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成骨细胞、骨骼和血液蛋白质组学数据的荟萃分析:对骨生物材料设计的可药物作用靶点、活性因子及潜在生物标志物的见解

Meta-analysis of proteomics data from osteoblasts, bone, and blood: Insights into druggable targets, active factors, and potential biomarkers for bone biomaterial design.

作者信息

Schmidt Johannes R, Adamowicz Klaudia, Arend Lis, Lehmann Jörg, List Markus, Poh Patrina Sp, Baumbach Jan, Kalkhof Stefan, Laske Tanja

机构信息

Department of Preclinical Development and Validation, Fraunhofer Institute for Cell Therapy and Immunology IZI, Leipzig, Germany.

Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany.

出版信息

J Tissue Eng. 2024 Nov 29;15:20417314241295332. doi: 10.1177/20417314241295332. eCollection 2024 Jan-Dec.

DOI:10.1177/20417314241295332
PMID:39620099
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11605762/
Abstract

Non-healing bone defects are a pressing public health concern accounting for one main cause for decreased life expectancy and quality. An aging population accompanied with increasing incidence of comorbidities, foreshadows a worsening of this socio-economic problem. Conventional treatments for non-healing bone defects prove ineffective for 5%-10% of fractures. Those challenges not only increase the patient's burden but also complicate medical intervention, underscoring the need for more effective treatment strategies and identification of patients at risk before treatment selection. To address this, our proteomic meta-analysis aims to identify universally affected proteins and functions in the context of bone regeneration that can be utilized as novel bioactive biomaterial functionalizations, drug targets or therapeutics as well as analytical endpoints, or biomarkers in implant design and testing, respectively. We compiled 29 proteomic studies covering cellular models, extracellular vesicles, extracellular matrix, bone tissue, and liquid-biopsies to address different tissue hierarchies and species. An innovative, integrated framework consisting of data harmonization, candidate protein selection, network construction, and functional enrichment as well as drug repurposing and protein scoring metrics was developed. To make this framework widely applicable to other research questions, we have published a detailed tutorial of our meta-analysis process. We identified 51 proteins that are potentially important for bone healing. This includes well-known ECM components such as collagens, fibronectin and periostin, and proteins less explored in bone biology like YWHAE, HSPG2, CCN1, HTRA1, IGFBP7, LGALS1, TGFBI, C3, SERPINA1, and ANXA1 that might be utilized in future bone biomaterial development. Furthermore, we discovered the compounds trifluoperazine, phenethyl isothiocyanate, quercetin, and artenimol, which target key proteins such as S100A4, YWHAZ, MMP2, and TPM4 providing the option to manipulate undesired processes in bone regeneration. This may open new ways for treatment options to face the increasing socio-economic pressure of non-healing bone defects.

摘要

难愈合骨缺损是一个紧迫的公共卫生问题,是预期寿命和生活质量下降的一个主要原因。人口老龄化伴随着合并症发病率的增加,预示着这一社会经济问题将恶化。传统的难愈合骨缺损治疗方法对5%-10%的骨折无效。这些挑战不仅增加了患者的负担,也使医疗干预复杂化,凸显了需要更有效的治疗策略以及在治疗选择前识别有风险的患者。为了解决这个问题,我们的蛋白质组学荟萃分析旨在确定在骨再生背景下普遍受到影响的蛋白质和功能,这些蛋白质和功能可分别用作新型生物活性生物材料功能化、药物靶点或治疗方法,以及植入物设计和测试中的分析终点或生物标志物。我们汇编了29项蛋白质组学研究,涵盖细胞模型、细胞外囊泡、细胞外基质、骨组织和液体活检,以研究不同的组织层次和物种。我们开发了一个创新的综合框架,包括数据协调、候选蛋白质选择、网络构建、功能富集以及药物再利用和蛋白质评分指标。为了使这个框架广泛适用于其他研究问题,我们已经发表了关于我们荟萃分析过程的详细教程。我们确定了51种对骨愈合可能重要的蛋白质。这包括众所周知的细胞外基质成分,如胶原蛋白、纤连蛋白和骨膜蛋白,以及在骨生物学中较少研究的蛋白质,如YWHAE、HSPG2、CCN1、HTRA1、IGFBP7、LGALS1、TGFBI、C3、SERPINA1和ANXA1,这些蛋白质可能会用于未来的骨生物材料开发。此外,我们发现了三氟拉嗪、异硫氰酸苯乙酯、槲皮素和蒿甲醚等化合物,它们靶向S100A4、YWHAZ、MMP2和TPM4等关键蛋白质,为调控骨再生中不期望的过程提供了选择。这可能为应对难愈合骨缺损日益增加的社会经济压力开辟新的治疗途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/48612e0279eb/10.1177_20417314241295332-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/dacff3c5303f/10.1177_20417314241295332-fig1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/48612e0279eb/10.1177_20417314241295332-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/dacff3c5303f/10.1177_20417314241295332-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/67c28f5b2815/10.1177_20417314241295332-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/e5ad4a6f15c5/10.1177_20417314241295332-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/a4fb417db22e/10.1177_20417314241295332-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/23ee9e1adb5d/10.1177_20417314241295332-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/4153d6d7497d/10.1177_20417314241295332-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b069/11605762/48612e0279eb/10.1177_20417314241295332-fig7.jpg

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