| Literature DB >> 29993362 |
Jia-Ren Lin1,2, Benjamin Izar1,2,3,4, Shu Wang1,5, Clarence Yapp1, Shaolin Mei1,3, Parin M Shah3, Sandro Santagata1,2,6,7, Peter K Sorger1,2.
Abstract
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.Entities:
Keywords: cancer biology; computational biology; human; immunopathology; multiplexed imaging; single-cell method; systems biology
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Year: 2018 PMID: 29993362 PMCID: PMC6075866 DOI: 10.7554/eLife.31657
Source DB: PubMed Journal: Elife ISSN: 2050-084X Impact factor: 8.140