Literature DB >> 15350512

Identification of compounds that enhance the anti-lymphoma activity of rituximab using flow cytometric high-content screening.

Maura Gasparetto1, Tracy Gentry, Said Sebti, Erica O'Bryan, Ramadevi Nimmanapalli, Michelle A Blaskovich, Kapil Bhalla, David Rizzieri, Perry Haaland, Jack Dunne, Clay Smith.   

Abstract

In this report, we describe a new flow cytometry technique termed flow cytometric high-content screening (FC-HCS) which involves semi-automated processing and analysis of multiparameter flow cytometry samples. As a first test of the FC-HCS technique, we used it to screen a 2000-compound library, called the National Cancer Institute (NCI) Diversity Set, to identify agents that would enhance the anti-lymphoma activity of the therapeutic monoclonal antibody rituximab. FC-HCS identified 15 compounds from the Diversity Set that significantly enhanced the ability of rituximab to inhibit cell cycle progression and induce apoptosis in lymphoma cells. The validity of the screening results was confirmed for several compounds using additional assays of cell proliferation, apoptosis and cell growth. The FC-HCS technique was relatively simple and reliable and could process up to 1000 samples/day on a single flow cytometer. The FC-HCS technique may be useful for a variety of applications including drug discovery, immunologic monitoring of patients, functional genomics studies and tissue engineering efforts.

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Year:  2004        PMID: 15350512     DOI: 10.1016/j.jim.2004.06.003

Source DB:  PubMed          Journal:  J Immunol Methods        ISSN: 0022-1759            Impact factor:   2.303


  16 in total

1.  Discovery of protein phosphatase 2C inhibitors by virtual screening.

Authors:  Jessica P Rogers; Albert E Beuscher; Marc Flajolet; Thomas McAvoy; Angus C Nairn; Arthur J Olson; Paul Greengard
Journal:  J Med Chem       Date:  2006-03-09       Impact factor: 7.446

2.  Data quality assessment of ungated flow cytometry data in high throughput experiments.

Authors:  Nolwenn Le Meur; Anthony Rossini; Maura Gasparetto; Clay Smith; Ryan R Brinkman; Robert Gentleman
Journal:  Cytometry A       Date:  2007-06       Impact factor: 4.355

3.  flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak finding.

Authors:  Yongchao Ge; Stuart C Sealfon
Journal:  Bioinformatics       Date:  2012-05-17       Impact factor: 6.937

4.  MIFlowCyt: the minimum information about a Flow Cytometry Experiment.

Authors:  Jamie A Lee; Josef Spidlen; Keith Boyce; Jennifer Cai; Nicholas Crosbie; Mark Dalphin; Jeff Furlong; Maura Gasparetto; Michael Goldberg; Elizabeth M Goralczyk; Bill Hyun; Kirstin Jansen; Tobias Kollmann; Megan Kong; Robert Leif; Shannon McWeeney; Thomas D Moloshok; Wayne Moore; Garry Nolan; John Nolan; Janko Nikolich-Zugich; David Parrish; Barclay Purcell; Yu Qian; Biruntha Selvaraj; Clayton Smith; Olga Tchuvatkina; Anne Wertheimer; Peter Wilkinson; Christopher Wilson; James Wood; Robert Zigon; Richard H Scheuermann; Ryan R Brinkman
Journal:  Cytometry A       Date:  2008-10       Impact factor: 4.355

5.  Leukemia Cell Cycle Chemical Profiling Identifies the G2-Phase Leukemia Specific Inhibitor Leusin-1.

Authors:  Xiaoyu Xia; Yu-Chen Lo; Ankur A Gholkar; Silvia Senese; Joseph Y Ong; Erick F Velasquez; Robert Damoiseaux; Jorge Z Torres
Journal:  ACS Chem Biol       Date:  2019-05-08       Impact factor: 5.100

Review 6.  Data standards for flow cytometry.

Authors:  Josef Spidlen; Robert C Gentleman; Perry D Haaland; Morgan Langille; Nolwenn Le Meur; Michael F Ochs; Charles Schmitt; Clayton A Smith; Adam S Treister; Ryan R Brinkman
Journal:  OMICS       Date:  2006

7.  High-content flow cytometry and temporal data analysis for defining a cellular signature of graft-versus-host disease.

Authors:  Ryan Remy Brinkman; Maura Gasparetto; Shang-Jung Jessica Lee; Albert J Ribickas; Janelle Perkins; William Janssen; Renee Smiley; Clay Smith
Journal:  Biol Blood Marrow Transplant       Date:  2007-04-06       Impact factor: 5.742

8.  Gating-ML: XML-based gating descriptions in flow cytometry.

Authors:  Josef Spidlen; Robert C Leif; Wayne Moore; Mario Roederer; Ryan R Brinkman
Journal:  Cytometry A       Date:  2008-12       Impact factor: 4.355

9.  Analysis of High-Throughput Flow Cytometry Data Using plateCore.

Authors:  Errol Strain; Florian Hahne; Ryan R Brinkman; Perry Haaland
Journal:  Adv Bioinformatics       Date:  2009-10-11

10.  The curvHDR method for gating flow cytometry samples.

Authors:  Ulrike Naumann; George Luta; Matthew P Wand
Journal:  BMC Bioinformatics       Date:  2010-01-22       Impact factor: 3.169

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