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  • 1
    In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 488-488
    Abstract: Background: Flow cytometric immuno-phenotyping of lineage-associated antigens is used in the diagnosis of BCP ALL to distinguish neoplastic B-cells. However, the resultant immunophenotypic expression patterns are inadequate to inform prognosis or choice of therapy. Mass cytometry allows for multi-parametric analysis of single cells to distinguish phenotypic and functional features of subpopulations from leukemia samples. Mass cytometric analysis of pediatric Ph+ BCP ALL constructs a novel model of ALL organized along the normal B cell developmental trajectory (Davis et al., Cell 2014). Leukemic cells share phenotypic features with their normal early B cell counterparts. Critical survival and proliferation signaling is also linked to phenotypic state. Further, the developmental state of leukemic populations common among the patients impacts in vitroresponse to inhibition of BCR-ABL kinase signaling. Methods: Mononuclear cells from diagnostic bone marrow samples were obtained from pediatric patients with Philadelphia chromosome positive BCP-ALL under informed consent (n=21) or healthy controls (n=5). Mass cytometry analysis of 40 proteins was performed at baseline state and perturbed state (IL-7, TSLP, anti-m, dasatinib, tofacitinib, BEZ-235) as previously described (Bendall et al., Science 2011). Analysis was restricted to progenitor and blast populations. Healthy bone marrow samples were gated as previously described along the trajectory of developing B cells (Davis et al., Cell2014). These populations were used as the foundation for a classifier in which each leukemia cell was assigned to its nearest healthy population based on a distance metric (Mahalanobis in nine dimensions). Results: Compared to healthy bone marrow controls, and as expected, ALL samples displayed overexpression of early B cell immunophenotypic markers including CD10 (healthy mean counts 3.83 vs. leukemic 283.3, p=0.03), CD34 (6.26 vs. 80.7; p=0.03), and TdT (2.03 vs.18.9; p=0.002). Leukemic cells expressed lower levels of CD45 and IgM compared to healthy developing B cells. Extended phenotyping revealed conserved patterns of protein expression consistent with different developmental stages in B cell development. We have previously identified the precise developmental ordering of human B cell fractions based on the combined expression of CD34, CD38, CD24, TdT (Davis et al., Cell 2014). ALL samples showed increased numbers of cells occupying B cell progenitor compartments compared to healthy bone marrow controls. To formalize this observation, a single-cell classifier was constructed based on the developmental trajectory of healthy B cells. Each leukemic cell was assigned its most related healthy B cell population based on the expression of nine developmental proteins. Across all samples, the size of the pre-proB (CD34+CD38+TdT+) and proB (CD34+CD38+TdT+CD24+) compartments expanded (12% and 33% in ALL vs. 1% and 2% in healthy, respectively) at the expense of progenitor and preB cell compartments. Interestingly, within a given sample, cells may expand within more than one progenitor compartment such that each leukemia had a corrupted, but distinct B cell developmental trajectory. In two diagnosis-relapse pairs, the relapse sample occupied a more mature phenotype compared to its diagnostic partner. Within the developmental compartments, blast cells retained functional features of their healthy counterparts. Blasts within the ProB cell compartment displayed higher basal levels of pSTAT5, pS6, p4EBP1 and pCreb than blasts in other developmental compartments. These cells were more proliferative based on higher mean expression of Ki67. In healthy bone marrow, cells in this developmental state are characterized by ligand-independent STAT5 activation. Indeed the leukemia’s overall level of pSTAT5 correlated with the percentage of cells in the ProB state (R2=0.71). Similarly, in the leukemic samples, patients with a high percentage of cells in this state were less able to respond to inhibition of STAT5 with the tyrosine kinase inhibitor, Dasatinib than cells in other developmental compartments. Conclusions: Deep proteomic profiling of BCP ALL establishes a single-cell classification linking phenotype with functional attributes of leukemic cells. This data demonstrates that leukemic cells are more or less sensitive to therapeutic intervention based on their developmental state. Disclosures Bendall: Fluidigm: Consultancy. Simonds:Fluidigm: Consultancy, Equity Ownership. Nolan:Fluidigm, Inc: Consultancy, Equity Ownership.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2014
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  • 2
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    American Society of Hematology ; 2012
    In:  Blood Vol. 120, No. 21 ( 2012-11-16), p. 1044-1044
    In: Blood, American Society of Hematology, Vol. 120, No. 21 ( 2012-11-16), p. 1044-1044
