Prathibha Ambegoda, Hsiu-Chuan Wei, Sophia R-J Jang
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引用次数: 0
Abstract
Resistance to treatment poses a major challenge for cancer therapy, and oncoviral treatment encounters the issue of viral resistance as well. In this investigation, we introduce deterministic differential equation models to explore the effect of resistance on oncolytic viral therapy. Specifically, we classify tumor cells into resistant, sensitive, or infected with respect to oncolytic viruses for our analysis. Immune cells can eliminate both tumor cells and viruses. Our research shows that the introduction of immune cells into the tumor-virus interaction prevents all tumor cells from becoming resistant in the absence of conversion from resistance to sensitivity, given that the proliferation rate of immune cells exceeds their death rate. The inclusion of immune cells leads to an additional virus-free equilibrium when the immune cell recruitment rate is sufficiently high. The total tumor burden at this virus-free equilibrium is smaller than that at the virus-free and immune-free equilibrium. Therefore, immune cells are capable of reducing the tumor load under the condition of sufficient immune strength. Numerical investigations reveal that the virus transmission rate and parameters related to the immune response significantly impact treatment outcomes. However, monotherapy alone is insufficient for eradicating tumor cells, necessitating the implementation of additional therapies. Further numerical simulation shows that combination therapy with chimeric antigen receptor (CAR T-cell) therapy can enhance the success of treatment.
抗药性是癌症治疗面临的一大挑战,肿瘤病毒治疗也会遇到病毒抗药性问题。在这项研究中,我们引入了确定性微分方程模型来探讨抗药性对溶瘤病毒治疗的影响。具体来说,我们将肿瘤细胞分为对溶瘤病毒耐药、敏感和感染三种类型进行分析。免疫细胞既能消灭肿瘤细胞,也能消灭病毒。我们的研究表明,由于免疫细胞的增殖率超过其死亡率,因此在肿瘤与病毒的相互作用中引入免疫细胞,可防止所有肿瘤细胞在未从抗药性转化为敏感性的情况下产生抗药性。当免疫细胞招募率足够高时,免疫细胞的加入会导致额外的无病毒平衡。这种无病毒平衡状态下的总肿瘤负荷小于无病毒和无免疫平衡状态下的总肿瘤负荷。因此,在免疫力足够强的条件下,免疫细胞能够减少肿瘤负荷。数值研究表明,病毒传播率和与免疫反应相关的参数对治疗效果有显著影响。然而,单靠单一疗法不足以根除肿瘤细胞,因此有必要采用其他疗法。进一步的数值模拟显示,与嵌合抗原受体(CAR T 细胞)疗法相结合可以提高治疗的成功率。
期刊介绍:
Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing.
MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).