4.3 Article

Immunohistochemical toolkit for tracking and quantifying xenotransplanted human stem cells

Journal

REGENERATIVE MEDICINE
Volume 9, Issue 4, Pages 437-452

Publisher

FUTURE MEDICINE LTD
DOI: 10.2217/RME.14.26

Keywords

cell therapy; human-specific biomarker; image quantification; stem cells; xenotransplantation

Funding

  1. Thierry Latran Foundation
  2. INSERM
  3. Institut Pasteur
  4. NIH [1R01NS079702]
  5. Craig H. Neilsen Foundation [190140]
  6. Televie program of the 'Fonds National de la Recherche Scientifique' (FNRS, Brussels, Belgium)
  7. Fonds Yvonne Boel
  8. European Regional Development Fund
  9. Walloon Region

Ask authors/readers for more resources

Aim: Biomarker-based tracking of human stem cells xenotransplanted into animal models is crucial for studying their fate in the field of cell therapy or tumor xenografting. Materials & methods: Using immunohistochemistry and in situ hybridization, we analyzed the expression of three human-specific biomarkers: Ku80, human mitochondria (hMito) and Alu. Results: We showed that Ku80, hMito and Alu biomarkers are broadly expressed in human tissues with no or low cross-reactivity toward rat, mouse or pig tissues. In vitro, we demonstrated that their expression is stable over time and does not change along the differentiation of human-derived induced pluripotent stem cells or human glial-restricted precursors. We tracked in vivo these cell populations after transplantation in rodent spinal cords using aforementioned biomarkers and human-specific antibodies detecting apoptotic, proliferating or neural-committed cells. Conclusion: This study assesses the human-species specificity of Ku80, hMito and Alu, and proposes useful biomarkers for characterizing human stem cells in xenotransplantation paradigms.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Oncology

The daily practice reality of PD-L1 (CD274) evaluation in non-small cell lung cancer: A retrospective study

Camille Verocq, Christine Decaestecker, Laureen Rocq, Sarah De Clercq, Audrey Verrellen, Zita Mekinda, Sebahat Ocak, Christophe Compere, Claudia Stanciu-Pop, Isabelle Salmon, Myriam Remmelink, Nicky D'Haene

ONCOLOGY LETTERS (2020)

Article Oncology

A Novel Approach for Quantifying Cancer Cells Showing Hybrid Epithelial/Mesenchymal States in Large Series of Tissue Samples: Towards a New Prognostic Marker

Louis Godin, Cedric Balsat, Yves-Remi Van Eycke, Justine Allard, Claire Royer, Myriam Remmelink, Ievgenia Pastushenko, Nicky D'Haene, Cedric Blanpain, Isabelle Salmon, Sandrine Rorive, Christine Decaestecker

CANCERS (2020)

Article Neurosciences

Clinical, radiological and molecular characterization of intramedullary astrocytomas

Laetitia Lebrun, Barbara Melendez, Oriane Blanchard, Nancy De Neve, Claude Van Campenhout, Julie Lelotte, Danielle Baleriaux, Matteo Riva, Jacques Brotchi, Michael Bruneau, Olivier De Witte, Christine Decaestecker, Nicky D'Haene, Isabelle Salmon

ACTA NEUROPATHOLOGICA COMMUNICATIONS (2020)

Article Neurosciences

Modifying macrophages at the periphery has the capacity to change microglial reactivity and to extend ALS survival

Aude Chiot, Sakina Zaidi, Charlene Iltis, Matthieu Ribon, Felix Berriat, Lorenzo Schiaffino, Ariane Jolly, Pierre de la Grange, Michel Mallat, Delphine Bohl, Stephanie Millecamps, Danielle Seilhean, Christian S. Lobsiger, Severine Boillee

NATURE NEUROSCIENCE (2020)

Article Geriatrics & Gerontology

Deletion of the inflammatory S100-A9/MRP14 protein does not influence survival in hS0D1G93A ALS mice

Matthieu Ribon, Celine Leone, Aude Chiot, Felix Berriat, Martine Rampanana, Julie Cottin, Delphine Bohl, Stephanie Millecamps, Christian S. Lobsiger, Michael T. Heneka, Severine Boillee

Summary: Neuroinflammation is a hallmark of ALS, where deletion of S100a9 did not improve mouse survival but instead accelerated symptoms, indicating that blocking 5100-A9 is not a viable strategy for treating ALS.

NEUROBIOLOGY OF AGING (2021)

Article Oncology

Voxelwise Principal Component Analysis of Dynamic [S-Methyl-11C]Methionine PET Data in Glioma Patients

Corentin Martens, Olivier Debeir, Christine Decaestecker, Thierry Metens, Laetitia Lebrun, Gil Leurquin-Sterk, Nicola Trotta, Serge Goldman, Gaetan Van Simaeys

Summary: Recent research on dynamic amino acid positron emission tomography (PET) in gliomas has shown potential for extracting key features with the use of principal component analysis (PCA) to better understand intra-tumor heterogeneity. The PCA model outperforms traditional pharmacokinetic modeling in distinguishing characteristic dynamic uptake behaviors within the tumor.