    Abstract: Abstract 1044 Background: Normal B cell development in the bone marrow (BM) is a seemingly well-understood, progressive process and thus represents a suitable test system in which to apply an algorithmic approach to modeling cellular differentiation. In humans, hematopoietic stem cells form lymphoid progenitor cells that develop into pro- then pre- B cells and finally those cells that escape negative selection become immature B cells that leave the BM for the peripheral immune organs. Flow cytometry can track these stages using the expression of immunophenotypic cell surface markers, including those for progenitors (CD34, CD38), early B cell populations (CD10), as well as those of more mature B cells (CD20, IgM). Expression of the B cell transcription factor PAX5, and immune diversity conferring enzymes terminal deoxynucleotidyl transferase (TdT) and recombination-activating gene (RAG) can also be tracked at the single cell level. Regulatory signaling by factors in the BM orchestrates critical checkpoints in the B cell developmental program, such as Interleukin (IL)-7-mediated STAT5 phosphorylation and signaling downstream the preB cell receptor/B cell receptor (BCR) (p-BLNK, p-Syk, p-PLCγ2, p-Erk). Successful coordination of these signals with immunoglobulin gene rearrangement results in a burst of proliferative expansion prior to maturation/exit to the periphery. Failure of any one of these processes results in B cell deletion while certain dysregulations driven by oncogenic processes can result in malignancy. While much of this core understanding has been founded in murine models, the rarity of early B cell progenitors and lack of genetic tools has complicated definition of B cell development in humans. Using 42 parameter mass cytometry in combination with a novel single-cell trajectory finding algorithm, we have now laid a human B cell developmental process in primary human BM to an unprecedented level of detail, mapping out the expression pattern of virtually all relevant B cell immunophenotypic markers as well as intracellular enzyme, transcription factor and regulatory modification simultaneously, at the single cell level. Methods: The mononuclear cell fraction of multiple healthy human marrows was characterized by simultaneously analyzing 42 antibody parameters with mass cytometry targeting a multitude of phenotypic markers, intracellular signaling molecules, hallmarks of cell cycle and apoptosis all in the context of in vitro perturbations relevant to B cell development (including IL-7 and BCR crosslinking). The resulting multidimensional data was modeled using a novel, scalable, robust graph-based trajectory algorithm that iteratively refines a solution trajectory using random landmarks to reduce variability. Populations of interest were prospectively isolated and a novel qPCR assay was created to quantitate immunoglobulin heavy chain (IgH) rearrangement in genomic DNA. Results/Conclusion: Modeling of the resulting data was undertaken using this algorithm (termed Wanderlust) that devised and ordered cellular relationships based on the average phenotypic progression from our defined starting point, in this case, CD34+CD38- hematopoietic stem cells, in order to calculate a developmental trajectory. The predicted trajectory was then used to inform a traditional 'gating' analysis of the data and provide a higher resolution view of human B cell development than previously published. It both confirmed established steps in human B cell progression, and importantly, revealed new populations of early B cell progenitors based on expression of CD34, CD38, CD24 and TdT. These populations were corroborated to be of B-lineage and ordered as predicted based on the progressive rearrangement of the IgH locus by qPCR of extracted genomic DNA. We aligned previously unregistered key developmental checkpoints such as STAT5 activation in response to IL-7 and proliferation in response preBCR expression with traditional immunophenotypic cell populations. While predicted in silico, and then molecularly verified and staged in vitro, these regulatory events all lay within discrete cell subsets that can now be demarcated using conventional cytometric methods. Together, this provides a backbone on which to further examine both healthy regulatory events as well as the corruption of this developmental process such as in malignant or immunodeficient states. Disclosures: No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2012
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  • 3
    In: Nature Cell Biology, Springer Science and Business Media LLC, Vol. 20, No. 8 ( 2018-8), p. 990-990
    Type of Medium: Online Resource
    ISSN: 1465-7392 , 1476-4679
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2018
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  • 4
    In: Bioconjugate Chemistry, American Chemical Society (ACS), Vol. 26, No. 8 ( 2015-08-19), p. 1590-1596
    Type of Medium: Online Resource
    ISSN: 1043-1802 , 1520-4812
    Language: English
    Publisher: American Chemical Society (ACS)
