我们感谢的皇家阿尔弗雷德王子"和"儿童权利公约"和正常的肠道黏膜的新鲜样品收集的协和遣返医院解剖病理学实验室的工作人员。这项工作是由癌症研究所的新南威尔士转化项目资助资助。

<img src="/files/ftp_upload/3322/3322fig1.jpg" alt="图1" /> 图1。暂停从手术的CRC样本活体细胞的准备工作流程。 1。临床样本分类所有样品均采自皇家阿尔弗雷德王子医院（坎珀，NSW，澳大利亚）和协和遣返医院（协和西澳大利亚新南威尔士州）X08 - 164号议定书下的知情同意。 <ol><li>收集的新鲜大肠癌（CRC）的或腺瘤标本，和正常的肠道黏膜至少10厘米的肿瘤。汉克的平衡盐溶液的pH值7.3（HBSS）在4 ° C储存长达12 h切除后的样品。 </li><li>按照人类病原体的安全法规，在II级生物安全柜过程中所有的临床样本。剖析到2毫米的多维数据集使用两个手术刀片在培养皿菜的样品。 </li><li>孵育肿瘤和正常组织，在单独的Eppendorf管，偶尔温柔的搅拌60分钟，在37 ° C与同等体积的RPMI 1640培养基含2％（V / V）型胶原酶4（沃辛顿，翠湖，美国新泽西州）和0.1 ％（W / V）从牛胰腺中的脱氧核糖核酸我（DNA酶I，Sigma - Aldrich公司）。 </li><li>部队半消化组织通过精细的丝网，用10毫升注射器的柱塞滤网，通过与HBSS洗涤细胞。 </li><li>传递导致细胞悬液通过200微米和50微米Filcon的过滤器（BD Biosciences公司），以去除细胞聚集。大多数被删除的DNA，粘液和细胞聚集在这个系列的过滤。 </li><li>离心细胞悬浮液在20 ° 5分钟的400 XG。 </li><li>热灭活的FCS悬浮细胞沉淀，用含10％二甲基亚砜（DMSO），慢慢地冻结在离心管和储存在-80 °。冻结过程中往往会降低样本中的粘液和裂解红细胞。 </li></ol> 2。细胞采集的样品制备<ol><li>解冻样品很快在37度水浴和10毫升的HBSS洗出二甲基亚砜悬浮细胞。 </li><li>离心细胞悬浮液在20 ° 5分钟的410 XG。 </li><li>弃上清，重悬细胞沉淀在500μL的HBSS中。 </li><li> 0.1％（W / V）DNA酶在室温下20分钟我的样本对待。 </li><li>台盼蓝等体积混合每个细胞悬液10μL，10μL的混合物装入一个血球。使用光学显微镜100倍的放大倍数，计数活细胞，出现明确的台盼蓝拒，死细胞染料。最低4 × 10 6活菌细胞上的芯片捕获。 </li><li> DNA酶处理后，重新悬浮在10毫升的HBSS和离心机的细胞悬液，在20 ° 5分钟在410 XG。 </li><li>倒出到终体积为200μL的RPMI 1640培养上清和悬浮细胞沉淀。 </li></ol> 3。抗体芯片的细胞捕捉<ol><li>浸湿浸入磷酸盐硝化棉节DotScan抗体芯片缓冲液（PBS约20秒）仔细擦拭折叠Kimwipes芯片的玻璃边缘，避免用手触摸硝酸纤维素部分。 </li><li>加水至芯片孵化托盘提供湿热试验箱。进入会议厅的芯片和潮湿的硝化棉部分滴入的RPMI 1640细胞悬液。移液器滴硝化棉的每个角落，以确保即使细胞扩散。 </li><li>在37 ° C孵育1小时的芯片孵化允许细胞定居和接触芯片上的抗体。细胞中表达表面抗原相应的抗体，他们的土地上，将被捕获。 </li><li>孵化后，轻轻沾的芯片和垂直方向上分为三个载有至少15毫升PBS洗掉未结合的细胞（每洗20秒）的波谷。 </li><li>准备3.7％（W / V）甲醛的PBS，修复细胞和抗体的交联。轻轻吸管约1毫升，包括硝化棉的芯片部分。孵育20分钟在室温。 </li><li>下一步DIP芯片的PBS（15毫升; 30秒）的变化分为3个洗出多余的甲醛。 </li><li>擦拭边缘和背面与Kimwipes载玻片和使用的DotScan扫描仪，同时扫描芯片，硝酸纤维素部分是湿润的。光学扫描提供例如CRC混合细胞群的细胞，白细胞和其他间质细胞的肿瘤抗原的表达模式。 </li></ol> 4。荧光复<ol><li>从扫描仪中取出芯片适用于200μL封闭液（2％W / V BSA，2％热灭活的人AB血清，PBS，pH值7.3）。在室温孵育20分钟的芯片托盘。 </li><li>准备的multip词法用铝箔覆盖的Eppendorf管中的解决方案:20μL藻红蛋白 - 抗CD3（Beckman Coulter公司，Gladesville，NSW，澳大利亚，＃IM12824; 1/7.5最终稀释），10μL的Alexa Fluor 647的抗EpCAM的（Biolegend美国加利福尼亚州圣迭戈的1 / 15稀释），2μL热灭活的人AB血清（Sigma - Aldrich公司，城堡山，新南威尔士州，澳大利亚）和118μL封闭液。 </li><li>从微阵列流掉多余的封闭液，滴入硝酸纤维素部分复用的解决方案，散布均匀。为在黑暗中30分钟，在室温下孵育。 </li><li> DIP芯片;纵向分为三个波谷15毫升新鲜PBS（每30秒）。 </li><li>让干的芯片，在黑暗中和存储在4 ° C在幻灯片框。该芯片可存储长达3个月没有损失的荧光，在黑暗中。 </li><li>扫描使用分辨率设置为50台风FLA 9000扫描仪（GE医疗，Rydalmere，NSW，澳大利亚）（532 nm激光，580 BP30 PE排放过滤器干燥的芯片。633 nm激光Alexa的647和670 BP30排放过滤器）。微阵列扫描硝化棉方面临在玻璃板上扫描仪托盘向下。 </li><li>保存为TIFF文件的荧光图像，使用Photoshop设置图像的大小为17 x 25厘米，分辨率72像素/厘米。 DotScan分析软件导入图像分析的点的强度。 </li><li> DotReader捕捉一个点结合模式的数字图像和量化每个抗体点的密度，一个8位的灰度范围（1-256 ü）的细胞结合。偶尔非特异性亚型控制绑定是绑定值中减去相应的免疫球蛋白亚型的抗体。对100％的强度设置最亮的点，每个点的荧光强度芯片正常化。在一个XML文件（原始数据）记录信号强度/现货或条形图中的一个代表。PDF文件（最终报告） </li><li>芯片heatsmaps和分层聚类进行使用TM4芯片软件套装（MultiExperiment的浏览器（兆电子伏） <a href="http://www.tm4.org/mev.html">版本</a> 4.4 http://www.tm4.org/mev.html ）。分层聚类进行调整的背景，使用完整的连锁分析MeV的数据。欧氏距离的相似性度量。 2尾的学生等方差t -检验来确定结果的统计学意义。 </li></ol> 5。代表性的成果: 从DotScan芯片的结果应该显示一致的细胞之间的重复阵列的结合模式。有力契合点绑定（CD44/CD29）使一个被放置在数组区域电网。图2给出了优化细胞的捕获和复用的一个例子。图3显示了细胞的捕获和可能的解决方案过程中遇到的一些常见问题。 芯片细胞结合的结果是可以量化的测量点上的灰度规模从1到256不等表达强度。图4显示了数值数据，从58手术的CRC样本，EpCAM的Alexa的647抗体染色，作为一个层次聚类的热图。即使样品的数量是有限的的，同一阶段的CRC往往在同一组群。 <img src="/files/ftp_upload/3322/3322fig2.jpg" alt="图2" /> 图2（澳大利亚临床病理分期，机场核心计划的阶段B1）大肠癌的临床肿瘤细胞结合模式。 （一）DotScan抗体键重复的微阵列（概述）的左半边显示抗体地点。顶部包含DotScan白血病芯片原有的82抗体。额外的40抗体，对应于特定的表面抗原发现在文献中被上调，作为一个CRC"卫星"芯片的补充。下面的部分，由同型对照抗体（二）"儿童权利公约"细胞​​结合微阵列的光学图像。 （C）CD3 + T细胞荧光图像显示。 （四）EpCAM的荧光图像显示的CRC细胞。 <img src="/files/ftp_upload/3322/3322fig3.jpg" alt="图3" /> 图3。贫困DotScan结果和可能的解决方案的例子。 （一）低细胞结合的解决方案:确保至少4x106可行的细胞阵列上（二）同型控制约束性和非特定的细胞结合;解决方案:孵化前对芯片的热灭活人AB血清样品，以尽量减少同型对照具有约束力。有时，硝化纤维细胞的非特异性约束力的少量发生与CRC的样品，并没有显著影响的结果。 （三）干燥硝化棉孵化过程中，解决方案:确保样本覆盖了整个的硝化棉部分和芯片是在一个平面上培养。 （四）高背景工件;解决方案:确保芯片是彻底清洗下孵化。 <img src="/files/ftp_upload/3322/3322fig4.jpg" alt="图4" /> 图4。DotScan分析软件生成的柱状图代表细胞结合上灰度规模的密度范围从1到256。轴的数字是指CD抗原。其它缩写的TCR，T细胞受体;κ，λ，免疫球蛋白轻链; SIG，表面免疫球蛋白; DCC，在大肠癌蛋白删除;表皮生长因子受体，表皮生长因子受体; FAP的，成纤维细胞激活蛋白的HLA - A，B， HLA - DR的彗星，人类白细胞抗原DR和A，B，C分别;云母，MHC I类链相关蛋白; MMP - 14，矩阵metallopeptidase 14; PIGR，聚免疫球蛋白受体; TSP - 1，凝血酶- 1;美罗华，源化抗CD20。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/3322/3322fig4large.jpg">点击这里查看大图</a> 。

