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BMC Genomics. 2017 Nov 25;18(1):906. doi: 10.1186/s12864-017-4286-1.

Genome-wide segregation of single nucleotide and structural variants into single cancer cells.

Author information

1
Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
2
Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
3
Buffalo Institute for Genomics and Data Analytics, University at Buffalo, Buffalo, NY, 14260, USA.
4
Present address: Buffalo Institute for Genomics and Data Analytics CBLS, 701 Ellicott St, Buffalo, NY, 14203, USA.
5
Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA. Charles.Gawad@STJUDE.ORG.
6
Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA. Charles.Gawad@STJUDE.ORG.
7
Present address: MS 1260, Room IA6042, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA. Charles.Gawad@STJUDE.ORG.

Abstract

BACKGROUND:

Single-cell genome sequencing provides high-resolution details of the clonal genomic modifications that occur during cancer initiation, progression, and ongoing evolution as patients undergo treatment. One limitation of current single-cell sequencing strategies is a suboptimal capacity to detect all classes of single-nucleotide and structural variants in the same cells.

RESULTS:

Here we present a new approach for determining comprehensive variant profiles of single cells using a microfluidic amplicon-based strategy to detect structural variant breakpoint sequences instead of using relative read depth to infer copy number changes. This method can reconstruct the clonal architecture and mutational history of a malignancy using all classes and sizes of somatic variants, providing more complete details of the temporal changes in mutational classes and processes that led to the development of a malignant neoplasm. Using this approach, we interrogated cells from a patient with leukemia, determining that processes producing structural variation preceded single nucleotide changes in the development of that malignancy.

CONCLUSIONS:

All classes and sizes of genomic variants can be efficiently detected in single cancer cells using our new method, enabling the ordering of distinct classes of mutations during tumor evolution.

KEYWORDS:

Single-cell genomics; acute lymphoblastic leukemia; cancer evolution

PMID:
29178827
PMCID:
PMC5702214
DOI:
10.1186/s12864-017-4286-1
[Indexed for MEDLINE]
Free PMC Article

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