该研究是由美国佛罗里达州的班克黑德 - 科莱科技团队格兰特（2BT03），健康/美国国家癌症研究所（1R21CA164322-01）和莫菲特癌症中心的团队科学格兰特全国学院的国家。这项工作已部分由转化研究核心设施的H. Lee Moffitt癌症中心和研究所，一个NCI指定的综合癌症中心（P30-CA076292）的支持。获得原代细胞成为可能通过总癌症护理协议在莫菲特癌症中心。

利用从如下所述批准了莫菲特的机构审查委员会和临床试验的H. Lee Moffitt癌症中心和研究所进行MCC＃14745下进行活检衍生人体细胞。 1.从排序骨髓穿刺MM细胞<ol><li>收集从患者肝素钠注射骨髓抽吸物（20毫升）中。 </li><li> （1用无菌PBS 1）在一个无菌的水性介质离心梯度，在400×g离心30分钟，在环境温度下通过离心稀释的骨髓分离的单核细胞。 </li><li>收集的接口，其中包含单核细胞。用冷PBS洗涤细胞，并用血球或自动细胞计数计数，用台盼蓝测定可行性。 </li><li>准备用Wright-Giemsa染色薄层细胞制剂滑板10和染色，以评估浆细胞百分比11。 </li><li>计算基于要使用的CD138珠的量的细胞和浆细胞百分比的数目。如果起始样品是小于20％的浆细胞，然后重新悬浮使用90微升的分离缓冲液和10微升每5×10 6个细胞的CD138珠细胞。如果起始样品是20％以上的浆细胞，重悬于用80微升的分离缓冲液和20μl的每1×10 7个细胞的CD138珠。 </li><li>孵育细胞珠子在4℃下进行15分钟。 </li><li>通过一个35微米的过滤器细胞加入到预润湿分离放置在磁场分离器（LS）柱（见材料清单）。 </li><li>从磁体删除列。通过洗涤塔3次用1毫升分离缓冲液收集CD138选定单元。 </li><li>评估CD138富集与另一染色薄层细胞制剂滑动10。 </li><li>从骨髓活检过滤血浆中获得来自每个患者用0.22μm的注射器过滤器。用新鲜血浆来自同一患者的CD138 +细胞。 </li><li>通过补充的RPMI-1640，用10％热灭活胎牛血清，10％患者的血浆和1％青霉素 - 链霉素准备媒体实验。 </li><li>收集流过所述选择（CD138-）的，并按照古典粘合方法12选择为骨髓间充质细胞（BMSC）。因为这个过程需要几个星期之前的BMSCs准备好被使用时，就必须具有骨髓基质细胞准备从以前患者或健康供体。 </li></ol>在板2种子细胞（使用手动多道移液器） <ol><li>使用多孔板（384或1536）用黑色壁和透明平底，用于光学应用和细胞培养优先一是优化。 </li><li>共培养骨髓基质细胞与MM细胞中任一I型胶原或基底膜基质，然而，内皮需要基底膜基质。 </li><li>保持每个细胞类型的最后密度在以下范围:3×10 5细胞/ ml的对MM细胞系，将2×10 5细胞/毫升的HUVECs或骨髓基质干细胞，和2×10 6个细胞/ ml的对源自患者的MM细胞。 注意:这些密度的实验优化的结果，以允许尽可能高的图像质量和尽可能长的成像时间，同时保持生物相关的测定。 MM细胞系接种在较低的密度比由于其较快的复制速率和更大的尺寸主MM细胞。 </li><li>共培养初级MM细胞与骨髓基质干细胞: <ol><li>制备预混合介质由20微升10×MEM，20微升去离子的H 2 O为10微升7.5％的碳酸氢钠溶液和50微升1×的RPMI 1640和存储的100微升等分试样在4℃下。 </li><li>在播种与MM细胞平板的时间，混合的预混合介质的等分试样用150微升3.1毫克/毫升牛I型胶原，以250微升的最终体积。 </li><li>再停赛结束加入50μl细胞在RPMI 1640在六次最终希望的密度。 </li><li>混合细胞悬液与胶原蛋白的组合，以创建一个使用吸管P200 300微升的最终体积。 </li><li>使用手动或中继器移液管，沉积最终电池的8微升滴/基质混合物中的每个的中心孔在384孔板中，或在1536孔板（参见空间排列的一例步骤2.6每孔加入2μl井）。 </li><li>离心机板在500×g离心2分钟，以集中在成像期间所有细胞中的相同焦平面。 </li><li>离开板在恒温箱（5％CO 2，37℃）1小时，对于凝胶聚合。 </li><li>添加80μl的补充的生长培养基（RPMI-1640,10％FBS，HI，10％患者来源血浆，1％P / S），以每孔在384孔板，或8微升在1536孔板中。 </li><li>离开板O / N中孵育箱（5％CO 2，37℃）为基质的粘附到板的底部。 </li></ol></li><li>联合立方米lture原MM细胞与内皮细胞的: <ol><li>从-80℃转印基底膜基质与冰水桶解冻。 </li><li>计数并在一个单独的管重悬的原代细胞和内皮细胞在RPMI-1640介质在4倍的最终密度，每。 </li><li>混合患者细胞和内皮细胞体积在1:1的比例。 </li><li>一旦基底膜基质解冻，但仍然未聚合，混合1:1与来自前一步骤的细胞混合物。 </li><li>种子液滴与细胞基质混合物在每个的中心适当体积以及（8微升用于384孔板和2μl为1536孔板，参见井空间排列的一例步骤2.6）。 </li><li>离心机板在500×g离心10分钟。 </li><li>广场板块在培养箱（5％CO 2，37℃）1小时矩阵聚合。 </li><li>添加的生长培养基（RPMI-1640添加有10％FBS，10％患者的血浆及1％P / S），以每孔（80微升为384孔板中，8微升1,536孔板）。 </li><li>离开板O / N中孵育箱（5％CO 2，37℃）的HUVECs到板的底部粘合性。 </li></ol></li><li>种子384孔板中。 