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空间组学在移植肾活检样本分类中的应用。

Application of spatial-omics to the classification of kidney biopsy samples in transplantation.

作者信息

Tasca Paola, van den Berg Bernard M, Rabelink Ton J, Wang Gangqi, Heijs Bram, van Kooten Cees, de Vries Aiko P J, Kers Jesper

机构信息

Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands.

Leiden Transplant Center, Leiden University Medical Center, Leiden, the Netherlands.

出版信息

Nat Rev Nephrol. 2024 Nov;20(11):755-766. doi: 10.1038/s41581-024-00861-x. Epub 2024 Jul 4.

DOI:10.1038/s41581-024-00861-x
PMID:38965417
Abstract

Improvement of long-term outcomes through targeted treatment is a primary concern in kidney transplant medicine. Currently, the validation of a rejection diagnosis and subsequent treatment depends on the histological assessment of allograft biopsy samples, according to the Banff classification system. However, the lack of (early) disease-specific tissue markers hinders accurate diagnosis and thus timely intervention. This challenge mainly results from an incomplete understanding of the pathophysiological processes underlying late allograft failure. Integration of large-scale multimodal approaches for investigating allograft biopsy samples might offer new insights into this pathophysiology, which are necessary for the identification of novel therapeutic targets and the development of tailored immunotherapeutic interventions. Several omics technologies - including transcriptomic, proteomic, lipidomic and metabolomic tools (and multimodal data analysis strategies) - can be applied to allograft biopsy investigation. However, despite their successful application in research settings and their potential clinical value, several barriers limit the broad implementation of many of these tools into clinical practice. Among spatial-omics technologies, mass spectrometry imaging, which is under-represented in the transplant field, has the potential to enable multi-omics investigations that might expand the insights gained with current clinical analysis technologies.

摘要

通过靶向治疗改善长期预后是肾移植医学的主要关注点。目前,根据班夫分类系统,排斥反应诊断及后续治疗的验证依赖于移植肾活检样本的组织学评估。然而,缺乏(早期)疾病特异性组织标志物阻碍了准确诊断,进而影响及时干预。这一挑战主要源于对移植肾晚期失功潜在病理生理过程的不完全理解。整合用于研究移植肾活检样本的大规模多模态方法可能会为这种病理生理学提供新的见解,这对于确定新的治疗靶点和开发定制的免疫治疗干预措施是必要的。几种组学技术——包括转录组学、蛋白质组学、脂质组学和代谢组学工具(以及多模态数据分析策略)——可应用于移植肾活检研究。然而,尽管它们在研究环境中成功应用且具有潜在临床价值,但一些障碍限制了其中许多工具在临床实践中的广泛应用。在空间组学技术中,质谱成像在移植领域的应用较少,它有可能实现多组学研究,从而拓展当前临床分析技术所获得的见解。

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本文引用的文献

1
European Society of Organ Transplantation Consensus Statement on Testing for Non-Invasive Diagnosis of Kidney Allograft Rejection.欧洲器官移植学会关于非侵入性诊断肾移植排斥反应检测的共识声明。
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Multiomic profiling of transplant glomerulopathy reveals a novel T-cell dominant subclass.移植性肾小球病的多组学分析揭示了一种新的T细胞主导亚类。
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利用集成的单细胞、空间和原位分析技术对肿瘤微环境进行高分辨率图谱绘制。
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Evaluation of antibody-based single cell type imaging techniques coupled to multiplexed imaging of N-glycans and collagen peptides by matrix-assisted laser desorption/ionization mass spectrometry imaging.基于抗体的单细胞类型成像技术与基质辅助激光解吸/电离质谱成像联用对 N-糖肽和胶原肽的多重成像评价。
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Automated Urinary Chemokine Assays for Noninvasive Detection of Kidney Transplant Rejection: A Prospective Cohort Study.自动化尿液趋化因子检测在肾移植排斥非侵入性诊断中的应用:一项前瞻性队列研究。
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