Diabetic retinopathy (DR) is a common complication of diabetes mellitus and a leading cause of visual impairment and blindness in the working-age population. The early stage of the disease is characterized by retinal capillary dysfunction, but the mechanisms whereby hyperglycemia disturbs capillary homeostasis at this initiating stage are poorly understood, posing a barrier to the development of effective early treatments. We used two mouse models of type I diabetes that replicate early features of human retinal vascular pathology. In both the streptozotocin (STZ) model, where hypoinsulinemia is chemically induced, and in the Ins2Akita model, which develops it spontaneously because of a mutation in the insulin gene, we observed early induction of the secreted glycoprotein gene leucine-rich α-2-glycoprotein 1 (Lrg1). Using the Ins2Akita mice, we showed that Lrg1 induction preceded that of vascular endothelial growth factor A (Vegfa). LRG1 initiated retinal microvascular dysfunction by modifying transforming growth factor-β (TGFβ) signaling in pericytes, driving transdifferentiation to a more contractile fibrotic phenotype, resulting in narrower capillaries and thickened basement membrane. Using computational modeling, we showed that these early vascular changes impaired retinal blood flow and oxygen delivery, consistent with a defect in visual transduction observed in both models. This early retinal phenotype could be rescued by Lrg1 knockout or by treatment with an LRG1 function-blocking antibody in both the STZ and Ins2Akita mice. These results demonstrate that LRG1 is a driver of vascular dysfunction that contributes to the onset of DR and presents itself as a potential preemptive therapeutic target.

Therapies targeting blood vessels hold promise for autosomal dominant polycystic kidney disease (ADPKD), the most common inherited disorder causing kidney failure. However, the onset and nature of kidney vascular abnormalities in ADPKD are poorly defined. Accordingly, we employed a combination of single-cell transcriptomics; three-dimensional imaging with geometric, topological and fractal analyses; and multimodal magnetic resonance imaging with arterial spin labelling to investigate aberrant microvasculature in ADPKD kidneys. Within human ADPKD kidneys with advanced cystic pathology and excretory failure, we identified a molecularly distinct blood microvascular subpopulation, characterised by impaired angiogenic signalling and metabolic dysfunction, differing from endothelial injury profiles observed in non-cystic human kidney diseases. Next, Pkd1 mutant mouse kidneys were examined postnatally, when cystic pathology is well established, but before excretory failure. An aberrant endothelial subpopulation was also detected, concurrent with reduced cortical blood perfusion. Disorganised kidney cortical microvasculature was also present in Pkd1 mutant mouse fetal kidneys when tubular dilation begins. Thus, aberrant features of cystic kidney vasculature are harmonised between human and mouse ADPKD, supporting early targeting of the vasculature as a strategy to ameliorate ADPKD progression.

Lymphatic vessels maintain tissue fluid homeostasis and modulate inflammation, yet their spatial organization and molecular identity in the healthy human kidney, and how these change during chronic transplant rejection, remain poorly defined. Here, we show that lymphatic capillaries initiate adjacent to cortical kidney tubules and lack smooth muscle coverage. These vessels exhibit an organ-specific molecular signature, enriched for CCL14, DNASE1L3, and MDK, with limited expression of canonical immune-trafficking markers found in other organ lymphatics, such as LYVE1 and CXCL8. In allografts with chronic mixed rejection, lymphatics become disorganized and infiltrate the medulla, with their endothelial junctions remodeling from a button-like to a continuous, zipper-like, architecture. Lymphatics in rejecting kidneys localize around and interconnect tertiary lymphoid structures at different maturation stages, with altered intralymphatic and perilymphatic CD4+ T cell distribution. The infiltrating T cells express IFN-γ, which upregulates coinhibitory ligands in lymphatic endothelial cells, including PVR and LGALS9. Simultaneously, lymphatics acquire HLA class II expression and exhibit C4d deposition, consistent with alloantibody binding and complement activation. Together, these findings define the spatial and molecular features of human kidney lymphatics, revealing tolerogenic reprogramming accompanied by structural perturbations during chronic transplant rejection.

