The authors would like to acknowledge prof. J.J. McGuire, prof. R. Kofler and dr. K. Quint for providing the resistant cell lines used in this work. The study has been founded by grants from Cancer Center Amsterdam (CCA) Foundation (to JC, EG and RS), the KiKa (Children Cancer-free grant for AW) foundation, the Law Offices of Peter G. Angelos Grant from the Mesothelioma Applied Research Foundation (to VEG and EG), Associazione Italiana per la Ricerca sul Cancro (AIRC), Istituto Toscano Tumori (ITT), and Regione Toscana Bando FAS Salute (to EG).

1.通过细胞毒性分析耐药性型材的表征<ol><li> 白血病细胞株培养 <ol><li>保持亲T细胞在10ml RPMI-1640培养基含有ALL细胞系CCRF-CEM（CEM-WT），以及其药物抗性亚系，包括CEM / R30dm，CEM-R5和CEM-C3，25 平方厘米2.3μM叶酸补充有10％胎牛血清和100单位/ ml青霉素G和100μg/ ml链霉素。 </li><li>培养在5％CO 2培养箱将细胞在湿润气氛中，在37℃。 </li><li>允许2之间细胞生长的浓度- 3×10 6细胞/毫升。 </li><li>每周分裂细胞两次以0.3×10 6细胞/ ml的初始浓度（ 例如，如果细胞浓度为3×10 6个细胞/ ml，在由9毫升新鲜培养基的新烧瓶传送1毫升细胞悬浮液）。经过连续20代丢弃文化。 </li></ol></LI&gt; <li> 胰腺癌细胞株培养 注:保持在75cm 2的培养瓶中的人胰腺癌细胞株的Panc-1在具有高葡萄糖和L-谷氨酰胺补充有10％胎牛血清和100单位/ ml青霉素G和100μg/ ml链霉素10毫升DMEM培养基。耐药变种，PANC-1R，是在含有1μM的吉西他滨溶解在无菌水中的相同培养基中培养。在24提供进一步的细节。 <ol><li>培养在5％CO 2培养箱将细胞在37℃。 </li><li>分裂细胞，每2 - 1天以1:5的比例时，细胞达到约90％汇合。 </li><li>分裂的细胞，用磷酸盐缓冲盐水（PBS）洗两次，每75cm 2的培养瓶中加入1ml胰蛋白酶/ EDTA中，并在37℃孵育3分钟。 </li><li>再加9毫升培养基和收获分离的细胞在15毫升管。在一个新的烧瓶CONTA种子2毫升细胞悬浮液进不去8毫升网上平台。经过连续20代丢弃文化。 </li></ol></li><li> MTT法对白血病细胞 <ol><li>预先制备的MTT溶液:溶于10毫升的PBS 500毫克MTT甲和搅拌（避光）用磁力搅拌器搅拌约1小时。消毒用0.22微米过滤器的溶液。注:该解决方案可以在-20℃储存在10毫升等分试样。解冻后直接避光。 </li><li>提前准备酸化异丙醇:加50毫升2 M盐酸至2.5升异丙醇。注意:使用前在室温下存放的解决方案，至少一个月。如果异丙醇没有被正确酸化，它可能形成具有介质沉淀并危及光度法读数。 </li><li>准备一个单独的96孔平底"第0天"（对照）板，以确保生长抑制的更准确的估计:奉献每个细胞系3至6个孔中，添加30微升的增长平台和120微升每孔150微升生长培养基的细胞悬浮液（8000个细胞）的对应于空白（无细胞）的孔中。从步骤1.3.9进行到步骤1.3.13本条以测量光密度（OD）。注:在4中提供进一步的细节。 </li><li>准备96孔平底试验板:奉献30口井，以药物的浓度（10个浓度，每个一式三份），10口井，以控制细胞和10个孔，以控制无细胞（空白）中，并准备地塞米松的一种药物稀释范围（地塞米松），使用二甲基亚砜作为溶剂。 注:对于CEM-WT细胞的地塞米松稀释范围为2微米和0.97纳米。对于CEM / R30dm，CEM-R5和CEM-C3细胞的地塞米松稀释范围为640微米和0.33纳米之间。 </li><li>添加从每塞米松稀释30微升到96孔板的适当孔。确保包括在一式三份的每个浓度。 </li><li>添加生长培养基的30μl到井的相应对照细胞和150微升生长培养基的对应于空白孔中。 </li><li>收获指数生长的细胞，重悬在其最佳接种浓度。 注意:为了确定最佳的起始细胞浓度时，建议通过在几个浓度接种细胞，并每日测量它为至少4天，以评估在一个96孔板的每个细胞系的细胞系的生长曲线。选择一个播种浓度，防止细胞的过度生长72小时后，因为这将通过饱和OD值影响的实验。对于CEM-WT，CEM-C5和CEM-R5的最佳接种浓度为8000个/孔，而CEM / R30dm是5,000个细胞/孔。 </li><li>添加120微升细胞悬液，以每孔含有任一药液或生长培养基（孔对应于控制单元）。填用150微升的PBS板的空外孔中以保证良好的湿度在所述板孵育第Ë板在37℃，5％的CO 2在细胞培养孵化72小时。 </li><li>添加15微升MTT溶液的各孔中，摇动板5分钟用板摇床最多900摇动/分钟。 </li><li>放置板背面，在37℃，5％的CO 2在细胞培养培养箱孵育另外4 - 6小时。 </li><li>添加150微升酸化异丙醇至每个孔，并用多道移液器拌匀彻底悬浮所有甲晶体。开始与空白孔，并确保在进行到板的另一行之前很好地漂洗提示。 </li><li>孵育在室温下（RT）的板10分钟。 </li><li>用酶标仪，确定的OD在540nm和720nm处通过校正背景外径，以确保准确的测量。然后在电子表格文件保存数据和分析4。 </li></ol></li><li> SRB法对胰腺癌细胞 <ol><li>以0.4％的最终浓度溶解在1％乙酸的SRB试剂（重量/体积）。 </li><li>在50％的最终浓度溶解在超纯水中三氯乙酸（TCA）（重量/体积）。 </li><li>溶解在超纯水中的Tris（羟甲基）氨基甲烷在10毫最终浓度。 </li><li>准备一个单独的96孔平底"第0天"控制盘，以确保生长抑制的更准确的估计:种子6个孔在适当的接种浓度在100μl培养基中指数期生长的细胞和100μl的培养基只添加到对应于井空白。在37℃用5％CO 2孵育过夜，以确保细胞在板的适当的粘合性。然后100微升中添加到所有井，并继续步骤1.4.8 - 1.4.16本节。 </li><li>准备96孔平底试验板:种子细胞在适当的密度生长在指数生长期中，一式三份在96孔平底板在100μl我的通过使用多通道移液管dium。 注意:为了确定最佳的起始细胞浓度时，建议通过在几个浓度接种细胞，并每日测量它为至少4天，以评估在一个96孔板的每个细胞系的细胞系的生长曲线。选择一个播种浓度，防止细胞的过度生长72小时后，因为这将通过饱和OD值影响的实验。对的Panc-1和PANC-1R的细胞，最优接种浓度为8000细胞/孔。 </li><li>将100μl培养基添加至中只孔中，在37℃用5％CO 2孵育过夜，以确保细胞在板的适当的粘合性。 </li><li>制备为1μM和10nM之间的吉西他滨的药物稀释范围的Panc-1和1mM和100nM为的Panc-1R的细胞。通过使用多通道移液管加入从每个稀释100微升到96孔板的适当孔。确保有一式三份每个浓度。此外，将100μl培养基添加至中只有井和对照细胞。在37℃下孵育，用5％CO 2的72小时。 </li><li>通过使用多通道移液管为至少60分钟，在4℃以沉淀，并在孔的底部固定所述蛋白质添加25μl的冷TCA溶液到孔中并孵育所述板。 </li><li>通过在组织除去培养基并干燥简要地清空板。 </li><li>洗5次用自来水，然后清空板，并让在室温下干燥。 </li><li>通过使用重复-吸管和染色，在室温下15分钟加入每孔50μl的SRB溶液。 </li><li>通过去除污渍SRB空板。 </li><li>洗4次，用1％乙酸再清空板，并让它干燥在室温。 </li><li>添加每孔150μl的Tris溶液通过使用多通道移液管和用于在平板摇床最多3分钟混合到最大的900摇动/分钟。 </li><li>读出的光密度在540nm（或如果492nm处吨他OD值过高）。 </li><li>分析数据。 </li></ol></li><li> 数据分析MTT和SRB测定 <ol><li>计算细胞的OD值在"0天"使用下列公式:OD 第0天 = OD 对照细胞 -平均OD 空白孔 </li><li>根据下列公式计算存活的细胞的百分比为每个药物浓度:％治疗细胞=平均[OD 处理的细胞 -平均OD 空白孔 - OD 第0天 ] / [OD 对照细胞 -平均OD 空白孔 -外径Day0] * 100 </li><li>绘制剂量反应曲线（药物浓度 - 在％生长抑制）。 </li><li>计算使用剂量-响应曲线，该曲线的50％抑制细胞生长的药物（IC 50）的浓度。 </li></ol></li></ol> 2. RNA分离和图书馆准备RNA测序<ol><li> 样品科尔挠度和RNA分离<ol><li>对于CEM细胞:直接从培养基中收获10 6个细胞。 </li><li>对的Panc-1和PANC-1R:除去介质，用PBS洗涤细胞两次，并通过添加胰蛋白酶-EDTA，并在37℃孵育3分钟分离。添加培养基和收获10 6个细胞。 </li><li>降速样品在300 XG 3分钟，除去上清液，用市售的二氧化硅膜离心柱，遵循manufacturer`s协议提取总RNA。 </li><li>通过使用紫外可见分光光度计测定总RNA的浓度和纯度。 注:RNA被认为是高纯度的，如果260纳米/ 280nm吸收比高于1.8。样品可以储存在 - 80℃。 </li><li>评估通过在用溴化乙锭染色的1％琼脂糖凝胶200毫​​微克的样品的电泳总RNA的完整性。 注:两种完整频带的对应于哺乳动物28S和18S个rRNA在约的检测2 kb和1 KB的大小指示良好的总RNA的完整性。 </li></ol></li><li> 测序文库制备 <ol><li>使用2微克每每个样品总mRNA的。根据制造商的说明按照mRNA的文库制备协议。 </li><li>通过使用生物分析系统确定每个库的质量和浓度。池单个样品上在库10 nmol / L的终浓度，并与生物分析仪测量。 </li><li>使用高通量测序系统的单读100个基点模式。 注:&gt; 80碱基的读取长度是必要的识别转录亚型。 </li></ol></li></ol> 3.不同的剪接检测从测序读<ol><li> 对准读取到参考基因组和质量检查 <ol><li>编译使用UCSC表浏览器（25963个基因）在NCBI refGene表中的基因注释（.gtf文件）。 </li><li>演出测序注释感知缺口对准读取使用STAR的参考基因组（GRCh37）。 </li><li>排序和指数与皮卡德工具所产生的调整文件。 </li><li>通过使用RSeQC和samtools执行映射后的质量控制。 </li></ol></li><li> 样品组之间的差异剪接检测 <ol><li>安装Python和numpy的和SciPy的相应版本。下载并安装samtools。下载并安装领结和高顶礼帽， </li><li>添加了Python，领结，高顶礼帽和samtools目录到$ PATH环境变量。下载预建领结指数（hg19）。下载rMATS版本3.0.9。 注意:在图19和34中提供了关于rMATS进一步细节。 </li><li>奔跑根据图5A通过比较每个塞米松抗性细胞系CEM-WT和PANC-1到的Panc-1R在单独MATS检测选择性剪接事件。 </li><li>检测从previo差别剪接事件usly对齐测序读数（.bam文件），使用这样的命令从图5B为CEM-WT与CEM-C3，CEM-WT与CEM-R 5，CEM-WT与CEM / R30dm和PANC1到Panc-运行MATS 1R比较。 注:MATS将创建一个输出文件夹与每个拼接分析事件的类型结果两项.txt文件（SE - 外显子跳跃，A5SS - 替代5&#39;剪接位点，A3SS - 替代3&#39;剪接位点，MEX - 相互排斥的外显子和RI - 内含子保留）:仅基于结计数和与基于结计数结果的第二文件一个文件含有的结果，并读取关于目标。此外，在同一文件夹中生成一个结果概要的附加.txt文件。 </li><li>对于SE，A5SS，A3SS和RI导入到电子表格基于结计数的.txt文件，读取目标。对于MEX进口仅基于结计数.txt文件。 注:MATS输出文件将被上升的P值和分类包含几个参数:基因身份证，基因符号，染色体和链位置，可变剪接片段的基因组坐标，计数以及夹杂物的长度和跳过两个分析样品形式，夹杂物的长度和跳过用于标准化，p值，假发现率表格（FDR ），基于标准化的计数和微分包含分数（平均（IncLevel1）每个样品包含水平 - 平均（IncLevel2））。 </li><li>与FDR &lt;进一步验证（ 例如 ，DDX5和PKM2）10％选择统计学显著的候选基因。 </li><li>可视化与结合基因组浏览器选择性剪接事件（IGV，https://www.broadinstitute.org/igv/），据报道在图5中。 </li></ol></li></ol> 4.验证通过RT-PCR和定量RT-PCR测定法的结果的<ol><li> 引物设计 注意:为了提供使用生物信息学管道中，mRNA反式获得的结果的一个可靠的验证从选择性剪接事件产生的cripts通过使用RT-PCR扩增和PCR产物的琼脂糖凝胶电泳可视化。花青绿色染料如SYBR绿定量RT-PCR分析被用于量化特定剪接变体相对于管家基因。 图7描绘了施加到形象化DDX5基因的外显子12跳跃事件和量化PKM基因的互斥外显子9和外显子10中的策略。 <ol><li>用于RT-PCR测定法，设计引物对退火到位于上游构外显子（外显子10和外显子13）和下游的可变剪接位点（ 图7A）。 注:扩增子大小应涵盖碱基100和800之间，以确保该预测PCR产物在琼脂糖凝胶上的明确分离。引物的退火温度应在55和65℃，GC含量°之间不应超过60％。 </li><li>花青绿测定（ 图7B）。 <ol&gt; <li>检查两个相互排斥的外显子和设计2种引物对每个具体的序列同源性，只有专门检测两个剪接变体中的一个。 注:对于PKM，反向引物退火到外显子共同11到两个变体，而正向引物变体特异性和退火外显子9（PKM1）或外显子10（PKM2）。 </li><li>为了检测DDX5全长基因，退火跳过外显子（外显子12）内的反向引物。 注:对于DDX5ΔEx12变体的特异性检测，反向引物横跨exon11 / exon13的边界。使用相同的正向引物退火组成的外显子10两个反应。 注:扩增子大小应在80和200碱基对之间。 </li></ol></li></ol></li><li> 第一链cDNA合成 <ol><li>设置的分离的RNA，以cDNA的1微克逆转录用200U /微升莫洛尼鼠白血病病毒的（M-MLV）逆向工程＆在其反应缓冲液本身酶1:5稀释用无菌水。添加DTT1μM的，随机六聚体的0.05微克，脱氧核苷酸的混合物（dNTP）1毫米，和核糖核酸酶抑制剂40U /微升。 </li><li>短暂涡旋并孵育反应混合物在37℃下2小时。 </li><li>孵育反应混合物在70℃下进行5分钟以灭活逆转录酶，在冰上转移混合，并通过使用微量离心。样品可以立即使用或储存于 - 20℃。 </li></ol></li><li> RT-PCR反应和琼脂糖凝胶 <ol><li>通过混合12.5微升2×的设置在每各样品在PCR管中进行PCR反应浓缩的PCR mastermix，1.25微升10μM的正向引物和同量为反向引物达25微升无菌水的终体积。 </li><li>加入1μl的cDNA的组合，然后将试管中的热循环。运行该程序如下:初始变性:95℃2分钟。重申下述步骤35个循环:变性95℃25秒;退火52℃35秒;延伸72℃1分钟。在72℃下5分钟，设置最终延伸。 </li><li>将1g琼脂糖溶解在100毫升1×TBE缓冲液制备1％琼脂糖凝胶。添加2.5微升的溴化乙锭的溶液中。注意:溴化乙锭是致癌物质，通过化学通风柜谨慎操作。 </li><li>加载样品和在100伏运行在1×TBE缓冲液的凝胶用于在电泳系统约30分钟。 </li><li>显示用数码相机UV胶并保存图像。 </li></ol></li><li> 定量RT-PCR和数据分析 <ol><li>设置每各样品的花青绿色PCR反应由混合12.5微升2×绿色的PCR反应体系的，2微升5微米正向引物和相同数量的反向引物达15微升无菌水在一PCR管的终体积。制备混合为每个特定的拼接变被检测到（PKM1，PKM2，DDX5全长，DDX5ΔEx12）和管家基因（GUS）。 </li><li>装载在白色96孔板的mastermix并准备每各样品重复。 </li><li>稀释10倍的cDNA在水中，加入5微升到每个组合，然后将盘在热循环。运行该程序如下:初始变性:95℃5分钟。重申下述步骤45个循环:变性95℃，10秒;退火在58℃（对DDX5和DDX5ΔEx12混合）或20秒60℃（对PKM1和PKM2混合）。在72℃，20秒的设定最终延伸。设置通过施加梯度从65到97℃熔化曲线。 </li><li>为了引物组的特异性评估他们的目标，则检查熔解曲线，并验证单峰每各引物组而形成的。 </li><li>计算扩增曲线的二阶导数的值，并导出周期阈值（CT）。 </li><li> CALCULATE中的mRNA剪接的相对表达水平（REL）的变体相比，GUS看家（参考）基因，通过使用"增量的Ct（ΔCT）"的方法的每个样本。其计算公式为:REL = 2 - ΔCT，其中ΔCT=的Ct 目标剪接变异体 -的Ct 参照基因 </li><li>为了量化剪接变体的相对丰度，通过使用公式计算REL比例:比例REL比= REL 剪接变体1 / REL 剪接变体2。 </li></ol></li></ol>

