Laboratory of Systems Pharmacology, Harvard Medical School, Boston, United States.
Ludwig Center for Cancer Research at Harvard, Harvard Medical School, Boston, United States.
Elife. 2018 Jul 11;7:e31657. doi: 10.7554/eLife.31657.
The architecture of normal and diseased tissues strongly influences the development and progression of disease as well as responsiveness and resistance to therapy. We describe a tissue-based cyclic immunofluorescence (t-CyCIF) method for highly multiplexed immuno-fluorescence imaging of formalin-fixed, paraffin-embedded (FFPE) specimens mounted on glass slides, the most widely used specimens for histopathological diagnosis of cancer and other diseases. t-CyCIF generates up to 60-plex images using an iterative process (a cycle) in which conventional low-plex fluorescence images are repeatedly collected from the same sample and then assembled into a high-dimensional representation. t-CyCIF requires no specialized instruments or reagents and is compatible with super-resolution imaging; we demonstrate its application to quantifying signal transduction cascades, tumor antigens and immune markers in diverse tissues and tumors. The simplicity and adaptability of t-CyCIF makes it an effective method for pre-clinical and clinical research and a natural complement to single-cell genomics.
正常组织和病变组织的结构强烈影响疾病的发展和进程，以及对治疗的反应性和耐药性。我们描述了一种基于组织的循环免疫荧光（t-CyCIF）方法，用于对固定在载玻片上的福尔马林固定、石蜡包埋（FFPE）标本进行高度多重免疫荧光成像，这些标本是用于癌症和其他疾病的组织病理学诊断的最广泛使用的标本。t-CyCIF 使用迭代过程（循环）生成多达 60 重的图像，在该过程中，从同一样本中反复收集传统的低重荧光图像，然后将其组装成高维表示。t-CyCIF 不需要特殊的仪器或试剂，并且与超分辨率成像兼容；我们证明了它在定量信号转导级联、肿瘤抗原和免疫标志物在不同组织和肿瘤中的应用。t-CyCIF 的简单性和适应性使其成为临床前和临床研究的有效方法，并且是单细胞基因组学的自然补充。
