Impact of metabolic heterogeneity on tumor growth, invasion, and treatment outcomes

Impact of metabolic heterogeneity on tumor growth, invasion, and treatment outcomes

Mark Robertson-Tessi, Robert J Gillies, Robert A Gatenby, Alexander RA Anderson

Abstract

A hybrid multiscale mathematical model of tumor growth is used to investigate how tumoral and microenvironmental heterogeneity affect treatment outcomes. A key component of this model is normal and tumor metabolism and its interaction with microenvironmental factors. In early stages of growth, tumors are stratified, with the most aggressive cells developing within the interior of the tumor. Simulations suggest that in some cases chemotherapy may increase the metabolic aggressiveness of a tumor due to drug-mediated selection.

Link: http://dx.doi.org/10.1101/038273

Estimating cell cycle model parameters using systems identification

Edwin Francisco Juarez Rosales, Ahmadreza Ghaffarizadeh, Samuel H Friedman, Edmond Jonckheere, PaulMacklin

doi: http://dx.doi.org/10.1101/035766

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Abstract

A current challenge in data-driven mathematical modeling of cancer is identifying biologically-relevant parameters of mathematical models from sparse and often noisy experimental data of mixed types. We describe a cell cycle model and outline how to use the Optimization Toolbox in Matlab to estimate its timescale parameters, given flow cytometry and cell viability (synthetic) data, and illustrate the technique with simulated data. This technique can be similarly applied to a variety of cell cycle models, particularly as more laboratories begin to use high-content, quantitative cell screening and imaging platforms. An advanced version of this work (CellPD: cell line phenotype digitizer) will be released as open source in early 2016 at MultiCellDS.org.

http://biorxiv.org/content/early/2015/12/31/035766

Simulating multi-substrate diffusive transport in 3-D tissues with BioFVM

Samuel H Friedman, Ahmadreza Ghaffarizadeh, Paul Macklin

doi: http://dx.doi.org/10.1101/035709

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Abstract

To simulate the spatiotemporal distribution of chemical compounds, we present BioFVM, an open-source reaction-diffusion equation solver using finite volume methods with motivation for biological applications. With various numerical solvers, we can simulate the interaction of dozens of compounds, including growth substrates, drugs, and signaling compounds in 3-D tissues, with cells by treating them as various source/sink terms. BioFVM has linear computational cost scalings and demonstrates first-order accuracy in time and second-order accuracy in space. Beyond simulating the transport of drugs and growth substrates in tissues, the ability to simulate dozens of compounds should make 3-D simulations of multicellular secretomics feasible.

http://biorxiv.org/content/early/2015/12/30/035709

Agent-based simulation of large tumors in 3-D microenvironments

Ahmadreza Ghaffarizadeh, Samuel H Friedman, Paul Macklin

doi: http://dx.doi.org/10.1101/035733

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Abstract

Multicellular simulations of tumor growth in complex 3-D tissues, where data come from high content in vitro and bioengineered experiments, have gained significant attention by the cancer modeling community in recent years. Agent-based models are often selected for these problems because they can directly model and track cells' states and their interactions with the microenvironment. We describe PhysiCell, a specific agent-based model that includes cell motion, cell cycling, and cell volume changes. The model has been performance tested on systems of 10^5 cells on desktop computers, and is expected to scale to 10^6 or more cells on single super-computer compute nodes. We plan an open source release of the software in early 2016 at PhysiCell.MathCancer.org.

http://biorxiv.org/content/early/2015/12/30/035733

The role of contact inhibition in intratumoral heterogeneity: An off-lattice individual based model

Jill Gallaher, Alexander Anderson

Abstract

We present a model that shows how intratumoral heterogeneity, in terms of tumor cell phenotypic traits, can evolve in a tumor mass as a result of selection when space is a limited resource. This model specifically looks at the traits of proliferation rate and migration speed. The competition for space amongst individuals in the tumor mass creates a selection pressure for the cells with the fittest traits. To allow for organic movement and capture the invasive behavior, we use an off-lattice individual-based model.

DOI: http://biorxiv.org/content/early/2016/01/11/036467

The role of oxygen in avascular tumor growth

David Robert Grimes, Pavitra Kannan, Alan McIntyre, Anthony Kavanagh, Abul Siddiky, Simon Wigfield, AdrianHarris, Mike Partridge

doi: http://dx.doi.org/10.1101/024562

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The oxygen status of a tumor has significant clinical implications for treatment prognosis, with well-oxygenated subvolumes responding markedly better to radiotherapy than poorly supplied regions. Oxygen is essential for tumor growth, yet estimation of local oxygen distribution can be difficult to ascertain in situ, due to chaotic patterns of vasculature. It is possible to avoid this confounding influence by using avascular tumor models, such as Multi-Cellular Tumor Spheroids (MCTS), where oxygen supply can be described by diffusion alone and are a much better approximation of realistic tumor dynamics than monolayers. Similar to in situ tumours, spheroids exhibit an approximately sigmoidal growth curve, often approximated and fitted by logistic and Gompertzian sigmoid functions. These describe the basic rate of growth well, but do not offer an explicitly mechanistic explanation. This work examines the oxygen dynamics of spheroids and demonstrates that this growth can be derived mechanistically with cellular doubling time and oxygen consumption rate (OCR) being key parameters. The model is fitted to growth curves for a range of cell lines and derived values of OCR are validated using clinical measurement. Finally, we illustrate how changes in OCR due to gemcitabine treatment can be directly inferred using this model.

http://biorxiv.org/content/early/2016/01/05/024562