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Davaapil H, Hopkins J, Bonnin N, Papadaki V, Leung A, Kosuge H, Tashima T, Nakakido M, Sekido R, Tsumoto K, Sagoo MS, Ohnuma SI. PRELP secreted from mural cells protects the function of blood brain barrier through regulation of endothelial cell-cell integrity. Front Cell Dev Biol 2023; 11:1147625. [PMID: 37936982 PMCID: PMC10626469 DOI: 10.3389/fcell.2023.1147625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 07/13/2023] [Indexed: 11/09/2023] Open
Abstract
Introduction: Proline/arginine-rich end leucine-rich repeat protein (PRELP), is a small secreted proteoglycan expressed by pericytes and vascular smooth muscle cells surrounding the brain vasculature of adult mouse. Methods: We utilised a Prelp knockout (Prelp -/-) mouse model to interrogate vasculature integrity in the brain alongside performing in vitro assays to characterise PRELP application to endothelial cells lines. Our findings were supplemented with RNA expression profiling to elucidate the mechanism of how PRELP maintains neurovasculature function. Results: Prelp -/- mice presented with neuroinflammation and reducedneurovasculature integrity, resulting in IgG and dextran leakage in the cerebellum and cortex. Histological analysis of Prelp -/- mice revealed reducedcell-cell integrity of the blood brain barrier, capillary attachment of pericytes andastrocyte end-feet. RNA-sequencing analysis found that cell-cell adhesion andinflammation are affected in Prelp -/- mice and gene ontology analysis as well as gene set enrichment analysis demonstrated that inflammation related processes and adhesion related processes such as epithelial-mesenchymal transition and apical junctions were significantly affected, suggesting PRELP is a regulator of cell-cell adhesion. Immunofluorescence analysis showed that adhesion junction protein expression levels of cadherin, claudin-5, and ZO-1, was suppressed in Prelp -/- mice neurovasculature. Additionally, in vitro studies revealed that PRELP application to endothelial cells enhances cell-cell integrity, induces mesenchymal-endothelial transition and inhibits TGF-β mediated damage to cell-cell adhesion. Discussion: Our study indicates that PRELP is a novel endogenous secreted regulator of neurovasculature integrity and that PRELP application may be a potential treatment for diseases associated with neurovascular damage.
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Affiliation(s)
| | - Jack Hopkins
- UCL Institute of Ophthalmology, UCL, London, Untited Kingdom
| | - Nadia Bonnin
- UCL Institute of Ophthalmology, UCL, London, Untited Kingdom
| | | | - Alex Leung
- UCL Institute of Ophthalmology, UCL, London, Untited Kingdom
| | - Hirofumi Kosuge
- Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Takumi Tashima
- Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Makoto Nakakido
- Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Ryohei Sekido
- UCL Institute of Ophthalmology, UCL, London, Untited Kingdom
| | - Kouhei Tsumoto
- Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Mandeep S. Sagoo
- UCL Institute of Ophthalmology, UCL, London, Untited Kingdom
- NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital, London, Untited Kingdom
- Retinoblastoma Genetic Screening Unit, Barts Health NHS Trust, Royal London Hospital, London, Untited Kingdom
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Schäfer H, Subbarayan K, Massa C, Vaxevanis C, Mueller A, Seliger B. Correlation of the tumor escape phenotype with loss of PRELP expression in melanoma. J Transl Med 2023; 21:643. [PMID: 37730606 PMCID: PMC10512569 DOI: 10.1186/s12967-023-04476-x] [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: 06/09/2023] [Accepted: 08/27/2023] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND Despite immunotherapies having revolutionized the treatment of advanced cutaneous melanoma, effective and durable responses were only reported in a few patients. A better understanding of the interaction of melanoma cells with the microenvironment, including extracellular matrix (ECM) components, might provide novel therapeutic options. Although the ECM has been linked to several hallmarks of cancer, little information is available regarding the expression and function of the ECM protein purine-arginine-rich and leucine-rich protein (PRELP) in cancer, including melanoma. METHODS The structural integrity, expression and function of PRELP, its correlation with the expression of immune modulatory molecules, immune cell infiltration and clinical parameters were determined using standard methods and/or bioinformatics. RESULTS Bioinformatics analysis revealed a heterogeneous, but statistically significant reduced PRELP expression in available datasets of skin cutaneous melanoma when compared to adjacent normal tissues, which was associated with reduced patients' survival, low expression levels of components of the MHC class I antigen processing machinery (APM) and interferon (IFN)-γ signal transduction pathway, but increased expression of the transforming growth factor (TGF)-β isoform 1 (TFGB1) and TGF-β receptor 1 (TGFBR1). In addition, a high frequency of intra-tumoral T cells directly correlated with the expression of MHC class I and PRELP as well as the T cell attractant CCL5 in melanoma lesions. Marginal to low PRELP expression levels were found in the 47/49 human melanoma cell lines analysis. Transfection of PRELP into melanoma cell lines restored MHC class I surface expression due to transcriptional upregulation of major MHC class I APM and IFN-γ pathway components. In addition, PRELP overexpression is accompanied by high CCL5 secretion levels in cell supernatant, an impaired TGF-β signaling as well as a reduced cell proliferation, migration and invasion of melanoma cells. CONCLUSIONS Our findings suggest that PRELP induces the expression of MHC class I and CCL5 in melanoma, which might be involved in an enhanced T cell recruitment and immunogenicity associated with an improved patients' outcome. Therefore, PRELP might serve as a marker for predicting disease progression and its recovery could revert the tumorigenic phenotype, which represents a novel therapeutic option for melanoma.
