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Pereira BA, Ritchie S, Chambers CR, Gordon KA, Magenau A, Murphy KJ, Nobis M, Tyma VM, Liew YF, Lucas MC, Naeini MM, Barkauskas DS, Chacon-Fajardo D, Howell AE, Parker AL, Warren SC, Reed DA, Lee V, Metcalf XL, Lee YK, O’Regan LP, Zhu J, Trpceski M, Fontaine ARM, Stoehr J, Rouet R, Lin X, Chitty JL, Porazinski S, Wu SZ, Filipe EC, Cadell AL, Holliday H, Yang J, Papanicolaou M, Lyons RJ, Zaratzian A, Tayao M, Da Silva A, Vennin C, Yin J, Dew AB, McMillan PJ, Goldstein LD, Deveson IW, Croucher DR, Samuel MS, Sim HW, Batten M, Chantrill L, Grimmond SM, Gill AJ, Samra J, Jeffry Evans TR, Sasaki T, Phan TG, Swarbrick A, Sansom OJ, Morton JP, Pajic M, Parker BL, Herrmann D, Cox TR, Timpson P. Temporally resolved proteomics identifies nidogen-2 as a cotarget in pancreatic cancer that modulates fibrosis and therapy response. SCIENCE ADVANCES 2024; 10:eadl1197. [PMID: 38959305 PMCID: PMC11221519 DOI: 10.1126/sciadv.adl1197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 05/30/2024] [Indexed: 07/05/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is characterized by increasing fibrosis, which can enhance tumor progression and spread. Here, we undertook an unbiased temporal assessment of the matrisome of the highly metastatic KPC (Pdx1-Cre, LSL-KrasG12D/+, LSL-Trp53R172H/+) and poorly metastatic KPflC (Pdx1-Cre, LSL-KrasG12D/+, Trp53fl/+) genetically engineered mouse models of pancreatic cancer using mass spectrometry proteomics. Our assessment at early-, mid-, and late-stage disease reveals an increased abundance of nidogen-2 (NID2) in the KPC model compared to KPflC, with further validation showing that NID2 is primarily expressed by cancer-associated fibroblasts (CAFs). Using biomechanical assessments, second harmonic generation imaging, and birefringence analysis, we show that NID2 reduction by CRISPR interference (CRISPRi) in CAFs reduces stiffness and matrix remodeling in three-dimensional models, leading to impaired cancer cell invasion. Intravital imaging revealed improved vascular patency in live NID2-depleted tumors, with enhanced response to gemcitabine/Abraxane. In orthotopic models, NID2 CRISPRi tumors had less liver metastasis and increased survival, highlighting NID2 as a potential PDAC cotarget.
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Affiliation(s)
- Brooke A. Pereira
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Shona Ritchie
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Cecilia R. Chambers
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Katie A. Gordon
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Astrid Magenau
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Kendelle J. Murphy
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Max Nobis
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Intravital Imaging Expertise Center, VIB Center for Cancer Biology, VIB, Leuven, Belgium
| | - Victoria M. Tyma
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Ying Fei Liew
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Morghan C. Lucas
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Marjan M. Naeini
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Genomics and Inherited Disease Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Deborah S. Barkauskas
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- ACRF INCITe Intravital Imaging Centre, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Diego Chacon-Fajardo
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Translational Oncology Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Anna E. Howell
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Amelia L. Parker
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Sean C. Warren
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Daniel A. Reed
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Victoria Lee
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Xanthe L. Metcalf
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Young Kyung Lee
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Luke P. O’Regan
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Jessie Zhu
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Michael Trpceski
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Angela R. M. Fontaine
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- ACRF INCITe Intravital Imaging Centre, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Janett Stoehr
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Romain Rouet
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Immune Biotherapies Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Xufeng Lin
- Data Science Platform, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Jessica L. Chitty
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Sean Porazinski
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Translational Oncology Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Sunny Z. Wu
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Genentech Inc., South San Francisco, CA, USA
| | - Elysse C. Filipe
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Antonia L. Cadell
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Translational Oncology Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Holly Holliday
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Children’s Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Kensington, New South Wales, Australia
| | - Jessica Yang
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Michael Papanicolaou
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Ruth J. Lyons
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Anaiis Zaratzian
- Histopathology Platform, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Michael Tayao
