这项研究是由该中心的维尔茨堡大学医院的多学科临床研究（IZKF，补助BD247）和拜仁飞度程序（授予海克Walles）赞助。

1.二维（2D）细胞培养<ol><li>商购获得肿瘤细胞系HCC827（DSMZ）。文化RPMI-1640肺腺癌细胞株HCC827（EGFR突变，KRAS野生型），辅以20％FCS。换液，每2 - 3天。分裂细胞每周两次。用于细胞到达通道20到。 </li><li>市售获得肿瘤细胞系A549（DSMZ）。培养的肺癌细胞株A549（EGFR野生型，KRAS突变的）的RPMI-1640添加有10％FCS中。如上所述执行文化。用于细胞到达通道20到。 </li><li> （ - 6周每4）污染如支原体污染定期测试细胞。 </li><li>培养A549或HCC827细胞在盖玻片<ol><li>放置1无菌玻璃盖玻片在使用镊子一个24孔板的每个孔中。 </li><li>在500微升在孔与卷两种细胞系的种子50000肿瘤细胞盖玻片，分别为。 </li><li>培养细胞，直到它们的标准培养条件下达到70％的汇合（37℃; 5％CO 2）。在此期间，吸使用巴氏吸管的旧培养基，加入500微升新鲜培养基每2 - 1天培养。 </li></ol></li></ol> 2.在生物胶原支架肿瘤测试系统生成<ol><li> 静态培养条件 <ol><li>生成脱细胞小肠-下层+黏膜（SISmuc）并修复它两个金属环，所谓细胞冠之间，如在先前的出版物25中所述。 </li><li>在500微升的总体积到固定在细胞冠肠道的前腔的侧面要么HCC827或A549细胞的种子100,000个细胞。 </li><li>允许肿瘤细胞在37℃，5％CO 2的附着2小时。加入1毫升培养基细胞树冠内外1毫升</li><li>文化肿瘤静态条件下的模型，在37℃，5％CO 2中孵化14天。改变培养基，每2 - 3天。因此，吸使用巴斯德吸管和吸管1毫升新鲜的RPMI与FCS的适量的培养基中的细胞冠内和1.5毫升相同培养基的外面（A549:20％:10％，HCC827）。 </li></ol></li><li> 动态培养条件 <ol><li>根据第2.1.1如描述2.1.3建立与小区牙冠和细胞接种内脱细胞基质中的肿瘤的测试系统。 </li><li>培养的肿瘤模型在静态条件下在37℃，5％CO 2在培养箱中培养3天。 </li><li>组装高压灭菌的生物反应器，并插入种子SISmuc如先前公布的25。 </li><li>吸管45毫升RPMI与FCS适量（A549:10％，HCC827:20％）到烧瓶中，并在无针取样装置连接到生物反应器和之间的管道系统中等烧瓶中。 </li><li>放置在生物反应器中的培养器，在37℃，5％CO 2它具有恒定 ​​介质流（3毫升/分钟）连接到所述泵和培养另外14天肿瘤模型。 </li><li> 7天后改变整个培养基。为此，移动从孵化器的生物反应器在层流罩下。吸在使用巴氏吸管介质烧瓶中的介质。抬起生物反应器同时吸摆脱在管道系统的介质的。吸管45毫升新鲜培养基到烧瓶中。放置在生物反应器放回培养箱并把它连接到泵上。 </li></ol></li></ol> 3.与吉非替尼静态肿瘤模型的治疗<ol><li>文化作为第2.1节所述的肿瘤模型。 </li><li>在培养第11天，与1μM吉非替尼（2.5毫升为每个单元冠）准备RPMI / FCS。吸从使用巴斯德吸管孔中的旧培养基并加入1 ml准备的RPMI / FCS /吉非替尼的内部吨他细胞冠和1.5ml以外相同培养基。 注:解冻吉非替尼原液可以储存在4℃下一周。 </li><li>根据第3.2中所述更改13日网上平台。 </li></ol> 4.刺激与TGF-β-1静止的肿瘤模型的EMT感应<ol><li>文化作为第2.1节所述的肿瘤模型。 </li><li>在培养的第3天，以2纳克/ ml的TGF-β-1载体（2.5毫升每个小区冠）制备的RPMI / FCS中。吸从使用巴斯德吸管孔中的旧培养基，并添加1 ml准备的RPMI / FCS / TG​​F-β-1的细胞冠里面和1.5ml以外相同培养基。变介质补充有TGF-β-1，每2 - 1天直到第14天，4.2下所述。 </li></ol> 5.读数<ol><li> 在抽取样本作酶联免疫吸附测定 <ol><li>取样品从静态（2.1节）和动态（第2.2节）文化在上清与天培养的11-14， 如图2所示吉非替尼（第3节）的治疗。此外，取处理之前（T0）的样品。 </li><li>在静态培养条件下，从细胞冠的内搭100微升样品。在动态培养条件，螺杆取样装置上的注射器和取1ml培养基出生物反应器系统的。在-80℃保存所有收集到的上清，直到进行ELISA。 </li></ol></li><li> M30-ELISA凋亡定量 <ol><li>量化凋亡上清液中根据制造商的说明进行细胞死亡检测。允许在进行试验之前所有试剂达到RT。 </li><li>涡所有试剂。溶解在500毫升新鲜的去离子水冲洗平板电脑。稀释HRP共轭9.2毫升共轭稀释缓冲液混匀。吸取25微升标准或样品每孔。 </li><li>加入75微升稀释的HRP Conju的每孔闸门的解决方案。覆盖板并孵育它在振荡器上在室温4小时。洗板手动，5次250微升准备洗液。 </li><li>加入200微升3,3&#39;，5,5&#39;-四甲基联苯胺（TMB）底物至每孔。孵育在黑暗中在RT下20分钟。加入50μl停止溶液每个孔中。摇微孔板10秒和读取吸光度之前离开5分钟微孔板。确定在一酶标仪450nm处的吸光度。计算标准曲线，并使用合适的程序处理的ELISA类型的数据，例如来源样品中的浓度。 </li></ol></li><li> 样品染色 <ol><li> 固定，石蜡包埋和三维模型的制备节 <ol><li>使用固定每个细胞冠2.5毫升4％多聚甲醛（PFA）的种子SISmuc 2小时，并嵌入到石蜡</li><li>制备3微米的组织切片进行染色以前发表25。 </li></ol></li><li> 在2D培养条件生长的细胞的修复 <ol><li>当达到70％汇合时，冲洗盖玻片上培养的细胞在24孔板一次用PBS，用500微升4％PFA /孔10分钟进行修复。 </li><li>除去PFA和直到进行染色存储在覆盖用PBS孔板的盖玻片在4℃。 </li></ol></li><li> H＆E染色 <ol><li>根据标准方案染色用苏木精/曙红再水化部分作为概述染色。 </li></ol></li><li> 三维模型的免疫荧光染色 <ol><li>对于免疫荧光染色，通过将脱蜡和再水合滑入蒸汽烹调器具有20分钟预热的柠檬酸盐缓冲液（pH 6.0）进行抗原恢复。 注:柠檬酸缓冲的准备见材料和设备的表。 </li><li>转移的幻灯片以洗涤缓冲液（0.5M PBS缓冲液+ 0.5％吐温），具有PAP笔圈部分，以尽量减少染色溶液至所需体积，然后将载玻片在保湿室中。 </li><li>方框组织切片与来自第5.3.4.6用于在RT 20分钟二次抗体的宿主物种5％血清。 </li><li> 100，兔抗波形蛋白1:100，小鼠抗泛细胞角蛋白1，根据制造商的指令（兔抗Ki67的1在稀释轻轻拍打的幻灯片到薄纸除去阻断血清并应用主抗体的环绕部分:100）。孵育O / N在4℃。对于双染色，必须使用从不同的宿主物种的初级抗体。 </li><li>仔细洗掉未结合的抗体用洗涤缓冲液3次5分钟。 </li><li>为检测抗原特异性抗体的绑定，申请二级抗体在稀释1:400的部分，并在室温孵育1小时。 </li><li>洗掉UNBound抗体用洗涤缓冲液5分钟三次。 </li><li>含DAPI来对细胞核，并让他们干O / N含水介质装入幻灯片。 </li></ol></li><li> 2D培养细胞的免疫荧光染色 <ol><li>移除PBS并覆盖用0.2％的Triton-X100的PBS接种的玻璃盖玻片5分钟为透。洗涤用洗涤缓冲液（0.5M PBS缓冲液+ 0.5％吐温），在玻璃盖玻片5分钟。 </li><li>执行步骤5.3.4.3至5.3.4.7。执行在摇摆平台上在孔板的所有步骤和通过反转所述板除去试剂。 </li><li>用于安装，斑含有DAPI来对细胞核到未涂覆载玻片和盖玻片面向使用镊子将安装培养基中的细胞转移到它的水性介质的下降。让它成像前干。 </li></ol></li></ol></li><li> 扩散指数的测定 <ol><li>执行免疫根据第5.3.4节对染色Ki67的。或5.3 5。 </li><li>取组织切片或2D培养细胞的荧光图像用倒置显微镜。使用不同的过滤器采取DAPI染色的和Ki67染色的图像。对于定量，使用每个条件的三维部分10的图像或2D培养（放大率20X）的5个图像从试样的非重叠部分。 </li><li>确定核数及阳性​​细胞核的数量Ki67的二维<ol><li> Ki67的计数使用软件斐济26的插件细胞计数手动阳性细胞核。因此，打开图像，然后单击"插件"→"分析"→"细胞计数"。按"初始化"，然后选择一个计数器类型。点击每个的Ki67阳性核。点击次数的显示旁边的选定的计数器的类型。 </li><li>为核的总数的自动细胞计数创建使用斐济27,28的宏。形容词乌斯宏对每个染色和细胞系。下面看一个例子如何创建一个宏。 <ol><li>启动宏录制。打开DAPI图像，并通过点击"图像"→"类型"→"8位"转换为8位格式。点击"增强对比度"，设置"饱和"为"1"和"正常化"。 </li><li>将"USM锐化"锐化图像。使用一个"1"和一条"0.60""掩模"的"半径"。点击"自动阈值"，选择方法"RenyiEntropy"与"白色物体黑色背景上的&#39;来binarise图像。 </li><li>点击"插件"→"BioVoxxel"→"分水岭不规则的特点"与"5"侵蚀半径来分离细胞。单击"分析"→"分析粒子"和"大小"设置为"0.02-∞"。 注:颗粒/细胞的数目是在汇总表的计数显示。 </li><li>点击"创建"即可保存宏进一步的图像分析。 </li></ol></li></ol></li><li>如第5.4.3.1所述手动确定在3D核数和Ki67的核正数。 </li><li>根据下列公式计算的平均增殖指数（PI）: <img alt="公式1" src="/files/ftp_upload/53885/53885equation1.jpg" /> N =图像数（3D:10，2D:5） </li></ol></li></ol> 6. 在 HCC827细胞瘤硅铝模型生成与仿真抗EGFR治疗<ol><li> 利用网络生成的网络分析软件 <ol><li>使用不同的已知数据库基础上重要的实验读出参数和HCC827细胞系的突变背景以产生肿瘤网络。 </li><li>打开网络分析软件21形象化网络。 <ol><li>单击"文件"→"新建"→输入"JoVE_tumor车型"→点击"确定"即可生成一个新的网络。点击"广场北特写"→"确定"以可视化的受体的双层膜。点击"通用蛋白质"可视化节点（=蛋白质）的矩形→类型"EGFR"→点击"确定";重复此为网络中的每个节点。 </li><li>标签节点在网络中:右击→"更改颜色和形状..."→选择节点和表皮生长因子受体（EGF-EGFR）的颜色代码"255,0,0"（红色）;为节点的c-Met和（C-MET）颜色代码"0,255,0"（颜色为绿色）;吉非替尼彩码"255,255,0"（黄色）;针对PI3K-INH颜色代码"204204204"（浅灰色）;对MEK-INH颜色代码"102102102"（颜色深灰色）;在网络中选择颜色代码的所有其他节点4; 255,255,255"（白色）。 </li><li>单击"表型"可视化读出参数六边形→类型"扩散"→点击"确定"→单击鼠标右键→"更改颜色和形状..."→选择颜色代码"255204204"（彩色鲑鱼）;重复此参数凋亡→选择颜色代码"255,51,204"（颜色紫色）。 </li><li>可视化边缘（=互动）:点击"状态转变"为激活（箭头），点击"紧箍咒"紧箍咒为（减弱箭头）;重复此为网络中的每个交互。 </li></ol></li><li>点击"文件"→"另存为..."→输入"JoVE_tumor models.xml"→点击"保存"将生成的信令网保存为.xml格式。 </li></ol></li><li> 电脑模拟使用SQUAD 注:阵容代表日E网络的拓扑结构为离散逻辑布尔系统（AND，OR，NOT），并进行稳态分析。稳态分析反映了系统的平衡，在信号刺激的责任（ 例如 ，药物的应用或突变）。 <ol><li>打开SQUAD 17软件，点击"加载网络"→上传"JoVE_tumor models.xml&#39;文件。点击"运行分析": 注:接下来，阵容适用指数函数插值布尔的网络连接，这使得一段时间内的网络行为的动态模拟（彩色乙状结肠活动曲线）。 </li><li>点击"高级"→"扰动器"写一个仿真协议。模拟抗EGFR阻力:点击"编辑协议" <ol><li>点击"扰动"→使用标准"参数initialstate = SS-4"（稳态4）→点击"添加"添加"新的恒定脉冲"→硒LECT参数"状态"→选择目标"翻转"→选择时间为"0"→选择值"0.4"→点击"确定"。 </li><li>重复此:点击"添加"→选择参数"状态"→选择目标"C-MET"→选择时间为"0"→选择值"0.4"→点击"确定";点击"添加"→选择参数"状态"→选择目标"吉非替尼"→选择时间为"0"→选择值"1"→点击"确定"。 </li><li>设置状态值，以主动节点（EGF-EGFR）:单击"activenode"→点击"编辑"→选择状态"0.8"→点击"确定";所有其他节点:点击"编辑"→选择状态为"0"→点击"确定"。点击"确定"保存协议。 </li><li>显示特定的曲线:进入面板"选项"→选择"（EGF-EGFR）"，"*（EGF-EGFR）"，"* MEK"，"半胱天冬"，"（C-MET）"，"PI3K" "吉非替尼"，"细胞凋亡"，"扩散"，"MEK-INH"和"PI3K-INH"的图形表示。点击"初始化"→"运行"，开始了系统的响应的完全仿真。点击"重置"，开始新的模拟。 </li></ol></li><li>模拟组合PI3K和MEK抑制剂治疗:点击"编辑协议" <ol><li> 6.2.2.3 - 6.2.2.1部分所述使用相同的节点参数。点击"扰动"→点击"添加"添加"新的恒定脉冲"→选择参数"状态"→选择目标"PI3K-INH"→选择时间为"0"→选择值"1"→点击"确定";点击"添加"添加"新恒定脉冲"→选择参数"状态"→选择目标"MEK-INH"→选择时间为"0"→选择值"1"→点击"确定"。 </li><li>点击"确定"保存协议。转到面板中的"选项":6.2.2.4部分所述使用相同的节点的图形表示。点击"初始化"→"运行"，开始了系统的响应的完全仿真。点击"重置"来完成模拟。 </li></ol></li></ol></li></ol>