图3示出了播种的典型空间分布。 <ol><li>作为药物被测试的启动以及B2，种子尽可能多的列。在图3的例子中，使用7种药物。 </li><li>要使用重复播​​种多次浓度。在图3的例子中，使用5个浓度。 </li><li>种子四个井控制的情况。 </li><li>重复步骤2.6.1和2.6.2的第二个重复。 </li><li>重复步骤2.6.1至2.6.4每个病人样本中板进行测试。 </li><li>在两行孔中，每一个与尽可能多井种子一个MM细胞系作为药物进行测试（一式两份）。每个孔将每种药物的最高浓度进行处理，以确保所使用的股票有足够POTEN立方码（参见图3为实施例）。 </li><li>种子两口井具有一个MM细胞系，作为实验条件，如台式培养箱的正常运作，生长培养基等控制。 </li></ol></li></ol> 3.播种在板电池（使用自动移液器） 注意:此系列步骤种子的384孔板使用机器人移液器。该板的设计示于补充图1中，其中初级MM细胞在两个重复测试对31个不同的药物的小组在五个不同的浓度，再加上负对照。的细胞系也接种作为阳性对照药物疗效评估，并在最高浓度测试对所有31个药品，在两个重复。所提供的文件是为特定的品牌和型号（见材料表），但该算法可以适应任何机器人移液器。 <ol><li>原MM细胞共培养s的骨髓基质干细胞: <ol><li>制备15毫升管组成的240微升10×MEM，240微升去离子的H 2 O为120微升7.5％的碳酸氢钠溶液，600微升1×的RPMI 1640和1.8毫升3.1毫克/毫升的牛I型胶原蛋白标签管为" 预混为CD138 +"。置于冰上直至使用。 </li><li>制备1.5 ml的管由50微升10×MEM，50微升去离子的H 2 O为25微升7.5％的碳酸氢钠溶液，125微升1×的RPMI 1640和375微升3.1毫克/毫升牛I型胶原蛋白标签管为" 预混对于细胞系 "。置于冰上直至使用。 </li><li>重悬300μl的CD138 +细胞在RPMI 1640在六次最终希望的密度。重悬300μl的BMSC细胞在RPMI 1640中在六次最终希望的密度。在1.5毫升管和标签"CD138 +"组合两个卷在一起。放置在培养箱中直至使用。 </li><li>重悬60微升在RPMI 1640细胞系在六次最终希望的密度。重悬60微升的BMSC细胞在RPMI 1640中在六次最终希望的密度。在1.5毫升管和标签" 细胞 "都混在一起卷。放置在培养箱中直至使用。 </li><li>使用装有机器人移液器软件，加载第一个脚本文件，"cell_seedingPt47.PGM"。放置一个200μl的移液管尖中，微量滴定板，和无菌384孔平板中的站A，B和E分别机器人。 </li><li>混合管中的内容" 预混为CD138 +"和"CD138 +"。传送将1.5ml其内容到孔＃1的微量滴定板的。放置在冰上剩余体积的管。启动该程序。机器人将种子在第一176孔中的384孔板（11最左边的列），然后暂停。传输管的其余在冰上孔＃微量滴定​​板的2。恢复计划。该机器人将种子剩余144孔中的384孔板和停顿。 </li><li>混合管中的内容" 预混对于细胞系 "和" 细胞系 "和传送内容到孔＃微量滴定板的3。恢复计划。机器人将种子剩余64孔中的384孔板的。 </li><li>放置384孔板在离心机在500×g离心10分钟，4℃。转印板孵化器（5％CO 2，37℃）1小时为胶原聚合。 </li><li>加载第二个脚本文件，"media_layer.PGM"。放置120微升枪头盒，试剂贮存器与31毫升的RPMI-1640的补充有10％FBS，10％患者的血浆及1％P / S和384孔板与细胞转化为站A，B和E，分别。运行该程序。机器人将81微升媒体传送到每个孔中。一旦完成，转移384孔板到孵化器，并允许基质粘附到基材O / N。 </li></ol></li></ol&gt; 4.药物制备及板的下药（使用手动多道移液器） <ol><li>制备类似的模板图3中为了便于添加药物至井的过程和减少混淆的机会。 </li><li>准备，在96孔板中，每种药物的连续稀释到在板进行测试，例如，对于使用了3​​倍稀释5个浓度: <ol><li>添加120微升的药物在10倍于最高浓度所需的浓度良好。例如，使用500μM的美法仑，如果浓度最高的细胞将在板暴露将是50微米。 </li><li>添加80μl的生长培养基（RPMI补加了10％FBS，10％患者来源血浆和1％青霉素/链霉素（P / S））的四个后续井。 </li><li>转移40微升由第一井向第二和混合，以120微升的总体积在1/3第一阱的药物浓度，或167微米。 </li><li>重复步骤4.2.3至剩余孔（ 如，传输从第二40微升至第三，混合，然后转移40微升从第三到第四， 等等 ）。 </li></ol></li><li>从含有很好地在细胞板的相应孔的各药物传送8微升。含井每种药物应该有足够量的10口井的单元板。在图3的例子中，各药物浓度被添加到6个不同的孔中，除了最高浓度，将其加入8孔。 </li><li>添加8微升生长培养基（RPMI补加了10％FBS，10％患者来源血浆和1％P / S），以对照孔。 </li><li>地方细胞在显微镜下，只要准备好，然后打开台式孵化。 </li></ol>板5.药物制备及下药（使用自动移液器） <ol><li>从http://www.i-genics.com/Jove2014Silva/Precision XS网络下载机器人移液器脚本文件les.zip </li><li>在自动移液器用户界面加载脚本"media_layer_DRUGPLATE.PGM"。