我们感谢薛Montgiraud，朱丽叶·希门尼斯和Magali Jaillard和Bertrand Bonnaud对本赫尔维-V2协议的初始开发和优化的贡献。我们还要感谢哈德Haidous他在道德方面的考虑指导。

1。手术一旦受术去除，保持前列腺置于冰上，直到由病理学家采取负责。 2。处理前列腺组织的<ol><li>尊重围手术期缺血的延迟，由专门的工作人员在手术切除后30分钟转让冰上前列腺癌根治术标本到实验室。冷冻的延迟应该小于20〜30分钟（ 图3A）。 </li><li>称重并根据通常的协议（ 例如，绿色的右侧，黑色的左边，参见图3B和3C）染色的前列腺。 </li><li>在后侧（ 图3D）执行腺大横截面。东方的前列腺，并把它放在前侧。在后侧，用无菌手术刀进行压盖的大横截面。 </li><li>解剖组织块上的过渡地带，在左和右边缘区域，留下边缘完好（ 图3E）。 </li><li>把组织的核心在一个Eppendorf管中，急速冷冻并储存在液氮（ 图3F）。如果你不使生物资料库直接进行步骤2.7进行。 </li><li>执行前列腺银行只有当癌症对活检的总长度是优越到10毫米。用缝合线，关闭前列腺和防止腺体畸变和手术切缘（ 图3G）最小的干扰。然后根据组织学分析的常规步骤修复前列腺癌根治术标本用福尔马林和嵌入在石蜡。 </li><li>安装冷冻组织核心垂直于一个小土堆华侨城，并在一个冰冻切片。采取第一单5微米冰冻切片，用甲苯胺蓝染色了。 </li><li>执行快速组织学检查来分析组织的性质（ 即 ，良性或恶性）。对于肿瘤组织，估计肿瘤细胞的数量并只选择核心，超过80％的肿瘤细胞。 </li><li>在此之后，执行新的单5μm的冰冻切片，用苏木，曙红和赛峰留下污点。然后，切段15×30微米，并将其放置在一个无RNA酶的离心管中。 </li><li>取最后5微米的冰冻切片进行苏木，曙红和赛峰集团和弄脏它来控制肿瘤细胞的数量在过程结束。 </li><li>将Eppendorf管在干冰中和样品传送到分子生物学实验室。 </li></ol> 3。 RNA提取，纯化和质量控制<ol><li>同质化。在1毫升Trizol/100毫克组织的存在下进行均质直至组织完全溶解在溶液中。加的Trizol溶液逐渐并使用手持式粉碎机进行护理冰上。一旦均质，等分的溶液至Eppendorf管中并在Trizol试剂留在室温下为五分钟。 </li><li>相分离。加入300μL氯仿（或150微升BCP/1.5毫升Trizol法）。涡流15秒，然后在室温留2-3分钟。 12,000×g离心15分钟，在2-8℃。 </li><li> RNA沉淀。仔细顶部水相转移到新管。加入750μL异丙醇。在室温下孵育10分钟（由反转搅拌）。孵育2小时，在-19°C/-31°C。以12,000×g离心30分钟离心分离的样品在2-8℃。 </li><li> RNA的洗和悬挂。离心后，除去上清液。洗涤RNA沉淀用1 ml 80％乙醇（轻轻扭转管）。在7500×g离心10分钟，离心样品在2-8°C。使用P1000和P10去除上清。让剩余的乙醇在空气中干燥2-3分钟。加入100μl无RNase水，输送管，以70℃加热块，让坐2-3分钟，以溶解沉淀。然后雪藏。储存于-19°C/-31°C于短期存储和 -80℃下长期储存。 </li><li> RNA纯化。使用RNeasy迷你试剂盒（Qiagen）纯化的RNA。简单地说，加入350μL缓冲液RLT至100微升RNA样品开始拌匀，然后按照Qiagen公司的程序。最后，取3微升（满分50微升）纯化产物的等分试样进行质量控制（步骤3.6）。商店的RNA在-19°C/-31°C为短期内或在-80℃下长期储存。 </li><li> RNA的质量控制（ 图4A）。检查RNA的质量和用生物分析仪（安捷伦科技），和一个的NanoDrop（热电）的RNA的完整性，根据制造商的指示。将RNA完整性数（RIN）是用来评估RNA的质量。特别是，成功的18S和28S峰值检测，强烈建议使用在接下来的步骤中样品。 </li></ol> 4。 WT-鼓掌RNA扩增建议执行使用WT-OV扩增​​步骤振动性扩增试剂盒在最佳条件: <ul><li>跑了不下8扩增样品在同一时间，以确保移液精度。然后，准备需要的工具包的分割成3个批次的8个反应预混时占1垃圾量。 </li><li>始终保持解冻的试剂和反应管置于冰上，除非另有指示。 </li><li>用于净化只有一个新鲜的80％乙醇溶液。 </li><li>不要停留在协议中的任何阶段。 </li></ul><ol><li>稀释的总RNA，以获得25纳克/微升的浓度。处理2微升稀释样品。 </li><li>准备多聚A RNA穗的控制解决方案通过连续稀释的多聚A RNA的股票与聚-A控制稀释液（Affymetrix公司），实现1:25,000稀释。 第1步:第一链cDNA合成从4.3 - 4.8。提到试剂由供应商简称如下:A1（第一链引物混合），A2（网络RST链缓冲液混合），A3（第一链酶混合物）。 </li><li>解冻A1和A2在室温下。通过使用涡旋混合器在2秒和旋转2秒混合。然后，迅速置于冰上。放置A3冰上。 </li><li>把2μL总RNA（50毫微克）的0.2 ml的PCR管中，加入2微升的A1（最终体积:4微升）。盖和旋管，持续2秒。 </li><li>孵育在65℃下5分钟，然后将试管置于冰上。 </li><li>制备的第一链cDNA的主混合物如下（假定为一个单一的反应）。吹打混匀并离心母液简要介绍。立即置于冰上。 <table border="1"><tbody><tr><th>试剂</th><th>量</th></tr><tr><td>第一链缓冲液混合（A2） </td><td> 5微升</td></tr><tr><td>多聚A RNA对照（1:25,000） </td><td> 0.5微升</td></tr><tr><td>第一链酶混合物（A3） </td><td> 0.5微升</td></tr></tbody></table></li><li>新增6＆＃181，L母液与RNA /含底漆管的。轻弹管，旋转2秒混匀，迅速置于冰上（最终体积:10微升）。 </li><li>孵育在4℃下1分钟，然后25℃10分钟，然后42℃10分钟，然后70℃15分钟。保持冷静，在4°C。从热循环仪中取出反应管中，短暂地旋转并保持在冰上。立即与第二链cDNA合成的步骤继续。 步骤2:第二链cDNA合成从4.8 - 4.12。 B1（第二链缓冲液混合）和B2（第二链酶混合物）中提到的试剂均由供应商提供如下简称。 </li><li>降速B2和B3为2秒，并迅速置于冰上。解冻B1在室温下。通过使用涡旋混合器在2秒内混合，旋转2秒，并迅速置于冰上。 </li><li>准备第二链预混如下（假定为一个单一的反应）。吹打混匀并离心母液布里飞。立即置于冰上。 <table border="1"><tbody><tr><th>试剂</th><th>量</th></tr><tr><td>第二链缓冲液混合（B1） </td><td> 9.75微升</td></tr><tr><td>第二链酶混合物（B2） </td><td> 0.25微升</td></tr></tbody></table></li><li>加入10微升的主要混合液的各第一链反应管。吹打3倍，自旋为2秒，并置于冰上（20微升最终体积）混合。 </li><li>孵育在4℃下1分钟，然后25℃10分钟，然后50℃30分钟，然后70℃5分钟。保持冷静，在4°C。从热循环仪中取出反应管中，短暂地旋转并保持在冰上。立即与后第二链提升一步继续。 第3步:后第二链提升4.13 - 4.15。提到试剂由供应商简称如下:B1（第二链缓冲液混合），B3（反应增强酶混合物）。 </p&gt; </li><li>通过结合B1和B3的组合如下（假定为一个单一的反应）准备母液。吹打混匀并离心母液简要介绍。立即置于冰上。 <table border="1"><tbody><tr><th>试剂</th><th>量</th></tr><tr><td>第二链缓冲液混合（B1） </td><td> 1.9微升</td></tr><tr><td>反应增强酶混合物（B3） </td><td> 0.1微升</td></tr></tbody></table></li><li>加入2μl的预混到每个第二链反应管。吹打3倍，自旋为2秒，并置于冰上（:22微升最终体积）混合。 </li><li>孵育在4℃下1分钟，然后37℃15分钟，然后80℃20分钟。保持冷静，在4°C。从热循环仪取出反应管中，短暂旋转并放置在冰上。