<ol>
	<li>Bhattacharjee, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biomedicine+Pharma+firms+push+for+sharing+of+cancer+trial+data.">Biomedicine Pharma firms push for sharing of cancer trial data.</a> Science. 338, 29 (2012).</li><li>Kola, I., Landis, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Can+the+pharmaceutical+industry+reduce+attrition+rates?.">Can the pharmaceutical industry reduce attrition rates?.</a> Nat Rev Drug Discov. 3, 711-715 (2004).</li><li>Arrowsmith, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trial+watch:+Phase+II+failures:+2008-2010.">Trial watch: Phase II failures: 2008-2010.</a> Nat Rev Drug Discov. 10, 328-329 (2011).</li><li>Arrowsmith, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trial+watch:+phase+III+and+submission+failures:+2007-2010.">Trial watch: phase III and submission failures: 2007-2010.</a> Nat Rev Drug Discov. 10, 87 (2011).</li><li>Arrowsmith, J., Miller, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trial+watch:+phase+II+and+phase+III+attrition+rates+2011-2012.">Trial watch: phase II and phase III attrition rates 2011-2012.</a> Nat Rev Drug Discov. 12, 569 (2013).</li><li>Pampaloni, F., Reynaud, E. G., Stelzer, E. 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+third+dimension+bridges+the+gap+between+cell+culture+and+live+tissue.">The third dimension bridges the gap between cell culture and live tissue.</a> Nat Rev Mol Cell Biol. 8, 839-845 (2007).</li><li>Hartung, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Toxicology+for+the+twenty-first+century.">Toxicology for the twenty-first century.</a> Nature. 460, 208-212 (2009).</li><li>Stratmann, A. T., Dandekar, G., Nietzer, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+in+vitro+tumor+Models+as+an+Alternative+for+Animal+Models+in+Preclinical+Studies.">Three-dimensional in vitro tumor Models as an Alternative for Animal Models in Preclinical Studies.</a> Pharm Ind. 75, 485-489 (2013).</li><li>Stratmann, A. T., Dandekar, G., Nietzer, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+in+vitro+tumor+Models+as+an+Alternative+for+Animal+Models+in+Preclinical+Studies.">Three-dimensional in vitro tumor Models as an Alternative for Animal Models in Preclinical Studies.</a> Pharm Ind. 75, 675-680 (2013).</li><li>Gudjonsson, T., Ronnov-Jessen, L., Villadsen, R., Bissell, M. J., Petersen, O. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=To+create+the+correct+microenvironment:+three-dimensional+heterotypic+collagen+assays+for+human+breast+epithelial+morphogenesis+and+neoplasia.">To create the correct microenvironment: three-dimensional heterotypic collagen assays for human breast epithelial morphogenesis and neoplasia.</a> Methods. 30, 247-255 (2003).</li><li>Weaver, V. M., Fischer, A. H., Peterson, O. W., Bissell, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+importance+of+the+microenvironment+in+breast+cancer+progression:+recapitulation+of+mammary+tumorigenesis+using+a+unique+human+mammary+epithelial+cell+model+and+a+three-dimensional+culture+assay.">The importance of the microenvironment in breast cancer progression: recapitulation of mammary tumorigenesis using a unique human mammary epithelial cell model and a three-dimensional culture assay.</a> Biochem Cell Biol. 74, 833-851 (1996).</li><li>Antoni, D., Burckel, H., Josset, E., Noel, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+cell+culture:+a+breakthrough+in+vivo.">Three-dimensional cell culture: a breakthrough in vivo.</a> Int J Mol Sci. 16, 5517-5527 (2015).</li><li>Kim, J., Tanner, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recapitulating+the+Tumor+Ecosystem+Along+the+Metastatic+Cascade+Using+3D+Culture+Models.">Recapitulating the Tumor Ecosystem Along the Metastatic Cascade Using 3D Culture Models.</a> Front Oncol. 5, 170 (2015).</li><li>Worthington, P., Pochan, D. J., Langhans, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peptide+Hydrogels+-+Versatile+Matrices+for+3D+Cell+Culture+in+Cancer+Medicine.">Peptide Hydrogels - Versatile Matrices for 3D Cell Culture in Cancer Medicine.</a> Front Oncol. 5, 92 (2015).</li><li>Tanner, K., Gottesman, M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Beyond+3D+culture+models+of+cancer.">Beyond 3D culture models of cancer.</a> Sci Transl Med. 7, 283ps9 (2015).</li><li>Stadler, 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=Increased+complexity+in+carcinomas:+Analyzing+and+modeling+the+interaction+of+human+cancer+cells+with+their+microenvironment.">Increased complexity in carcinomas: Analyzing and modeling the interaction of human cancer cells with their microenvironment.</a> Semin Cancer Biol. , (2015).</li><li>Stratmann, A. T., 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=Establishment+of+a+human+3D+lung+cancer+model+based+on+a+biological+tissue+matrix+combined+with+a+Boolean+in+silico+model.">Establishment of a human 3D lung cancer model based on a biological tissue matrix combined with a Boolean in silico model.</a> Mol Oncol. 8, 351-365 (2014).</li><li>Mok, T. S., 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=Gefitinib+or+carboplatin-paclitaxel+in+pulmonary+adenocarcinoma.">Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma.</a> N Engl J Med. 361, 947-957 (2009).</li><li>Maemondo, 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=Gefitinib+or+chemotherapy+for+non-small-cell+lung+cancer+with+mutated+EGFR.">Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR.</a> N Engl J Med. 362, 2380-2388 (2010).</li><li>Rosell, R., 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=Erlotinib+versus+standard+chemotherapy+as+first-line+treatment+for+European+patients+with+advanced+EGFR+mutation-positive+non-small-cell+lung+cancer+(EURTAC):+a+multicentre,+open-label,+randomised+phase+3+trial.">Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial.</a> Lancet Oncol. 13, 239-246 (2012).</li><li>Sequist, L. V., 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=Phase+III+study+of+afatinib+or+cisplatin+plus+pemetrexed+in+patients+with+metastatic+lung+adenocarcinoma+with+EGFR+mutations.">Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations.</a> J Clin Oncol. 31, 3327-3334 (2013).</li><li>Lee, J. M., Dedhar, S., Kalluri, R., Thompson, E. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+epithelial-mesenchymal+transition:+new+insights+in+signaling,+development,+and+disease.">The epithelial-mesenchymal transition: new insights in signaling, development, and disease.</a> J Cell Biol. 172, 973-981 (2006).</li><li>Wells, A., Yates, C., Shepard, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=E-cadherin+as+an+indicator+of+mesenchymal+to+epithelial+reverting+transitions+during+the+metastatic+seeding+of+disseminated+carcinomas.">E-cadherin as an indicator of mesenchymal to epithelial reverting transitions during the metastatic seeding of disseminated carcinomas.</a> Clin Exp Metastasis. 25, 621-628 (2008).</li><li>Janne, P. A., 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=AZD9291+in+EGFR+inhibitor-resistant+non-small-cell+lung+cancer.">AZD9291 in EGFR inhibitor-resistant non-small-cell lung cancer.</a> N Engl J Med. 372, 1689-1699 (2015).</li><li>Moll, C., 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=Tissue+engineering+of+a+human+3D+in+vitro+tumor+test+system.">Tissue engineering of a human 3D in vitro tumor test system.</a> J Vis Exp. , (2013).</li><li>Funahashi, A., 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=CellDesigner+3.5:+A+Versatile+Modeling+Tool+for+Biochemical+Networks.">CellDesigner 3.5: A Versatile Modeling Tool for Biochemical Networks.</a> Proceedings of the IEEE. 96, 1254-1265 (2008).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Auto Threshold(ImageJ)v.v1.15. , (2013).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> BioVoxxel Toolbox (ImageJ / Fiji). , (2015).</li><li>Buettner, R., Wolf, J., Thomas, R. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lessons+learned+from+lung+cancer+genomics:+the+emerging+concept+of+individualized+diagnostics+and+treatment.">Lessons learned from lung cancer genomics: the emerging concept of individualized diagnostics and treatment.</a> J Clin Oncol. 31, 1858-1865 (2013).</li><li>Engelman, J. A., 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=MET+amplification+leads+to+gefitinib+resistance+in+lung+cancer+by+activating+ERBB3+signaling.">MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling.</a> Science. 316, 1039-1043 (2007).</li><li>Mukohara, T., 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=Differential+effects+of+gefitinib+and+cetuximab+on+non-small-cell+lung+cancers+bearing+epidermal+growth+factor+receptor+mutations.">Differential effects of gefitinib and cetuximab on non-small-cell lung cancers bearing epidermal growth factor receptor mutations.</a> J Natl Cancer Inst. 97, 1185-1194 (2005).</li><li>Noro, R., 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=Gefitinib+(IRESSA)+sensitive+lung+cancer+cell+lines+show+phosphorylation+of+Akt+without+ligand+stimulation.">Gefitinib (IRESSA) sensitive lung cancer cell lines show phosphorylation of Akt without ligand stimulation.</a> BMC Cancer. 6, 277 (2006).</li><li>Gill, B. 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+synthetic+matrix+with+independently+tunable+biochemistry+and+mechanical+properties+to+study+epithelial+morphogenesis+and+EMT+in+a+lung+adenocarcinoma+model.">A synthetic matrix with independently tunable biochemistry and mechanical properties to study epithelial morphogenesis and EMT in a lung adenocarcinoma model.</a> Cancer Res. 72, 6013-6023 (2012).</li></ol>

