Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia
Applying a new, more sensitive single-cell transcriptomics method to diagnosis, remission and progression samples from patients with chronic myeloid leukemia reveals insight into the heterogeneity of cells that resist treatment with targeted therapy, as well as into the dynamics of disease progressi...
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| Vydané v: | Nature medicine Ročník 23; číslo 6; s. 692 - 702 |
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| Hlavní autori: | , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
New York
Nature Publishing Group US
01.06.2017
Nature Publishing Group |
| Predmet: | |
| ISSN: | 1078-8956, 1546-170X, 1546-170X |
| On-line prístup: | Získať plný text |
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| Abstract | Applying a new, more sensitive single-cell transcriptomics method to diagnosis, remission and progression samples from patients with chronic myeloid leukemia reveals insight into the heterogeneity of cells that resist treatment with targeted therapy, as well as into the dynamics of disease progression and its effects on nontransformed hematopoietic stem cells.
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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| AbstractList | 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. Applying a new, more sensitive single-cell transcriptomics method to diagnosis, remission and progression samples from patients with chronic myeloid leukemia reveals insight into the heterogeneity of cells that resist treatment with targeted therapy, as well as into the dynamics of disease progression and its effects on nontransformed hematopoietic stem cells. 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. 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.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. |
| Audience | Academic |
| Author | Woll, Petter S Vyas, Paresh Jacobsen, Sten Eirik W Mead, Adam J Thongjuea, Supat Ashley, Neil Mustjoki, Satu Jamieson, Lauren Segerstolpe, Åsa Olsson-Strömberg, Ulla Sopp, Paul Giustacchini, Alice Booth, Christopher A G Qian, Hong Povinelli, Benjamin J Barkas, Nikolaos Anderson, Kristina Sandberg, Rickard Norfo, Ruggiero Rodriguez-Meira, Alba |
| Author_xml | – sequence: 1 givenname: Alice orcidid: 0000-0002-8733-8594 surname: Giustacchini fullname: Giustacchini, Alice organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 2 givenname: Supat surname: Thongjuea fullname: Thongjuea, Supat organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 3 givenname: Nikolaos surname: Barkas fullname: Barkas, Nikolaos organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 4 givenname: Petter S surname: Woll fullname: Woll, Petter S organization: Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 5 givenname: Benjamin J surname: Povinelli fullname: Povinelli, Benjamin J organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 6 givenname: Christopher A G surname: Booth fullname: Booth, Christopher A G organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 7 givenname: Paul surname: Sopp fullname: Sopp, Paul organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 8 givenname: Ruggiero surname: Norfo fullname: Norfo, Ruggiero organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 9 givenname: Alba surname: Rodriguez-Meira fullname: Rodriguez-Meira, Alba organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 10 givenname: Neil surname: Ashley fullname: Ashley, Neil organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 11 givenname: Lauren surname: Jamieson fullname: Jamieson, Lauren organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 12 givenname: Paresh orcidid: 0000-0003-3931-0914 surname: Vyas fullname: Vyas, Paresh organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford – sequence: 13 givenname: Kristina surname: Anderson fullname: Anderson, Kristina organization: Department of Cellular Therapy, Norwegian Radium Hospital, Oslo University Hospital – sequence: 14 givenname: Åsa surname: Segerstolpe fullname: Segerstolpe, Åsa organization: Department of Cell and Molecular Biology, Karolinska Institutet, Integrated Cardio Metabolic Center (ICMC), Karolinska Institutet – sequence: 15 givenname: Hong orcidid: 0000-0002-2512-9199 surname: Qian fullname: Qian, Hong organization: Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet – sequence: 16 givenname: Ulla surname: Olsson-Strömberg fullname: Olsson-Strömberg, Ulla organization: Department of Medical Science and Division of Hematology, University Hospital – sequence: 17 givenname: Satu surname: Mustjoki fullname: Mustjoki, Satu organization: Department of Clinical Chemistry and Hematology, Hematology Research Unit Helsinki, University of Helsinki and Helsinki University Hospital Comprehensive Cancer Center – sequence: 18 givenname: Rickard orcidid: 0000-0001-6473-1740 surname: Sandberg fullname: Sandberg, Rickard organization: Department of Cell and Molecular Biology, Karolinska Institutet, Ludwig Institute for Cancer Research – sequence: 19 givenname: Sten Eirik W surname: Jacobsen fullname: Jacobsen, Sten Eirik W email: sten.eirik.jacobsen@ki.se organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Department of Cell and Molecular Biology, Karolinska Institutet, Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Karolinska University Hospital – sequence: 20 givenname: Adam J orcidid: 0000-0001-8522-1002 surname: Mead fullname: Mead, Adam J email: adam.mead@imm.ox.ac.uk organization: MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Haemopoietic Stem Cell Biology Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, NIHR Biomedical Research Centre, Churchill Hospital |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28504724$$D View this record in MEDLINE/PubMed https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-327138$$DView record from Swedish Publication Index (Uppsala universitet) http://kipublications.ki.se/Default.aspx?queryparsed=id:135948867$$DView record from Swedish Publication Index (Karolinska Institutet) |
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| Title | Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia |
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