立即与三亚凤凰国际机场扩增步骤继续。 步骤4:单链cDNA（sscDNA）合成从4.16 SPIA程序-4.19。 C1（SPIA引物混合物），C2（SPIA缓冲液混合），C3（SPIA酶混合物）中提到的试剂均由供应商提供如下简称。 </li><li>解冻的C1和C2在室温下。通过使用涡旋混合器，旋转2秒，并迅速置于冰上混合。解冻C3冰上。轻轻颠倒混匀5倍的含量。确保不要引入气泡。然后，旋转2秒，并置于冰上。 </li><li>准备三亚凤凰国际机场，预混，占0.5废弃物量，如下所示。吹打混匀并离心母液简要介绍。立即置于冰上。 <table border="1"><tbody><tr><th>试剂</th><th>量</th></tr><tr><td>三亚凤凰国际机场缓冲区混合（C2） </td><td> 5微升</td></tr><tr><td>三亚凤凰国际机场 - 底漆混合（C1） </td><td> 5微升</td></tr><tr><td>三亚凤凰国际机场 - 酶混合物（C3） </td><td> 10微升</td></tr></tbody></table></li><li>加入20微升的三亚凤凰国际机场预混，以增强第二链反应吨宇部。吹打6-8X，自旋和冰上快速放置（42微升最终体积）混合。 </li><li>孵育在4℃下1分钟，然后47℃60分钟，然后95℃5分钟。保持冷静，在4°C。从热循环仪中取出试管，简单地旋转并放置在冰上。 </li></ol> 5。 sscDNA纯化和质量控制<ol><li> sscDNA净化。使用QIAquik PCR纯化试剂盒（Qiagen）纯化sscDNA。简要地说，通过添加200μl的缓冲PB到42微升扩增的cDNA产物的开始，混合和负载在该柱上。然后按照Qiagen公司的程序。最后，取3μL（出30微升）的sscDNA纯化产物的等分质量控制（步骤5.2）。 </li><li> sscDNA收率和粒度分布的验证（ 图4B）。检查sscDNA产量和使用生物分析仪和一个的NanoDrop粒度分布，根据制造商的指示。扩增的cDNA分布的大小B应该要E 100和1500个碱基长大约有600个碱基的峰之间通常由。 </li></ol> 6。 sscDNA碎片<ol><li>准备2微克cDNA在30微升，调节使用不含核酸酶的水的体积。 </li><li>准备1X一普 - 所有缓冲区PLUS（OPA），从10倍OPA缓冲Plus解决方案开始。 </li><li>准备0.2 U /μL的DNase I（5倍稀释1 U /μL的DNase I的）。 </li><li>准备一个碎片预混如下（假定为一个单一的反应）: <table border="1"><tbody><tr><th>试剂</th><th>量</th></tr><tr><td> 10X一普 - 所有缓冲液加</td><td> 3.6微升</td></tr><tr><td> DNA酶I（0.2 U /μL） </td><td> 3微升</td></tr></tbody></table></li><li>加入6.6微升碎片混合到30微升sscDNA的。 </li><li>自旋和孵育在37℃下进行10分钟，然后加入灭活DNA酶I在95℃下10分钟，并保持在冰上。分装1＆＃181;升零散的cDNA安捷伦基于尺寸分布的验证。 </li><li> sscDNA尺寸分布验证（ 图4C）。利用生物分析仪（安捷伦）检查sscDNA粒度分布。分散的cDNA的大小分布应在35至200个碱基之间，典型地包括。 </li></ol> 7。零散sscDNA的标签<ol><li>稀释DLR-1A 7.5至5mm于DEPC水中。 </li><li>准备一个标签预混如下（假定为一个单一的反应）: <table border="1"><tbody><tr><th>试剂</th><th>量</th></tr><tr><td> 5X末端转移酶反应缓冲液</td><td> 14微升</td></tr><tr><td> 氯化钴（25毫米） </td><td> 14微升</td></tr><tr><td> DLR-1A（5毫米） </td><td> 1微升</td></tr><tr><td>末端转移酶（400 U /μL） </td><td> 4.4微升</td></tr></tbody></table></li><li>加入33.4微升标签组合每个碎片cDNA样品。 </li><li>轻弹管混匀，短暂地旋转，在37℃下60分钟，然后放在冰上。 </li></ol> 8。杂交的赫尔维微阵列芯片<ol><li>预湿的HERV基因芯片用200μl的预杂交混合物（Affymetrix公司）中，并孵育在50℃下，每分钟60转，10分钟。 </li><li>制备的杂交组合如下（假定为一个单一的反应）: <table border="1"><tbody><tr><th>试剂</th><th>量</th></tr><tr><td>控制寡核苷酸B2（为3nM） </td><td> 3.3微升</td></tr><tr><td> 20倍的真核杂交对照</td><td> 10微升</td></tr><tr><td> 2个杂交组合</td><td> 100微升</td></tr><tr><td> 99.9％的DMSO </td><td> 17.7微升</td></tr></tbody></table></li><li>加入131微升杂交组合中的69微升分散和标记的cDNA在室温下做出最后的画外音lume明的200微升。 </li><li>混合和变性2分钟，在95℃，然后保温在50℃下5分钟，然后以最大速度离心5分钟。 </li><li>清空预湿赫尔维基因芯片和装载200微升目标的准备。在两个隔膜适用强硬点。 </li><li>杂交在50℃下，每分钟60转，18小时。 </li><li> 18小时后，清空赫尔维基因芯片和收集的杂交液保存在4°C补探针阵列用250μl洗涤缓冲液A。如果芯片不立即运行到流体，贮存于4℃。 </li></ol> 9。洗涤和染色<ol><li>从全球气候观测系统菜单栏运行射流。在射流对话框中，选择感兴趣的车站（1 - 4），然后选择Shutdown_450所有模块，然后运行。浸泡3射流抽吸线到Milli-Q水。按照液晶显示屏的提示。 </li><li>该Prime_450程序适用于所有模块。将管材洗涤缓冲液A中再说装有400 mL清洗缓冲液A瓶，并在含200ml洗涤缓冲液B的瓶一对洗涤缓冲液B，按照液晶显示屏的提示。 </li><li>抬起的织针，然后将600μl的染色鸡尾酒1（SAPE溶液混合）和600μl的染色鸡尾酒2（抗体溶液混合）的含微量离心管中在位置＃1，＃2，和800微升阵列保持缓冲溶液在位置＃3 。 </li><li>分配合适的芯片给每个模块中，选择FS450-004协议和运行的每个模块，按照屏幕上的说明操作。 </li></ol> 10。扫描<ol><li>热身GS3000扫描仪。这是准备当指示灯变为绿色进行扫描。 </li><li>适用强硬点到隔，以避免泄漏，直接在芯片然后加载到自动加载磁带机或交替放入扫描仪。开始扫描。 </li><li>扫描芯片后，。产生CEL文件。检查图像和对齐到网格当场识别探针细胞（&lt;STRONG&gt;图4D-F）。 </li></ol> 11。数据分析<ol><li>质量控制。参考标准的Affymetrix控制，以验证该HERV-V2芯片满足质量控制标准。为了这个目的，下面的陈述可以使用:日志强度值分布（密度图和箱线图），平均绝对偏差（MAD）的相对强度中位数（MAD - 地中海）地块，该地块的背景，归一化缩放的标准误差（怒色）地块和相对数表达（RLE）地块。 </li><li>正常化。此外，该数据集应探讨以突出意想不到的效果批次和统计分析之前纠正它们。数据预处理因此包括一个背景校正（ 例如 ，基于所述色氨酸探测基准信号），其次是RMA归一化并聚合15。 </li><li>数据挖掘和寻找差异表达基因。正常化的芯片和应用层次clusteri纳克的方法来探索数据集（ 图6A）。然后，通过使用微阵列的一个经典的显著分析（SAM）的步骤16后跟一个假发现率（FDR）校正17执行搜索为差异表达的基因（DEG）。请注意，这些步骤是完全集成在一些软件分析套件将Partek像高盛，但也可以使用R统计软件18从Bioconductor的项目19个包进行。统计分析后，筛选数据集，以排除对其中的表达值均小于2 6探针组。 </li><li>可视化和解释。从解释中使用注释数据库专用接口的赫尔维-V2芯片的结果。 </li></ol>

