Biology subjects

Dunne, P.

Publications and source records attributed to Dunne, P..

7 recordsLinked to original sources

bioRxiv2025

Runx1 and Runx2 act in concert to suppress Wnt/β-catenin-driven mammary tumourigenesis

The genes encoding transcription factor RUNX1 and its binding partner CBFB have been reported to be mutated in human breast cancer. Here, we provide evidence that Runx1 loss of function results in accelerated disease onset and tumour development in mouse models of breast cancer, in keeping with a tumour suppressor role for RUNX1 in this disease setting. Combined deletion of Runx1 and the related family member Runx2 resulted in mammary epithelial cells becoming exquisitely sensitive to WNT-driven transformation, with the emergence of multiple tumours early in life. Clonogenic assays indicated that Runx1 ablation induced a stem cell like phenotype in mammary epithelial cells, whilst transcriptome analysis demonstrated activation of multiple oncogenic pathways, especially when Runx2 was co- deleted. Interestingly, altered Runx expression in the mammary epithelium also drove profound alterations in the tumour microenvironment, impacting the immune landscape. These results highlight that Runx1 restricts some forms of breast cancer and inhibits the full oncogenic potential of aberrant WNT signalling. Loss of Runx2 itself did not result in tumour promotion, yet the dramatic effects of combined Runx1 and Runx2 loss suggest that Runx2 can substitute for Runx1 in dampening the oncogenic effects of WNT signalling.

cancer biology↗

bioRxiv2025

The characteristic of epithelial-specific phenotypes and immunosuppressive microenvironment in the context of tumour budding in colorectal cancer

BackgroundTumour budding (TB), defined as a small cluster of up to four cells at the invasive front of the tumour, is a well-established independent and robust prognostic biomarker in colorectal cancer (CRC). This is strongly associated with adverse clinicopathological features and poor survival outcomes. Despite its clinical relevance, the precise underlying mechanism responsible for TB phenomenon remains unclear. MethodsMulti-omic approaches from bulk, regional GeoMx and Spatial Molecular Imager (SMI) RNA were used to identify the underlying mechanism of TB and its possible correlation with tumour microenvironment (TME) in CRC tissue. The results were validated using immunohistochemistry (IHC) and multiplex immunofluorescence (mIF) staining. ResultsPatients with high TB experience worse outcomes and associate with adverse clinical factors across two independent CRC cohorts. Bulk and regional RNA expression analyses reveal that tumours with high TB are significantly enriched for TNF- and TGF-{beta} signatures in both cohorts. Single cell CosMx SMI analysis confirmed TB cells exhibit higher expression of these signatures than adjacent invasive edge tumour cells. Elevated cyclinD1 expression was also observed within TB, and high cyclinD1 levels tend to experience poorer CRC prognosis. Furthermore, regional bulk RNA expression within the non-tumour (PanCK-) invasive edge areas demonstrated that tumours exhibiting high TB revealed the significantly differential expressions of immune-related genes (e.g. CD3, NKG7, IL6, CXCR6, CD47, IFNAR1 and VSIR). Single cell CosMx SMI analysis revealed that cancer-associated fibroblasts (CAFs) were physically the closest cells to TB cells. This spatial proximity was confirmed at the protein level using mIF, where the distance from TB to CD68+ macrophages predicted significantly poorer CRC outcomes. ConclusionThis multi-omic study confirms the prognostic significance of TB in CRC patients across two independent cohorts. Our findings highlight that TNF- and TGF-{beta} signalling play a crucial role in budding cells development by regulating cyclinD1. Furthermore, the transcriptomic analysis reveals an immunosuppressive niche characterised by reduced immune activity and close spatial interactions with CAFs and macrophages Ultimately, this study provides valuable insight into TBs underlying mechanism and its complex interactions within the TME. This could provide a foundation for developing targeted therapeutic strategies in CRC.

cancer biology↗

bioRxiv2025

Identification of a novel GREMLIN1 uptake pathway in epithelial cells that requires BMP binding

Gremlin1 is a member of a cysteine-knot containing family of secreted antagonists of bone morphogenetic protein signaling. GREM1 binding to BMP targets prevents their engagement with cognate BMP receptors, attenuating BMP-dependent gene expression. Some evidence suggests that GREM1 can directly bind to receptor tyrosine kinases on the plasma membrane, further complicating our understanding of GREM1 biology. To attempt to clarify the modalities of GREM1 signaling, we show that GREM1 protein is produced and secreted by intestinal fibroblasts and endocytosed by neighbouring epithelial cells. GREM1 uptake is a slow process and occurs by both clathrin- and caveolin-mediated endocytosis. Cell membrane heparin sulfate proteoglycans are required for GREM1 binding and uptake, and once internalised, GREM1 appears to localise to the early endosomes. Addition of BMP2 enhanced GREM1 uptake into cells. Remarkably, generation of a BMP-resistant GREM1 mutant abolished GREM1 uptake both in the presence and absence of BMP2. These data suggest that GREM1 binding and uptake into cells requires BMP binding, a process that may contribute to the antagonism of BMP signaling by GREM1. SummaryIn this article, we demonstrate differential GREM1 mRNA versus protein expression in mouse intestine. We also identify a novel GREM1 endocytosis pathway whereby mammalian cells take up GREM1 protein in what appears to be a BMP-dependent mechanism.

