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Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia

Abstract

Recent advances in single-cell transcriptomics are ideally placed to unravel intratumoral heterogeneity and selective resistance of cancer stem cell (SC) subpopulations to molecularly targeted cancer therapies. However, current single-cell RNA-sequencing approaches lack the sensitivity required to reliably detect somatic mutations. We developed a method that combines high-sensitivity mutation detection with whole-transcriptome analysis of the same single cell. We applied this technique to analyze more than 2,000 SCs from patients with chronic myeloid leukemia (CML) throughout the disease course, revealing heterogeneity of CML-SCs, including the identification of a subgroup of CML-SCs with a distinct molecular signature that selectively persisted during prolonged therapy. Analysis of nonleukemic SCs from patients with CML also provided new insights into cell-extrinsic disruption of hematopoiesis in CML associated with clinical outcome. Furthermore, we used this single-cell approach to identify a blast-crisis-specific SC population, which was also present in a subclone of CML-SCs during the chronic phase in a patient who subsequently developed blast crisis. This approach, which might be broadly applied to any malignancy, illustrates how single-cell analysis can identify subpopulations of therapy-resistant SCs that are not apparent through cell-population analysis.

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Figure 1: High-sensitivity single-cell detection of BCR-ABL with parallel unbiased whole-transcriptome analysis.
Figure 2: Single-cell whole-transcriptome analysis and BCR-ABL detection in single CML stem cells.
Figure 3: Single-cell RNA-sequencing reveals distinct molecular signatures of BCR-ABL+ CML-SCs at diagnosis.
Figure 4: Single-cell RNA sequencing of SCs at diagnosis of patients with CML predicts molecular response to TKI.
Figure 5: Single-cell analysis reveals distinct molecular signatures of quiescent CML-SCs persisting during TKI therapy.
Figure 6: Single-cell RNA sequencing reveals heterogeneity of CML stem cells associated with disease progression in CML.

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Acknowledgements

This work was funded by a Medical Research Council Senior Clinical Fellowship (MR/L006340/1), MRC Confidence in Concept award (MC_PC_13073) and Rosetrees Trust award (A712: Rosetrees Trust Award (A712)) to A.J.M., the MRC Molecular Haematology Unit core award (A.J.M. and S.E.W.J.; MC_UU_12009/5), a MRC programme grant to S.E.W.J. (G0801073), an international-recruitment award from the Swedish Research Council (S.E.W.J.), and grants from the Tobias Foundation (S.E.W.J.) and the Center for Innovative Medicine (CIMED) at the Karolinska Institute (S.E.W.J.). This work was also supported by the MRC-funded Oxford Consortium for Single-cell Biology (MR/M00919X/1) and the Oxford NIHR Biomedical Centre based at Oxford University Hospitals NHS Trust and University of Oxford. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or the NIH. The work was also supported by an educational grant from Novartis. The authors acknowledge the contributions of the WIMM Flow Cytometry Facility, supported by the MRC HIU; MRC MHU (MC_UU_12009); NIHR Oxford BRC and John Fell Fund (131/030 and 101/517), the EPA fund (CF182 and CF170) and by the WIMM Strategic Alliance awards G0902418 and MC_UU_12025. N.A. was supported by the Oxford–Wellcome Trust Institutional Strategic Support Fund. S.M. is supported by the Finnish Cancer Institute and the Finnish Cancer Organizations.

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Authors and Affiliations

Authors

Contributions

A.G. designed, performed and analyzed experiments and contributed to writing the manuscript. S.T. designed and performed bioinformatic analyses and contributed to writing the manuscript. N.B. and B.J.P. performed analyses of RNA sequencing and qPCR results. P.S.W. and P.S. were involved in FACS analysis and sorting. R.N., A.R.-M., C.A.G.B. and L.J. performed experiments. N.A. maintained single-cell facility infrastructure. P.V., S.M. and H.Q. provided infrastructure for sample banking and provided input on experimental design and analysis. K.A. performed FISH experiments. Å.S. was involved in RNA-sequencing experiments. U.O.-S. collected clinical information. R.S. provided input on RNA-sequencing experiments. A.J.M. and S.E.W.J. conceived and supervised the project, designed and analyzed experiments and wrote the manuscript.

Corresponding authors

Correspondence to Sten Eirik W Jacobsen or Adam J Mead.

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Competing interests

A.J.M. has received honoraria and research funding from Novartis.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–16 and Table 12–15. (PDF 3114 kb)

Supplementary Table 1

Patient demographics and characteristics. (XLSX 46 kb)

Supplementary Table 2

Differentially expressed genes between normal HSCs, BCRABL+ and BCR-ABL- SCs from CP-CML patients at diagnosis. (XLSX 186 kb)

Supplementary Table 3

Gene-sets from previous studies on CML stem and progenitor cells. (XLSX 113 kb)

Supplementary Table 4

Results from GSEA comparing normal HSCs to BCRABL+ SCs and BCR-ABL- SCs from CP-CML patients at diagnosis and using gene-sets from previous studies on CML stem and progenitor cells. (XLSX 24 kb)

Supplementary Table 5

Results from GSEA comparing normal HSCs to BCRABL+ SCs and BCR-ABL- SCs from CP-CML patients at diagnosis and using HALLMARK gene sets (XLSX 79 kb)

Supplementary Table 6

Results from GSEA comparing diagnostic samples from good and poor responder CML patients. (XLSX 28 kb)

Supplementary Table 7

Top 500 informative genes for distinguishing normal-HSCs from BCR-ABL+ SCs at diagnosis and during remission. (XLSX 72 kb)

Supplementary Table 8

Results from GSEA on HALLMARK gene-sets comparing remission group-A BCR-ABL+ SCs to remission group-B BCRABL+ SCs. (XLSX 12 kb)

Supplementary Table 9

Differentially expressed genes between normal HSCs, BCRABL+ SCs from diagnosis, remission group-A and remission group-B. (XLSX 704 kb)

Supplementary Table 10

Results from GSEA comparing remission group-A BCRABL+ SCs to normal HSCs and remission BCR-ABL- SCs. (XLSX 27 kb)

Supplementary Table 11

Differentially expressed genes between single BCRABL+ SCs falling in CP-CML cluster and BCR-ABL+ SCs falling in BC-CML cluster. (XLSX 193 kb)

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Giustacchini, A., Thongjuea, S., Barkas, N. et al. Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia. Nat Med 23, 692–702 (2017). https://doi.org/10.1038/nm.4336

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