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J., Jansen, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Classification+of+ex+vivo+methotrexate+resistance+in+acute+lymphoblastic+and+myeloid+leukaemia.">Classification of ex vivo methotrexate resistance in acute lymphoblastic and myeloid leukaemia.</a> Br J Haematol. 110 (4), 791-800 (2000).</li><li>Funel, N., 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=Laser+microdissection+and+primary+cell+cultures+improve+pharmacogenetic+analysis+in+pancreatic+adenocarcinoma.">Laser microdissection and primary cell cultures improve pharmacogenetic analysis in pancreatic adenocarcinoma.</a> Lab Invest. 88 (7), 773-784 (2008).</li><li>Gillet, J. 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The authors have nothing to disclose.

这里，我们介绍，结合成熟的细胞毒性筛选技术和功能强大的基于NGS-转录分析，以鉴别与耐药性差异剪接事件的新方法。分光光度测定法是方便和健壮高通量方法，以评估在体外癌症模型药物敏感性和代表第一选择许多实验室进行的细胞毒性筛查。故障诊断以及用于此方法的可能变化被广泛别处4,5-说明。 高通量基因组分析目前用于探索耐药机制主要依靠单核苷酸多态性检测和差分具有一定的耐药表型相关基因的表达估计。在这项研究中，我们描述了使用的RNA测序方法，再加上强大的生物信息学管道的mRNA转录的精确注释和DIF检测髓鞘拼接。所描述的协议的一个特别重要的特征是，以确定具有不同药物的敏感性型材两个样品组之间新的剪接变体的能力。其中的一个准确，公正的分析，关键步骤是RNA的分离，它必须是高纯度和完整性。 MATS是一系列可用的类似的生物信息学工具，我们选择软件（ 例如，Cuffdiff 2，DEXseq，DiffSplice和拼接指南针）检测选择性剪接18。这使它成为首选的主要主要特点是其卓越的精密度和准确度，以及识别新的事件的可能性。 MATS生成两种类型包含输出差别剪接分析的:首先是仅基于外显子连接计数和所述第二基于结计数以及读取目标。而后者是优选的，用于检测外显子跳跃的事件，则建议用于互斥的外显子的分析的第一个选项，因为这种方法降低了假阳性候补数为这种特殊类型的剪接改变的。 此外，用于分析集中于内含子保留，替代3&#39;和5&#39;剪接位点的事件，应使用带注释内含一个.gtf文件。最终，为了减少样本组中的生物和技术变化和确保高真阳性率，强烈建议序列至少三次重复34。基于MATS输出差异剪接的候选基因的选择与使用RT-PCR验证的步骤相结合。这是真阳性变体之间有统计学显著候选人大列表的选择至关重要。一个准确的验证的关键因素是寡核苷酸的设计，并根据分子生物学的标准的PCR反应进行优化。特别注意设计引物跨越外显子 - 外显子连接处和附加验证步骤，如用Sanger法的扩增子的测序时，应采取的，是必要的，以确认它们的特异性。 通过MATS检测DDX5和PKM转录物的差别剪接代表与药物抗性的异常剪接的两个例子。 DDX5ΔEx12未在耐GC-细胞系（CEM-C3和R 5），其已经长时间地塞米松曝光之后被选择表达。 DDX5ΔEx12是在亲代细胞系，而且在亚克隆CEM / R30dm，它被选定为抗性的化疗剂的MTX而非塞米松表达。在癌细胞中，PKM2高表达相比，它的剪接变体PKM1，但比PKM2 / PKM1在塞米松抗性细胞较高，由NGS结果建议。这是不是为PANC-1样本观测相比，其耐吉西他滨对应，实际上，这种候选基因不属此列在MATS分析统计学显著事件。这可能反映了由吉西他滨诱导的曝光耐药的不同细胞类型和机制。 总之，本协议构成剪接变体，其可依据药物抗性和可应用于任一白血病细胞30或实体瘤细胞31的发现一个合适的方法。一个明显的局限性在于肿瘤细胞系仅捕获癌症异质的一小部分。此外，大多数细胞系已经连续多年保持在促生长介质单层。这些条件影响的细胞特征，导致在从原发性肿瘤从它们起源的细胞显着不同亚群的选择。然而，许多所涉及药物抗性的基因也参与其它枢轴细胞功能如细胞生长和细胞凋亡可能由长期culturin受到影响<html>克塑料。因此，为了提高耐药性的研究中，更多的努力应朝向新颖的临床前模型，例如原代培养物和异种移植物的发展定向，即更接近地模拟体内癌症的微环境，以避免在细胞特性的相关变化引起的细胞培养和培养条件的长时间。 32值得注意的是，我们的协议可以也适用于原代细胞，使用细胞毒性试验为了确定离体的IC 50值。另一个限制是，由于用于各抗癌剂存在性的许多机制，电阻的类似的或不同的机制可以在暴露于相同的，但是独立处理的细胞发展。因此，比较选择策略应该包括平行的选择和分析，包括对剪接变异体的遗传分析与同化疗药物处理的相同亲代细胞的。 jove_content"&gt;为功能验证的其他方法应着眼于过表达所关注的剪接变体中的细胞系或特别通过使用RNA干扰或剪接切换寡核苷酸33下调其表达。