cell biology↗

bioRxiv2024

Uridine Phosphorylase-1 supports metastasis of mammary cancer by altering immune and extracellular matrix landscapes of the lung

Understanding the mechanisms that facilitate early events in metastatic seeding is key to developing therapeutic approaches to reduce metastasis - the leading cause of cancer-related death. Using whole animal screens in genetically engineered mouse models of cancer we have identified circulating metabolites associated with metastasis. Specifically, we highlight the pyrimidine uracil as a prominent metastasis-associated metabolite. Uracil is generated by neutrophils expressing the enzyme uridine phosphorylase-1 (UPP1), and neutrophil specific Upp1 expression is increased in cancer. Altered UPP1 activity influences expression of adhesion molecules on the surface of neutrophils, leading to decreased neutrophil motility in the pre-metastatic lung. Furthermore, we find that UPP1-expressing neutrophils suppress T-cell proliferation, and the UPP1 product uracil can increase fibronectin deposition in the extracellular microenvironment. Consistently, knockout or inhibition of UPP1 in mice with mammary tumours increases the number of T-cells and reduces fibronectin content in the lung and decreases the proportion of mice that develop lung metastasis. These data indicate that UPP1 influences neutrophil behaviour and extracellular matrix deposition in the lung and suggest that pharmacological targeting of this pathway could be an effective strategy to reduce metastasis.

cancer biology↗

bioRxiv2022

MmCMS: Mouse models' Consensus Molecular Subtypes of colorectal cancer

BACKGROUNDColorectal cancer (CRC) primary tumours are molecularly classified into four consensus molecular subtypes (CMS1-4). Genetically engineered mouse models aim to faithfully mimic the complexity of human cancers and, when appropriately aligned, represent ideal pre-clinical systems to test new drug treatments. Despite its importance, dual-species classification has been limited by the lack of a reliable approach. Here we utilise, develop and test a set of options for human-to-mouse CMS classifications of CRC tissue. METHODSUsing transcriptional data from established collections of CRC tumours, including human (TCGA cohort; n=577) and mouse (n=57 across n=8 genotypes) tumours with combinations of random forest and nearest template prediction algorithms, alongside gene ontology collections, we comprehensively assess the performance of a suite of new dual-species classifiers. RESULTSWe developed three approaches: MmCMS-A; a gene-level classifier, MmCMS-B; an ontology-level approach and MmCMS-C; a combined pathway system encompassing multiple biological and histological signalling cascades. Although all options could identify tumours associated with stromal-rich CMS4-like biology, MmCMS-A was unable to accurately classify the biology underpinning epithelial-like subtypes (CMS2/3) in mouse tumours. CONCLUSIONSWhen applying human-based transcriptional classifiers to mouse tumour data, a pathway-level classifier, rather than an individual gene-level system, is optimal. Our R package with three options helps researchers select suitable mouse models of human CRC subtype for their experimental testing.

cancer biology↗

bioRxiv2021

An atlas of inter- and intra-tumor heterogeneityof apoptosis competency in colorectal cancertissue at single cell resolution

Cancer cells ability to inhibit apoptosis is key to malignant transformation and limits response to therapy. Here, we performed multiplexed immunofluorescence analysis on tissue microarrays with 373 cores from 168 patients, segmentation of 2.4 million individual cells and quantification of 20 cell lineage and apoptosis proteins. Ordinary differential equation-based modelling of apoptosis sensitivity at single cell resolution was conducted and an atlas of inter- and intra-tumor heterogeneity in apoptosis susceptibility generated. We identified an enrichment for BCL2 in immune, and BAK, SMAC and XIAP in cancer cells. ODE-based modelling at single cell resolution identified an enhanced sensitivity of cancer cells to mitochondrial permeabilization and executioner caspase activation compared to immune and stromal cells, with significant inter- and intra-tumor heterogeneity. However, we did not find increased spatial heterogeneity of apoptosis signaling in cancer cells, suggesting that such heterogeneity is an intrinsic, non-genomic property not increased by the process of malignant transformation.

cancer biology↗

bioRxiv2019

Image-based consensus molecular subtype classification (imCMS) of colorectal cancer using deep learning

Image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data. Here we predict consensus molecular subtypes (CMS) of colorectal cancer (CRC) from standard H&E sections using deep learning. Domain adversarial training of a neural classification network was performed using 1,553 tissue sections with comprehensive multi- omic data from three independent datasets. Image-based consensus molecular subtyping (imCMS) accurately classified CRC whole-slide images and preoperative biopsies, spatially resolved intratumoural heterogeneity and provided accurate secondary calls with higher discriminatory power than bioinformatic prediction. In all three cohorts imCMS established sensible classification in CMS unclassified samples, reproduced expected correlations with (epi)genomic alterations and effectively stratified patients into prognostic subgroups. Leveraging artificial intelligence for the development of novel biomarkers extracted from histological slides with molecular and biological interpretability has remarkable potential for clinical translation.

cancer biology↗