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没有利益冲突的声明。

在这段视频中，我们将演示如何DotScan抗体芯片可以在一个简单的，半定量的方法来研究从启联资源中心组织的细胞群表面抗原型材的使用。 从组织中获得一个可行的单细胞悬液，实验的成功是至关重要的，因为似乎是公司具有约束力的全细胞抗体点的孵化过程中所需的能源依赖的过程（如抗原上限和/或伪足形成），而随后冲关死细胞。 1型胶原酶最初受雇于组织disaggregation8，但被替换胶原酶4，这将导致较少破坏细胞膜，因为它包含较少的蛋白酶污染物。这种变化并没有影响小区产量，可行性或有约束力的模式。从某些肿瘤和控制样本的粘液减少细胞产量和干扰细胞捕获。储存在10％的DMSO / FCS的分类细胞悬液，在-80 ° C，大概是由于粘液性质的变化冻结和解冻9后，这种粘液的粘性减少到最低限度。随后，所有样品均在10％DMSO / FCS的冷冻后分类存储和快速解冻可行的细胞悬浮液，产生一致的结合模式。 &lt;50％的可行性，或显示对齐/看家点（CD44/CD29）的贫困约束力的样品是从分析省略。 几个抗体克隆显示时绑定的硝化棉可能是由于改变构象，如减少亲和力，突出CRC标记CD15s很少或没有的细胞结合。应更换不同的杂交瘤细胞克隆抗体表现出始终如一的负面结果。活动度差一些抗体的另一个可能的原因是牛血清白蛋白（BSA）结合的干扰。 BSA的抗体，应在可能的情况下，使用的芯片。 虽然大的病人同伙所需的微阵列数据进行统计分析，我们的研究结果的层次聚类（58个临床样本）一直鼓励。杨10所描述的方法使用的数据的正常化应该提供更好的统计意义。 DotScan抗体芯片使已知CD抗原表达的新模式的决心，这是最有效的发现蛋白质组学的技术，如二维凝胶电泳的LC - iTRAQ的MS，结合使用时，要确定新的差异丰富的蛋白质。这种新型蛋白质都是潜在的标记;相应的抗​​体，可以添加到数组中，并与临床CRC样本验证。 使用荧光标记的抗体来分析捕获的细胞子集提供了一种分析细胞混合种群的强大DotScan平台。

