Biology subjects

Hardman, D.

Publications and source records attributed to Hardman, D..

6 recordsLinked to original sources

bioRxiv2026

Kindlin-1 loss disrupts vascular and extracellular matrix organisation to sustain hypoxia in cutaneous squamous cell carcinoma

Kindlin-1, encoded by FERMT1, is an essential integrin co-activator that regulates cell-extracellular matrix (ECM) adhesion, tissue architecture, and microenvironment signalling. Loss-of-function mutations in FERMT1 cause Kindler epidermolysis bullosa, which is strongly associated with aggressive cutaneous squamous cell carcinoma (cSCC). Although Kindlin-1 deficiency promotes hypoxia and invasion, the impacts on ECM-vascular organisation and oxygen homeostasis are not known. Here, using genetic deletion of Kindlin-1 in a murine model of cSCC across 2D cultures, 3D spheroids, and in vivo tumours, combined with collagen and vascular imaging and spatial mixed-effects modelling, we show that Kindlin-1 loss uncouples ECM-vascular regulation, driving hypoxia and tumour progression. Tumours in which Kindlin-1 was deleted displayed a dense but dysfunctional vascular network, with reduced tissue-to-vessel and inter-bifurcation distances, increased vessel alignment, and persistent hypoxia despite increased vascular density. Collagen deposition was reduced and fibres were straighter, indicating a simplified, invasion-permissive matrix. Hypoxia increased Vegfa and Angpt1 expression while reducing Col1a1, and hypoxia-responsive spheroids confirmed greater hypoxia and invasiveness in Kindlin-1-deficient cells. Transcriptomic analysis revealed enrichment of ECM degradation and vascular dysfunction pathways, including upregulation of matrix-remodelling and vascular permeability genes such as Mmp13, Mmp3, and Ptgs2, alongside reduced collagen-associated and vascular homeostasis genes. Spatial modelling further showed disrupted collagen-vascular coupling and an association between hypoxia and reduced vessel diameter, consistent with dysfunctional angiogenesis rather than improved perfusion. These changes arose early and independently of tumour size, establishing impaired integrin activation as a central mechanism linking ECM degradation, vascular dysfunction, and sustained hypoxia in aggressive cSCC.

cancer biology↗

bioRxiv2025

Disrupted endothelial cell-cell dynamics in ALK1 and SMAD4 deficiency drive arteriovenous malformations

Arteriovenous malformations (AVMs) are a hallmark of hereditary haemorrhagic telangiectasia (HHT) and arise from abnormal vascular remodelling. Although AVM formation has been associated with disruptions in the BMP9/10 signalling pathway, the distinct contributions of its components remain unclear. Here, we combine in vitro mosaic endothelial cell (EC) cultures with agent-based modelling (ABM) to investigate how knockdown of the BMP9/10 pathway components ALK1 and SMAD4 alters cell-cell interactions and collective vascular organisation. Using cell tracking data, we inferred the mechanical interactions between neighbouring ECs in 2D monolayers by applying Approximate Bayesian Computation to an ABM of cell migration. SMAD4 knockdown increased the motile forces generated by ECs, while ALK1 knockdown weakened the ability of cells to push apart and rearrange with their neighbours, both resulting in greater mixing and fluidity within the cell layer. When these altered interaction profiles were incorporated into an ABM of collective EC dynamics during vascular remodelling, they gave rise to distinct AVM-prone phenotypes. SMAD4-deficient populations exhibited local blockages as highly polarised cells migrated excessively, whereas ALK1-deficient populations disrupted vascular patterning by impairing coordinated polarity and neighbour separation, favouring flow reversal. Our findings suggest that canonical BMP9/10 pathway defects destabilise the biomechanical balance of endothelial interactions, leading to emergent collective behaviours that predispose vessels to AVM formation. Significance StatementArteriovenous malformations (AVMs) are abnormal connections between arteries and veins that disrupt blood flow and can cause stroke or life-threatening bleeding. They are a hallmark of hereditary haemorrhagic telangiectasia (HHT), a genetic vascular disorder, but the cellular events that initiate AVMs remain unclear. Using a combination of endothelial cell cultures and computational modelling, we show that loss of two key HHT-linked genes, ALK1 and SMAD4, disrupts the coordinated movement and interactions of endothelial cells. Although both deficiencies lead to AVM-like behaviours, they do so through distinct mechanisms. SMAD4 loss drives excessive collective migration, whereas ALK1 loss impairs polarity and neighbour separation. These findings provide a mechanistic framework for how genetic defects could contribute to cell-cell dynamics observed in vascular malformations.

