Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Clonal diversity is a consequence of cancer cell evolution driven by Darwinian selection. Precise characterization of clonal architecture is essential to understand the evolutionary history of tumor development and its association with treatment resistance. Here, using a single-cell DNA sequencing, we report the clonal architecture and mutational histories of 123 acute myeloid leukemia (AML) patients. The single-cell data reveals cell-level mutation co-occurrence and enables reconstruction of mutational histories characterized by linear and branching patterns of clonal evolution, with the latter including convergent evolution. Through xenotransplantion, we show leukemia initiating capabilities of individual subclones evolving in parallel. Also, by simultaneous single-cell DNA and cell surface protein analysis, we illustrate both genetic and phenotypic evolution in AML. Lastly, single-cell analysis of longitudinal samples reveals underlying evolutionary process of therapeutic resistance. Together, these data unravel clonal diversity and evolution patterns of AML, and highlight their clinical relevance in the era of precision medicine.

Abstract

Understanding the evolutionary trajectory of cancer samples may enable understanding resistance to treatment. Here, the authors used single cell sequencing of a cohort of acute myeloid leukemia tumours and identify features of linear and branching evolution in tumours.

Related collections

Most cited references 40

Record: found
Abstract: not found
Article: not found

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Yoav Benjamini, Yosef Hochberg (1995)

0 comments Cited 23748 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Investigation of the freely available easy-to-use software ‘EZR' for medical statistics

Y Kanda (2012)

Although there are many commercially available statistical software packages, only a few implement a competing risk analysis or a proportional hazards regression model with time-dependent covariates, which are necessary in studies on hematopoietic SCT. In addition, most packages are not clinician friendly, as they require that commands be written based on statistical languages. This report describes the statistical software ‘EZR' (Easy R), which is based on R and R commander. EZR enables the application of statistical functions that are frequently used in clinical studies, such as survival analyses, including competing risk analyses and the use of time-dependent covariates, receiver operating characteristics analyses, meta-analyses, sample size calculation and so on, by point-and-click access. EZR is freely available on our website (http://www.jichi.ac.jp/saitama-sct/SaitamaHP.files/statmed.html) and runs on both Windows (Microsoft Corporation, USA) and Mac OS X (Apple, USA). This report provides instructions for the installation and operation of EZR.

0 comments Cited 3057 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Marco Gerlinger, Andrew J. Rowan, Stuart Horswell … (2012)

Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples. To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression. Phylogenetic reconstruction revealed branched evolutionary tumor growth, with 63 to 69% of all somatic mutations not detectable across every tumor region. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin (mTOR) kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro. Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors. Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection. (Funded by the Medical Research Council and others.).

0 comments Cited 1072 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Niko Beerenwinkel:

ORCID: http://orcid.org/0000-0002-0573-6119

niko.beerenwinkel@bsse.ethz.ch

P. Andrew Futreal:

ORCID: http://orcid.org/0000-0001-8663-2671

afutreal@mdanderson.org

Koichi Takahashi:

ORCID: http://orcid.org/0000-0002-8027-9659

ktakahashi@mdanderson.org

Journal

Journal ID (nlm-ta): Nat Commun

Journal ID (iso-abbrev): Nat Commun

Title: Nature Communications

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2041-1723

Publication date (Electronic): 21 October 2020

Publication date PMC-release: 21 October 2020

Publication date Collection: 2020

Volume: 11

Electronic Location Identifier: 5327

Affiliations

[1 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Leukemia, , The University of Texas MD Anderson Cancer Center, ; Houston, TX USA

[2 ]GRID grid.26999.3d, ISNI 0000 0001 2151 536X, Department of Hematology and Oncology, , Graduate School of Medicine, The University of Tokyo, ; Tokyo, Japan

[3 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Genomic Medicine, , The University of Texas MD Anderson Cancer Center, ; Houston, TX USA

[4 ]GRID grid.5801.c, ISNI 0000 0001 2156 2780, Department of Biosystems Science and Engineering, , ETH Zurich, ; Basel, Switzerland