The author's email has been corrected in the publication of <a href="https://www-jove-com.remotexs.ntu.edu.sg/video/3322">Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing</a>. There was an error with the author, Jerry Zhou's, email. The author's email has been updated to:
j.zhou@uws.edu.au
from:
jzho7551@mail.usyd.edu.au

Erratum: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

<table border="1"><tbody><tr><th>试剂或设备名称</th><th>公司</th><th>目录编号</th><th>评论</th></tr><tr><td>汉克斯"平衡盐溶液</td><td> Sigma - Aldrich公司</td><td> H6136 - 10X1L </td><td>缓冲25毫米HEPES（Sigma公司＃H3375） </td></tr><tr><td> Airpure生物安全柜II类</td><td>西屋电气公司</td><td> 1687-2340/612 </td><td></td></tr><tr><td>手术刀</td><td>利文斯通</td><td> 090609 </td><td>每包100 </td></tr><tr><td> 2毫米HEPES的RPMI 1640 </td><td> Sigma - Aldrich公司</td><td> R4130 - 10X1L </td><td></td></tr><tr><td>型胶原酶4 </td><td>沃辛顿</td><td> 4188 </td><td></td></tr><tr><td>脱氧核糖核酸1 </td><td> Sigma - Aldrich公司</td><td> DN25 - 1G </td><td></td></tr><tr><td> Terumo公司注射器（10毫升） </td><td> Terumo公司</td><td> SS 10大号</td><td>盒:100个</td></tr><tr><td> Filcon过滤器（200微米） </td><td> BD公司</td><td> 340615 </td><td></td></tr><tr><td> Filcon过滤器（50微米） </td><td> Filcon过滤器（50微米） </td><td> Filcon Filcon过滤器（50微米）过滤器（50微米）340603 </td><td></td></tr><tr><td>胎牛血清</td><td> GIBCO / Invitrogen公司</td><td> 10099-141 </td><td></td></tr><tr><td>离心5810 ř </td><td> Eppendorf公司</td><td> 7017 </td><td></td></tr><tr><td>二甲基亚砜</td><td> Sigma - Aldrich公司</td><td> D2650 </td><td></td></tr><tr><td>台盼蓝</td><td> Sigma - Aldrich公司</td><td> T8154 </td><td></td></tr><tr><td> Hemocymeter Technocolor Neubar </td><td>赫斯曼</td><td>不可用</td><td></td></tr><tr><td>光镜下</td><td>尼康</td><td>尼康TMS </td><td></td></tr><tr><td> Cyrovial管</td><td>格雷纳生物一</td><td> 121278 </td><td></td></tr><tr><td>低温冷冻contrainer </td><td> NALGENE </td><td> 5100-0001 </td><td></td></tr><tr><td> DotScan抗体芯片试剂盒</td><td> Medsaic </td><td>不可用</td><td></td></tr><tr><td> DotScan芯片洗托盘</td><td> Medsaic </td><td>不可用</td><td></td></tr><tr><td> KimWipes </td><td>金佰利</td><td> 4103 </td><td></td></tr><tr><td>甲醛37％ </td><td> Sigma - Aldrich公司</td><td> F1635 - 500ML </td><td></td></tr><tr><td> DotReaderTM </td><td> Medsaic </td><td>不可用</td><td></td></tr><tr><td>牛血清白蛋白</td><td> Sigma - Aldrich公司</td><td> A9418 - 10G </td><td></td></tr><tr><td>热灭活AB血清2％ </td><td> Invitrogen公司</td><td> 34005100 </td><td></td></tr><tr><td>藻红蛋白的共轭CD3 </td><td> Beckman Coulter公司</td><td> ET386 </td><td></td></tr><tr><td> AlexaFluor647 -共轭EpCAM的</td><td> BioLegend </td><td> 324212 </td><td></td></tr><tr><td>台风的FLA 9000 </td><td> GE医疗集团</td><td> 28-9558-08 </td><td> 532 nm激光，580 BP30 PE排放过滤器。 633 nm激光和670 BP30 Alexa647排放过滤器</td></tr><tr><td> MultiExperiment浏览器V4.4 </td><td> TM4芯片软件套件</td><td>打开 - 源码软件（参11） </td><td></td></tr></tbody></table>