尽管在癌症治疗中，恶性细胞抗化疗，无论是本征或在长时间暴露于药物取得相当大的进展，是治疗失败的广泛白血病和实体瘤1的主要原因。 为了描绘耐药背后的机制， 在体外细胞系模型是由癌细胞对化疗药物抗性的逐步选择开发的。这个过程模仿临床设置中使用的制度，因此允许在有关耐药机制深入调查。其生存的治疗抗性细胞，然后从亲敏感细胞使用细胞生存力/细胞毒性试验2区分开。 在原代细胞的体外药物抗性型材已被证明是显著相关临床化疗反应3。 高通量cytotoxicity测定构成一种方便的方法，以确定在体外药物的敏感性。在此，细胞的存活率是通过评估实例的3- [4,5-二甲基-2-基] -2,5-二苯基四唑鎓溴化物- MTT法4，这是基于某些基材的代谢转化（即四唑盐）为有色产物，从而反映细胞的线粒体活性。可替代地，细胞蛋白质含量可以使用磺基罗丹明B（SRB）测定5来量化。这里，活细胞的数目正比于在分光光度计的适当波长测得的光密度（OD），不需要的 广泛而耗时的细胞计数的过程。通过一定的化疗药物诱导的生长抑制可以基于其中细胞用测试试剂处理，并用未处理的对照细胞的OD相比的孔的OD来计算。剂量反应曲线是OBTA通过绘制药物浓度对相对于对照细胞的活细胞的百分比INED。最后，药物敏感性可以报告相比，未经处理的细胞（IC 50），其导致细胞生长抑制50％的浓度。 耐药背后的机制包括许多不同的异常，如影响药物活性和细胞代谢的决定因素的基因表达的改变。这些分子的病变，包括突变，像差在转录和转录后水平以及干扰表观遗传调控往往影响或药物代谢或细胞凋亡6所涉及的基因。 替代前体mRNA剪接和它的复杂调控最近受到相当关注，因为这可能会决定癌细胞7耐药一种新型的实体。达人基因95％交替地在正常细胞通过此手段剪接紧紧从同一基因产生许多不同的蛋白质同种型调节的过程。选择性剪接经常失调在癌症和多种肿瘤都受到了越来越多的涉及药物代谢（ 即 ，脱氧胞苷激酶，叶酰聚谷氨酸合成酶，或者多药耐药蛋白）6,8-基因的改变的剪接特征。然而，耐药细胞的拼接型材综合分析是痛苦的缺乏。因此，当务之急是制定选择性剪接分析的高通量方法。这将有助于开发更有效的治疗方法。 在过去十年中，新一代测序（NGS）技术的快速发展，丰富了新的见解执政基因表达的调控以及它们在不同的生物过程9作用的分子机制的生物医学研究。 RNA的测序（RNA-SEQ）是一个功能强大的子应用程序在转录的字段NGS。它允许一个全基因组分析的数千同时基因的表达模式的（在质量和数量），是非常适合于新的编码mRNA的表征以及长的非编码RNA，miRNA的，siRNA的和其他小RNA类（ 如小核RNA和piRNA基因）10,11。 RNA测序已超过以往技术的转录组特征（ 例如，Sanger测序及表达微阵列）的许多优点。它不是基于现有基因组注释，它具有高分辨率的单核苷酸水平并且它有用于表达水平估计更宽的动态范围。简言之，将RNA测序实验的基本实验流程包括多聚腺苷酸转录（mRNA）的选择和碎片，然后转化成cDNA，图书馆建设，最后，大规模并行深度测序12,13。由于sequencin的快速下降在过去的几年中，RNA-SEQ G值正在逐步取代其他技术，并正在作出显著努力提高图书馆准备协议。例如，现在有可能通过标记用脱氧尿苷三磷酸（dUTP的）和之前，PCR扩增，消化与尿嘧啶DNA-glycosilase化酶（UDG）标记的链的第二链cDNA保留mRNA转录物的链信息。该方法增强了表达水平14,15的基因注释和估计的准确度。 分析和RNA测序数据的解读需要生物信息学管道16,17内的复杂和强大的计算软件包和处理。首先，原料读通过消除技术和生物文物和丢弃（切边），它没有达到严格的质量要求序列进行质量控制。接着各样品的读取映射到参考基因组和索引入基因级，外显子级，或转录级，以便确定每个类别的丰度。根据不同的应用，精制数据，然后通过统计模型进行等位基因特异性表达，剪接，基因融合和单核苷酸多态性（SNP）12的识别来计算。最后，在选定的水平（ 即，基因表达或剪接）的差分分析可以用来比较不同条件下获得的样品。 不同的剪接分析介绍了两个样本之间拼接网站使用的差异。越来越多的用于这一目的的软件包可以根据不同的统计模型，表演和用户接口18。其中，MATS（成绩单拼接的多因素分析）涌现作为基于贝叶斯统计框架免费提供的，精确的计算工具，旨在检测迪菲从单个或配对末端RNA测序数据rential剪接事件。从对齐（.bam）文件开始，MATS可以检测所有主要类型的选择性剪接事件（外显子跳跃，替代3&#39;剪接位点，替代5&#39;剪接位点，互斥的外显子和内含子保留-也参见图1）。 首先，软件识别读取支持一定剪接事件，例如外显子跳跃，并把它们分类成两种类型。 "夹杂读取"（用于规范剪接事件）映射调查外显子内，并且跨越该特定外显子和两个上游和下游侧翼的外显子之间的连接处。 "跳读"（用于选择性剪接事件）跨越两个侧翼外显子之间的交界处。随后，MATS返回纳入规范化水平为规范和替代的事件和样品或条件之间进行比较值。最终，它计算P值一第二假发现率（FDR）假设两个条件之间的基因的变体比率的差超过为每个拼接事件19,34给定的用户定义的阈值。 以下在用RNA-SEQ结合差别剪接分析，广泛的实验验证以鉴定真阳性候选基因18必要的。定量反转录聚合酶链式反应（QRT-PCR）是由RNA测序分析20获得候选验证最常用的和最佳的方法。本文的目的是提供一种完善的方法来调查在实体瘤和血液恶性肿瘤药耐药相关剪接轮廓。我们的方法利用了与耐药性有牵连的候选基因的验证建立定量RT-PCR方法相结合抗药性癌症的选择细胞系模型的RNA-SEQ基于转录组分析。 5）21,22和甲氨蝶呤（MTX）抗性亚系CEM / R30dm 23。虽然基于GC和MTX的当前疗法的情况下，约90％建立临床益处，GC-耐药性的出现仍然代表具有不明确的分子机理的未解决的问题。以分离抗性的GC-子克隆，CEM-WT细胞在1μM的地塞米松为2〜3周培养。 MTX抗性亚系CEM / R30dm通过反复短期（24小时）的CEM-WT细胞暴露于30μM的MTX作为模拟的临床方案开发的。有趣的是，该细胞系也显示塞米松交叉耐药（未发表的结果）的量，机制尚不完全清楚。 固体TUM或模型在本研究调查的是胰腺导管腺癌，臭名昭著的非凡耐火度化疗。为此，我们选择的Panc-1细胞系和由连续孵育与药物24的1μM得到其耐吉西他子克隆的Panc-1R。在这里，我们描述了一种方法通过组合三个协议来发现在体外耐药底层新颖机制:比色细胞毒性试验，以评估在白血病细胞和实体瘤，RNA-SEQ基于管道癌细胞药物敏感性，以确定相关的新的剪接变体药物敏感性/抗性和RT-PCR和定量RT-PCR分析，以验证潜在候选。

