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Bondoc A, Glaser K, Jin K, Lake C, Cairo S, Geller J, Tiao G, Aronow B. Identification of distinct tumor cell populations and key genetic mechanisms through single cell sequencing in hepatoblastoma. Commun Biol 2021; 4:1049. [PMID: 34497364 PMCID: PMC8426487 DOI: 10.1038/s42003-021-02562-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 08/16/2021] [Indexed: 02/07/2023] Open
Abstract
Hepatoblastoma (HB) is the most common primary liver malignancy of childhood, and molecular investigations are limited and effective treatment options for chemoresistant disease are lacking. There is a knowledge gap in the investigation of key driver cells of HB in tumor. Here we show single cell ribonucleic acid sequencing (scRNAseq) analysis of human tumor, background liver, and patient derived xenograft (PDX) to demonstrate gene expression patterns within tumor and to identify intratumor cell subtype heterogeneity to define differing roles in pathogenesis based on intracellular signaling in pediatric HB. We have identified a driver tumor cell cluster in HB by genetic expression which can be examined to define disease mechanism and treatments. Identification of both critical mechanistic pathways combined with unique cell populations provide the basis for discovery and investigation of novel treatment strategies in vitro and in vivo.
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Affiliation(s)
- Alexander Bondoc
- Division of Pediatric General and Thoracic Surgery, Cincinnati Children's Hospital, Medical Center, Cincinnati, OH, USA.
| | - Kathryn Glaser
- Division of Pediatric General and Thoracic Surgery, Cincinnati Children's Hospital, Medical Center, Cincinnati, OH, USA
| | - Kang Jin
- Division of Biomedical Informatics, Developmental Biology, and Pediatrics, Cincinnati, Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Biomedical Informatics, University of Cincinnati, Cincinnati, OH, USA
| | - Charissa Lake
- Division of Pediatric General and Thoracic Surgery, Cincinnati Children's Hospital, Medical Center, Cincinnati, OH, USA
| | - Stefano Cairo
- Research and Development Unit, XenTech, Genopole-Campus 3, Fontaine, France
- Istituto di Ricerca Pediatrica (IRP), Corso Stati Uniti, Padua, Italy
| | - James Geller
- Division of Oncology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Gregory Tiao
- Division of Pediatric General and Thoracic Surgery, Cincinnati Children's Hospital, Medical Center, Cincinnati, OH, USA
| | - Bruce Aronow
- Division of Biomedical Informatics, Developmental Biology, and Pediatrics, Cincinnati, Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Biomedical Informatics, University of Cincinnati, Cincinnati, OH, USA
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Chen D, Nauen DW, Park HC, Li D, Yuan W, Li A, Guan H, Kut C, Chaichana KL, Bettegowda C, Quiñones-Hinojosa A, Li X. Label-free imaging of human brain tissue at subcellular resolution for potential rapid intra-operative assessment of glioma surgery. Am J Cancer Res 2021; 11:7222-7234. [PMID: 34158846 PMCID: PMC8210590 DOI: 10.7150/thno.59244] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/11/2021] [Indexed: 12/20/2022] Open
Abstract
Background: Frozen section and smear preparation are the current standard for intraoperative histopathology during cancer surgery. However, these methods are time-consuming and subject to limited sampling. Multiphoton microscopy (MPM) is a high-resolution non-destructive imaging technique capable of optical sectioning in real time with subcellular resolution. In this report, we systematically investigated the feasibility and translation potential of MPM for rapid histopathological assessment of label- and processing-free surgical specimens. Methods: We employed a customized MPM platform to capture architectural and cytological features of biological tissues based on two-photon excited NADH and FAD autofluorescence and second harmonic generation from collagen. Infiltrating glioma, an aggressive disease that requires subcellular resolution for definitive characterization during surgery, was chosen as an example for this validation study. MPM images were collected from resected brain specimens of 19 patients and correlated with histopathology. Deep learning was introduced to assist with image feature recognition. Results: MPM robustly captures diagnostic features of glioma including increased cellularity, cellular and nuclear pleomorphism, microvascular proliferation, necrosis, and collagen deposition. Preliminary application of deep learning to MPM images achieves high accuracy in distinguishing gray from white matter and cancer from non-cancer. We also demonstrate the ability to obtain such images from intact brain tissue with a multiphoton endomicroscope for intraoperative application. Conclusion: Multiphoton imaging correlates well with histopathology and is a promising tool for characterization of cancer and delineation of infiltration within seconds during brain surgery.
