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Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches

BACKGROUND: High-throughput transcriptomics has matured into a very well established and widely utilised research tool over the last two decades. Clinical datasets generated on a range of different platforms continue to be deposited in public repositories provide an ever-growing, valuable resource f...

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Autores principales: Turnbull, Arran K., Selli, Cigdem, Martinez-Perez, Carlos, Fernando, Anu, Renshaw, Lorna, Keys, Jane, Figueroa, Jonine D., He, Xiaping, Tanioka, Maki, Munro, Alison F., Murphy, Lee, Fawkes, Angie, Clark, Richard, Coutts, Audrey, Perou, Charles M., Carey, Lisa A., Dixon, J. Michael, Sims, Andrew H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988223/
https://www.ncbi.nlm.nih.gov/pubmed/31992186
http://dx.doi.org/10.1186/s12859-020-3365-5
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author Turnbull, Arran K.
Selli, Cigdem
Martinez-Perez, Carlos
Fernando, Anu
Renshaw, Lorna
Keys, Jane
Figueroa, Jonine D.
He, Xiaping
Tanioka, Maki
Munro, Alison F.
Murphy, Lee
Fawkes, Angie
Clark, Richard
Coutts, Audrey
Perou, Charles M.
Carey, Lisa A.
Dixon, J. Michael
Sims, Andrew H.
author_facet Turnbull, Arran K.
Selli, Cigdem
Martinez-Perez, Carlos
Fernando, Anu
Renshaw, Lorna
Keys, Jane
Figueroa, Jonine D.
He, Xiaping
Tanioka, Maki
Munro, Alison F.
Murphy, Lee
Fawkes, Angie
Clark, Richard
Coutts, Audrey
Perou, Charles M.
Carey, Lisa A.
Dixon, J. Michael
Sims, Andrew H.
author_sort Turnbull, Arran K.
collection PubMed
description BACKGROUND: High-throughput transcriptomics has matured into a very well established and widely utilised research tool over the last two decades. Clinical datasets generated on a range of different platforms continue to be deposited in public repositories provide an ever-growing, valuable resource for reanalysis. Cost and tissue availability normally preclude processing samples across multiple technologies, making it challenging to directly evaluate performance and whether data from different platforms can be reliably compared or integrated. METHODS: This study describes our experiences of nine new and established mRNA profiling techniques including Lexogen QuantSeq, Qiagen QiaSeq, BioSpyder TempO-Seq, Ion AmpliSeq, Nanostring, Affymetrix Clariom S or U133A, Illumina BeadChip and RNA-seq of formalin-fixed paraffin embedded (FFPE) and fresh frozen (FF) sequential patient-matched breast tumour samples. RESULTS: The number of genes represented and reliability varied between the platforms, but overall all methods provided data which were largely comparable. Crucially we found that it is possible to integrate data for combined analyses across FFPE/FF and platforms using established batch correction methods as required to increase cohort sizes. However, some platforms appear to be better suited to FFPE samples, particularly archival material. CONCLUSIONS: Overall, we illustrate that technology selection is a balance between required resolution, sample quality, availability and cost.
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spelling pubmed-69882232020-01-31 Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches Turnbull, Arran K. Selli, Cigdem Martinez-Perez, Carlos Fernando, Anu Renshaw, Lorna Keys, Jane Figueroa, Jonine D. He, Xiaping Tanioka, Maki Munro, Alison F. Murphy, Lee Fawkes, Angie Clark, Richard Coutts, Audrey Perou, Charles M. Carey, Lisa A. Dixon, J. Michael Sims, Andrew H. BMC Bioinformatics Research Article BACKGROUND: High-throughput transcriptomics has matured into a very well established and widely utilised research tool over the last two decades. Clinical datasets generated on a range of different platforms continue to be deposited in public repositories provide an ever-growing, valuable resource for reanalysis. Cost and tissue availability normally preclude processing samples across multiple technologies, making it challenging to directly evaluate performance and whether data from different platforms can be reliably compared or integrated. METHODS: This study describes our experiences of nine new and established mRNA profiling techniques including Lexogen QuantSeq, Qiagen QiaSeq, BioSpyder TempO-Seq, Ion AmpliSeq, Nanostring, Affymetrix Clariom S or U133A, Illumina BeadChip and RNA-seq of formalin-fixed paraffin embedded (FFPE) and fresh frozen (FF) sequential patient-matched breast tumour samples. RESULTS: The number of genes represented and reliability varied between the platforms, but overall all methods provided data which were largely comparable. Crucially we found that it is possible to integrate data for combined analyses across FFPE/FF and platforms using established batch correction methods as required to increase cohort sizes. However, some platforms appear to be better suited to FFPE samples, particularly archival material. CONCLUSIONS: Overall, we illustrate that technology selection is a balance between required resolution, sample quality, availability and cost. BioMed Central 2020-01-28 /pmc/articles/PMC6988223/ /pubmed/31992186 http://dx.doi.org/10.1186/s12859-020-3365-5 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Turnbull, Arran K.
Selli, Cigdem
Martinez-Perez, Carlos
Fernando, Anu
Renshaw, Lorna
Keys, Jane
Figueroa, Jonine D.
He, Xiaping
Tanioka, Maki
Munro, Alison F.
Murphy, Lee
Fawkes, Angie
Clark, Richard
Coutts, Audrey
Perou, Charles M.
Carey, Lisa A.
Dixon, J. Michael
Sims, Andrew H.
Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches
title Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches
title_full Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches
title_fullStr Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches
title_full_unstemmed Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches
title_short Unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches
title_sort unlocking the transcriptomic potential of formalin-fixed paraffin embedded clinical tissues: comparison of gene expression profiling approaches
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6988223/
https://www.ncbi.nlm.nih.gov/pubmed/31992186
http://dx.doi.org/10.1186/s12859-020-3365-5
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