CML Exome Sequencing
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB27083 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR2608890_1.fastq.gz | Fastqsanger.gz | |||
| ERR2608890_2.fastq.gz | Fastqsanger.gz |
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Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
2014-08-12 | GSE60254 | GEO
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing.
2014-08-12 | GSE60168 | GEO
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of mouse squamous cell lung cancer (SCLC) were generated with ENCODER from whole exome sequencing data and compared to results from the NimbleGen array
2014-08-12 | E-GEOD-60254 | biostudies-arrayexpress
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of melanoma PDX sample were generated with ENCODER from whole exome sequencing data and compared to results from the SNP6 platform.
2014-08-12 | E-GEOD-60168 | biostudies-arrayexpress
Project description:Chronic myeloid leukemia (CML) results from hematopoietic stem cell transformation by the BCR-ABL tyrosine kinase. We have shown that the SIRT1 deacetylase is overexpressed in CML LSC, and may contribute to their maintenance. Here, using genetic deletion of SIRT1 in transgenic CML mice, we definitively demonstrate that SIRT1 is required for leukemia development, and reveal its critical role in mediating increased mitochondrial respiration in CML LSC.
2019-08-01 | GSE129158 | GEO
Project description:we demonstrate that conditional deletion of acidic leucine-rich nuclear phosphoprotein 32B (ANP32B) in hematopoietic cells impairs repopulation capacity and postinjury regeneration of HSCs. Mechanistically, ANP32B forms a repressive complex with and thus inhibits the transcriptional activity of p53 in hematopoietic cells, and p53 deletion rescues the functional defect in Anp32b-deficient HSCs. Of great interest, ANP32B is highly expressed in leukemic cells from patients with chronic myelogenous leukemia (CML). Anp32b deletion enhances p53 transcriptional activity to impair LSC function in a murine CML model and exhibits synergistic therapeutic effects with tyrosine kinase inhibitors in inhibiting CML propagation. In summary, our findings provide a novel strategy to enhance p53 activity in LSCs by inhibiting ANP32B and identify ANP32B as a potential therapeutic target in treating CML.
2021-09-27 | GSE184474 | GEO
Project description:Properties of cancer stem cells (CSC) involved in drug-resistance and relapse have significant effect on clinical outcome. Although tyrosine kinase inhibitors (TKIs) have dramatically improved survival of patients with chronic myelogenous leukemia (CML), TKIs have not fully cure CML due to TKI-resistant CML stem cells. Moreover, the relapse after discontinuation of TKIs has not been predicted in CML patients with best TKI-response. In our study, pre-hematoopoietic progenitor cells (pre-HPCs), a model of CML stem cells derived from CML-iPSCs identified a novel antigen of TKI-resistant CML cells. Even in the fraction reported as TKI-sensitive, the antigen+ cells showed TKI-resistance in CML patients. In addition, residual CML cells in patients with optimal TKI-response were concentrated in the antigen+ population.
2016-12-21 | GSE92624 | GEO
Project description:BACKGROUND: BCR-ABL1+ chronic myeloid leukemia (CML) is characterized by abnormal production of leukemic stem (LSC) and progenitor cells and their spread from the bone marrow into the blood resulting in extramedullary myeloproliferation. So far, little is known about specific markers and functions of LSC in CML. METHODS: We examined the phenotype and function of CD34+/CD38─/Lin─ CML LSC by a multi-parameter screen approach employing antibody-phenotyping, mRNA expression profiling, and functional studies, including LSC repopulation experiments in irradiated NOD-SCID-IL-2Rgamma-/- (NSG) mice, followed by marker-validation using diverse control-cohorts and follow-up samples of CML patients treated with imatinib. RESULTS: Of all LSC markers examined, dipeptidylpeptidase IV (DPPIV=CD26) was identified as specific and functionally relevant surface marker-enzyme on CD34+/CD38─ CML LSC. CD26 was not detected on normal CD34+/CD38─ stem cells or LSC in other hematopoietic malignancies. The percentage of CD26+ CML LSC decreased to undetectable levels during successful treatment with imatinib in all patients (p<0.001). Whereas the sorted CD26─ stem cells obtained from CML patients engrafted