Terry Fox Laboratory
Terry Fox Laboratory
Spidlen J.,Terry Fox Laboratory |
Brinkman R.R.,Terry Fox Laboratory |
Roederer M.,U.S. National Institutes of Health |
Chattopadhyay P.K.,U.S. National Institutes of Health
Cytometry Part A | Year: 2016
Modern flow cytometry systems can be coupled to plate readers for high-throughput acquisition. These systems allow hundreds of samples to be analyzed in a single day. Quality control of the data remains challenging, however, and is further complicated when a large number of parameters is measured in an experiment. Our examination of 29,228 publicly available FCS files from laboratories worldwide indicates 13.7% have a fluorescence anomaly. In particular, fluorescence measurements for a sample over the collection time may not remain stable due to fluctuations in fluid dynamics; the impact of instabilities may differ between samples and among parameters. Therefore, we hypothesized that tracking cell populations (which represent a summary of all parameters) in centered log ratio space would provide a sensitive and consistent method of quality control. Here, we present flowClean, an algorithm to track subset frequency changes within a sample during acquisition, and flag time periods with fluorescence perturbations leading to the emergence of false populations. Aberrant time periods are reported as a new parameter and added to a revised data file, allowing users to easily review and exclude those events from further analysis. We apply this method to proof-of-concept datasets and also to a subset of data from a recent vaccine trial. The algorithm flags events that are suspicious by visual inspection, as well as those showing more subtle effects that might not be consistently flagged by investigators reviewing the data manually, and out-performs the current state-of-the-art. flowClean is available as an R package on Bioconductor, as a module on the free-to-use GenePattern web server, and as a plugin for FlowJo X. © 2016 International Society for Advancement of Cytometry.
Courtot M.,Terry Fox Laboratory |
Juty N.,European Bioinformatics Institute |
Knupfer C.,Friedrich - Schiller University of Jena |
Waltemath D.,University of Rostock |
And 27 more authors.
Molecular Systems Biology | Year: 2011
The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments. © 2011 EMBO and Macmillan Publishers Limited.
Flamant S.,Centenary Institute |
Flamant S.,Terry Fox Laboratory |
Flamant S.,French Institute of Health and Medical Research |
Ritchie W.,Centenary Institute |
And 11 more authors.
Haematologica | Year: 2010
Background Micro-RNAs (miRNAs) control gene expression by destabilizing targeted transcripts and inhibiting their translation. Aberrant expression of miRNAs has been described in many human cancers, including chronic myeloid leukemia. Current first-line therapy for newly diagnosed chronic myeloid leukemia is imatinib mesylate, which typically produces a rapid hematologic response. However the effect of imatinib on miRNA expression in vivo has not been thoroughly examined. Design and Methods Using a TaqMan Low-Density Array system, we analyzed miRNA expression in blood samples from newly diagnosed chronic myeloid leukemia patients before and within the first two weeks of imatinib therapy. Quantitative real-time PCR was used to validate imatinib-modulated miRNAs in sequential primary chronic myeloid leukemia samples (n=11, plus 12 additional validation patients). Bioinformatic target gene prediction analysis was performed based on changes in miRNA expression. Results We observed increased expression of miR-150 and miR-146a, and reduced expression of miR-142-3p and miR-199b-5p (3-fold median change) after two weeks of imatinib therapy. A significant correlation (P<0.05) between the Sokal score and pre-treatment miR-142-3p levels was noted. Expression changes in the same miRNAs were consistently found in an additional cohort of chronic myeloid leukemia patients, as compared to healthy subjects. Peripheral blood cells from chronic phase and blast crisis patients displayed a 30-fold lower expression of miR-150 compared to normal samples, which is of particular interest since c-Myb, a known target of miR-150, was recently shown to be necessary for Bcr-Abl-mediated transformation. Conclusions We found that imatinib treatment of chronic myeloid leukemia patients rapidly normalizes the characteristic miRNA expression profile, suggesting that miRNAs may serve as a novel clinically useful biomarker in this disease. © 2010 Ferrata Storti Foundation.
Liu M.,Terry Fox Laboratory |
Liu M.,Chinese Culture University |
Miller C.L.,STEMCELL Technologies |
Eaves C.J.,British Columbia Cancer Agency
Methods in Molecular Biology | Year: 2013
The long-term culture initiating cell (LTC-IC) assay, founded on the bone marrow long-term culture (LTC) system, measures primitive hematopoietic stem cells (termed LTC-IC) based on their capacity to produce myeloid progeny for at least 5 weeks. Adaptations of the LTC system including the use of stromal cell lines, application of limiting dilution analysis, and estimation of average hematopoietic progenitor output per LTC-IC under defined conditions have made it possible to accurately determine LTC-IC content in minimally separated and highly purified cell populations from human hematopoietic tissue sources such as bone marrow, peripheral blood, cord blood, fetal liver as well as cord blood and mobilized peripheral blood. Methodologies for measuring human LTC-IC using bulk cultures, limiting dilution analysis, and single cell cultures are described. © 2013 Springer Science+Business Media, LLC.
