Scope of the present work is to frame into a rigorous, quantitative scaffold - stemmed from stochastic process theory - two sets of experiments designed to infer the spontaneous organization of leukocytes against cancer cells, namely mice splenocytes vs. B16 mouse tumor cells, and embedded in an "ad hoc" microfluidic environment developed on a LabOnChip technology. In the former, splenocytes from knocked out (KO) mice engineered to silence the transcription factor IRF-8, crucial for the development and function of several immune populations, were used. In this case lymphocytes and cancer cells exhibited a poor reciprocal exchange, resulting in the inability of coordinating or mounting an effective immune response against melanoma. In the second class of tests, wild type (WT) splenocytes were able to interact with and to coordinate a response against the tumor cells through physical interaction. The environment where cells moved was built of by two different chambers, containing respectively melanoma cells and splenocytes, connected by capillary migration channels allowing leucocytes to migrate from their chamber toward the melanoma one. We collected and analyzed data on the motility of the cells and found that the first ensemble of IRF-8 KO cells performed pure uncorrelated random walks, while WT splenocytes were able to make singular drifted random walks, that, averaged over the ensemble of cells, collapsed on a straight ballistic motion for the system as a whole. At a finer level of investigation, we found that IRF-8 KO splenocytes moved rather uniformly since their step lengths were exponentially distributed, while WT counterpart displayed a qualitatively broader motion as their step lengths along the direction of the melanoma were log-normally distributed.
Sensitivity analysis-guided model reduction of a mathematical model of pembrolizumab therapy for de novo metastatic MSI-H/dMMR colorectal cancer
School of Mathematics and Statistics, University of Sydney（悉尼大学数学与统计学院）；Department of Immuno-Oncology, Beckman Research Institute, City of Hope（城市之希望贝克曼研究所免疫肿瘤学系）
本文通过灵敏度分析指导的方法，对 pembrolizumab 治疗 de novo 转移性 MSI-H/dMMR 结直肠癌的数学模型进行简化，构建了两种模型以研究免疫检查点阻断的动态机制。
Optimisation of neoadjuvant pembrolizumab therapy for locally advanced MSI-H/dMMR colorectal cancer using data-driven delay integro-differential equations
School of Mathematics and Statistics, University of Sydney（悉尼大学数学与统计学院）；Department of Immuno-Oncology, Beckman Research Institute, City of Hope（希科医院贝克曼研究所免疫肿瘤学系）
