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PMID: 24489640 Published · epublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Multidimensional single-cell analysis of BCR signaling reveals proximal activation defect as a hallmark of chronic lymphocytic leukemia B cells.

PloS one ·Vol. 9 ·No. 1 ·2014-00-00 ·页码 e79987

Palomba ML, Piersanti K, Ziegler CG, Decker H, Cotari JW, Bantilan K, Rijo I, Gardner JR, Heaney M, Bemis D, Balderas R, Malek SN, Seymour E, Zelenetz AD, van den Brink MR, Altan-Bonnet G

Abstract

Chronic Lymphocytic Leukemia (CLL) is defined by a perturbed B-cell receptor-mediated signaling machinery. We aimed to model differential signaling behavior between B cells from CLL and healthy individuals to pinpoint modes of dysregulation. We developed an experimental methodology combining immunophenotyping, multiplexed phosphospecific flow cytometry, and multifactorial statistical modeling. Utilizing patterns of signaling network covariance, we modeled BCR signaling in 67 CLL patients using Partial Least Squares Regression (PLSR). Results from multidimensional modeling were validated using an independent test cohort of 38 patients. We identified a dynamic and variable imbalance between proximal (pSYK, pBTK) and distal (pPLCγ2, pBLNK, ppERK) phosphoresponses. PLSR identified the relationship between upstream tyrosine kinase SYK and its target, PLCγ2, as maximally predictive and sufficient to distinguish CLL from healthy samples, pointing to this juncture in the signaling pathway as a hallmark of CLL B cells. Specific BCR pathway signaling signatures that correlate with the disease and its degree of aggressiveness were identified. Heterogeneity in the PLSR response variable within the B cell population is both a characteristic mark of healthy samples and predictive of disease aggressiveness. Single-cell multidimensional analysis of BCR signaling permitted focused analysis of the variability and heterogeneity of signaling behavior from patient-to-patient, and from cell-to-cell. Disruption of the pSYK/pPLCγ2 relationship is uncovered as a robust hallmark of CLL B cell signaling behavior. Together, these observations implicate novel elements of the BCR signal transduction as potential therapeutic targets.

MeSH 主题词
Antibodies, Anti-Idiotypic/pharmacology B-Lymphocytes/drug effects,metabolism,pathology Flow Cytometry Gene Expression Regulation, Leukemic Humans Immunophenotyping Intracellular Signaling Peptides and Proteins/genetics,metabolism Least-Squares Analysis Leukemia, Lymphocytic, Chronic, B-Cell/genetics,metabolism,pathology Lymphocyte Activation/drug effects Models, Statistical Phospholipase C gamma/genetics,metabolism Phosphorylation Protein-Tyrosine Kinases/genetics,metabolism Receptors, Antigen, B-Cell/genetics,metabolism Signal Transduction Single-Cell Analysis Syk Kinase
化学物质
Antibodies, Anti-Idiotypic Intracellular Signaling Peptides and Proteins Receptors, Antigen, B-Cell anti-IgM Protein-Tyrosine Kinases SYK protein, human Syk Kinase Phospholipase C gamma
作者与单位
共 16 位作者,点击展开单位 / ORCID
Palomba M Lia
Division of Hematology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America ; Center Cancer Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Piersanti Kelly
Division of Hematology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America ; Center Cancer Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Ziegler Carly G K
Center Cancer Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America ; Program in Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Decker Hugo
Center Cancer Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America ; Program in Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Cotari Jesse W
Center Cancer Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America ; Program in Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Bantilan Kurt
Division of Hematology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Rijo Ivelise
Division of Hematology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Gardner Jeff R
Division of Hematology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Heaney Mark
Division of Hematology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Bemis Debra
Center Cancer Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America ; Program in Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Balderas Robert
BD Biosciences, San Diego, California, United States of America.
Malek Sami N
Division of Hematology/Oncology, University of Michigan Health System, Ann Harbor, Michigan, United States of America.
Seymour Erlene
Division of Hematology/Oncology, University of Michigan Health System, Ann Harbor, Michigan, United States of America.
Zelenetz Andrew D
Division of Hematology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
van den Brink Marcel R M
Division of Hematology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Altan-Bonnet Grégoire
Center Cancer Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America ; Program in Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Article Info
Journal
PloS one
Abbr.
PLoS One
ISSN
1932-6203
Published
2014-00-00
电子出版
2014-00-29
页码
e79987
Language
English
Country/Region
United States
NLM ID
101285081
基金资助
NHLBI NIH HHS · R01 HL069929 · United States
NCI NIH HHS · R01 CA107096 · United States
NHLBI NIH HHS · R01-HL069929 · United States
NCI NIH HHS · R01-CA107096 · United States
NIAID NIH HHS · R56 AI083408 · United States
NIAID NIH HHS · R01 AI083408 · United States
NIAID NIH HHS · R01-AI080455 · United States
NIAID NIH HHS · R01 AI080455 · United States
NIAID NIH HHS · T32 AI007621 · United States
NCI NIH HHS · U54 CA148967 · United States
NCI NIH HHS · K08 CA118260 · United States
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