Optimal strategies of oncolytic virus-bortezomib therapy via the apoptotic, necroptotic, and oncolysis signaling network
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Title
- Optimal strategies of oncolytic virus-bortezomib therapy via the apoptotic, necroptotic, and oncolysis signaling network
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Author(s)
- Lee, Donggu; Aurelio A. de los Reyes V; Kim, Yangjin
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Publication Date
- 2024-02
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Journal
- Mathematical Biosciences and Engineering, v.21, no.3, pp.3876 - 3909
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Publisher
- American Institute of Mathematical Sciences
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Abstract
- Bortezomib and oncolytic virotherapy are two emerging targeted cancer therapies. Bortezomib, a proteasome inhibitor, disrupts protein degradation in cells, leading to the accumulation of unfolded proteins that induce apoptosis. On the other hand, virotherapy uses genetically modified oncolytic viruses (OVs) to infect cancer cells, trigger cell lysis, and activate anti-tumor response. Despite progress in cancer treatment, identifying administration protocols for therapeutic agents remains a significant concern, aiming to strike a balance between efficacy, minimizing toxicity, and administrative costs. In this work, optimal control theory was employed to design a cost-effective and efficient co-administration protocols for bortezomib and OVs that could significantly diminish the population of cancer cells via the cell death program with the NFκB-BAX-RIP1 signaling network. Both linear and quadratic control strategies were explored to obtain practical treatment approaches by adapting necroptosis protocols to efficient cell death programs. Our findings demonstrated that a combination therapy commencing with the administration of OVs followed by bortezomib infusions yields an effective tumor-killing outcome. These results could provide valuable guidance for the development of clinical administration protocols in cancer treatment. © 2024 the Author(s).
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URI
- https://pr.ibs.re.kr/handle/8788114/15032
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DOI
- 10.3934/mbe.2024173
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ISSN
- 1547-1063
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Appears in Collections:
- Pioneer Research Center for Mathematical and Computational Sciences(수리 및 계산과학 연구단) > Biomedical Mathematics Group(의생명 수학 그룹) > 1. Journal Papers (저널논문)
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