这项工作是由Knut和Alice Wallenberg基金会赠款支持。整个人类蛋白质图集中心在乌普萨拉，斯德哥尔摩和印度的工作人员都承认他们的努力产生的人类蛋白质图集。作者希望拍戏时特别感谢的照片和忆念美Karlberg留言弗兰克·Hammar和SOFIE古斯塔夫森的援助援助与TMA的生产。

1。如何准备组织芯片生产组织（动画1） <ol><li>选择有关福尔马林固定石蜡包埋材料，包括相应的​​苏木染色组织切片（组织或细胞样本）。 </li><li>马克的组织切片上的相关领域。建议将新鲜切割的苏木染色部分相应的石蜡块。 </li><li> TMA的生产中使用的模板设计。随机样本，模板，以避免技术问题，如覆盖在整个TMA节和切片问题的抗体引起的工件内。添加额外的导向标志为导向的模板。 </li><li>组织的组织，根据模板。 </li></ol> 2。手动组织芯片制作（拍摄基本） <ol><li>为了能够获得标准化组织核心长度，标志着如管芯4.5毫米（ 图2）。 guidelINES为样本中心之间的间距： 核心规格0.6毫米 - 0.8-1.0毫米 核心大小1.0毫米 - 1.8-2.0毫米 核心规格1.5毫米 - 2.0-3.0毫米 核心规格2.0毫米 - 2.5-4.0毫米 建议离开2.5-3.0毫米利润率每一侧的石蜡块，石蜡，以避免开裂。 </li><li><ol class="lalpha"><li>装入选定要使用的拳。开始持有的地方冲六角螺丝松动。冲床正确定位时，在冲枢纽的凹槽坚决反对的金属棒放在塑料V型块。拧紧螺丝，确保边缘的金属夹子水平。 </li><li>收件人冲床（红色和绿色，分销商的具体标记）应放置到左边。捐助冲（绿色和蓝色，经销商具体标明），其中有一个稍大的直径应放置到正确的（ 图3）。 </li></ol></li><li><ol class="lalpha"><li>移动通过XY调节旋钮沿x和y轴的拳。正确调节旋钮沿x轴移动拳和左调节旋钮沿Y轴移动的拳。 两个调节旋钮上有一个数字千分尺读数。这些动旋钮时被激活。 </li><li> →按重置的ZERO / ABS键。 英寸和毫米之间的转变→按/毫米按钮。 孔之间的间距应为2.0毫米（测量孔中心之间），当使用一个9x8的模板1毫米​​打孔。 </li></ol></li><li><ol class="lalpha"><li>为了确保你不推入块一拳太远下来，击中录音带和破坏冲，放无石蜡的持有人的录像带，并设置收件人的冲床的底部位置1毫米以上的纸盒底部通过在深度停止螺丝左上角的Z-指南（ 图3）。 </li><li>在持有人把的收件人块和用最小的螺丝刀拧紧螺丝。不紧或拧紧螺丝，石蜡可能打破从纸盒宽松。 </li><li>收件人块推入收件人冲床下降约5毫米，并使用在冲手柄旋转冲头，来回一次（ 图3）。将块推入冲床时尽量下尽可能为5毫米深的洞。 </li><li>慢慢减轻向下推压，使弹簧可以移动一拳。使用管芯清空冲和丢弃的石蜡核心。 </li></ol></li><li>移动炮塔切换到捐助冲床（ 图3）。 </li><li>放置捐助块桥与超过收件人块持有人的捐助块（ 图3）。 </li><li><ol class="lalpha"><li>推动捐助puncH +进入捐助块选定区域。使用相应的苏木精和曙红染色幻灯片感兴趣的区域已标记为找到组织进行采样。手动举行捐助块，用左手的位置，并用右手推了一拳。请注意，你不应该管芯上推。深度停止不阻止拳打在适当的位置捐助块的议案，所以重要的是，你停止推动时的第二个标志是在管芯上可见。 </li><li>旋转手柄上冲一次（ 图3）。慢慢释放向下压力，同时仍保持对捐助块桥捐助块。 </li><li>捐助组织是最好砸出0.5毫米比收件人核心短。这一过程将确保在收件人的块面的内核可调对齐，避免宝贵的代表组织的损失。 </li></ol></li><li>拆除的桥梁和捐助块。使确保捐助冲床与早些时候作出的（4点）的孔对齐。你必须调整使用的固定螺钉，如果不对齐的捐助力度和在收件人块孔的打孔位置。 </li><li>小心推冲头向下，直到其尖端到达收件人块孔上方。持这种立场的同时，使用管芯流到洞的组织核心。核心表面应该是对齐的块面。 </li><li>移动炮塔后面的收件人冲。 </li><li>与XY调节旋钮，移动到下一个位置。 </li><li>从以上点4C重复，直到数组是完整的。 </li><li>当完成整个收件人块，松开在收件人块支架的螺钉。烤40分钟，42°C间的块。放在玻片上面临的切片面积的块。试管持有人（或其他适当的建设），并在T地点上放置块玻片他烤箱。烘烤后，从炉中取出试管支架和扁平块表面轻轻抚摸玻片。 </li><li>放置玻片上一个10分钟的冷却板块。 为了确保整个公会的代表组织，质量控制上每节50 日进行。 </li></ol> 3。如何节TMAs（动画） <ol><li>第传输系统（航模355S，MICROM）的使用切片机，切4微米厚的部分。该系统可用于所有当前的旋转切片机。该系统包括一个刀架与综合传输的桥梁，热水浴和一个控制单元。从刀片的部分通过转移到水浴桥湿转让表面上滑行。 </li><li>应采取的部分，从水浴后，他们立即伸出，避免敏感的组织点（如富含脂质，如乳腺癌和脑组织）的融化。解放军CE节上superfrost玻片。部分可以留在水中的时间取决于石蜡打蜡使用和水温。我们的实验室使用石蜡HistoLab产品AB，其中有一个熔点56-58℃，我们建议的水浴温度37-39°C。 </li><li>过夜干燥，在室温（RT），放置在一个幻灯片持有人的幻灯片。 </li><li>在50℃烘烤12-24小时的幻灯片。你有没有STS的运输如使用刷子部分手动从刀片水浴一个microtom。 </li></ol> 4。试验和免疫组织化学滴定法程序（动画3） 每个抗体是一个标准化的测试程序，使用专门设计TMAs包含组织和不同类型的细胞组合。其目的是评估个人和优化每一个抗体染色协议。最初稀释，基于蚂蚁ibody股票的主要抗体浓度进行测试。这个测试染色的成果用于指导进一步的稀释和协议的优化。 <ol><li> deparaffinization和二甲苯和梯度乙醇水化蒸馏水之前进行免疫。 </li><li>阻塞一步解渴内源性过氧化物酶的H 2 O 2 0.3％，95％乙醇5分钟。 </li><li>热诱导表面抗原检索（HIER）的执行中检索缓冲pH值6，使用压力锅炉（Decloaking室，医疗Biocare公司）作为热量来源为4分钟，在125°C。幻灯片完成后沸腾，保持中压锅炉，并让其冷却到90°C。