Pentimalli Tancredi Massimo, Karaiskos Nikos, Rajewsky Nikolaus
Charité - Universitätsmedizin Berlin, Berlin, Germany.
Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany; email:
Annu Rev Pathol. 2025 Jan;20(1):405-432. doi: 10.1146/annurev-pathmechdis-111523-023417. Epub 2025 Jan 2.
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.
病理学的发展一直得益于技术进步。组织学以单细胞分辨率推动了组织结构研究，至今仍是临床病理学的基石。在过去十年中，下一代测序技术已为多种疾病的靶向治疗提供了信息，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在完整组织切片中以亚细胞分辨率将基因表达数字化，使得对常规采集和存档的临床样本中的细胞类型、细胞表型及细胞间通讯进行计算分析成为可能。在此，我们回顾此类分子显微镜的工作原理，强调其在识别疾病机制和指导个性化治疗方面的潜力，并为临床研究设计提供指导。最后，我们讨论高分辨率空间转录组学技术快速转化面临的挑战，以及多模态读数与深度学习方法的整合如何让我们更接近对组织生物学和病理学的全面理解。
