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临床来源人体组织数字空间分析的严谨性与可重复性

Rigor and Reproducibility of Digital Spatial Profiling on Clinically Sourced Human Tissues.

作者信息

Smith Kelly D, MacDonald James W, Li Xianwu, Beirne Emily, Stewart Galen, Bammler Theo K, Akilesh Shreeram

机构信息

Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195.

Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98105.

出版信息

bioRxiv. 2024 Oct 18:2024.10.16.618750. doi: 10.1101/2024.10.16.618750.

Abstract

Spatial transcriptomic profiling enables precise quantification of gene expression with simultaneous localization of expression profiles onto tissue structures. This new technology promises to improve our understanding of the disease mechanisms. Therefore, there is intense interest in applying these methods in clinical trials or as laboratory developed tests to aid in diagnosis of disease. Before these technologies can be more broadly deployed in clinical research and diagnostics, it is necessary to thoroughly understand their performance in real world conditions. In this study, we vet technical reproducibility, data normalization methods and assay sensitivity focusing predominantly on one widely used spatial transcriptomic methodology, digital spatial profiling. Using clinically sourced human tissue specimens, we find that digital spatial profiling exhibits high rigor and reproducibility. Our approach lays the foundation for incorporation of digital spatial profiling methods into clinical workflows.

摘要

空间转录组分析能够精确量化基因表达,并将表达谱同时定位到组织结构上。这项新技术有望增进我们对疾病机制的理解。因此,人们对将这些方法应用于临床试验或作为实验室研发的检测手段以辅助疾病诊断有着浓厚的兴趣。在这些技术能够更广泛地应用于临床研究和诊断之前,有必要全面了解它们在实际条件下的性能。在本研究中,我们主要针对一种广泛使用的空间转录组方法——数字空间分析,审查其技术可重复性、数据归一化方法和检测灵敏度。使用临床来源的人体组织标本,我们发现数字空间分析具有高度的严谨性和可重复性。我们的方法为将数字空间分析方法纳入临床工作流程奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7bd/11507912/66da5f864796/nihpp-2024.10.16.618750v1-f0001.jpg

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