Dataset Information

Hematopoietic stem cell and progenitor cell mechanisms in myelodysplastic syndromes.

ABSTRACT: Myelodysplastic syndromes (MDS) are a group of disorders characterized by variable cytopenias and ineffective hematopoiesis. Hematopoietic stem cells (HSCs) and myeloid progenitors in MDS have not been extensively characterized. We transplanted purified human HSCs from MDS samples into immunodeficient mice and show that HSCs are the disease-initiating cells in MDS. We identify a recurrent loss of granulocyte-macrophage progenitors (GMPs) in the bone marrow of low risk MDS patients that can distinguish low risk MDS from clinical mimics, thus providing a simple diagnostic tool. The loss of GMPs is likely due to increased apoptosis and increased phagocytosis, the latter due to the up-regulation of cell surface calreticulin, a prophagocytic marker. Blocking calreticulin on low risk MDS myeloid progenitors rescues them from phagocytosis in vitro. However, in the high-risk refractory anemia with excess blasts (RAEB) stages of MDS, the GMP population is increased in frequency compared with normal, and myeloid progenitors evade phagocytosis due to up-regulation of CD47, an antiphagocytic marker. Blocking CD47 leads to the selective phagocytosis of this population. We propose that MDS HSCs compete with normal HSCs in the patients by increasing their frequency at the expense of normal hematopoiesis, that the loss of MDS myeloid progenitors by programmed cell death and programmed cell removal are, in part, responsible for the cytopenias, and that up-regulation of the "don't eat me" signal CD47 on MDS myeloid progenitors is an important transition step leading from low risk MDS to high risk MDS and, possibly, to acute myeloid leukemia.

SUBMITTER: Pang WW

PROVIDER: S-EPMC3581956 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Hematopoietic stem cell and progenitor cell mechanisms in myelodysplastic syndromes.

Pang Wendy W WW Pluvinage John V JV Price Elizabeth A EA Sridhar Kunju K Arber Daniel A DA Greenberg Peter L PL Schrier Stanley L SL Park Christopher Y CY Weissman Irving L IL

Proceedings of the National Academy of Sciences of the United States of America 20130206 8

Myelodysplastic syndromes (MDS) are a group of disorders characterized by variable cytopenias and ineffective hematopoiesis. Hematopoietic stem cells (HSCs) and myeloid progenitors in MDS have not been extensively characterized. We transplanted purified human HSCs from MDS samples into immunodeficient mice and show that HSCs are the disease-initiating cells in MDS. We identify a recurrent loss of granulocyte-macrophage progenitors (GMPs) in the bone marrow of low risk MDS patients that can disti ...[more]

PMID: 23388639

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Project description:Allogeneic hematopoietic stem cell transplantation (HCT) is the only curative treatment for myelodysplastic syndrome (MDS). The proportion of MDS patients referred for transplantation evaluation, those undergoing transplantation, and the reasons for not undergoing transplantation are unknown. In this retrospective analysis, predefined HCT eligibility and indications criteria were applied to 362 unselected patients with newly diagnosed MDS seen by leukemia faculty between 2008 and 2015 at Memorial Sloan Kettering Cancer Center. Two hundred ninety-four patients (81%) were deemed eligible for transplantation and among these, transplantation was considered indicated in 244 (83%). Of these, 158 of 244 (65%) were referred for transplantation evaluation at a median of 3.9 months from diagnosis. Overall 120 of 362 (33%) underwent transplantation at a median of 7.7 months from diagnosis. Metastatic solid-organ malignancy was the major reason for transplantation ineligibility (54%), and death due to MDS, which occurred in 41% of candidates who did not undergo transplantation, was the major reason for not undergoing transplantation. Factors associated with a lower likelihood of referral for transplantation evaluation included age ≥65 (P < .001), ≥2 comorbidities (P = .008), intermediate-1/low risk MDS (P < .001), <5% blasts at diagnosis (overall P < .001), having Medicare/Medicaid health insurance (P < .001), not being married (P = .017), and diagnosis between 2008 and 2011 (P = .035). On multivariate analysis adjusting for all of the previous factors, diagnosis between 2008 and 2011 (P < .001), age ≥65 (P = .001), and <5% blasts at diagnosis (overall P = .031) were associated with a lower likelihood of referral for transplantation evaluation. Factors associated with a lower likelihood of undergoing transplantation included age ≥65 (P < .001), ≥2 comorbidities (P = .003), intermediate-1/low risk MDS (P < .001), <5% blasts (overall P < .001), very low/low/intermediate risk International Prognostic Scoring System-revised karyotype (P = .018), and having Medicare/Medicaid health insurance (P < .001). In multivariate analysis adjusting for all of the previous factors, age ≥65 (P = .021), presence of ≥2 comorbidities (P = .018), and <5% blasts (overall P = .011) were associated with a lower likelihood of undergoing transplantation. The results highlight that transplantation for MDS remains underutilized, particularly for candidates over the age of 65.

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

Hematopoietic stem cell and progenitor cell mechanisms in myelodysplastic syndromes.

Publications

Hematopoietic stem cell and progenitor cell mechanisms in myelodysplastic syndromes.

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