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Summarizing performance for genome scale measurement of miRNA: reference samples and metrics

BACKGROUND: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we eval...

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Autores principales: Pine, P. Scott, Lund, Steven P., Parsons, Jerod R., Vang, Lindsay K., Mahabal, Ashish A., Cinquini, Luca, Kelly, Sean C., Kincaid, Heather, Crichton, Daniel J., Spira, Avrum, Liu, Gang, Gower, Adam C., Pass, Harvey I., Goparaju, Chandra, Dubinett, Steven M., Krysan, Kostyantyn, Stass, Sanford A., Kukuruga, Debra, Van Keuren-Jensen, Kendall, Courtright-Lim, Amanda, Thompson, Karol L., Rosenzweig, Barry A., Sorbara, Lynn, Srivastava, Sudhir, Salit, Marc L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5838960/
https://www.ncbi.nlm.nih.gov/pubmed/29510677
http://dx.doi.org/10.1186/s12864-018-4496-1
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author Pine, P. Scott
Lund, Steven P.
Parsons, Jerod R.
Vang, Lindsay K.
Mahabal, Ashish A.
Cinquini, Luca
Kelly, Sean C.
Kincaid, Heather
Crichton, Daniel J.
Spira, Avrum
Liu, Gang
Gower, Adam C.
Pass, Harvey I.
Goparaju, Chandra
Dubinett, Steven M.
Krysan, Kostyantyn
Stass, Sanford A.
Kukuruga, Debra
Van Keuren-Jensen, Kendall
Courtright-Lim, Amanda
Thompson, Karol L.
Rosenzweig, Barry A.
Sorbara, Lynn
Srivastava, Sudhir
Salit, Marc L.
author_facet Pine, P. Scott
Lund, Steven P.
Parsons, Jerod R.
Vang, Lindsay K.
Mahabal, Ashish A.
Cinquini, Luca
Kelly, Sean C.
Kincaid, Heather
Crichton, Daniel J.
Spira, Avrum
Liu, Gang
Gower, Adam C.
Pass, Harvey I.
Goparaju, Chandra
Dubinett, Steven M.
Krysan, Kostyantyn
Stass, Sanford A.
Kukuruga, Debra
Van Keuren-Jensen, Kendall
Courtright-Lim, Amanda
Thompson, Karol L.
Rosenzweig, Barry A.
Sorbara, Lynn
Srivastava, Sudhir
Salit, Marc L.
author_sort Pine, P. Scott
collection PubMed
description BACKGROUND: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. RESULTS: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. CONCLUSIONS: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-4496-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-58389602018-03-09 Summarizing performance for genome scale measurement of miRNA: reference samples and metrics Pine, P. Scott Lund, Steven P. Parsons, Jerod R. Vang, Lindsay K. Mahabal, Ashish A. Cinquini, Luca Kelly, Sean C. Kincaid, Heather Crichton, Daniel J. Spira, Avrum Liu, Gang Gower, Adam C. Pass, Harvey I. Goparaju, Chandra Dubinett, Steven M. Krysan, Kostyantyn Stass, Sanford A. Kukuruga, Debra Van Keuren-Jensen, Kendall Courtright-Lim, Amanda Thompson, Karol L. Rosenzweig, Barry A. Sorbara, Lynn Srivastava, Sudhir Salit, Marc L. BMC Genomics Methodology Article BACKGROUND: The potential utility of microRNA as biomarkers for early detection of cancer and other diseases is being investigated with genome-scale profiling of differentially expressed microRNA. Processes for measurement assurance are critical components of genome-scale measurements. Here, we evaluated the utility of a set of total RNA samples, designed with between-sample differences in the relative abundance of miRNAs, as process controls. RESULTS: Three pure total human RNA samples (brain, liver, and placenta) and two different mixtures of these components were evaluated as measurement assurance control samples on multiple measurement systems at multiple sites and over multiple rounds. In silico modeling of mixtures provided benchmark values for comparison with physical mixtures. Biomarker development laboratories using next-generation sequencing (NGS) or genome-scale hybridization assays participated in the study and returned data from the samples using their routine workflows. Multiplexed and single assay reverse-transcription PCR (RT-PCR) was used to confirm in silico predicted sample differences. Data visualizations and summary metrics for genome-scale miRNA profiling assessment were developed using this dataset, and a range of performance was observed. These metrics have been incorporated into an online data analysis pipeline and provide a convenient dashboard view of results from experiments following the described design. The website also serves as a repository for the accumulation of performance values providing new participants in the project an opportunity to learn what may be achievable with similar measurement processes. CONCLUSIONS: The set of reference samples used in this study provides benchmark values suitable for assessing genome-scale miRNA profiling processes. Incorporation of these metrics into an online resource allows laboratories to periodically evaluate their performance and assess any changes introduced into their measurement process. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-4496-1) contains supplementary material, which is available to authorized users. BioMed Central 2018-03-06 /pmc/articles/PMC5838960/ /pubmed/29510677 http://dx.doi.org/10.1186/s12864-018-4496-1 Text en © The Author(s). 2018 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 Methodology Article
Pine, P. Scott
Lund, Steven P.
Parsons, Jerod R.
Vang, Lindsay K.
Mahabal, Ashish A.
Cinquini, Luca
Kelly, Sean C.
Kincaid, Heather
Crichton, Daniel J.
Spira, Avrum
Liu, Gang
Gower, Adam C.
Pass, Harvey I.
Goparaju, Chandra
Dubinett, Steven M.
Krysan, Kostyantyn
Stass, Sanford A.
Kukuruga, Debra
Van Keuren-Jensen, Kendall
Courtright-Lim, Amanda
Thompson, Karol L.
Rosenzweig, Barry A.
Sorbara, Lynn
Srivastava, Sudhir
Salit, Marc L.
Summarizing performance for genome scale measurement of miRNA: reference samples and metrics
title Summarizing performance for genome scale measurement of miRNA: reference samples and metrics
title_full Summarizing performance for genome scale measurement of miRNA: reference samples and metrics
title_fullStr Summarizing performance for genome scale measurement of miRNA: reference samples and metrics
title_full_unstemmed Summarizing performance for genome scale measurement of miRNA: reference samples and metrics
title_short Summarizing performance for genome scale measurement of miRNA: reference samples and metrics
title_sort summarizing performance for genome scale measurement of mirna: reference samples and metrics
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5838960/
https://www.ncbi.nlm.nih.gov/pubmed/29510677
http://dx.doi.org/10.1186/s12864-018-4496-1
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