A computational model for quantitative analysis of cell cycle arrest and its contribution to overall growth inhibition by anticancer agents

Citation
Hj. Kuh et al., A computational model for quantitative analysis of cell cycle arrest and its contribution to overall growth inhibition by anticancer agents, JPN J CANC, 91(12), 2000, pp. 1303-1313
Citations number
22
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Onconogenesis & Cancer Research
Journal title
JAPANESE JOURNAL OF CANCER RESEARCH
ISSN journal
0910-5050 → ACNP
Volume
91
Issue
12
Year of publication
2000
Pages
1303 - 1313
Database
ISI
SICI code
0910-5050(200012)91:12<1303:ACMFQA>2.0.ZU;2-5
Abstract
Most anticancer agents induce cell cycle arrest (cytostatic effect) and cel l death (cytotoxic effect), resulting in the inhibition of population growt h of cancer cells. When asynchronous cells are to be examined, the currentl y used flow cytometric method can not provide checkpoint-specific and quant itative information on the drug-induced cell cycle arrest. Hence, despite i ts significance, no good method to analyze in detail the mechanism of cell cycle arrest and its contribution to overall growth inhibition induced by a n anticancer agent has yet been established. We describe in this study the development of a discrete time (Markov model)-based computational model for cell cycle progression/arrest with transition probability (TPi) as a model parameter. TPi was calculated using model equations that include easily me asurable parameters such as the fraction of cells in each cell cycle phase and population doubling time. The TPi was then used to analyze checkpoint-s pecific and quantitative changes in cell cycle progression. We also used TP i in a Monte-Carlo simulation to predict growth inhibition caused by cell c ycle arrest only. Human SCLC cells (SBC-3) exposed to UCN-01 were used to v alidate the model. The model-predicted growth curves agreed with the observ ed data for SBC-3 cells not treated or treated at a cytostatic concentratio n (0.2 muM) of UCN-01, indicating validity of the present model. The change s in TPi indicated that UCN-01 reduced the G(i)-to-S transition rate and in creased the S-to-G(2)/M and G(2)/M-to-G(1) transition rates of SBC-3 cells in a concentration- and time-dependent manner. When the model-predicted gro wth curves were compared with the observed data for cells treated at a cyto toxic concentration (2 muM), they suggested that 22% out of 65% and 32% out of 73% of the growth inhibition could be attributed to the cell cycle arre st effect after 48 h and 72 h exposure, respectively. In conclusion, we rep ort here the establishment of a novel method of analysis that can provide c heckpoint-specific and quantitative information about cell cycle arrest ind uced by an anticancer agent and that can be used to assess the contribution of cell cycle arrest effect to the overall growth inhibition.