Single-Cell ATAC+RNAseq from CD34+ cells of a Primary Myelofibrosis patient evolved to secondary Acute Myeloid Leukemia
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE221946 | GEO | 2024/04/29
REPOSITORIES: GEO
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Project description:Philadelphia chromosome-negative myeloproliferative neoplasms (MPN) consist of primary myelofibrosis (PMF), polycythemia vera (PV), essential thrombocythemia (ET) and seconday myelofibrosis (SMF), comprising post-ET-MF(pET-MF) and post-PV-MF(pPV-MF). In this dataset, we compare the gene expression data of bone marrow or peripheral blood mononuclear cells (BMMCs/PBMCs) of CD34+ cells from MPN patients and healthy donors.
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Project description:Philadelphia chromosome-negative myeloproliferative neoplasms (MPN) consist of primary myelofibrosis (PMF), polycythemia vera (PV), essential thrombocythemia (ET) In this dataset, we compare the gene expression data of patients JAK2V617F vs. CALR-mutated MPN patients.
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Project description:Philadelphia chromosome-negative myeloproliferative neoplasms (MPN) consist of primary myelofibrosis (PMF), polycythemia vera (PV), essential thrombocythemia (ET) and seconday myelofibrosis (pPV-MF or pET-MF) In this dataset, we compare the gene expression data of bone marrow (BM) or peripheral blood (PB) mononuclear cells of CD34+ cells from JAK2V617F mutated patients vs. healthy donors
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Project description:Philadelphia-chromosome negative myeloproliferative neoplasms (MPNs) including polycythemia vera, essential thrombocythemia and primary myelofibrosis show an inherent tendency for transformation into leukemia (MPN-blast phase), which is hypothesized to be accompanied by acquisition of additional genomic lesions. We, therefore, examined chromosomal abnormalities by high-resolution single-nucleotide polymorphism (SNP) array in 88 MPN patients, as well as 71 cases with MPN-blast phase, and correlated these findings with their clinical parameters. Frequent genomic alterations were found in MPN after leukemic transformation with up to 3-fold more genomic changes per sample compared to samples in chronic phase (p<0.001). We identified commonly altered regions involved in disease progression including established targets (ETV6, TP53 and RUNX1), as well as new candidate genes on 7q, 16q, 19p and 21q. Moreover, trisomy 8 or amplification of 8q24 (MYC) was almost exclusively detected in JAK2V617F(-) cases with MPN-blast phase. Remarkably, copy-number neutral-loss of heterozygosity (CNN-LOH) on either 7q or 9p including homozygous JAK2V617F was related to decreased survival after leukemic transformation (p=0.01 and p=0.016, respectively). Our high density SNP-array analysis of MPN genomes in the chronic compared to leukemic stage identified novel target genes and provided prognostic insights associated with the evolution to leukemia. Keywords: SNP-chip To identify oncogenic lesions in MPD, we performed a genome-wide analysis of primary MPD samples using high-density SNP arrays (Affymetrix GeneChip).
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Project description:Ph-negative myeloproliferative neoplasms (MPNs) are characterized by many somatic mutations which have already been shown useful in the prognostic assessment of MPN patients. Moreover, aberrant microRNA (miRNA) expression seems to add to the molecular complexity of MPNs, as specific miRNA signatures capable of discriminating MPN cells from those of normal donors were previously reported. In order to have a comprehensive picture of miRNA deregulation and its relationship with differential gene expression in primary myelofibrosis (PMF) cells, we obtained gene- (GEP) and miRNA expression profiles (miEP) of CD34+ cells from 31 healthy donors and 42 PMF patients using Affymetrix technology (HG-U219 and miRNA 2.0 arrays). Differentially expressed genes (DEG) and miRNAs (DEM) were sorted out by means of Partek Genomic Suite vs 6.6. Since each miRNA can target many mRNAs while a single mRNA can be targeted by multiple miRNAs, we performed Integrative Analysis (IA) by means of Ingenuity Pathway Analysis (IPA) to untangle this combinatorial complexity. In particular, IPA points out DEM-DEG pairs among experimentally validated interactions from TarBase, miRecords and Ingenuity Expert Findings as well as predicted microRNA-mRNA interactions from TargetScan. IPA microRNA Target Filter was then employed to select only the DEM-DEG pairs showing an anti-correlated expression pattern and to build regulatory networks. Finally, 3'UTR luciferase reporter assays were performed to validate IPA predicted miRNA-mRNA interactions. This study allowed the identification of different networks possibly involved in PMF onset and progression, highlighting an aberrant cross-regulation in miRNA-targets involved in malignant hematopoiesis. Furthermore, Integrative analysis was proved a powerful tool to unravel miRNA-mRNA interactions in functional networks, shedding light on the potential contribution of miRNAs to PMF pathogenesis. Gene expression profile (GEP) and miRNA expression profile (miEP) were performed starting from the same totalRNA of CD34+ cells from 42 PMF patients and 31 healthy donors (n=16 PB CD34+, n=15 BM CD34+) (1 replicate for each sample). In particular, GEP and miEP were performed on 23 PMF patients carrying the mutation JAK2V617F and 19 wild-type samples.
