Suppr超能文献

在异质细胞群体中对溶瘤病毒进行建模,以预测其向非癌细胞的扩散。

Modeling of oncolytic viruses in a heterogeneous cell population to predict spread into non-cancerous cells.

机构信息

SUNY Upstate Medical University, Syracuse, NY, United States of America; Department of Physics and Astronomy, Texas Christian University, Fort Worth, TX, United States of America.

Department of Physics and Astronomy, Texas Christian University, Fort Worth, TX, United States of America.

出版信息

Comput Biol Med. 2023 Oct;165:107362. doi: 10.1016/j.compbiomed.2023.107362. Epub 2023 Aug 19.

Abstract

New cancer treatment modalities that limit patient discomfort need to be developed. One possible new therapy is the use of oncolytic (cancer-killing) viruses. It is only recently that our ability to manipulate viral genomes has allowed us to consider deliberately infecting cancer patients with viruses. One key consideration is to ensure that the virus exclusively targets cancer cells and does not harm nearby non-cancerous cells. Here, we use a mathematical model of viral infection to determine the characteristics a virus would need to have in order to eradicate a tumor, but leave non-cancerous cells untouched. We conclude that the virus must differ in its ability to infect the two different cell types, with the infection rate of non-cancerous cells needing to be less than one hundredth of the infection rate of cancer cells. Differences in viral production rate or infectious cell death rate alone are not sufficient to protect non-cancerous cells.

摘要

需要开发新的癌症治疗方法,以减轻患者的不适。一种可能的新疗法是使用溶瘤(杀死癌细胞)病毒。直到最近,我们才有能力操纵病毒基因组,从而考虑故意用病毒感染癌症患者。一个关键的考虑因素是确保病毒专门针对癌细胞,而不会伤害附近的非癌细胞。在这里,我们使用病毒感染的数学模型来确定病毒需要具有哪些特征才能消除肿瘤,但又不损伤非癌细胞。我们的结论是,病毒在感染两种不同细胞类型的能力上必须有所不同,非癌细胞的感染率需要小于癌细胞感染率的百分之一。仅靠病毒产生率或感染细胞死亡率的差异不足以保护非癌细胞。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验