Cancer is a complex phenomenon, and the sheer variation in behaviour across different types renders it difficult to ascertain underlying biological mechanisms. Experimental approaches frequently yield conflicting results for myriad reasons, and mathematical modelling of cancer is a vital tool to explore what we cannot readily measure, and ultimately improve treatment and prognosis. Like experiments, models are underpinned by certain biological assumptions, variation of which can lead to divergent predictions. An outstanding and important question concerns contact inhibition of proliferation (CIP), the observation that proliferation ceases when cells are spatially confined by their neighbours. CIP is a characteristic of many healthy adult tissues, but it remains unclear to which extent it holds in solid tumours, which exhibit regions of hyper-proliferation, and apparent breakdown of CIP. What precisely occurs in tumour tissue remains an open question, which mathematical modelling can help shed light on. In this perspective piece, we explore the implications of different hypotheses and available experimental evidence to elucidate the implications of these scenarios. We also outline how erroneous conclusions about the nature of tumour growth may be arrived at by looking selectively at biological data in isolation, and how this might be circumvented.

中文翻译：

---

细胞种类的近距离接触：接触抑制对肿瘤生长和癌症模型的影响


癌症是一种复杂的现象，不同类型的行为存在巨大差异，因此很难确定潜在的生物学机制。由于多种原因，实验方法经常会产生相互矛盾的结果，而癌症的数学模型是探索我们无法轻易测量的事物并最终改善治疗和预后的重要工具。与实验一样，模型也以某些生物学假设为基础，这些假设的变化可能会导致不同的预测。一个突出且重要的问题涉及增殖的接触抑制（CIP），即当细胞在空间上受到邻近细胞限制时增殖就会停止。 CIP 是许多健康成人组织的特征，但目前尚不清楚它在实体瘤中的存在程度，实体瘤表现出过度增殖的区域和 CIP 的明显分解。肿瘤组织中到底发生了什么仍然是一个悬而未决的问题，数学模型可以帮助揭示这一点。在这篇透视文章中，我们探讨了不同假设和可用实验证据的含义，以阐明这些场景的含义。我们还概述了如何通过选择性地孤立地观察生物数据来得出关于肿瘤生长性质的错误结论，以及如何避免这种情况。