为HIER总加工时间约45分钟。 </li><li>如果没有在最初的测试中取得决定性的结果是，做进一步的测试的基础上观测到的染色模式5 6。一项试验研究，在HPA高吞吐量的设置，显示其中HIER pH为6，但其他检索方法，如蛋白酶，微波炉和沸点较高或较低的pH值的缓冲预孵化，当然可以使用的最有用的抗原检索。通过改变免疫组化的条件，如改变抗体孵育时间，抗体稀释和二氨基联苯胺（DAB）的孵育时间，染色模式可以提供更确凿的结果​​。 </li></ol> 5。染色程序，Autostainer自动480（赛默飞世尔科技） 全部孵化完成后在室温下，此协议也可以用作手动设置在一个相同的试剂。 <ol><li>在洗涤缓冲液冲洗。 </li><li>超V型块的潜伏期为5分钟。 </li><li>在洗涤缓冲液冲洗。 </li><li>潜伏期30分钟的主要抗体。 </li><li>在洗涤缓冲液冲洗（X2）。 </li><li>孵育30分钟标记的辣根过氧化物酶聚合物。 </li><li>在洗涤缓冲液冲洗（X2）。 </li><li>在民建联发展的解决方案10分钟。 </li><li>在洗涤缓冲液冲洗（X2）。 </li><li>在迈耶斯苏木为5分钟* Counterstaining。当使用一个渐进的染色方法（例如：迈耶斯苏木）的力度取决于时间和没有分化是必需的。一种倒退的染色方法，如哈里斯苏木需要从组织中删除多余的染料，以突出结构的分化。 </li><li> *自来水冲洗。 </li><li>在碳酸锂水冲洗，经稀释的饱和溶液1分钟* 1:5。 </li><li>在自来水冲洗5分钟。 </li><li>幻灯片梯度乙醇脱水和幻灯片coverslipped（PERTEX，Histolab） </li></ol>适用于所有的试剂体积300μL每张幻灯片。 *步骤10-14在histostaining仪器（Autostainer自动XL，莱卡）和盖片是加在coverslipper系统（自动玻璃coverslipper的CV5030，徕卡）。 6。如何扫描幻灯片扫描幻灯片的方法是依赖于正在利用数字扫描仪，该协议只定义了如何使用自动扫描系统Aperio XT（Aperio技术）扫描幻灯片。在人类蛋白质图集设置20倍放大倍率的细胞组织和40X。自动扫描可能会遇到的焦点问题，由于异质性组织，包括在TMA不同组织的数量。 <ol><li>清洁的载玻片和污垢，胶水检查盖玻片节之间的气泡。在气泡重新安装幻灯片的情况。 </li><li>在机架上放幻灯片，并将其放置在数字扫描仪机架。在20倍放大倍率1 TMA扫描时间约6分钟。从Aperio的软件是用来选择感兴趣的领域。在软件自动对焦点选择。手动扫描区域和着力点的选择也是可能的。 </li><li>后的图像Ĥ已经产生，它可用于免疫组化染色的评价和注解。图像仍然是一个实验的结果文件，并可以向同事派发的讨论，并进一步公布的数据使用。这些图像可以被视为在Aperio一个免费软件。 </li></ol> 7。如何搜索您最喜爱的蛋白在人类蛋白质图集<ol><li>浏览到<a href="http://www.proteinatlas.org." target="_blank">www.proteinatlas.org。</a> </li><li>输入您最喜爱的蛋白质，Ensembl的ID，UniProt加入号码或HGNC名称，如胰岛素的名称。 </li><li>进入摘要页面，向下滚动到正常组织和器官的总结。概述显示在胰蛋白表达。 </li><li>点击“更多组织的数据”。你进入正常组织观看在这里你可以看到包括所有组织器官排序。 </li><li>对胰腺点击查看针对相同的蛋白质抗体的免疫组化结果。要查看一喜胰腺点击图片GH-高分辨率图像。 </li><li>有关蛋白表达在癌组织，细胞和人类蛋白质图集内的进一步验证数据的附加信息可以发现人类蛋白质图集网站浏览。 </li></ol> 8。代表结果 动画1。如何准备组织芯片的生产组织。 <a href="https://www.jove.com/files/ftp_upload/3620/3620_animation_1_Web.mov" target="_blank">点击这里查看动画1</a> 。 动画2。第TMAs。 <a href="https://www.jove.com/files/ftp_upload/3620/3620_animation_2_Web.mov" target="_blank">点击这里查看动画2</a> 。 动画3。免疫组化技术描述。 <a href="https://www.jove.com/files/ftp_upload/3620/3620_animation_3_Web.mov" target="_blank">点击这里查看动画3</a> 。<img alt="图1" src="/files/ftp_upload/3620/3620fig1.jpg" /> 图1。在人类蛋白质图集乌普萨拉进程的总体方案。 <img alt="图2" src="/files/ftp_upload/3620/3620fig2.jpg" /> 图2。捐助管芯标准化组织核心的长度标记，例如4.5毫米。 <img alt="图3" src="/files/ftp_upload/3620/3620fig3.jpg" /> 图3。手册组织微阵列。 <img alt="图4" src="/files/ftp_upload/3620/3620fig4.jpg" /> 图4。TMAs生产不同质量的例子。 （A）直和正确对齐TMA的行和列以及石蜡边缘之间有足够的空间。 （B）与一些核心公会过于接近切片时可能困难的边缘。 （C）财资市场公会已烤为TOO长在倒塌的公会不正确的模板。 <img alt="图5" src="/files/ftp_upload/3620/3620fig5.jpg" /> 图5。苏木精和曙红染色TMAs。 （A）直和对齐的列和行的部分适当削减。用坏的或脏的刀片可能会导致分裂（B）或压缩的部分（三）。 <img alt="图6" src="/files/ftp_upload/3620/3620fig6.jpg" /> 图6。抗体滴定。 （一）反应中心细胞在淋巴结显示最佳剂量的抗体，导致在一个特定的细胞质染色，无背景（棕色）。 （二）组织切片显示弱阳性。阴性或弱阳性，被发现时，初级抗体的浓度过低或如果目标蛋白是不存在的免疫染色组织。 （三）组织部分overstained由于使用初级抗体浓度过高。在D在确定由于溢出，交叉反应和假阳性的亚细胞定位的困难方舟的色彩效果。