作者什么都没有透露。

/在硅片肿瘤测试系统的生物标志物指导的治疗预言我们已经建立了体外组合。 在体外模型评价化合物的动作的不同的重要方面如在一个特定的突变背景也可以在计算机芯片 17模拟肿瘤细胞增殖和凋亡的变更。在这里，我们提出了三维肿瘤模型的生成和包括增殖和凋亡的量化和在硅片模型建立的预测复合测试的标准化协议。三维肿瘤模型是基于肿瘤细胞系轴承特异性突变。细胞生长在细胞冠脱细胞组织基质。基质脱细胞中，两个金属环（细胞冠）之间的固定，组装的生物反应器系统，以及播种支架的已在朱庇特25之前被可视化。 体外 </EM&gt; 3D肿瘤模型 此处所取得的成果进入临床的翻译需要合适的肿瘤细胞的轴承利益的突变，以根据生物标志物选择有针对性的药物的患者进行分类的精心挑选。对于分层药，通过新一代测序鉴定成药司机突变是一个重大问题特别是在非小细胞肺癌和未来29有望揭示新的遗传标记。 在体外试验中，感兴趣的化合物应该针对一个网站，是在所选择的细胞系或原代细胞中高度活跃。这里，细胞系HCC827和A549，由于被选择它们在EGFR突变状态差和报超敏反应（HCC827细胞）和中间灵敏度（A549细胞）朝向在2D培养30-32的TKI吉非替尼。在所选择的肿瘤的三维肿瘤模型生成，细胞数和培养期间的第一步骤的细胞必须adju如果使用从这里提到的不同细胞受激发射损耗。找到最优化合物浓度，最好是确定在二维市售活力测定的帮助IC 50值。根据该试验中，化合物应在IC 50浓度，并在三维模型的下一个更高的浓度使用。我们选择治疗一方面三天以两到三周之内并便于比较2D肿瘤测试系统，另一方面获得结果。然而，治疗期可以延长到调查长期效果。然而，应当考虑到长期治疗或测试化合物的高剂量可引起完整细胞损失，从而防止扩散或其他免疫组化标记的评估。 为可靠的信令网络分析，在用一定的化合物治疗的肿瘤应答，必须分析增殖和apo区分下垂。这些读数被不同地连接的信令网络。因此，这两个参数的独特分析，可以更好地了解药物作用和随后的目标预测。如前面提到的，肿瘤细胞的增殖中的3D模型相比，减小2D培养条件，从而，应减少测试细胞抑制化合物的假阳性结果。为增殖指数的确定，有核的总数和核阳性的Ki67染色的数量使用软件斐济例如进行定量。这可以通过在肿瘤细胞中的2D培养宏的使用可以简化其中然而，分别是，不可能的，如果细胞形成紧聚集体，因为这会导致核的更低或更高的数字。在所有情况下，宏设置有每个细胞系和染色，以仔细调整。凋亡可以从上清液测定胱天蛋白酶裂解细胞角蛋白18来定量非侵入性，WHICH被限制为上皮特征的细胞，使用M30-ELISA。这具有几个优点:I）中它允许对随时监视治疗功效，并确定有效的治疗方法的起点。 II）的样品不被破坏，并且可以用于其他的读出技术。 Ⅲ）上皮细胞凋亡可以由间充质细胞凋亡，这是在共培养设置最佳区分开来。这种技术，然而，可能不适合将经历EMT，从而失去其上皮表型的肿瘤细胞。因此，使用的每个肿瘤细胞系的细胞角蛋白18的表达应该通过免疫组化染色应用此技术之前验证。也可以在一个更肿瘤干细胞样表型进行化合物的检测。通常在药物测试的不同侵袭阶段被忽略，即使大部分的靶向药物，如TKI的，在更先进的肿瘤的阶段施加。我们的模型能够侵入或没有调查正侵袭性肿瘤细胞时，由于保留基底膜17其中细胞具有在入侵过程跨越。对细胞运动和侵袭的一个关键步骤是EMT可以在不同的肺癌模型通过刺激TGF-β-1 17,33诱发。然而，这减少了对支架的增殖，从而细胞数。这种负面副作用可通过动态培养条件的应用，在3D模型强烈增加肿瘤细胞密度来规避。即使在生物反应器调整培养生理条件，它必须被认为电池特性和信号可以通过暴露的影响剪切应力25。 采用电子 模拟，以加速细胞系特异性药物测试 虽然仅半定量，事件的顺序被正确由我们在硅片模型由护理建模充分考虑每个特定细胞系已知的突变。这包括细胞系的不同的受体激活水平的具体的修改，在何种程度上涉及激酶被激活，并且当与网络输出多久如细胞凋亡或增殖是可以预料的。例如，可以考虑，被认为在获得抗EGFR治疗电阻30的大约20％至发生临床上已知的c-MET扩增。接着， 在硅片模型计算随时间变化的相应的网络行为， 例如 ，吉非替尼抗性发展以增加的增殖表示和降低凋亡。在我们的模型中，我们确定的MEK和PI3K作为最有希望的目标候选。因此，新的潜在的治疗组合，可以迅速地在硅片预评估，作为用于进一步在体外测试的基础。另外，从体外实验的输出数据可可以使用由适合的实验结果最好的网络调整来细化，在硅片系统。半定量，在硅片的策略有关于网络的大小（约100蛋白质-蛋白质相互作用可以考虑）一些限制。此外，它是所有关键蛋白质的节点到网络的拓扑结构整合，以产生实际的结果是至关重要的。因此，在硅片模型仅给出在活的肿瘤细胞的现有网络的近似。然而，这种聚焦视图允许我们模拟感兴趣的特定的变化， 例如 ，药物组合对所述细胞系不同突变的背景的影响。这有助于我们系统地了解这种癌症的信令网络的复杂性，以及衍生新的治疗策略。 总之，我们相信，我们已经开发出体外的工具设计一个有用的组织，可以很容易地集成到precli上单一药物化合物和它们的组合的功效nical测试。为了降低测试成本和时间，这种肿瘤模型还通过在硅片预测工具，允许延长收集的药物和药物联合作用的细胞类型特异性的预测，包括面向临床靶向治疗或新玩家考虑数据补充（ 例如 ，微RNA）。

医药行业在癌症治疗领域的临床阶段面临着高达95％的高流失率造成了巨大的成本1-5。对于这个逆差的一个原因是目前潜在的新的化合物的功效在对癌症细胞系的2D细胞培养物或动物模型中的大型放映被评估的事实。动物模型具有较高的复杂性，但也有老鼠和人之间的6,7重要区别。在过去十年中，已经生成使用不同的方法的3D癌症模型弥合的癌细胞系的2D培养和体内肿瘤6,8,9复杂之间的差距。三维环境对细胞分化和也对信号的影响已经在一些研究中已显示年前（ 例如 ，由米娜比斯尔）10,11。今天，许多3D细胞培养模型可用，如球体文化，水凝胶或微流控芯片12-16。虽然THESE型增强复杂相比传统二维培养系统，它们大多缺乏该已知具有肿瘤支撑效应并且还影响药效的组织的微环境。 为了解决这个问题，我们产生基于称为SISmuc（ 小肠-下层+粘膜 ）的生物支架，其由脱细胞猪空肠衍生的三维肿瘤模型。从而，组织架构和诸如不同胶原以及基底膜结构ECM的重要组成部分被保留17。这种独特的特征是肿瘤模型生成从上皮出现并包括实体肿瘤的约80％的癌中是至关重要的。此外，在我们的组织工程化的肿瘤模型中的细胞增殖率相比，在2D培养取得的人为的高率降低。如增殖是在评估药物疗效的重要参数，药物测试是在我们的模型中启用更多类似在体内条件下肿瘤17。 为了评估我们的模型来正确预测生物标记物相关的药物的疗效，我们对在他们的EGFR -biomarker状态不同的两种不同的肺癌细胞系这里本数据的潜力。这种突变状态已经开始在小细胞肺癌患者常规测定。靶向治疗与TKIs的如EGFR -inhibitor抗肿瘤轴承相比，含铂类化疗18-21活化EGFR突变呈现出优异的成果吉非替尼。 我们建立了相关评价化合物功效几个读出的技术。此外，TGF-β-1刺激后，我们能够调查在肿瘤细胞中启动该EMT过程，这被认为是在恶变22,23的一个重要步骤，并连接到药物resistan化合物的动作CE 24。 三维肿瘤模型允许监测细胞特异性反应针对性的治疗，化学疗法，或具有良好反差的药物组合。为了进一步增强和加速药物筛选和遇到阻力，这是通过一个在电脑模拟的补充。基于一些实验，肿瘤反应，可以在硅片方面的成果进行全方位的药物及其组合预测。