- Histopathology Platform, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Andrew Da Silva
- Histopathology Platform, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Claire Vennin
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Division of Molecular Pathology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, Netherlands
- Oncode Institute, Amsterdam, Netherlands
| | - Julia Yin
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Translational Oncology Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Alysha B. Dew
- Centre for Advanced Histology & Microscopy, Peter MacCallum Cancer Centre, Parkville, Victoria, Australia
| | - Paul J. McMillan
- Centre for Advanced Histology & Microscopy, Peter MacCallum Cancer Centre, Parkville, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, Australia
- Biological Optical Microscopy Platform, The University of Melbourne, Parkville, Victoria, Australia
| | - Leonard D. Goldstein
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Data Science Platform, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Ira W. Deveson
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Genomics and Inherited Disease Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - David R. Croucher
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Translational Oncology Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Michael S. Samuel
- Centre for Cancer Biology, An Alliance of SA Pathology and University of South Australia, Adelaide, South Australia, Australia
- Basil Hetzel Institute for Translational Health Research, Queen Elizabeth Hospital, Woodville South, South Australia, Australia
| | - Hao-Wen Sim
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- NHMRC Clinical Trials Centre, University of Sydney, Camperdown, New South Wales, Australia
- Department of Medical Oncology, Chris O’Brien Lifehouse, Camperdown, New South Wales, Australia
| | - Marcel Batten
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Lorraine Chantrill
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- Department of Medical Oncology, Illawarra Shoalhaven Local Health District, Wollongong, New South Wales, Australia
| | - Sean M. Grimmond
- Centre for Cancer Research and Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Anthony J. Gill
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- NSW Health Pathology, Department of Anatomical Pathology, Royal North Shore Hospital, St Leonards, New South Wales, Australia
- Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia
| | - Jaswinder Samra
- Department of Surgery, Royal North Shore Hospital, St Leonards, New South Wales, Australia
| | - Thomas R. Jeffry Evans
- Cancer Research UK Beatson Institute, Glasgow, UK
- School of Cancer Sciences, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Takako Sasaki
- Department of Biochemistry, Faculty of Medicine, Oita University, Oita, Japan
| | - Tri G. Phan
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Precision Immunology Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Owen J. Sansom
- Cancer Research UK Beatson Institute, Glasgow, UK
- School of Cancer Sciences, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | - Jennifer P. Morton
- Cancer Research UK Beatson Institute, Glasgow, UK
- School of Cancer Sciences, Institute of Cancer Sciences, University of Glasgow, Glasgow, UK
| | | | | | - Marina Pajic
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
- Translational Oncology Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
| | - Benjamin L. Parker
- Department of Anatomy and Physiology, University of Melbourne, Parkville, Victoria, Australia
| | - David Herrmann
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Thomas R. Cox
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
| | - Paul Timpson
- Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, New South Wales, Australia
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2
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Ashworth JC, Cox TR. The importance of 3D fibre architecture in cancer and implications for biomaterial model design. Nat Rev Cancer 2024; 24:461-479. [PMID: 38886573 DOI: 10.1038/s41568-024-00704-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/07/2024] [Indexed: 06/20/2024]
Abstract
The need for improved prediction of clinical response is driving the development of cancer models with enhanced physiological relevance. A new concept of 'precision biomaterials' is emerging, encompassing patient-mimetic biomaterial models that seek to accurately detect, treat and model cancer by faithfully recapitulating key microenvironmental characteristics. Despite recent advances allowing tissue-mimetic stiffness and molecular composition to be replicated in vitro, approaches for reproducing the 3D fibre architectures found in tumour extracellular matrix (ECM) remain relatively unexplored. Although the precise influences of patient-specific fibre architecture are unclear, we summarize the known roles of tumour fibre architecture, underlining their implications in cell-matrix interactions and ultimately clinical outcome. We then explore the challenges in reproducing tissue-specific 3D fibre architecture(s) in vitro, highlighting relevant biomaterial fabrication techniques and their benefits and limitations. Finally, we discuss imaging and image analysis techniques (focussing on collagen I-optimized approaches) that could hold the key to mapping tumour-specific ECM into high-fidelity biomaterial models. We anticipate that an interdisciplinary approach, combining materials science, cancer research and image analysis, will elucidate the role of 3D fibre architecture in tumour development, leading to the next generation of patient-mimetic models for mechanistic studies and drug discovery.
