ArticleGenome biology2014
Characterizing heterogeneity in leukemic cells using single-cell gene expression analysis.
Article in Genome biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 63 citations in OpenAlex.
- Exploring the Role of Cuproptosis-related Genes in Acute Myeloid Leukemia Through WGCNA, Single-cell Sequencing and Experiments.Current medicinal chemistry · 2026Article
- From Chemotherapy to Targeted Therapy: Unraveling Resistance in Acute Myeloid Leukemia Through Genetic and Non-Genetic Insights.International journal of molecular sciences · 2025Review
- Application and research progress of single cell sequencing technology in leukemia.Frontiers in oncology · 2024Review
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- RNA cytometry of single-cells using semi-permeable microcapsules.Nucleic acids research · 2023Article
- Editorial: Molecular mechanisms regulating phenotypic heterogeneity in human inflammatory diseases.Frontiers in immunology · 2023Article
- Cancer Stem Cells and Epithelial-to-Mesenchymal Transition in Cancer Metastasis.Cold Spring Harbor perspectives in medicine · 2020Review
- Article
- Stem cells in cancer initiation and progression.The Journal of cell biology · 2020Review
- A comparison framework and guideline of clustering methods for mass cytometry data.Genome biology · 2019Article
- [Research progress of single cell sequencing in the diagnosis and treatment of hematological diseases].Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi · 2019Article
- Tumour heterogeneity and metastasis at single-cell resolution.Nature cell biology · 2018Review
- The Human Cell Atlas: Technical approaches and challenges.Briefings in functional genomics · 2018Review
- Novel single-cell technologies in acute myeloid leukemia research.Translational research : the journal of laboratory and clinical medicine · 2017Review
- Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia.Nature medicine · 2017Article
- Challenges and emerging directions in single-cell analysis.Genome biology · 2017Review
- Global preamplification simplifies targeted mRNA quantification.Scientific reports · 2017Article
- Article
- Biologically Relevant Heterogeneity: Metrics and Practical Insights.SLAS discovery : advancing life sciences R & D · 2017Review
- Automation of sample preparation for mass cytometry barcoding in support of clinical research: protocol optimization.Analytical and bioanalytical chemistry · 2017Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundA fundamental challenge for cancer therapy is that each tumor contains a highly heterogeneous cell population whose structure and mechanistic underpinnings remain incompletely understood. Recent advances in single-cell gene expression profiling have created new possibilities to characterize this heterogeneity and to dissect the potential intra-cancer cellular hierarchy.
resultsHere, we apply single-cell analysis to systematically characterize the heterogeneity within leukemic cells using the MLL-AF9 driven mouse model of acute myeloid leukemia. We start with fluorescence-activated cell sorting analysis with seven surface markers, and extend by using a multiplexing quantitative polymerase chain reaction approach to assay the transcriptional profile of a panel of 175 carefully selected genes in leukemic cells at the single-cell level. By employing a set of computational tools we find striking heterogeneity within leukemic cells. Mapping to the normal hematopoietic cellular hierarchy identifies two distinct subtypes of leukemic cells; one similar to granulocyte/monocyte progenitors and the other to macrophage and dendritic cells. Further functional experiments suggest that these subtypes differ in proliferation rates and clonal phenotypes. Finally, co-expression network analysis reveals similarities as well as organizational differences between leukemia and normal granulocyte/monocyte progenitor networks.
conclusionsOverall, our single-cell analysis pinpoints previously uncharacterized heterogeneity within leukemic cells and provides new insights into the molecular signatures of acute myeloid leukemia.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.