Literature DB >> 31092926

Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia.

Federico Gaiti1,2, Ronan Chaligne1,2, Hongcang Gu3, Ryan M Brand1,2, Steven Kothen-Hill1,2, Rafael C Schulman1,2, Kirill Grigorev2, Davide Risso2,4, Kyu-Tae Kim1,2, Alessandro Pastore5, Kevin Y Huang1,2, Alicia Alonso2, Caroline Sheridan2, Nathaniel D Omans1,2, Evan Biederstedt1,2, Kendell Clement3, Lili Wang6, Joshua A Felsenfeld2, Erica B Bhavsar2, Martin J Aryee3,7, John N Allan2, Richard Furman2, Andreas Gnirke3, Catherine J Wu3,8, Alexander Meissner3,9, Dan A Landau10,11.   

Abstract

Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy2,3. The CLL epigenome is also an important disease-defining feature4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.

Entities:  

Mesh:

Year:  2019        PMID: 31092926      PMCID: PMC6533116          DOI: 10.1038/s41586-019-1198-z

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  1 in total

1.  Protection of the intestinal mucosa during ischaemia by intraluminal perfusion.

Authors:  V Mirkovitch; H Menge; J W Robinson
Journal:  Res Exp Med (Berl)       Date:  1975-12-11
  1 in total
  62 in total

1.  An 'on' switch for proteins.

Authors:  Klaus Michael Hahn
Journal:  Nature       Date:  2019-05       Impact factor: 49.962

2.  Clonal dynamics in chronic lymphocytic leukemia.

Authors:  Catherine Gutierrez; Catherine J Wu
Journal:  Blood Adv       Date:  2019-11-26

3.  Quantitative comparison of within-sample heterogeneity scores for DNA methylation data.

Authors:  Michael Scherer; Almut Nebel; Andre Franke; Jörn Walter; Thomas Lengauer; Christoph Bock; Fabian Müller; Markus List
Journal:  Nucleic Acids Res       Date:  2020-05-07       Impact factor: 16.971

4.  Epigenomic State Transitions Characterize Tumor Progression in Mouse Lung Adenocarcinoma.

Authors:  Lindsay M LaFave; Vinay K Kartha; Sai Ma; Kevin Meli; Isabella Del Priore; Caleb Lareau; Santiago Naranjo; Peter M K Westcott; Fabiana M Duarte; Venkat Sankar; Zachary Chiang; Alison Brack; Travis Law; Haley Hauck; Annalisa Okimoto; Aviv Regev; Jason D Buenrostro; Tyler Jacks
Journal:  Cancer Cell       Date:  2020-07-23       Impact factor: 31.743

Review 5.  Clonal dynamics in chronic lymphocytic leukemia.

Authors:  Catherine Gutierrez; Catherine J Wu
Journal:  Hematology Am Soc Hematol Educ Program       Date:  2019-12-06

Review 6.  Advancing Cancer Research and Medicine with Single-Cell Genomics.

Authors:  Bora Lim; Yiyun Lin; Nicholas Navin
Journal:  Cancer Cell       Date:  2020-04-13       Impact factor: 31.743

Review 7.  Targeting cancer epigenetics with CRISPR-dCAS9: Principles and prospects.

Authors:  Mohammad Mijanur Rahman; Trygve O Tollefsbol
Journal:  Methods       Date:  2020-04-18       Impact factor: 3.608

Review 8.  Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics.

Authors:  Anna S Nam; Ronan Chaligne; Dan A Landau
Journal:  Nat Rev Genet       Date:  2020-08-17       Impact factor: 53.242

9.  The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability.

Authors:  Jennifer Derrien; Catherine Guérin-Charbonnel; Victor Gaborit; Loïc Campion; Magali Devic; Elise Douillard; Nathalie Roi; Hervé Avet-Loiseau; Olivier Decaux; Thierry Facon; Jan-Philipp Mallm; Roland Eils; Nikhil C Munshi; Philippe Moreau; Carl Herrmann; Florence Magrangeas; Stéphane Minvielle
Journal:  Genome Med       Date:  2021-08-09       Impact factor: 11.117

10.  Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM.

Authors:  Jerry Fong; Jacob R Gardner; Jared M Andrews; Amanda F Cashen; Jacqueline E Payton; Kilian Q Weinberger; John R Edwards
Journal:  Nucleic Acids Res       Date:  2021-09-20       Impact factor: 16.971

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