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Affiliation(s)
- J C Ashworth
- School of Veterinary Medicine & Science, Sutton Bonington Campus, University of Nottingham, Leicestershire, UK.
- Biodiscovery Institute, School of Medicine, University of Nottingham, Nottingham, UK.
- Cancer Ecosystems Program, The Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.
| | - T R Cox
- Cancer Ecosystems Program, The Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia.
- The Kinghorn Cancer Centre, Darlinghurst, New South Wales, Australia.
- School of Clinical Medicine, St Vincent's Healthcare Clinical Campus, UNSW Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia.
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3
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Suarez CF, Harb OA, Robledo A, Largoza G, Ahn JJ, Alley EK, Wu T, Veeraragavan S, McClugage ST, Iacobas I, Fish JE, Kan PT, Marrelli SP, Wythe JD. MEK signaling represents a viable therapeutic vulnerability of KRAS-driven somatic brain arteriovenous malformations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.15.594335. [PMID: 38766159 PMCID: PMC11101126 DOI: 10.1101/2024.05.15.594335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Brain arteriovenous malformations (bAVMs) are direct connections between arteries and veins that remodel into a complex nidus susceptible to rupture and hemorrhage. Most sporadic bAVMs feature somatic activating mutations within KRAS, and endothelial-specific expression of the constitutively active variant KRASG12D models sporadic bAVM in mice. By leveraging 3D-based micro-CT imaging, we demonstrate that KRASG12D-driven bAVMs arise in stereotypical anatomical locations within the murine brain, which coincide with high endogenous Kras expression. We extend these analyses to show that a distinct variant, KRASG12C, also generates bAVMs in predictable locations. Analysis of 15,000 human patients revealed that, similar to murine models, bAVMs preferentially occur in distinct regions of the adult brain. Furthermore, bAVM location correlates with hemorrhagic frequency. Quantification of 3D imaging revealed that G12D and G12C alter vessel density, tortuosity, and diameter within the mouse brain. Notably, aged G12D mice feature increased lethality, as well as impaired cognition and motor function. Critically, we show that pharmacological blockade of the downstream kinase, MEK, after lesion formation ameliorates KRASG12D-driven changes in the murine cerebrovasculature and may also impede bAVM progression in human pediatric patients. Collectively, these data show that distinct KRAS variants drive bAVMs in similar patterns and suggest MEK inhibition represents a non-surgical alternative therapy for sporadic bAVM.
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4
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Renton AI, Dao TT, Johnstone T, Civier O, Sullivan RP, White DJ, Lyons P, Slade BM, Abbott DF, Amos TJ, Bollmann S, Botting A, Campbell MEJ, Chang J, Close TG, Dörig M, Eckstein K, Egan GF, Evas S, Flandin G, Garner KG, Garrido MI, Ghosh SS, Grignard M, Halchenko YO, Hannan AJ, Heinsfeld AS, Huber L, Hughes ME, Kaczmarzyk JR, Kasper L, Kuhlmann L, Lou K, Mantilla-Ramos YJ, Mattingley JB, Meier ML, Morris J, Narayanan A, Pestilli F, Puce A, Ribeiro FL, Rogasch NC, Rorden C, Schira MM, Shaw TB, Sowman PF, Spitz G, Stewart AW, Ye X, Zhu JD, Narayanan A, Bollmann S. Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging. Nat Methods 2024; 21:804-808. [PMID: 38191935 PMCID: PMC11180540 DOI: 10.1038/s41592-023-02145-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 11/27/2023] [Indexed: 01/10/2024]
Abstract
Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.