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Project description:Primary myelofibrosis (PMF) together with polycythemia vera (PV) and essential thrombocythemia (ET) belongs to the classic Philadelphia-negative myeloproliferative neoplasms (MPNs). PV and ET can evolve to secondary myelofibrosis (SMF) giving rise to post-PV (PPV) and post-ET (PET) myelofibrosis (MF). PMF and SMF patients are currently managed in the same way and prediction of survival is based on the same prognostic models, even if it has been demonstrated that they can’t accurately distinguish different risk categories in SMF. In the last few years interest grew concerning the ability of gene expression profiling (GEP) to provide valuable prognostic information for clinical decision making. To construct a molecular signature that can predict survival according to gene expression we studied GEP of granulocytes from 114 MF patients, including 35 prefibrotic/early PMF (Pre-PMF), 37 overt PMF (Overt-PMF), 26 PET and 16 PPV, using microarray platform.
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Project description:Philadelphia-chromosome negative myeloproliferative neoplasms (MPNs) including polycythemia vera, essential thrombocythemia and primary myelofibrosis show an inherent tendency for transformation into leukemia (MPN-blast phase), which is hypothesized to be accompanied by acquisition of additional genomic lesions. We, therefore, examined chromosomal abnormalities by high-resolution single-nucleotide polymorphism (SNP) array in 88 MPN patients, as well as 71 cases with MPN-blast phase, and correlated these findings with their clinical parameters. Frequent genomic alterations were found in MPN after leukemic transformation with up to 3-fold more genomic changes per sample compared to samples in chronic phase (p<0.001). We identified commonly altered regions involved in disease progression including established targets (ETV6, TP53 and RUNX1), as well as new candidate genes on 7q, 16q, 19p and 21q. Moreover, trisomy 8 or amplification of 8q24 (MYC) was almost exclusively detected in JAK2V617F(-) cases with MPN-blast phase. Remarkably, copy-number neutral-loss of heterozygosity (CNN-LOH) on either 7q or 9p including homozygous JAK2V617F was related to decreased survival after leukemic transformation (p=0.01 and p=0.016, respectively). Our high density SNP-array analysis of MPN genomes in the chronic compared to leukemic stage identified novel target genes and provided prognostic insights associated with the evolution to leukemia. Keywords: SNP-chip
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Project description:Ph-negative myeloproliferative neoplasms (MPNs) are characterized by many somatic mutations which have already been shown useful in the prognostic assessment of MPN patients. Moreover, aberrant microRNA (miRNA) expression seems to add to the molecular complexity of MPNs, as specific miRNA signatures capable of discriminating MPN cells from those of normal donors were previously reported. In order to have a comprehensive picture of miRNA deregulation and its relationship with differential gene expression in primary myelofibrosis (PMF) cells, we obtained gene- (GEP) and miRNA expression profiles (miEP) of CD34+ cells from 31 healthy donors and 42 PMF patients using Affymetrix technology (HG-U219 and miRNA 2.0 arrays). Differentially expressed genes (DEG) and miRNAs (DEM) were sorted out by means of Partek Genomic Suite vs 6.6. Since each miRNA can target many mRNAs while a single mRNA can be targeted by multiple miRNAs, we performed Integrative Analysis (IA) by means of Ingenuity Pathway Analysis (IPA) to untangle this combinatorial complexity. In particular, IPA points out DEM-DEG pairs among experimentally validated interactions from TarBase, miRecords and Ingenuity Expert Findings as well as predicted microRNA-mRNA interactions from TargetScan. IPA microRNA Target Filter was then employed to select only the DEM-DEG pairs showing an anti-correlated expression pattern and to build regulatory networks. Finally, 3'UTR luciferase reporter assays were performed to validate IPA predicted miRNA-mRNA interactions. This study allowed the identification of different networks possibly involved in PMF onset and progression, highlighting an aberrant cross-regulation in miRNA-targets involved in malignant hematopoiesis. Furthermore, Integrative analysis was proved a powerful tool to unravel miRNA-mRNA interactions in functional networks, shedding light on the potential contribution of miRNAs to PMF pathogenesis.
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Project description:Myeloproliferative neoplasms (MPN) are a heterogeneous group of clonal disorders characterized by aberrant hematopoietic proliferation and an intrinsic risk of progression to blast phase. The WHO classification 2022 identifies chronic myeloid leukemia and the BCR::ABL1 negative MPNs polycythemia vera, primary myelofibrosis and essential thrombocythemia as individual entities. However, overlaps, borderline findings or transitions between MPN subtypes occur and incomplete clinical data often complicates diagnosis. By conducting a thorough genetic analysis, we've developed a model that relies on 12 genetic markers to accurately stratify MPN patients. The model can be simplified into a decision tree for routine use. Comparing samples at chronic and blast phase revealed, that one third of patients lost their MPN driver-gene mutation, while mutations in splicing and chromatin modifying genes were stable, indicating a shared founder clone of chronic and blast phase with different driver mutations and therefore different progressing capacities. This was further supported by gain of typical de novo AML gene mutations, accompanied by gain of complex karyotypes and RAS pathway gene mutations. Our data suggest to perform a broader genetic screening at diagnosis and also at clinical progression, as driver mutations may change and the MPN driver mutations present at diagnosis may disappear.
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Project description:An increased number of circulating CD34+ hematopoietic progenitors (HP) and a prominent amplification of dystrophic megakaryocytes (MK) are observed in PMF patients. As transcriptome data from CD34+ hematopoietic progenitors showed modulations of FLT3 and MAP kinase expression independently of the JAK2V617F mutation status
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