这项工作是由生物梅里埃SA，该收容所Civils里昂和法国公共机构OSEO（高级诊断为新的治疗方法，专门用于个性化医疗法国​​政府资助的计划）的支持。 PP，VC + +，GO，NM，和FM是生物梅里埃SA的员工。 PP，新墨西哥州和FM提交涵盖了本文的研究结果的专利申请。

在过去的10年中，大部分为尝试HERV表达测量都使用了RT-PCR技术，要么专注于某一特定位点20-24或基于的聚合酶基因的相对保护内赫尔维属25,26评估的一般趋势。此外，使用加上用于检测和量化HERV家庭27,28的表达低密度微阵列高度简并引物PCR扩增。为了跟踪一个家庭内的单个基因座的表达，方法的基础上的保守区结合随后的克隆和测序的PCR扩增使HML-2 29,30或HERV-E4.1 31家庭到转录活性的不同元件被识别。还通过克隆和测序步骤结束时，基因组重复表达监测技术，目的是查明确定主动HML-2特异性人孤零零的LTR重复发起人之一<sup&gt; 32,33。我们先后开发了两代的高密度微阵列专用于赫尔维转录组的分析，引入适合重复的元素探测的设计方法，以减少家庭34,35内旁系同源分子之间的交叉反应。该赫尔维-V2芯片，针对2,690截然不同的HERV-W，HERV-H，HERV-E 4.1，赫尔维 - FRD，HERV-K HML-2和赫尔维-K HML-5系列的原病毒和2,883独奏的LTR，亮相的1718 HERV位点（图7A和B）在一个宽范围的组织35，以推定的前列腺癌生物标志物的鉴定中示出本文的表达。此外，在给定的轨迹中使用多个探针组的信息是关于它的转录调控。首先，在同一个U5正面1结合一个U3的负信号进行分类的LTR启动子，并且相反地U3正极和U5的负信号可以反映一个多聚腺苷酸化作用。因此，我们我dentified在广泛的组织35，并在此基础上的U3 U5由阵列提供二分信息326的LTR启动子，我们提出，并通过实验证实了一段选定的情况下，这种独立的转录是得到了甲基化依赖的表观遗传过程34（ 图控制8）。其次，从如 LTR的检测信号， 插科打诨和env独立的探针或针对特定剪接点探针发出的信息是对前病毒拼接策略，就说明了在胎盘或睾丸肿瘤34 ERVWE1/Syncytin1表达谱。这表明，赫尔维特异性探针的选择过程是强大到足以支持组织相关的拼接战略的确定，尽可能高效率地用于传统的基因36（ 图8）。 这种方法是第一次尝试，以确定个别赫尔维表达基因使用基于Affymetrix公司的技术，一个自定义的高密度微阵列。微阵列格式的明确优势破译HERV转录组包括（i）协调勘探几个HERV家庭及（ii）同时和独立分析不同区域的每个基因座的， 例如 。 U3和U5结构域独奏和原病毒的LTR，GAG或包膜的区域和可能的前病毒的结构相关联的拼接连接处，没有任何先验的HERV元件的功能。前景依赖于微阵列相关的生物运算工具注解的改进。这应该允许一个转换芯片信号转换成生物假说，如证明积极HERVs是否推动lncRNA转录或调节或多或少近端编码基因的表达。事实上，这样的假设是支持最近的研究，发现含有的V分量前列腺癌相关的非编码RNA转录物iral的ORF从HERV-K内源性逆转录病毒家族或部分的病毒LTR启动子区域37，以及2基因融合事件即HERV-K22q11-ETV1和HERV-K17-ETV 38,39。两者合计，整个转录组的方法结合LTR功能和拼接策略标识可以帮助破译的标记与赫尔维表达的触发组件慢性40,41和传染病42,43。