<table border="0" cellpadding="0" cellspacing="0" width="732">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">Sulforhodamine B</td>
			<td style="width:195px;">Sigma-Aldrich</td>
			<td style="width:119px;">230162</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">Trichloroacetic acid</td>
			<td style="width:195px;">Sigma-Aldrich</td>
			<td style="width:119px;">251399</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">CCRF-CEM</td>
			<td style="width:195px;">ATCC, Manassas, VA, USA</td>
			<td style="width:119px;">ATCC CCL-119</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">Panc-1</td>
			<td style="width:195px;">ATCC, Manassas, VA, USA</td>
			<td style="width:119px;">ATCC CRL-1469</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">DMEM high glucose</td>
			<td style="width:195px;">Lonza, Basel, Switzerland</td>
			<td style="width:119px;">12-604F</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">RPMI-1640&#160;</td>
			<td style="width:195px;">Gibco, Carlsbad, CA, USA</td>
			<td style="width:119px;">11875093</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:252px;">Fetal bovine and calf serum</td>
			<td style="width:195px;">Greiner Bio-One, Frickenhausen, Germany</td>
			<td style="width:119px;">758093</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">penicillin G streptomycin sulphate</td>
			<td style="width:195px;">Gibco, Carlsbad, CA, USA</td>
			<td style="width:119px;">15140122</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">Tris(hydroxymethyl)-aminomethane</td>
			<td style="width:195px;">Sigma Aldrich</td>
			<td style="width:119px;">252859</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">MTT formazan</td>
			<td style="width:195px;">Sigma Aldrich</td>
			<td style="width:119px;">M2003</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:252px;">Anthos-Elisa-reader 2001</td>
			<td style="width:195px;">Labtec, Heerhugowaard, Netherlands</td>
			<td></td>
			<td>UV-Vis 96-well plate spectrophotometer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">Greiner CELLSTAR 96 well plates</td>
			<td style="width:195px;">Greiner/Sigma</td>
			<td>M0812-100EA</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:252px;">Trypsin/EDTA Solution 100 ml</td>
			<td style="width:195px;">Lonza, Basel, Switzerland</td>
			<td>CC-5012</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;">CELLSTAR Cell Culture Flasks 25 cm2</td>
			<td style="width:195px;">Greiner Bio-One, Frickenhausen, Germany</td>
			<td>82051-074</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;">CELLSTAR Cell Culture Flasks 75 cm3</td>
			<td style="width:195px;">Greiner Bio-One, Frickenhausen, Germany</td>
			<td>82050-856</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Phosphate Buffered Saline (NaCl 0.9%)</td>
			<td>B.Braun Melsungen AG, Germany</td>
			<td>362 3140</td>
			<td></td>
		</tr>
	</tbody>
</table>

using rna-sequencing to detect novel splice variants related to drug resistance in in vitro cancer models

抗药性仍然是癌症治疗为恶性血液病和实体瘤的一个主要问题。固有或获得性可通过多种机制，包括药物的消除增加引起的，药物吸收，药物失活和药物靶点的改变降低。最近的数据表明，除了通过公知的基因（突变，扩增）和表观遗传（DNA的甲基化，组蛋白的翻译后修饰）的修改，耐药机制也可能会被拼接像差调节。这是调查一个值得今后注意，以规划更加有效的治疗方法的迅速增长领域。在本文中描述的协议的目的是调查异常剪接的耐药性在实体瘤和恶性血液病的影响。为了这个目标，我们通过RNA测序和分析建立在体外模型几个转录概况ED一个定量RT-PCR为基础的方法来验证候选基因。特别是，我们评估DDX5和PKM转录物的差别剪接。由计算工具MATS检测出的异常剪接在白血病细胞进行了验证，显示出不同DDX5剪接变体是在亲代与抗性细胞中表达。在这些细胞中，我们也观察到了更高PKM2 / PKM1比，这未在的Panc-1抗吉西他滨的对应检测相比亲Panc-1细胞，这表明由吉西他滨诱导的曝光耐药的不同的机制。

