Mathematical Model-Guided Adoptive Immunotherapy in Bladder Cancer

摘要 膀胱癌是男性第四大常见癌症，也是男性癌症死亡的主要原因。 女性的膀胱癌发病率和与膀胱癌相关的死亡率没有 在过去的40年里减少了。因此，需要新的更精确的治疗策略。膀胱 长期以来，癌症一直被认为是一种对免疫治疗有反应的恶性肿瘤。其中一个 新的免疫治疗方法利用过继细胞疗法(ACT)，其中自体肿瘤浸润性 T淋巴细胞(TIL)在体外被扩增和激活，然后再注入癌症患者体内。然而， 典型的ACT-TIL全身给药需要事先去除淋巴组织，从而注射TIL 很少见，而且数量很多。膀胱是一种特殊的器官，它允许直接在膀胱内分娩 通过导管给药和T细胞，使其更容易发生多次和更频繁 输注TIL和其他治疗药物，可能剂量较小。这给了一个前所未有的 有机会使用与临床前小鼠模型集成的数学建模来设计、优化和 验证ACT-TIL联合疗法将最大限度地提高肿瘤反应并将毒性降至最低。我们的方法 包括由体外、体内和体外支持硅胶模型的微观和宏观水平 实验数据，定义的T细胞和模拟临床相关的膀胱癌小鼠模型 程序。在目标1中，我们将建立电子计算机模型以增强T细胞在膀胱肿瘤中的渗透。在……里面 目的2，我们将在体外优化T细胞的特性，以实现最有效的T细胞-癌细胞相互作用。在《目标3》中， 我们将应用我们的综合方法来设计最有效的联合治疗方案，以增加 再注入TILs的有效性。这项研究的成果将提高我们对 膀胱癌微环境影响T细胞浸润和T细胞-肿瘤细胞相互作用 通过数学优化治疗计划来改善膀胱癌治疗的策略。

Summary Bladder cancer is the fourth most common cancer in men and a leading cause of cancer mortality among men and women with the rates of bladder cancer incidents and bladder cancer-related deaths that have not decreased over the last 40 years. Therefore, novel more precise treatment strategies are desired. Bladder cancer has long been recognized as a malignancy that is responsive to immune-based therapy. One of the novel immunotherapy approaches utilizes the adoptive cell therapy (ACT), where autologous tumor-infiltrating T lymphocytes (TIL) are expanded and activated ex vivo and then reinfused into the cancer patient. However, typical systemic administration of ACT-TIL requires prior lymphodepletion and thus TIL are injected infrequently and in large numbers. Bladder is a specific organ which allows for intravesical delivery by direct administration of drugs and T cells through a catheter making it amenable to multiple and more frequent infusions of TIL and other therapeutics, potentially with smaller doses. This gives an unprecedented opportunity to use mathematical modeling integrated with pre-clinical mouse models to design, optimize and validate ACT-TIL combination therapies that will maximize tumor response and minimize toxicity. Our methods include microscopic- and macroscopic-level in silico models supported by in vitro, in vivo and ex vivo experimental data, defined T cells and a murine models of bladder cancer that mimic clinically-relevant procedures. In Aim 1, we will develop in silico models to enhance T cell infiltration into the bladder tumors. In Aim 2, we will optimize T cell properties ex vivo for the most effective T cell-cancer cell interactions. In Aim 3, we will apply our integrated methodology to design most effective combination therapy protocols to increase the effectiveness of reinfused TILs. The deliverables of this study will improve our understanding of how the bladder tumor microenvironment impacts T cell infiltration and T cell-tumor cell interactions and will lead to strategies that improve bladder cancer treatment by mathematically optimizing treatment schedules.