<ol>
	<li>Battifora, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+multitumor+(sausage)+tissue+block:+novel+method+for+immunohistochemical+antibody+testing.">The multitumor (sausage) tissue block: novel method for immunohistochemical antibody testing.</a> Lab Invest. 55, 244-244 (1986).</li><li>Kononen, J., Bubendorf, L., Kallioniemi, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tissue+microarrays+for+high-throughput+molecular+profiling+of+tumor+specimens.">Tissue microarrays for high-throughput molecular profiling of tumor specimens.</a> Nat. Med. 4, 844-844 (1998).</li><li>Berglund, L., Bjorling, E., Oksvold, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+genecentric+Human+Protein+Atlas+for+expression+profiles+based+on+antibodies.">A genecentric Human Protein Atlas for expression profiles based on antibodies.</a> Mol. Cell Proteomics. 7, 2019 (2008).</li><li>Uhlen, M., Bjorling, E., Agaton, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+human+protein+atlas+for+normal+and+cancer+tissues+based+on+antibody+proteomics.">A human protein atlas for normal and cancer tissues based on antibody proteomics.</a> Mol. Cell Proteomics. 4, 1920 (2005).</li><li>Paavilainen, L., Edvinsson, A., Asplund, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+impact+of+tissue+fixatives+on+morphology+and+antibody-based+protein+profiling+in+tissues+and+cells.">The impact of tissue fixatives on morphology and antibody-based protein profiling in tissues and cells.</a> J. Histochem. Cytochem. 58, 237-237 (2010).</li><li>Paavilainen, L., Wernerus, H., Nilsson, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+monospecific+antibodies:+a+comparison+study+with+commercial+analogs+using+immunohistochemistry+on+tissue+microarrays.">Evaluation of monospecific antibodies: a comparison study with commercial analogs using immunohistochemistry on tissue microarrays.</a> Appl. Immunohistochem. Mol. Morphol. 16, 493-493 (2008).</li><li>Kampf, C., Andersson, A. C., Wester, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antibody-based+tissue+profiling+as+a+tool+for+clinical+proteomics.">Antibody-based tissue profiling as a tool for clinical proteomics.</a> Clinical Proteomics. 1, 285-285 (2004).</li><li>Ponten, F., Jirstrom, K., Uhlen, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Human+Protein+Atlas+-+a+tool+for+pathology.">The Human Protein Atlas - a tool for pathology.</a> J. Pathol. 216, 387-387 (2008).</li><li>Andersson, A. C., Stromberg, S., Backvall, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+protein+expression+in+cell+microarrays:+a+tool+for+antibody-based+proteomics.">Analysis of protein expression in cell microarrays: a tool for antibody-based proteomics.</a> J. Histochem. Cytochem. 54, 1413-14 (2006).</li><li>Stromberg, S., Bjorklund, M. G., Asplund, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+high-throughput+strategy+for+protein+profiling+in+cell+microarrays+using+automated+image+analysis.">A high-throughput strategy for protein profiling in cell microarrays using automated image analysis.</a> Proteomics. 7, 2142 (2007).</li><li>Jogi, A., Brennan, D. J., Ryden, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nuclear+expression+of+the+RNA-binding+protein+RBM3+is+associated+with+an+improved+clinical+outcome+in+breast+cancer.">Nuclear expression of the RNA-binding protein RBM3 is associated with an improved clinical outcome in breast cancer.</a> Mod. Pathol. 22, 1564 (2009).</li><li>Magnusson, K., De Wit, M., Brennan, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SATB2+in+combination+with+cytokeratin+20+identifies+over+95%+of+all+colorectal+carcinomas.">SATB2 in combination with cytokeratin 20 identifies over 95% of all colorectal carcinomas.</a> Am. J. Surg. Pathol. 35, 937 (2011).</li><li>Nocito, A., Kononen, J., Kallioniemi, O. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tissue+microarrays+(TMAs)+for+high-throughput+molecular+pathology+research.">Tissue microarrays (TMAs) for high-throughput molecular pathology research.</a> Int. J. Cancer. 94, 1 (2001).</li><li>Rimm, D. L., Camp, R. L., Charette, L. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tissue+microarray:+a+new+technology+for+amplification+of+tissue+resources.">Tissue microarray: a new technology for amplification of tissue resources.</a> Cancer J. 7, 24 (2001).</li><li>Catchpoole, D., Mackie, N., McIver, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tape+transfer+sectioning+of+tissue+microarrays+introduces+nonspecific+immunohistochemical+staining+artifacts.">Tape transfer sectioning of tissue microarrays introduces nonspecific immunohistochemical staining artifacts.</a> Biotech. Histochem. , (2010).</li><li>UniProt. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Nucleic acids research. 39, D214 (2011).</li><li>Uhlen, M., Oksvold, P., Fagerberg, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Towards+a+knowledge-based+Human+Protein+Atlas.">Towards a knowledge-based Human Protein Atlas.</a> Nature Biotechnol. 28, 1248 (2010).</li><li>Leong, A. S., Leong, T. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Standardization+in+immunohistology.">Standardization in immunohistology.</a> Method Mol. Cell Biol. 724, 37 (2011).</li></ol>