在协议中所描述的细胞毒性测定法提供了可靠的和可靠的方法对癌细胞的电阻评估体外化疗剂。 CEM / R30dm，CEM-R5和CEM-C3:通过MTT测定法的手段，以地塞米松灵敏度在四个T-ALL细胞系，包括地塞米松敏感亲代的CEM-WT细胞，和三个塞米松抗性亚系进行了测定。两种不同的浓度范围不得不由于用来在灵敏度CEM-WT之间（2μM - 0.97纳米）的大的差异和地塞米松抗性细胞系（640μM - 0.33纳米）。 MTT测定清楚地显示在CEM / R30dm（IC 50 = 456±49μM），CEM-R 5（IC 50&gt; 640微米）和CEM-C3（IC 50 = 386±98μM）塞米松电阻相比，CEM-野生型细胞（IC 50 = 0.028±0.003微米）。同样，SRB测定表明在PANC-1R株高耐吉西他滨（IC 50 = 3。16±0.01μM）相比亲Panc-1细胞（IC 50 = 0.077±0.03μM），为显示在图2中。 继都被认为是细胞耐药的确认，我们接下来要进行mRNA分离，文库制备和RNA测序。通过使用二氧化硅膜离心柱总mRNA的提取是优于其它方法的优选的选择，因为它避免了苯酚和蛋白污染，并提供与远高于1.8 260纳米/ 280nm吸收比样品的高纯度。这对于复杂的下游应用，如深度测序一项重要的要求。使用琼脂糖检查RNA样品的完整性1％的方法，特别适用于新鲜分离细胞（ 图3）。由于该协议的目的是检测耐药细胞系中异常表达的替代剪接变异体，我们选择积极的SelectIO用于测序文库制备聚腺苷酸化mRNA的N，通过使用链mRNA试剂盒。单并汇集库的电泳图4中所描绘的，显示出大约300碱基对的平均片段大小，测序系统的要求相一致。然后准备库采用单读100个基点模式芯片测序。测序的选择读取100个基点是必要的，通过生物信息学下游管线探测可变剪接。 经过初步处理步骤和质量控制，清洁读取对准人类基因组（hg19）进行使用MATS差分拼接分析。在此分析中，我们抗性亚系分开制造的药物敏感亲代细胞系和其每一个药物的之间的比较（ 即，CEM WT 与 CEM / R30dm，CEM WT 与 CEM-C3 等 ）。 MATS依赖于灵活和精确的统计模型用于检测样品之间差异剪接。通过使用默认的分析选项和FDR值&lt;10％为截止（ 图5B描绘的），我们能够确定38±12显著差异剪接的候选基因每按类型选择性剪接事件的排序比较，与大多数命中划分为外显子跳跃。 图6示出了用于比较的Panc-1对的Panc-1R的典型分析输出。 我们进一步关注我们的研究最常见的两种类型的选择性剪接事件:外显子跳跃和下面描述每个类别的一名代表候选人相互排斥的外显子的事件。 DDX5（DEAD盒解旋酶5）已经由MATS分析检测为在比较CEM-WT 与 CEM-C3和CEM-R5统计学显著，但在比较CEM-WT 与 CEM / R30dm不显著。鉴于白血病25,26其公认的作用，我们选择这个候选人进一步验证。强烈建议在基因组类似浏览器的工具，可视化的RNA序列数据。 IGV提供了一种通用的和用户友好界面为此目的， 如图7的基因候选DDX5。 PKM（丙酮酸激酶肌肉同工酶）是在比较有统计学显著互斥外显子事件的CEM-WT 相对于全体塞米松抗性亚系，但不是在该比较的Panc-1 对的Panc-1R。鉴于实体肿瘤代谢27,28这种酶的相关性和在糖皮质激素抵抗的T-ALL 29细胞代谢的新作用，我们选择这个候选人采用RT-PCR进一步验证。 引物设计时必须格外小心，以扩增了正确的扩增子，特别是当引物退火到外显子 - 外显子边界（在反向引物检测DDX5ΔEx12变体的情况下）或当t进行哎退火相互排斥的外显子具有较高的序列同源性（外显子9和外显子PKM的10）。 图8示出的引物设计策略，而图9示出了的RT-PCR用于DDX5基因候选的结果。 DDX5ΔEx12样品CEM-WT和CEM / R30dm但不是在CEM-C3和CEM-R5中被检测到，从而确认以定性的方式MATS数据。花青绿的qRT-PCR测定准确量化DDX5和PKM剪接变体的表达水平，如分别示于图10和图11中 ，。 <img alt="图1" src="/files/ftp_upload/54714/54714fig1.jpg" /> 图1: 选择性剪接的示意图。的基因的选择性剪接的可能的模式的示意图。盒是可以独立地包括或来自MR排除离散的外显子NA成绩单。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig1large.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/54714/54714fig2.jpg" /> 图2:细胞毒性分析的结果。 （A）中为白血病细胞系MTT法示出了在CEM-C3高水平地塞米松抗性（IC 50 = 386±98），CEM-R 5（IC 50&gt; 640微米）和CEM / R30dm（IC 50 = 456±49μM ）相比亲CEM-WT（IC 50 = 0.028±0.003微米）。对于胰腺癌细胞系（B）的 SRB测定揭示高水平的Panc-1R吉西他滨抗性（IC 50 = 3.16±0.01μM）相比亲本的Panc-1（IC 50 = 77.22±2.76纳米）。这些图表±3 INDEP的SEM报告平均细胞生长％endent实验。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig2large.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/54714/54714fig3.jpg" /> 图3: RNA质量评估使用琼脂糖凝胶。 总mRNA的二百纳克被上用溴化乙锭染色的1％琼脂糖凝胶上运行。对应于核糖体RNA（rRNA基因）物种18S和28S以及没有在较低分子量涂片完整条带的指示的良好品质的RNA。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig3large.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/54714/54714fig4.jpg" /> 图4:&lt;测序文库的STRONG&gt;生物分析仪痕迹。 （A）测序文库中的电泳显示峰在大约300基点，这表明质量好。样品1至6 = CEM-WT，CEM-C3，CEM-R 5，CEM / R30dm，PANC-1和PANC-1R。汇集的样品（B）的电泳（FU，荧光单位）。 <img alt="图5" src="/files/ftp_upload/54714/54714fig5.jpg" /> 图5: 不同的剪接的检测用草席。 （A）组比较，用来运行MATS（B）的脚本。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig5large.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/54714/54714fig6.jpg" /> 图6: <eM&gt; MATS输出列表。该图描绘了MATS分析的典型输出与电子表格软件:此报告在比较PANC-1 对 PANC-1R的外显子跳跃事件（FDR &lt;10％）中差异拼接的候选人。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig6large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图7" src="/files/ftp_upload/54714/54714fig7.jpg" /> 图7: 通过IGV基因组浏览器候选DDX5基因的差异剪接的可视化。有排列的文件中读取相应的白血病细胞（.bam）已上载IGV基因组浏览器，并通过使用生鱼片地块（最低结计值= 10形象化显著剪接事件）可视化。剪接点计数通过连接线表示与对应于RNA的以次一个读取数跨越外显子。 CEM-WT和CEM / R30dm显示跳过计数跨越外显子11外显子13相比的CEM-C3和CEM-R5不显示出任何显子12跳跃。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig7large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图8" src="/files/ftp_upload/54714/54714fig8.jpg" /> 图8:用于RT-PCR和花菁绿定量RT-PCR引物设计。 （A），RT-PCR:引物对检测DDX5退火到位于上游和下游的可变剪接的外显子组成型外显子（外显子10和外显子13）的差别剪接。 （B）的定量RT-PCR分析:用于从外显子跳跃事件所造成相比规范转录转录物的相对定量，反向引物退火或者跳过外显子（可替代变体）内，或到DDX5基因的exon11 / exon13边界（典型变种）。用于互斥的外显子的量化，反向引物退火的外显子共同11到两种异构体，而正向引物退火任一外显子9（PKM1）或外显子10（PKM2）。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig8large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图9" src="/files/ftp_upload/54714/54714fig9.jpg" /> 图9:DDX5 差别剪接的，RT-PCR验证。在1％琼脂糖凝胶显示了白血病细胞的DDX5基因的差异剪接。对应DDX5全长扩增（650 bp）的片段在所有样品中被放大，同时DDX5ΔEx12（430 bp）的变体在CEM-WT和CEM / R30dm放大样本和大小对应于外显子12跳跃。这不是在CEM-C3和CEM-R5细胞中检测到，如阻止通过分析MATS开采。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig9large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图10" src="/files/ftp_upload/54714/54714fig10.jpg" /> 图10: 在CEM细胞DDX5剪接变体的mRNA表达水平的影响。 （A）实时定量RT-PCR检测。平均相对表达水平和平均值的两个独立的实验（REL±SEM）的标准误差。 （B）中的剪接变体的REL的比率（±SEM）。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig10large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图11" src="/files/ftp_upload/54714/54714fig11.jpg" /> 图11: mRNA表达水平小号PKM剪接变体在CEM和Panc-1细胞的。 （A）实时定量RT-PCR检测。平均相对表达水平，平均为CEM细胞的剪接变体的REL的两个独立实验（REL±SEM）和比率的标准误差。 （B）定量RT-PCR检测。平均REL±对Panc-1细胞的剪接变体的两个独立的实验和REL（±SEM）的比率SEM表示。 <a href="https://ecsource-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54714/54714fig11large.jpg" target="_blank">请点击此处查看该图的放大版本。</a>

Watch this Scientific Journal Video about Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models at JoVE.com

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

这里，我们描述旨在调查异常剪接的耐药性在实体瘤和血液恶性肿瘤的影响的协议。为了这个目标，我们通过RNA测序分析，家长和体外抗车型的转录配置文件，并建立了定量RT-PCR为基础的方法来验证候选基因。

利用RNA测序来检测新剪接变异体在相关耐药<em&gt;体外</em&gt;癌症模型

Drug resistance remains a major problem in the treatment of cancer for both hematological malignancies and solid tumors. Intrinsic or acquired resistance ...

using-rna-sequencing-to-detect-novel-splice-variants-related-to-drug

Nanyang Technological University

Research

JoVE Journal

Cancer Research

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

13.6K 次观看.  VU University Medical Center. 这里，我们描述旨在调查异常剪接的耐药性在实体瘤和血液恶性肿瘤的影响的协议。为了这个目标，我们通过RNA测序分析，家长和体外抗车型的转录配置文件，并建立了定量RT-PCR为基础的方法来验证候选基因。 

视频: Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery of the next generation of novel drug targets. It is becoming apparent that more complex models of cancer are required to fully appreciate the contributing factors that drive tumorigenesis in vivo and increase the efficacy of novel therapies that make the transition from pre-clinical models to clinical trials.
Here we present a methodology for generating uniform and reproducible tumor spheroids that can be subjected to siRNA functional screening. These spheroids display many characteristics that are found in solid tumors that are not present in traditional two-dimension culture. We show that several commonly used breast cancer cell lines are amenable to this protocol. Furthermore, we provide proof-of-principle data utilizing the breast cancer cell line BT474, confirming their dependency on amplification of the epidermal growth factor receptor HER2 and mutation of phosphatidylinositol-4,5-biphosphate 3-kinase (PIK3CA) when grown as tumor spheroids. Finally, we are able to further investigate and confirm the spatial impact of these dependencies using immunohistochemistry.