放置一个120μl的移液管尖中，贮存器，用21毫升的RPMI-1640的补充有10％FBS，10％患者的血浆及1％P / S和一个空的384孔板在站A，B和E分别。运行程序，机器人移液器将添加30微升培养基到所有孔中，在384孔板中。 </li><li>以下从补充图2的模板以20×最大浓度添加200μl的药物与微量滴定板的每个孔中。这种设置可容纳多达31个药品。向对照孔（CTRL），添加的RPMI-1640添加有10％FBS，10％患者的血浆及1％P / S。 </li><li>放置一个120μl的移液管尖中，微量滴定板用药物在20X浓度，和384以及与媒体（来自步骤5.1）在站A，B和C，分别。加载程序"drug_plate.PGM"。机器人移液器将创建一个连续稀释的1:3，以下在参考图1中的空间分布。 </li><li>放置一个120μl的移液管尖中，在384孔板药物稀释液（来自步骤5.3）和384孔板与细胞（来自步骤3.1.9）插入站A，B和C，分别。加载和运行程序"drug_add.PGM"。机器人移液器将在药物板在细胞板转移8微升药物从每个孔中与其对应。一旦完成，一旦转移单元板到数字显微镜的孵化器成为可能。 </li></ol> 6.成像板细胞注意:以下过程适用于EVOS汽车FL显微镜，但可以很容易地适应其他机动阶段显微镜与台式孵化孵化器或嵌入式显微镜。 <ol><li>清洁台式孵化器的内部用乙醇湿纸巾，小心地取出板的盖子，同时将INC。的盖子ubator。 </li><li>按照软件的步骤添加的信标。这是用来指标为感兴趣区域的术语，也可以连续地在实验（详见软件用户指南）期间成像。 </li><li>使用5倍或10倍的放大倍率目标。确保重点是类似于图2:MM细胞出现由暗环骨髓基质干细胞和内皮细胞或勉强可见包围的明亮磁盘。一些主要的MM细胞是非常小的，因此一个微调可能需要找到最佳聚焦。 </li><li>调整之间10-30分钟，并在至少96小时的持续时间的获取间隔。而采集之间较长的时间间隔是可以接受的，在45分钟以上的时间间隔可能显著降低存活率的测定精度。 </li><li>配置软件，使得每个孔的图像被存储在名为信标1，信标2， 等等。如果使用的机器人移液器单独的文件中，设置信标中所描述的顺序补充图3。 </li><li>确保有足够的水在孵化加湿器和气体，从而使细胞将处于最佳条件。 </li><li>在实验完成后，复制包含所述图像，以将运行分析的计算机的文件夹。 </li></ol> 7.定量药敏注意:下面的说明书中使用利用计算机集群的图像分析中，由于多孔板的在个人计算机中的分析是非常耗时。 <ol><li>从美国国立卫生研究院的网站下载软件的ImageJ:http://imagej.nih.gov/ij/ </li><li>在http://www.i-genics.com/Jove2014Silva/下载脚本和插件</li><li>按照http://www.i-genics.com/Jove2014Silva/UserGuide.pdf说明运行数字图像分析软件。结果应该是一个名为Results.csv含定期为EAC生存能力测量电子表格ħ以及在该板的实验（ 即，96小时）的持续时间。 </li><li>如果使用手动多道移液器，执行以下步骤。 <ol><li>下载文件http://www.i-genics.com/Jove2014Silva/ExperimentalDesign.txt并修改它以匹配盘的在步骤3.1中定义的布局（ 例如， 图3）。 </li><li>下载软件http://www.i-genics.com/Jove2014Silva/Evos384.jar并利用在步骤5.3和5.4作为输入参数创建的文件运行它。其结果将是一个文件夹的名称的报告包含多个电子表格，每个分组的结果为一特定的药物。 </li><li>在电子表格模板http://www.i-genics.com/Jove2014Silva/GraphPadAnalysisPT.pzfx复制和粘贴内容 注意:结果应该是图表，如在图4中描述的，代表样本的敏感性，以不同的药物作为药物浓度和暴露时间的函数。 </li> &lt;/ OL&gt; </li><li>如果使用自动移液器，执行以下步骤。 <ol><li>从http://www.i-genics.com/Jove2014Silva/Robotic模板Files.zip下载从机器人移液器下载脚本文件模板文件和目录中提取文件。 </li><li>修改文件DrugList.csv根据药物在板与细胞中的列表和最高药物浓度。遵循参考图2的布局。 </li><li>运行程序BuildExperimentalDesign.java作为传递参数包含从步骤7.3步骤7.5.1提取的文件和文件Results.csv的文件夹。该结果应该是两个文件夹的名字和MM1_S PtSample。第一个包含各孔（药物和浓度）为细胞系的阳性对照的描述。第二个是包含相同的信息，但对于板接种患者的细胞的部分。 </li><li>文件Results.csv复制到每个在步骤7.5.3中创建的目录。下载软件http://www.i-genics.com/Jove2014Silva/Evos384.jar和使用步骤7.5.3为这两个文件夹下创建的文件运行它。其结果将是在每个在7.5.3中创建的文件夹的文件夹名称的报告。报告文件夹中包含多个电子表格，每个分组结果为特定的药物。 </li><li>运行程序BuildGraphPadFile.java并作为参数传递含有步骤7.5.1提取文件的文件夹和文件从步骤7.3 Results.csv。其结果将是通过控制含的剂量响应曲线的每个的31药物的GraphPad文件，和归一化。每个图表将包含5的药物浓度对于主MM细胞和一种浓度为阳性细胞系的控制。 </li></ol></li></ol>