Objectives Machine perfusion of organs outside of the body is a growing area of research with significant applications in the fields of organ preservation and transplantation, but more widely it offers a new approach to study disease processes and to evaluate new therapeutics and devices. Magnetic Resonance Imaging (MRI) allows for non-invasive assessment of organ structure and function, enabling quantitative measurement of tissue perfusion and microstructure. In this study, we demonstrate that MR imaging sequences can be obtained from machine-perfused porcine livers using a modified perfusion rig for MR compatibility and highlight the quantitative measures that can be obtained through this methodology. Materials and Methods 7 porcine livers were retrieved fresh from the abattoir using a previously published protocol and following transport in cold preservative underwent perfusion with oxygenated autologous blood inside a 3T clinical MRI scanner using a custom modified perfusion rig. Multiple MR imaging sequences were acquired: T2-weighted imaging, Diffusion Weighted Imaging and Dynamic Contrast Enhanced imaging following injection of Gadolinium dye into the portal vein and hepatic artery. Histological analysis was performed to assess preservation injury to the liver. Control samples for histology were obtained from livers with similar preservation periods but preserved in standard cold storage on ice (Static Cold Storage). Results Concurrent MR imaging and machine perfusion were successfully performed, allowing dynamic measurement of tissue perfusion to be obtained in ex vivo livers, including calculation of gadolinium contrast enhancement curves and Apparent Diffusion Coefficient maps. Segmentation of vessels down to a radius of 0.45mm allowed detailed morphological analysis of the vascular network, including extraction of clinically relevant parameters such as vessel tortuosity. Histological evaluation showed better preservation of the hepatic acinar structure in perfused than non-perfused livers. Conclusions Our results demonstrate that MR imaging of machine-perfused organs enables high-resolution quantitative evaluation of whole-organ vascular morphology and flow dynamics. This platform provides opportunities to study vascular pathology in diseased human organs and evaluate novel therapeutic interventions, with particular relevance for drug-delivery strategies. ### Competing Interest Statement The authors have declared no competing interest. * MRI : Magnetic Resonance Imaging DCE : Dynamic Contrast Enhancement DWI : Diffusion Weighted Imaging ADC : Apparent Diffusion Coefficient BTFE : Balanced Turbo Field Echo Cancer Research UK, C44767/A29458, C23017/A27935 Wellcome/EPSRC Centre for Interventional and Surgical Sciences, 203145/Z/16/Z Royal Free Charity, 1278/RD UCL EPSRC IAA Robot Assisted Organ Perfusion with Imaging and Sensing

Structural changes to microvascular networks are increasingly highlighted as markers of pathogenesis in a wide range of disease, e.g. Alzheimer’s disease, vascular dementia and tumour growth. This has motivated the development of dedicated 3D imaging techniques, alongside the creation of computational modelling frameworks capable of using 3D reconstructed networks to simulate functional behaviours such as blood flow or transport processes. Extraction of 3D networks from imaging data broadly consists of two image processing steps: segmentation followed by skeletonisation. Much research effort has been devoted to segmentation field, and there are standard and widely-applied methodologies for creating and assessing gold standards or ground truths produced by manual annotation or automated algorithms.The Skeletonisation field, however, lacks widely applied, simple to compute metrics for the validation or optimisation of the numerous algorithms that exist to extract skeletons from binary images. This is particularly problematic as 3D imaging datasets increase in size and visual inspection becomes an insufficient validation approach. In this work, we first demonstrate the extent of the problem by applying 4 widely-used skeletonisation algorithms to 3 different imaging datasets. In doing so we show significant variability between reconstructed skeletons of the same segmented imaging dataset. Moreover, we show that such a structural variability propagates to simulated metrics such as blood flow. To mitigate this variability we introduce a new, fast and easy to compute super metric that compares the volume, connectivity, medialness, bifurcation point identification and homology of the reconstructed skeletons to the original segmented data. We then show that such a metric can be used to select the best performing skeletonisation algorithm for a given dataset, as well as to optimise its parameters. Finally, we demonstrate that the super metric can also be used to quickly identify how a particular skeletonisation algorithm could be improved, becoming a powerful tool in understanding the complex implication of small structural changes in a network.

Abstract Background Carcinogenesis is driven by interactions between genetic mutations and the local tumor microenvironment. Recent research has identified hundreds of cancer driver genes; however, these studies often include a mixture of different molecular subtypes and ecological niches and ignore the impact of the immune system. Results In this study, we compare the landscape of driver genes in tumors that escaped the immune system (escape +) versus those that did not (escape −). We analyze 9896 primary tumors from The Cancer Genome Atlas using the ratio of non-synonymous to synonymous mutations (dN/dS) and find 85 driver genes, including 27 and 16 novel genes, in escape − and escape + tumors, respectively. The dN/dS of driver genes in immune escaped tumors is significantly lower and closer to neutrality than in non-escaped tumors, suggesting selection buffering in driver genes fueled by immune escape. Additionally, we find that immune evasion leads to more mutated sites, a diverse array of mutational signatures and is linked to tumor prognosis. Conclusions Our findings highlight the need for improved patient stratification to identify new therapeutic targets for cancer treatment.

