Estimating the Total Rate of DNA Replication Using Branching Processes

Larsson, Sara; Rydén, Tobias; Holst, Ulla; Oredsson, Stina; Johansson, Martin

doi:10.1007/s11538-008-9339-9

Cited by 10 publications

(6 citation statements)

References 27 publications

(37 reference statements)

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“…That is, tumors become more diverse and heterogeneous when one or more genes suffer many mutations in cells located at different positions. To express the FD time evolution in terms of a biological time scale one can relate one simulation cycle T with a biological cell division cycle that lasts about 35 hours [55]. Since a full simulation of the in-silico tumors lasts about 800 cycles, the typical simulations reported here correspond to approximately 28,000 hours, about 38.9 months of real time.…”

Section: Resultsmentioning

confidence: 99%

Model for breast cancer diversity and spatial heterogeneity

et al. 2018

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We present and analyze a growth model of an avascular tumor that considers the basic biological principles of proliferation, motility, death and genetic mutations of the cell. From a regulatory network analysis and an analysis of genomic data we identify two sets of genes-a set of six genes and a set of sixteen genes-that are believed to play an important role in the evolution of breast cancer. Considering that cancer cells shape the tissue microenvironment and niches to their competitive advantage, the model assumes that cancer and normal cells compete for essential nutrients and that the rate of the "driver" mutations depends on nutrient availability. To this end, we propose a coupling between the transport of nutrients and gene mutations dynamics. Gene mutation dynamics are modeled as a Yule-Furry Markovian process, while transport of nutrients is described with a system of reaction-diffusion equations. For each representative tumor we calculate its diversity, represented by the Shannon index, and its spatial heterogeneity, measured by its fractal dimension. These quantities are important in the clinical diagnosis of tumor malignancy. A tumor malignancy diagram, obtained by plotting diversity versus fractal dimension, is calculated for different values of a parameter β, which is related to the occurrence of driver mutations. It is found that when β < 1, tumors show greater diversity and more spatial heterogeneity as compared with β > 1. More importantly, it is found that the results and conclusions are similar when we use the six-gene set versus sixteen-gene set.

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Section: Resultsmentioning

confidence: 99%

Model for breast cancer diversity and spatial heterogeneity

et al. 2018

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“…The onset of effects was observed ∼ 24 h later than in HeLa cells. This is a result of the longer doubling times of MCF‐7 cells (∼ 36 h) [55] when compared with HeLa cells (∼ 22 h). These results strongly suggest that the balance between CKα and CKβ dictates cell survival such that knockdown of CKβ reduces, or abolishes, the cell‐killing effect of single CKα knockdown.…”

Section: Resultsmentioning

confidence: 99%

Balance of human choline kinase isoforms is critical for cell cycle regulation

et al. 2012

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The enzyme choline kinase (CK), which catalyzes the phosphorylation of choline to phosphorylcholine in the presence of ATP, has an essential role in the biosynthesis of phosphatidylcholine, the major constituent of all mammalian cell membranes. CK is encoded by two separate genes expressing the three isoforms CKα1, CKα2 and CKβ that are active as homodimeric or heterodimeric species. Metabolic changes observed in various cancer cell lines and tumors have been associated with differential and marked up‐regulation of the CKα genes, and specific inhibition of CKα activity has been proposed as a potential anti‐cancer strategy. As a result, less attention has been given to CKβ and its interaction with CKα. With the aim of profiling the intracellular roles of CKα and CKβ, we used RNA interference (RNAi) as a molecular approach to down‐regulate the expression of CK in HeLa cells. Individual and simultaneous RNAi‐based silencing of the CK α and β isoforms was achieved using different combinations of knockdown strategies. Efficient knockdown was confirmed by immunodetection using our isoform‐specific antibodies and by quantitative real‐time PCR. Our analyses of the phenotypic consequences of CK depletion showed the expected lethal effect of CKα knockdown. However, CKβ‐ and CKα + CKβ‐silenced cells had no aberrant phenotype. Therefore, our results support the hypothesis that the balance of the α and β isoforms is critical for cancer cell survival. The suppression of the cancer cell killing effect of CKα silencing by simultaneous knockdown of both isoforms implies that a more effective CK‐based anti‐cancer strategy can be achieved by reducing cross‐reactivity with CKβ.

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“…The gamma distribution is a flexible two-parameter family that is commonly used to model lifetimes [Oprea and Kepler (2001), Larsson et al (2008)]. Specifically, if the parameters are a and b, the probability density function is…”

Section: The Branching Process Model: Data Analysismentioning

confidence: 99%