    Publication Date: 2015
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  • 5
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2022-02-17)
    Abstract: The increasing use of mass cytometry for analyzing clinical samples offers the possibility to perform comparative analyses across public datasets. However, challenges in batch normalization and data integration limit the comparison of datasets not intended to be analyzed together. Here, we present a data integration strategy, CytofIn, using generalized anchors to integrate mass cytometry datasets from the public domain. We show that low-variance controls, such as healthy samples and stable channels, are inherently homogeneous, robust against stimulation, and can serve as generalized anchors for batch correction. Single-cell quantification comparing mass cytometry data from 989 leukemia files pre- and post normalization with CytofIn demonstrates effective batch correction while recapitulating the gold-standard bead normalization. CytofIn integration of public cancer datasets enabled the comparison of immune features across histologies and treatments. We demonstrate the ability to integrate public datasets without necessitating identical control samples or bead standards for fast and robust analysis using CytofIn.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 73, No. 8_Supplement ( 2013-04-15), p. 3178-3178
    Abstract: Acute myeloid leukemia (AML) can present with multiple concurrent subclones at diagnosis. Subclone-specific mutations may confer resistance to molecular-targeted drugs through loss of antigen expression or rewiring of intracellular signaling pathways, leading to relapse. Deep sequencing approaches improve the detection of rare subclones, but the ability to prospectively identify subclones (i.e. without relapse material) is limited, and the effects of subclone-specific mutations on phenotype are poorly understood. In the course of a broader study of oligoclonal pediatric AML patients, we focused investigation on a diagnosis bone marrow sample from a patient harboring 3 presumed subclones (two with distinct NRAS-G12D, NRAS-G13D mutations) as determined by whole-genome sequencing (WGS). We employed a combination of 31-parameter mass cytometry, deep sequencing, FACS sorting, and computational modeling to produce a detailed profile of the subclonal genotypes and phenotypes in this patient. The 3 anticipated subclones did not correlate with a clear subset of surface markers in the mass cytometry analysis. Instead, we observed a single continuous ‘differentiation trajectory’ from progenitor-like to monocyte-like blasts. To dissect this trajectory, 7 distinct myeloid/progenitor subsets were FACS-sorted, plus T/B cells as a non-leukemic control. For each subset we performed capture-based deep sequencing of 307 tumor-specific variants (Tier 1: 13; Tier 2: 33; Tier 3: 261; median depth: 1420x). Shifts in allele frequencies among the FACS-sorted subsets provided critical information to a Bayesian mixture modeling algorithm, allowing identification of 5 subclones, as opposed to the 3 subclones anticipated by WGS. The inferred subclonal genotypes were validated and further refined by targeted single-cell Sanger sequencing of multiple Tier 3 loci. Although all 5 subclones were present throughout the differentiation trajectory, some were enriched in certain phenotypic states or ‘reservoirs’. For example, the NRAS-G12D subclone was enriched in a progenitor-like subset, but its daughter subclone, which harbored an additional mutation in RAC2 (implicated in HSC engraftment), was enriched in the more differentiated subsets, suggesting an opposing effect. Notably, the T/B cell population harbored 2 tumor-specific Tier 1 mutations at & gt;15% allele frequency, suggesting its presence in a preleukemic, multilineage-competent HSC. Taken together, subclone-specific mutations appear to skew cells toward either progenitor or mature phenotypes, but the developmental trajectory enforced by parental mutations is resistant to change. Furthermore, characterization of subclones is possible at diagnosis, and may improve the selection of targeted therapies. *Contributed equally: EFS, SCB & ALG Citation Format: Erin F. Simonds, Sean C. Bendall, Amanda L. Gedman, Jacob H. Levine, Kara L. Davis, Harris G. Fienberg, Astraea Jager, El-ad D. Amir, Ina Radtke, Wendy J. Fantl, Dana Pe'er, James R. Downing, Garry P. Nolan. Deep sequencing of immunophenotypically distinct subsets in acute myeloid leukemia reveals reservoirs of genetically distinct subclones along a conserved differentiation trajectory. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3178. doi:10.1158/1538-7445.AM2013-3178
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2013
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 2693-2693
