Genetic variegation of clonal architecture and stem cells in leukaemia
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE24412 | GEO | 2010/12/16
SECONDARY ACCESSION(S): PRJNA132711
REPOSITORIES: GEO
Similar Datasets
Project description:Little is known of the genetic architecture of cancer at the subclonal and single cell level or in the stem-like cells responsible for cancer clone maintenance and propagation. We have examined this issue in ALL in which ETV6-RUNX1 gene fuson is an early or initiating genetic lesion followed by a modest number of driver copy number alterations. By multiplexing FISH probes for these mutations, up to eight genetic abnormalities can be detected in single cells, a genetic signature of sub-clones identified and a composite picture of sub-clonal architecture and putative ancestral trees assembled. Sub-clones in ALL have variegated genetics and complex, non-linear or branching evolutionary histories. CNA are independently and recurrently acquired in sub-clones of individual patients, and in no preferential order. Clonal architecture is dynamic and changes in the lead up to a diagnosis and in relapse. Leukaemic stem cells, assayed by transplantation in NOD/SCID IL2Rgamma deficient mice, are also genetically variegated, mirroring sub-clonal patterns. These findings have significant implications for the cancer stem cell concept, for interpretation of cancer genome data and for therapeutic targetting in cancer. Mononuclear cells were isolated at diagnosis of ALL for patient #3 and #7. Transplantation of 2 000 - 2 000 000 unsorted leukaemia cells was performed by intra-tibial injection into 7 - 14 week old NOD/SCID IL2Rgamma deficient mice. Mice were sacrificed when peripheral blood engraftment was >2%. An equivalent of 2 000 - 200 000 CD45 cells were used for serial transplantation. DNA was extracted from mononuclear cells at initial diagnosis and after second transplantation. Copy number analysis of Affymetrix 500K SNP arrays was performed in CNAG 3.0 for patients #3 and #7 at initial diagnosis and after second transplantation. Reference files were 9 samples from leukemia in remission.
2010-12-16 | E-GEOD-24412 | biostudies-arrayexpress
Project description:<p>Hematopoietic stem cell (HSC) mutations can result in clonal hematopoiesis (CH) with heterogeneous clinical outcomes. Here, we investigated how the cell state preceding <em>Tet2</em> mutation impacts the pre-malignant phenotype. Using an inducible system for clonal analysis of myeloid progenitors, we found that the epigenetic features of clones at similar differentiation status were highly heterogeneous and functionally responded differently to <em>Tet2</em> mutation. Cell differentiation stage also influenced <em>Tet2</em> mutation response indicating that the cell of origin's epigenome modulates clone-specific behaviors in CH. Molecular features associated with higher risk outcomes include <em>Sox4</em> that sensitized cells to <em>Tet2</em> inactivation, inducing dedifferentiation, altered metabolism and increasing the <em>in vivo</em> clonal output of mutant cells, as confirmed in primary GMP and HSC models. Our findings validate the hypothesis that epigenetic features can predispose specific clones for dominance, explaining why identical genetic mutations can result in different phenotypes.</p>
1970-01-01 | MTBLS9914 | MetaboLights
Project description:Insights into the complex clonal architecture of acute myeloid leukemia (AML) unravelled by deep sequencing technologies have challenged the concept of AML as a hierarchically organised disease initiated and driven by rare self-renewing leukemic stem cells (LSCs). The lack of clone-specific surface markers, however, precludes prospective isolation and functional characterisation of distinct clones. Here, we performed RNA-Sequencing and assessed LSC frequencies for 56 primary AML samples in xenograft assays. We found that G-protein coupled receptor 56 (GPR56) identified the engrafting fraction in CD34positive samples and was associated with most high-risk mutations and poor outcome. Furthermore, variant allele frequency analysis revealed different clonal composition of engrafting GPR56+ versus non-engrafting GPR56- fractions identifying GPR56 as a discriminator of leukemic sub-clones with high and low leukemia initiating capacity. Our data suggest that the NSG-model rather than reproducing the full clonal diversity of the human disease selects for leukemic sub-clones based on their distinct functional properties.
2020-05-01 | GSE68623 | GEO
Project description:The remarkable evolutionary capacity of cancer poses major challenges to current therapeutic efforts, and results from the vast clonal heterogeneity and ability of individual cancer cells to adapt to diverse selective pressures. More complete mechanistic understanding of the basis of therapeutic resistance has been limited by difficulties in coupling information regarding genetic and epigenetic alterations present within individual cells to their respective transcriptomic and functional outputs. To this end, we developed a novel high-complexity expressed barcode system, ClonMapper, that integrates DNA barcoding with single-cell RNA-sequencing and clonal isolation to characterize thousands of clones within a mixed cancer cell population. In applying this system to the chronic lymphocytic leukemia cell line HG3 in the setting of resistance to fludarabine-based chemotherapy, we discover pretreatment sub-populations with distinct expression profiles (i.e. upregulated Wnt, Notch and CXCR4 signaling) that not only confer distinct treatment survivorship trajectories, but also provide the basis for long-term clonal equilibrium between co-existing clones in the absence of treatment. Characterization of individual clones comprising these sub-populations revealed remarkable genetic heterogeneity and the persistence of unique transcriptomic signatures throughout treatment exposure. These data reveal the diverse clonal characteristics and therapeutic responses of a heterogeneous cancer cell population and highlight the unprecedented resolution that can be achieved using ClonMapper.