PubMed | University of Brighton, Guys and St Thomas Hospital, Brighton and Sussex Medical School, Fred Hutchinson Cancer Research Center and 12 more.
Type: | Journal: Scientific reports | Year: 2016
Standardization of immunophenotyping requires careful attention to reagents, sample handling, instrument setup, and data analysis, and is essential for successful cross-study and cross-center comparison of data. Experts developed five standardized, eight-color panels for identification of major immune cell subsets in peripheral blood. These were produced as pre-configured, lyophilized, reagents in 96-well plates. We present the results of a coordinated analysis of samples across nine laboratories using these panels with standardized operating procedures (SOPs). Manual gating was performed by each site and by a central site. Automated gating algorithms were developed and tested by the FlowCAP consortium. Centralized manual gating can reduce cross-center variability, and we sought to determine whether automated methods could streamline and standardize the analysis. Within-site variability was low in all experiments, but cross-site variability was lower when central analysis was performed in comparison with site-specific analysis. It was also lower for clearly defined cell subsets than those based on dim markers and for rare populations. Automated gating was able to match the performance of central manual analysis for all tested panels, exhibiting little to no bias and comparable variability. Standardized staining, data collection, and automated gating can increase power, reduce variability, and streamline analysis for immunophenotyping.
Finak G.,Fred Hutchinson Cancer Research Center |
Perez J.-M.,Institute Of Recherches Cliniques Of Montreal |
Weng A.,Terry Fox Laboratory |
Gottardo R.,Fred Hutchinson Cancer Research Center
BMC Bioinformatics | Year: 2010
Background: In a high throughput setting, effective flow cytometry data analysis depends heavily on proper data preprocessing. While usual preprocessing steps of quality assessment, outlier removal, normalization, and gating have received considerable scrutiny from the community, the influence of data transformation on the output of high throughput analysis has been largely overlooked. Flow cytometry measurements can vary over several orders of magnitude, cell populations can have variances that depend on their mean fluorescence intensities, and may exhibit heavily-skewed distributions. Consequently, the choice of data transformation can influence the output of automated gating. An appropriate data transformation aids in data visualization and gating of cell populations across the range of data. Experience shows that the choice of transformation is data specific. Our goal here is to compare the performance of different transformations applied to flow cytometry data in the context of automated gating in a high throughput, fully automated setting. We examine the most common transformations used in flow cytometry, including the generalized hyperbolic arcsine, biexponential, linlog, and generalized Box-Cox, all within the BioConductor flowCore framework that is widely used in high throughput, automated flow cytometry data analysis. All of these transformations have adjustable parameters whose effects upon the data are non-intuitive for most users. By making some modelling assumptions about the transformed data, we develop maximum likelihood criteria to optimize parameter choice for these different transformations.Results: We compare the performance of parameter-optimized and default-parameter (in flowCore) data transformations on real and simulated data by measuring the variation in the locations of cell populations across samples, discovered via automated gating in both the scatter and fluorescence channels. We find that parameter-optimized transformations improve visualization, reduce variability in the location of discovered cell populations across samples, and decrease the misclassification (mis-gating) of individual events when compared to default-parameter counterparts.Conclusions: Our results indicate that the preferred transformation for fluorescence channels is a parameter- optimized biexponential or generalized Box-Cox, in accordance with current best practices. Interestingly, for populations in the scatter channels, we find that the optimized hyperbolic arcsine may be a better choice in a high-throughput setting than current standard practice of no transformation. However, generally speaking, the choice of transformation remains data-dependent. We have implemented our algorithm in the BioConductor package, flowTrans, which is publicly available. © 2010 Finak et al; licensee BioMed Central Ltd.
Eaves C.J.,Terry Fox Laboratory |
Eaves C.J.,University of British Columbia
Blood | Year: 2015
Hematopoietic stem cell (HSC) research took hold in the 1950s with the demonstration that intravenously injected bone marrow cells can rescue irradiated mice from lethality by reestablishing blood cell production. Attempts to quantify the cells responsible led to the discovery of serially transplantable, donor-derived, macroscopic, multilineage colonies detectable on the spleen surface 1 to 2 weeks posttransplant. The concept of self-renewing multipotent HSCs was born, but accompanied by perplexing evidence of great variability in the outcomes of HSC self-renewal divisions. The next 60 years saw an explosion in the development and use of more refined tools for assessing the behavior of prospectively purified subsets of hematopoietic cells with blood cell-producing capacity. These developments have led to the formulation of increasingly complex hierarchical models of hematopoiesis and a growing list of intrinsic and extrinsic elements that regulate HSC cycling status, viability, self-renewal, and lineage outputs. More recent examination of these properties in individual, highly purified HSCs and analyses of their perpetuation in clonally generated progeny HSCs have now provided definitive evidence of linearly transmitted heterogeneity in HSC states. These results anticipate the need and use of emerging new technologies to establish models that will accommodate such pluralistic features of HSCs and their control mechanisms. © 2015 by The American Society of Hematology.