Missions into Deep Space are planned this decade. Yet the health consequences of exposure to microgravity and galactic cosmic radiation (GCR) over years-long missions on indispensable visceral organs such as the kidney are largely unexplored. We performed biomolecular (epigenomic, transcriptomic, proteomic, epiproteomic, metabolomic, metagenomic), clinical chemistry (electrolytes, endocrinology, biochemistry) and morphometry (histology, 3D imaging, miRNA-ISH, tissue weights) analyses using samples and datasets available from 11 spaceflight-exposed mouse and 5 human, 1 simulated microgravity rat and 4 simulated GCR-exposed mouse missions. We found that spaceflight induces: 1) renal transporter dephosphorylation which may indicate astronauts’ increased risk of nephrolithiasis is in part a primary renal phenomenon rather than solely a secondary consequence of bone loss; 2) remodelling of the nephron that results in expansion of distal convoluted tubule size but loss of overall tubule density; 3) renal damage and dysfunction when exposed to a Mars roundtrip dose-equivalent of simulated GCR.

Disruption of retinal vasculature is linked to various diseases, including diabetic retinopathy and macular degeneration, leading to vision loss. We present here a novel algorithmic approach that generates highly realistic digital models of human retinal blood vessels based on established biophysical principles, including fully-connected arterial and venous trees with a single inlet and outlet. This approach, using physics-informed generative adversarial networks (PI-GAN), enables the segmentation and reconstruction of blood vessel networks that requires no human input and out-performs human labelling. Our findings highlight the potential of PI-GAN for accurate retinal vasculature characterization, with implications for improving early disease detection, monitoring disease progression, and improving patient care.

Cancer hallmarks describe key physiological characteristics that distinguish cancers from normal tissues. The temporal order in which these hallmarks appear during cancer pathogenesis is of interest from both evolutionary and clinical perspectives but has not been investigated before. Here, we order hallmarks based on the allele frequency and selective advantage of mutations in cancer hallmark genes across >10k untreated primary tumors and >8K healthy tissues. Using this novel approach, we identified a common evolutionary trajectory for 27 of 32 cancer types with genomic instability as the first and immune evasion as the last hallmark. We demonstrated widespread positive selection in cancer and strong negative selection in normal tissues for all hallmarks. Notable exceptions to the hallmark ordering in tumours were melanomas (uveal and skin) suggesting that strong environmental factors could disrupt common evolutionary paths. Clustering of hallmark trajectories across patients revealed 2 clusters defined by early or late genomic instability, with differential prognosis. Our study is the first to identify the temporal order of cancer hallmarks during tumorigenesis and demonstrate a prognostic value that could be exploited for early detection and risk stratification across multiple cancer types.### Competing Interest StatementThe authors have declared no competing interest.

We present a 3D discrete-continuum model to simulate blood pressure in large microvascular tissues in the absence of known capillary network architecture. Our hybrid approach combines a 1D Poiseuille flow description for large, discrete arteriolar and venular networks coupled to a continuum-based Darcy model, point sources of flux, for transport in the capillary bed. We evaluate our hybrid approach using a vascular network imaged from the mouse brain medulla/pons using multi-fluorescence high-resolution episcopic microscopy (MF-HREM). We use the fully-resolved vascular network to predict the hydraulic conductivity of the capillary network and generate a fully-discrete pressure solution to benchmark against. Our results demonstrate that the discrete-continuum methodology is a computationally feasible and effective tool for predicting blood pressure in real-world microvascular tissues when capillary microvessels are poorly defined.

Though the earliest stages of oncogenesis, post initiation, are not well understood, it is generally appreciated that a successful transition from a collection of dysregulated cells to an aggressive tumour requires complex ecological interactions between cancer cells and their environment. One key component of tumorigenesis is immune evasion. To investigate the interplay amongst the ecological behaviour of mutualism and immune evasion, we used a computational simulation framework. Sensitivity analyses of the growth of a virtual tumour implemented as a 2D-hexagonal lattice model suggests tumour survival depends on the interplay between growth rates, mutualism and immune evasion. In 60% of simulations, cancer clones with low growth rates, but exhibiting mutualism were able to evade the immune system and continue progressing suggesting that tumours with equivalent growth rates and no mutualism are more likely to be eliminated than tumours with mutualism. Tumours with faster growth rates showed a lower dependence upon mutualism for progression. Geostatistical analysis showed decreased spatial heterogeneity over time for polyclonal tumours with a high division rate. Overall, these results suggest that in slow growing tumours, mutualism is critical for early tumorigenesis.

