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Bette M, Mandic R. Cottontail Rabbit Papillomavirus (CRPV) Related Animal Models for Head and Neck Cancer Research: A Comprehensive Review of the Literature. Viruses 2024; 16:1722. [PMID: 39599834 PMCID: PMC11598981 DOI: 10.3390/v16111722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2024] [Revised: 10/16/2024] [Accepted: 10/28/2024] [Indexed: 11/29/2024] Open
Abstract
Having suitable animal models is crucial to mimic human disease states and for the successful transfer of experimental data into clinical practice. In the field of papillomavirus research, the domestic rabbit (Oryctolagus cuniculus) has served as an indispensable model organism for almost 100 years. The identification and characterization of the first papillomaviruses in rabbits, their carcinogenic potential and their immunogenicity have contributed significantly to the state of knowledge on the genetics and life cycle of papillomaviruses in general, as well as the development of antiviral strategies such as vaccination procedures. Due to the high species specificity of papillomaviruses, only rabbit papillomaviruses (RPVs) can be used for animal studies on papilloma-based tumor diseases in the rabbit. The major focus of this article is on cottontail rabbit papillomavirus (CRPV)-related rabbit squamous cell carcinoma (RSCC). A brief history outlines the discovery and generation of experimentally used RSCC tumors. A comprehensive overview of the current CRPV-associated VX2 carcinoma-based tumor models with a major focus on human head and neck squamous cell carcinoma (HNSCC) tumor models is provided, and their strengths in terms of transferability to human HNSCC are discussed.
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Affiliation(s)
- Michael Bette
- Institute of Anatomy and Cell Biology, Philipps-Universität Marburg, 35037 Marburg, Germany
| | - Robert Mandic
- Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Marburg, Philipps-Universität Marburg, 35033 Marburg, Germany;
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Gu C, Li Y, Cao D, Miao X, Paez AG, Sun Y, Cai J, Li W, Li X, Pillai JJ, Earley CJ, van Zijl PC, Hua J. On the optimization of 3D inflow-based vascular-space-occupancy (iVASO) MRI for the quantification of arterial cerebral blood volume (CBVa). Magn Reson Med 2024; 91:1893-1907. [PMID: 38115573 PMCID: PMC10950541 DOI: 10.1002/mrm.29971] [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: 11/01/2023] [Revised: 11/20/2023] [Accepted: 11/25/2023] [Indexed: 12/21/2023]
Abstract
PURPOSE The inflow-based vascular-space-occupancy (iVASO) MRI was originally developed in a single-slice mode to measure arterial cerebral blood volume (CBVa). When vascular crushers are applied in iVASO, the signals can be sensitized predominantly to small pial arteries and arterioles. The purpose of this study is to perform a systematic optimization and evaluation of a 3D iVASO sequence on both 3 T and 7 T for the quantification of CBVa values in the human brain. METHODS Three sets of experiments were performed in three separate cohorts. (1) 3D iVASO MRI protocols were compared to single-slice iVASO, and the reproducibility of whole-brain 3D iVASO MRI was evaluated. (2) The effects from different vascular crushers in iVASO were assessed. (3) 3D iVASO MRI results were evaluated in arterial and venous blood vessels identified using ultrasmall-superparamagnetic-iron-oxides-enhanced MRI to validate its arterial origin. RESULTS 3D iVASO scans showed signal-to-noise ratio (SNR) and CBVa measures consistent with single-slice iVASO with reasonable intrasubject reproducibility. Among the iVASO scans performed with different vascular crushers, the whole-brain 3D iVASO scan with a motion-sensitized-driven-equilibrium preparation with two binomial refocusing pulses and an effective TE of 50 ms showed the best suppression of macrovascular signals, with a relatively low specific absorption rate. When no vascular crusher was applied, the CBVa maps from 3D iVASO scans showed large CBVa values in arterial vessels but well-suppressed signals in venous vessels. CONCLUSION A whole-brain 3D iVASO MRI scan was optimized for CBVa measurement in the human brain. When only microvascular signals are desired, a motion-sensitized-driven-equilibrium-based vascular crusher with binomial refocusing pulses can be applied in 3D iVASO.