人类内源性逆转录病毒（也称为HERVs）是我们整个基因组中传播。他们从生殖系内的祖先和独立的感染，其次是复制粘贴的传播过程，并导致多拷贝的家庭起源。今天，他们没有更多的传染性，但它们占据了人基因组的8％;作为比较点，外显子跨越了人类基因组的2％。从2012年出版ENCODE项目的数据表明，不同类型的RNA覆盖约62％的基因组，其中包括在间隔区的三分之一。此外，似乎的转录调控基序的量为比对应于编码蛋白质的外显子1的至少4.5倍高。 HERVs长末端重复序列（LTR）代表广泛的潜在的转录调控元件的，因为它是在感染性逆转录病毒它们通常的功能。从历史上看，除了少数位点表达的胎盘或睾丸，人们普遍认为，赫尔维是无声的，由于EPigenetic调节。因此，我们设计了高密度微阵列，在Affymetrix公司的形式，旨在以最佳表征个体赫尔维位点表达，以便更好地了解它们是否处于活动状态，如果他们驾驶lncRNA转录或调节编码基因的表达。该工具被称为HERV-V2的基因芯片集成了23,583赫尔维的探针，可以区分个人的LTR组成5,573截然不同的赫尔维元素，以及完整的和部分原病毒（ 图2）。 诊断，评估和计划: 前列腺癌的诊断依据前列腺特异性抗原（PSA）的生物标志物在临床实验室，直肠指检评估前列腺形态学改变，最后由病理学家观察前列腺活检的用量。传统的癌症生物标志物，如PSA前列腺癌之间足够的特异性和敏感性的缺乏，已被广泛认可AF之三几十年的临床意义1。首先，提出了在前列腺11腺癌的诊断和治疗的PSA。这是后者建议癌症筛查和监测疾病12的发展。但是，仍然存在一个问题，经常问:"如何使用PSA"。 （I）对应于浓度血清2.5-10纳克灰色地带/毫升不允许被癌症和非癌症2之间作出了明确的差异;（二）两个大型队列研究招募成千上万的人在欧洲和美国未能前来关于筛查在疾病特异性死亡率13,14条款的有效性一个明确的结论;（三）分析术后PSA动力学参数，如PSA的间隙，PSA速度和倍增时间的，虽然简单的理论，可能会造成在实际应用中3,4相当大的挑战。我们可以预期，在未来几年，生物标志物的应用程序lications将支持观察等待和更多的还是依赖于肿瘤的表型较不积极治疗之间的一种临床选择。至于由病理学家提供的诊断，第一限制因素来自前列腺活检中有20％的假阴性诊断（许多癌症是由采样错过了）。第二个关注涉及以下的负1，这可能呈现的不利影响，需要额外的活检程序。 前列腺癌根治术是目前前列腺癌的标准治疗方法之一。所以建议在健康的患者，从45-65岁（格里森7至10）老化，特别是在积极的图案的情况下，多灶性肿瘤或可触知的肿瘤。它现在在我科采用机器人辅助手术完成。因为越来越多的证据表明，分子标记技术将在未来几年内最为重要的，我们决定向所有的患者参加一个节目前列腺的可能性组织库。更确切地说，对前列腺癌的分子扩大研究计划已经导致越来越要求获得高品质的新鲜肿瘤组织中前列腺切除标本。这项研究，特别是基因组学方法，要求高的DNA / RNA的质量大样本。需要的肿瘤和邻近的"非肿瘤&#39;从同一患者的组织。处理和加工根治性前列腺切除术的建议，目的是确保确定阶段和边缘状态，从而可能进一步治疗和预后病理特征。任何新鲜组织抽样的方法，因此，不应影响随后的病理评估，以可以接受的诊断。前列腺的解剖肉眼很难和高度重视需要支付保证金的组织和包膜浸润:任何解剖前列腺银行应始终由经过培训的uropathologist根据同意进行D协议。医学院和国家医疗委员会的伦理委员会同意这些调查和知情同意的获得为包含在前列腺组织银行所有患者。

<table border="0" cellpadding="0" cellspacing="0" width="717">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="22">
			<td height="22" style="height:22px;width:195px;">Trizol</td>
			<td style="width:92px;">Invitrogen</td>
			<td style="width:137px;">15596-026</td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:195px;">RNA poly-A control stock</td>
			<td style="width:92px;">Affymetrix</td>
			<td style="width:137px;">900433</td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:195px;">DNAse 1</td>
			<td style="width:92px;">Promega</td>
			<td style="width:137px;">M6101</td>
			<td style="width:295px;">1,000 U (1 U/&#181;l)</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:195px;">Terminal transferase</td>
			<td style="width:92px;">Roche</td>
			<td style="width:137px;">3333574001</td>
			<td style="width:295px;">400 U. Including enzyme and coenzyme (CoCl2).</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:195px;">DLR-1a</td>
			<td style="width:92px;">Affymetrix</td>
			<td style="width:137px;">900542</td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="85">
			<td height="85" style="height:85px;width:195px;">Hybridization internal controls B2 and 20x Eukaryotic Hybridization Control</td>
			<td style="width:92px;">Affymetrix</td>
			<td style="width:137px;">900454</td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:195px;">GeneChip Hybridization, Wash and staining</td>
			<td style="width:92px;">Affymetrix</td>
			<td style="width:137px;">900720</td>
			<td style="width:295px;">Including PreHybridization Mix and 2x Hybridization Mix for 30 reactions</td>
		</tr>
		<tr height="106">
			<td height="106" style="height:106px;width:195px;">10x One-Phor-All Buffer PLUS</td>
			<td style="width:92px;"></td>
			<td style="width:137px;"></td>
			<td style="width:295px;">Composition in DEPC-treated water: 100 mM Tris-acetate pH 7.5; 100 mM magnesium acetate; 500 mM potassium acetate.</td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:195px;">RNeasy Mini kit</td>
			<td style="width:92px;">Qiagen</td>
			<td style="width:137px;">74104</td>
			<td style="width:295px;">RNA cleanup protocol</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:195px;">WT-Ovation RNA amplification system</td>
			<td style="width:92px;">Nugen</td>
			<td style="width:137px;">2210-24</td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:195px;">QIAquik PCR purification kit</td>
			<td style="width:92px;">Qiagen</td>
			<td style="width:137px;">28104</td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:195px;">EQUIPMENT</td>
			<td style="width:92px;"></td>
			<td style="width:137px;"></td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:195px;">Material Name</td>
			<td style="width:92px;">Company</td>
			<td style="width:137px;">Catalogue Number</td>
			<td style="width:295px;">Comments</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:195px;">Nanodrop 1000</td>
			<td style="width:92px;">Thermo Scientific</td>
			<td style="width:137px;"></td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="22">
			<td height="22" style="height:22px;width:195px;">GeneChip Scanner 3000 7G</td>
			<td style="width:92px;">Affymetrix</td>
			<td style="width:137px;">GS30007G</td>
			<td style="width:295px;">Optional: autoloader</td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:195px;">GeneChip Fluidics Station 450</td>
			<td style="width:92px;">Affymetrix</td>
			<td style="width:137px;">FS450</td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="43">
			<td height="43" style="height:43px;width:195px;">GeneChip Hybridization 640 Oven</td>
			<td style="width:92px;">Affymetrix</td>
			<td style="width:137px;">640</td>
			<td style="width:295px;">Includes 4 GeneChip Probe array carriers</td>
		</tr>
		<tr height="127">
			<td height="127" style="height:127px;width:195px;">Workstation loaded with GeneChip Operating Software (GCOS) including the GeneChip Scanner 3000 High-Resolution Scanning Patch</td>
			<td style="width:92px;"></td>
			<td style="width:137px;"></td>
			<td style="width:295px;"></td>
		</tr>
		<tr height="232">
			<td height="232" style="height:232px;width:195px;">HERV-V2 chip</td>
			<td style="width:92px;">Affymetrix</td>
			<td style="width:137px;"></td>
			<td style="width:295px;">Custom array. 
			For microarray availability (for research use only), please contact: 
			Fran&#231;ois Mallet 
			Laboratoire Commun de Recherche Hospices Civils de Lyon-bioM&#233;rieux 
			Medical Diagnostic Discovery Department 
			Centre Hospitalier Lyon Sud, B&#226;timent 3F 
			69495, Pierre B&#233;nite cedex France 
			Phone: 33 (0)4 72 67 87 85 
			Email: francois.mallet@biomerieux.com</td>
		</tr>
		<tr height="717">
			<td></td>
			<td></td>
			<td></td>
			<td>HERV-V2 conception 
			Dedicated database and annotations 
			 
			The construction of a dedicated database, grouping genomic HERV sequences belonging to 6 HERV families, has been achieved by the following procedure: (i) the most complete and representative sequence of each HERV family was selected from the literature and defined as a prototype sequence (Figure 2). (ii) The 6 prototypes were functionally annotated with reference to their LTR (U3/R/U5) and internal parts (gag/pol/env). (iii) RepeatMasker 44 was then applied using these functional sequences as input libraries. A genome-wide search of all related sequences was performed over the human genome on the basis of a minimum 80% homology (NCBI 36/hg18). (iv) Finally, the functional sequences retrieved by this process were assembled into distinct loci on the basis of their genomic location and eventually implemented in a dedicated HERV database. This database, called HERV-gDB3, contains 10,035 individual HERV loci35. 
			 
