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SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines
Translational research hinges on the ability to make observations in model systems and to implement those findings into clinical applications, such as the development of diagnostic tools or targeted therapeutics. Tumor cell lines are commonly used to model carcinogenesis. The same tumor cell line ca...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367734/ https://www.ncbi.nlm.nih.gov/pubmed/18304946 http://dx.doi.org/10.1093/nar/gkn089 |
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author | Demichelis, Francesca Greulich, Heidi Macoska, Jill A. Beroukhim, Rameen Sellers, William R. Garraway, Levi Rubin, Mark A. |
author_facet | Demichelis, Francesca Greulich, Heidi Macoska, Jill A. Beroukhim, Rameen Sellers, William R. Garraway, Levi Rubin, Mark A. |
author_sort | Demichelis, Francesca |
collection | PubMed |
description | Translational research hinges on the ability to make observations in model systems and to implement those findings into clinical applications, such as the development of diagnostic tools or targeted therapeutics. Tumor cell lines are commonly used to model carcinogenesis. The same tumor cell line can be simultaneously studied in multiple research laboratories throughout the world, theoretically generating results that are directly comparable. One important assumption in this paradigm is that researchers are working with the same cells. However, recent work using high throughput genomic analyses questions the accuracy of this assumption. Observations by our group and others suggest that experiments reported in the scientific literature may contain pre-analytic errors due to inaccurate identities of the cell lines employed. To address this problem, we developed a simple approach that enables an accurate determination of cell line identity by genotyping 34 single nucleotide polymorphisms (SNPs). Here, we describe the empirical development of a SNP panel identification assay (SPIA) compatible with routine use in the laboratory setting to ensure the identity of tumor cell lines and human tumor samples throughout the course of long term research use. |
format | Text |
id | pubmed-2367734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-23677342008-05-07 SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines Demichelis, Francesca Greulich, Heidi Macoska, Jill A. Beroukhim, Rameen Sellers, William R. Garraway, Levi Rubin, Mark A. Nucleic Acids Res Computational Biology Translational research hinges on the ability to make observations in model systems and to implement those findings into clinical applications, such as the development of diagnostic tools or targeted therapeutics. Tumor cell lines are commonly used to model carcinogenesis. The same tumor cell line can be simultaneously studied in multiple research laboratories throughout the world, theoretically generating results that are directly comparable. One important assumption in this paradigm is that researchers are working with the same cells. However, recent work using high throughput genomic analyses questions the accuracy of this assumption. Observations by our group and others suggest that experiments reported in the scientific literature may contain pre-analytic errors due to inaccurate identities of the cell lines employed. To address this problem, we developed a simple approach that enables an accurate determination of cell line identity by genotyping 34 single nucleotide polymorphisms (SNPs). Here, we describe the empirical development of a SNP panel identification assay (SPIA) compatible with routine use in the laboratory setting to ensure the identity of tumor cell lines and human tumor samples throughout the course of long term research use. Oxford University Press 2008-04 2008-02-27 /pmc/articles/PMC2367734/ /pubmed/18304946 http://dx.doi.org/10.1093/nar/gkn089 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Demichelis, Francesca Greulich, Heidi Macoska, Jill A. Beroukhim, Rameen Sellers, William R. Garraway, Levi Rubin, Mark A. SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines |
title | SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines |
title_full | SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines |
title_fullStr | SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines |
title_full_unstemmed | SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines |
title_short | SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines |
title_sort | snp panel identification assay (spia): a genetic-based assay for the identification of cell lines |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2367734/ https://www.ncbi.nlm.nih.gov/pubmed/18304946 http://dx.doi.org/10.1093/nar/gkn089 |
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