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Affiliation(s)
- Helene Schäfer
- Medical Faculty, Martin Luther University Halle-Wittenberg, Magdeburger Str. 2, 06112, Halle (Saale), Germany
| | - Karthikeyan Subbarayan
- Medical Faculty, Martin Luther University Halle-Wittenberg, Magdeburger Str. 2, 06112, Halle (Saale), Germany
| | - Chiara Massa
- Medical Faculty, Martin Luther University Halle-Wittenberg, Magdeburger Str. 2, 06112, Halle (Saale), Germany
| | - Christoforos Vaxevanis
- Medical Faculty, Martin Luther University Halle-Wittenberg, Magdeburger Str. 2, 06112, Halle (Saale), Germany
| | - Anja Mueller
- Medical Faculty, Martin Luther University Halle-Wittenberg, Magdeburger Str. 2, 06112, Halle (Saale), Germany
| | - Barbara Seliger
- Medical Faculty, Martin Luther University Halle-Wittenberg, Magdeburger Str. 2, 06112, Halle (Saale), Germany.
- Fraunhofer Institute for Cell Therapy and Immunology, Perlickstr. 1, 04103, Leipzig, Germany.
- Institute of Translational Medicine, Medical School Brandenburg, Hochstr. 29, 14770, Brandenburg an der Havel, Germany.
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Mezentsev Y, Ershov P, Yablokov E, Kaluzhskiy L, Kupriyanov K, Gnedenko O, Ivanov A. Protein Interactome Profiling of Stable Molecular Complexes in Biomaterial Lysate. Int J Mol Sci 2022; 23:ijms232415697. [PMID: 36555337 PMCID: PMC9779103 DOI: 10.3390/ijms232415697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022] Open
Abstract
Most proteins function as part of various complexes, forming via stable and dynamic protein-protein interactions (PPIs). The profiling of PPIs expands the fundamental knowledge about the structures, functions, and regulation patterns of protein complexes and intracellular molecular machineries. Protein interactomics aims at solving three main tasks: (1) identification of protein partners and parts of complex intracellular structures; (2) analysis of PPIs parameters (affinity, molecular-recognition specificity, kinetic rate constants, and thermodynamic-parameters determination); (3) the study of the functional role of novel PPIs. The purpose of this work is to update the current state and prospects of multi-omics approaches to profiling of proteins involved in the formation of stable complexes. Methodological paradigm includes a development of protein-extraction and -separation techniques from tissues or cellular lysates and subsequent identification of proteins using mass-spectrometry analysis. In addition, some aspects of authors' experimental platforms, based on high-performance size-exclusion chromatography, procedures of molecular fishing, and protein identification, as well as the possibilities of interactomic taxonomy of each protein, are discussed.
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Dozen A, Shozu K, Shinkai N, Ikawa N, Aoyama R, Machino H, Asada K, Yoshida H, Kato T, Hamamoto R, Kaneko S, Komatsu M. Tumor Suppressive Role of the PRELP Gene in Ovarian Clear Cell Carcinoma. J Pers Med 2022; 12:jpm12121999. [PMID: 36556220 PMCID: PMC9785654 DOI: 10.3390/jpm12121999] [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] [Received: 11/01/2022] [Revised: 11/18/2022] [Accepted: 11/29/2022] [Indexed: 12/12/2022] Open
Abstract
Ovarian clear cell carcinoma (OCCC) has a poor prognosis, and its therapeutic strategy has not been established. PRELP is a leucine-rich repeat protein in the extracellular matrix of connective tissues. Although PRELP anchors the basement membrane to the connective tissue and is absent in most epithelial cancers, much remains unknown regarding its function as a regulator of ligand-mediated signaling pathways. Here, we obtained sets of differentially expressed genes by PRELP expression using OCCC cell lines. We found that more than 1000 genes were significantly altered by PRELP expression, particularly affecting the expression of a group of genes involved in the PI3K-AKT signaling pathway. Furthermore, we revealed the loss of active histone marks on the loci of the PRELP gene in patients with OCCC and how its forced expression inhibited cell proliferation. These findings suggest that PRELP is not only a molecule anchored in connective tissues but is also a signaling molecule acting in a tumor-suppressive manner. It can serve as the basis for early detection and novel therapeutic approaches for OCCC toward precision medicine.