<ol>
	<li>Salmon, S. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitation+of+differential+sensitivity+of+human-tumor+stem+cells+to+anticancer+drugs.">Quantitation of differential sensitivity of human-tumor stem cells to anticancer drugs.</a> N Engl J Med. 298, 1321-1327 (1978).</li><li>Suggitt, M., Bibby, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=50+years+of+preclinical+anticancer+drug+screening:+empirical+to+target-driven+approaches.">50 years of preclinical anticancer drug screening: empirical to target-driven approaches.</a> Clin Cancer Res. 11, 971-981 (2005).</li><li>Kirshner, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+unique+three-dimensional+model+for+evaluating+the+impact+of+therapy+on+multiple+myeloma.">A unique three-dimensional model for evaluating the impact of therapy on multiple myeloma.</a> Blood. 112, 2935-2945 (2008).</li><li>Durie, B. G., Jacobson, J., Barlogie, B., Crowley, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Magnitude+of+response+with+myeloma+frontline+therapy+does+not+predict+outcome:+importance+of+time+to+progression+in+southwest+oncology+group+chemotherapy+trials.">Magnitude of response with myeloma frontline therapy does not predict outcome: importance of time to progression in southwest oncology group chemotherapy trials.</a> J Clin Oncol. 22, 1857-1863 (2004).</li><li>Harousseau, J. L., Attal, M., Avet-Loiseau, 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+role+of+complete+response+in+multiple+myeloma.">The role of complete response in multiple myeloma.</a> Blood. 114, 3139-3146 (2009).</li><li>Khin, Z. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+preclinical+assay+for+chemosensitivity+in+multiple+myeloma.">A preclinical assay for chemosensitivity in multiple myeloma.</a> Cancer Res. 74, 56-67 (2014).</li><li>Misund, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+method+for+measurement+of+drug+sensitivity+of+myeloma+cells+co-cultured+with+bone+marrow+stromal+cells.">A method for measurement of drug sensitivity of myeloma cells co-cultured with bone marrow stromal cells.</a> J Biomol Screen. 18, 637-646 (2013).</li><li>Ramasamy, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence-based+experimental+model+to+evaluate+the+concomitant+effect+of+drugs+on+the+tumour+microenvironment+and+cancer+cells.">Fluorescence-based experimental model to evaluate the concomitant effect of drugs on the tumour microenvironment and cancer cells.</a> Br J Haematol. 157, 564-579 (2012).</li><li>McMillin, D. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumor+cell-specific+bioluminescence+platform+to+identify+stroma-induced+changes+to+anticancer+drug+activity.">Tumor cell-specific bioluminescence platform to identify stroma-induced changes to anticancer drug activity.</a> Nat Med. 16, 483-489 (2010).</li><li>Koh, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preparation+of+cells+for+microscopy+using+cytospin.">Preparation of cells for microscopy using cytospin.</a> Methods Enzymol. 533, 235-240 (2013).</li><li>Al-Quran, S. Z., Yang, L., Magill, J. M., Braylan, R. C., Douglas-Nikitin, V. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assessment+of+bone+marrow+plasma+cell+infiltrates+in+multiple+myeloma:+the+added+value+of+CD138+immunohistochemistry.">Assessment of bone marrow plasma cell infiltrates in multiple myeloma: the added value of CD138 immunohistochemistry.</a> Hum Pathol. 38, 1779-1787 (2007).</li><li>Najar, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mesenchymal+stromal+cells+promote+or+suppress+the+proliferation+of+T+lymphocytes+from+cord+blood+and+peripheral+blood:+the+importance+of+low+cell+ratio+and+role+of+interleukin-6.">Mesenchymal stromal cells promote or suppress the proliferation of T lymphocytes from cord blood and peripheral blood: the importance of low cell ratio and role of interleukin-6.</a> Cytotherapy. 11, 570-583 (2009).</li><li>Scott, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phase+i+trialist.">Phase i trialist.</a> Lancet Oncol. 13, 236 (2012).</li></ol>