<table><tbody><tr><td>Bioreactors</td><td>Chair of Tissue Engineering and Regenerative Medicine, W&amp;uuml;rzburg (GER)</td><td></td><td>Bioreactor setup</td></tr><tr><td>BioVoxxel Toolbox (ImageJ / Fiji)</td><td>Jan Brocher, Thorsten Wagner, https://github.com/biovoxxel/BioVoxxel_Toolbox</td><td></td><td></td></tr><tr><td>Cell crowns</td><td>Chair of Tissue Engineering and Regenerative Medicine, W&amp;uuml;rzburg (GER)</td><td></td><td>for static 3D culture</td></tr><tr><td>CellDesigner</td><td>http://www.celldesigner.org/</td><td>-</td><td>This software was used for drawing the network.</td></tr><tr><td>Citrate buffer stock solution (10x)</td><td>in house production</td><td></td><td>42 g/L Citric acid monohydrate, 17.6 g/L Sodium hydroxide pellets in deionized water, pH 6.0, stored at RT.&amp;nbsp;</td></tr><tr><td>Citrate buffer working solution</td><td>in house production</td><td></td><td>10% Citrate buffer stock solution in demineralized water, stored at RT.</td></tr><tr><td>Citric acid monohydrate</td><td>VWR, Darmstadt (GER)</td><td>1002441000</td><td>used for the citrate buffer</td></tr><tr><td>Cover slips</td><td>VWR, Darmstadt (GER)</td><td>631-1339</td><td></td></tr><tr><td>DAPI Fluoromount-G&lt;sup&gt;TM&lt;/sup&gt;</td><td>SouthernBiotech, Birmingham (USA)</td><td>SBA-0100-20</td><td></td></tr><tr><td>Databases such as KEGG, HPRD and QIAGEN (Genes &amp;amp; Pathways)</td><td>http://www.genome.jp/kegg/pathway.html; http://www.hprd.org/; https://www.qiagen.com/de/geneglobe/</td><td>-</td><td>Different known literature databases were used for generating the network topology.</td></tr><tr><td>Female Luer Lug Style Tee</td><td>Mednet, M&amp;uuml;nster (GER)</td><td>FTLT-1</td><td>Bioreactor setup</td></tr><tr><td>Female Luer Thread Style with 5/16&quot; Hex to 1/4-28 UNF Thread</td><td>Mednet, M&amp;uuml;nster (GER)</td><td>SFTLL-J1A&amp;nbsp;</td><td>Bioreactor setup</td></tr><tr><td>Fetal Calf Serum</td><td>Bio&amp;amp;SELL, Feucht (GER)</td><td>FCS.ADD.0500</td><td>not heat-inactivated</td></tr><tr><td>Gefitinib</td><td>Absource Diagnostics GmbH, M&amp;uuml;nchen (GER)</td><td>S1025-100 mg</td><td>100 mM stock solution with DMSO</td></tr><tr><td>Glas flask (Schott, GER) provided with glas hose connection</td><td>Weckert, Kitzingen (GER)</td><td>custom made</td><td></td></tr><tr><td>Histofix 4% (Paraformaldehyd)</td><td>Carl Roth, Karlsruhe (GER)</td><td>P087.1</td><td></td></tr><tr><td>Hose coupling</td><td>Mednet, M&amp;uuml;nster (GER)</td><td>CC-9</td><td>Bioreactor setup</td></tr><tr><td>Incubator for bioreactors</td><td>Chair of Tissue Engineering and Regenerative Medicine, W&amp;uuml;rzburg (GER)</td><td></td><td>Bioreactor setup</td></tr><tr><td>M30 CytoDeath&lt;sup&gt;TM&lt;/sup&gt; ELISA</td><td>Peviva, Bromma (SWE)</td><td>10900</td><td></td></tr><tr><td>Male Luer Integral Lock Ring</td><td>Mednet, M&amp;uuml;nster (GER)</td><td>MTLL230-J1A</td><td>Bioreactor setup</td></tr><tr><td>Moisture chamber</td><td>custom made</td><td></td><td></td></tr><tr><td>Mouse anti Pan-Cytokeratin</td><td>Sigma-Aldrich, Munich (GER)&amp;nbsp;&amp;nbsp;</td><td>C2562-2ML</td><td>Clone C-11+PCK-26+CY-90+KS-1A3
+M20+A53-B/A2, used 1/100 for immunofluorescence</td></tr><tr><td>Needlefree Swabable Valve Female Luer</td><td>Mednet, M&amp;uuml;nster (GER)</td><td>NVFMLLPC</td><td>Bioreactor setup, for sampling, gamma-sterilized</td></tr><tr><td>O-Ring MVQ 10 red 37 x 3 mm</td><td>Arcus Dichtelemente, Seevetal (GER)</td><td>21444</td><td>O-ring large, Bioreactor setup</td></tr><tr><td>O-Ring MVQ 70 red 27 x 2.5 mm</td><td>Arcus Dichtelemente, Seevetal (GER)</td><td>19170</td><td>O-ring small, Bioreactor setup</td></tr><tr><td>PAP pen</td><td>Dako, Hamburg (GER)</td><td>S002</td><td></td></tr><tr><td>Paraffin</td><td>Carl Roth, Karlsruhe (GER)</td><td>6642.6</td><td></td></tr><tr><td>Peristaltic pump</td><td>Ismatec, Wertheim-Mondfeld (GER)</td><td></td><td>Bioreactor setup</td></tr><tr><td>Phosphate Buffered Saline</td><td>Sigma-Aldrich, Munich (GER)&amp;nbsp;&amp;nbsp;</td><td>D8537-6x500ml</td><td></td></tr><tr><td>Pump tubing cassette</td><td>Ismatec, Wertheim (GER)</td><td>IS 3710</td><td>Bioreactor setup</td></tr><tr><td>Rabbit anti Ki67</td><td>Abcam, Cambridge (UK)</td><td>ab16667</td><td>Clone SP6, used for 1/100 for IF</td></tr><tr><td>Rabbit anti Vimentin</td><td>Abcam, Cambridge (UK)</td><td>ab92547</td><td>used 1/100 for IF</td></tr><tr><td>RPMI-1640 medium</td><td>Life technologies, Darmstadt (GER)</td><td>61870-044</td><td>warm in 37 &amp;deg;C waterbath before use</td></tr><tr><td>Silicone tube</td><td>Carl Roth GmbH, Karlsruhe (GER)</td><td>HC66.1</td><td>Bioreactor setup</td></tr><tr><td>Sodium Hydroxide</td><td>Sigma-Aldrich, M&amp;uuml;nchen (GER)</td><td>30620-1KG-R</td><td>used for the citrate buffer</td></tr><tr><td>SQUAD</td><td>http://sbos.eu/docu/docu/SQUAD/doku.php.htm</td><td>-</td><td>This software was used for performing the semiquantitative simulations.</td></tr><tr><td>Sterile air filter, pore size 0.2 &amp;micro;m</td><td>Sartorius Stedium Biotech, G&amp;ouml;ttlingen (GER)</td><td>16596-HYK</td><td>Bioreactor setup</td></tr><tr><td>Syringe Luer Lok 5 ml</td><td>BD Biosciences, Heidelberg (GER)</td><td>309649</td><td>for bioreactor sampling</td></tr><tr><td>Tissue culture test plates: 6-,&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 12-, 24-, 96- well</td><td>TPP Techno Plastic Products AG, Trasadingen (GER)</td><td>92006, 92012, 92024, 92048&amp;nbsp;</td><td></td></tr><tr><td>Transforming growth factor-beta 1 (TGF-&amp;beta;1) with carrier</td><td>Cell Signaling, Frankfurt (GER)</td><td>8915LC</td><td>stock solution in sterile citrate buffer pH 3.0</td></tr><tr><td>Triton X-100</td><td>Sigma-Aldrich, M&amp;uuml;nchen (GER)</td><td>X100-1L</td><td></td></tr><tr><td>Tween-20</td><td>Sigma-Aldrich, M&amp;uuml;nchen (GER)</td><td>P7949-500ml</td><td>for washing buffer of immunofluorescent staining</td></tr></tbody></table>

a combined 3d tissue engineered in vitro/in silico lung tumor model for predicting drug effectiveness in specific mutational backgrounds

