Biology subjects

Colliver, E.

Publications and source records attributed to Colliver, E..

5 recordsLinked to original sources

bioRxiv2025

Oncogenic RAS activity is linked to immune priming and adenosine-driven immune evasion in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a leading cause of cancer death worldwide, with RAS signalling as a key oncogenic driver. Although KRAS mutations have been linked to immune evasion in preclinical models, the relationship between RAS activity and tumour immunity or response to immunotherapy in patients remains unclear. Here, we applied our previously validated RAS84 transcriptional signature to stratify LUAD patient cohorts and dissect the immune landscape associated with RAS signalling. We report that tumours with elevated RAS activity exhibited features of immune priming, including increased immune infiltration, interferon response, and immune checkpoint gene expression, and showed improved progression-free survival in an independent cohort of patients treated with anti-PD-1. Yet, in both LUAD tumours and cell lines, RAS activity also correlated with elevated immunosuppressive interstitial adenosine mediated by transcriptional regulation of several components of the adenosinergic pathway. In orthotopic pre-clinical models of high-RAS activity lung tumours, blocking adenosine signalling delayed tumour growth and improved response to anti-PD-1 and KRAS inhibition, with a significant effect on innate immunity. This study reveals a dual role for RAS signalling in tumour progression, fostering a pro-immunogenic environment whilst simultaneously dampening anti-tumoural immunity via mechanisms including extracellular adenosine accumulation. Stratifying patients based on RAS transcriptional activity, rather than genetic alterations alone, could inform immunotherapy strategies and improve clinical outcomes.

cancer biology↗

bioRxiv2024

Spatial proteomic analysis of a lung cancer model reveals regulatory T cells attenuate KRAS-G12C inhibitor-induced immune responses

We recently showed that lung tumor specific KRAS-G12C inhibition causes remodelling of the tumor immune microenvironment from cold to hot. As a result, KRAS-G12C inhibition is able to synergise with anti-PD-1 treatment, but only in tumor models that were already moderately responsive to immune checkpoint blockade at baseline. To investigate mechanisms that restrain immunotherapy sensitivity in non-responsive tumors, we used multiplex imaging mass cytometry to explore spatial patterns in the tumor microenvironment of the highly immune evasive KRAS mutant murine Lewis Lung Cancer model. Clustering of close neighbour information per cell allowed characterisation of spatial patterns or communities in the tissue. We identified a community harbouring features of localised T-cell activation, where CD4+ and CD8+ T cells and dendritic cells were gathered together. KRAS-G12C inhibition led to increased expression of PD-1 on T cells, CXCL9 expression by dendritic cells, together with increased proliferation and potential cytotoxicity of CD8+ T cells, indicating an effector response. However, we also observed a high incidence of regulatory T cells (Tregs) within this community, which had frequent contact with effector T cells, suggesting that Tregs may be able to dampen anti-tumoral immune responses following KRAS-G12C inhibition. Similar communities were detected in human lung adenocarcinoma clinical samples. Depleting Tregs in vivo with anti-CTLA-4 antibody rescued the anti-tumor immune response and led to enhanced tumor control in combination with anti-PD-1 and KRAS-G12C inhibitor. We therefore propose use of KRAS-G12C inhibitor in combination with Treg depletion as a therapeutic opportunity that increases anti-tumoral immune responses and initiates tumor regression. One sentence summarySpatial analysis identified regulatory T cells as potential source of local T cell repression, mediating resistance to KRAS-G12Ci and anti-PD1 therapy.

cancer biology↗

bioRxiv2024

Deciphering the diversity and sequence of extracellular matrix and cellular spatial patterns in lung adenocarcinoma using topological data analysis

Extracellular matrix (ECM) organization influences cancer development and progression. It modulates the invasion of cancer cells and can hinder the access of immune cells to cancer cells. Effective quantification of ECM architecture and its relationship to the position of different cell types is, therefore, important when investigating the role of ECM in cancer development. Using topological data analysis (TDA), particularly persistent homology and Dowker persistent homology, we develop a novel analysis pipeline for quantifying ECM architecture, spatial patterns of cell positions, and the spatial relationships between distinct constituents of the tumour microenvironment. We apply the pipeline to 44 surgical specimens of lung adenocarcinoma from the lung TRACERx study stained with picrosirius red and haematoxylin. We show that persistent homology effectively encodes the architectural features of the tumour microenvironment. Inference using pseudo-time analysis and spatial mapping to centimetre scale tissues suggests a gradual and progressive route of change in ECM architecture, with two different end states. Dowker persistent homology enables the analysis of spatial relationship between any pair of constituents of the tumour microenvironment, such as ECM, cancer cells, and leukocytes. We use Dowker persistent homology to quantify the spatial segregation of cancer and immune cells over different length scales. A combined analysis of both topological and non-topological features of the tumour microenvironment indicates that progressive changes in the ECM are linked to increased immune exclusion and reduced oxidative metabolism.

cancer biology↗

bioRxiv2022

cloneMap: a R package to visualise clonal heterogeneity

Genomic evolution and clonal heterogeneity in the soma are widespread and are involved in various pathologies with devastating consequences to human health, most prominently in neoplasia. Tools to interrogate and visualise the diversity of clonal populations in malignant or non-malignant tissues are currently lacking. cloneMap is a tool to represent clonal heterogeneity in a sample or set of samples, accounting for the clone size and phylogenetic relationships between clones. We apply cloneMap to several publicly available cancer sequencing datasets to demonstrate its ability to provide biological inferences of clonal heterogeneity. cloneMap is an R package available on github (https://github.com/amf71/cloneMap).

bioinformatics↗

bioRxiv2021

Characterisation of tumour immune microenvironment remodelling following oncogene inhibition in preclinical studies using an optimised imaging mass cytometry workflow

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.

cancer biology↗