2021-04-18 | GSE171833 | GEO
Project description:The remarkable evolutionary capacity of cancer poses major challenges to current therapeutic efforts, and results from the vast clonal heterogeneity and ability of individual cancer cells to adapt to diverse selective pressures. More complete mechanistic understanding of the basis of therapeutic resistance has been limited by difficulties in coupling information regarding genetic and epigenetic alterations present within individual cells to their respective transcriptomic and functional outputs. To this end, we developed a novel high-complexity expressed barcode system, ClonMapper, that integrates DNA barcoding with single-cell RNA-sequencing and clonal isolation to characterize thousands of clones within a mixed cancer cell population. In applying this system to the chronic lymphocytic leukemia cell line HG3 in the setting of resistance to fludarabine-based chemotherapy, we discover pretreatment sub-populations with distinct expression profiles (i.e. upregulated Wnt, Notch and CXCR4 signaling) that not only confer distinct treatment survivorship trajectories, but also provide the basis for long-term clonal equilibrium between co-existing clones in the absence of treatment. Characterization of individual clones comprising these sub-populations revealed remarkable genetic heterogeneity and the persistence of unique transcriptomic signatures throughout treatment exposure. These data reveal the diverse clonal characteristics and therapeutic responses of a heterogeneous cancer cell population and highlight the unprecedented resolution that can be achieved using ClonMapper.
2021-04-18 | GSE151569 | GEO
Project description:The remarkable evolutionary capacity of cancer poses major challenges to current therapeutic efforts, and results from the vast clonal heterogeneity and ability of individual cancer cells to adapt to diverse selective pressures. More complete mechanistic understanding of the basis of therapeutic resistance has been limited by difficulties in coupling information regarding genetic and epigenetic alterations present within individual cells to their respective transcriptomic and functional outputs. To this end, we developed a novel high-complexity expressed barcode system, ClonMapper, that integrates DNA barcoding with single-cell RNA-sequencing and clonal isolation to characterize thousands of clones within a mixed cancer cell population. In applying this system to the chronic lymphocytic leukemia cell line HG3 in the setting of resistance to fludarabine-based chemotherapy, we discover pretreatment sub-populations with distinct expression profiles (i.e. upregulated Wnt, Notch and CXCR4 signaling) that not only confer distinct treatment survivorship trajectories, but also provide the basis for long-term clonal equilibrium between co-existing clones in the absence of treatment. Characterization of individual clones comprising these sub-populations revealed remarkable genetic heterogeneity and the persistence of unique transcriptomic signatures throughout treatment exposure. These data reveal the diverse clonal characteristics and therapeutic responses of a heterogeneous cancer cell population and highlight the unprecedented resolution that can be achieved using ClonMapper.
2021-04-18 | GSE151430 | GEO
Project description:The remarkable evolutionary capacity of cancer poses major challenges to current therapeutic efforts, and results from the vast clonal heterogeneity and ability of individual cancer cells to adapt to diverse selective pressures. More complete mechanistic understanding of the basis of therapeutic resistance has been limited by difficulties in coupling information regarding genetic and epigenetic alterations present within individual cells to their respective transcriptomic and functional outputs. To this end, we developed a novel high-complexity expressed barcode system, ClonMapper, that integrates DNA barcoding with single-cell RNA-sequencing and clonal isolation to characterize thousands of clones within a mixed cancer cell population. In applying this system to the chronic lymphocytic leukemia cell line HG3 in the setting of resistance to fludarabine-based chemotherapy, we discover pretreatment sub-populations with distinct expression profiles (i.e. upregulated Wnt, Notch and CXCR4 signaling) that not only confer distinct treatment survivorship trajectories, but also provide the basis for long-term clonal equilibrium between co-existing clones in the absence of treatment. Characterization of individual clones comprising these sub-populations revealed remarkable genetic heterogeneity and the persistence of unique transcriptomic signatures throughout treatment exposure. These data reveal the diverse clonal characteristics and therapeutic responses of a heterogeneous cancer cell population and highlight the unprecedented resolution that can be achieved using ClonMapper.