The authors have no conflict of interest to disclose.

总之，这是一个强大的和高通量的方法来量化主要的MM细胞的药物体外药效学的敏感性在重建骨髓。这个协议中的关键步骤是该井的正确播种和适当聚焦（ 见图2预期的结果）:确保MM和基质细胞是均匀分布的，即基质细胞粘附到井的底部，即所有的MM细胞在同一焦平面，并且MM细胞具有明亮的圆盘由一个暗环所包围的部分。 在不适当的情况下，播种（ ?...

该方法的目标是多发性骨髓瘤（MM）的药物敏感性初级细胞表征的试剂离体面板，尽可能接近生理条件，并且以足够的精度，这些结果可以被用于识别化疗耐药子在肿瘤负荷，并最终人口，参数化设计，估计临床反应的计算模型。 计算模型是有力工具分析复杂系统，如癌症宿主治疗的相互作用。然而，模型是仅作为数据用于参数它们作为良好。不幸的是，在文献中可获得大多数数据不能用在目前的形式来参数这样的模型，因为它们常常是在相互排斥的实验条件下获得的。因此，新的实验，通常需要以获得该组所需要的实验参数的目标。大多数存活测定，但是，是破坏性的，第我们限于少量的时间点，通常只有一个。这极大障碍敏感性测定法的使用来参数计算模型，因为这样的实验未能提供对系统的时间动态信息。这是原发性癌细胞，这往往限于少数百万每个样品，并有活检后很短的寿命，因此限制了可用的实验条件下的数量，尤其如此。此外，大多数存活测定需要来自非癌症（基质）细胞在量化，这将增加额外的工作来的协议时的癌症的分离，进一步扰乱细胞，并限制了可被执行的实验数。 40年前，鲑鱼和合作者1中提出其著名的体外集落形成试验对肿瘤细胞的化疗敏感性的评估。不幸的是这个实验发现混杂的成功是由于小数倍的MYE洛马（MM）的患者样本均能够形成对照条件下的菌落:据估计，只有一小亚组的0.001％至MM细胞的0.1％是能复制的，被称为多发性骨髓瘤干细胞2。这显著限于该测定的成功率，而且可以在同一时间进行测试的药物的数量，即使是在更近的模型3。这个问题更重要，现在，当MM剂（标准或实验）比四十年前更多了。 这些早期试验中的主要限制是其​​对分输出:要么患者是"敏感"或"抗性"，以一个特定的药物。没有任何信息是关于敏感性肿瘤人口和异质性程度。因此，患者的小亚群快速增长的抗性细胞将被归类为"敏感"，以治疗，但会复发不久，因而不奔从EFIT治疗。定响应的癌症患者4,5的总生存率（OS）的持续时间的重要性，显然这些测定如何不能够正确估计操作系统一致。 为了克服这些限制，并能够生成患者特异性的计算模型，将估计的个性化的临床反应的药物的一个面板上，我们已经开发出的多发性骨髓瘤（MM）细胞系，非破坏性测试药物敏感性的方法和初级MM细胞在离体重建骨髓微环境，包括细胞外基质和基质6。该测定中，然而，有依靠一个特定的商业微流体滑动，其尺寸和成本的限制，可以在一个给定的设备来进行一次实验或药物的数量的限制。 在此描述的系统扩展这种原始检测到高-throughput器官剂量-反应平台，用于在体外筛选药物，基于数字图像分析算法，以非破坏性地量化细胞活力。每个孔在384或1536孔板是3D重建骨髓微环境，其中包括初级MM细胞，细胞外基质，和患者来源基质和生长因子。在线显微镜和数字图像分析被用于检测在不同的药物浓度，其用于产生剂量反应表面的细胞死亡的事件。从体外数据，建立数学模型确定在患者的肿瘤负荷的大小和亚群的敏感性，并可以用来模拟如何肿瘤会响应在生理条件的药物（多个）在临床治疗方案6（ 图1）。 该平台的主要创新点有:（一）少数必需的癌细胞（1000-10000元药concent比）; （二）在生理条件下的药效（细胞外基质，基质，病人衍生的生长因子）的评估; （c）约生存能力标记7，因为只有亮场成像无毒性的情况下，因此，不需要转染细胞与荧光8或生物发光9; （四）连续成像提供药物的效果的浓度和暴露时间（药效学）的函数;和（e） 在体外和计算演化模型之间的整合，来估计临床结果6（Silva 等，准备中）。 允许所述数字图像分析算法来从基质细胞辨别癌症的关键因素是其不同的亲和力的井底:MM细胞不附着，并保持在悬浮液中的基质，而基质细胞粘附的底部好，再舒展。 这种分离发生，即使MM和基质一再接种在同一时间，并在孵化的O / N的过程发生。该板的在离心纺丝向下以下播种进一步加速了这一过程。其结果是，MM细胞出现在图像如由暗环围绕圆亮磁盘中，而基质保持低调和暗的阴影（ 图2）。因此，在目前形式的测定法是最适合于非粘附癌细胞，尽管该算法中调整可以基于其它形态学特征，例如大小和形状来完成，以独立的癌症和基质。在这个协议中，我们描述了两种类型的细胞外基质（胶原和基底膜基质），以及两种类型的共培养物，与（骨髓间充质干细胞）的BMSC和脐静脉内皮细胞，代表骨髓的间质和血管周围龛分别。 使用384孔板，5个浓度每药物和两次重复，我们能够TES牛逼多达31种不同的药物与单个患者的样本。在1536孔板这个数目是127。 图3示出了目前用于人工细胞接种的布局，而补充图1表示使用机器人移液器的最佳分配。在从图3的设计中，每个384孔板可以携带与7种不同的药物，或一个患者样品与21的药物测试3的患者样品。每种药物由5个浓度表示，并且每个条件被接种在重复。 4对照孔（无药物加）接种为每组7药物（如井36-39，126-129和200-203）。为了确保使用的药物的效力，人类骨髓瘤细胞系（ 例如，H929或MM1.S）也是播种，并且在每个使用的（孔76-89）的药物的最高浓度麻醉中重复。阳性细胞系控制可确保所使用的药物具有足够的效力，因为它们的剂量响应曲线具有可比性的交流罗斯的实验。两口井接种与骨髓瘤细胞系作为对照的环境条件，换言之，以检测在台式培养箱可能出现的问题在成像期间（井75和90）。孔的枚举如下之字形图案，以减少所涉及的显微镜的电动载物台，从而减少采集时间，并降低了设备的磨损的距离。

<table><tbody><tr><td>EVOS FL AUTO</td><td>AMG</td><td>AMAFD1000 + AMC1000</td><td>Digital microscope equipped with motorized stage and bench top incubator.</td></tr><tr><td>384-well plate CellBind</td><td>CORNING</td><td>CLS3683 SIGMA</td><td>Corning CellBIND 384 well plates&lt;br/&gt; 384 well plate, polystyrene, CellBIND surface, sterile, clear flat bottom, black, w/lid</td></tr><tr><td>1,536-well plate CellBind</td><td>CORNING</td><td>CLS3832 ALDRICH</td><td>Corning 1,536 well plates, low base, surface treatment CellBIND, sterile</td></tr><tr><td>Ficoll-Paque Plus&amp;nbsp;</td><td>GE Healthcare</td><td>GE17-1440-02 SIGMA</td><td>For &lt;em&gt;in vitro&lt;/em&gt; isolation of lymphocytes from human peripheral blood.</td></tr><tr><td>CD138 magnetic beads</td><td>Miltenyi&amp;nbsp;</td><td>130-051-301</td><td>Antibody conjugated magnetic beads for selection of CD138+ cells.</td></tr><tr><td>LS columns</td><td>Miltenyi&amp;nbsp;</td><td>&amp;nbsp;130-042-401</td><td>Column for separation of cells.</td></tr><tr><td>MidiMACS Separator</td><td>Miltenyi&amp;nbsp;</td><td>130-042-302</td><td>Magnet for separation column.</td></tr><tr><td>Matrigel</td><td>Sigma-Aldrich</td><td>E6909 SIGMA</td><td>ECM Gel from Engelbreth-Holm-Swarm murine sarcoma</td></tr><tr><td>Getrex</td><td>Life Technologies</td><td>A1413201</td><td>LDEV-Free Reduced Growth Factor Basement Membrane Matrix</td></tr><tr><td>HUVEC</td><td>Life Technologies</td><td>C-003-25P-B</td><td>Human Umbilical Vein Endothelial Cells (HUVEC )</td></tr><tr><td>RPMI-1640 media</td><td>GIBCO</td><td>11875-093</td><td>RPMI 1640 Medium + L-Glutamine + Phenol Red</td></tr><tr><td>FBS Heat inactivated</td><td>GIBCO</td><td>10082-147</td><td>Fetal Bovine Serum, certified, heat inactivated, US origin</td></tr><tr><td>3.1 mg/ml Bovine collagen type I</td><td>Advanced Biomatrix</td><td>5005-B</td><td>Bovine Collagen Solution, Type I, 3 mg/ml, 100 ml</td></tr><tr><td>Precision XS</td><td>BIOTEK</td><td>PRC3841</td><td>Robotic pipettor system</td></tr></tbody></table>

an organotypic high throughput system for characterization of drug sensitivity of primary multiple myeloma cells