Identifying novel drug targets that transition from pre-clinical testing to human trials is a scientific priority. To that end, here we describe a functional genomics approach for examining the impact of gene depletion on cancer cell line spheroids, which more appropriately model human cancers in vivo.

利用功能基因组筛选识别在肿瘤细胞球体培养潜在的新药物靶标

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery ...

科研

癌症研究

Establishing Dual Resistance to EGFR-TKI and MET-TKI in Lung Adenocarcinoma Cells In Vitro with a 2-step Dose-escalation Procedure

Drug resistance is a major challenge in cancer therapy. The generation of resistant sublines in vitro is necessary for discovering novel mechanisms to overcome this challenge. Here, a 2-step dose-escalation method for establishing dual-resistance to an epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI), gefitinib, and a MET-TKI, PHA665752, is described. This method is based on simple stepwise dose-escalation of inhibitors for inducing acquired resistance in cell lines. The alternate method for generating resistant sublines involves exposing the cells to high concentrations of the inhibitor in one step. The stepwise dose-escalation method has a higher possibility of successfully inducing acquired resistance than this method. Activating EGFR mutations are biomarkers of a response to treatment with EGFR-TKI, which is an applied first-line treatment for non-small cell lung cancers (NSCLC) that harbor these mutations. However, despite reports of effective responses, the use of EGFR-TKI is limited because tumors inevitably acquire resistance. The major mechanisms behind EGFR-TKI resistance include a secondary mutation at the gatekeeper site, T790M in exon 20 of EGFR, and a bypass signal of MET. Thus, a potential solution for this issue would be a combination of EGFR-TKI and MET-TKI. This combined treatment has been shown to be effective in an in vitro study model. Acquired gefitinib-resistance was established through MET-amplification by stepwise dose-escalation of gefitinib for 12 months, and a cell line named PC-9MET1000 was generated in a previous study. To further investigate the mechanisms of acquired MET-TKI and EGFR-TKI resistance, a MET-TKI, PHA665752, was administered to these cells with stepwise dose-escalation in the presence of gefitinib for 12 months. This protocol has also been successfully applied for a number of combination therapies to establish acquired resistance to other inhibitor molecules.

Establishing Dual Resistance to EGFR-TKI and MET-TKI in Lung Adenocarcinoma Cells In Vitro with a 2-step Dose-escalation Procedure

An in vitro method for establishing dual resistance to an EGFR-TKI and a MET-TKI in cancer cells is described. This method is useful for developing treatments for patients with EGFR-mutations, who exhibit disease progression despite EGFR-TKI treatment with MET-amplification. It can also be modified for inhibitors targeting other molecules.

建立双抗 EGFR-使用 tki 药物治疗和满足使用 tki 药物治疗在肺腺癌细胞体外与 2 步剂量升级程序

Drug resistance is a major challenge in cancer therapy. The generation of resistant sublines in vitro is necessary for discovering novel mechanisms to ...

Generation of Prostate Cancer Cell Models of Resistance to the Anti-mitotic Agent Docetaxel

Microtubule targeting agents (MTAs) are a mainstay in the treatment of a wide range of tumors. However, acquired resistance to chemotherapeutic drugs is a common mechanism of disease progression and a prognostic-determinant feature of malignant tumors. In prostate cancer (PC), resistance to MTAs such as the taxane Docetaxel dictates treatment failure as well as progression towards lethal stages of disease that are defined by a poor prognosis and high mortality rates. Though studied for decades, the array of mechanisms contributing to acquired resistance are not completely understood, and thus pose a significant limitation to the development of new therapeutic strategies that could benefit patients in these advanced stages of disease. In this protocol, we describe the generation of Docetaxel-resistant prostate cancer cell lines that mimic lethal features of late-stage prostate cancer, and therefore can be used to study the mechanisms by which acquired chemoresistance arises. Despite potential limitations intrinsic to a cell based model, such as the loss of resistance properties over time, the Docetaxel-resistant cell lines produced by this method have been successfully used in recent studies and offer&#160;the opportunity to advance our molecular understanding of acquired chemoresistance in lethal prostate cancer.

Resistance to cancer therapies contributes to disease progression and death. Determining the mechanistic underpinnings of resistance is crucial for improving therapeutic response. This manuscript details the protocol to generate taxane-resistant cell models of prostate cancer (PC) to help dissecting the pathways involved in progression to Docetaxel resistance in PC patients.

抗有丝分裂药物多西紫杉醇的前列腺癌细胞模型的建立

Microtubule targeting agents (MTAs) are a mainstay in the treatment of a wide range of tumors. However, acquired resistance to chemotherapeutic drugs is a ...

Establishment of Gastric Cancer Patient-derived Xenograft Models and Primary Cell Lines

The use of preclinical models to advance our understanding of tumor biology and investigate the efficacy of therapeutic agents is key to cancer research. Although there are many established gastric cancer cell lines and many conventional transgenic mouse models for preclinical research, the disadvantages of these in vitro and in vivo models limit their applications. Because the characteristics of these models have changed in culture, they no longer model tumor heterogeneity, and their responses have not been able to predict responses in humans. Thus, alternative models that better represent tumor heterogeneity are being developed. Patient-derived xenograft (PDX) models preserve the histologic appearance of cancer cells, retain intratumoral heterogeneity, and better reflect the relevant human components of the tumor microenvironment. However, it usually takes 4-8 months to develop a PDX model, which is longer than the expected survival of many gastric patients. For this reason, establishing primary cancer cell lines may be an effective complementary method for drug response studies. The current protocol describes methods to establish PDX models and primary cancer cell lines from surgical gastric cancer samples. These methods provide a useful tool for drug development and cancer biology research.

The current protocol describes methods to establish patient-derived xenograft (PDX) models and primary cancer cell lines from surgical gastric cancer samples. The methods provide a useful tool for drug development and cancer biology research.

建立胃癌患者衍生异种移植模型和原细胞系

The use of preclinical models to advance our understanding of tumor biology and investigate the efficacy of therapeutic agents is key to cancer research. ...

In Vitro Assay to Study Tumor-macrophage Interaction

Tumor associated macrophages (TAMs) account for a large percentage of cells in the tumor mass for different types of cancers. Glioblastoma (GBM), a malignant brain tumor with no cure, has up to a half the tumor mass TAMs. TAMs can be pro-tumoral or anti-tumoral, depending on the activation of specific genes in the cells. Genetic mutations in the tumors, through regulating cytokine expression, can affect recruitment of TAMs to the tumor microenvironment. Here, we describe a quantitative cell-based assay to assess macrophage recruitment by the conditioned medium from the tumor cells. This assay uses the human macrophage cell line MV-4-11 to study macrophage attraction by the conditioned medium from glioblastoma, allowing for high reproducibility and low variability. Data generated with this assay can contribute to a better understanding of the interaction between the tumor and the tumor microenvironment. Similar assay can be used to assess interaction between the tumor cells and other immune cells, including T cells and natural killer (NK) cells.

This article represents a useful in vitro assay to evaluate the capability of conditioned medium from tumor cells to attract macrophages.

体外测定研究肿瘤-巨噬菌体相互作用

Tumor associated macrophages (TAMs) account for a large percentage of cells in the tumor mass for different types of cancers. Glioblastoma (GBM), a ...

