The goal of immunotherapy is to mobilize the immune system to kill cancer cells. Immunotherapy is more effective and, in general, the prognosis is better, when more immune cells infiltrate the tumor. We explore the question of whether the spatial distribution rather than just the density of immune cells in the tumor is important in forecasting whether cancer recurs. After reviewing previous work on this issue, we introduce a novel application of maximum entropy to quantify the spatial distribution of discrete point-like objects. We apply our approach to B and T cells in images of tumor tissue taken from triple negative breast cancer (TNBC) patients. We find that the immune cells are more spatially dispersed in good clinical outcome (no recurrence of cancer within at least 5 years of diagnosis) compared to poor clinical outcome (recurrence within 3 years of diagnosis). Our results highlight the importance of spatial distribution of immune cells within tumors with regard to clinical outcome, and raise new questions on their role in cancer recurrence.

中文翻译：

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肿瘤中免疫细胞空间分布的物理方法

免疫疗法的目标是调动免疫系统杀死癌细胞。当更多的免疫细胞浸润肿瘤时，免疫疗法更有效，并且通常预后更好。我们探讨了空间分布而不仅仅是肿瘤中免疫细胞的密度在预测癌症是否复发方面是否重要的​​问题。在回顾了之前关于这个问题的工作之后，我们引入了最大熵的一种新应用来量化离散点状物体的空间分布。我们将我们的方法应用于取自三阴性乳腺癌 (TNBC) 患者的肿瘤组织图像中的 B 和 T 细胞。我们发现，与较差的临床结果（诊断后 3 年内复发）相比，免疫细胞在良好的临床结果（诊断后至少 5 年内没有癌症复发）的情况下在空间上更分散。我们的结果强调了肿瘤内免疫细胞空间分布对临床结果的重要性，并提出了关于它们在癌症复发中的作用的新问题。