Agent Based Modeling of Lung Metastasis-Immune System Competition,

Extended Abstract The Triplex vaccine is a cell vaccine developed as an immunopreventive approach to breast cancer. Recent studies showed that the same vaccine has a considerable therapeutic effect against lung metastases derived by mammary carcinoma Using three different signals (the target antigen, interleukin-12 (IL-12) and allogeneic MHC molecules) it stimulates immune system response in many ways. The "in vivo" experiment lasts for 32 days. For the induction of lung micrometastasis, all mice received an intravenous injection of 2.5·10 4 metastatic cells at day 0. In standard "in vivo" experiments it is considered common practice to use multiple sets of mice, each treated with a different protocol. One of these sets (the control set) is usually treated with a placebo solution in order to study/represen

Drosophila as a model system to study nonautonomous mechanisms affecting tumour growth and cell death

The study of cancer has represented a central focus in medical research for over a century. The great complexity and constant evolution of the pathology require the use of multiple research model systems and interdisciplinary approaches. This is necessary in order to achieve a comprehensive understanding into the mechanisms driving disease initiation and progression, to aid the development of appropriate therapies. In recent decades, the fruit fly Drosophila melanogaster and its associated powerful genetic tools have become a very attractive model system to study tumour-intrinsic and non-tumour-derived processes that mediate tumour development in vivo. In this review, we will summarize recent work on Drosophila as a model system to study cancer biology. We will focus on the interactions between tumours and their microenvironment, including extrinsic mechanisms affecting tumour growth and how tumours impact systemic host physiology

Niche inheritance: a cooperative pathway to enhance cancer cell fitness though ecosystem engineering

Cancer cells can be described as an invasive species that is able to establish itself in a new environment. The concept of niche construction can be utilized to describe the process by which cancer cells terraform their environment, thereby engineering an ecosystem that promotes the genetic fitness of the species. Ecological dispersion theory can then be utilized to describe and model the steps and barriers involved in a successful diaspora as the cancer cells leave the original host organ and migrate to new host organs to successfully establish a new metastatic community. These ecological concepts can be further utilized to define new diagnostic and therapeutic areas for lethal cancers.Comment: 8 pages, 1 Table, 4 Figure

Modeling the competition between lung metastases and the immune system using agents

<p>Abstract</p> <p>Background</p> <p>The Triplex cell vaccine is a cancer cellular vaccine that can prevent almost completely the mammary tumor onset in HER-2/neu transgenic mice. In a translational perspective, the activity of the Triplex vaccine was also investigated against lung metastases showing that the vaccine is an effective treatment also for the cure of metastases. A future human application of the Triplex vaccine should take into account several aspects of biological behavior of the involved entities to improve the efficacy of therapeutic treatment and to try to predict, for example, the outcomes of longer experiments in order to move faster towards clinical phase I trials. To help to address this problem, MetastaSim, a hybrid Agent Based - ODE model for the simulation of the vaccine-elicited immune system response against lung metastases in mice is presented. The model is used as in silico wet-lab. As a first application MetastaSim is used to find protocols capable of maximizing the total number of prevented metastases, minimizing the number of vaccine administrations.</p> <p>Results</p> <p>The model shows that it is possible to obtain "in silico" a 45% reduction in the number of vaccinations. The analysis of the results further suggests that any optimal protocol for preventing lung metastases formation should be composed by an initial massive vaccine dosage followed by few vaccine recalls.</p> <p>Conclusions</p> <p>Such a reduction may represent an important result from the point of view of translational medicine to humans, since a downsizing of the number of vaccinations is usually advisable in order to minimize undesirable effects. The suggested vaccination strategy also represents a notable outcome. Even if this strategy is commonly used for many infectious diseases such as tetanus and hepatitis-B, it can be in fact considered as a relevant result in the field of cancer-vaccines immunotherapy. These results can be then used and verified in future "in vivo" experiments, and their outcome can be used to further improve and refine the model.</p

Mathematical model of brain tumour with glia-neuron interactions and chemotherapy treatment

Acknowledgements This study was possible by partial financial support from the following Brazilian government agencies: Fundação Araucária, EPSRC-EP/I032606/1 and CNPq, CAPES and Science Without Borders Program Process nos. 17656125, 99999.010583/2013-00 and 245377/2012-3.Peer reviewedPreprin

Metabolism within the tumor microenvironment and its implication on cancer progression: an ongoing therapeutic target

Since reprogramming energy metabolism is considered a new hallmark of cancer, tumor metabolism is again in the spotlight of cancer research. Many studies have been carried out and many possible therapies have been developed in the last years. However, tumor cells are not alone. A series of extracellular components and stromal cells, such as endothelial cells, cancer-associated fibroblasts, tumor-associated macrophages and tumor-infiltrating T cells, surround tumor cells in the so-called tumor microenvironment. Metabolic features of these cells are being studied in deep in order to find relationships between metabolism within the tumor microenvironment and tumor progression. Moreover, it cannot be forgotten that tumor growth is able to modulate host metabolism and homeostasis, so that tumor microenvironment is not the whole story. Importantly, the metabolic switch in cancer is just a consequence of the flexibility and adaptability of metabolism and should not be surprising. Treatments of cancer patients with combined therapies including anti-tumor agents with those targeting stromal cell metabolism, anti-angiogenic drugs and/or immunotherapy are being developed as promising therapeutics.Mª Carmen Ocaña is recipient of a predoctoral FPU grant from the Spanish Ministry of Education, Culture and Sport. Supported by grants BIO2014-56092-R (MINECO and FEDER), P12-CTS-1507 (Andalusian Government and FEDER) and funds from group BIO-267 (Andalusian Government). The "CIBER de Enfermedades Raras" is an initiative from the ISCIII (Spain). The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript

Recipes for calibration and validation of agent-based models in cancer biomedicine

Computational models and simulations are not just appealing because of their intrinsic characteristics across spatiotemporal scales, scalability, and predictive power, but also because the set of problems in cancer biomedicine that can be addressed computationally exceeds the set of those amenable to analytical solutions. Agent-based models and simulations are especially interesting candidates among computational modelling strategies in cancer research due to their capabilities to replicate realistic local and global interaction dynamics at a convenient and relevant scale. Yet, the absence of methods to validate the consistency of the results across scales can hinder adoption by turning fine-tuned models into black boxes. This review compiles relevant literature to explore strategies to leverage high-fidelity simulations of multi-scale, or multi-level, cancer models with a focus on validation approached as simulation calibration. We argue that simulation calibration goes beyond parameter optimization by embedding informative priors to generate plausible parameter configurations across multiple dimensions