![]() To do so, a number of proteins (the molecules involved in nearly all life’s processes) need to be tracked in healthy and diseased cells and tissues. ![]() This helps them to identify different types of tumor cells and to tailor the best treatment for the patient. However, clinicians and scientists often need to look into what happens inside individual cells in the tissues so they can understand how cancers arise and progress. These biopsies are then thinly sliced and treated with dyes to identify healthy and cancerous cells. To diagnose a disease such as cancer, doctors sometimes take small tissue samples called biopsies from the affected area. The simplicity and adaptability of t-C圜IF makes it an effective method for pre-clinical and clinical research and a natural complement to single-cell genomics. ![]() t-C圜IF 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. t-C圜IF 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. We describe a tissue-based cyclic immunofluorescence (t-C圜IF) 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. The architecture of normal and diseased tissues strongly influences the development and progression of disease as well as responsiveness and resistance to therapy.
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