Dataset Information

Myelodysplastic syndromes are multiclonal diseases derived from hematopoietic stem and progenitor cells.

ABSTRACT: Myelodysplastic syndromes (MDS) are generally considered as a group of clonal diseases derived from hematopoietic stem cells, but a number of studies have suggested that they are derived from myeloid progenitor cells. We aimed to identify the cell of origin in MDS by single-cell analyses. Targeted single-cell RNA sequencing, covering six frequently mutated genes (U2AF1, SF3B1, TET2, ASXL1, TP53, and DNMT3A) in MDS, was developed and performed on individual cells isolated from the CD34⁺ and six lineage populations in the bone marrow of healthy donors (HDs) and patients with MDS. The detected mutations were used as clonal markers to define clones. By dissecting the distribution of clones in six lineages, the clonal origin was determined. We identified three mutations both in HDs and patients with MDS, termed clonal hematopoiesis (CH) mutations. We also identified fifteen mutations only detected in patients with MDS, termed MDS mutations. Clonal analysis showed that CH clones marked by CH mutations and MDS clones marked by MDS mutations were derived from hematopoietic stem cells as well as various hematopoietic progenitor cells. Most patients with MDS showed the chimeric state with CH clones and MDS clones. Clone size analysis suggested that CH mutations may not contribute to clonal expansion of MDS. In conclusion, MDS comprise multiple clones derived from hematopoietic stem and progenitor cells.

SUBMITTER: Luo B

PROVIDER: S-EPMC9109331 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Myelodysplastic syndromes are multiclonal diseases derived from hematopoietic stem and progenitor cells.

Luo Bingqing B Dong Fang F Qin Tiejun T Zhang Qingyun Q Bai Haitao H Wang Jinhong J Jia Yujiao Y Ma Shihui S Jiang Erlie E Cheng Tao T Xiao Zhijian Z Ema Hideo H

Experimental hematology & oncology 20220516 1

Myelodysplastic syndromes (MDS) are generally considered as a group of clonal diseases derived from hematopoietic stem cells, but a number of studies have suggested that they are derived from myeloid progenitor cells. We aimed to identify the cell of origin in MDS by single-cell analyses. Targeted single-cell RNA sequencing, covering six frequently mutated genes (U2AF1, SF3B1, TET2, ASXL1, TP53, and DNMT3A) in MDS, was developed and performed on individual cells isolated from the CD34<sup>+</sup ...[more]

PMID: 35578364

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Project description:ObjectiveThis study aims to investigate and analyze the differentially expressed genes (DEGs) in CD34 + hematopoietic stem cells (HSCs) from patients with myelodysplastic syndromes (MDS) through bioinformatics analysis, with the ultimate goal of uncovering the potential molecular mechanisms underlying pathogenesis of MDS. The findings of this study are expected to provide novel insights into clinical treatment strategies for MDS.MethodsInitially, we downloaded three datasets, GSE81173, GSE4619, and GSE58831, from the public Gene Expression Omnibus (GEO) database as our training sets, and selected the GSE19429 dataset as the validation set. To ensure data consistency and comparability, we standardized the training sets and removed batch effects using the ComBat algorithm, thereby integrating them into a unified gene expression dataset. Subsequently, we conducted differential expression analysis to identify genes with significant changes in expression levels across different disease states. In order to enhance prediction accuracy, we incorporated six common predictive models and trained them based on the filtered differential gene expression dataset. After comprehensive evaluation, we ultimately selected three algorithms-Lasso regression, random forest, and support vector machine (SVM)-as our core predictive models. To more precisely pinpoint genes closely related to disease characteristics, we utilized the aforementioned three machine learning methods for prediction and took the intersection of these prediction results, yielding a more robust list of genes associated with disease features. Following this, we conducted in-depth analysis of these key genes in the training set and validated the results independently using the GSE19429 dataset. Furthermore, we performed differential analysis of gene groups, co-expression analysis, and enrichment analysis to delve deeper into the mechanisms underlying the roles of these genes in disease initiation and progression. Through these analyses, we aim to provide new insights and foundations for disease diagnosis and treatment. Figure illustrates the data preprocessing and analysis workflow of this study.ResultsOur analysis of differentially expressed genes (DEGs) in CD34+ hematopoietic stem cells (HSCs) from patients with myelodysplastic syndromes (MDS) revealed significant differences in gene expression patterns compared to the control group (individuals without MDS). Specifically, the expression levels of two key genes, IRF4 and ELANE, were notably downregulated in CD34+ HSCs of MDS patients, indicating their downregulatory roles in the pathological process of MDS.ConclusionThis study sheds light on the potential molecular mechanisms underlying MDS, with a particular focus on the pivotal roles of IRF4 and ELANE as key pathogenic genes. Our findings provide a novel perspective for understanding the complexity of MDS and exploring therapeutic strategies. They may also guide the development of precise and effective treatments, such as targeted interventions directed against these genes.

Dataset Information

Myelodysplastic syndromes are multiclonal diseases derived from hematopoietic stem and progenitor cells.

Publications

Myelodysplastic syndromes are multiclonal diseases derived from hematopoietic stem and progenitor cells.

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