在本研究中，我们结合一个体外三维肺肿瘤模型与在硅片模型基于特定突变背景，以优化药物的反应的预测。该模型是上再现有关的细胞外基质的组成和架构，包括基底膜组织特异性特征的猪去细胞支架产生的。我们标准化的协议，允许在14天内，包括药物治疗三天人造肿瘤组织产生。我们的文章提供了三维的几个详细描述读出的筛选技术，例如增殖指数的Ki67染色的，凋亡的M30-ELISA测定从上清液和上皮的评估至间质转变 （EMT），这是有用的工具，用于评估的有效性治疗化合物。我们可以证明相比于2D文化在我们的三维肿瘤模型减少扩散是RELAT编临床情况。尽管该下扩散，模型正确地根据该生物标记状态如由肺癌细胞系HCC827的比较预测EGFR -targeted药物反应（EGFR -mutated，KRAS野生型）和A549（EGFR野生型，KRAS -突变）用酪氨酸激酶抑制剂 （TKI）吉非替尼治疗。调查更先进的肿瘤细胞的药物反应，我们诱导的EMT由长期治疗的TGF-β-1波形蛋白/泛细胞角蛋白免疫荧光染色所评估。甲流生物反应器是用来调整文化，生理条件，提高了组织的产生。此外，我们表现出药物反应在吉非替尼治疗或TGF-β-1刺激的整合-细胞凋亡，增殖指数和EMT -为布尔在硅片模式。此外，我们解释了与特定突变的背景和计数肿瘤细胞如何药物反应抗阻力erstrategies可以预测的。我们有信心， 我们特别是其在硅片扩张体外方法3D提供了更现实的条件临床前药物测试比二维细胞培养的附加 ​​价值。

在SISmuc支架（ 图2A至C）的基础上，我们建立了一个三维肿瘤的测试系统（ 图2D）的产生，刺激和治疗的标准化操作协议。此模型使增殖指数和使用M30-ELISA分别示于图1和图3中 ，细胞凋亡的定量的测定。 图3示出了A549和HCC827模型代表H＆E染色和吉非替尼一个代表性的细胞凋亡测定。在这里提出的模型是用它成功地在临床上有针对性的抑制剂治疗EGFR -mutated非小细胞肺癌的例子设计。相应地，只有EGFR -mutated HCC827细胞而不是A549细胞通过在如由细胞凋亡的增加评估我们的模型的TKI吉非替尼EGFR抑制响应。 图4 </STRONG&gt;显示了EMT诱导TGF-β-1刺激后我们的模型的一个代表性染色。 如图5C和D。此外，根据动态培养条件吉非替尼在流动生物反应器增强组织生成动态培养条件对EGFR -mutated HCC827（ 图5D）有强烈的影响。 图6示出了网络拓扑结构（ 图6A）和在 HCC827细胞（ 图6B，C），抗EGFR的治疗抵抗的硅片模拟详细。用已知的文献的数据库如HPRD，KEGG和QIAGEN（基因与途径）溶液中产生的信令网络，从而导致42个节点和55边缘的拓扑与CellDesigner软件26可视化。已知驱动突变EGFR（红色）和c-MET共激活的模拟（绿色，值约为0.7）表示增加的海峡iferation率（鲑鱼曲线），并降低细胞凋亡率（紫色线），随着时间的推移反映了吉非替尼（黄色）电阻HCC827细胞MEK和PI3K（ 图6B，深绿色和青色）的激活一起去。合并的PI3K和MEK抑制剂（暗和浅灰曲线）的结果中的抗EGFR电阻效应的逆转，建模减少增殖并诱导凋亡（ 图6C）。 <img alt="图1" src="/files/ftp_upload/53885/53885fig1.jpg" /> 图1扩散率在3D相比减少到2D细胞培养。的Ki67阳性HCC827细胞（红色在A和B）在二维细胞培养物（A）和三维细胞培养物进行染色上SISmuc（B）。 HCC827细胞和A549细胞进行计数并测定增殖指数（Ki67的阳性细胞的百分比）（C &lt;/ STRONG&gt;，一位代表数出五）。 在扩展酒吧和B:100微米<a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53885/53885fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图2" src="/files/ftp_upload/53885/53885fig2.jpg" /> 图2. SISmuc脚手架形态和治疗方案与吉非替尼TKI细胞接种于它由小肠黏膜下层 （SIS）+黏膜（A的SISmuc:明，B:DAPI染色细胞的SISmuc，C的顶部:覆盖A和B），并在第0天被固定在细胞冠的治疗方案示于D:中等变化（MC）的每2至3天。在11天的治疗开始。收集上清液并用于M30-ELISA才能随着时间的推移量化细胞凋亡（蓝色箭头和框）。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53885/53885fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图3" src="/files/ftp_upload/53885/53885fig3.jpg" /> 图3.在SISmuc和诱导凋亡在HCC827吉非替尼治疗的变化细胞生长，但不能在A549 3D肿瘤模型，没有任何处理，这两种细胞系上形成SISmuc（A和B）的单层，也解决前隐窝结构。而A549细胞的生长模式与吉非替尼（C）的处理后没有改变，HCC827细胞的数目减少伴随着改变的细长细胞形状（D）。细胞凋亡是由吉非替尼在HCC827模型诱导从培养上清液M30-ELISA测量所看到（E </st荣&gt;，一位代表测量出五）。比例尺在D:100微米的A至D <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53885/53885fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图4" src="/files/ftp_upload/53885/53885fig4.jpg" /> 图4. TGF-β-1诱导EMT在HCC827细胞的SISmuc。HCC827细胞培养的3D显示泛细胞角蛋白（PCK）的整体表达（绿色A，A1），但只有单细胞表达波形蛋白（红A， a2）。的TGF-β-1刺激后，将细胞改变它们的形态，以伸长的形状和波形蛋白的表达强烈增加（B中的红，b2）中，而PCK的表达被保持（绿色B，B1）。比例尺在B:100微米对于A </STRONG&gt;和B。 <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53885/53885fig4large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图5" src="/files/ftp_upload/53885/53885fig5.jpg" /> 图5.动态细胞培养增强组织生成，当在生物反应器3D条件（B），从静态模型（A，H＆E染色）从单层（A）为多层组织变化（C，H＆E染色单层下培养）。 HCC827细胞出示吉非替尼治疗（D，H＆E染色）强烈的药物反应。比例尺在D:100微米的A，C和D <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53885/53885fig5large.jpg" target="_blank">，请点击此处查看该图的放大版本</a>。 <img alt="图6" src="/files/ftp_upload/53885/53885fig6.jpg" /> 图。 6. 在硅片 肿瘤模型生成和红色（EGFR途径）与关键的信号节点的肿瘤细胞的抗EGFR治疗耐药，网络拓扑和绿色（C-MET）及其下游节点的模拟 。特点肿瘤读出参数增殖（鲑鱼）和细胞凋亡（紫罗兰）被表示为六边形。箭头表示激活，钝箭抑制作用。的治疗目标是由暗和亮灰色矩形表示时，抑制由吉非替尼在黄色（A）中示出。通过e-功能（彩色曲线）内插的布尔网络连接（AND，OR，NOT）动态仿真; EGFR和c-MET的共表达导致吉非替尼抗性的增加增殖（鲑曲线）和广告的指示关于任意时间点8（B）后细胞凋亡（紫色线）的ecrease。潜在的治疗铲球都PI3K和MEK抑制剂所（黄色曲线下，相同的激活，见协议）。（C） <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/53885/53885fig6large.jpg" target="_blank">请点击此处查看该图的放大版本。</a>

Watch this Scientific Journal Video about A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds at JoVE.com

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

We present a three-dimensional (3D) lung cancer model based on a biological collagen scaffold to study sensitivity towards non-small-cell-lung-cancer-(NSCLC)-targeted therapies. We demonstrate different read-out techniques to determine the proliferation index, apoptosis and epithelial-mesenchymal transition (EMT) status. Collected data are integrated into an in silico model for prediction of drug sensitivity.

一种混合的3D组织工程<em&gt;体外</em&gt; /<em&gt;在硅片</em在具体的突变背景预测药物的有效性&gt;肺肿瘤模型

In the present study, we combined an in vitro 3D lung tumor model with an in silico model to optimize predictions of drug response based on a specific ...

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Universidad San Sebastian

Research

JoVE Journal

Bioengineering

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

10.1K 次观看.  University Hospital Wuerzburg. We present a three-dimensional (3D) lung cancer model based on a biological collagen scaffold to study sensitivity towards non-small-cell-lung-cancer-(NSCLC)-targeted therapies. We demonstrate different read-out techniques to determine the proliferation index, apoptosis and epithelial-mesenchymal transition (EMT) status. Collected data are integrated into an in silico model for prediction of drug sensitivity. 