在这项工作中，我们描述了一种新的方法，结合了体外药物敏感性测定和数字图像分析以估计敏感性病人衍生的多发性骨髓瘤（MM）细胞的异质性。这种方法包括在接种初级MM细胞从骨髓抽吸新鲜萃取入在多孔板实施，各由一个重建骨髓微环境的微流体腔室，包括细胞外基质（胶原或基底膜基质）和基质（患者 - 间充质干细胞）或来源于人的内皮细胞（HUVECs）。该室被麻醉用不同剂和浓度，并依次为96小时，通过亮视野显微术成像，在电动显微镜配备有数码相机。数字图像分析软件检测从存在或不存在膜运动的活的和死的细胞，并产生变化的曲线中存活力作为函数O˚F药物浓度和暴露时间。我们使用的计算模型，以确定肿瘤人口每种药物的敏感性的参数，以及亚群表现为肿瘤的异质性的量度的数量。这些患者定制模型可以用于模拟治疗方案，并估计临床反应。

该实验的流动在图1中简要描述如果所有步骤都成功完成，通过显微镜获得的图像应相当于图2:活MM细胞应清楚地看到明亮的磁盘和骨髓基质细胞或内皮细胞应勉强可见且分布均匀的背景。正如图2A所示 ，MM细胞的尺寸范围从一个病人到其他，但一般它们比细胞系小。因为它们几乎不实验的间隔期间复制体外 （96小时），他们可在较高浓度下（1-3百万个细...

Watch this Scientific Journal Video about An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells at JoVE.com

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells

We describe a high-throughput drug sensitivity assay for primary multiple myeloma cells. It consists of a reconstruction of the bone marrow microenvironment (including extracellular matrix and stroma) in multi-well plates, and a non-invasive method for longitudinal quantification of cell viability.

一个器官高通量系统原发性多发性骨髓瘤细胞的药物敏感性的表征

In this work we describe a novel approach that combines ex vivo drug sensitivity assays and digital image analysis to estimate chemosensitivity and ...

an-organotypic-high-throughput-system-for-characterization-drug

Research

JoVE Journal

Medicine

8.6K 次观看.  H. Lee Moffitt Cancer Center and Research Institute. We describe a high-throughput drug sensitivity assay for primary multiple myeloma cells. It consists of a reconstruction of the bone marrow microenvironment (including extracellular matrix and stroma) in multi-well plates, and a non-invasive method for longitudinal quantification of cell viability.

视频: An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells

Multimodal Bioluminescent and Positronic-emission Tomography/Computational Tomography Imaging of Multiple Myeloma Bone Marrow Xenografts in NOG Mice

Multiple myeloma (MM) tumors engraft in the bone marrow (BM) and their survival and progression are dependent upon complex molecular and cellular interactions that exist within this microenvironment. Yet the BM microenvironment cannot be easily replicated in vitro, which potentially limits the physiologic relevance of many in vitro and ex vivo experimental models. These issues can be overcome by utilizing a xenograft model in which luciferase (LUC)-transfected 8226 MM cells will specifically engraft in the mouse skeleton. When these mice are given the appropriate substrate, D-luciferin, the effects of therapy on tumor growth and survival can be analyzed by measuring changes in the bioluminescent images (BLI) produced by the tumors in vivo. This BLI data combined with positronic-emission tomography/computational tomography (PET/CT) analysis using the metabolic marker 2-deoxy-2-(18F)fluoro-D-glucose (18F-FDG) is used to monitor changes in tumor metabolism over time. These imaging platforms allow for multiple noninvasive measurements within the tumor/BM microenvironment.

Here we use bioluminescent, X-ray, and positron-emission tomography/computed tomography imaging to study how inhibiting mTOR activity impacts bone marrow-engrafted myeloma tumors in a xenograft model. This allows for physiologically relevant, non-invasive, and multimodal analyses of the anti-myeloma effect of therapies targeting bone marrow-engrafted myeloma tumors in vivo.

nog 小鼠多发性骨髓瘤异种移植的多模态生物发光和正电子发射成形断层扫描成像

Multiple myeloma (MM) tumors engraft in the bone marrow (BM) and their survival and progression are dependent upon complex molecular and cellular ...

科研

癌症研究

Methods for Evaluating the Role of c-Fos and Dusp1 in Oncogene Dependence

The demonstration of tyrosine kinase inhibitors (TKIs) in treating chronic myeloid leukemia (CML) has heralded a new era in cancer therapeutics. However, a small population of cells does not respond to TKI treatment, resulting in minimal residual disease (MRD); even the most potent TKIs fail to eradicate these cells. These MRD cells serve as a reservoir to develop resistance to therapy. Why TKI treatment is ineffective against MRD cells is not known. Growth factor signaling is implicated in supporting the survival of MRD cells during TKI treatment, but a mechanistic understanding is lacking. Recent studies demonstrated that an elevated c-Fos and Dusp1 expression as a result of convergent oncogenic and growth factor signaling in MRD cells mediate TKI resistance. The genetic and chemical inhibition of c-Fos and Dusp1 renders CML exquisitely sensitive to TKIs and cures CML in both genetic and humanized mouse models. We identified these target genes using multiple microarrays from TKI-sensitive and -resistant cells. Here, we provide methods for target validation using in vitro and in vivo mouse models. These methods can easily be applied to any target for genetic validation and therapeutic development.

Here, we describe protocols for the genetic and chemical validation of c-Fos and Dusp1 as a drug target in leukemia using in vitro and in vivo genetic and humanized mouse models. This method can be applied to any target for genetic validation and therapeutic development.

c-fos 和 dusp1 在癌基因依赖性中的作用评价方法

The demonstration of tyrosine kinase inhibitors (TKIs) in treating chronic myeloid leukemia (CML) has heralded a new era in cancer therapeutics. However, ...