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Affiliation(s)
- Angela I Renton
- The University of Queensland, Queensland Brain Institute, St Lucia, Brisbane, Queensland, Australia.
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia.
| | - Thuy T Dao
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Tom Johnstone
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Oren Civier
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Ryan P Sullivan
- The University of Sydney, School of Biomedical Engineering, Sydney, New South Wales, Australia
| | - David J White
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Paris Lyons
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Benjamin M Slade
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - David F Abbott
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Toluwani J Amos
- School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, China
| | - Saskia Bollmann
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Andy Botting
- Australian Research Data Commons (ARDC), Sydney, New South Wales, Australia
| | - Megan E J Campbell
- School of Psychological Sciences, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute Imaging Centre, Newcastle, New South Wales, Australia
| | - Jeryn Chang
- The University of Queensland, School of Biomedical Sciences, St Lucia, Brisbane, Queensland, Australia
| | - Thomas G Close
- The University of Sydney, School of Biomedical Engineering, Sydney, New South Wales, Australia
| | - Monika Dörig
- Integrative Spinal Research, Department of Chiropractic Medicine, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Korbinian Eckstein
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Gary F Egan
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Stefanie Evas
- School of Psychology, University of Adelaide, Adelaide, South Australia, Australia
- Human Health, Health & Biosecurity, CSIRO, Adelaide, South Australia, Australia
| | - Guillaume Flandin
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Kelly G Garner
- School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
- The University of Queensland, School of Psychology, St Lucia, Brisbane, Queensland, Australia
| | - Marta I Garrido
- Melbourne School of Psychological Sciences, he University of Melbourne, Melbourne, Victoria, Australia
- Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
| | - Satrajit S Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Otolaryngology - Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
| | - Martin Grignard
- GIGA CRC In-Vivo Imaging, University of Liège, Liège, Belgium
| | - Yaroslav O Halchenko
- Center for Open Neuroscience, Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Anthony J Hannan
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Anibal S Heinsfeld
- Department of Psychology, Center for Perceptual Systems, Institute for Neuroscience, Center For Learning and Memory, The University of Texas at Austin, Austin, TX, USA
| | - Laurentius Huber
- National Institute of Mental Health (NIMH), National Institutes Health, Bethesda, MD, USA
| | - Matthew E Hughes
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Jakub R Kaczmarzyk
- Department of Biomedical Informatics, Stony Brook University, New York, NY, USA
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, New York, NY, USA
| | - Lars Kasper
- BRAIN-TO Lab, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Levin Kuhlmann
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia
| | - Kexin Lou
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yorguin-Jose Mantilla-Ramos
- Grupo Neuropsicología y Conducta (GRUNECO), Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
| | - Jason B Mattingley
- The University of Queensland, Queensland Brain Institute, St Lucia, Brisbane, Queensland, Australia
- The University of Queensland, School of Psychology, St Lucia, Brisbane, Queensland, Australia
| | - Michael L Meier
- Integrative Spinal Research, Department of Chiropractic Medicine, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Jo Morris
- Australian Research Data Commons (ARDC), Sydney, New South Wales, Australia
| | - Akshaiy Narayanan
- School of Computer Science, The University of Auckland, Auckland, New Zealand
| | - Franco Pestilli
- Department of Psychology, Center for Perceptual Systems, Institute for Neuroscience, Center For Learning and Memory, The University of Texas at Austin, Austin, TX, USA
| | - Aina Puce
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Fernanda L Ribeiro
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Nigel C Rogasch
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
- Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia
| | - Chris Rorden
- McCausland Center for Brain Imaging, Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Mark M Schira
- School of Psychology, University of Wollongong, Wollongong, New South Wales, Australia
| | - Thomas B Shaw
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia
- Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
| | - Paul F Sowman
- Macquarie University, School of Psychological Sciences, Sydney, New South Wales, Australia
| | - Gershon Spitz
- Department of Neuroscience, Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Ashley W Stewart
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
| | - Xincheng Ye
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Judy D Zhu
- Macquarie University, School of Psychological Sciences, Sydney, New South Wales, Australia
| | - Aswin Narayanan
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia
| | - Steffen Bollmann
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia.