我们什么都没有透露。

免疫组化是迄今为止TMAs最常用的应用程序。 IHC和TMAs的组合，可以用来在几个不同的设置，如高通量筛选组织7 8蛋白的表达模式和细胞组织样本从大的病人同伙11 12及以上的基本肿瘤生物学基础9月10日 ，生物标志物的发现研究研究，包括不同的基因型/表型，分化阶段，进展和转移13。使用TMAs的一个好处是，大同伙的材料可以在同一时间进行分析，既节省了宝贵的生物材料，并确保更多的重复性实验。此外，TMA技术的使用，节省试剂成本和实验室处理时间。作为一个公会只包含数量有限的组织，组织的异质性是一个问题。根据组织类型和要解决的问题，可能需要几个样品相同specimeN。对于肿瘤组织，利用两到四个内核，每个试样建议，因为它已被证明，导致在整个组织切片13 14代表高度的准确性。根据组织组成的拳（范围从0.6毫米至2毫米）直径可以调整。组织是复杂的，既有多种不同的细胞类型，结构和细胞外基质组成。每个不同类型的可变数量的脂肪组织中含有的成分，血管，结缔组织，软骨等，会影响冲压和收集单独的内核所需的压力。因此，它是重要的前1 TMA的生产与组织定义为实验目的，练习过程中的所有步骤上，是没有任何价值的材料。 当一个公会块切片在各种不同的组织块的组成可能影响的能力，以获得高品质的部分。 CErtain组织，如皮肤，骨髓，脂肪，大脑和乳腺癌，渲染切片的TMA块困难，因为质地差异影响如何节伸展在水浴的作用，以及如何不同硬度被切断刀片等因此，建议类似的功能组组织成一个公会的脂质丰富的组织，例如，当适用。癌组织中的大多数在这个意义上是均匀的，这有利于癌症TMAs切片。处理异构类型的组织1 TMA时，可以采用替代切片稳定的芯片内核的方法。胶带的使用可以帮助，以避免在切片TMA的核心和下降的损失。胶带的使用，应采用谨慎，因为磁带可以影响切片内核的厚度和随后也IHC染色15的结果。在人类蛋白质图集设置了9x8公会的模板（不含标志）内核ARE中。它是获得最大数量的部分，并保持整个街区为代表的所有组织的重要性。为了节省试剂和扫描时间，2节被放置在一个玻璃允许9x8的最大模板的幻灯片。 主要为蛋白质信息库，通用的蛋白质资源的16包括约20.300审查人类蛋白质项，其中只有约66％，在蛋白质水平的证据。也为广大的基因，这些基因的蛋白质水平上存在的证据，有很少或没有表达的蛋白质的功能和分布的信息。对于未来的一个重要挑战是分析的分布格局和这些未知的蛋白质在人体组织的各类相对丰度。如Uniprot，ENSEMBL公布的数据显示，从医学数据库中的信息可用于为指导，以建立，如果使用抗体免疫组化染色模式病房未知的蛋白质代表实际的预定目标蛋白的蛋白质图谱。此外，其他几个验证战略的需要，以确保抗体的功能，例如蛋白质阵列的抗体，免疫印迹，免疫荧光，免疫沉淀和下拉实验功能。也许抗体的功能验证的最重要的工具是使用配对的抗体，即反对独立，互不重叠的表位的两种不同的抗体，对同一目标蛋白，比较具体分析的结果17。 的基础上编制的信息，抗体测试和滴定根据免疫组化的标准和35.000抗体在人类蛋白质图集项目的测试和验证的经验。对于超过20％的基因与蛋白质表达谱，配对抗体（2个或更多的对非重叠的表位相同的蛋白质的抗体）的数据已被用来确定最佳估计相应的蛋白表达模式的队友。配对抗体提供验证基于特定的免疫组化蛋白表达模式的最终战略。这一战略是有价值的，因为多种不同的组织包括在基本筛选增加了交叉反应的风险。还应当指出的是，某些组织一般更容易显示背景染色，如巨噬细胞，平滑肌，肾远端小管和肝细胞。额外要考虑的问题包括组织处理技术的变化，随着时间的推移，从档案材料中所采取的组织，这可能会导致假阴性或不适当的免疫组化染色阳性模式。这种现象也遇到了大断面分析。正面和负面的控制是至关重要的，应尽可能使用。为更深入的研究，包括功能分析，被迫表达的细胞株和相应的TR的具体敲anscripts（RNA干扰技术），可用于创建控件。免疫组化的最佳效果，它是重要的抗原检索系统进行测试和使用，因为福尔马林固定引起不同的化学修饰，如交联，水解希夫基地掩盖抗原18。 总之，采用TMA技术和IHC抗体为基础的蛋白质组学是一个强大的战略产生了大规模的蛋白表达数据。人体蛋白质的Atlas项目已成立，创造了人类在正常的人体组织和​​癌蛋白表达的地图。这个项目的目的是提出一个全面的人类蛋白质图集“的第一稿，到2015年。除了在正常组织和器官的蛋白质图谱，这项工作还提供了一个生物医学研究项目，包括临床生物标志物的发现工作的出发点。最终目标是在人类基因组序列的顶部添加下一个信息层，无线网络将是至关重要的一个潜在的各种疾病状态的生物学更深入的了解，并为开发新的诊断和治疗手段提供依据。

