TY - CHAP
T1 - A quantitative integrated systems biology approach for modeling cell cycle pathways in normal and tumor cells
AU - Tummala, Hemanth
AU - Khalil, Hilal S.
AU - Goszcz, Katarzyna
AU - Tupone, Maria Grazia
AU - Stoyanova, Viii
AU - Nikolova, Ekaterina
AU - Mitev, Vanio
AU - Zhelev, Nikolai
N1 - ©2012 American Association for Cancer Research
PY - 2012/4/15
Y1 - 2012/4/15
N2 - We have developed a novel biological system for quantitative analysis of biochemical pathways in normal and tumour human cells. The system is based on cells growing in tissue culture media where the concentrations of growth factors, hormones and other components of the media are precisely defined and continuously monitored. Quantitative immunoblotting and luminescence-based reporter assays are then used to measure the cellular concentration of key cell cycle regulatory proteins and their activity in real time in live cells. This technology resulted in accurate measurement of cellular concentration of a number of key cell cycle regulatory proteins such as Cyclins, CDKs and CDK inhibitors during the cell cycle. The data are being utilized in the development of a quantitative integrated systems biology approach to the cell cycle. The approach consists of a comprehensive network of the molecular interaction pathways regulating cell cycle in normal and tumor cells and a model which incorporates the activity of key molecular species in a single dynamical system which can be solved using genetic algorithms designed to match experimental data, both qualitative and quantitative, to the model kinetics. The model could be utilized for the development of new drug targets and would be capable of consistently measuring the effects of existing drugs (either single or in combination) and opens up a methodology for establishing the effectiveness of these drugs with clear implications for cost/benefit assessment. Major impact is expected on clinical research where the model can be a tool in determining intervention strategies in the molecular pathways concerned. Apart from the development of new drug targets the model will be capable of consistently measuring the effects of existing drugs (either single or in combination) and opens up a methodology for establishing the effectiveness of anti-cancer drugs.
AB - We have developed a novel biological system for quantitative analysis of biochemical pathways in normal and tumour human cells. The system is based on cells growing in tissue culture media where the concentrations of growth factors, hormones and other components of the media are precisely defined and continuously monitored. Quantitative immunoblotting and luminescence-based reporter assays are then used to measure the cellular concentration of key cell cycle regulatory proteins and their activity in real time in live cells. This technology resulted in accurate measurement of cellular concentration of a number of key cell cycle regulatory proteins such as Cyclins, CDKs and CDK inhibitors during the cell cycle. The data are being utilized in the development of a quantitative integrated systems biology approach to the cell cycle. The approach consists of a comprehensive network of the molecular interaction pathways regulating cell cycle in normal and tumor cells and a model which incorporates the activity of key molecular species in a single dynamical system which can be solved using genetic algorithms designed to match experimental data, both qualitative and quantitative, to the model kinetics. The model could be utilized for the development of new drug targets and would be capable of consistently measuring the effects of existing drugs (either single or in combination) and opens up a methodology for establishing the effectiveness of these drugs with clear implications for cost/benefit assessment. Major impact is expected on clinical research where the model can be a tool in determining intervention strategies in the molecular pathways concerned. Apart from the development of new drug targets the model will be capable of consistently measuring the effects of existing drugs (either single or in combination) and opens up a methodology for establishing the effectiveness of anti-cancer drugs.
U2 - 10.1158/1538-7445.AM2012-4913
DO - 10.1158/1538-7445.AM2012-4913
M3 - Chapter (peer-reviewed)
SN - 0008-5472
VL - 72
SP - 4913
BT - Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL
CY - Chicago
ER -