CANCERS (2021)

Article Pathology

Severe Acute Respiratory Syndrome Coronavirus 2 (BARS-CoV-2) Genome Sequencing from Post-Mortem Formalin-Fixed, Paraffin-Embedded Lung Tissues

Claude Van Campenhout, Ricardo De Mendonca, Barbara Alexiou, Sarah De Clercq, Marie-Lucie Racu, Claire Royer-Chardon, Stefan Rusu, Marie Van Eycken, Maria Artesi, Keith Durkin, Patrick Mardulyn, Vincent Bours, Christine Decaestecker, Myriam Remmelink, Isabell Salmon, Nicky D'Haene

Summary: This study validates the feasibility of SARS-CoV-2 genome sequencing on FFPE lung tissues from deceased COVID-19 patients.

JOURNAL OF MOLECULAR DIAGNOSTICS (2021)

Review Neurosciences

Neuroinflammation in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia and the Interest of Induced Pluripotent Stem Cells to Study Immune Cells Interactions With Neurons

Elise Liu, Lea Karpf, Delphine Bohl

Summary: Inflammation is a shared hallmark between ALS and FTD, now recognized as a potential driver of the diseases. The iPSC technology offers hope in studying intercellular interactions and disease-specific defects. New cellular tools could potentially lead to new therapeutic approaches for ALS, ALS-FTD, and FTD patients.

FRONTIERS IN MOLECULAR NEUROSCIENCE (2021)

Editorial Material Computer Science, Interdisciplinary Applications

Comments on MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge

Adrien Foucart, Olivier Debeir, Christine Decaestecker

Summary: The MoNuSAC 2020 challenge hosted at the ISBI 2020 conference has been analyzed, revealing three problems in the computation of the metric used for ranking. The incorrect code version was used to rank the algorithms in the challenge. The results can be replicated using the code provided on GitHub.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2022)

Article Oncology

Deep Learning for Reaction-Diffusion Glioma Growth Modeling: Towards a Fully Personalized Model?

Corentin Martens, Antonin Rovai, Daniele Bonatto, Thierry Metens, Olivier Debeir, Christine Decaestecker, Serge Goldman, Gaetan Van Simaeys

Summary: This research proposed a deep learning-based approach to address problems in glioma growth models. By training deep neural networks, it is possible to reconstruct the cell-density distribution of the tumor and accurately evaluate model parameters. This approach has significant potential application value for glioma characterization and therapy planning.

CANCERS (2022)

Article Computer Science, Artificial Intelligence

Evaluating participating methods in image analysis challenges: Lessons from MoNuSAC 2020

Adrien Foucart, Olivier Debeir, Christine Decaestecker

Summary: Biomedical image analysis competitions often use a single metric to rank participants, which makes it difficult to assess the strengths and weaknesses of algorithms. The MoNuSAC 2020 challenge provides an interesting opportunity to study the information lost by using entangled metrics by involving multiple capabilities and releasing prediction masks from different teams. The results analysis using Panoptic Quality (PQ) and disentangled metrics shows that PQ hides interesting aspects of the results and is sensitive to small changes in prediction masks, making it hard to interpret and draw insights from the results. Access to raw predictions from participating teams is necessary for better analysis and usefulness to the research community.

PATTERN RECOGNITION (2023)

Article Radiology, Nuclear Medicine & Medical Imaging

Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study

Corentin Martens, Laetitia Lebrun, Christine Decaestecker, Thomas Vandamme, Yves-Remi Van Eycke, Antonin Rovai, Thierry Metens, Olivier Debeir, Serge Goldman, Isabelle Salmon, Gaetan Van Simaeys

Summary: This study uses a 3D-printed slicer for stereotactic histological analysis of an unoperated brain with glioblastoma, revealing limitations of conventional MRI in deriving glioma cell density maps and emphasizing the need for other initialization methods for reaction-diffusion models in clinical practice.

TOMOGRAPHY (2021)

Article Clinical Neurology

Analyses of DNA Methylation Profiling in the Diagnosis of Intramedullary Astrocytomas

Laetitia Lebrun, Martin Bizet, Barbara Melendez, Barbara Alexiou, Lara Absil, Claude Van Campenhout, Nicky D'Haene, Sandrine Rorive, Francois Fuks, Christine Decaestecker, Isabelle Salmon

Summary: In this study, 16 intramedullary astrocytoma (IMA) samples were analyzed, revealing that the current DNA methylation-based classification method is insufficient for accurate classification of IMAs. Further research is needed to provide pathologists with a more comprehensive tool for classification of IMAs.

JOURNAL OF NEUROPATHOLOGY AND EXPERIMENTAL NEUROLOGY (2021)

Review Medicine, General & Internal

Strategies to Reduce the Expert Supervision Required for Deep Learning-Based Segmentation of Histopathological Images

Yves-Remi Van Eycke, Adrien Foucart, Christine Decaestecker

FRONTIERS IN MEDICINE (2019)

Proceedings Paper Engineering, Biomedical

SNOW: SEMI SUPERVISED, NOISY AND/OR WEAK DATA FOR DEEP LEARNING IN DIGITAL PATHOLOGY

Adrien Foucart, Olivier Debeir, Christine Decaestecker

2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019) (2019)

No Data Available