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia.
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia.
- Queensland Digital Health Centre, The University of Queensland, Brisbane, Queensland, Australia.
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5
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Liu JA, Bumgarner JR, Walker WH, Meléndez-Fernández OH, Walton JC, DeVries AC, Nelson RJ. Chronic phase advances reduces recognition memory and increases vascular cognitive dementia-like impairments in aged mice. Sci Rep 2024; 14:7760. [PMID: 38565934 PMCID: PMC10987525 DOI: 10.1038/s41598-024-57511-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/19/2024] [Indexed: 04/04/2024] Open
Abstract
Disrupted or atypical light-dark cycles disrupts synchronization of endogenous circadian clocks to the external environment; extensive circadian rhythm desynchrony promotes adverse health outcomes. Previous studies suggest that disrupted circadian rhythms promote neuroinflammation and neuronal damage post-ischemia in otherwise healthy mice, however, few studies to date have evaluated these health risks with aging. Because most strokes occur in aged individuals, we sought to identify whether, in addition to being a risk factor for poor ischemic outcome, circadian rhythm disruption can increase risk for vascular cognitive impairment and dementia (VCID). We hypothesized that repeated 6 h phase advances (chronic jet lag; CJL) for 8 weeks alters cerebrovascular architecture leading to increased cognitive impairments in aged mice. Female CJL mice displayed impaired spatial processing during a spontaneous alternation task and reduced acquisition during auditory-cued associative learning. Male CJL mice displayed impaired retention of the auditory-cued associative learning task 24 h following acquisition. CJL increased vascular tortuosity in the isocortex, associated with increased risk for vascular disease. These results demonstrate that CJL increased sex-specific cognitive impairments coinciding with structural changes to vasculature in the brain. We highlight that CJL may accelerate aged-related functional decline and could be a crucial target against disease progression.
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Affiliation(s)
- Jennifer A Liu
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, USA.
| | - Jacob R Bumgarner
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, USA
| | - William H Walker
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, USA
- Department of Medicine, West Virginia University, Morgantown, USA
| | | | - James C Walton
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, USA
| | - A Courtney DeVries
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, USA
- Department of Medicine, West Virginia University, Morgantown, USA
- West Virginia University Cancer Institute, West Virginia University, Morgantown, USA
| | - Randy J Nelson
- Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, USA
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6
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Gaupp C, Schmid B, Tripal P, Edwards A, Daniel C, Zimmermann S, Goppelt-Struebe M, Willam C, Rosen S, Schley G. Reconfiguration and loss of peritubular capillaries in chronic kidney disease. Sci Rep 2023; 13:19660. [PMID: 37952029 PMCID: PMC10640592 DOI: 10.1038/s41598-023-46146-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 10/27/2023] [Indexed: 11/14/2023] Open
Abstract
Functional and structural alterations of peritubular capillaries (PTCs) are a major determinant of chronic kidney disease (CKD). Using a software-based algorithm for semiautomatic segmentation and morphometric quantification, this study analyzes alterations of PTC shape associated with chronic tubulointerstitial injury in three mouse models and in human biopsies. In normal kidney tissue PTC shape was predominantly elongated, whereas the majority of PTCs associated with chronic tubulointerstitial injury had a rounder shape. This was reflected by significantly reduced PTC luminal area, perimeter and diameters as well as by significantly increased circularity and roundness. These morphological alterations were consistent in all mouse models and human kidney biopsies. The mean circularity of PTCs correlated significantly with categorized glomerular filtration rates and the degree of interstitial fibrosis and tubular atrophy (IFTA) and classified the presence of CKD or IFTA. 3D reconstruction of renal capillaries revealed not only a significant reduction, but more importantly a substantial simplification and reconfiguration of the renal microvasculature in mice with chronic tubulointerstitial injury. Computational modelling predicted that round PTCs can deliver oxygen more homogeneously to the surrounding tissue. Our findings indicate that alterations of PTC shape represent a common and uniform reaction to chronic tubulointerstitial injury independent of the underlying kidney disease.
