Recent successes of immune-modulating therapies for cancer have stimulated research on information flow within the immune system and, in turn, clinical applications of concepts from information theory. Through information theory, one can describe and formalize, in a mathematically rigorous fashion, the function of interconnected components of the immune system in health and disease. Specifically, using concepts including entropy, mutual information, and channel capacity, one can quantify the storage, transmission, encoding, and flow of information within and between cellular components of the immune system on multiple temporal and spatial scales. To understand, at the quantitative level, immune signaling function and dysfunction in cancer, we present a methodology-oriented review of information-theoretic treatment of biochemical signal transduction and transmission coupled with mathematical modeling.

最近癌症免疫调节疗法的成功刺激了对免疫系统内信息流的研究，进而促进了信息论概念的临床应用。通过信息论，人们可以以数学上严格的方式描述和形式化免疫系统相互关联的组成部分在健康和疾病中的功能。具体来说，使用包括熵、互信息和通道容量在内的概念，可以在多个时间和空间尺度上量化免疫系统的细胞成分内部和细胞成分之间的信息存储、传输、编码和流动。为了在定量水平上了解癌症中的免疫信号功能和功能障碍，我们对生化信号转导和传递的信息论治疗与数学模型相结合进行了以方法论为导向的综述。