colorectal cancer cell surface protein profiling using an antibody microarray and fluorescence multiplexing

依靠目前的预后和"儿童权利公约"的分类分期，病理组织学和临床研究结果结合起来的系统。然而，在大多数"儿童权利公约"的情况下，细胞功能障碍是众多的基因突变，修改蛋白表达和翻译后修饰1的结果。 一些细胞表面抗原，包括集群分化（CD）抗原，已被确定为潜在的预后或转移的生物标志物在CRC。这些抗原的表达理想的生物标志物往往与肿瘤进展或与其他类型的细胞，如互动的变化的肿瘤浸润淋巴细胞（TILS）和肿瘤相关的（TAMS）巨噬细胞。 使用免疫组织化学（IHC）癌症的子分类和预测是公认的对某些类型的肿瘤2,3。但是，没有一个"标记"显示预后意义大于临床病理分期或获得广泛接受，在所有儿童权利公约"情况下的常规病理报告为使用。 最近的方针疾病表型的预后分层依赖的表面蛋白的配置文件使用多个"标记"。虽然表达的肿瘤蛋白质组技术如iTRAQ分析是一个功能强大的工具biomarkers4发现，它不是诊断实验室常规使用的最佳选择，不能区分不同类型的细胞在混合人口。此外，肿瘤组织大量的纯化的质膜糖蛋白的分析，这些方法都需要。 在这段视频中，我们描述了一个简单的方法，从分类的CRC使用DotScan CRC抗体芯片的样品活细胞的表面蛋白质组分析。 122抗体芯片包括一个标准的82 -抗体确认系特定标记的白细胞粘附分子，受体和炎症和免疫反应 5标志物的范围，CRC的40个潜在的预后标志物的检测与卫星地区的区域。细胞被捕获，只对他们表达相应抗原的抗体。光学扫描确定，每个点的细胞密度，反映了细胞表达，抗原，抗原的表达和亲和力的抗体6水平的比例。 CRC的组织或正常的肠道黏膜，光学扫描反映免疫细胞混合种群。然后，可以使用复用荧光来分析细胞阵列上捕获的利益选择的细分人群。例如，Alexa的647抗上皮细胞粘附分子（EpCAM的; CD326），是一个泛上皮被用来检测的CRC细胞和正常的肠道黏膜上皮细胞的分化抗原，而藻红蛋白 - 抗CD3，检测浸润T细胞7。 DotScan的CRC芯片应诊断替代的解剖学基础CRC分期系统的原型。

Watch this Scientific Journal Video about Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing at JoVE.com

Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

我们描述了一个过程分解大肠直肠癌（CRC）来产生可行的单个细胞，然后在定制的抗体，认识表面抗原（DotScan CRC芯片）芯片捕获。绑定到芯片的细胞亚群可以分析使用荧光标记的单克隆抗体与荧光染料的复用。

