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Optimal vaccination schedule search using genetic algorithm over MPI technology
Cristiano Calonaci1, Ferdinando Chiacchio, Francesco Pappalardo
1CINECA, Bologna, Italy.
Background:
Immunological strategies that achieve the prevention of tumor growth are based on the presumption that the immune system, if triggered before tumor onset, could be able to defend from specific cancers. In supporting this assertion, in the last decade active immunization approaches prevented some virus-related cancers in humans. An immunopreventive cell vaccine for the non-virus-related human breast cancer has been recently developed. This vaccine, called Triplex, targets the HER-2-neu oncogene in HER-2/neu transgenic mice and has shown to almost completely prevent HER-2/neu-driven mammary carcinogenesis when administered with an intensive and life-long schedule.
Methods:
To better understand the preventive efficacy of the Triplex vaccine in reduced schedules we employed a computational approach. The computer model developed allowed us to test in silico specific vaccination schedules in the quest for optimality. Specifically here we present a parallel genetic algorithm able to suggest optimal vaccination schedule.
Results & Conclusions:
The enormous complexity of combinatorial space to be explored makes this approach the only possible one. The suggested schedule was then tested in vivo, giving good results. Finally, biologically relevant outcomes of optimization are presented.
Insights
A novel computational approach optimized the Triplex vaccine schedule for preventing HER-2/neu-driven breast cancer. This optimized schedule, identified through a genetic algorithm, proved effective in vivo, offering a more efficient cancer prevention strategy.
Area of Science:
- Oncology
- Immunology
- Computational Biology
Background:
- Immunological strategies aim to prevent tumor growth by priming the immune system before cancer onset.
- Active immunization has successfully prevented virus-related cancers; a new cell vaccine, Triplex, targets HER-2/neu for breast cancer prevention.
- The Triplex vaccine demonstrated significant efficacy in preventing HER-2/neu-driven mammary carcinogenesis in mice with a lifelong schedule.
Purpose of the Study:
- To determine the preventive efficacy of the Triplex vaccine using reduced vaccination schedules.
- To identify an optimal vaccination schedule for the Triplex vaccine through computational modeling.
Main Methods:
- A computational approach using a parallel genetic algorithm was developed to test various vaccination schedules in silico.
- The algorithm aimed to find the optimal vaccination schedule for the Triplex vaccine.
Main Results:
- The computational model successfully identified an optimized vaccination schedule for the Triplex vaccine.
- In silico testing explored the vast combinatorial space of potential schedules.
Conclusions:
- The optimized Triplex vaccine schedule, determined computationally, was validated in vivo, yielding positive results.
- This approach offers a biologically relevant and efficient strategy for HER-2/neu-driven breast cancer prevention.
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