Characterisation of tumour microenvironment remodelling following oncogene inhibition in preclinical studies with imaging mass cytometry

Mouse models are critical in pre-clinical studies of cancer therapy, allowing dissection of mechanisms through chemical and genetic manipulations that are not feasible in the clinical setting. In studies of the tumour microenvironment (TME), multiplexed imaging methods can provide a rich source of information. However, the application of such technologies in mouse tissues is still in its infancy. Here we present a workflow for studying the TME using imaging mass cytometry with a panel of 27 antibodies on frozen mouse tissues. We optimise and validate image segmentation strategies and automate the process in a Nextflow-based pipeline (imcyto) that is scalable and portable, allowing for parallelised segmentation of large multi-image datasets. With these methods we interrogate the remodelling of the TME induced by a KRAS G12C inhibitor in an immune competent mouse orthotopic lung cancer model, highlighting the infiltration and activation of antigen presenting cells and effector cells. The tumour microenvironment (TME) may change in response to cancer treatments such as KRAS G12C inhibition, with potential implications for combination therapies. Here, the authors provide an antibody panel and workflow for analysing the TME with imaging mass cytometry in pre-clinical mouse models.

Automated summary

This study introduces a workflow for studying the TME in mouse models using imaging mass cytometry, allowing for optimized image segmentation strategies and automated processes for parallel segmentation of large multi-image datasets.