大肠癌细胞表面蛋白的分析，使用一种抗体的芯片和荧光多路复用

The current prognosis and classification of CRC relies on staging systems that integrate histopathologic and clinical findings. However, in the majority ...

colorectal-cancer-cell-surface-protein-profiling-using-an-antibody

Nanyang Technological University

Research

JoVE Journal

Immunology and Infection

13.9K 次观看.  University of Sydney. 我们描述了一个过程分解大肠直肠癌（CRC）来产生可行的单个细胞，然后在定制的抗体，认识表面抗原（DotScan CRC芯片）芯片捕获。绑定到芯片的细胞亚群可以分析使用荧光标记的单克隆抗体与荧光染料的复用。

视频: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

Multiplexed Fluorescent Microarray for Human Salivary Protein Analysis Using Polymer Microspheres and Fiber-optic Bundles

Herein, we describe a protocol for simultaneously measuring six proteins in saliva using a fiber-optic microsphere-based antibody array. The immuno-array technology employed combines the advantages of microsphere-based suspension array fabrication with the use of fluorescence microscopy. As described in the video protocol, commercially available 4.5 &#956;m polymer microspheres were encoded into seven different types, differentiated by the concentration of two fluorescent dyes physically trapped inside the microspheres. The encoded microspheres containing surface carboxyl groups were modified with monoclonal capture antibodies through EDC/NHS coupling chemistry. To assemble the protein microarray, the different types of encoded and functionalized microspheres were mixed and randomly deposited in 4.5 &#956;m microwells, which were chemically etched at the proximal end of a fiber-optic bundle. The fiber-optic bundle was used as both a carrier and for imaging the microspheres. Once assembled, the microarray was used to capture proteins in the saliva supernatant collected from the clinic. The detection was based on a sandwich immunoassay using a mixture of biotinylated detection antibodies for different analytes with a streptavidin-conjugated fluorescent probe, R-phycoerythrin. The microarray was imaged by fluorescence microscopy in three different channels, two for microsphere registration and one for the assay signal. The fluorescence micrographs were then decoded and analyzed using a homemade algorithm in MATLAB.

We describe a procedure for profiling salivary proteins using multiplexed microsphere-based antibody arrays. Monoclonal antibodies were covalently linked to fluorescent dye-encoded 4.5 &#x03BC;m polymer microspheres using carbodiimide chemistry. The modified microspheres were deposited in fiber-optic microwells to measure protein levels in saliva using fluorescence sandwich immunoassays.

复用荧光微阵列人类唾液蛋白质分析用高分子微球和光纤束

Herein, we describe a protocol for simultaneously measuring six proteins in saliva using a fiber-optic microsphere-based antibody array. The immuno-array ...

科研

化学

Automated Multiplex Immunofluorescence Panel for Immuno-oncology Studies on Formalin-fixed Carcinoma Tissue Specimens

Continued developments in immuno-oncology require an increased understanding of the mechanisms of cancer immunology. The immunoprofiling analysis of tissue samples from formalin-fixed, paraffin-embedded (FFPE) biopsies has become a key tool for understanding the complexity of tumor immunology and discovering novel predictive biomarkers for cancer immunotherapy. Immunoprofiling analysis of tissues requires the evaluation of combined markers, including inflammatory cell subpopulations and immune checkpoints, in the tumor microenvironment. The advent of novel multiplex immunohistochemical methods allows for a more efficient multiparametric analysis of single tissue sections than does standard monoplex immunohistochemistry (IHC). One commercially available multiplex immunofluorescence (IF) method is based on tyramide-signal amplification and, combined with multispectral microscopic analysis, allows for a better signal separation of diverse markers in tissue. This methodology is compatible with the use of unconjugated primary antibodies that have been optimized for standard IHC on FFPE tissue samples. Herein we describe in detail an automated protocol that allows multiplex IF labeling of carcinoma tissue samples with a six-marker multiplex antibody panel comprising PD-L1, PD-1, CD68, CD8, Ki-67, and AE1/AE3 cytokeratins with 4&#8242;,6-diamidino-2-phenylindole as a nuclear cell counterstain. The multiplex panel protocol is optimized in an automated IHC stainer for a staining time that is shorter than that of the manual protocol and can be directly applied and adapted by any laboratory investigator for immuno-oncology studies on human FFPE tissue samples. Also described are several controls and tools, including a drop-control method for fine quality control of a new multiplex IF panel, that are useful for the optimization and validation of the technique.

