Mathematical Modeling Reveals That Changes to Local Cell Density Dynamically Modulate Baseline Variations in Cell Growth and Drug Response

Greene, James M.; Levy, Doron; Herrada, Sylvia P.; Gottesman, Michael M.; Lavi, Orit

doi:10.1158/0008-5472.can-15-3232

Cited by 23 publications

(14 citation statements)

References 22 publications

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“…Moreover, in the context of ovarian cancer, Greene et al . 41 have shown that local cell density and initial global cell density, are able to lead to significant differences in spatial growth, proliferation, and paclitaxel-induced apoptosis rates in OVCAR8 cells, thus having a role not only in cancer cells growth but also in drug response.…”

Section: Discussionmentioning

confidence: 99%

Cysteine allows ovarian cancer cells to adapt to hypoxia and to escape from carboplatin cytotoxicity

Nunes

Ramos

Lopes‐Coelho

et al. 2018

Sci Rep

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Ovarian cancer is the second most common gynaecologic malignancy and the main cause of death from gynaecologic cancer, due to late diagnosis and chemoresistance. Studies have reported the role of cysteine in cancer, by contributing for hydrogen sulphide (H2S) generation and as a precursor of glutathione (GSH). However, the role of cysteine in the adaptation to hypoxia and therapy response remains unclear. We used several ovarian cancer cell lines, ES2, OVCAR3, OVCAR8, A2780 and A2780cisR, to clarify cysteine relevance in ovarian cancer cells survival upon hypoxia and carboplatin. Results show that ES2 and OVCAR8 cells presented a stronger dependence on cysteine availability upon hypoxia and carboplatin exposure than OVCAR3 cells. Interestingly, the A2780 cisR, but not A2780 parental cells, benefits from cysteine upon carboplatin exposure, showing that cysteine is crucial for chemoresistance. Moreover, GSH degradation and subsequent cysteine recycling pathway is associated with ovarian cancer as seen in peripheral blood serum from patients. Higher levels of total free cysteine (Cys) and homocysteine (HCys) were found in ovarian cancer patients in comparison with benign tumours and lower levels of GSH were found in ovarian neoplasms patients in comparison with healthy individuals. Importantly, the total and S-Homocysteinylated levels distinguished blood donors from patients with neoplasms as well as patients with benign from patients with malignant tumours. The levels of S-cysteinylated proteins distinguish blood donors from patients with neoplasms and the free levels of Cys in serum distinguish blood from patients with benign tumours from patients with malignant tumours. Herein we disclosed that cysteine contributes for a worse disease prognosis, allowing faster adaptation to hypoxia and protecting cells from carboplatin. The measurement of serum cysteine levels can be an effective tool for early diagnosis, for outcome prediction and follow up of disease progression.

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Section: Discussionmentioning

confidence: 99%

Cysteine allows ovarian cancer cells to adapt to hypoxia and to escape from carboplatin cytotoxicity

Nunes

Ramos

Lopes‐Coelho

et al. 2018

Sci Rep

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“…Although the observation of a weak Allee effect in glioblastoma recurrence is certainly provocative, it is limited by the fact that the earliest stages of tumor growth from low cell densities cannot be easily detected in vivo and thus the critical measurements at the relevant regime cannot be captured with current imaging technologies. Numerous studies have investigated the manifestation of the Allee effect in ecology [32][33][34][35] and a few have posed theoretical implications and possible mechanisms of cooperative kinetics of the Allee effect in cancer growth [36][37][38][39][40]. However, none have performed an in-depth quantitative analysis of cancer cell proliferation kinetics captured in the low cell density regime.…”

Section: Introductionmentioning

confidence: 99%

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

et al. 2019

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Most models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations to account for observed slowing of growth rate only at higher densities due to limited resources such as space and nutrients. However, recent preclinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale positively with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models, however, tumor growth data are limited by the lower limit of detection (i.e., a measurable lesion) and confounding variables, such as tumor microenvironment, and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to disentangle expected deviations due to small population size stochastic effects from cooperative growth and use the moment approach for stochastic parameter estimation to calibrate the observed growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells increases with cell number in the regime of small population size. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging and relapsed tumors.

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“…Although many proposed mathematical models account for the natural variability in the proliferative capacity of the cell population by introducing heterogeneity in the cell cycle duration ( 11 – 14 ), the direct effect this heterogeneity plays on tumor evolution, when cytotoxic treatment is applied, has not been demonstrated. Differences between mitotic and random death rates reflecting different drug pharmacodynamics have not been demonstrated either.…”

Section: Introductionmentioning

confidence: 99%

Modeling How Heterogeneity in Cell Cycle Length Affects Cancer Cell Growth Dynamics in Response to Treatment

2020

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Tumors are complex, dynamic, and adaptive biological systems characterized by high heterogeneity at genetic, epigenetic, phenotypic, as well as tissue microenvironmental level. In this work, utilizing cellular automata methods, we focus on intrinsic heterogeneity with respect to cell cycle duration and explore whether and to what extent this heterogeneity affects cancer cell growth dynamics when cytotoxic treatment is applied. We assume that treatment acts on cancer cells specifically during mitosis and compare it with a (cell cycle-non-specific) cytotoxic treatment that acts randomly regardless of the cell cycle phase. We simulate the spatiotemporal evolution of tumor cells with different initial spatial configurations and different cell length probability distributions. We observed that in heterogeneous populations, strong selection forces act on cancer cells favoring the faster cells, when the death rates are lower than the proliferation rates. However, at higher mitotic death rates, selection of the slower proliferative cells is favored, leading to slower post-treatment regrowth rates, as compared to untreated growth. Of note, random cell death progressively eliminates the slower proliferative cells, consistently, favoring highly proliferative phenotypes. Interestingly, compared to the monoclonal populations that exhibit complete response at high random death rates, emergent resistance arises naturally in heterogeneous populations during treatment. As divergent selection forces may act on a heterogeneous cancer cell population, we argue that treatment plan selection can considerably alter the post-treatment tumor dynamics, cell survival, and emergence of resistance, proving its significant biological and therapeutic impact.

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Mathematical Modeling Reveals That Changes to Local Cell Density Dynamically Modulate Baseline Variations in Cell Growth and Drug Response

Cited by 23 publications

References 22 publications

Cysteine allows ovarian cancer cells to adapt to hypoxia and to escape from carboplatin cytotoxicity

Cysteine allows ovarian cancer cells to adapt to hypoxia and to escape from carboplatin cytotoxicity

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Modeling How Heterogeneity in Cell Cycle Length Affects Cancer Cell Growth Dynamics in Response to Treatment

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