<table border="1"><tbody><tr><td> 试剂名称 </td><td> 公司 </td><td> 目录编号 </td></tr><tr><td>洗缓冲区</td><td>赛默飞世尔科技</td><td> TA-999 - TT </td></tr><tr><td>柠檬酸缓冲PH6 </td><td>赛默飞世尔科技</td><td> TA-250-Pm1X </td></tr><tr><td>抗体稀释液</td><td>赛默飞世尔科技</td><td> TA-125-UD的</td></tr><tr><td> UltraVision唱片HRP的聚合物</td><td>赛默飞世尔科技</td><td> TL-125-红莲</td></tr><tr><td>民建联加上基板系统</td><td>赛默飞世尔科技</td><td> TA-125-的HDX </td></tr><tr><td>超V型块</td><td>赛默飞世尔科技</td><td> TA-125-瑞银</td></tr><tr><td>初级抗体增强</td><td>赛默飞世尔科技</td><td>的TL-125-PB </td></tr><tr><td>迈耶斯苏木</td><td> histolAB </td><td> 01820 </td></tr><tr><td> PERTEX </td><td> histolab </td><td> 00871.0500 </td></tr><tr><td colspan="3"></td></tr><tr><td> 设备名称 </td><td> 公司 </td><td> 目录编号 </td></tr><tr><td>手册组织微arrayer </td><td> estigen，彻仪器</td><td> MTA的1 </td></tr><tr><td>瀑布切片</td><td>赛默飞世尔科技</td><td> MICROM航模355S </td></tr><tr><td>自动图像扫描仪</td><td> aperio技术</td><td> XT的</td></tr><tr><td>幻灯片自动染色系统</td><td>赛默飞世尔科技</td><td> Autostainer自动480S-2D </td></tr><tr><td>自动幻灯片为deparafinization和脱水染色系统</td><td>徕卡生物系统公司</td><td> Autostainer自动加大</td></tr><tr><td>自动玻璃coverslipper的</td><td>徕卡的BIOSystems </td><td> CV5030 </td></tr><tr><td> decloaking室</td><td>保科医疗</td><td> DC2008INTEL </td></tr></tbody></table>

production of tissue microarrays, immunohistochemistry staining and digitalization within the human protein atlas

组织芯片（TMA）技术提供了多个组织和细胞的高通量分析手段。这项技术被用于人类蛋白质图集项目内，在正常的人体组织，癌症和细胞系的蛋白质表达模式的全球分析。在这里，我们提出了1毫米的核心组件，检索，从微观选择的代表组织成一个单一的收件者公会块。在TMA块核心的数量和大小可以改变数百个0.6毫米的核心大约四十2毫米的核心。使用TMA技术的优点是，可以迅速获得大量的数据，使用单一染色协议，以避免实验变异。重要的是，数量有限，只有稀缺的组织是必要的，允许对大量病人的分析同伙1 2。约250名（4微米厚）的连续部分可以从TMA块切割，用于免疫组化staini吴以确定特定的蛋白质表达模式为250种不同的抗体。在人类蛋白质图集项目，对所有人类蛋白质产生抗体，和来自216个不同的病人，代表人类癌症的20个最常见的形式，获得相应的蛋白质图谱，从144个人和癌组织，在正常的人体组织。 TMA的免疫组化染色玻片上部分扫描创建高分辨率的图像，从病理学家可以解释和注释免疫组化的结果。图像与相应的病理基础的注释数据为研究社会公开可通过人类蛋白质图集门户网站（ <a href="http://www.proteinatlas.org" target="_blank">www.proteinatlas.org</a> ）（ 图1）3 4。人体蛋白质图谱，提供了地图显示的蛋白质在人体中的分布和相对丰度。当前版本的锡安包含超过11万与12.238独特的蛋白，相应的超过61％的人类基因组编码的所有蛋白质的蛋白表达数据的图像。

