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Hendriks, J. M.

Publications and source records attributed to Hendriks, J. M..

2 recordsLinked to original sources

Multiscale mapping of venous remodelling in idiopathic pulmonary fibrosis

The integrity of the pulmonary vasculature is a key determinant of lung health, yet challenges in visualisation and quantification have hindered interrogation of its pathophysiological role in chronic lung disease. Here, we align recent advances in microscale image acquisition with novel computer vision-based vessel segmentation models to demonstrate expansion of the bronchial and pulmonary veins across varying severities of tissue remodelling in idiopathic pulmonary fibrosis (IPF). Relating these imaging findings to molecular data in control, mild, and severe fibrosis, we show that bronchial venous endothelial cells expand beyond their physiological peribronchial niche even in mild disease, acquiring persistent angiogenic, inflammatory, and matrix-remodelling programmes that define a specialised fibrovascular-immune interface. Finally, we relate these microscale and molecular observations to clinical CT imaging, demonstrating that intrapulmonary vein enlargement independently associates with worsened survival across three IPF cohorts. Collectively, our multimodal, multiscale approach connects previously unresolved three-dimensional venous architecture to its molecular endothelial correlate, establishing venous enlargement as a prognostically significant and clinically relevant feature of IPF. Our analytical approach also demonstrates how biological discoveries made in intact ex vivo human organs can translate into measurable phenotypes in living patients, providing a template for other organs and diseases.

pathology↗

OrBITS: A High-throughput, time-lapse, and label-free drug screening platform for patient-derived 3D organoids

BackgroundPatient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. MethodsHere, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. ResultsOrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D(R)-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, intra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. ConclusionsOur findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

cancer biology↗