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Self-digitization chip for single-cell genotyping of cancer-related mutations

Cancer is a heterogeneous disease, and patient-level genetic assessments can guide therapy choice and impact prognosis. However, little is known about the impact of genetic variability within a tumor, intratumoral heterogeneity (ITH), on disease progression or outcome. Current approaches using bulk...

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Autores principales: Thompson, Alison M., Smith, Jordan L., Monroe, Luke D., Kreutz, Jason E., Schneider, Thomas, Fujimoto, Bryant S., Chiu, Daniel T., Radich, Jerald P., Paguirigan, Amy L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931502/
https://www.ncbi.nlm.nih.gov/pubmed/29718986
http://dx.doi.org/10.1371/journal.pone.0196801
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author Thompson, Alison M.
Smith, Jordan L.
Monroe, Luke D.
Kreutz, Jason E.
Schneider, Thomas
Fujimoto, Bryant S.
Chiu, Daniel T.
Radich, Jerald P.
Paguirigan, Amy L.
author_facet Thompson, Alison M.
Smith, Jordan L.
Monroe, Luke D.
Kreutz, Jason E.
Schneider, Thomas
Fujimoto, Bryant S.
Chiu, Daniel T.
Radich, Jerald P.
Paguirigan, Amy L.
author_sort Thompson, Alison M.
collection PubMed
description Cancer is a heterogeneous disease, and patient-level genetic assessments can guide therapy choice and impact prognosis. However, little is known about the impact of genetic variability within a tumor, intratumoral heterogeneity (ITH), on disease progression or outcome. Current approaches using bulk tumor specimens can suggest the presence of ITH, but only single-cell genetic methods have the resolution to describe the underlying clonal structures themselves. Current techniques tend to be labor and resource intensive and challenging to characterize with respect to sources of biological and technical variability. We have developed a platform using a microfluidic self-digitization chip to partition cells in stationary volumes for cell imaging and allele-specific PCR. Genotyping data from only confirmed single-cell volumes is obtained and subject to a variety of relevant quality control assessments such as allele dropout, false positive, and false negative rates. We demonstrate single-cell genotyping of the NPM1 type A mutation, an important prognostic indicator in acute myeloid leukemia, on single cells of the cell line OCI-AML3, describing a more complex zygosity distribution than would be predicted via bulk analysis.
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spelling pubmed-59315022018-05-11 Self-digitization chip for single-cell genotyping of cancer-related mutations Thompson, Alison M. Smith, Jordan L. Monroe, Luke D. Kreutz, Jason E. Schneider, Thomas Fujimoto, Bryant S. Chiu, Daniel T. Radich, Jerald P. Paguirigan, Amy L. PLoS One Research Article Cancer is a heterogeneous disease, and patient-level genetic assessments can guide therapy choice and impact prognosis. However, little is known about the impact of genetic variability within a tumor, intratumoral heterogeneity (ITH), on disease progression or outcome. Current approaches using bulk tumor specimens can suggest the presence of ITH, but only single-cell genetic methods have the resolution to describe the underlying clonal structures themselves. Current techniques tend to be labor and resource intensive and challenging to characterize with respect to sources of biological and technical variability. We have developed a platform using a microfluidic self-digitization chip to partition cells in stationary volumes for cell imaging and allele-specific PCR. Genotyping data from only confirmed single-cell volumes is obtained and subject to a variety of relevant quality control assessments such as allele dropout, false positive, and false negative rates. We demonstrate single-cell genotyping of the NPM1 type A mutation, an important prognostic indicator in acute myeloid leukemia, on single cells of the cell line OCI-AML3, describing a more complex zygosity distribution than would be predicted via bulk analysis. Public Library of Science 2018-05-02 /pmc/articles/PMC5931502/ /pubmed/29718986 http://dx.doi.org/10.1371/journal.pone.0196801 Text en © 2018 Thompson 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Thompson, Alison M.
Smith, Jordan L.
Monroe, Luke D.
Kreutz, Jason E.
Schneider, Thomas
Fujimoto, Bryant S.
Chiu, Daniel T.
Radich, Jerald P.
Paguirigan, Amy L.
Self-digitization chip for single-cell genotyping of cancer-related mutations
title Self-digitization chip for single-cell genotyping of cancer-related mutations
title_full Self-digitization chip for single-cell genotyping of cancer-related mutations
title_fullStr Self-digitization chip for single-cell genotyping of cancer-related mutations
title_full_unstemmed Self-digitization chip for single-cell genotyping of cancer-related mutations
title_short Self-digitization chip for single-cell genotyping of cancer-related mutations
title_sort self-digitization chip for single-cell genotyping of cancer-related mutations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931502/
https://www.ncbi.nlm.nih.gov/pubmed/29718986
http://dx.doi.org/10.1371/journal.pone.0196801
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