irradiated NSG mice with multilineage BCR-ABL1-negative hematopoiesis, CD26+ LSC engrafted NSG mice with BCR-ABL1+ cells. Functionally, CD26 was identified as target-enzyme disrupting the SDF-1alpha-CXCR4-axis by cleaving SDF-1alpha a chemotaxin for CXCR4+ stem cells. Whereas CD26 was found to inhibit SDF-1alpha-induced migration, CD26-targeting gliptins reverted this effect and blocked the mobilization of CML LSC in a stroma co-culture assay. CONCLUSIONS: CD26 is a robust biomarker of LSC and a useful tool for their quantification and isolation in patients with BCR/ABL1+ CML. Moreover, CD26 expression may explain the extramedullary spread of LSC in CML. To define specific mRNA expression patterns and to identify specific LSC markers in CML LSC, gene array analyses were performed. RNA was isolated from sorted CD34+/CD45+/CD38─ CML LSC, CD34+/CD45+/CD38+ CML progenitor cells, CML MNC, sorted CD34+/CD38─ cord blood (CB) SC, CB-derived CD34+/CD38+ progenitor cells, and CB MNC. Total RNA was extracted from sorted cells using RNeasy Micro-Kit (Qiagen) and used (100 ng total RNA) for Gene Chip analyses. Preparation of terminal-labeled cRNA, hybridization to genome-wide human PrimeView GeneChips (Affymetrix, Santa Clara, CA, USA) and scanning of arrays were carried out according to the manufacturer's protocols (https://www.affymetrix.com). Robust Multichip Average (RMA) signal extraction and normalization were performed according to http://www.bioconductor.org/ as described.18 Differences in mRNA expression levels (from multiple paired samples) were calculated as mRNA ratio of i) CML LSC versus CB SC, ii) CML LSC versus CD34+/CD38+ CML progenitors, and normal cord blood SC versus cord blood progenitors. To calculate differential gene expression between individual sample groups where appropriate, we performed a statistical comparison using the LIMMA package as described previously. Briefly, LIMMA estimates the fold change between predefined sample groups by fitting a linear model and using an empirical Bayes method to moderate the standard errors of the estimated log-fold changes for each probe set.
2014-04-17 | E-GEOD-40721 | biostudies-arrayexpress
Project description:To investigate why dipeptides accumulate in immature CML cells, we examined upstream gene expression patterns. We isolated the most primitive long-term stem cells, short-term stem cells, and KLS- progenitor cells from healthy littermate control and CML-affected mice and performed gene expression profiling using next-generation RNA-sequencing.
2015-09-18 | GSE70031 | GEO
Project description:BACKGROUND: BCR-ABL1+ chronic myeloid leukemia (CML) is characterized by abnormal production of leukemic stem (LSC) and progenitor cells and their spread from the bone marrow into the blood resulting in extramedullary myeloproliferation. So far, little is known about specific markers and functions of LSC in CML. METHODS: We examined the phenotype and function of CD34+/CD38─/Lin─ CML LSC by a multi-parameter screen approach employing antibody-phenotyping, mRNA expression profiling, and functional studies, including LSC repopulation experiments in irradiated NOD-SCID-IL-2Rgamma-/- (NSG) mice, followed by marker-validation using diverse control-cohorts and follow-up samples of CML patients treated with imatinib. RESULTS: Of all LSC markers examined, dipeptidylpeptidase IV (DPPIV=CD26) was identified as specific and functionally relevant surface marker-enzyme on CD34+/CD38─ CML LSC. CD26 was not detected on normal CD34+/CD38─ stem cells or LSC in other hematopoietic malignancies. The percentage of CD26+ CML LSC decreased to undetectable levels during successful treatment with imatinib in all patients (p<0.001). Whereas the sorted CD26─ stem cells obtained from CML patients engrafted irradiated NSG mice with multilineage BCR-ABL1-negative hematopoiesis, CD26+ LSC engrafted NSG mice with BCR-ABL1+ cells. Functionally, CD26 was identified as target-enzyme disrupting the SDF-1alpha-CXCR4-axis by cleaving SDF-1alpha a chemotaxin for CXCR4+ stem cells. Whereas CD26 was found to inhibit SDF-1alpha-induced migration, CD26-targeting gliptins reverted this effect and blocked the mobilization of CML LSC in a stroma co-culture assay. CONCLUSIONS: CD26 is a robust biomarker of LSC and a useful tool for their quantification and isolation in patients with BCR/ABL1+ CML. Moreover, CD26 expression may explain the extramedullary spread of LSC in CML.
2014-04-17 | GSE40721 | GEO