Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia

Identifying the causes of human diseases requires deconvolution of abnormal molecular phenotypes spanning DNA accessibility, gene expression and protein abundance . We present a single-cell framework that integrates highly multiplexed protein quantification, transcriptome profiling and analysis of c...

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Bibliographic Details
Published in:Nature biotechnology Vol. 37; no. 12; pp. 1458 - 1465
Main Authors: Granja, Jeffrey M, Klemm, Sandy, McGinnis, Lisa M, Kathiria, Arwa S, Mezger, Anja, Corces, M Ryan, Parks, Benjamin, Gars, Eric, Liedtke, Michaela, Zheng, Grace X Y, Chang, Howard Y, Majeti, Ravindra, Greenleaf, William J
Format: Journal Article
Language:English
Published: United States Nature Publishing Group 01.12.2019
Subjects:
Accessibility
Blood
Bone Marrow Cells - cytology
CD69 antigen
Chromatin
Chromatin - chemistry
Chromatin - genetics
Cluster Analysis
Core Binding Factor Alpha 2 Subunit - genetics
Deoxyribonucleic acid
DNA
Epigenesis, Genetic - genetics
Epigenetics
Epigenomics - methods
Gene expression
Gene Expression Profiling - methods
Gene Expression Regulation, Neoplastic - genetics
Gene mapping
Heterogeneity
Humans
Leukemia
Leukemia, Biphenotypic, Acute - genetics
Molecular modelling
Patients
Phenotypes
Proteins
Regulatory sequences
Regulatory Sequences, Nucleic Acid - genetics
Runx1 protein
Single-Cell Analysis - methods
Transcription factors
Transcriptome - genetics
ISSN:1087-0156, 1546-1696, 1546-1696
Online Access:Get full text
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Summary:Identifying the causes of human diseases requires deconvolution of abnormal molecular phenotypes spanning DNA accessibility, gene expression and protein abundance . We present a single-cell framework that integrates highly multiplexed protein quantification, transcriptome profiling and analysis of chromatin accessibility. Using this approach, we establish a normal epigenetic baseline for healthy blood development, which we then use to deconvolve aberrant molecular features within blood from patients with mixed-phenotype acute leukemia . Despite widespread epigenetic heterogeneity within the patient cohort, we observe common malignant signatures across patients as well as patient-specific regulatory features that are shared across phenotypic compartments of individual patients. Integrative analysis of transcriptomic and chromatin-accessibility maps identified 91,601 putative peak-to-gene linkages and transcription factors that regulate leukemia-specific genes, such as RUNX1-linked regulatory elements proximal to the marker gene CD69. These results demonstrate how integrative, multiomic analysis of single cells within the framework of normal development can reveal both distinct and shared molecular mechanisms of disease from patient samples.
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ISSN:1087-0156
1546-1696
1546-1696
DOI:10.1038/s41587-019-0332-7