Pathology has always been fueled by technological advances. Histology powered the study of tissue architecture at single-cell resolution and remains a cornerstone of clinical pathology today. In the last decade, next-generation sequencing has become informative for the targeted treatment of many diseases, demonstrating the importance of genome-scale molecular information for personalized medicine. Today, revolutionary developments in spatial transcriptomics technologies digitalize gene expression at subcellular resolution in intact tissue sections, enabling the computational analysis of cell types, cellular phenotypes, and cell–cell communication in routinely collected and archival clinical samples. Here we review how such molecular microscopes work, highlight their potential to identify disease mechanisms and guide personalized therapies, and provide guidance for clinical study design. Finally, we discuss remaining challenges to the swift translation of high-resolution spatial transcriptomics technologies and how integration of multimodal readouts and deep learning approaches is bringing us closer to a holistic understanding of tissue biology and pathology.

中文翻译：

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高分辨率空间转录组学临床转化的挑战和机遇


病理学一直受到技术进步的推动。组织学为单细胞分辨率的组织结构研究提供了动力，至今仍是临床病理学的基石。在过去十年中，新一代测序已成为许多疾病靶向治疗的信息，证明了基因组规模分子信息对个性化医疗的重要性。如今，空间转录组学技术的革命性发展使完整组织切片中亚细胞分辨率的基因表达数字化，从而能够对常规收集和存档临床样本中的细胞类型、细胞表型和细胞间通讯进行计算分析。在这里，我们回顾了这种分子显微镜的工作原理，强调了它们识别疾病机制和指导个性化治疗的潜力，并为临床研究设计提供指导。最后，我们讨论了高分辨率空间转录组学技术快速转化仍然存在的挑战，以及多模态读数和深度学习方法的集成如何使我们更接近对组织生物学和病理学的整体理解。