Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia

Lili Wang; Jean Fan; Joshua M. Francis; George Georghiou; Sarah Hergert; Shuqiang Li; Rutendo Gambe; Chensheng W. Zhou; Chunxiao Yang; Sheng Xiao; Paola Dal Cin; Michaela Bowden; Dylan Kotliar; Sachet A. Shukla; Jennifer R. Brown; Donna Neuberg; Dario R. Alessi; Cheng-Zhong Zhang; Peter V. Kharchenko; Kenneth J. Livak; Catherine J. Wu

doi:10.1101/gr.217331.116

Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia

Lili Wang, Jean Fan, Joshua M. Francis, George Georghiou, Sarah Hergert, Shuqiang Li, Rutendo Gambe, Chensheng W. Zhou, Chunxiao Yang, Sheng Xiao, Paola Dal Cin, Michaela Bowden, Dylan Kotliar, Sachet A. Shukla, Jennifer R. Brown, Donna Neuberg, Dario R. Alessi, Cheng-Zhong Zhang (Lead / Corresponding author), Peter V. Kharchenko, Kenneth J. LivakCatherine J. Wu (Lead / Corresponding author)

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Abstract

Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

Original language	English
Pages (from-to)	1300-1311
Number of pages	11
Journal	Genome Research
Volume	27
Early online date	5 Jul 2017
DOIs	https://doi.org/10.1101/gr.217331.116
Publication status	Published - 5 Jul 2017

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© 2017 Wang et al. This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
Final published version, 823 KBLicence: CC BY-NC

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Wang, L., Fan, J., Francis, J. M., Georghiou, G., Hergert, S., Li, S., Gambe, R., Zhou, C. W., Yang, C., Xiao, S., Cin, P. D., Bowden, M., Kotliar, D., Shukla, S. A., Brown, J. R., Neuberg, D., Alessi, D. R., Zhang, C.-Z., Kharchenko, P. V., ... Wu, C. J. (2017). Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia. Genome Research, 27, 1300-1311. https://doi.org/10.1101/gr.217331.116

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title = "Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia",

abstract = "Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.",

author = "Lili Wang and Jean Fan and Francis, {Joshua M.} and George Georghiou and Sarah Hergert and Shuqiang Li and Rutendo Gambe and Zhou, {Chensheng W.} and Chunxiao Yang and Sheng Xiao and Cin, {Paola Dal} and Michaela Bowden and Dylan Kotliar and Shukla, {Sachet A.} and Brown, {Jennifer R.} and Donna Neuberg and Alessi, {Dario R.} and Cheng-Zhong Zhang and Kharchenko, {Peter V.} and Livak, {Kenneth J.} and Wu, {Catherine J.}",

note = "Funding: Medical Research Council (MC_UU_12016/2)",

year = "2017",

month = jul,

day = "5",

doi = "10.1101/gr.217331.116",

language = "English",

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publisher = "Cold Spring Harbor Laboratory Press",

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Wang, L, Fan, J, Francis, JM, Georghiou, G, Hergert, S, Li, S, Gambe, R, Zhou, CW, Yang, C, Xiao, S, Cin, PD, Bowden, M, Kotliar, D, Shukla, SA, Brown, JR, Neuberg, D, Alessi, DR, Zhang, C-Z, Kharchenko, PV, Livak, KJ & Wu, CJ 2017, 'Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia', Genome Research, vol. 27, pp. 1300-1311. https://doi.org/10.1101/gr.217331.116

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T1 - Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia

AU - Wang, Lili

AU - Fan, Jean

AU - Francis, Joshua M.

AU - Georghiou, George

AU - Hergert, Sarah

AU - Li, Shuqiang

AU - Gambe, Rutendo

AU - Zhou, Chensheng W.

AU - Yang, Chunxiao

AU - Xiao, Sheng

AU - Cin, Paola Dal

AU - Bowden, Michaela

AU - Kotliar, Dylan

AU - Shukla, Sachet A.

AU - Brown, Jennifer R.

AU - Neuberg, Donna

AU - Alessi, Dario R.

AU - Zhang, Cheng-Zhong

AU - Kharchenko, Peter V.

AU - Livak, Kenneth J.

AU - Wu, Catherine J.

N1 - Funding: Medical Research Council (MC_UU_12016/2)

PY - 2017/7/5

Y1 - 2017/7/5

N2 - Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

AB - Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

U2 - 10.1101/gr.217331.116

DO - 10.1101/gr.217331.116

M3 - Article

C2 - 28679620

SN - 1088-9051

VL - 27

SP - 1300

EP - 1311

JO - Genome Research

JF - Genome Research

ER -

Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia

Abstract

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