扩大大型组织的空间转录组学：利用iSCALE揭示传统平台之外的细胞级组织结构，这一成果由宾夕法尼亚大学Mingyao Li课题组经过不懈努力而取得。这一研究成果发表在2025年9月15日出版的国际学术期刊《自然—方法学》上。

在这里，课题组提出了iSCALE，一种重建大规模，超分辨率基因表达景观的方法，并在超过当前ST平台捕获区域的样本中自动注释细胞水平的组织结构。通过基准实验、免疫组织化学染色和病理学家手工注释等综合评价来评估iSCALE的性能。当应用于多发性硬化症人脑样本时，iSCALE揭示了常规ST实验无法检测到的病变相关细胞特征。他们的研究结果证明了iSCALE在分析大组织方面的实用性，通过实现无偏注释，解析细胞类型组成，绘制细胞微环境和揭示超出标准ST分析或常规组织病理学评估范围的空间特征。

据介绍，空间转录组学（ST）技术的最新进展已经改变了它们在保留组织内关键空间背景的同时描述基因表达的能力。然而，现有的ST平台受到高成本、长周转时间、低分辨率、有限的基因覆盖和固有的小组织捕获区域的限制，阻碍了它们的广泛应用。

附：英文原文

Title: Scaling up spatial transcriptomics for large-sized tissues: uncovering cellular-level tissue architecture beyond conventional platforms with iSCALE

Author: Schroeder, Amelia, Loth, Melanie L., Luo, Chunyu, Yao, Sicong, Yan, Hanying, Zhang, Daiwei, Piya, Sarbottam, Plowey, Edward, Hu, Wenxing, Clemenceau, Jean R., Jang, Inyeop, Kim, Minji, Barnfather, Isabel, Chan, Su Jing, Reynolds, Taylor L., Carlile, Thomas, Cullen, Patrick, Sung, Ji-Youn, Tsai, Hui-Hsin, Park, Jeong Hwan, Hwang, Tae Hyun, Zhang, Baohong, Li, Mingyao

Issue&Volume: 2025-09-15

Abstract: Recent advances in spatial transcriptomics (ST) technologies have transformed our ability to profile gene expression while preserving crucial spatial context within tissues. However, existing ST platforms are constrained by high costs, long turnaround times, low resolution, limited gene coverage and inherently small tissue capture areas, which hinder their broad applications. Here we present iSCALE, a method that reconstructs large-scale, super-resolution gene expression landscapes and automatically annotates cellular-level tissue architecture in samples exceeding capture areas of current ST platforms. The performance of iSCALE was assessed by comprehensive evaluations involving benchmarking experiments, immunohistochemistry staining and manual annotations by pathologists. When applied to multiple sclerosis human brain samples, iSCALE uncovered lesion-associated cellular characteristics undetectable by conventional ST experiments. Our results demonstrate the utility of iSCALE in analyzing large tissues by enabling unbiased annotation, resolving cell type composition, mapping cellular microenvironments and revealing spatial features beyond the reach of standard ST analysis or routine histopathological assessment.

DOI: 10.1038/s41592-025-02770-8

Source: https://www.nature.com/articles/s41592-025-02770-8