Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes.
Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes.
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DOI：
10.7554/elife.31657
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发表时间：
2018-07-11
期刊：
影响因子：
7.7
通讯作者：
Sorger PK
中科院分区：
文献类型：
--
作者：
Lin JR;Izar B;Wang S;Yapp C;Mei S;Shah PM;Santagata S;Sorger PK
正常和患病组织的结构强烈影响疾病的发展和进展以及对治疗的反应性和抗性。我们描述了一种基于组织的循环免疫荧光（t-CyCIF）方法，用于福尔马林固定，石蜡包埋（FFPE）标本安装在载玻片上的高度多重免疫荧光成像，最广泛使用的标本用于癌症和其他疾病的组织病理学诊断。t-CyCIF使用迭代过程（循环）生成高达60重的图像，其中从同一样品重复收集常规的低重荧光图像，然后将其组装成高维表示。t-CyCIF不需要专门的仪器或试剂，并且与超分辨率成像兼容;我们展示了其在不同组织和肿瘤中定量信号转导级联、肿瘤抗原和免疫标记物的应用。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，也是单细胞基因组学的自然补充。为了诊断像癌症这样的疾病，医生有时会从受影响的区域采集小的组织样本，称为活组织检查。然后将这些活检切片并用染料处理以识别健康和癌细胞。然而，临床医生和科学家经常需要研究组织中单个细胞内部发生的事情，以便他们能够了解癌症如何发生和发展。这有助于他们识别不同类型的肿瘤细胞，并为患者量身定制最佳治疗方案。要做到这一点，需要在健康和患病的细胞和组织中跟踪许多蛋白质（几乎所有生命过程中所涉及的分子）。这可以通过一系列称为免疫荧光显微镜的方法来实现，但是在同一切片上跟踪不同的蛋白质是困难的。然而，一种称为t-CyCIF的新型免疫荧光可能是一种解决方案。通过这种技术，应用荧光化合物，其将结合到感兴趣的特定蛋白质。当对样品成像时，显微镜可以从化合物中拾取光，从而揭示蛋白质在细胞或组织中的位置。然后，使用使荧光信号失活的物质。在此之后，使用另一种与新型蛋白质结合的化合物并成像。这个循环重复几次以定位不同的蛋白质。最后，将单个图像处理并拼接在一起，以揭示细胞及其内部结构。在这里，Lin，Izar等人表明，t-CyCIF可用于研究活检，并获得覆盖大面积健康人体组织和肿瘤的图像。该技术帮助追踪了人类患者正常和肿瘤组织样本中的60多种不同蛋白质。几组实验表明，t-CyCIF可以揭示癌症过程中被破坏的分子机制，但也揭示了单个肿瘤的复杂性。事实上，正如脑癌的活检所示，肿瘤中的癌细胞可以是惊人的不同，即使它们彼此接近。最后，该方法有助于确定哪些类型的免疫细胞参与对抗肾脏肿瘤。总的来说，这些信息不能用常规方法获得，但对诊断和治疗至关重要。大多数实验室可以很容易地使用t-CyCIF，因为该技术是开源的，并且需要容易获得的设备。事实上，这项技术应该很快就能用于评估某些药物帮助免疫系统对抗癌症的效果。最终，更好地利用活检是定制癌症护理的关键。
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. To diagnose a disease such as cancer, doctors sometimes take small tissue samples called biopsies from the affected area. These biopsies are then thinly sliced and treated with dyes to identify healthy and cancerous cells. 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. This helps them to identify different types of tumor cells and to tailor the best treatment for the patient. 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 can be done thanks to a range of methods known as immunofluorescence microscopy, but following different proteins on the same slice of a sample is difficult. However, a new type of immunofluorescence known as t-CyCIF may be a solution. With this technique, a fluorescent compound is applied that will bind to a specific protein of interest. A microscope can pick up the light from the compound when the sample is imaged, which reveals the protein’s location in the cell or tissue. Then, a substance is used that deactivates the fluorescence signal. After this, another compound that binds to a new type of protein is used, and imaged. This cycle is repeated several times to locate different proteins. Lastly, the individual images are processed and stitched together to reveal the cells and their internal structures. Here, Lin, Izar et al. showed that t-CyCIF could be used to study biopsies and to obtain images that covered a large area of healthy human tissues and tumors. The technique helped to track over 60 different proteins in normal and tumor tissue samples from human patients. Several sets of experiments showed that t-CyCIF could uncover the molecular mechanisms that are disrupted during cancer, but also reveal the complexity of a single tumor. In fact, as shown with biopsies of brain cancer, cancerous cells in a tumor can be strikingly different, even when they are close to each other. Finally, the method helped to pinpoint which types of immune cells are involved in fighting a kidney tumor. Overall, such information cannot be obtained with conventional methods, yet is crucial for diagnosis and treatment. Most laboratories can readily use t-CyCIF since the technique is open source and requires equipment that is easily accessible. In fact, the technique should soon be used to assess how well certain drugs help the immune system combat cancer. Ultimately, better use of biopsies is key to customizing cancer care.