In Vitro Evaluation of Oncogenic Transformation in Human Mammary Epithelial Cells

Tumorigenesis is a multi-step process in which cells acquire capabilities&#160;that allow their growth, survival, and dissemination under hostile conditions. Different tests seek to identify and quantify these hallmarks of cancerous cells; however, they often focus on a single aspect of cellular transformation and, in fact, multiple tests are required for their proper characterization. The purpose of this work is to provide researchers with a set of tools to assess cellular transformation in vitro from a broad perspective, thereby making it possible to draw sound conclusions.
A sustained proliferative signaling activation is the major feature of tumoral tissues and can be easily monitored under in vitro conditions by calculating the number of population doublings achieved over time. Besides, the growth of cells in 3D cultures allows their interaction with surrounding cells, resembling what occurs in vivo. This enables the evaluation of cellular aggregation and, together with immunofluorescent labeling of distinctive cellular markers, to obtain information on another relevant feature of tumoral transformation: the loss of proper organization. Another remarkable characteristic of transformed cells is their capacity to grow without attachment to other cells and to the extracellular matrix, which can be evaluated with the anchorage assay.
Detailed experimental procedures to evaluate cell growth rate, to perform immunofluorescent labeling of cell lineage markers in 3D cultures, and to test anchorage-independent cell growth in soft agar are provided. These methodologies are optimized for Breast Primary Epithelial Cells (BPEC) due to its relevance in breast cancer; however, procedures can be applied to other cell types after some adjustments.

This protocol provides experimental in vitro tools to evaluate the transformation of human mammary cells. Detailed steps to follow-up cell proliferation rate, anchorage-independent growth capacity, and distribution of cell lineages in 3D cultures with basement membrane matrix are described.

人类乳腺上皮细胞致癌转化的体外评价

Tumorigenesis is a multi-step process in which cells acquire capabilities&#160;that allow their growth, survival, and dissemination under hostile ...

Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients

An understanding of drug resistance and the development of novel strategies to sensitize highly resistant cancers rely on the availability of suitable preclinical models that can accurately predict patient responses. One of the disadvantages of existing preclinical models is the inability to contextually preserve the human tumor microenvironment (TME) and accurately represent intratumoral heterogeneity, thus limiting the clinical translation of data. By contrast, by representing the culture of live fragments of human tumors, the patient-derived explant (PDE) platform allows drug responses to be examined in a three-dimensional (3D) context that mirrors the pathological and architectural features of the original tumors as closely as possible. Previous reports with PDEs have documented the ability of the platform to distinguish chemosensitive from chemoresistant tumors, and it has been shown that this segregation is predictive of patient responses to the same chemotherapies. Simultaneously, PDEs allow the opportunity to interrogate molecular, genetic, and histological features of tumors that predict drug responses, thereby identifying biomarkers for patient stratification as well as novel interventional approaches to sensitize resistant tumors. This paper reports PDE methodology in detail, from collection of patient samples through to endpoint analysis. It provides a detailed description of explant derivation and culture methods, highlighting bespoke conditions for particular tumors, where appropriate. For endpoint analysis, there is a focus on multiplexed immunofluorescence and multispectral imaging for the spatial profiling of key biomarkers within both tumoral and stromal regions. By combining these methods, it is possible to generate quantitative and qualitative drug response data that can be related to various clinicopathological parameters and thus potentially be used for biomarker identification.

This paper describes methods for the generation, drug treatment, and analysis of patient-derived explants for assessing tumor drug responses in a live, patient-relevant, preclinical model system.

患者源性肿瘤外植体作为预测患者耐药性的"实时"临床前平台

An understanding of drug resistance and the development of novel strategies to sensitize highly resistant cancers rely on the availability of suitable ...

Pooled shRNA Library Screening to Identify Factors that Modulate a Drug Resistance Phenotype

Understanding clinically relevant driver mechanisms of acquired chemo-resistance is crucial for elucidating ways to circumvent resistance and improve survival in patients with acute myeloid leukemia (AML). A small fraction of leukemic cells that survive chemotherapy have a poised epigenetic state to tolerate chemotherapeutic insult. Further exposure to chemotherapy allows these drug persister cells to attain a fixed epigenetic state, which leads to altered gene expression, resulting in the proliferation of these drug-resistant populations and eventually relapse or refractory disease. Therefore, identifying epigenetic modulations that necessitate the survival of drug-resistant leukemic cells is critical. We detail a protocol to identify epigenetic modulators that mediate resistance to the nucleoside analog cytarabine (AraC) using pooled shRNA library screening in an acquired cytarabine-resistant AML cell line. The library consists of 5,485 shRNA constructs targeting 407 human epigenetic factors, which allows high-throughput epigenetic factor screening.

High-throughput RNA interference (RNAi) screening using a pool of lentiviral shRNAs can be a tool to detect therapeutically relevant synthetic lethal targets in malignancies. We provide a pooled shRNA screening approach to investigate the epigenetic effectors in acute myeloid leukemia (AML).

合并的shRNA文库筛选，以确定调节耐药性表型的因素

Understanding clinically relevant driver mechanisms of acquired chemo-resistance is crucial for elucidating ways to circumvent resistance and improve ...

Zebrafish Larvae as a Model to Evaluate Potential Radiosensitizers or Protectors

Zebrafish are extensively used in several kinds of research because they are one of the easily maintained vertebrate models and exhibit several features of a unique and convenient model system. As highly proliferative cells are more susceptible to radiation-induced DNA damage, zebrafish embryos are a front-line in vivo model in radiation research. In addition, this model projects the effect of radiation and different drugs within a short time, along with major biological events and associated responses. Several cancer studies have used zebrafish, and this protocol is based on the use of radiation modifiers in the context of radiotherapy and cancer. This method can be readily used to validate the effects of different drugs on irradiated and control (non-irradiated) embryos, thus identifying drugs as radio sensitizing or protective drugs. Although this methodology is used in most drug screening experiments, the details of the experiment and the toxicity assessment with the background of X-ray radiation exposure are limited or only briefly addressed, making it difficult to perform. This protocol addresses this issue and discusses the procedure and toxicity evaluation with a detailed illustration. The procedure describes a simple approach for using zebrafish embryos for radiation studies and radiation-based drug screening with much reliability and reproducibility.

The zebrafish has recently been exploited as a model to validate potential radiation modifiers. The present protocol describes the detailed steps to use zebrafish embryos for radiation-based screening experiments and some observational approaches to evaluate the effect of different treatments and radiation.

斑马鱼幼虫作为评估潜在放射增敏剂或保护剂的模型

Zebrafish are extensively used in several kinds of research because they are one of the easily maintained vertebrate models and exhibit several features ...

使用非放射性化学发光检测定量端粒长度

Optimization of Performance Parameters of the TAGGG Telomere Length Assay

Telomeres are repetitive sequences which are present at chromosomal ends; their shortening is a characteristic feature of human somatic cells. Shortening occurs due to a problem with end replication and the absence of the telomerase enzyme, which is responsible for maintaining telomere length. Interestingly, telomeres also shorten in response to various internal physiological processes, like oxidative stress and inflammation, which may be impacted due to extracellular agents like pollutants, infectious agents, nutrients, or radiation. Thus, telomere length serves as an excellent biomarker of aging and various physiological health parameters. The TAGGG telomere length assay kit is used to quantify average telomere lengths using the telomere restriction fragment (TRF) assay and is highly reproducible. However, it is an expensive method, and because of this, it is not employed routinely for large sample numbers. Here, we describe a detailed protocol for an optimized and cost-effective measurement of telomere length using Southern blots or TRF analysis and non-radioactive chemiluminescence-based detection.

作者聚焦：TAGGG 端粒长度测定性能参数的优化  

Here, we describe in detail the protocol for quantifying telomere length using non-radioactive chemiluminescent detection, with a focus on the optimization of various performance parameters of the TAGGG telomere length assay kit, such as buffer quantities and probe concentrations.

TAGGG端粒长度测定性能参数优化

Telomeres are repetitive sequences which are present at chromosomal ends; their shortening is a characteristic feature of human somatic cells. Shortening ...