cell biology↗

bioRxiv2025

Identifying tissue states by spatial protein patterns related to chemotherapy response in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is an aggressive malignancy with limited targeted therapies and variable responses to conventional chemotherapy, influenced by intratumoral heterogeneity and complex tumor microenvironment (TME) interactions. Understanding spatiotemporal cellular interplay and tissue organization is crucial for advancing tumor biology and improving patient stratification. Spatially resolved proteomics, such as Imaging Mass Cytometry (IMC), offers a powerful approach to dissect the TME. We present an end-to-end computational pipeline for robust quantitative analysis of large-scale IMC datasets, addressing the challenge of batch effects through image-level contrast adjustment. Applying this framework to 813 tissue regions encompassing over 4 million cells from 63 TNBC patients, we revealed distinct spatial arrangements of cell types between chemotherapy responders and non-responders. Non-responders showed reduced cytotoxic T-cell infiltration into tumor regions and increased spatial co-localization between fibroblasts and macrophages, a pattern that persisted and intensified after chemotherapy treatment. To integrate these complex spatial-molecular relationships, we used graph neural networks (GNNs) to predict treatment response from pre-treatment samples with AUROC=0.71. Interpretability analysis identified B7H4, CD11b, CD366, and FOXP3 as the most predictive protein markers, with fibroblasts, cancer cells, and CD8+ T cells being the most informative cell types. This study introduces a scalable analytical framework for spatial proteomics with interpretable predictions, suggesting features of tissue state that could guide treatment decisions in TNBC and further our understanding of the spatial determinants of therapeutic response.

cancer biology↗

bioRxiv2022

Generating fast-twitch myotubes in vitro using an optogenetic-based, quantitative contractility assay

The composition of fiber types within skeletal muscle impacts the tissues physiological characteristics and susceptibility to disease and ageing. In vitro systems should therefore account for fiber type composition when modelling muscle conditions. To induce fiber specification in vitro, we designed a quantitative contractility assay based on optogenetics and particle image velocimetry. We submitted cultured myotubes to long-term intermittent light stimulation patterns and characterized their structural and functional adaptations. After several days of in vitro exercise, myotubes contract faster and are more resistant to fatigue. The enhanced contractile functionality was accompanied by advanced maturation such as increased width and upregulation of neuron receptor genes. We observed an upregulation in the expression of distinct myosin heavy chain isoforms (namely, neonatal-Myh8 and fast-Myh), which induced a shift towards a fast fiber phenotype. This long-term in vitro exercise strategy can be used to study fiber specification and refine muscle disease modelling.

cell biology↗

bioRxiv2021

An in vitro - agent based modelling approach to optimisation of culture medium for generating muscle cells

Methodologies for culturing muscle tissue are currently lacking in terms of quality and quantity of mature cells produced. We analyse images from in vitro experiments to quantify the effects of culture media composition on mouse-derived myoblast behaviour and myotube quality. Computational modelling was used to predict an optimum media composition for culturing. Metrics of early indicators of cell quality were defined. Images of muscle cell differentiation reveal that altering culture media significantly affects quality indicators and myoblast migratory behaviours. To predict cell quality from early-stage myoblast behaviours, metrics drawn from experimental images or inferred by Approximate Bayesian Computation were applied as inputs to an agent-based model (ABM) of differentiation with quality indicator metrics as outputs. We describe cell behaviours as a set of functions of media composition to predict cell quality using the ABM. Our results suggest that culturing muscle cells in neural cell differentiation medium reduces cell-cell fusion but does not diminish cell quality and that increasing serum concentration increases myoblast fusion implying a trade-off between the quantity and quality of cells produced when choosing a culture medium. Our model provided a good prediction of experimental results for media with 5% serum provided the myoblast proliferation rate was known. Author summaryFunctional skeletal muscle tissue can be grown in the lab but is most useful if the constituent muscle cells behave as they would in vivo. Optimising the conditions to promote precursor muscle cell fusion and growth is therefore vital. With many different factors influencing cell growth finding optimal conditions through rounds of experimentation alone is difficult especially as we strive to complexify our cultures with multiple cell types. We created metrics quantifying mature muscle cell quality at an early stage of development and applied them to experiments with a variety of culture media compositions. Changing the concentration of serum and proportion of neuron differentiation medium produced differences in the behaviour of fusing cells and in the quality and quantity of mature cells. From these results we created phenomenological models describing the behaviour of fusing cells for any combination of serum and neuron medium concentration. We integrated these models into a multiscale agent-based computational model of cell fusion to predict cell quality and quantity through virtual experiments in an emergent fashion. Our model suggests that choosing culture media composition will involve fundamental compromises between cell quantity and quality and that cells which initially fuse quickly may produce less final yield.

bioengineering↗

bioRxiv2020

Vessel compression biases red blood cell partitioning at bifurcations in a haematocrit-dependent manner: implications for tumour blood flow

The tumour microenvironment is abnormal and associated with tumour tissue hypoxia, immunosuppression, and poor response to treatment. One important abnormality present in tumours is vessel compression. Vessel decompression has been shown to increase survival rates in animal models via enhanced and more homogeneous oxygenation. However, our knowledge of the biophysical mechanisms linking tumour decompression to improved tumour oxygenation is limited. In this study, we propose a computational model to investigate the impact of vessel compression on red blood cell (RBC) dynamics in tumour vascular networks. Our results demonstrate that vessel compression can alter RBC partitioning at bifurcations in a haematocrit-dependent and flowrate-independent manner. We identify RBC focussing due to cross-streamline migration as the mechanism responsible and characterise the spatiotemporal recovery dynamics controlling downstream partitioning. Based on this knowledge, we formulate a reduced-order model that will help future research to elucidate how these effects propagate at a whole vascular network level. These findings contribute to the mechanistic understanding of haemodilution in tumour vascular networks and oxygen homogenisation following pharmacological solid tumour decompression.

cancer biology↗