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Affiliation(s)
- Charlotte Gaupp
- Department of Nephrology and Hypertension, Friedrich-Alexander University Erlangen-Nürnberg (FAU) and University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
| | - Benjamin Schmid
- Optical Imaging Center Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Philipp Tripal
- Optical Imaging Center Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Aurélie Edwards
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Christoph Daniel
- Department of Nephropathology, Friedrich-Alexander University Erlangen-Nürnberg (FAU) and University Hospital Erlangen, Erlangen, Germany
| | - Stefan Zimmermann
- Department of Computer Science, University of Applied Sciences Worms, Worms, Germany
| | - Margarete Goppelt-Struebe
- Department of Nephrology and Hypertension, Friedrich-Alexander University Erlangen-Nürnberg (FAU) and University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
| | - Carsten Willam
- Department of Nephrology and Hypertension, Friedrich-Alexander University Erlangen-Nürnberg (FAU) and University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
| | - Seymour Rosen
- Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Gunnar Schley
- Department of Nephrology and Hypertension, Friedrich-Alexander University Erlangen-Nürnberg (FAU) and University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany.
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7
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Nicolas N, Dinet V, Roux E. 3D imaging and morphometric descriptors of vascular networks on optically cleared organs. iScience 2023; 26:108007. [PMID: 37810224 PMCID: PMC10551892 DOI: 10.1016/j.isci.2023.108007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2023] Open
Abstract
The vascular system is a multi-scale network whose functionality depends on its structure, and for which structural alterations can be linked to pathological shifts. Though biologists use multiple 3D imaging techniques to visualize vascular networks, the 3D image processing methodologies remain sources of biases, and the extraction of quantitative morphometric descriptors remains flawed. The article, first, reviews the current 3D image processing methodologies, and morphometric descriptors of vascular network images mainly obtained by light-sheet microscopy on optically cleared organs, found in the literature. Second, it proposes operator-independent segmentation and skeletonization methodologies using the freeware ImageJ. Third, it gives more extractable network-level (density, connectivity, fractal dimension) and segment-level (length, diameter, tortuosity) 3D morphometric descriptors and how to statistically analyze them. Thus, it can serve as a guideline for biologists using 3D imaging techniques of vascular networks, allowing the production of more comparable studies in the future.
