Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:3063-3067. doi: 10.1109/EMBC48229.2022.9871251.
Multiplexed immunofluorescence provides an un-precedented opportunity for studying specific cell-to-cell and cell microenvironment interactions. We employ graph neural networks to combine features obtained from tissue morphology with measurements of protein expression to profile the tumour microenvironment associated with different tumour stages. Our framework presents a new approach to analysing and processing these complex multi-dimensional datasets that overcomes some of the key challenges in analysing these data and opens up the opportunity to abstract biologically meaningful interactions.
多重免疫荧光为研究特定细胞间和细胞微环境相互作用提供了前所未有的机会。我们利用图神经网络将组织形态学获得的特征与蛋白质表达测量值相结合，以分析与不同肿瘤阶段相关的肿瘤微环境。我们的框架提出了一种新的分析和处理这些复杂多维数据集的方法，克服了分析这些数据的一些关键挑战，并为提取有生物学意义的相互作用提供了机会。