2021-04-18 | GSE151357 | GEO
Project description:Variegated ripening berries belonging to the Vitis vinifera cultivars cv. ‘Béquignol Noir’
| PRJEB41689 | ENA
Project description:Triple Negative Breast Cancer (TNBC) is an aggressive subtype of breast cancer with high intra-tumoral heterogeneity, frequently resistant to treatment and no known targeted therapy available to improve patient outcomes. It has been hypothesized that the genomic architecture of a TNBC tumour evolves over time, both before, and during therapy, leading to therapy resistance and a high propensity to relapse. Whether this is an inherent property of the tumour or acquired over time is not well characterized. Despite this important clinical implication, limited studies have been carried out to unravel temporal evolution of TNBC over time. Herein, we report an OMICS based analysis of three TNBC patients who were longitudinally sampled during their treatment at different times of relapse. We recruited three TNBC patients at the time of their first relapse who were then followed-up through the course of their treatment. We obtained retrospective samples (tumour samples) from patient tumours at diagnosis (before neo-adjuvant chemotherapy - NACT) at surgery (post NACT) and prospectively sampled them at each subsequent relapse (tumour, blood plasma, and buffy coat) as determined by RECIST criteria. Tumor and buffy coat DNA were subjected to whole exome sequencing (WES) at 200x, and SNP arrays for copy number variation (CNV) analysis. RNA from tumour samples at relapse was subjected to whole transcriptome sequencing. Pathogenic germline BRCA1 variants identified in WES were validated using Sanger sequencing. 1084 somatic mutations identified in whole exome sequencing of all tumour tissues (n=13) from three patients, were subjected to a custom amplicon ultra-deep sequencing assay at 30,000X in their germline DNA (n=3), tumour DNA (n=10), and cfDNA from plasma samples at relapse (n=8). Copy number corrected allele frequencies, tumour ploidy, tumour purity, and ultra-deep sequencing assay derived variant allele frequencies were used to infer clonal and phylogenetic architecture of each patient as it evolved under selective pressure of therapy over time. Clonality analysis incorporating allele fractions from ultra-deep sequencing identified clones comprising of mutations that are present throughout the course of therapy which we term as founding clones and stem mutations respectively. Such founding clones comprising of stem mutations in all 3 patients were present throughout the course of treatment, irrespective of change in treatment modalities. These stem clones included well characterized cancer related genes like PDGFRB & ARID2 (Patient 02), TP53, BRAF & CSF3R (Patient 04) and ESR1, APC, EZH2 & TP53 (Patient 07). Such branching evolution is seen in all three patients wherein the dominant clone (stem clone) acquires additional mutations to form sub-clones, while persisting over time. These sub-clones may be chemo and radio resistant, while also providing for organ specific metastatic potential. Allele fractions of expressed variants inferred from RNA-Seq data co-related with allele fractions from WES data indicating that all somatic.
2022-12-30 | E-MTAB-11909 | biostudies-arrayexpress
Project description:Triple Negative Breast Cancer (TNBC) is an aggressive subtype of breast cancer with high intra-tumoral heterogeneity, frequently resistant to treatment and no known targeted therapy available to improve patient outcomes. It has been hypothesized that the genomic architecture of a TNBC tumour evolves over time, both before, and during therapy, leading to therapy resistance and a high propensity to relapse. Whether this is an inherent property of the tumour or acquired over time is not well characterized. Despite this important clinical implication, limited studies have been carried out to unravel temporal evolution of TNBC over time. Herein, we report an OMICS based analysis of three TNBC patients who were longitudinally sampled during their treatment at different times of relapse. We recruited three TNBC patients at the time of their first relapse who were then followed-up through the course of their treatment. We obtained retrospective samples (tumour samples) from patient tumours at diagnosis (before neo-adjuvant chemotherapy - NACT) at surgery (post NACT) and prospectively sampled them at each subsequent relapse (tumour, blood plasma, and buffy coat) as determined by RECIST criteria. Tumor and buffy coat DNA were subjected to whole exome sequencing (WES) at 200x, and SNP arrays for copy number variation (CNV) analysis. RNA from tumour samples at relapse was subjected to whole transcriptome sequencing. Pathogenic germline BRCA1 variants identified in WES were validated using Sanger sequencing. 1084 somatic mutations identified in whole exome sequencing of all tumour tissues (n=13) from three patients, were subjected to a custom amplicon ultra-deep sequencing assay at 30,000X in their germline DNA (n=3), tumour DNA (n=10), and cfDNA from plasma samples at relapse (n=8). Copy number corrected allele frequencies, tumour ploidy, tumour purity, and ultra-deep sequencing assay derived variant allele frequencies were used to infer clonal and phylogenetic architecture of each patient as it evolved under selective pressure of therapy over time. Clonality analysis incorporating allele fractions from ultra-deep sequencing identified clones comprising of mutations that are present throughout the course of therapy which we term as founding clones and stem mutations respectively. Such founding clones comprising of stem mutations in all 3 patients were present throughout the course of treatment, irrespective of change in treatment modalities. These stem clones included well characterized cancer related genes like PDGFRB & ARID2 (Patient 02), TP53, BRAF & CSF3R (Patient 04) and ESR1, APC, EZH2 & TP53 (Patient 07). Such branching evolution is seen in all three patients wherein the dominant clone (stem clone) acquires additional mutations to form sub-clones, while persisting over time. These sub-clones may be chemo and radio resistant, while also providing for organ specific metastatic potential. Allele fractions of expressed variants inferred from RNA-Seq data co-related with allele fractions from WES data indicating that all somatic.
2023-08-09 | E-MTAB-11375 | biostudies-arrayexpress