			Locus-specific probes design 
			Starting from HERV-gDB3, overlapping tracks of 25-mer candidate probes were firstly generated. Each candidate probe was then aligned against the human genome using KASH 45 in order to assess the cross-hybridization potentialities. This latter estimation was performed by a model developed specifically for this purpose and referred to as EDA+. Briefly, the principle of EDA+ is to take into account the instability brought by mismatches and gaps in a 25-mer target/probe hybridization complex. Candidate probes exhibiting low cross-hybridization risks (i.e. a low number of non-specific genomic targets) are selected and lastly assembled into probesets. 
			 
			Custom HERV GeneChip microarray 
			The custom HERV GeneChip integrates 23,583 HERV probesets and can discriminate 5,573 distinct HERV elements, composed of solo LTRs, complete and partial proviruses (Figure 2). The standard Affymetrix control probes for unbiased amplification and hybridization were also included in the microarray.</td>
		</tr>
	</tbody>
</table>

microarray-based identification of individual herv loci expression: application to biomarker discovery in prostate cancer

前列腺特异性抗原（PSA）是用于临床使用的前列腺癌的主要诊断的生物标志物，但它缺乏特异性和敏感性，尤其是在低剂量值1。 "如何使用PSA"仍然是当前的问题，无论是对诊断为对应于血清2.5-10纳克/毫升的浓度不允许的癌症和非癌症2或病人随访取得了明显的分化灰色地带时作为手术后的PSA分析动力学参数可能会造成相当大的挑战，他们的实际应用3,4。另外，非编码RNA（ncRNA方法）正在成为人类癌症的关键分子，有潜力成为疾病的新型标志物， 如 PCA3在前列腺癌5,6和揭示肿瘤生物学的未知问题。此外，从2012年出版ENCODE项目的数据表明，不同类型的RNA覆盖约62％的根的青梅。而且，看来的转录调控基序的量为比对应于编码蛋白质的外显子1的至少4.5倍高。因此，人的内源性逆转录病毒（HERVs）的长末端重复序列（LTRs）构成了广泛推定/候选转录调节序列的，因为它是在感染性逆转录病毒它们的主要功能。 HERVs，它们扩散到整个人类基因组中，从种系内的祖先和独立的感染，随后复制粘贴扩展过程，并导致多拷贝的家庭占人类基因组的8％（注意，外显子跨越了基因组的2％的起源）。有些赫尔维位点仍表现已经与几个病症包括癌症7-10相关的蛋白质。我们设计了高密度微阵列，在Affymetrix公司形式，旨在以最佳表征个体赫尔维位点表达，以便更好地了解他们是否可以活动，如果他们驾驶的非编码RNA的转录或Modulate编码基因的表达。这个工具已经在前列腺癌字段（ 图1）中得到应用。