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is inherently a single-cell assay, however prior to molecular analysis, the target cells are often prospectively isolated in bulk, thereby losing single-cell resolution. Single-cell gene expression analysis provides a means to understand molecular differences between individual cells in heterogeneous cell populations. In bulk cell analysis an overrepresentation of a distinct cell type results in biases and occlusions of signals from rare cells with biological importance. By utilizing FACS index sorting coupled to single-cell gene expression analysis, populations can be investigated without the loss of single-cell resolution while cells with intermediate cell surface marker expression are also captured, enabling evaluation of the relevance of continuous surface marker expression. Here, we describe an approach that combines single-cell reverse transcription quantitative PCR (RT-qPCR) and FACS index sorting to simultaneously characterize the molecular and immunophenotypic heterogeneity within cell populations.
In contrast to single-cell RNA sequencing methods, the use of qPCR with specific target amplification allows for robust measurements of low-abundance transcripts with fewer dropouts, while it is not confounded by issues related to cell-to-cell variations in read depth. Moreover, by directly index-sorting single-cells into lysis buffer this method, allows for cDNA synthesis and specific target pre-amplification to be performed in one step as well as for correlation of subsequently derived molecular signatures with cell surface marker expression. The described approach has been developed to investigate hematopoietic single-cells, but have also been used successfully on other cell types.
In conclusion, the approach described herein allows for sensitive measurement of mRNA expression for a panel of pre-selected genes with the possibility to develop protocols for subsequent prospective isolation of molecularly distinct subpopulations.

Bulk gene expression measurements cloud individual cell differences in heterogeneous cell populations. Here, we describe a protocol for how single-cell gene expression analysis and index sorting by Florescence Activated Cell Sorting (FACS) can be combined to delineate heterogeneity and immunophenotypically characterize molecularly distinct cell populations.

一种组合单细胞法表征人茎和祖种群的分子和免疫表型异质性

Immunophenotypic characterization and molecular analysis have long been used to delineate heterogeneity and define distinct cell populations. FACS is ...

遗传学

High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids

Patient-derived tumor organoids (PDOs) are expected to be a preclinical cancer model with better reproducibility of disease than traditional cell culture models. PDOs have been successfully generated from a variety of human tumors to recapitulate the architecture and function of tumor tissue accurately and efficiently. However, PDOs are unsuitable for an in vitro high-throughput assay system (HTS) or cell analysis using 96-well or 384-well plates when evaluating anticancer drugs because they are heterogeneous in size and form large clusters in culture. These cultures and assays use extracellular matrices, such as Matrigel, to create tumor tissue scaffolds. Therefore, PDOs have a low throughput and high cost, and it has been difficult to develop a suitable assay system. To address this issue, a simpler and more accurate HTS was established using PDOs to evaluate the potency of anticancer drugs and immunotherapy. An in vitro HTS was created that uses PDOs established from solid tumors cultured in 384-well plates. An HTS was also developed for assessment of antibody-dependent cellular cytotoxicity activity to represent the immune response using PDOs cultured in 96-well plates.

High-Throughput In Vitro Assay using Patient-Derived Tumor Organoids

A highly accurate in vitro high-throughput assay system was developed to evaluate anticancer drugs using patient-derived tumor organoids (PDOs), similar to cancer tissues but are unsuitable for in vitro high-throughput assay systems with 96-well and 384-well plates.

使用患者源性肿瘤类器官的高通量 体外 检测

Patient-derived tumor organoids (PDOs) are expected to be a preclinical cancer model with better reproducibility of disease than traditional cell culture ...

Profiling Sensitivity to Targeted Therapies in EGFR-Mutant NSCLC Patient-Derived Organoids

Novel 3D cancer organoid cultures derived from clinical patient specimens represent an important model system to evaluate intratumor heterogeneity and treatment response to targeted inhibitors in cancer. Pioneering work in gastrointestinal and pancreatic cancers has highlighted the promise of patient-derived organoids (PDOs) as a patient-proximate culture system, with an increasing number of models emerging. Similarly, work in other cancer types has focused on establishing organoid models and optimizing culture protocols. Notably, 3D cancer organoid models maintain the genetic complexity of original tumor specimens and thus translate tumor-derived sequencing data into treatment with genetically informed targeted therapies in an experimental setting. Further, PDOs might foster the evaluation of rational combination treatments to overcome resistance-associated adaptation of tumors in the future. The latter focuses on intense research efforts in non-small-cell lung cancer (NSCLC), as resistance development ultimately limits the treatment success of targeted inhibitors. An early assessment of therapeutically targetable mechanisms using NSCLC PDOs could help inform rational combination treatments. This manuscript describes a standardized protocol for the cell culture plate-based assessment of drug sensitivities to targeted inhibitors in NSCLC-derived 3D PDOs, with potential adaptability to combinational treatments and other treatment modalities.

This protocol describes a standardized evaluation of drug sensitivities to targeted signaling inhibitors in NSCLC patient-derived organoid models.

分析EGFR突变型NSCLC患者衍生类器官靶向治疗的敏感性

Novel 3D cancer organoid cultures derived from clinical patient specimens represent an important model system to evaluate intratumor heterogeneity and ...

Multiparametric Tumor Organoid Drug Screening Using Widefield Live-Cell Imaging for Bulk and Single-Organoid Analysis

Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex vivo drug screenings. However, current adenosine triphosphate (ATP)-based drug screening assays do not capture the complexity of a drug response (cytostatic or cytotoxic) and intratumor heterogeneity that has been shown to be retained in PDTOs due to a bulk readout. Live-cell imaging is a powerful tool to overcome this issue and visualize drug responses more in-depth. However, image analysis software is often not adapted to the three-dimensionality of PDTOs, requires fluorescent viability dyes, or is not compatible with a 384-well microplate format. This paper describes a semi-automated methodology to seed, treat, and image PDTOs in a high-throughput, 384-well format using conventional, widefield, live-cell imaging systems. In addition, we developed viability marker-free image analysis software to quantify growth rate-based drug response metrics that improve reproducibility and correct growth rate variations between different PDTO lines. Using the normalized drug response metric, which scores drug response based on the growth rate normalized to a positive and negative control condition, and a fluorescent cell death dye, cytotoxic and cytostatic drug responses can be easily distinguished, profoundly improving the classification of responders and non-responders. In addition, drug-response heterogeneity can by quantified from single-organoid drug response analysis to identify potential, resistant clones. Ultimately, this method aims to improve the prediction of clinical therapy response by capturing a multiparametric drug response signature, which includes kinetic growth arrest and cell death quantification.

This protocol describes a semi-automated method for medium- to high-throughput organoid drug screenings and microscope-agnostic, automated image analysis software to quantify and visualize multiparametric, single-organoid drug responses to capture intratumor heterogeneity.