Watch this Scientific Journal Video about Production of Tissue Microarrays, Immunohistochemistry Staining and Digitalization Within the Human Protein Atlas at JoVE.com

Production of Tissue Microarrays, Immunohistochemistry Staining and Digitalization Within the Human Protein Atlas

组织芯片允许一个有效的方法，从众多的组织中获得的并发信息。组织的代表零件组装成一个单一的石蜡块。从块中的部分用于免疫组化和蛋白表达模式的分析。数字扫描生成相应的图像数据分布。

组织芯片，​​免疫组织化学染色和数字化生产在人类蛋白质图集

The  tissue microarray (TMA) technology provides the means for high-throughput  analysis of multiple tissues and cells. The technique is used within the ...

production-tissue-microarrays-immunohistochemistry-staining

Research

JoVE Journal

Biology

56.0K 次观看.  Uppsala University. 组织芯片允许一个有效的方法，从众多的组织中获得的并发信息。组织的代表零件组装成一个单一的石蜡块。从块中的部分用于免疫组化和蛋白表达模式的分析。数字扫描生成相应的图像数据分布。

视频: Production of Tissue Microarrays, Immunohistochemistry Staining and Digitalization Within the Human Protein Atlas

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. 
Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ.
We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7.
To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.

Here we describe a method to quantify molecular heterogeneity in histological sections of tumor material using quantitative immunofluorescence, image analysis, and a statistical measure of heterogeneity. The method is intended for use in clinical biomarker development and analysis.

在使用定量免疫肿瘤的异质性蛋白表达的映射

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of ...

科研

医学

Digital Analysis of Immunostaining of ZW10 Interacting Protein in Human Lung Tissues

The purpose of this study is to introduce a methodology of the immunostaining of human lung tissues, followed by whole-slide digital scanning and image analysis. Digital scanning is a fast way to scan a stack of slides and produce digital images with high quality. It can produce concordant results with conventional light microscopy (CLM) by pathologists. Furthermore, the availability of digital images makes it possible that the same slide can be concurrently observed by multiple people. Moreover, digital images of slides can be stored in a database, which means the long-term deterioration of glass slides is avoided. The limitations of this technique are as follows. First, it needs high-quality prepared tissue and the original immunohistochemistry (IHC) slides without any damage or excess sealant residue. Second, tumor or nontumor areas should be specified by experienced pathologists before the analysis using software, in order to avoid any confusion about the tumor or nontumor areas during scoring. Third, the operator needs to control the color reproduction throughout the digitization process in whole-slide imaging.

ZW10 interacting protein (ZWINT) participates in the mitotic spindle checkpoint and the pathogenesis of carcinoma. Here, we introduce a methodology of the immunostaining of ZWINT in human lung cancer tissues, followed by the digital scanning of whole slides and image analysis. This methodology can provide high-quality digital images and reliable results.

人肺组织中ZW10相互作用蛋白免疫染色的数字化分析

The purpose of this study is to introduce a methodology of the immunostaining of human lung tissues, followed by whole-slide digital scanning and image ...

癌症研究

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Multiplexing enables the assessment of several markers on the same tissue while providing spatial context. Spatial Omics technologies allow both protein and RNA multiplexing by leveraging photo-cleavable oligo-tagged antibodies and probes, respectively. Oligos are cleaved and quantified from specific regions across the tissue to elucidate the underlying biology. Here, the study demonstrates that automated custom antibody visualization protocols can be utilized to guide ROI selection in conjunction with spatial proteomics assays. This specific method did not show acceptable performance with spatial transcriptomics assays. The protocol describes the development of a 3-plex immunofluorescent (IF) assay for marker visualization on an automated platform, using tyramide signal amplification (TSA) to amplify the fluorescent signal from a given protein target and increase the antibody pool to choose from. The visualization protocol was automated using a thoroughly validated 3-plex assay to ensure quality and reproducibility. In addition, the exchange of DAPI for SYTO dyes was evaluated to allow imaging of TSA-based IF assays on the spatial profiling platform. Additionally, we tested the ability of selecting small ROIs using the spatial transcriptomics assay to allow the investigation of highly-specific areas of interest (e.g., areas enriched for a given cell type). ROIs of 50 &#181;m and 300 &#181;m diameter were collected, which corresponds to approximately 15 cells and 100 cells, respectively. Samples were made into libraries and sequenced to investigate the capability to detect signals from small ROIs and profile-specific regions of the tissue. We determined that spatial proteomics technologies highly benefit from automated, standardized protocols to guide ROI selection. While this automated visualization protocol was not compatible with spatial transcriptomics assays, we were able to test and confirm that specific cell populations can successfully be detected even in small ROIs with the standard manual visualization protocol.

Here, we describe a protocol for fine-tuning regions of interest (ROIs) for Spatial Omics technologies to better characterize the tumor microenvironment and identify specific cell populations. For proteomics assays, automated customized protocols can guide ROI selection, while transcriptomics assays can be fine-tuned utilizing ROIs as small as 50 &#181;m.

组织中蛋白质和RNA表达的空间分析:一种微调虚拟显微切割的方法

Multiplexing enables the assessment of several markers on the same tissue while providing spatial context. Spatial Omics technologies allow both protein ...

