title: In vivo systems analysis identifies spatial and temporal aspects of the modulation of TNF-α-induced apoptosis and proliferation by MAPKs.
abstract: Cellular responses to external stimuli depend on dynamic features of multipathway network signaling; thus, cell behavior is influenced in a complex manner by the environment and by intrinsic properties. Methods of multivariate systems analysis have provided an understanding of these convoluted effects, but only for relatively simplified examples in vitro. To determine whether such approaches could be successfully used in vivo, we analyzed the signaling network that determines the response of intestinal epithelial cells to tumor necrosis factor-α (TNF-α). We built data-driven, partial least-squares discriminant analysis (PLSDA) models based on signaling, apoptotic, and proliferative responses in the mouse small intestinal epithelium after systemic exposure to TNF-α. The extracellular signal-regulated kinase (ERK) signaling axis was a critical modulator of the temporal variation in apoptosis at different doses of TNF-α and of the spatial variation in proliferation in distinct intestinal regions. Inhibition of MEK, a mitogen-activated protein kinase kinase upstream of ERK, altered the signaling network and changed the temporal and spatial phenotypes consistent with model predictions. Our results demonstrate the dynamic, adaptive nature of in vivo signaling networks and identify natural, tissue-level variation in responses that can be deconvoluted only with quantitative, multivariate computational modeling. This study lays a foundation for the use of systems-based approaches to understand how dysregulation of the cellular network state underlies complex diseases.
authors.affiliation: Molecular Pathology Unit, Center for Cancer Research, and Center for Systems Biology, Massachusetts General Hospital, Charlestown, MA 02129, USA.
authors.forename: Ken S
authors.initials: KS
authors.lastname: Lau
authors.forename: Alwin M
authors.initials: AM
authors.lastname: Juchheim
authors.forename: Kimberly R
authors.initials: KR
authors.lastname: Cavaliere
authors.forename: Sarah R
authors.initials: SR
authors.lastname: Philips
authors.forename: Douglas A
authors.initials: DA
authors.lastname: Lauffenburger
authors.forename: Kevin M
authors.initials: KM
authors.lastname: Haigis
mesh_terms: D000818:Animals; D017209:Apoptosis / Q000187:drug effects*; D001549:Benzamides / Q000494:pharmacology; D015153:Blotting, Western; D049109:Cell Proliferation / Q000187:drug effects*; D016000:Cluster Analysis; D004159:Diphenylamine / Q000031:analogs & derivatives / Q000494:pharmacology; D016002:Discriminant Analysis; D004305:Dose-Response Relationship, Drug; D004386:Duodenum / Q000187:drug effects / Q000378:metabolism; D007082:Ileum / Q000187:drug effects / Q000378:metabolism; D016018:Least-Squares Analysis; D020935:MAP Kinase Signaling System / Q000187:drug effects*; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D018345:Mice, Knockout; D019950:Mitogen-Activated Protein Kinase 1 / Q000037:antagonists & inhibitors / Q000378:metabolism; D048052:Mitogen-Activated Protein Kinase 3 / Q000037:antagonists & inhibitors / Q000378:metabolism; D020928:Mitogen-Activated Protein Kinases / Q000037:antagonists & inhibitors / Q000378:metabolism*; D008954:Models, Biological; D010750:Phosphoproteins / Q000378:metabolism; D047888:Receptors, Tumor Necrosis Factor, Type I / Q000235:genetics / Q000378:metabolism; D047889:Receptors, Tumor Necrosis Factor, Type II / Q000235:genetics / Q000378:metabolism; D013997:Time Factors; D014409:Tumor Necrosis Factor-alpha / Q000494:pharmacology*
chemical_list: D001549:Benzamides; D010750:Phosphoproteins; D047888:Receptors, Tumor Necrosis Factor, Type I; D047889:Receptors, Tumor Necrosis Factor, Type II; D014409:Tumor Necrosis Factor-alpha; C506614:mirdametinib; D004159:Diphenylamine; D019950:Mitogen-Activated Protein Kinase 1; D048052:Mitogen-Activated Protein Kinase 3; D020928:Mitogen-Activated Protein Kinases