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Affiliation(s)
- Ai Dozen
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
- Department of Obstetrics and Gynecology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Kanto Shozu
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
- Department of Obstetrics and Gynecology, University of Toyama, 2630 Sugitani, Toyama 930-0194, Japan
| | - Norio Shinkai
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
- Department of NCC Cancer Science, Biomedical Science and Engineering Track, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan
| | - Noriko Ikawa
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
| | - Rina Aoyama
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
- Department of Obstetrics and Gynecology, Showa University School of Medicine, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8666, Japan
| | - Hidenori Machino
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
| | - Ken Asada
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
| | - Hiroshi Yoshida
- Department of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104–0045, Japan
| | - Tomoyasu Kato
- Department of Gynecology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104–0045, Japan
| | - Ryuji Hamamoto
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
- Department of NCC Cancer Science, Biomedical Science and Engineering Track, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan
| | - Syuzo Kaneko
- Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
- Correspondence: (S.K.); (M.K.); Tel.: +81-3-3547-5201 (S.K. & M.K.)
| | - Masaaki Komatsu
- Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
- Correspondence: (S.K.); (M.K.); Tel.: +81-3-3547-5201 (S.K. & M.K.)
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Shozu K, Kaneko S, Shinkai N, Dozen A, Kosuge H, Nakakido M, Machino H, Takasawa K, Asada K, Komatsu M, Tsumoto K, Ohnuma SI, Hamamoto R. Repression of the PRELP gene is relieved by histone deacetylase inhibitors through acetylation of histone H2B lysine 5 in bladder cancer. Clin Epigenetics 2022; 14:147. [PMID: 36371227 PMCID: PMC9656081 DOI: 10.1186/s13148-022-01370-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 11/04/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Proline/arginine-rich end leucine-rich repeat protein (PRELP) is a member of the small leucine-rich proteoglycan family of extracellular matrix proteins, which is markedly suppressed in the majority of early-stage epithelial cancers and plays a role in regulating the epithelial-mesenchymal transition by altering cell-cell adhesion. Although PRELP is an important factor in the development and progression of bladder cancer, the mechanism of PRELP gene repression remains unclear. RESULTS Here, we show that repression of PRELP mRNA expression in bladder cancer cells is alleviated by HDAC inhibitors (HDACi) through histone acetylation. Using ChIP-qPCR analysis, we found that acetylation of lysine residue 5 of histone H2B in the PRELP gene promoter region is a marker for the de-repression of PRELP expression. CONCLUSIONS These results suggest a mechanism through which HDACi may partially regulate the function of PRELP to suppress the development and progression of bladder cancer. Some HDACi are already in clinical use, and the findings of this study provide a mechanistic basis for further investigation of HDACi-based therapeutic strategies.
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Affiliation(s)
- Kanto Shozu
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan ,grid.267346.20000 0001 2171 836XDepartment of Obstetrics and Gynecology, University of Toyama, Toyama, Japan
| | - Syuzo Kaneko
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan ,grid.509456.bRIKEN Center for Advanced Intelligence Project, Cancer Translational Research Team, Tokyo, Japan
| | - Norio Shinkai
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan ,grid.509456.bRIKEN Center for Advanced Intelligence Project, Cancer Translational Research Team, Tokyo, Japan ,grid.265073.50000 0001 1014 9130Department of NCC Cancer Science, Biomedical Science and Engineering Track, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Ai Dozen
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan
| | - Hirofumi Kosuge
- grid.26999.3d0000 0001 2151 536XSchool of Engineering, The University of Tokyo, Tokyo, Japan
| | - Makoto Nakakido
- grid.26999.3d0000 0001 2151 536XSchool of Engineering, The University of Tokyo, Tokyo, Japan
| | - Hidenori Machino
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan ,grid.509456.bRIKEN Center for Advanced Intelligence Project, Cancer Translational Research Team, Tokyo, Japan
| | - Ken Takasawa
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan ,grid.509456.bRIKEN Center for Advanced Intelligence Project, Cancer Translational Research Team, Tokyo, Japan
| | - Ken Asada
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan ,grid.509456.bRIKEN Center for Advanced Intelligence Project, Cancer Translational Research Team, Tokyo, Japan
| | - Masaaki Komatsu
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan ,grid.509456.bRIKEN Center for Advanced Intelligence Project, Cancer Translational Research Team, Tokyo, Japan
| | - Kouhei Tsumoto
- grid.26999.3d0000 0001 2151 536XSchool of Engineering, The University of Tokyo, Tokyo, Japan
| | - Shin-Ichi Ohnuma
- grid.83440.3b0000000121901201UCL Institute of Ophthalmology, University College London, 11-43 Bath Street, London, EC1V 9EL UK ,grid.5335.00000000121885934Department of Oncology, The Hutchison/MRC Research Center, University of Cambridge, Hills Road, Cambridge, CB2 2XZ UK
| | - Ryuji Hamamoto
- grid.272242.30000 0001 2168 5385Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045 Japan ,grid.509456.bRIKEN Center for Advanced Intelligence Project, Cancer Translational Research Team, Tokyo, Japan
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