Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX.

The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights.

Therapeutic KRASG12C inhibition drives effective interferon-mediated antitumor immunity in immunogenic lung cancers.

Recently developed KRASG12C inhibitory drugs are beneficial to lung cancer patients harboring KRASG12C mutations, but drug resistance frequently develops. Because of the immunosuppressive nature of the signaling network controlled by oncogenic KRAS, these drugs can indirectly affect antitumor immunity, providing a rationale for their combination with immune checkpoint blockade. In this study, we have characterized how KRASG12C inhibition reverses immunosuppression driven by oncogenic KRAS in a number of preclinical lung cancer models with varying levels of immunogenicity. Mechanistically, KRASG12C inhibition up-regulates interferon signaling via Myc inhibition, leading to reduced tumor infiltration by immunosuppressive cells, enhanced infiltration and activation of cytotoxic T cells, and increased antigen presentation. However, the combination of KRASG12C inhibitors with immune checkpoint blockade only provides synergistic benefit in the most immunogenic tumor model. KRASG12C inhibition fails to sensitize cold tumors to immunotherapy, with implications for the design of clinical trials combining KRASG12C inhibitors with anti-PD1 drugs.

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.