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Wang S, Lin B, Lin G, Lin R, Huang F, Liu W, Wang X, Liu X, Zhang Y, Wang F, Lin Y, Chen L, Chen J. Automated label-free detection of injured neuron with deep learning by two-photon microscopy. JOURNAL OF BIOPHOTONICS 2020; 13:e201960062. [PMID: 31602806 DOI: 10.1002/jbio.201960062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/18/2019] [Accepted: 09/27/2019] [Indexed: 06/10/2023]
Abstract
Stroke is a significant cause of morbidity and long-term disability globally. Detection of injured neuron is a prerequisite for defining the degree of focal ischemic brain injury, which can be used to guide further therapy. Here, we demonstrate the capability of two-photon microscopy (TPM) to label-freely identify injured neurons on unstained thin section and fresh tissue of rat cerebral ischemia-reperfusion model, revealing definite diagnostic features compared with conventional staining images. Moreover, a deep learning model based on convolutional neural network is developed to automatically detect the location of injured neurons on TPM images. We then apply deep learning-assisted TPM to evaluate the ischemic regions based on tissue edema, two-photon excited fluorescence signal intensity, as well as neuronal injury, presenting a novel manner for identifying the infarct core, peri-infarct area, and remote area. These results propose an automated and label-free method that could provide supplementary information to augment the diagnostic accuracy, as well as hold the potential to be used as an intravital diagnostic tool for evaluating the effectiveness of drug interventions and predicting potential therapeutics.
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Affiliation(s)
- Shu Wang
- College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
| | - Bingbing Lin
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Guimin Lin
- College of Physics & Electronic Information Engineering, Minjiang University, Fuzhou, China
| | - Ruolan Lin
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Feng Huang
- College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China
| | - Weilin Liu
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Xingfu Wang
- Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Xueyong Liu
- Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Yu Zhang
- Department of Pathology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Feng Wang
- Department of Neurosurgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Yuanxiang Lin
- Department of Neurosurgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Lidian Chen
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jianxin Chen
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
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König TT, Goedeke J, Muensterer OJ. Multiphoton microscopy in surgical oncology- a systematic review and guide for clinical translatability. Surg Oncol 2019; 31:119-131. [PMID: 31654957 DOI: 10.1016/j.suronc.2019.10.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 10/02/2019] [Accepted: 10/13/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND Multiphoton microscopy (MPM) facilitates three-dimensional, high-resolution functional imaging of unlabeled tissues in vivo and ex vivo. This systematic review discusses the diagnostic value, advantages and challenges in the practical use of MPM in surgical oncology. METHOD AND FINDINGS A Medline search was conducted in April 2019. Fifty-three original research papers investigating MPM compared to standard histology in human patients with solid tumors were identified. A qualitative synopsis and meta-analysis of 14 blinded studies was performed. Risk of bias and applicability were evaluated. MPM can image fresh, frozen or fixed tissues up to a depth 1000 μm in the z-plane. Best results including functional imaging and virtual histochemistry are obtained by in vivo imaging or scanning fresh tissue immediately after excision. Two-photon excited fluorescence by natural fluorophores of the cytoplasm and second harmonic generation signals by fluorophores of the extracellular matrix can be scanned simultaneously, providing high resolution optical histochemistry comparable to standard histology. Functional parameters like fluorescence lifetime imaging or optical redox ratio provide additional objective information. A major concern is inability to visualize the nucleus. However, in a subpopulation analysis of 440 specimens, MPM yielded a sensitivity of 94%, specificity of 96% and accuracy of 95% for the detection of malignant tissue. CONCLUSION MPM is a promising emerging technique in surgical oncology. Ex vivo imaging has high sensitivity, specificity and accuracy for the detection of tumor cells. For broad clinical application in vivo, technical challenges need to be resolved.
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Affiliation(s)
| | - Jan Goedeke
- Universitätsmedizin Mainz, Department of Pediatric Surgery, Mainz, Germany
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