视频: A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

Acellular and Cellular Lung Model to Study Tumor Metastasis

It is difficult to isolate tumor cells at different points of tumor progression. We created an ex vivo lung model that can show the interaction of tumor cells with a natural matrix and continual flow of nutrients, as well as a model that shows the interaction of tumor cells with normal cellular components and a natural matrix. The acellular ex vivo lung model is created by isolating a rat heart-lung block and removing all the cells using the decellularization process. The right main bronchus is tied off and tumor cells are placed in the trachea by a syringe. The cells move and populate the left lung. The lung is then placed in a bioreactor where the pulmonary artery receives a continual flow of media in a closed circuit. The tumor grown on the left lung is the primary tumor. The tumor cells that are isolated in the circulating media are circulating tumor cells and the tumor cells in the right lung are metastatic lesions. The cellular ex vivo lung model is created by skipping the decellularization process. Each model can be used to answer different research questions.

Here, we present a protocol for an ex vivo lung cancer model that mimics the steps of tumor progression and helps to isolate a primary tumor, circulating tumor cells, and metastatic lesions.

脱细胞和细胞肺模型研究肿瘤转移

It is difficult to isolate tumor cells at different points of tumor progression. We created an ex vivo lung model that can show the interaction of tumor ...

科研

癌症研究

Tissue Engineering of a Human 3D in vitro Tumor Test System

Cancer is one of the leading causes of death worldwide. Current therapeutic strategies are predominantly developed in 2D culture systems, which inadequately reflect physiological conditions in vivo. Biological 3D matrices provide cells an environment in which cells can self-organize, allowing the study of tissue organization and cell differentiation. Such scaffolds can be seeded with a mixture of different cell types to study direct 3D cell-cell-interactions. To mimic the 3D complexity of cancer tumors, our group has developed a 3D in vitro tumor test system.	
	Our 3D tissue test system models the in vivo situation of malignant peripheral nerve sheath tumors (MPNSTs), which we established with our decellularized porcine jejunal segment derived biological vascularized scaffold (BioVaSc). In our model, we reseeded a modified BioVaSc matrix with primary fibroblasts, microvascular endothelial cells (mvECs) and the S462 tumor cell line. For static culture, the vascular structure of the BioVaSc is removed and the remaining scaffold is cut open on one side (Small Intestinal Submucosa SIS-Muc). The resulting matrix is then fixed between two metal rings (cell crowns).	
	Another option is to culture the cell-seeded SIS-Muc in a flow bioreactor system that exposes the cells to shear stress. Here, the bioreactor is connected to a peristaltic pump in a self-constructed incubator. A computer regulates the arterial oxygen and nutrient supply via parameters such as blood pressure, temperature, and flow rate. This setup allows for a dynamic culture with either pressure-regulated pulsatile or constant flow.	
	In this study, we could successfully establish both a static and dynamic 3D culture system for MPNSTs. The ability to model cancer tumors in a more natural 3D environment will enable the discovery, testing, and validation of future pharmaceuticals in a human-like model.

Tissue Engineering of a Human 3D in vitro Tumor Test System

Methods to create human 3D tumor tissues as test systems are described. These technologies are based on a decellularized Biological Vascularized Scaffold (BioVaSc), primary human cells and a tumor cell line, which can be cultured under static as well as under dynamic conditions in a flow bioreactor.

一个人的3D组织工程<em&gt;在体外</em&gt;肿瘤测试系统

Cancer is one of the leading causes of death worldwide.  Current therapeutic strategies are predominantly developed in 2D culture  systems, which ...

生物工程

Multidimensional Coculture System to Model Lung Squamous Carcinoma Progression

Tumor-stroma interactions play a critical role in the development of lung squamous carcinoma (LUSC). However, understanding how these dynamic interactions contribute to tissue architectural changes observed during tumorigenesis remains challenging due to the lack of appropriate models. In this protocol, we describe the generation of a 3D coculture model using a LUSC primary cell culture known as TUM622. TUM622 cells were established from a LUSC patient-derived xenograft (PDX) and have the unique property to form acinar-like structures when seeded in a basement membrane matrix. We demonstrate that TUM622 acini in 3D coculture recapitulate key features of tissue architecture during LUSC progression as well as the dynamic interactions between LUSC cells and components of the tumor microenvironment (TME), including the extracellular matrix (ECM) and cancer-associated fibroblasts (CAFs). We further adapt our principal 3D culturing protocol to demonstrate how this system could be utilized for various downstream analyses. Overall, this organoid model creates a biologically rich and adaptable platform that enables one to gain insight into the cell-intrinsic and extrinsic mechanisms that promote the disruption of epithelial architectures during carcinoma progression and will aid the search for new therapeutic targets and diagnostic markers.

An in vitro model system was developed to capture tissue architectural changes during lung squamous carcinoma (LUSC) progression in a 3-dimensional (3D) co-culture with cancer-associated fibroblasts (CAFs). This organoid system provides a unique platform to investigate the roles of diverse tumor cell-intrinsic and extrinsic changes that modulate the tumor phenotype.

多维共同培养系统模拟肺鳞癌进展

Tumor-stroma interactions play a critical role in the development of lung squamous carcinoma (LUSC). However, understanding how these dynamic interactions ...

Measuring Real-time Drug Response in Organotypic Tumor Tissue Slices

Tumor tissues are composed of cancerous cells, infiltrated immune cells, endothelial cells, fibroblasts, and extracellular matrix. This complex milieu constitutes the tumor microenvironment (TME) and can modulate response to therapy in vivo or drug response ex vivo. Conventional cancer drug discovery screens are carried out on cells cultured in a monolayer, a system critically lacking the influence of TME. Thus, experimental systems that integrate sensitive and high-throughput assays with physiological TME will strengthen the preclinical drug discovery process. Here, we introduce ex vivo tumor tissue slice culture as a platform for medium-high-throughput drug screening. Organotypic tissue slice culture constitutes precisely-cut, thin tumor sections that are maintained with the support of a porous membrane in a liquid-air interface. In this protocol, we describe the preparation and maintenance of tissue slices prepared from mouse tumors and tumors from patient-derived xenograft (PDX) models. To assess changes in tissue viability in response to drug treatment, we leveraged a biocompatible luminescence-based viability assay that enables real-time, rapid, and sensitive measurement of viable cells in the tissue. Using this platform, we evaluated dose-dependent responses of tissue slices to the multi-kinase inhibitor, staurosporine, and cytotoxic agent, doxorubicin. Further, we demonstrate the application of tissue slices for ex vivo pharmacology by screening 17 clinical and preclinical drugs on tissue slices prepared from a single PDX tumor. Our physiologically-relevant, highly-sensitive, and robust ex vivo screening platform will greatly strengthen preclinical oncology drug discovery and treatment decision making.&#160;

We introduce a protocol for measuring real-time drug response in organotypic tumor tissue slices. The experimental strategy outlined here provides a platform to carry out medium-high throughput drug screens on tissue slices derived from clinical or mouse tumors in ex vivo conditions.

测量组织肿瘤组织切片的实时药物反应

Tumor tissues are composed of cancerous cells, infiltrated immune cells, endothelial cells, fibroblasts, and extracellular matrix. This complex milieu ...

Monitoring Cancer Cell Invasion and T-Cell Cytotoxicity in 3D Culture

Significant progress has been made in treating cancer with immunotherapy, although a large number of cancers remain resistant to treatment. A limited number of assays allow for direct monitoring and mechanistic insights into the interactions between tumor and immune cells, amongst which, T-cells play a significant role in executing the cytotoxic response of the adaptive immune system to cancer cells. Most assays are based on two-dimensional (2D) co-culture of cells due to the relative ease of use but with limited representation of the invasive growth phenotype, one of the hallmarks of cancer cells. Current three-dimensional (3D) co-culture systems either require special equipment or separate monitoring for invasion of co-cultured cancer cells and interacting T-cells.
Here we describe an approach to simultaneously monitor the invasive behavior in 3D of cancer cell spheroids and T-cell cytotoxicity in co-culture. Spheroid formation is driven by enhanced cell-cell interactions in scaffold-free agarose microwell casts with U-shaped bottoms. Both T-cell co-culture and cancer cell invasion into type I collagen matrix are performed within the microwells of the agarose casts without the need to transfer the cells, thus maintaining an intact 3D co-culture system throughout the assay. The collagen matrix can be separated from the agarose cast, allowing for immunofluorescence (IF) staining and for confocal imaging of cells. Also, cells can be isolated for further growth or subjected to analyses such as for gene expression or fluorescence activated cell sorting (FACS). Finally, the 3D co-culture can be analyzed by immunohistochemistry (IHC) after embedding and sectioning. Possible modifications of the assay include altered compositions of the extracellular matrix (ECM) as well as the inclusion of different stromal or immune cells with the cancer cells.