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Affiliation(s)
- Chunming Gu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Yinghao Li
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Di Cao
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Xinyuan Miao
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Adrian G. Paez
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Yuanqi Sun
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Jitong Cai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Wenbo Li
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Xu Li
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Jay J. Pillai
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Division of Neuroradiology, Mayo Clinic College of Medicine and Science, Rochester, MN, United States
| | - Christopher J. Earley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Peter C.M. van Zijl
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Jun Hua
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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Huang W, Wang K, Huang W, He Z, Zhang J, Zhang B, Xiong Z, Gillen KM, Li W, Chen F, Yang X, Zhang S, Tian J. Carbonic anhydrase IX stratifies patient prognosis and identifies nodal status in animal models of nasopharyngeal carcinoma using a targeted imaging strategy. Eur J Nucl Med Mol Imaging 2022; 49:4427-4439. [PMID: 35925443 DOI: 10.1007/s00259-022-05922-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 07/12/2022] [Indexed: 12/16/2022]
Abstract
PURPOSE Accurate identification of nodal status enables adequate neck irradiation for nasopharyngeal carcinoma (NPC). However, most conventional techniques are unable to pick up occult metastases, leading to underestimation of tumor extensions. Here we investigate the clinical significance of carbonic anhydrase IX (CAIX) in human NPC samples, and develop a CAIX-targeted imaging strategy to identify occult lymph node metastases (LNMs) and extranodal extension (ENE) in animal studies. METHODS A total of 211 NPC samples are performed CAIX staining, and clinical outcomes are analyzed. The metastatic murine models are generated by foot pad injection of NPC cells, and a CAIX-targeted imaging agent (CAIX-800) is intravenously administered. We adopt fluorescence molecular tomography and ultrasonography (US)-guided spectroscopic photoacoustic (sPA) imaging to perform in vivo studies. Histological and immunohistochemical characterization are carried out via node-by-node analysis. RESULTS For clinical samples, 90.1% (91/101) primary tumors, 73.3% (66/90) metastases, and 100% (20/20) local recurrences are CAIX positive. In metastases group, 84.7% (61/72) nodal metastases and 22.2% (4/18) organ metastases are CAIX positive. CAIX expression in primary tumors is significantly associated with NPC stage and prognosis. For animal studies, CAIX-800-based fluorescence imaging achieves 81.3% sensitivity and 93.8% specificity in detecting occult LNMs in vivo, with a minimum detectable diameter of 1.7 mm. Coupled with CAIX-800, US-guided sPA imaging could not only detect subcapsular deposits of metastatic cancer cells 2 weeks earlier than conventional techniques, but also successfully track pathological ENE. CONCLUSION CAIX remarkably expresses in human NPCs and stratifies patient prognosis. In preclinical studies, CAIX-800-based imaging successfully identifies occult LNMs and tracks early stage of pathological ENE. This attractive method shows potential in clinic, allowing medical workers to longitudinally monitor nodal status and helping to reduce unnecessary nodal biopsy for patients with NPC. The schematic diagram for the study. CAIX, carbonic anhydrase IX; NPC, nasopharyngeal carcinoma; US, ultrasonography; sPA, spectroscopic photoacoustic.
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Affiliation(s)
- Wenhui Huang
- College of Medicine and Biological Information Engineering, Northeastern University, 110057, Shenyang, China.,CAS Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, No. 95 Zhongguancun East Road, Haidian District, Beijing, 100190, China.,Medical Imaging Center, the First Affiliated Hospital, Jinan University, No. 613, Huangpu West Road, Tianhe District, 510632, Guangzhou, China
| | - Kun Wang
- CAS Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, No. 95 Zhongguancun East Road, Haidian District, Beijing, 100190, China
| | - Weiyuan Huang
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), 570311, Haikou, China
| | - Zicong He
- Medical Imaging Center, the First Affiliated Hospital, Jinan University, No. 613, Huangpu West Road, Tianhe District, 510632, Guangzhou, China
| | - Jingming Zhang
- Department of Nuclear Medicine, Peking University First Hospital, No. 8, Xishiku Road, Xicheng District, Beijing, 100034, China
| | - Bin Zhang
- Medical Imaging Center, the First Affiliated Hospital, Jinan University, No. 613, Huangpu West Road, Tianhe District, 510632, Guangzhou, China
| | - Zhiyuan Xiong
- Department of Chemical and Bio-Molecular Engineering, The University of Melbourne, Victoria 3010, Melbourne, Australia
| | - Kelly McCabe Gillen
- Department of Radiology, Weill Medical College of Cornell University, 407 E 61st Street, New York, NY, USA
| | - Wenzhe Li
- State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China
| | - Feng Chen
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), 570311, Haikou, China
| | - Xing Yang
- Department of Nuclear Medicine, Peking University First Hospital, No. 8, Xishiku Road, Xicheng District, Beijing, 100034, China.
| | - Shuixing Zhang
- Medical Imaging Center, the First Affiliated Hospital, Jinan University, No. 613, Huangpu West Road, Tianhe District, 510632, Guangzhou, China.
| | - Jie Tian
- College of Medicine and Biological Information Engineering, Northeastern University, 110057, Shenyang, China. .,CAS Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, No. 95 Zhongguancun East Road, Haidian District, Beijing, 100190, China. .,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, 100191, Beijing, China.
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