Please use this identifier to cite or link to this item: https://doi.org/10.3892/ol.2017.5669
Title: Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study
Authors: Yan, Benedict
Hu, Yongli
Ban, Kenneth HK 
Tiang, Zenia
Ng, Christopher
Lee, Joanne
Tan, Wilson
Chiu, Lily
Tan, Tin Wee
Seah, Elaine
Ng, Chin Hin
Chng, Wee-Joo 
Foo, Roger
Keywords: Science & Technology
Life Sciences & Biomedicine
Oncology
single cell
genomics
acute myeloid leukei transcriptomics
gene expression
RNA-SEQ
FLOW-CYTOMETRY
HETEROGENEITY
TRANSCRIPTOME
EXPRESSION
Issue Date: 1-Mar-2017
Publisher: SPANDIDOS PUBL LTD
Citation: Yan, Benedict, Hu, Yongli, Ban, Kenneth HK, Tiang, Zenia, Ng, Christopher, Lee, Joanne, Tan, Wilson, Chiu, Lily, Tan, Tin Wee, Seah, Elaine, Ng, Chin Hin, Chng, Wee-Joo, Foo, Roger (2017-03-01). Single-cell genomic profiling of acute myeloid leukemia for clinical use: A pilot study. ONCOLOGY LETTERS 13 (3) : 1625-1630. ScholarBank@NUS Repository. https://doi.org/10.3892/ol.2017.5669
Abstract: 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.
Source Title: ONCOLOGY LETTERS
URI: https://scholarbank.nus.edu.sg/handle/10635/229090
ISSN: 17921074
17921082
DOI: 10.3892/ol.2017.5669
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