Manual Construction of a Tissue Microarray using the Tape Method and a Handheld Microarrayer

The tissue microarray (TMA) is an important research tool in which many formalin fixed paraffin embedded (FFPE) samples can be represented in a single paraffin block. This is achieved by using tissue cores extracted from the region of interest of different donor FFPE blocks and arranging them into a single TMA paraffin block. Once constructed, sections from the completed TMA can be used to perform immunohistochemistry, chromogenic, fluorescence in situ hybridization (FISH) and RNA ISH studies to assess protein expression as well as genomic and transcriptional alterations in many samples simultaneously, thus minimizing tissue usage and reducing reagent costs. There are several different TMA construction techniques. One of the most common construction methods is the recipient method, which works best with cores of the same length for which a minimum length of 4 mm is recommended. Unfortunately, tissue blocks can be heavily resected during the diagnostic process, frequently resulting in "non-ideal" donor block thicknesses of less than 4 mm. The current article and video focus on the double-sided adhesive tape method; an alternative manual, low cost, easy to use, and rapid method to construct low density (&lt;50 cores) TMAs that is highly compatible with these non-ideal donor blocks. This protocol provides a step-by-step guide on how to construct a TMA using this method, with a focus on the critical importance of pathological review and post construction validation.

This protocol outlines the tape method on how to manually construct a tissue microarray using FFPE donor blocks of differing depths.

使用胶带法和手持式微阵列仪手动构建组织微阵列

The tissue microarray (TMA) is an important research tool in which many formalin fixed paraffin embedded (FFPE) samples can be represented in a single ...

Expanding the Comprehension of the Tumor Microenvironment using Mass Spectrometry Imaging of Formalin-Fixed and Paraffin-Embedded Tissue Samples

Advances in immune-based therapies have revolutionized cancer treatment and research. This has triggered growing demand for the characterization of the tumor immune landscape. Although standard immunohistochemistry is suitable for studying tissue architecture, it is limited to the analysis of a small number of markers. Conversely, techniques such as flow cytometry can evaluate multiple markers simultaneously, although information about tissue morphology is lost. In recent years, multiplexed strategies that integrate phenotypic and spatial analysis have emerged as comprehensive approaches to the characterization of the tumor immune landscape. Herein, we discuss an innovative technology combining metal-labeled antibodies and secondary ion mass spectrometry focusing on the technical steps in assay development and optimization, tissue preparation, and image acquisition and processing. Before staining, a metal-labeled antibody panel must be developed and optimized. This hi-plex image system supports up to 40 metal-tagged antibodies in a single tissue section. Of note, the risk of signal interference increases with the number of markers included in the panel. After panel design, particular attention should be given to the metal isotope assignment to the antibody to minimize this interference. Preliminary panel testing is performed using a small subset of antibodies and subsequent testing of the entire panel in control tissues. Formalin-fixed, paraffin-embedded tissue sections are obtained and mounted on gold-coated slides and further stained. The staining takes 2 days and closely resembles standard immunohistochemical staining. Once samples are stained, they are placed in the image acquisition instrument. Fields of view are selected, and images are acquired, uploaded, and stored. The final stage is image preparation for the filtering and removal of interference using the system&#39;s image processing software. A disadvantage of this platform is the lack of analytical software. However, the images generated are supported by different computational pathology software.

In the era of cancer immunotherapy, interest in elucidating tumor microenvironment dynamics has increased strikingly. This protocol details a mass spectrometry imaging technique with respect to its staining and imaging steps, which allow for highly multiplexed spatial analysis.

使用福尔马林固定和石蜡包埋组织样品的质谱成像扩展肿瘤微环境的理解

Advances in immune-based therapies have revolutionized cancer treatment and research. This has triggered growing demand for the characterization of the ...

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell populations. To characterize proteome-level variation and tumor heterogeneity at scale, high-throughput methods are needed to selectively isolate discrete cellular populations in solid tumor malignancies. This protocol describes a high-throughput workflow, enabled by artificial intelligence (AI), that segments images of hematoxylin and eosin (H&#38;E)-stained, thin tissue sections into pathology-confirmed regions of interest for selective harvest of histology-resolved cell populations using laser microdissection (LMD). This strategy includes a novel algorithm enabling the transfer of regions denoting cell populations of interest, annotated using digital image software, directly to laser microscopes, thus enabling more facile collections. Successful implementation of this workflow was performed, demonstrating the utility of this harmonized method to selectively harvest tumor cell populations from the TME for quantitative, multiplexed proteomic analysis by high-resolution mass spectrometry. This strategy fully integrates with routine histopathology review, leveraging digital image analysis to support enrichment of cellular populations of interest and is fully generalizable, enabling harmonized harvests of cell populations from the TME for multiomic analyses.

This protocol describes a high-throughput workflow for artificial intelligence-driven segmentation of pathology-confirmed regions of interest from stained, thin tissue section images for enrichment of histology-resolved cell populations using laser microdissection. This strategy includes a novel algorithm enabling the transfer of demarcations denoting cell populations of interest directly to laser microscopes.

工业化、人工智能引导的激光显微切割，用于肿瘤微环境的微尺度蛋白质组学分析

The tumor microenvironment (TME) represents a complex ecosystem comprised of dozens of distinct cell types, including tumor, stroma, and immune cell ...