[5 ]SIB Swiss Institute of Bioinformatics, Basel, Switzerland

[6 ]GRID grid.39382.33, ISNI 0000 0001 2160 926X, Department of Molecular and Human Genetics, , Baylor College of Medicine, ; Houston, TX USA

[7 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Hematopathology, , The University of Texas MD Anderson Cancer Center, ; Houston, TX USA

[8 ]GRID grid.267308.8, ISNI 0000 0000 9206 2401, Department of Neurosurgery, , The University of Texas Health Science Center at Houston, ; Houston, TX USA

[9 ]GRID grid.257016.7, ISNI 0000 0001 0673 6172, Department of Oral and Maxillofacial Surgery, , Hirosaki University Graduate School of Medicine, ; Aomori, Japan

[10 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Genetics, , The University of Texas MD Anderson Cancer Center, ; Houston, TX USA

[11 ]GRID grid.240145.6, ISNI 0000 0001 2291 4776, Department of Bioinformatics and Computational Biology, , The University of Texas MD Anderson Cancer Center, ; Houston, TX USA

Author information

Kiyomi Morita http://orcid.org/0000-0002-0407-1565

Sanam Loghavi http://orcid.org/0000-0001-8980-3202

Jianhua Zhang http://orcid.org/0000-0001-5412-9860

Courtney D. DiNardo http://orcid.org/0000-0001-9003-0390

Jorge Cortes http://orcid.org/0000-0002-8636-1071

Guillermo Garcia-Manero http://orcid.org/0000-0002-3631-2482

Marina Konopleva http://orcid.org/0000-0002-9347-2212

Daisuke Nakada http://orcid.org/0000-0001-6010-7094

Niko Beerenwinkel http://orcid.org/0000-0002-0573-6119

P. Andrew Futreal http://orcid.org/0000-0001-8663-2671

Koichi Takahashi http://orcid.org/0000-0002-8027-9659

Article

Publisher ID: 19119

DOI: 10.1038/s41467-020-19119-8

PMC ID: 7577981

PubMed ID: 33087716

SO-VID: 5e175828-5c1a-4113-aa3b-e419bbad49c9

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 4 August 2020

Date accepted : 22 September 2020

Funding

Funded by: FundRef https://doi.org/10.13039/100004917, Cancer Prevention and Research Institute of Texas (Cancer Prevention Research Institute of Texas);

Award ID: R120501

Award Recipient : Koichi Takahashi

Funded by: FundRef https://doi.org/10.13039/100000928, Welch Foundation;

Award ID: G-0040

Award Recipient : Koichi Takahashi

Funded by: FundRef https://doi.org/10.13039/100005189, Leukemia and Lymphoma Society (Leukemia & Lymphoma Society);

Award ID: CA193235

Award Recipient : Koichi Takahashi

Funded by: FundRef https://doi.org/10.13039/100007423, Lyda Hill Foundation;

Funded by: Physician Scientist Program at MD Anderson, Charif Souki Cancer Research Fund, Leukemia Research Fund, Japan Society for the Promotion of Science Research Fellowships for Young Scientists, Japan Society for the Promotion of Science Overseas Research Fellowships, generous philanthropic contributions to MD Anderson’s Moon Shot Program

Custom metadata

ScienceOpen disciplines: Uncategorized

Keywords: cancer genomics,acute myeloid leukaemia,tumour heterogeneity

Data availability:

ScienceOpen disciplines: Uncategorized

Keywords: cancer genomics, acute myeloid leukaemia, tumour heterogeneity

Comments

Comment on this article

scite_

Cited by 111

See all cited by

Most referenced authors 1,776

See all reference authors

- Version 1
- Version 1

Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics

Read this article at

Abstract

Abstract

Related collections

Crocodylian evolution

Most cited references 40

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Investigation of the freely available easy-to-use software ‘EZR' for medical statistics

Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Author and article information

Contributors

Journal

Affiliations

Author information

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 450

Cited by 111

Most referenced authors 1,776