转录组学研究的价值主要在于起始生物材料的质量。如果在最佳条件下进行提取RNA，该RNA完整性数（RIN）通常为7或更大（ 图4A）。杂交2微克cDNA的Affymetrix公司的HERV-V2芯片上的需要意味着使用放大处理的。一个成功的扩增步骤导致一个钟形分布（ 图4B）。然后，DNAse1碎片是为了杂交（ 图4C）前大约100个核苷酸至均质化的cDNA大小分布进行的。杂交和扫描（ 图4D）之后，图像的目视检查使能1，以检查是否在网格以及对准点（ 图4E），如果杂交的控制是一致的（ 图4F）。这个步骤也是有用的，以排除微阵列，其中气泡或错误<html>在实验过程中发生的。 一旦芯片都通过质量控制（ 图5）和归一化之后，5匹配对肿瘤和正常前列腺RNA样品从里昂肥皂水医院统计分析导致了207 HERV探针组的识别差异表达的值（p.val &lt;0.05）（ 图6A）。为了支持这些记录并对其进行前列腺特异性信息，35附加的匹配对取样（结肠癌，卵巢癌，睾丸癌，乳腺癌，肺癌和前列腺癌）加入到最终确定的分析和SAM-FDR程序（FDR = 20％） 44前列腺特异性赫尔维探针组。其中，最相关的10 HERV结构进行说明（ 图6B）。进一步的临床研究将需要进行评估的灵敏度这些候选生物标志物和特异性的值。 pload/50713/50713fig1.jpg"宽度="500px的"/&gt; 从诊所的整体过程如图1方案 （1:前列腺切除术的临床医师和组织准备由病理学家）板凳（2-6:样品制备，靶的制备，芯片加工），导致候选生物标志物的鉴定（7:生物运算的赫尔维微阵列分析）。从正常组织来源的核酸被描述为橙色，从肿瘤领域衍生的核酸包括正常（橙色）和肿瘤特异性（黑色）核酸的组合。 <a href="https://www.jove.com/files/ftp_upload/50713/50713fig1highres.jpg" target="_blank">点击这里查看大图</a> 。 <img alt="图2" fo:content-width="6in" src="/files/ftp_upload/50713/50713fig2.jpg" width="500px" /> 图2概念和赫尔维-V2芯片的内容 :赫尔维序列从人类基因组中检索存储在一个所谓的HERV-gDB3数据库，则25 - 聚体候选探针之前被最终合成在阵列上通过专用的杂交建模程序（EDA +）（所得到的目标子区域被描绘为每个家庭）。 <a href="https://www.jove.com/files/ftp_upload/50713/50713fig2highres.jpg" target="_blank">点击这里查看大图</a> 。 <img alt="图3" fo:content-width="6in" src="/files/ftp_upload/50713/50713fig3.jpg" width="500px" /> 图3。前列腺处理由病理学家（A）新鲜前列腺癌根治术标本被转移到实验室。 （BC）前列腺是染色（绿右侧，黑色的左侧）。 （D）的腺体上后侧大横截面。 （ 五）离开边缘完好，PIEC组织中的ES被从前列腺不同区域解剖。组织（F）芯体被放置在Eppendorf管中。 （G）的缝合线是用来关闭前列腺和防止压盖失真和手术切缘最小的中断。然后，前列腺癌根治术标本准备根据组织学分析通常的程序固定在福尔马林。 <a href="https://www.jove.com/files/ftp_upload/50713/50713fig3highres.jpg" target="_blank">点击这里查看大图</a> 。 <img alt="图4" fo:content-width="6in" src="/files/ftp_upload/50713/50713fig4.jpg" width="500px" /> 核酸制备和杂交效率图4。质量控制 。 （A）+ RNA的完整性，（B）的cDNA扩增目标和（C）在杂交阶段使用零散的目标。钍ESE三个质量对照组与生物分析仪利用RNA纳米芯片和纳米真核生物意甲第二实验获得的。 （ 四）赫尔维-V2芯片杂交区域扫描后，（E）的左上角显示网格对齐控制的扩大和中心区域呈现斑点杂交对照（六）扩大的整体形象。 <a href="https://www.jove.com/files/ftp_upload/50713/50713fig4highres.jpg" target="_blank">点击这里查看大图</a> 。 <img alt="图5" fo:content-width="6in" src="/files/ftp_upload/50713/50713fig5.jpg" width="500px" /> 图5。处理的信号 。 （ 一 ）Affymetrix公司多聚腺苷酸秒杀式放大控制。多聚A控制沓，苏氨酸，苯丙氨酸和赖氨酸B.从成绩单枯草芽孢杆菌基因飙升的RNA样品中，并用来评估整体成功<html>目标准备步骤。强度应在这些尖峰在控件之间递减的值进行检测，以确保有高和低表达的基因之间的WT-的Ovation扩增过程中没有偏差。 （二）Affymetrix公司穗杂交控制。这些目标从大肠杆菌中分离大肠杆菌和P1噬菌体的标记过程前飙升。从BioB，BIOC，BIOD和Cre重组酶增加值表明杂交的全面成功。 （C）强度RMA标准化后的芯片信号的分布。大多数与价值观的探针表现出信号的2比6（背景）下，显示的整体表达主要局限于某些特定的赫尔维位点。 <a href="https://www.jove.com/files/ftp_upload/50713/50713fig5highres.jpg" target="_blank">点击这里查看大图</a> 。 ftp_upload/50713/50713fig6.jpg"宽度="500px的"/&gt; 图6的数据分析 。正常和肿瘤样本（ 一 ）分层聚类分析。和向下的正常和肿瘤样品中（蓝色）调节 - 使用欧几里德距离函数算法，分组探针组成向上（红色）分区聚类施加到标准化的表达值。 （ 二）选择确定为前列腺癌的候选生物标志物的前10赫尔维结构。对于每个赫尔维元素，相关的赫尔维家族，基因组坐标（NCBI 36/hg18）和赫尔维结构的简要说明中给出。 <a href="https://www.jove.com/files/ftp_upload/50713/50713fig6highres.jpg" target="_blank">点击这里查看大图</a> 。 <img alt="图7" fo:content-width="6in" src="/files/ftp_upload/50713/50713fig7.jpg" width="500px" /> 图7。 </strong&gt; 的赫尔维剧目。（一 ）人类基因组测序结果显示25,000个蛋白质编码基因（外显子，2％）和大量的转座因子，包括200,000的长末端重复序列（LTR）的反转录转座子（赫尔维，8％）。 （ 二）从赫尔维-V2芯片的内容外推和相关表达谱数据（79样品8正常与肿瘤的组织类型始发）表明，赫尔维剧目的三分之一是转录活性。 <a href="https://www.jove.com/files/ftp_upload/50713/50713fig7highres.jpg" target="_blank">点击这里查看大图</a> 。 <img alt="图8" fo:content-width="6in" src="/files/ftp_upload/50713/50713fig8.jpg" width="500px" /> 图8的从芯片的信号的功能的解释 。 （ 一 ）发起人的身份证明和表观遗传控制:U3的负信号（红棒，5&#39;LTR） 与 R-U5正面的信号（蓝色探头，5&#39;LTR）建议U3驱动的转录，通过不同的CpG甲基化（实心黑圈）U3的癌旁正常与肿瘤组织内容的支持。 （二）拼接策略:假定的3.1 kb的信封编码mRNA的表达只在肿瘤采用SD1/SA2拼接位点重叠的探测识别。 *与其他非胎盘组织的比较推断出来。 <a href="https://www.jove.com/files/ftp_upload/50713/50713fig8highres.jpg" target="_blank">点击这里查看大图</a> 。

Watch this Scientific Journal Video about Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer at JoVE.com

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer

人内源性反转录病毒（HERV），它占据了人类基因组中的8％，保留稀缺编码能力，但一十万长末端重复序列（LTRs）。一个自定义的Affymetrix基因芯片的目的是找出个人赫尔维基因的表达，并用在前列腺癌组织的概念，为今后的临床研究证明。

应用生物标志物发现在前列腺癌:个别赫尔维位点表达微阵列鉴定

The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, ...

microarray-based-identification-individual-herv-loci-expression

Research

JoVE Journal

Medicine

16.5K 次观看.  Joint Unit Hospices de Lyon-bioMérieux. 人内源性反转录病毒（HERV），它占据了人类基因组中的8％，保留稀缺编码能力，但一十万长末端重复序列（LTRs）。一个自定义的Affymetrix基因芯片的目的是找出个人赫尔维基因的表达，并用在前列腺癌组织的概念，为今后的临床研究证明。 

视频: Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer

Evaluation of Nanoparticle Uptake in Tumors in Real Time Using Intravital Imaging

Current technologies for tumor imaging, such as ultrasound, MRI, PET and CT, are unable to yield high-resolution images for the assessment of nanoparticle uptake in tumors at the microscopic level1,2,3, highlighting the utility of a suitable xenograft model in which to perform detailed uptake analyses. Here, we use high-resolution intravital imaging to evaluate nanoparticle uptake in human tumor xenografts in a modified, shell-less chicken embryo model. The chicken embryo model is particularly well-suited for these in vivo analyses because it supports the growth of human tumors, is relatively inexpensive and does not require anesthetization or surgery 4,5. Tumor cells form fully vascularized xenografts within 7 days when implanted into the chorioallantoic membrane (CAM) 6. The resulting tumors are visualized by non-invasive real-time, high-resolution imaging that can be maintained for up to 72 hours with little impact on either the host or tumor systems. Nanoparticles with a wide range of sizes and formulations administered distal to the tumor can be visualized and quantified as they flow through the bloodstream, extravasate from leaky tumor vasculature, and accumulate at the tumor site. We describe here the analysis of nanoparticles derived from Cowpea mosaic virus (CPMV) decorated with near-infrared fluorescent dyes and/or polyethylene glycol polymers (PEG) 7, 8, 9,10,11. Upon intravenous administration, these viral nanoparticles are rapidly internalized by endothelial cells, resulting in global labeling of the vasculature both outside and within the tumor7,12. PEGylation of the viral nanoparticles increases their plasma half-life, extends their time in the circulation, and ultimately enhances their accumulation in tumors via the enhanced permeability and retention (EPR) effect 7, 10,11. The rate and extent of accumulation of nanoparticles in a tumor is measured over time using image analysis software. This technique provides a method to both visualize and quantify nanoparticle dynamics in human tumors.

We present a novel approach to quantify nanoparticle localization in the vasculature of human xenografted tumors using dynamic, real-time intravital imaging in an avian embryo model.

使用实时活体成像在肿瘤纳米粒子吸收的评价

Current technologies for tumor imaging, such as ultrasound, MRI, PET and CT, are unable to yield high-resolution images for the assessment of nanoparticle ...