A detailed protocol for a six-marker multiplex immunofluorescence panel is optimized and performed, using an automated stainer for more consistent results and a shorter procedure time. This approach can be directly adapted by any laboratory for immuno-oncology studies.

福尔马林固定癌组织标本免疫肿瘤学自动复合免疫荧光小组研究

Continued developments in immuno-oncology require an increased understanding of the mechanisms of cancer immunology. The immunoprofiling analysis of ...

癌症研究

Optimization, Design and Avoiding Pitfalls in Manual Multiplex Fluorescent Immunohistochemistry

Microenvironment evaluation of intact tissue for analysis of cell infiltration and spatial organization are essential in understanding the complexity of disease processes. The principle techniques used in the past include immunohistochemistry (IHC) and immunofluorescence (IF) which enable visualization of cells as a snapshot in time using between 1 and 4 markers. Both techniques have shortcomings including difficulty staining poorly antigenic targets and limitations related to cross-species reactivity. IHC is reliable and reproducible, but the nature of the chemistry and reliance on the visible light spectrum allows for only a few markers to be used and makes co-localization challenging. Use of IF broadens potential markers but typically relies on frozen tissue due to the extensive tissue autofluorescence following formalin fixation. Flow cytometry, a technique that enables simultaneous labeling of multiple epitopes, abrogates many of the deficiencies of IF and IHC, however, the need to examine cells as a single cell suspension loses the spatial context of cells discarding important biologic relationships. Multiplex fluorescent immunohistochemistry (mfIHC) bridges these technologies allowing for multi-epitope cellular phenotyping in formalin fixed paraffin embedded (FFPE) tissue while preserving the overall microenvironment architecture and spatial relationship of cells within intact undisrupted tissue. High fluorescent intensity fluorophores that covalently bond to the tissue epitope enables multiple applications of primary antibodies without worry of species specific cross-reactivity by secondary antibodies. Although this technology has been proven to produce reliable and accurate images for the study of disease, the process of creating a useful mfIHC staining strategy can be time consuming and exacting due to extensive optimization and design. In order to make robust images that represent accurate cellular interactions in-situ and to mitigate the optimization period for manual analysis, presented here are methods for slide preparation, optimizing antibodies, multiplex design as well as errors commonly encountered during the staining process.

Multiplex fluorescent immunohistochemistry is an emerging technology that enables the visualization of multiple cell types within intact formalin-fixed, paraffin embedded (FFPE) tissue. Presented are guidelines for ensuring a successful 7-color multiplex with instructions for optimizing antibodies and reagents, preparing slides, design and tips for avoiding common problems.

手动复用荧光免疫学的优化、设计和避免陷阱

Microenvironment evaluation of intact tissue for analysis of cell infiltration and spatial organization are essential in understanding the complexity of ...

Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts

Invading colorectal cancer (CRC) cells have acquired the capacity to break free from their sister cells, infiltrate the stroma, and remodel the extracellular matrix (ECM). Characterizing the biology of this phenotypically distinct group of cells could substantially improve our understanding of early events during the metastatic cascade.

Tumor invasion is a dynamic process facilitated by bidirectional interactions between malignant epithelium and the cancer associated stroma. In order to examine cell-specific responses at the tumor stroma-interface we have combined organotypic co-culture and laser micro-dissection techniques.
Organotypic models, in which key stromal constituents such as fibroblasts are 3-dimentioanally co-cultured with cancer epithelial cells, are highly manipulatable experimental tools which enable invasion and cancer-stroma interactions to be studied in near-physiological conditions.