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is an effective methodology for tumor evaluation that improves the understanding of the tumor microenvironment. The visualization of protein expression in formalin-fixed, paraffin-embedded&#160;tissues is achieved when a specific fluorophore is annealed to an antibody-bound barcode via complementary oligonucleotides and then sample imaging is performed; indeed, this method allows for the use of customizable panels of more than 40 antibodies in a single tissue staining reaction. This method is compatible with fresh frozen tissue, formalin-fixed, paraffin-embedded tissue, cultured cells, and peripheral blood mononuclear cells, meaning that researchers can use this technology to view a variety of sample types at single-cell resolution. This method starts with a manual staining and fixing protocol, and all the antibody barcodes are applied using an antibody cocktail. The staining fluidics instrument is fully automated and performs iterative cycles of labeling, imaging, and removing spectrally distinct fluorophores until all the biomarkers have been imaged using a standard fluorescence microscope. The images are then collected and compiled across all the imaging cycles to achieve single-cell resolution for all the markers. The single-step staining and gentle fluorophore removal not only allow for highly multiplexed biomarker analysis but also preserve the sample for additional downstream analysis if desired (e.g., hematoxylin and eosin staining). Furthermore, the image analysis software enables image processing-drift compensation, background subtraction, cell segmentation, and clustering-as well as the visualization and analysis of the images and cell phenotypes for the generation of spatial network maps. In summary, this technology employs a computerized microfluidics system and fluorescence microscope to iteratively hybridize, image, and strip fluorescently labeled DNA probes that are complementary to tissue-bound, oligonucleotide-conjugated antibodies.

Multiplexed barcoding image analysis has recently improved the characterization of the tumor microenvironment, permitting comprehensive studies of cell composition, functional state, and cell-cell interactions. Herein, we describe a staining and imaging protocol using the barcoding of oligonucleotide-conjugated antibodies and cycle imaging, which allows for the use of a high-dimensional image&#160;analysis technique.

多重条形码图像分析，用于石蜡组织样品单细胞分析中的免疫分析和空间映射表征

Multiplexed imaging technology using antibody barcoding with oligonucleotides, which sequentially detects multiple epitopes in the same tissue section, is ...

肿瘤微环境的多重免疫荧光和空间图像分析

Multiplex Immunofluorescence Combined with Spatial Image Analysis for the Clinical and Biological Assessment of the Tumor Microenvironment

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending on its composition and the interactions between cancer cells and peri-tumoral cells, the TME may affect cancer progression. The characterization of tumors and their complex microenvironment could improve the understanding of cancer diseases and may help scientists and clinicians to discover new biomarkers.
We recently developed several multiplex immunofluorescence (mIF) panels based on tyramide signal amplification (TSA) for the characterization of the TME in colorectal cancer, head and neck squamous cell carcinoma, melanoma, and lung cancer. Once the staining and scanning of the corresponding panels are completed, the samples are analyzed on an image analysis software. The spatial position and the staining of each cell are then exported from this quantification software into R. We developed R scripts that allow us not only to analyze the density of each cell type in several tumor compartments (e.g. the center of the tumor, the margin of the tumor, and the stroma) but also to perform distance-based analyses between different cell types.
This particular workflow adds a spatial dimension to the classical density analysis already routinely performed for several markers. mIF analysis could allow scientists to have a better understanding of the complex interaction between cancer cells and the TME and to discover new predictive biomarkers of response to treatments, such as immune checkpoint inhibitors, and targeted therapies.

作者聚焦：多重免疫荧光结合空间图像分析用于肿瘤微环境的临床和生物学评估  

In this article, a protocol for manual tyramide signal amplification (TSA) multiplex immunofluorescence (mIF) combined with image analysis and spatial analysis is described. This protocol can be used with formalin-fixed paraffin-embedded (FFPE) sections for the staining of two to six antigens per slide depending on the slide scanner available in the laboratory.

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

The tumor microenvironment (TME) is composed of a plethora of different cell types, such as cytotoxic immune cells and immunomodulatory cells. Depending ...

组织芯片，免疫组织化学染色和数字化生产在人类蛋白质图集

摘要

探索更多视频

此视频中的章节

在使用定量免疫肿瘤的异质性蛋白表达的映射

人肺组织中ZW10相互作用蛋白免疫染色的数字化分析

组织中蛋白质和RNA表达的空间分析:一种微调虚拟显微切割的方法

使用胶带法和手持式微阵列仪手动构建组织微阵列

使用福尔马林固定和石蜡包埋组织样品的质谱成像扩展肿瘤微环境的理解

工业化、人工智能引导的激光显微切割，用于肿瘤微环境的微尺度蛋白质组学分析

多重条形码图像分析，用于石蜡组织样品单细胞分析中的免疫分析和空间映射表征

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

组织芯片，​​免疫组织化学染色和数字化生产在人类蛋白质图集

摘要

探索更多视频

此视频中的章节

在使用定量免疫肿瘤的异质性蛋白表达的映射

人肺组织中ZW10相互作用蛋白免疫染色的数字化分析

组织中蛋白质和RNA表达的空间分析:一种微调虚拟显微切割的方法

使用胶带法和手持式微阵列仪手动构建组织微阵列

使用福尔马林固定和石蜡包埋组织样品的质谱成像扩展肿瘤微环境的理解

工业化、人工智能引导的激光显微切割，用于肿瘤微环境的微尺度蛋白质组学分析

多重条形码图像分析，用于石蜡组织样品单细胞分析中的免疫分析和空间映射表征

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

多重免疫荧光结合空间图像分析，用于肿瘤微环境的临床和生物学评估

组织芯片，免疫组织化学染色和数字化生产在人类蛋白质图集