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Affiliation(s)
- Nabil Nicolas
- University Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600 Pessac, France
| | - Virginie Dinet
- University Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600 Pessac, France
| | - Etienne Roux
- University Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600 Pessac, France
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8
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Bumgarner JR, Walker WH, Quintana DD, White RC, Richmond AA, Meléndez-Fernández OH, Liu JA, Becker-Krail DD, Walton JC, Simpkins JW, DeVries AC, Nelson RJ. Acute exposure to artificial light at night alters hippocampal vascular structure in mice. iScience 2023; 26:106996. [PMID: 37534143 PMCID: PMC10391664 DOI: 10.1016/j.isci.2023.106996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 03/15/2023] [Accepted: 05/25/2023] [Indexed: 08/04/2023] Open
Abstract
The structure and function of the cardiovascular system are modulated across the day by circadian rhythms, making this system susceptible to circadian rhythm disruption. Recent evidence demonstrated that short-term exposure to a pervasive circadian rhythm disruptor, artificial light at night (ALAN), increased inflammation and altered angiogenic transcripts in the hippocampi of mice. Here, we examined the effects of four nights of ALAN exposure on mouse hippocampal vascular networks. To do this, we analyzed 2D and 3D images of hippocampal vasculature and hippocampal transcriptomic profiles of mice exposed to ALAN. ALAN reduced vascular density in the CA1 and CA2/3 of female mice and the dentate gyrus of male mice. Network structure and connectivity were also impaired in the CA2/3 of female mice. These results demonstrate the rapid and potent effects of ALAN on cerebrovascular networks, highlighting the importance of ALAN mitigation in the context of health and cerebrovascular disease.
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Affiliation(s)
- Jacob R Bumgarner
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | - William H Walker
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | - Dominic D Quintana
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | - Rhett C White
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | - Alexandra A Richmond
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | | | - Jennifer A Liu
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | - Darius D Becker-Krail
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | - James C Walton
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | - James W Simpkins
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
| | - A Courtney DeVries
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
- Department of Medicine, Division of Oncology/Hematology West Virginia University Morgantown, WV 26505, USA
- WVU Cancer Institute West Virginia University Morgantown, WV 26505 USA
| | - Randy J Nelson
- Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University Morgantown, WV 26505, USA
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9
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Retinal image blood vessel classification using hybrid deep learning in cataract diseased fundus images. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
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10
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Spangenberg P, Hagemann N, Squire A, Förster N, Krauß SD, Qi Y, Mohamud Yusuf A, Wang J, Grüneboom A, Kowitz L, Korste S, Totzeck M, Cibir Z, Tuz AA, Singh V, Siemes D, Struensee L, Engel DR, Ludewig P, Martins Nascentes Melo L, Helfrich I, Chen J, Gunzer M, Hermann DM, Mosig A. Rapid and fully automated blood vasculature analysis in 3D light-sheet image volumes of different organs. CELL REPORTS METHODS 2023; 3:100436. [PMID: 37056368 PMCID: PMC10088239 DOI: 10.1016/j.crmeth.2023.100436] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/25/2022] [Accepted: 03/01/2023] [Indexed: 03/19/2023]
Abstract
Light-sheet fluorescence microscopy (LSFM) can produce high-resolution tomograms of tissue vasculature with high accuracy. However, data processing and analysis is laborious due to the size of the datasets. Here, we introduce VesselExpress, an automated software that reliably analyzes six characteristic vascular network parameters including vessel diameter in LSFM data on average computing hardware. VesselExpress is ∼100 times faster than other existing vessel analysis tools, requires no user interaction, and integrates batch processing and parallelization. Employing an innovative dual Frangi filter approach, we show that obesity induces a large-scale modulation of brain vasculature in mice and that seven other major organs differ strongly in their 3D vascular makeup. Hence, VesselExpress transforms LSFM from an observational to an analytical working tool.
