2012 | OriginalPaper | Chapter
Transcriptome to Reactome Deterministic Modeling: Validation of in Silico Simulations of Transforming Growth Factor-β1 Signaling in MG63 Osteosarcoma Cells, TTR Deterministic Modeling
Authors : Clyde F. Phelix, Bethaney Watson, Richard G. LeBaron, Greg Villareal, Dawnlee Roberson
Published in: Proceedings of the 2011 2nd International Congress on Computer Applications and Computational Science
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Integrated Systems Biology was used to study bone cancer via an iterative process of
in vitro
testing for validation of an
in silico
computer simulation where the transcriptome was used to derive the parameters of a kinetic model. A computer simulation model of the transforming growth factor-beta (TGF-
β
1) signaling pathway was obtained from Reactome®. The transcriptome of MG-63 cells was accessed from NCBI GEO GSE11414. With this method the model is not trained to match the biological system. The
in vitro
study on osteosarcoma (MG-63) cells was used to compare with the results from the computer simulation. MG-63 cells were grown in culture and exposed to TGF-
β
1 to identify differences in expression of a target-gene, TGF-
β
-Induced 68kDa protein (TGFBI), at serial time intervals. Real-time PCR was used to measure TGFBI mRNA levels and the temporal profile was identical with that predicted by the
in silico
model. A sensitivities test was performed through the
in silico
model and a candidate target for gene-knock-down in the TGF-
β
signaling pathway, Smad3, was identified. An 80% reduction of this reactant in the model attenuated TGFBI expression by 64%, an effect that matched such knockdown of Smad3,
in vitro
, for other target genes reported in the literature. The assumption that the transcriptome drives the reactome is validated and substantiates a novel method for deriving parameters for kinetic deterministic models of biological systems.