科研

医学

The Use of Reverse Phase Protein Arrays (RPPA) to Explore Protein Expression Variation within Individual Renal Cell Cancers

Currently there is no curative treatment for metastatic clear cell renal cell cancer, the commonest variant of the disease. A key factor in this treatment resistance is thought to be the molecular complexity of the disease 1. Targeted therapy such as the tyrosine kinase inhibitor (TKI)-sunitinib have been utilized, but only 40% of patients will respond, with the overwhelming majority of these patients relapsing within 1 year 2. As such the question of intrinsic and acquired resistance in renal cell cancer patients is highly relevant 3.
In order to study resistance to TKIs, with the ultimate goal of developing effective, personalized treatments, sequential tissue after a specific period of targeted therapy is required, an approach which had proved successful in chronic myeloid leukaemia 4. However the application of such a strategy in renal cell carcinoma is complicated by the high level of both inter- and intratumoral heterogeneity, which is a feature of renal cell carcinoma5,6 as well as other solid tumors 7. Intertumoral heterogeneity due to transcriptomic and genetic differences is well established even in patients with similar presentation, stage and grade of tumor. In addition it is clear that there is great morphological (intratumoral) heterogeneity in RCC, which is likely to represent even greater molecular heterogeneity. Detailed mapping and categorization of RCC tumors by combined morphological analysis and Fuhrman grading allows the selection of representative areas for proteomic analysis.
Protein based analysis of RCC8 is attractive due to its widespread availability in pathology laboratories; however, its application can be problematic due to the limited availability of specific antibodies 9. Due to the dot blot nature of the Reverse Phase Protein Arrays (RPPA), antibody specificity must be pre-validated; as such strict quality control of antibodies used is of paramount importance. Despite this limitation the dot blot format does allow assay miniaturization, allowing for the printing of hundreds of samples onto a single nitrocellulose slide. Printed slides can then be analyzed in a similar fashion to Western analysis with the use of target specific primary antibodies and fluorescently labelled secondary antibodies, allowing for multiplexing. Differential protein expression across all the samples on a slide can then be analyzed simultaneously by comparing the relative level of fluorescence in a more cost-effective and high-throughput manner.

The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers

RPPA enables the protein expression of hundreds of samples, printed on nitrocellulose slides to be interrogated simultaneously, using fluorescently labelled antibodies. This technique has been applied to study the effect of drug treatment heterogeneity within clear cell renal carcinoma.

使用反时相蛋白的阵列（RPPA）探索在个人的肾细胞癌蛋白表达的变化

Currently there is no curative treatment for metastatic clear cell renal cell cancer, the commonest variant of the disease. A key factor in this treatment ...

A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics

We have successfully integrated previously established Intracranial window (ICW) technology 1-4 with intravital 2-photon confocal microscopy to develop a novel platform that allows for direct long-term visualization of tissue structure changes intracranially. Imaging at a single cell resolution in a real-time fashion provides supplementary dynamic information beyond that provided by standard end-point histological analysis, which looks solely at 'snap-shot' cross sections of tissue.
Establishing this intravital imaging technique in fluorescent chimeric mice, we are able to image four fluorescent channels simultaneously. By incorporating fluorescently labeled cells, such as GFP+ bone marrow, it is possible to track the fate of these cells studying their long-term migration, integration and differentiation within tissue. Further integration of a secondary reporter cell, such as an mCherry glioma tumor line, allows for characterization of cell:cell interactions. Structural changes in the tissue microenvironment can be highlighted through the addition of intra-vital dyes and antibodies, for example CD31 tagged antibodies and Dextran molecules.
Moreover, we describe the combination of our ICW imaging model with a small animal micro-irradiator that provides stereotactic irradiation, creating a platform through which the dynamic tissue changes that occur following the administration of ionizing irradiation can be assessed.
Current limitations of our model include penetrance of the microscope, which is limited to a depth of up to 900 &mu;m from the sub cortical surface, limiting imaging to the dorsal axis of the brain. The presence of the skull bone makes the ICW a more challenging technical procedure, compared to the more established and utilized chamber models currently used to study mammary tissue and fat pads 5-7. In addition, the ICW provides many challenges when optimizing the imaging.

A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics

We describe a novel in vivo imaging technique that couples fluorescent chimeric mice with intracranial windows and high-resolution 2-photon microscopy. This imaging platform aids studies of dynamic changes in brain tissue and microvasculature, at a single-cell level, following pathological insults and is adaptable to assess intracranial drug delivery and distribution.

一种新型的高分辨率<em&gt;在体内</em&gt;成像技术研究肿瘤生长及治疗颅内结构的动态响应

We have successfully integrated previously established Intracranial window (ICW) technology 1-4 with intravital 2-photon confocal microscopy to develop a ...

An Orthotopic Murine Model of Human Prostate Cancer Metastasis

Our laboratory has developed a novel orthotopic implantation model of human prostate cancer (PCa). As PCa death is not due to the primary tumor, but rather the formation of distinct metastasis, the ability to effectively model this progression pre-clinically is of high value. In this model, cells are directly implanted into the ventral lobe of the prostate in Balb/c athymic mice, and allowed to progress for 4-6 weeks. At experiment termination, several distinct endpoints can be measured, such as size and molecular characterization of the primary tumor, the presence and quantification of circulating tumor cells in the blood and bone marrow, and formation of metastasis to the lung. In addition to a variety of endpoints, this model provides a picture of a cells ability to invade and escape the primary organ, enter and survive in the circulatory system, and implant and grow in a secondary site. This model has been used effectively to measure metastatic response to both changes in protein expression as well as to response to small molecule therapeutics, in a short turnaround time.

This orthotopic model of human prostate cancer allows for quantification of tumor size, circulating tumor cells, and formation of distinct metastasis to the lung. As cells must escape the primary organ, enter the blood stream, and implant into a secondary site, this model effectively recapitulates the scenario in humans.

人类前列腺癌转移的原位小鼠模型

Our laboratory has developed a novel orthotopic implantation model of  human prostate cancer (PCa). As PCa death is not due to the primary tumor, but  ...

Isolation of Cancer Stem Cells From Human Prostate Cancer Samples

The cancer stem cell (CSC) model has been considerably revisited over the last two decades. During this time CSCs have been identified and directly isolated from human tissues and serially propagated in immunodeficient mice, typically through antibody labeling of subpopulations of cells and fractionation by flow cytometry. However, the unique clinical features of prostate cancer have considerably limited the study of prostate CSCs from fresh human tumor samples. We recently reported the isolation of prostate CSCs directly from human tissues by virtue of their HLA class I (HLAI)-negative phenotype. Prostate cancer cells are harvested from surgical specimens and mechanically dissociated. A cell suspension is generated and labeled with fluorescently conjugated HLAI and stromal antibodies. Subpopulations of HLAI-negative cells are finally isolated using a flow cytometer. The principal limitation of this protocol is the frequently microscopic and multifocal nature of primary cancer in prostatectomy specimens. Nonetheless, isolated live prostate CSCs are suitable for molecular characterization and functional validation by transplantation in immunodeficient mice.

The isolation of cancer stem cells (CSCs) directly from human tissues is requisite for their biological characterization. This manuscript describes a methodology for the isolation of prostate CSCs from human tissues, while also providing tips on troubleshooting difficult steps.

