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Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE120446 | GEO | 2018/09/26

REPOSITORIES: GEO

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Human bone marrow assessment by single-cell RNA sequencing, mass cytometry, and flow cytometry.

Project description:New techniques for single-cell analysis have led to insights into hematopoiesis and the immune system, but the ability of these techniques to cross-validate and reproducibly identify the biological variation in diverse human samples is currently unproven. We therefore performed a comprehensive assessment of human bone marrow cells using both single-cell RNA sequencing and multiparameter flow cytometry from 20 healthy adult human donors across a broad age range. These data characterize variation between healthy donors as well as age-associated changes in cell population frequencies. Direct comparison of techniques revealed discrepancy in the quantification of T lymphocyte and natural killer cell populations. Orthogonal validation of immunophenotyping using mass cytometry demonstrated a strong correlation with flow cytometry. Technical replicates using single-cell RNA sequencing matched robustly, while biological replicates showed variation. Given the increasing use of single-cell technologies in translational research, this resource serves as an important reference data set and highlights opportunities for further refinement.

| S-EPMC6328018 | biostudies-literature

Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry [bulk]

Project description:Bulk RNA Sequencing of Healthy Bone Marrow Mononuclear Cells

2018-09-26 | GSE120444 | GEO

Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry [scRNA]

Project description:New techniques for single-cell analysis have led to insights into hematopoiesis and the immune system, but the ability of these techniques to cross-validate and reproducibly identify the biological variation in diverse human samples is currently unproven. We therefore performed a comprehensive assessment of human bone marrow cells using both single-cell RNA sequencing and multiparameter flow cytometry from twenty healthy adult human donors across a broad age range. These data characterize variation between healthy donors as well as age-associated changes in cell population frequencies. Direct comparison of techniques revealed discrepancy in the quantification of T lymphocyte and natural killer cell populations. Orthogonal validation of immunophenotyping using mass cytometry demonstrated good correlation with flow cytometry. Technical replicates using single-cell RNA sequencing matched robustly, while biological replicates showed variation. Given the increasing use of single-cell technologies in translational research, this resource serves as an important reference dataset and highlights opportunities for further refinement. [Funding source] Project Number: 1ZIAHL006163-05 Contact PI / Project Leader: HOURIGAN, CHRISTOPHER Title: DETECTION, PREVENTION AND TREATMENT OF ACUTE MYELOID LEUKEMIA (AML) RELAPSE. Awardee Organization: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE

2018-09-21 | GSE120221 | GEO

Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry

Project description:Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry

| PRJNA493078 | ENA

Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry [bulk]

Project description:Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry [bulk]

| PRJNA493081 | ENA

Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry [scRNA]

Project description:Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry [scRNA]

| PRJNA492227 | ENA

Ten Color Multiparameter Flow Cytometry in Bone Marrow and Apheresis Products for Assessment and Outcome Prediction in Multiple Myeloma Patients.

Project description:ObjectiveIn clinical trials (CTs), the assessment of minimal residual disease (MRD) has proven to have prognostic value for multiple myeloma (MM) patients. Multiparameter flow cytometry (MFC) and next-generation sequencing are currently used in CTs as effective tools for outcome prediction. We have previously described 6- and 8-color MFC panels with and without kappa/lambda, which were equally reliable in detecting aberrant plasma cells (aPC) in myeloma bone marrow (BM) specimens. This follow-up study a) established a highly sensitive single-tube 10-color MFC panel for MRD detection in myeloma samples carrying different disease burden (monoclonal gammopathy of unknown significance (MGUS), smoldering multiple myeloma (SMM), MM), b) evaluated additional, rarely used markers included in this panel, and c) assessed MRD levels and the predictive value in apheresis vs. BM samples of MM patients undergoing autologous stem cell transplantation (ASCT).Methods + resultsThe 10-color MFC was performed in BM and apheresis samples of 128 MM and pre-MM (MGUS/SMM) patients. The markers CD28, CD200, CD19, and CD117 underwent closer examination. The analysis revealed distinct differences in these antigens between MM, MGUS/SMM, and patients under treatment. In apheresis samples, the 10-color panel determined MRD negativity in 44% of patients. Absence of aPC in apheresis corresponded with disease burden, cytogenetics, and response to induction. It also determined MRD negativity in BM samples after ASCT and was associated with improved progression-free survival.ConclusionThese results highlight the significance of the evaluation of both BM and apheresis samples with a novel highly sensitive 10-color MFC panel.

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Multiparameter flow cytometry quantification of bone marrow plasma cells at diagnosis provides more prognostic information than morphological assessment in myeloma patients.

Project description:Quantification of bone marrow plasma cells in multiple myeloma patients using conventional morphology is of limited prognostic value, while the merit of multiparameter flow cytometry immunophenotyping is still considered unproven. Here we compare the bone marrow plasma cell counts obtained by morphology and multiparameter flow cytometry and explore the potential prognostic impact of both techniques in 765 newly diagnosed, uniformly treated multiple myeloma patients. Although multiparameter flow cytometry generally yields lower plasma cell counts (median percentage of 11% vs. 40%, respectively; p<0.001), there is a significant positive correlation between the two techniques (R =0.46, p<0.001). Regarding prognosis, multivariate analysis selected the bone marrow plasma cell counts obtained by multiparameter flow cytometry as an independent prognostic factor for overall survival (p=0.007), supporting the incorporation of multiparameter flow cytometry immunophenotyping into the routine diagnostic evaluation of multiple myeloma patients and validating the clinical utility of bone marrow plasma cell counting by multiparameter flow cytometry approaches. (clinicaltrials.gov identifier: NCT00560053).

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RNA sequencing of bone marrow

Project description:This SuperSeries is composed of the SubSeries listed below.

2024-06-19 | GSE236768 | GEO

Isolation of human bone marrow stromal cells from bone marrow biopsies for single-cell RNA sequencing.

Project description:Bone marrow (BM) mesenchymal stromal cells play an important role in regulating stem cell quiescence and homeostasis; they are also key contributors to various hematological malignancies. However, human bone marrow stromal cells are difficult to isolate and prone to damage during isolation. This protocol describes a combination of mechanical and enzymatic isolation of BM stromal cells from human BM biopsies, followed by FACS sorting to separate stromal sub-populations including mesenchymal stromal cells, fibroblasts, and Schwann cells for single-cell RNA sequencing. For complete details on the use and execution of this protocol, please refer to Leimkühler et al. (2020).

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