Gul-Uludag H.,University of Alberta |
Valencia-Serna J.,University of Alberta |
Kucharski C.,University of Alberta |
Marquez-Curtis L.A.,Center for Innovation Formerly R andD |
And 6 more authors.
Leukemia Research | Year: 2014
The adhesion receptor CD44 plays an important role in the survival and retention of leukemic stem/progenitor cells (LSPC) within the bone marrow (BM) niche, as well as in the high relapse rates of acute myeloid leukemia (AML). Down-regulating CD44 could be clinically relevant not only for suppression of the deregulated function of LSPC but also in LSPC response to chemotherapeutic agents. Small interfering RNA (siRNA) delivery is a promising approach for AML treatment, and we recently reported effective siRNA delivery into difficult-to-transfect AML cell lines using lipid-substituted polyethylenimine/siRNA complexes (polymeric nanoparticles). In this study, we investigated polymeric nanoparticle-mediated silencing of CD44 in CD34+ LSPC cell models (leukemic KG-1 and KG-1a cell lines) as well as primary AML cells. Polymeric nanoparticle-mediated silencing decreased surface CD44 levels in KG-1, KG-1a and primary AML cells by up to 27%, 30% and 20% at day 3, respectively. Moreover, CD44 silencing resulted in induction of apoptosis in KG-1 cells, reduced adhesion of KG-1 and KG-1a cells to hyaluronic acid-coated cell culture plates and BM-MSC, and decreased adhesion of primary AML cells to BM-MSC. Our results suggest that polymeric nanoparticle-mediated silencing of CD44 might be a useful technique for inhibiting LSPC interactions with their microenvironment, thereby prohibiting leukemia progression or sensitizing LSPC to chemotherapy. © 2014 Elsevier Ltd.
Samudio I.,Terry Fox Laboratory |
Konopleva M.,University of Texas
Blood | Year: 2013
In this issue of Blood, Willems et al describe the dependence of acute myeloid leukemia (AML) cells on glutamine for maintaining protein synthesis downstream of mammalian target of rapamycin (mTOR) and show that the enzyme asparaginase can be used to target this dependence. Using various AML cell lines, primary samples, and CD34 stem cells from healthy donors, the authors support the notion that asparaginase may offer a therapeutic benefit in AML-not from its well-known enzymatic activity, but from its "off-target" effects on glutamine levels that result in inhibition of downstream mTOR signaling, inhibition of protein synthesis, and ultimately loss of viability. © 2013 by The American Society of Hematology.
Ahmadi S.,Kurdistan University of Medical Sciences |
Veinotte L.L.,Terry Fox Laboratory
Pakistan Journal of Biological Sciences | Year: 2011
Natural Killer (NK) cells are thought to develop from common lymphoid progenitors in the bone marrow. Even though thymus is not essential for NK cell development, T-cell/natural killer-cell (T/NK) precursors, DN1 (CD44+CD25-) and DN2 (CD44+CD25+) when cultured on an OP9 stroma, give rise to some NK1.1+ cells. Genes of the Schlafen (Slfn) family are involved in hematopoietic and immune processes. The contribution of the Slfn genes in NK cell development from Double Negative (DN) cells is unknown. We transduced DN1 and DN2 progenitors prepared from C57BL/6 (B6) mouse thymus with Schlafen 1 (Slfn1) and Schlafen 2 (Slfn2) genes using Mig retroviral vector containing the Green Fluorescent Protein (GFP) gene and cultured those transduced progenitors on OP9 and OP9 stroma expressing the Notch ligand Delta-like 1 (OP9-DL1) with appropriate cytokines to see if they affect generating NK and T-cells differently. Maturation of both NK and T cells from immature T/NK thymocytes hampered by Slfn1 and Slfn2 transduction but we got a small number of Slfn1 and Slfn2 expressing cells upon culture of transduced DN progenitors on stroma cells. There was no difference between Slfn1 expressing (GFP+) and none expressing T cells regarding CD3 expression but all mature NK cells were from Slfn1 negative population. Slfn2 completely blocked maturation of T cells but there was no difference between Slfn2 expressing and none expressing NK cells. Based on our findings both Slfn1 and Slfn2 interfere with maturation of DN2 progenitors but T cell development is more sensitive to Slfn2 expression than NK cell. © 2011 Asian Network for Scientific Information.