The tumour microenvironment plays a fundamental role in understanding the development and progression of cancer. This paper proposes a novel spatial point process model that accounts for inhomogeneity and interaction to flexibly model a complex database of cells in the tumour immune microenvironments of a cohort of patients with non-small-cell lung cancer whose samples have been processed using digital pathology techniques. Specifically, an inhomogeneous multitype Gibbs point process model with an associated Fiksel-type interaction function is proposed. Estimation and inference procedures are conducted through maximum pseudolikelihood, considering replicated multitype point patterns.

翻译：肿瘤微环境在理解癌症的发生和发展中起着基础性作用。本文提出了一种新颖的空间点过程模型，该模型考虑了非均匀性和交互作用，以灵活地建模一组非小细胞肺癌患者的肿瘤免疫微环境中的复杂细胞数据库，这些患者的样本已通过数字病理学技术处理。具体而言，本文提出了一种非均匀多类型吉布斯点过程模型，该模型具有相关的Fiksel型交互函数。通过考虑重复的多类型点模式，利用最大伪似然方法进行了估计和推断过程。