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  • 1
    Publication Date: 2014-10-25
    Description: Cellular circuits sense the environment, process signals, and compute decisions using networks of interacting proteins. To model such a system, the abundance of each activated protein species can be described as a stochastic function of the abundance of other proteins. High-dimensional single-cell technologies, such as mass cytometry, offer an opportunity to characterize signaling circuit-wide. However, the challenge of developing and applying computational approaches to interpret such complex data remains. Here, we developed computational methods, based on established statistical concepts, to characterize signaling network relationships by quantifying the strengths of network edges and deriving signaling response functions. In comparing signaling between naive and antigen-exposed CD4(+) T lymphocytes, we find that although these two cell subtypes had similarly wired networks, naive cells transmitted more information along a key signaling cascade than did antigen-exposed cells. We validated our characterization on mice lacking the extracellular-regulated mitogen-activated protein kinase (MAPK) ERK2, which showed stronger influence of pERK on pS6 (phosphorylated-ribosomal protein S6), in naive cells as compared with antigen-exposed cells, as predicted. We demonstrate that by using cell-to-cell variation inherent in single-cell data, we can derive response functions underlying molecular circuits and drive the understanding of how cells process signals.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4334155/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4334155/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Krishnaswamy, Smita -- Spitzer, Matthew H -- Mingueneau, Michael -- Bendall, Sean C -- Litvin, Oren -- Stone, Erica -- Pe'er, Dana -- Nolan, Garry P -- 1K01DK095008/DK/NIDDK NIH HHS/ -- 1R01CA130826/CA/NCI NIH HHS/ -- 1U54CA121852-01A1/CA/NCI NIH HHS/ -- CA 09-011/CA/NCI NIH HHS/ -- HHSN268201000034C/HV/NHLBI NIH HHS/ -- HHSN272200700038C/PHS HHS/ -- HV-10-05/HV/NHLBI NIH HHS/ -- K01 DK095008/DK/NIDDK NIH HHS/ -- P01 CA034233/CA/NCI NIH HHS/ -- R00 GM104148/GM/NIGMS NIH HHS/ -- R01 CA130826/CA/NCI NIH HHS/ -- S10RR027582-01/RR/NCRR NIH HHS/ -- U19 AI057229/AI/NIAID NIH HHS/ -- U19 AI100627/AI/NIAID NIH HHS/ -- U54 CA149145/CA/NCI NIH HHS/ -- New York, N.Y. -- Science. 2014 Nov 28;346(6213):1250689. doi: 10.1126/science.1250689. Epub 2014 Oct 23.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Biological Sciences, Department of Systems Biology, Columbia University, New York, NY, USA. ; Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA. ; Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA, USA. ; Molecular Biology Section, Division of Biological Sciences, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA. ; Department of Biological Sciences, Department of Systems Biology, Columbia University, New York, NY, USA. dpeer@biology.columbia.edu.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25342659" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; CD4-Positive T-Lymphocytes/*immunology ; Computer Simulation ; Image Cytometry ; Male ; Mice ; Mice, Mutant Strains ; Mitogen-Activated Protein Kinase 1/genetics ; Receptors, Antigen, T-Cell/*metabolism ; Ribosomal Protein S6/metabolism ; Signal Transduction ; Single-Cell Analysis/*methods ; Systems Biology/*methods ; eIF-2 Kinase/metabolism
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2011-05-10
    Description: Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell "mass cytometry" to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3273988/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3273988/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Bendall, Sean C -- Simonds, Erin F -- Qiu, Peng -- Amir, El-ad D -- Krutzik, Peter O -- Finck, Rachel -- Bruggner, Robert V -- Melamed, Rachel -- Trejo, Angelica -- Ornatsky, Olga I -- Balderas, Robert S -- Plevritis, Sylvia K -- Sachs, Karen -- Pe'er, Dana -- Tanner, Scott D -- Nolan, Garry P -- 1R01CA130826/CA/NCI NIH HHS/ -- 272200700038C/PHS HHS/ -- 5U54 CA143907/CA/NCI NIH HHS/ -- HHSN268201000034C/HV/NHLBI NIH HHS/ -- N0I-HV-00242/HV/NHLBI NIH HHS/ -- P01 CA034233/CA/NCI NIH HHS/ -- PN2 EY018228/EY/NEI NIH HHS/ -- R01 CA130826/CA/NCI NIH HHS/ -- R01 CA130826-04/CA/NCI NIH HHS/ -- RB2-01592/PHS HHS/ -- U19 AI057229/AI/NIAID NIH HHS/ -- U54 CA149145/CA/NCI NIH HHS/ -- New York, N.Y. -- Science. 2011 May 6;332(6030):687-96. doi: 10.1126/science.1198704.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/21551058" target="_blank"〉PubMed〈/a〉
    Keywords: Algorithms ; Antibodies ; Antigens, Surface/analysis ; B-Lymphocytes/drug effects/immunology/metabolism ; Bone Marrow Cells/cytology/*drug effects/*immunology/metabolism ; Cytokines/metabolism ; Dasatinib ; Flow Cytometry/*methods ; Hematopoiesis ; Humans ; Immunophenotyping ; Lanthanoid Series Elements ; Leukocytes, Mononuclear/drug effects/immunology/metabolism ; Lymphocyte Activation ; Lymphocyte Subsets/*drug effects/*immunology/metabolism ; Mass Spectrometry ; Phosphorylation ; Protein Kinase Inhibitors/pharmacology ; Protein-Tyrosine Kinases/antagonists & inhibitors ; Pyrimidines/*pharmacology ; *Signal Transduction/drug effects ; Single-Cell Analysis/*methods ; T-Lymphocytes/drug effects/immunology/metabolism ; Thiazoles/*pharmacology ; Transition Elements
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 3
    Keywords: RNA ; PATIENT ; TISSUES ; BREAST-CANCER ; IN-SITU ; resistance ; EVOLUTION ; SINGLE CELLS ; INTRATUMOR HETEROGENEITY ; CHALLENGE
    Abstract: The extent of tumor heterogeneity is an emerging theme that researchers are only beginning to understand. How genetic and epigenetic heterogeneity affects tumor evolution and clinical progression is unknown. The precise nature of the environmental factors that influence this heterogeneity is also yet to be characterized. Nature Medicine, Nature Biotechnology and the Volkswagen Foundation organized a meeting focused on identifying the obstacles that need to be overcome to advance translational research in and tumor heterogeneity. Once these key questions were established, the attendees devised potential solutions. Their ideas are presented here.
    Type of Publication: Journal article published
    PubMed ID: 26248267
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