Transitions in lineage specification and gene regulatory networks in hematopoietic stem/progenitor cells over human development

Roy, Anindita; Wang, Guanlin; Iskander, Deena; O’Byrne, Sorcha; Elliott, Natalina E.; O’Sullivan, Jennifer; Buck, Gemma; Heuston, Elisabeth F.; Wen, Wei; Rodríguez-Meira, Alba; Hua, Peng; Karadimitris, Anastasios; Mead, Adam J.; Bodine, David M.; Roberts, Irene; Psaila, Bethan; Thongjuea, Supat

doi:10.1016/j.celrep.2021.109698

Cited by 50 publications

(90 citation statements)

References 48 publications

(73 reference statements)

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“…Reads were then aligned to the human genome (hg19) using STAR (version 2.4.2a) and counts for each gene were obtained with FeatureCounts (version 1.4.5-p1; options --primary). Counts were then normalized by dividing each gene count by the total library size of each cell and multiplying this value by the median library size of all cells processed, as implemented in the “ normalize_UMIs ” function from the SingCellaR package 67 (https://github.com/supatt-lab/SingCellaR). A summary of the pre-processing pipeline can be found in https://github.com/albarmeira/TARGET-seq-WTA.…”

Section: Methodsmentioning

confidence: 99%

Deciphering TP53 mutant Cancer Evolution with Single-Cell Multi-Omics

Rodríguez-Meira

Norfo

Wen

et al. 2022

Preprint

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SummaryTP53 is the most commonly mutated gene in human cancer, typically occurring in association with complex cytogenetics and dismal outcomes. Understanding the genetic and non-genetic determinants of TP53-mutation driven clonal evolution and subsequent transformation is a crucial step towards the design of rational therapeutic strategies. Here, we carry out allelic resolution single-cell multi-omic analysis of haematopoietic stem/progenitor cells (HSPC) from patients with a myeloproliferative neoplasm who transform to TP53-mutant secondary acute myeloid leukaemia (AML), a tractable model of TP53-mutant cancer evolution. All patients showed dominant TP53 ‘multi-hit’ HSPC clones at transformation, with a leukaemia stem cell transcriptional signature strongly predictive of adverse outcome in independent cohorts, across both TP53-mutant and wild-type AML. Through analysis of serial samples and antecedent TP53-heterozygous clones, we demonstrate a hitherto unrecognised effect of chronic inflammation, which supressed TP53 wild-type HSPC whilst enhancing the fitness advantage of TP53 mutant cells. Our findings will facilitate the development of risk-stratification, early detection and treatment strategies for TP53-mutant leukaemia, and are of broader relevance to other cancer types.

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Section: Methodsmentioning

confidence: 99%

Deciphering TP53 mutant Cancer Evolution with Single-Cell Multi-Omics

Rodríguez-Meira

Norfo

Wen

et al. 2022

Preprint

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“…Although the phenotype of JMML patients is dominated by the expansion of myeloid cells, there is evidence that also indicates the involvement of other hematopoietic lineages [ 4 , 20 , 132 ]. For this reason, JMML is considered a disease of the HSPC compartment [ 1 , 84 , 133 ]. However, very little is known about the cell hierarchies involved in leukemia progression, the intratumor heterogeneity, the specific identity of the leukemia initiating cells, or the clonal evolution of the disease.…”

Section: Current Challenges and Future Perspectives In Jmml Researchmentioning

confidence: 99%

Genomic and Epigenomic Landscape of Juvenile Myelomonocytic Leukemia

Fiñana

Gómez-Molina

Alonso-Moreno

et al. 2022

Cancers

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Juvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic/myeloproliferative neoplasm of early childhood. Most of JMML patients experience an aggressive clinical course of the disease and require hematopoietic stem cell transplantation, which is currently the only curative treatment. JMML is characterized by RAS signaling hyperactivation, which is mainly driven by mutations in one of five genes of the RAS pathway, including PTPN11, KRAS, NRAS, NF1, and CBL. These driving mutations define different disease subtypes with specific clinico-biological features. Secondary mutations affecting other genes inside and outside the RAS pathway contribute to JMML pathogenesis and are associated with a poorer prognosis. In addition to these genetic alterations, JMML commonly presents aberrant epigenetic profiles that strongly correlate with the clinical outcome of the patients. This observation led to the recent publication of an international JMML stratification consensus, which defines three JMML clinical groups based on DNA methylation status. Although the characterization of the genomic and epigenomic landscapes in JMML has significantly contributed to better understand the molecular mechanisms driving the disease, our knowledge on JMML origin, cell identity, and intratumor and interpatient heterogeneity is still scarce. The application of new single-cell sequencing technologies will be critical to address these questions in the future.

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“…Demultiplexed FASTQ files were aligned to the human reference genome (GRCh38/hg38) using standard CellRanger (version 6.0.1) 'cellranger count' pipeline (10x Genomics). SingCellaR (35) (https://supatt-lab.github.io/SingCellaR.Doc/) was used for the downstream analysis. Data was first subject to quality control with the maximum percentage of mitochondrial genes, maximum detected genes and max number of UMIs set to 12%, 6,000, and 50,000, respectively.…”

Section: Single Cell Rna Sequencing Data Processing and Analysismentioning

confidence: 99%

“…We applied Symphony (39) to map cells from VEGFA+C organoids to published scRNAseq datasets from human bone marrow (36) and fetal liver and bone marrow cells (35,38) respectively.…”

Section: Single Cell Rna Sequencing Data Processing and Analysismentioning

confidence: 99%

Human bone marrow organoids for disease modelling, discovery and validation of therapeutic targets in hematological malignancies

Khan

Colombo

Reyat

et al. 2022

Preprint

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A lack of models that recapitulate the complexity of human bone marrow has hampered mechanistic studies of normal and malignant hematopoiesis and the validation of novel therapies. Here, we describe a step-wise, directed-differentiation protocol in which organoids are generated from iPSCs committed to mesenchymal, endothelial and hematopoietic lineages. These 3-dimensional structures capture key features of human bone marrow - stroma, lumen-forming sinusoidal vessels and myeloid cells including pro-platelet forming megakaryocytes. The organoids supported the engraftment and survival of cells from patients with blood malignancies, including cancer types notoriously difficult to maintain ex vivo. Fibrosis of the organoid occurred following TGFβ ; stimulation and engraftment with myelofibrosis but not healthy donor-derived cells, validating this platform as a powerful tool for studies of malignant cells and their interactions within a human bone marrow-like milieu. This enabling technology is likely to accelerate discovery and prioritization of novel targets for bone marrow disorders and blood cancers.

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Transitions in lineage specification and gene regulatory networks in hematopoietic stem/progenitor cells over human development

Cited by 50 publications

References 48 publications

Deciphering TP53 mutant Cancer Evolution with Single-Cell Multi-Omics

Deciphering TP53 mutant Cancer Evolution with Single-Cell Multi-Omics

Genomic and Epigenomic Landscape of Juvenile Myelomonocytic Leukemia

Human bone marrow organoids for disease modelling, discovery and validation of therapeutic targets in hematological malignancies

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