    Abstract: B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is the most common type of childhood cancer and is characterized by the malignant expansion of B-lymphocyte progenitors in the bone marrow (BM). Current therapy improves the relapse-free survival in children to over 80%. However, the ∼20% of patients who relapse have a poor prognosis and there are no reliable tests that predict relapse using diagnostic samples. We reasoned that aligning BCP-ALL cells according to a formalized context of normal B-lymphocyte development would reveal hidden cell states associated with relapse, and potentially expose targets to augment therapy for patients at risk. Until recently, our ability to pinpoint the identities of B-cell progenitors had been hindered by the vast cellular diversity within the BM and by the scarcity of the primary BM samples. We applied a single-cell proteomics platform termed mass cytometry by time-of-flight (CyTOF). In CyTOF, elemental mass reporter tagged antibodies probe proteins defining cellular identity and signaling within those cells. CyTOF simultaneously quantifies & gt; 40 proteins per cell in millions of individual cells. We defined a cell-state signature for 15 developmental populations of B lymphocytes within the normal human BM. Using this signature we assigned each leukemia cell from 52 primary diagnostic samples to its closest match in B lymphopoiesis using a classifier based on Mahalanobis distance. When applied to BM samples from 4 healthy donors our classifier correctly assigned cells to the true developmental population (accuracy = 0.92, F-measure = 0.92). Using this classifier it was determined that each BCP-ALL sample contains a mix of developmental populations - with 97% of samples enriched in populations that span the pre-pro-B to pre-B transition. We identified 20 predictors (using a machine learning approach) in diagnostic samples that perfectly separate patients who will relapse from those who will not (lasso; predictive AUC = 0.83). This is superior to the NCI risk that is currently employed at clinical diagnosis. These predictors are informative and suggest that high basal activation of IL-7 signaling nodes (pSTAT5, pAKT) in pre-pro-B to pro-BII cells and poor response following pre-B-cell receptor engagement in pre-BI cells portend relapse. As such, these pathways might eventually be targeted via drug repurposing to improve outcomes and to guide therapy in the high-risk childhood BCP-ALL patients identified with our predictor signature. Such an approach to cancer cell developmental classification could be generally applicable across various investigations on understanding and preventing relapse. Citation Format: Zinaida Good, Jolanda Sarno, Astraea Jager, Nikolay Samusik, Wendy Fantl, Nima Aghaeepour, Robert Tibshirani, Sean C. Bendall, Giuseppe Gaipa, Andrea Biondi, Garry P. Nolan, Kara L. Davis. Relapse in BCP-ALL predicted by activated signaling in pro-B cell subsets. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2693.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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  • 8
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 14, No. 1 ( 2023-05-22)
    Abstract: Resistance to glucocorticoids (GC) is associated with an increased risk of relapse in B-cell progenitor acute lymphoblastic leukemia (BCP-ALL). Performing transcriptomic and single-cell proteomic studies in healthy B-cell progenitors, we herein identify coordination between the glucocorticoid receptor pathway with B-cell developmental pathways. Healthy pro-B cells most highly express the glucocorticoid receptor, and this developmental expression is conserved in primary BCP-ALL cells from patients at diagnosis and relapse. In-vitro and in vivo glucocorticoid treatment of primary BCP-ALL cells demonstrate that the interplay between B-cell development and the glucocorticoid pathways is crucial for GC resistance in leukemic cells. Gene set enrichment analysis in BCP-ALL cell lines surviving GC treatment show enrichment of B cell receptor signaling pathways. In addition, primary BCP-ALL cells surviving GC treatment in vitro and in vivo demonstrate a late pre-B cell phenotype with activation of PI3K/mTOR and CREB signaling. Dasatinib, a multi-kinase inhibitor, most effectively targets this active signaling in GC-resistant cells, and when combined with glucocorticoids, results in increased cell death in vitro and decreased leukemic burden and prolonged survival in an in vivo xenograft model. Targeting the active signaling through the addition of dasatinib may represent a therapeutic approach to overcome GC resistance in BCP-ALL.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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  • 9
    In: Cell, Elsevier BV, Vol. 162, No. 1 ( 2015-07), p. 184-197
    Type of Medium: Online Resource
    ISSN: 0092-8674
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2015
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  • 10
    In: Cytometry Part A, Wiley, Vol. 83A, No. 5 ( 2013-05), p. 483-494
    Type of Medium: Online Resource
    ISSN: 1552-4922
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2013
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    SSG: 12
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