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Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study
Although bulk high-throughput genomic profiling studies have led to a significant increase in the understanding of cancer biology, there is increasing awareness that bulk profiling approaches do not completely elucidate tumor heterogeneity. Single-cell genomic profiling enables the distinction of tu...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5403273/ https://www.ncbi.nlm.nih.gov/pubmed/28454300 http://dx.doi.org/10.3892/ol.2017.5669 |
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author | Yan, Benedict Hu, Yongli Ban, Kenneth H.K. Tiang, Zenia Ng, Christopher Lee, Joanne Tan, Wilson Chiu, Lily Tan, Tin Wee Seah, Elaine Ng, Chin Hin Chng, Wee-Joo Foo, Roger |
author_facet | Yan, Benedict Hu, Yongli Ban, Kenneth H.K. Tiang, Zenia Ng, Christopher Lee, Joanne Tan, Wilson Chiu, Lily Tan, Tin Wee Seah, Elaine Ng, Chin Hin Chng, Wee-Joo Foo, Roger |
author_sort | Yan, Benedict |
collection | PubMed |
description | Although bulk high-throughput genomic profiling studies have led to a significant increase in the understanding of cancer biology, there is increasing awareness that bulk profiling approaches do not completely elucidate tumor heterogeneity. Single-cell genomic profiling enables the distinction of tumor heterogeneity, and may improve clinical diagnosis through the identification and characterization of putative subclonal populations. In the present study, the challenges associated with a single-cell genomics profiling workflow for clinical diagnostics were investigated. Single-cell RNA-sequencing (RNA-seq) was performed on 20 cells from an acute myeloid leukemia bone marrow sample. Putative blasts were identified based on their gene expression profiles and principal component analysis was performed to identify outlier cells. Variant calling was performed on the single-cell RNA-seq data. The present pilot study demonstrates a proof of concept for clinical single-cell genomic profiling. The recognized limitations include significant stochastic RNA loss and the relatively low throughput of the current proposed platform. Although the results of the present study are promising, further technological advances and protocol optimization are necessary for single-cell genomic profiling to be clinically viable. |
format | Online Article Text |
id | pubmed-5403273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-54032732017-04-27 Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study Yan, Benedict Hu, Yongli Ban, Kenneth H.K. Tiang, Zenia Ng, Christopher Lee, Joanne Tan, Wilson Chiu, Lily Tan, Tin Wee Seah, Elaine Ng, Chin Hin Chng, Wee-Joo Foo, Roger Oncol Lett Articles Although bulk high-throughput genomic profiling studies have led to a significant increase in the understanding of cancer biology, there is increasing awareness that bulk profiling approaches do not completely elucidate tumor heterogeneity. Single-cell genomic profiling enables the distinction of tumor heterogeneity, and may improve clinical diagnosis through the identification and characterization of putative subclonal populations. In the present study, the challenges associated with a single-cell genomics profiling workflow for clinical diagnostics were investigated. Single-cell RNA-sequencing (RNA-seq) was performed on 20 cells from an acute myeloid leukemia bone marrow sample. Putative blasts were identified based on their gene expression profiles and principal component analysis was performed to identify outlier cells. Variant calling was performed on the single-cell RNA-seq data. The present pilot study demonstrates a proof of concept for clinical single-cell genomic profiling. The recognized limitations include significant stochastic RNA loss and the relatively low throughput of the current proposed platform. Although the results of the present study are promising, further technological advances and protocol optimization are necessary for single-cell genomic profiling to be clinically viable. D.A. Spandidos 2017-03 2017-02-01 /pmc/articles/PMC5403273/ /pubmed/28454300 http://dx.doi.org/10.3892/ol.2017.5669 Text en Copyright: © Yan et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Yan, Benedict Hu, Yongli Ban, Kenneth H.K. Tiang, Zenia Ng, Christopher Lee, Joanne Tan, Wilson Chiu, Lily Tan, Tin Wee Seah, Elaine Ng, Chin Hin Chng, Wee-Joo Foo, Roger Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study |
title | Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study |
title_full | Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study |
title_fullStr | Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study |
title_full_unstemmed | Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study |
title_short | Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study |
title_sort | single-cell genomic profiling of acute myeloid leukemia for clinical use: a pilot study |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5403273/ https://www.ncbi.nlm.nih.gov/pubmed/28454300 http://dx.doi.org/10.3892/ol.2017.5669 |
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