The presented approach simultaneously evaluates cancer cell invasion in 3D spheroid assays and T-cell cytotoxicity. Spheroids are generated in a scaffold-free agarose multi-microwell cast. Co-culture and embedding in type I collagen matrix are performed within the same device which allows to monitor cancer cell invasion and T-cell mediated cytotoxicity.

监测三D培养中的癌细胞入侵和T细胞毒性

Significant progress has been made in treating cancer with immunotherapy, although a large number of cancers remain resistant to treatment. A limited ...

Assessment of Mitochondrial Health in Cancer-Associated Fibroblasts Isolated from 3D Multicellular Lung Tumor Spheroids

Cancer-associated fibroblasts (CAFs) are among the most abundant stromal cells present in the tumor microenvironment, facilitating tumor growth and progression. Complexity within the tumor microenvironment, including tumor secretome, low-grade inflammation, hypoxia, and redox imbalance, fosters heterotypic interaction and allows the transformation of inactive resident fibroblasts to become active CAFs. CAFs are metabolically distinguished from normal fibroblasts (NFs) as they are more glycolytically active, produce higher levels of reactive oxygen species (ROS), and overexpress lactate exporter MCT-4, leading to the opening of the mitochondrial permeability transition pore (MPTP). Here a method has been described to analyze the mitochondrial health of activated CAFs isolated from the multicellular 3D tumor spheroids comprising of human lung adenocarcinoma cells (A549), human monocytes (THP-1), and human lung fibroblast cells (MRC5). Tumor spheroids were disintegrated at different time intervals and through magnetic-activated cell sorting, CAFs were isolated. The mitochondrial membrane potential of CAFs was assessed using JC-1 dye, ROS production by 2',7'-dichlorodihydrofluorescein diacetate (DCFDA) staining, and enzyme activity in the isolated CAFs. Analyzing the mitochondrial health of isolated CAFs provides a better understanding of the reverse Warburg effect and can also be applied to study the consequences of CAF mitochondrial changes, such as metabolic fluxes and the corresponding regulatory mechanisms on lung cancer heterogeneity. Thus, the present study advocates an understanding of tumor-stroma interactions on mitochondrial health. It would provide a platform to check mitochondrial-specific drug candidates for their efficacies against CAFs as potential therapeutics in the tumor microenvironment, thereby preventing CAF involvement in lung cancer progression.

Multicellular 3D tumor spheroids were prepared with lung adenocarcinoma cells, fibroblasts, and monocytes, followed by the isolation of cancer-associated fibroblasts (CAFs) from these spheroids. Isolated CAFs were compared with normal fibroblasts to assess mitochondrial health by studying the mitochondrial transmembrane potential, reactive oxygen species, and enzymatic activities.

评估从3D多细胞肺肿瘤球体中分离的癌症相关成纤维细胞的线粒体健康

Cancer-associated fibroblasts (CAFs) are among the most abundant stromal cells present in the tumor microenvironment, facilitating tumor growth and ...

Establishing 3-Dimensional Spheroids from Patient-Derived Tumor Samples and Evaluating their Sensitivity to Drugs

Despite remarkable advances in understanding tumor biology, the vast majority of oncology drug candidates entering clinical trials fail, often due to a lack of clinical efficacy. This high failure rate illuminates the inability of the current preclinical models to predict clinical efficacy, mainly due to their inadequacy in reflecting tumor heterogeneity and the tumor microenvironment. These limitations can be addressed with 3-dimensional (3D) culture models (spheroids) established from human tumor samples derived from individual patients. These 3D cultures represent real-world biology better than established cell lines that do not reflect tumor heterogeneity. Furthermore, 3D cultures are better than 2-dimensional (2D) culture models (monolayer structures) since they replicate elements of the tumor environment, such as hypoxia, necrosis, and cell adhesion, and preserve the natural cell shape and growth. In the present study, a method was developed for preparing primary cultures of cancer cells from individual patients that are 3D and grow in multicellular spheroids. The cells can be derived directly from patient tumors or patient-derived xenografts. The method is widely applicable to solid tumors (e.g., colon, breast, and lung) and is also cost-effective, as it can be performed in its entirety in a typical cancer research/cell biology lab without relying on specialized equipment. Herein, a protocol is presented for generating 3D tumor culture models (multicellular spheroids) from primary cancer cells and evaluating their sensitivity to drugs using two complementary approaches: a cell-viability assay (MTT) and microscopic examinations. These multicellular spheroids can be used to assess potential drug candidates, identify potential biomarkers or therapeutic targets, and investigate the mechanisms of response and resistance.

The present protocol describes generating 3D tumor culture models from primary cancer cells and evaluating their sensitivity to drugs using cell-viability assays and microscopic examinations.

从患者来源的肿瘤样本中建立三维微球并评估其对药物的敏感性

Despite remarkable advances in understanding tumor biology, the vast majority of oncology drug candidates entering clinical trials fail, often due to a ...

Generation of 3D Tumor Spheroids for Drug Evaluation Studies

In recent decades, in addition to monolayer-cultured cells, three-dimensional tumor spheroids have been developed as a potentially powerful tool for the evaluation of anticancer drugs. However, the conventional culture methods lack the ability to manipulate the tumor spheroids in a homogeneous manner at the three-dimensional level. To address this limitation, in this paper, we present a convenient and effective method of constructing average-sized tumor spheroids. Additionally, we describe a method of image-based analysis using artificial intelligence-based analysis software that can scan the whole plate and obtain data on three-dimensional spheroids. Several parameters were studied. By using a standard method of tumor spheroid construction and a high-throughput imaging and analysis system, the effectiveness and accuracy of drug tests performed on three-dimensional spheroids can be dramatically increased.

This article demonstrates a standardized method for constructing three-dimensional tumor spheroids. A strategy for spheroid observation and image-based deep-learning analysis using an automated imaging system is also described.

生成用于药物评估研究的 3D 肿瘤微球

In recent decades, in addition to monolayer-cultured cells, three-dimensional tumor spheroids have been developed as a potentially powerful tool for the ...

制备基于微流体的血管化人类微肿瘤模型

Establishing a Physiologic Human Vascularized Micro-Tumor Model for Cancer Research

A lack of validated cancer models that recapitulate the tumor microenvironment of solid cancers in vitro remains a significant bottleneck for preclinical cancer research and therapeutic development.&#160;To overcome this problem, we have developed the vascularized microtumor (VMT), or tumor chip, a microphysiological system that realistically models the complex human tumor microenvironment. The VMT forms de novo within a microfluidic platform by co-culture of multiple human cell types under dynamic, physiological flow conditions. This tissue-engineered micro-tumor construct incorporates a living perfused vascular network that supports the growing tumor mass just as newly formed vessels do in vivo. Importantly, drugs and immune cells must cross the endothelial layer to reach the tumor, modeling in vivo physiological barriers to therapeutic delivery and efficacy. Since the VMT platform is optically transparent, high-resolution imaging of dynamic processes such as immune cell extravasation and metastasis can be achieved with direct visualization of fluorescently labeled cells within the tissue. Further, the VMT retains in vivo tumor heterogeneity, gene expression signatures, and drug responses. Virtually any tumor type can be adapted to the platform, and primary cells from fresh surgical tissues grow and respond to drug treatment in the VMT, paving the way toward truly personalized medicine. Here, the methods for establishing the VMT and utilizing it for oncology research are outlined. This innovative approach opens new possibilities for studying tumors and drug responses, providing researchers with a powerful tool to advance cancer research.

作者聚焦：创建人类血管化微肿瘤作为转化癌症研究的模型 

This protocol presents a physiologically relevant tumor-on-a-chip model to perform high-throughput basic and translational human cancer research, advancing drug screening, disease modeling, and personalized medicine approaches with a description of loading, maintenance, and evaluation procedures.

建立用于癌症研究的生理性人血管化微肿瘤模型

A lack of validated cancer models that recapitulate the tumor microenvironment of solid cancers in vitro remains a significant bottleneck for preclinical ...

一种混合的3D组织工程

摘要

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此视频中的章节

脱细胞和细胞肺模型研究肿瘤转移

一个人的3D组织工程

多维共同培养系统模拟肺鳞癌进展

测量组织肿瘤组织切片的实时药物反应

监测三D培养中的癌细胞入侵和T细胞毒性

评估从3D多细胞肺肿瘤球体中分离的癌症相关成纤维细胞的线粒体健康

从患者来源的肿瘤样本中建立三维微球并评估其对药物的敏感性

生成用于药物评估研究的 3D 肿瘤微球

建立用于癌症研究的生理性人血管化微肿瘤模型

建立用于癌症研究的生理性人血管化微肿瘤模型