使用宽场活细胞成像进行批量和单类器官分析的多参数肿瘤类器官药物筛选

Patient-derived tumor organoids (PDTOs) hold great promise for preclinical and translational research and predicting the patient therapy response from ex ...

基因组规模筛选，用于识别和比较肿瘤中的治疗靶点

Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor

Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are derived from Schwann cells or their precursors. In patients with the tumor susceptibility syndrome neurofibromatosis type 1 (NF1), MPNSTs are the most common malignancy and the leading cause of death. These rare and aggressive soft-tissue sarcomas offer a stark future, with 5-year disease-free survival rates of 34-60%. Treatment options for individuals with MPNSTs are disappointingly limited, with disfiguring surgery being the foremost treatment option. Many once-promising therapies such as tipifarnib, an inhibitor of Ras signaling, have failed clinically. Likewise, phase II clinical trials with erlotinib, which targets the epidermal growth factor (EFGR), and sorafenib, which targets the vascular endothelial growth factor receptor (VEGF), platelet-derived growth factor receptor (PDGF), and Raf, in combination with standard chemotherapy, have also failed to produce a response in patients. 
In recent years, functional genomic screening methods combined with genetic profiling of cancer cell lines have proven useful for identifying essential cytoplasmic signaling pathways and the development of target-specific therapies. In the case of rare tumor types, a variation of this approach known as cross-species comparative oncogenomics is increasingly being used to identify novel therapeutic targets. In cross-species comparative oncogenomics, genetic profiling and functional genomics are performed in genetically engineered mouse (GEM) models and the results are then validated in the rare human specimens and cell lines that are available. 
This paper describes how to identify candidate driver gene mutations in human and mouse MPNST cells using whole exome sequencing (WES). We then describe how to perform genome-scale shRNA screens to identify and compare critical signaling pathways in mouse and human MPNST cells and identify druggable targets in these pathways. These methodologies provide an effective approach to identifying new therapeutic targets in a variety of human cancer types.

作者聚焦:通过基因组规模 shRNA 筛选寻找恶性周围神经鞘瘤的新治疗靶点 

We have developed a cross-species comparative oncogenomics approach utilizing genomic analyses and functional genomic screens to identify and compare therapeutic targets in tumors arising in genetically engineered mouse models and the corresponding human tumor type.

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are derived from Schwann cells or their precursors. In patients with the tumor susceptibility syndrome ...

Establishment of a Human Multiple Myeloma Xenograft Model in the Chicken to Study Tumor Growth, Invasion and Angiogenesis

Multiple myeloma (MM), a malignant plasma cell disease, remains incurable and novel drugs are required to improve the prognosis of patients. Due to the lack of the bone microenvironment and auto/paracrine growth factors human MM cells are difficult to cultivate. Therefore, there is an urgent need to establish proper in vitro and in vivo culture systems to study the action of novel therapeutics on human MM cells. Here we present a model to grow human multiple myeloma cells in a complex 3D environment in vitro and in vivo. MM cell lines OPM-2 and RPMI-8226 were transfected to express the transgene GFP and were cultivated in the presence of human mesenchymal cells and collagen type-I matrix as three-dimensional spheroids. In addition, spheroids were grafted on the chorioallantoic membrane (CAM) of chicken embryos and tumor growth was monitored by stereo fluorescence microscopy. Both models allow the study of novel therapeutic drugs in a complex 3D environment and the quantification of the tumor cell mass after homogenization of grafts in a transgene-specific GFP-ELISA. Moreover, angiogenic responses of the host and invasion of tumor cells into the subjacent host tissue can be monitored daily by a stereo microscope and analyzed by immunohistochemical staining against human tumor cells (Ki-67, CD138, Vimentin) or host mural cells covering blood vessels (desmin/ASMA).
In conclusion, the onplant system allows studying MM cell growth and angiogenesis in a complex 3D environment and enables screening for novel therapeutic compounds targeting survival and proliferation of MM cells.

Human multiple myeloma (MM) cells require the supportive microenvironment of mesenchymal cells and extracellular matrix components for survival and proliferation. We established an in vivo chicken embryo model with engrafted human myeloma and mesenchymal cells to study effects of cancer drugs on tumor growth, invasion and angiogenesis.

建立一个人类多发性骨髓瘤异种移植模型中的鸡，研究肿瘤的生长，侵袭和血管生成

Multiple myeloma (MM), a malignant plasma cell disease, remains incurable and novel drugs are required to improve the prognosis of patients. Due to the ...

一个器官高通量系统原发性多发性骨髓瘤细胞的药物敏感性的表征

摘要

探索更多视频

此视频中的章节

nog 小鼠多发性骨髓瘤异种移植的多模态生物发光和正电子发射成形断层扫描成像

c-fos 和 dusp1 在癌基因依赖性中的作用评价方法

一种组合单细胞法表征人茎和祖种群的分子和免疫表型异质性

使用患者源性肿瘤类器官的高通量体外检测

分析EGFR突变型NSCLC患者衍生类器官靶向治疗的敏感性

使用宽场活细胞成像进行批量和单类器官分析的多参数肿瘤类器官药物筛选

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

建立一个人类多发性骨髓瘤异种移植模型中的鸡，研究肿瘤的生长，侵袭和血管生成

一个器官高通量系统原发性多发性骨髓瘤细胞的药物敏感性的表征

摘要

探索更多视频

此视频中的章节

nog 小鼠多发性骨髓瘤异种移植的多模态生物发光和正电子发射成形断层扫描成像

c-fos 和 dusp1 在癌基因依赖性中的作用评价方法

一种组合单细胞法表征人茎和祖种群的分子和免疫表型异质性

使用患者源性肿瘤类器官的高通量 体外 检测

分析EGFR突变型NSCLC患者衍生类器官靶向治疗的敏感性

使用宽场活细胞成像进行批量和单类器官分析的多参数肿瘤类器官药物筛选

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

遗传分析和基因组规模的辍学筛选以确定恶性周围神经鞘瘤小鼠模型中的治疗靶点

建立一个人类多发性骨髓瘤异种移植模型中的鸡，研究肿瘤的生长，侵袭和血管生成

使用患者源性肿瘤类器官的高通量体外检测