Laser microdissection (LMD) is a technique which entails the surgical dissection and extraction of the various strata within tumor tissue, with micron level precision.
By combining these techniques with genomic, transcriptomic and epigenetic profiling we aim to develop a deeper understanding of the molecular characteristics of invading tumor cells and surrounding stromal tissue, and in doing so potentially reveal novel biomarkers and opportunities for drug development in CRC.&#160;&#160;&#160;

Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts

Molecular profiling of laser microdissected cells and stroma from synthetic, tissue-engineered colorectal cancer models represents a novel and manipulatable approach to characterize and dissect the distinctive biology at the interface between tumor cells at the invasive front and cancer associated stromal cells. &#160;

在结直肠癌细胞的三维模型的入侵肿瘤微环境的分子剖析和<em&gt;体外</em&gt;成纤维细胞

Invading colorectal cancer (CRC) cells have acquired the capacity to break free from their sister cells, infiltrate the stroma, and remodel the ...

医学

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 ...

<meta charset="utf8"></head><body>使用糖组学指导的糖蛋白质组学分析结直肠癌组织

Glycomics-Guided Glycoproteomics Facilitates Comprehensive Profiling of the Glycoproteome in Complex Tumor Microenvironments

Glycosylation is a common and structurally diverse protein modification that impacts a wide range of tumorigenic processes. Mass spectrometry-driven glycomics and glycoproteomics have emerged as powerful approaches to analyze liberated glycans and intact glycopeptides, respectively, offering a deeper understanding of the heterogeneous glycoproteome in the tumor microenvironment (TME). This protocol details the glycomics-guided glycoproteomics method, an integrated omics technology, which firstly employs porous graphitized carbon-LC-MS/MS-based glycomics to elucidate the glycan structures and their quantitative distribution in the glycome of tumor tissues, cell populations, or bodily fluids being investigated. This allows for a comparative glycomics analysis to identify altered glycosylation across patient groups, disease stages, or conditions, and, importantly, serves to enhance the downstream glycoproteomics analysis of the same sample(s) by creating a library of known glycan structures, thus reducing the data search time and the glycoprotein misidentification rate. Focusing on N-glycoproteome profiling, the sample preparation steps for the glycomics-guided glycoproteomics method are detailed in this protocol, and key aspects of the data collection and analysis are discussed. The glycomics-guided glycoproteomics method provides quantitative information on the glycoproteins present in the TME and their glycosylation sites, site occupancy, and site-specific glycan structures. Representative results are presented from formalin-fixed paraffin-embedded tumor tissues from colorectal cancer patients, demonstrating that the method is sensitive and compatible with tissue sections commonly found in biobanks. Glycomics-guided glycoproteomics, therefore, offers a comprehensive view into the heterogeneity and dynamics of the glycoproteome in complex TMEs, generating robust biochemical data required to better understand the glycobiology of cancers.

<meta charset="utf8"></head><body>糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

This protocol details the glycomics-guided glycoproteomics method, an integrated omics technology that offers comprehensive insights into the heterogeneous glycoproteome in complex tumor microenvironments required to better understand the glycobiology of cancers.

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组 

Glycosylation is a common and structurally diverse protein modification that impacts a wide range of tumorigenic processes. Mass spectrometry-driven ...

大肠癌细胞表面蛋白的分析，使用一种抗体的芯片和荧光多路复用

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此视频中的章节

复用荧光微阵列人类唾液蛋白质分析用高分子微球和光纤束

福尔马林固定癌组织标本免疫肿瘤学自动复合免疫荧光小组研究

手动复用荧光免疫学的优化、设计和避免陷阱

在结直肠癌细胞的三维模型的入侵肿瘤微环境的分子剖析和

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

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组

糖组学引导的糖蛋白质组学有助于在复杂的肿瘤微环境中全面分析糖蛋白质组