应用现代统计力学的癌症新组合疗法
New combinational therapies for cancer using modern statistical mechanics
摘要：
我们研究了一个新的动力学系统，描述肿瘤-宿主相互作用。描述未治疗肿瘤生长的方程基于非广延统计力学。最近，该模型已被证明可以成功地拟合指数、Gompertz、Logistic和幂律肿瘤生长。我们已经能够包括尽可能多的癌症特征。我们还研究了治疗下癌症的动态反应。使用我们的模型，当我们改变参数和/或初始条件时，我们可以预测不同的结果。我们可以确定影响肿瘤生长的不同因素的重要性。我们发现不同的治疗和药物的协同治疗作用。癌症通常无法使用常规单一疗法治疗。我们考虑常规疗法、癌基因靶向疗法、肿瘤抑制基因靶向疗法、免疫疗法、抗血管生成疗法、病毒疗法等。我们需要能够同时靶向肿瘤细胞和肿瘤微环境的疗法。靶向癌基因和肿瘤抑制基因的药物可以有效治疗某些癌症。然而，大多数肿瘤会复发。我们发现，当与其他癌细胞杀伤疗法联合使用时，可以看到新治疗药物的成功。我们的研究结果使我们能够设计一种可以完全根除癌症的联合疗法。
英文摘要：
We investigate a new dynamical system that describes tumor-host interaction. The equation that describes the untreated tumor growth is based on non-extensive statistical mechanics. Recently, this model has been shown to fit successfully exponential, Gompertz, logistic, and power-law tumor growths. We have been able to include as many hallmarks of cancer as possible. We study also the dynamic response of cancer under therapy. Using our model, we can make predictions about the different outcomes when we change the parameters, and/or the initial conditions. We can determine the importance of different factors to influence tumor growth. We discover synergistic therapeutic effects of different treatments and drugs. Cancer is generally untreatable using conventional monotherapy. We consider conventional therapies, oncogene-targeted therapies, tumor-suppressors gene-targeted therapies, immunotherapies, anti-angiogenesis therapies, virotherapy, among others. We need therapies with the potential to target both tumor cells and the tumors' microenvironment. Drugs that target oncogenes and tumor-suppressor genes can be effective in the treatment of some cancers. However, most tumors do reoccur. We have found that the success of the new therapeutic agents can be seen when used in combination with other cancer-cell-killing therapies. Our results have allowed us to design a combinational therapy that can lead to the complete eradication of cancer.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
