseph W. Lacroute, Phil Smith, Cheryl L. Tibshirani, Robert van de Rijn, Matt Sidow, Arend West, Robert B. PLoS One Research Article Gene expression microarrays are the most widely used technique for genome-wide expression profiling. However, microarrays do not perform well on formalin fixed paraffin embedded tissue (FFPET). Consequently, microarrays cannot be effectively utilized to perform gene expression profiling on the vast majority of archival tumor samples. To address this limitation of gene expression microarrays, we designed a novel procedure (3′-end sequencing for expression quantification (3SEQ)) for gene expression profiling from FFPET using next-generation sequencing. We performed gene expression profiling by 3SEQ and microarray on both frozen tissue and FFPET from two soft tissue tumors (desmoid type fibromatosis (DTF) and solitary fibrous tumor (SFT)) (total n = 23 samples, which were each profiled by at least one of the four platform-tissue preparation combinations). Analysis of 3SEQ data revealed many genes differentially expressed between the tumor types (FDR<0.01) on both the frozen tissue (∼9.6K genes) and FFPET (∼8.1K genes). Analysis of microarray data from frozen tissue revealed fewer differentially expressed genes (∼4.64K), and analysis of microarray data on FFPET revealed very few (69) differentially expressed genes. Functional gene set analysis of 3SEQ data from both frozen tissue and FFPET identified biological pathways known to be important in DTF and SFT pathogenesis and suggested several additional candidate oncogenic pathways in these tumors. These findings demonstrate that 3SEQ is an effective technique for gene expression profiling from archival tumor samples and may facilitate significant advances in translational cancer research. Public Library of Science 2010-01-19 /pmc/articles/PMC2808244/ /pubmed/20098735 http://dx.doi.org/10.1371/journal.pone.0008768 Text en Beck et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Beck, Andrew H.
Weng, Ziming
Witten, Daniela M.
Zhu, Shirley
Foley, Joseph W.
Lacroute, Phil
Smith, Cheryl L.
Tibshirani, Robert
van de Rijn, Matt
Sidow, Arend
West, Robert B.
3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples
title 3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples
title_full 3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples
title_fullStr 3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples
title_full_unstemmed 3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples
title_short 3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples
title_sort 3′-end sequencing for expression quantification (3seq) from archival tumor samples
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808244/
https://www.ncbi.nlm.nih.gov/pubmed/20098735
http://dx.doi.org/10.1371/journal.pone.0008768
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