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Updated: Jun 6, 2026
Primary Tumor and MEF Cell Isolation to Study Lung Metastasis
Published on: May 20, 2015
Modeling the competition between lung metastases and the immune system using agents
Marzio Pennisi1, Francesco Pappalardo, Ariannna Palladini
1Department of Mathematics and Computer Science, University of Catania, V,le A, Doria 6, Catania, Italy. mpennisi@dmi.unict.it
Background:
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.
Results:
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.
Conclusions:
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.
Insights
A new simulation model, MetastaSim, can reduce cancer vaccine administrations by 45%. This cancer immunotherapy strategy involves an initial dose followed by recalls, minimizing side effects for potential human application.
Area of Science:
- Immunology
- Computational Biology
- Oncology
Background:
- The Triplex cell vaccine effectively prevents mammary tumors and lung metastases in HER-2/neu transgenic mice.
- Translational research requires predicting vaccine efficacy for human trials, necessitating improved simulation models.
- MetastaSim, a hybrid Agent Based-Ordinary Differential Equation model, simulates immune response to cancer vaccines.
Purpose of the Study:
- To develop and utilize MetastaSim as an in silico tool to optimize cancer vaccine protocols.
- To identify vaccination strategies that maximize metastasis prevention while minimizing administrations.
- To inform future clinical trials for the Triplex vaccine.
Main Methods:
- Developed MetastaSim, a hybrid Agent Based-ODE model.
- Simulated vaccine-elicited immune response against lung metastases in mice.
- Used the model to explore vaccination protocols for efficacy and efficiency.
Main Results:
- Achieved a 45% reduction in vaccine administrations in silico.
- Identified an optimal protocol: initial high-dose vaccination followed by booster recalls.
- Demonstrated the model's utility in optimizing cancer immunotherapy strategies.
Conclusions:
- The 45% reduction in vaccinations is significant for translational medicine, potentially minimizing adverse effects.
- The proposed vaccination strategy, common in infectious diseases, is a novel finding for cancer vaccine immunotherapy.
- Results provide a basis for future in vivo validation and model refinement.