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Affiliation(s)
- Philippa Spangenberg
- Department of Immunodynamics, Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, Bochum, Germany
| | - Nina Hagemann
- Department of Neurology, University Hospital Essen, Essen, Germany
| | - Anthony Squire
- Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
| | - Nils Förster
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, Bochum, Germany
- Bioinformatics Group, Faculty for Biology and Biotechnology, Ruhr-University Bochum, Germany
| | - Sascha D. Krauß
- Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
| | - Yachao Qi
- Department of Neurology, University Hospital Essen, Essen, Germany
| | | | - Jing Wang
- Department of Neurology, University Hospital Essen, Essen, Germany
| | - Anika Grüneboom
- Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Dortmund, Germany
| | - Lennart Kowitz
- Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Dortmund, Germany
| | - Sebastian Korste
- Department of Cardiology and Vascular Medicine, University Hospital Essen, Essen, Germany
| | - Matthias Totzeck
- Department of Cardiology and Vascular Medicine, University Hospital Essen, Essen, Germany
| | - Zülal Cibir
- Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
| | - Ali Ata Tuz
- Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
| | - Vikramjeet Singh
- Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
| | - Devon Siemes
- Department of Immunodynamics, Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
| | - Laura Struensee
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, Bochum, Germany
| | - Daniel R. Engel
- Department of Immunodynamics, Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
| | - Peter Ludewig
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Iris Helfrich
- Clinic of Dermatology, University Hospital Essen, Essen, Germany
| | - Jianxu Chen
- Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Dortmund, Germany
| | - Matthias Gunzer
- Institute for Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany
- Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Dortmund, Germany
| | - Dirk M. Hermann
- Department of Neurology, University Hospital Essen, Essen, Germany
| | - Axel Mosig
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, Bochum, Germany
- Bioinformatics Group, Faculty for Biology and Biotechnology, Ruhr-University Bochum, Germany
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11
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Aw WY, Cho C, Wang H, Cooper AH, Doherty EL, Rocco D, Huang SA, Kubik S, Whitworth CP, Armstrong R, Hickey AJ, Griffith B, Kutys ML, Blatt J, Polacheck WJ. Microphysiological model of PIK3CA-driven vascular malformations reveals a role of dysregulated Rac1 and mTORC1/2 in lesion formation. SCIENCE ADVANCES 2023; 9:eade8939. [PMID: 36791204 PMCID: PMC9931220 DOI: 10.1126/sciadv.ade8939] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 01/13/2023] [Indexed: 05/09/2023]
Abstract
Somatic activating mutations of PIK3CA are associated with development of vascular malformations (VMs). Here, we describe a microfluidic model of PIK3CA-driven VMs consisting of human umbilical vein endothelial cells expressing PIK3CA activating mutations embedded in three-dimensional hydrogels. We observed enlarged, irregular vessel phenotypes and the formation of cyst-like structures consistent with clinical signatures and not previously observed in cell culture models. Pathologic morphologies occurred concomitant with up-regulation of Rac1/p21-activated kinase (PAK), mitogen-activated protein kinase cascades (MEK/ERK), and mammalian target of rapamycin (mTORC1/2) signaling networks. We observed differential effects between alpelisib, a PIK3CA inhibitor, and rapamycin, an mTORC1 inhibitor, in mitigating matrix degradation and network topology. While both were effective in preventing vessel enlargement, rapamycin failed to reduce MEK/ERK and mTORC2 activity and resulted in hyperbranching, while inhibiting PAK, MEK1/2, and mTORC1/2 mitigates abnormal growth and vascular dilation. Collectively, these findings demonstrate an in vitro platform for VMs and establish a role of dysregulated Rac1/PAK and mTORC1/2 signaling in PIK3CA-driven VMs.
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Affiliation(s)
- Wen Yih Aw
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Crescentia Cho
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
| | - Hao Wang
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
| | - Anne Hope Cooper
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
| | - Elizabeth L. Doherty
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - David Rocco
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
| | - Stephanie A. Huang
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
| | - Sarah Kubik
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
| | - Chloe P. Whitworth
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
| | - Ryan Armstrong
- Department of Physics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Anthony J. Hickey
- UNC Catalyst for Rare Diseases, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Boyce Griffith
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
- Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Computational Medicine Program, University of North Carolina, Chapel Hill, NC, USA
- McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Matthew L. Kutys
- Department of Cell and Tissue Biology, University of California, San Francisco, San Francisco, CA, USA
| | - Julie Blatt
- Department of Pediatrics (Division of Pediatric Hematology Oncology), University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - William J. Polacheck
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA and North Carolina State University, Raleigh, NC, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
- McAllister Heart Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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