Hallmarks of autosomal dominant polycystic kidney disease (ADPKD), the most common hereditary kidney anomaly, include expanding fluid-filled epithelial cysts, inflammation, and fibrosis. Despite previous work showing the potential of vascular-based therapies, renal microvascular alterations in ADPKD, and their timing, are poorly understood. Using single-cell transcriptomics of human kidney microvasculature, we identify a population of endothelial cells adjacent to cysts in ADPKD. This pericystic endothelium, distinguishable by its expression of osteopontin (SPP1), has a distinct molecular profile compared to the common endothelial cell injury signature in other kidney diseases. SPP1+ pericystic endothelium was also present in an orthologous mouse model of ADPKD before overt kidney functional decline. By interrogating geometric, topological and fractal properties from three-dimensional imaging of early ADPKD mouse kidneys, we show that pericystic endothelium associates with disorganisation and non-uniformity of the renal cortical microvasculature. Concurrently, we detected region-specific reductions in cortical blood flow within ADPKD murine kidneys using arterial spin labelling. We conclude that ADPKD kidneys contain a unique subset of endothelium manifesting with aberrant remodelling and impaired blood perfusion. Its detection, prior to renal functional decline, advocates the vasculature as a therapeutic target to modulate or preserve renal function in early ADPKD. ### Competing Interest Statement The authors have declared no competing interest.

Supplemental Movie 4: Animated EVAC streamlines (grey lines), showing the path taken by interstitial fluid, overlaid on vascular perfusion measurements (colour scale, measured in vivo using arterial spin labelling) and the location of blood vessels (yellow structures, measured ex vivo using micro-CT). The data were acquired in an SW1222 colorectal carcinoma tumour xenograft.

Vascularization is driven by morphogen signals and mechanical cues that coordinately regulate cellular force generation, migration, and shape change to sculpt the developing vascular network. However, it remains unclear whether developing vasculature actively regulates its own mechanical properties to achieve effective vascularization. We engineered tissue constructs containing endothelial cells and fibroblasts to investigate the mechanics of vascularization. Tissue stiffness increases during vascular morphogenesis resulting from emergent interactions between endothelial cells, fibroblasts, and ECM and correlates with enhanced vascular function. Contractile cellular forces are key to emergent tissue stiffening and synergize with ECM mechanical properties to modulate the mechanics of vascularization. Emergent tissue stiffening and vascular function rely on mechanotransduction signaling within fibroblasts, mediated by YAP1. Mouse embryos lacking YAP1 in fibroblasts exhibit both reduced tissue stiffness and develop lethal vascular defects. Translating our findings through biology-inspired vascular tissue engineering approaches will have substantial implications in regenerative medicine.

Supplemental Movie 3: Animated EVAC streamlines (grey lines), showing the path taken by interstitial fluid, overlaid on vascular perfusion measurements (colour scale, measured in vivo using arterial spin labelling) and the location of blood vessels (yellow structures, measured ex vivo using micro-CT). The data were acquired in an LS174T colorectal carcinoma tumour xenograft.

Complex interactions between the physical environment and phenotype of a tumour, and genomics, transcriptomics, proteomics and epigenomics, are increasingly known to have a significant influence on cancer development, progression and evolution. For example, mechanical stress can alter both genome maintenance and histone modifications, which consequently affect transcription and the epigenome. Increased stiffness has been linked to genetic heterogeneity and is responsible for heterochromatin accumulations. Stiffness thereby leads to deregulation in gene expression, disrupts the proteome and can impact angiogenesis. Several studies have shown how the physics of cancer can influence diverse cancer hallmarks such as resistance to cell death, angiogenesis and evasion from immune destruction. In this review, we will explain the role that physics of cancer plays in cancer evolution and explore how multiomics are being used to elucidate the mechanisms underpinning them.

Supplemental Movie 5: Interstitial convection, measured using EVAC-MRI and animated using a particle simulation (left), compared with MRI signal enhancement with time, following injection with a contrast agent (Gd-DTPA), in an LS174T tumour.