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Type 2 diabetes mellitus is a major risk factor for hepatocellular carcinoma (HCC). Changes in extracellular matrix (ECM) mechanics contribute to cancer development 1 , 2 , and increased stiffness is known to promote HCC progression in cirrhotic conditions 3 , 4 . Type 2 diabetes mellitus is characterized by an accumulation of advanced glycation end-products (AGEs) in the ECM; however, how this affects HCC in non-cirrhotic conditions is unclear. Here we find that, in patients and animal models, AGEs promote changes in collagen architecture and enhance ECM viscoelasticity, with greater viscous dissipation and faster stress relaxation, but not changes in stiffness. High AGEs and viscoelasticity combined with oncogenic β-catenin signalling promote HCC induction, whereas inhibiting AGE production, reconstituting the AGE clearance receptor AGER1 or breaking AGE-mediated collagen cross-links reduces viscoelasticity and HCC growth. Matrix analysis and computational modelling demonstrate that lower interconnectivity of AGE-bundled collagen matrix, marked by shorter fibre length and greater heterogeneity, enhances viscoelasticity. Mechanistically, animal studies and 3D cell cultures show that enhanced viscoelasticity promotes HCC cell proliferation and invasion through an integrin-β1–tensin-1–YAP mechanotransductive pathway. These results reveal that AGE-mediated structural changes enhance ECM viscoelasticity, and that viscoelasticity can promote cancer progression in vivo, independent of stiffness. Structural changes mediated by advanced glycation end-products enhance extracellular matrix viscoelasticity, and that viscoelasticity can promote cancer progression in vivo, independent of stiffness.

Molecular imaging using positron emission tomography (PET) provides sensitive detection and mapping of molecular targets. While cancer-associated fibroblasts and integrins have been proposed as targets for imaging of pancreatic ductal adenocarcinoma (PDAC), herein, spatial transcriptomics and proteomics of human surgical samples are applied to select PDAC targets. We find that selected cancer cell surface markers are spatially correlated and provide specific cancer localization, whereas the spatial correlation between cancer markers and immune-related or fibroblast markers is low. Claudin-4 expression increases ~16 fold in cancer as compared with normal pancreas, and tight junction localization confers low background for imaging in normal tissue. We develop a peptide-based molecular imaging agent targeted to claudin-4 with accumulation to ~25% injected activity per cubic centimeter (IA/cc) in metastases and ~18% IA/cc in tumors. Our work motivates a data-driven approach to selection of molecular targets. Improved imaging methods are crucial to map pancreatic ductal adenocarcinoma (PDAC). Here, the authors analyse PDAC samples using spatial transcriptomics and proteomics, identify claudin-4 as a potential theranostic target, and develop an imaging agent to track claudin-4 in primary and metastatic PDAC tumours.

Background Liver alignment between series/exams is challenged by dynamic morphology or variability in patient positioning or motion. Image registration can improve image interpretation and lesion co-localization. We assessed the performance of a convolutional neural network algorithm to register cross-sectional liver imaging series and compared its performance to manual image registration. Methods Three hundred fourteen patients, including internal and external datasets, who underwent gadoxetate disodium-enhanced magnetic resonance imaging for clinical care from 2011 to 2018, were retrospectively selected. Automated registration was applied to all 2,663 within-patient series pairs derived from these datasets. Additionally, 100 within-patient series pairs from the internal dataset were independently manually registered by expert readers. Liver overlap, image correlation, and intra-observation distances for manual versus automated registrations were compared using paired t tests. Influence of patient demographics, imaging characteristics, and liver uptake function was evaluated using univariate and multivariate mixed models. Results Compared to the manual, automated registration produced significantly lower intra-observation distance ( p < 0.001) and higher liver overlap and image correlation ( p < 0.001). Intra-exam automated registration achieved 0.88 mean liver overlap and 0.44 mean image correlation for the internal dataset and 0.91 and 0.41, respectively, for the external dataset. For inter-exam registration, mean overlap was 0.81 and image correlation 0.41. Older age, female sex, greater inter-series time interval, differing uptake, and greater voxel size differences independently reduced automated registration performance ( p ≤ 0.020). Conclusion A fully automated algorithm accurately registered the liver within and between examinations, yielding better liver and focal observation co-localization compared to manual registration.

Objective To assess the safety and efficacy of magnetic resonance-guided focused ultrasound (MRgFUS) for the treatment extra-abdominal desmoids. Methods A total of 105 patients with desmoid fibromatosis (79 females, 26 males; 35 ± 14 years) were treated with MRgFUS between 2011 and 2021 in three centers. Total and viable tumors were evaluated per patient at last follow-up after treatment. Response and progression-free survival (PFS) were assessed with (modified) response evaluation criteria in solid tumors (RECIST v.1.1 and mRECIST). Change in Numerical Rating Scale (NRS) pain and 36-item Short Form Health Survey (SF-36) scores were compared. Treatment-related adverse events were recorded. Results The median initial tumor volume was 114 mL (IQR 314 mL). After MRgFUS, median total and viable tumor volume decreased to 51 mL (95% CI: 30–71 mL, n  = 101, p  < 0.0001) and 29 mL (95% CI: 17–57 mL, n  = 88, p  < 0.0001), respectively, at last follow-up (median: 15 months, 95% CI: 11–20 months). Based on total tumor measurements (RECIST), 86% (95% CI: 75–93%) had at least stable disease or better at last follow-up, but 50% (95% CI: 38–62%) of remaining viable nodules (mRECIST) progressed within the tumor. Median PFS was reached at 17 and 13 months for total and viable tumors, respectively. NRS decreased from 6 (IQR 3) to 3 (IQR 4) ( p  < 0.001). SF-36 scores improved (physical health (41 (IQR 15) to 46 (IQR 12); p  = 0.05, and mental health (49 (IQR 17) to 53 (IQR 9); p  = 0.02)). Complications occurred in 36%, most commonly 1 st /2 nd degree skin burns. Conclusion MRgFUS reduced tumor volume, reduced pain, and improved quality of life in this series of 105 patients with extra-abdominal desmoid fibromatosis. Clinical relevance statement Imaging-guided ablation is being increasingly used as an alternative to surgery, radiation, and medical therapy for the treatment of desmoid fibromatosis. MR-guided high-intensity focused ultrasound is an incisionless ablation technique that can be used to reduce tumor burden effectively and safely. Key Points • Desmoid fibromatosis was treated with MR-guided high-intensity focused ultrasound in 105 patients. • MR-guided focused ultrasound ablation reduced tumor volume and pain and improved quality of life. • MR-guided focused ultrasound is a treatment option for patients with extra-abdominal desmoid tumors.

We apply spatial transcriptomics and proteomics to select pancreatic cancer surface receptor targets for molecular imaging and theranostics using an approach that can be applied to many cancers. Selected cancer surfaceome epithelial markers were spatially correlated and provided specific cancer localization, whereas the spatial correlation between cancer markers and immune- cell or fibroblast markers was low. While molecular imaging of cancer-associated fibroblasts and integrins has been proposed for pancreatic cancer, our data point to the tight junction protein claudin-4 as a theranostic target. Claudin-4 expression increased ∼16 fold in cancer as compared with normal pancreas, and the tight junction localization conferred low background for imaging in normal tissue. We developed a peptide-based molecular imaging agent targeted to claudin-4 with accumulation to ∼25% injected activity per cc (IA/cc) in metastases and ∼18% IA/cc in tumors. Our work motivates a new approach for data-driven selection of molecular targets.