title: Construction of a computable cell proliferation network focused on non-diseased lung cells.
abstract: BACKGROUND
  Critical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work.
  
  
  RESULTS
  To further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data.
  
  
  CONCLUSIONS
  To the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.
authors: Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000 Neuchâtel, Switzerland.
authors: Jurjen W
authors: JW
authors: Westra
authors: Walter K
authors: WK
authors: Schlage
authors: Brian P
authors: BP
authors: Frushour
authors: Stephan
authors: S
authors: Gebel
authors: Natalie L
authors: NL
authors: Catlett
authors: Wanjiang
authors: W
authors: Han
authors: Sean F
authors: SF
authors: Eddy
authors: Arnd
authors: A
authors: Hengstermann
authors: Andrea L
authors: AL
authors: Matthews
authors: Carole
authors: C
authors: Mathis
authors: Rosemarie B
authors: RB
authors: Lichtner
authors: Carine
authors: C
authors: Poussin
authors: Marja
authors: M
authors: Talikka
authors: Emilija
authors: E
authors: Veljkovic
authors: Aaron A
authors: AA
authors: Van Hooser
authors: Benjamin
authors: B
authors: Wong
authors: Michael J
authors: MJ
authors: Maria
authors: Manuel C
authors: MC
authors: Peitsch
authors: Renee
authors: R
authors: Deehan
authors: Julia
authors: J
authors: Hoeng
mesh_terms: D000818:Animals; D049109:Cell Proliferation; D044127:Epigenesis, Genetic; D008168:Lung / Q000166:cytology*; D008322:Mammals; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*; D049490:Systems Biology / Q000379:methods*