癌症干细胞从人类前列腺癌样本隔离

The cancer stem cell (CSC) model has been considerably revisited over the last two decades. During this time CSCs have been identified and directly ...

miRNA Expression Analyses in Prostate Cancer Clinical Tissues

A critical challenge in prostate cancer (PCa) clinical management is posed by the inadequacy of currently used biomarkers for disease screening, diagnosis, prognosis and treatment. In recent years, microRNAs (miRNAs) have emerged as promising alternate biomarkers for prostate cancer diagnosis and prognosis. However, the development of miRNAs as effective biomarkers for prostate cancer heavily relies on their accurate detection in clinical tissues. miRNA analyses in prostate cancer clinical specimens is often challenging owing to tumor heterogeneity, sampling errors, stromal contamination etc. The goal of this article is to describe a simplified workflow for miRNA analyses in archived FFPE or fresh frozen prostate cancer clinical specimens using a combination of quantitative real-time PCR (RT-PCR) and in situ hybridization (ISH). Within this workflow, we optimize the existing methodologies for miRNA extraction from FFPE and frozen prostate tissues and expression analyses by Taqman-probe based miRNA RT-PCR. In addition, we describe an optimized method for ISH analyses formiRNA detection in prostate tissues using locked nucleic acid (LNA)- based probes. Our optimized miRNA ISH protocol can be applied to prostate cancer tissue slides or prostate cancer tissue microarrays (TMA).

Here we describe a simplified protocol for microRNA (miRNA) expression analyses in archived Formalin-Fixed, Paraffin-Embedded (FFPE) or fresh frozen prostate cancer (PCa) clinical tissues employing quantitative real-time PCR (RT-PCR) and in situ hybridization (ISH).

在前列腺癌的临床组织中miRNA的表达分析

A critical challenge in prostate cancer (PCa) clinical management is posed by the inadequacy of currently used biomarkers for disease screening, ...

Generation of Prostate Cancer Patient Derived Xenograft Models from Circulating Tumor Cells

Patient derived xenograft (PDX) models are gaining popularity in cancer research and are used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. Circulating tumor cells (CTC) play a critical role in tumor metastasis and have been isolated from patients with several tumor types. Recently, CTCs have been used to generate PDX experimental models of breast and prostate cancer. This manuscript details the method for the generation of prostate cancer PDX models from CTCs developed by our group. Advantages of this method over conventional PDX models include independence from surgical sample collection and generating experimental models at various disease stages. Density gradient centrifugation followed by red blood cell lysis and flow cytometry depletion of CD45 positive mononuclear cells is used to enrich CTCs from peripheral blood samples collected from patients with metastatic disease. The CTCs are then injected into immunocompromised mice; subsequently generated xenografts can be used for functional studies or harvested for molecular characterization. The primary limitation of this method is the negative selection method used for CTC enrichment. Despite this limitation, the generation of PDX models from CTCs provides a novel experimental model to be applied to prostate cancer research.

This manuscript details a method used to generate prostate cancer patient derived xenografts (PDXs) from circulating tumor cells (CTCs). The generation of PDX models from CTCs provides an alternative experimental model to study prostate cancer; the most commonly diagnosed tumor and a frequent cause of death from cancer in men.

前列腺癌患者产生派生异种移植模型从循环肿瘤细胞

Patient derived xenograft (PDX) models are gaining popularity in cancer research and are used for preclinical drug evaluation, biomarker identification, ...

Clinicopathological Analysis of miRNA Expression in Breast Cancer Tissues by Using miRNA In Situ Hybridization

In this article, we describe a detailed protocol for miRNA detection in breast cancer tissue using in situ hybridization with a digoxigenin-labelled LNA (Locked Nucleic Acid) probe. The probe was recognized by anti-DIG alkaline phosphatase antibodies and later developed using alkaline phosphatase substrate producing fluorescence signals. Here we utilized miRNA in situ hybridization (MISH) technique to analyze expression of miR-489 in tissues from breast cancer patients. This technique can detect the localization of miRNA of interest in individual tissue samples. This technique can be used to compare the expression of desired miRNA in tumor tissue with that in adjacent normal tissue and to identify the specific structures responsible for expressing this miRNA. This technique can be very useful in answering certain clinical questions, such as role of specific miRNA in the development of cancer. Our results indicate that mammary epithelial cells express significantly higher levels of miR-489 than adjacent tumor cells.

Clinicopathological Analysis of miRNA Expression in Breast Cancer Tissues by Using miRNA In Situ Hybridization

Here we present a protocol to detect miRNA expression in breast cancer patient samples using miRNA in situ hybridization.

利用miRNA的miRNA表达的临床病理分析乳腺癌组织<em&gt;原位</em&gt;杂交

In this article, we describe a detailed protocol for miRNA detection in breast cancer tissue using in situ hybridization with a digoxigenin-labelled LNA ...

Pre-clinical Orthotopic Murine Model of Human Prostate Cancer

To study the multifaceted biology of prostate cancer, pre-clinical in vivo models offer a range of options to uncover critical biological information about this disease. The human orthotopic prostate cancer xenograft mouse model provides a useful alternative approach for understanding the specific interactions between genetically and molecularly altered tumor cells, their organ microenvironment, and for evaluation of efficacy of therapeutic regimens. This is a well characterized model designed to study the molecular events of primary tumor development and it recapitulates the early events in the metastatic cascade prior to embolism and entry of tumor cells into the circulation. Thus it allows elucidation of molecular mechanisms underlying the initial phase of metastatic disease. In addition, this model can annotate drug targets of clinical relevance and is a valuable tool to study prostate cancer progression. In this manuscript we describe a detailed procedure to establish a human orthotopic prostate cancer xenograft mouse model.

Prostate cancer is the second most common cause of cancer-related deaths in the United States. An orthotopic cancer model provides a useful approach to understand the biology of prostate cancer and to evaluate the efficacy of therapeutic regimens. This protocol describes detailed steps necessary to establish an orthotopic prostate cancer mouse model.

人前列腺癌的临床前原位小鼠模型

To study the multifaceted biology of prostate cancer, pre-clinical in vivo models offer a range of options to uncover critical biological information ...

Use of Magnetic Resonance Imaging and Biopsy Data to Guide Sampling Procedures for Prostate Cancer Biobanking

Previous methods for biobanking prostate tissue, following radical prostatectomy, generally involved random sampling. In order to increase efficiency, and enable a greater range of downstream applications, a more targeted method of sampling prostate tissue was developed. Here we use both magnetic resonance imaging (MRI) and biopsy data to target specific areas of the organ for sampling. The method involves use of a previously published prostate slicing device which removes a 5 mm transverse slice from a predetermined region of the prostate, followed by the removal of 6 mm punch biopsies from predetermined areas of this slice. These samples can be stored frozen or fixed for biobanking purposes, or used fresh immediately with 70% confidence of tumor content, as compared with 10% confidence from the random sampling approach. This enables the use of all standard downstream techniques such as genomics, proteomics or histological work, but also work that requires fresh tissue such as live tissue imaging or ex vivo culture.

This method involves utilization of clinical diagnostic data for prostate cancer patients in order to guide sampling procedures, when biobanking tissue following radical prostatectomy. This overcomes issues with previously published methods around efficiency and availability of fresh tissue for a wider range of downstream applications.

使用磁共振成像和活检数据指导前列腺癌生物库的取样程序

Previous methods for biobanking prostate tissue, following radical prostatectomy, generally involved random sampling. In order to increase efficiency, and ...

应用生物标志物发现在前列腺癌:个别赫尔维位点表达微阵列鉴定

摘要

探索更多视频

此视频中的章节