Ontology highlight
ABSTRACT:
PROVIDER: PRJNA718560 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14107100_1.fastq.gz | Fastqsanger.gz | |||
| SRR14107100_2.fastq.gz | Fastqsanger.gz | |||
| SRR14107101_1.fastq.gz | Fastqsanger.gz | |||
| SRR14107101_2.fastq.gz | Fastqsanger.gz | |||
| SRR14107102_1.fastq.gz | Fastqsanger.gz |
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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>
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Project description:The microarray gene expression pattern was studied using 798 different cancer cell lines. The cancer cell lines are obtained from different centers. Annotation information were provided in the supplementary file. golub-00327 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HT_HG-U133A Organism: Homo sapiens (ncbitax) Tissue Sites: leukemia, Urinary tract, Lung, BiliaryTract, Autonomic Ganglion, Thyroid gland, Stomach, Breast, Pancreas, Head and Neck, Lymphoma, Colorectal, Placenta, Liver, Brain, Bone, pleura, Skin, endometrium, Ovary, cervix, Oesophagus, Connective and Soft Tissue, Muscle, Kidney, Prostate, Adrenal Gland, Eye, Testis, Smooth Muscle Tissue, Vulva, Unknow Material Types: cell, synthetic_RNA, whole_organism, total_RNA, BVG Disease States: M3 acute myeloid leukemia, hairy cell leukemia, transitional cell carcinoma, Adenocarcinoma, B cell lymphoma unspecified, Acute Lymphoblastic Leukemia, blast phase chronic myeloid leukemia, Carcinoma, M6 acute myeloid leukemia, Neuroblastoma, follicular carcinoma, ductal carcinoma, Burkitt Lymphoma, Squamous Cell Carcinoma, M5 acute myeloid leukemia, Mycosis Fungoides and Sezary Syndrome, Acute T-Cell Lymphoblastic Leukemia, Adult T-Cell Leukemia/Lymphoma, M2 Therapy-Related Myeloid Neoplasm, Choriocarcinoma, Plasma Cell Myeloma, Hepatocellular Carcinoma, anaplastic large cell lymphoma, primitive neuroectodermal tumor-medulloblastoma, M4 acute myeloid leukemia, B Acute Lymphoblastic Leukemia, Acute Leukemia of Ambiguous Lineage, Osteosarcoma, Hodgkin Lymphoma, Mesothelioma, chondrosarcoma, Glioblastoma Multiforme, Malignant Melanoma, carcinosarcoma-malignant mesodermal mixed tumor, bronchioloalveolar adenocarcinoma, chronic lymphocytic leukemia-small lymphocytic lymphoma, micropapillary carcinoma, diffuse large B cell lymphoma, myelodysplastic syndrome, giant cell carcinoma, teratoma, multipotential sarcoma, Small Cell Carcinoma, ASTROCYTOMA, Fibrosarcoma, mucoepidermoid carcinoma, Rhabdomyosarcoma, L1 Acute T-Cell Lymphoblastic Leukemia, Glioma, Anaplastic Astrocytoma, Non-small cell carcinoma, Large Cell Carcinoma, mucinous carcinoma, Acute Myeloid Leukemia, malignant fibrous histiocytoma-pleomorphic sarcoma, clear cell carcinoma, B cell lymphoma unspecified, Anaplastic Carcinoma, Ewings sarcoma-peripheral primitive neuroectodermal tumor, undifferentiated carcinoma, Sarcoma, Embryonal Rhabdomyosarcoma, epithelioid sarcoma, renal cell carcinoma, carcinoid-endocrine tumor, Synovial Sarcoma, lymphoid neoplasm, rhabdoid tumor, Refractory Anemia with Excess Blasts, Liposarcoma, biphasic mesothelioma, adrenal cortical carcinoma, adenosquamous carcinoma, L2 Acute T-Cell Lymphoblastic Leukemia, chronic myeloid leukemia, Micropapillary Serous Carcinoma, desmoplastic, acute leukemia, Retinoblastoma, teratocarcinoma, clear cell renal cell carcinoma, Follicular Lymphoma, Wilms Tumor, M7 acute myeloid leukemia, gliosarcoma, embryonal carcinoma, Leiomyosarcoma, medullary carcinoma, granulosa cell tumor, papillary carcinoma, NS Acute Lymphoblastic Leukemia, papillary transitional cell carcinoma, small cell adenocarcinoma, epithelial dysplasia, hyperplasia, tubular adenocarcinoma, metaplasia, papillary ductal carcinoma, chronic eosinophilic leukemia-hypereosinophilic syndrome, #N/A, malignant trichilemmal cyst, Medullary Breast Carcinoma, L2 Acute Lymphoblastic Leukemia, Osteoblastic Osteosarcoma
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Project description:Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate and are primed toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we evaluated HSPCs obtained from young and elderly healthy donors using single-cell RNA sequencing to identify the transcriptional and regulatory perturbations associated with healthy aging at single cell resolution. We then applied this knowledge to identify specific changes associated with the development of myeloid malignancies. Based on the transcriptional profile obtained, we identified changes in the proportions of progenitor compartments during aging, and differences in their functionality, as evidenced by gene set enrichment analysis. Trajectory inference revealed that altered gene expression dynamics accompanied cell differentiation, which could explain age-associated aberrant hematopoiesis. Next, we focused on key regulators of transcription by constructing gene regulatory networks and detected regulons that were specifically active in elderly individuals. Using the previous findings as a reference, we analyzed scRNA-seq data obtained from patients with myelodysplastic syndrome and acute myeloid leukemia and detected an alteration of the expression dynamics of genes involved in erythroid differentiation and identified specific transcription factors deregulated in acute myeloid leukemia. We demonstrate that the combination of single cell technologies and computational tools enables the study of a variety of cellular mechanisms involved in early hematopoiesis and can be used to dissect perturbed differentiation trajectories associated with aging and malignant transformation. Furthermore, the identification of abnormal regulatory mechanisms associated with myeloid malignancies could be exploited for personalized therapeutic approaches in individual patients.
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