We would like to thank Dr Hamish Campbell and Prof Antony Braithwaite for their help in developing the transduced MCF-7-LeGO cell lines. We would like to acknowledge our funding support by the Bloomfield Group Foundation through the Hunter Medical Research Institute. B.C.M is supported by an APA scholarship through the University of Newcastle and the MM Sawyer Scholarship through the Hunter Medical Research Institute.

1.准备用于细胞增殖检测注:准备以相同的方式和种子中的两种细胞系在相同的格式对于要分析的每个方法。 <ol><li>使用生长的MCF-7-LEGO和MCF-7-Δ40p537细胞至75-80％汇合T中75cm 2的组织培养瓶无酚红的Dulbecco改良Eagle培养基（DMEM）中补充有10％胎牛血清（FBS）的，200 2mM L-谷氨酰胺，2微克/毫升的胰岛素和1μg/ ml的嘌呤霉素，在37℃，5％的CO 2。处理细胞II无菌生物安全柜类。 注意:需要的时间的细胞生长至汇合的量取决于播种稀释而变化。在用于电镀的细胞的增殖测定的准备，种子的细胞以1:3稀释在补充的DMEM，并在正常生长条件保持3天，直至75-80％汇合。 </li><li>从烧瓶中除去细胞，媒体倒出成一个废物容器。立即用2ml预热2×胰蛋白酶的洗细胞层。吸胰蛋白酶。在37℃的培养箱中添加进一步2毫升预温热胰蛋白酶的细胞层和地点的5分钟，用5％ 的 CO 2。 <ol><li>一旦细胞脱离，洗涤细胞，用10ml温热新鲜补充的DMEM。在RT细胞悬液转移到无菌的15毫升管和离心491 xg离心5分钟。小心吸取上清液处置。 </li></ol></li><li>重悬细胞沉淀在5毫升新鲜的DMEM加味的。进行细胞计数，以确定正确的密度播种的细胞在96孔板中。 <ol><li>稀释100微升在900微升1×Dulbecco氏磷酸盐缓冲盐水（DPBS）中的细胞悬浮液。将新的60微米传感器到自动细胞计数。按住柱塞和淹没在稀释的细胞悬浮液中的传感器。慢慢地松开细胞计数柱塞。从细胞凑取出传感器当完成NTER。 注:细胞计数，将显示在细胞/ ml的细胞计数器。 </li></ol></li><li>种子的细胞以在约20％汇合100微升（在DMEM）在一个96孔板的最终体积，以允许室超过3-5天（ 见表1）的增殖的细胞生长和测量。种子一式三份所有细胞系。 注意:在这个实验中，三个不同的细胞密度进行了评估，以确定最佳的细胞密度。所需的细胞数以较低的密度概括于表1中 。种子细胞，如果需要更长期的增长的测量。 <ol><li>对于血球和基于发光的测定，每准备时间点的一个板块（ 即每次检测4板）。对细胞成像测定法中，在实验的持续时间仅准备一个板。 </li></ol></li><li>维持细胞在37℃，5％CO 2的24小时。 </li></ol> 2.确定细胞计数我们ING血球<ol><li>在细胞培养培养箱预暖既介质和胰蛋白酶至37℃，烘箱或水浴中。从细胞中吸出培养基到废物容器中，用2×胰蛋白酶的30微升洗一次，并吸出胰蛋白酶。 </li><li>用2×胰蛋白酶的30微升再次洗涤细胞，并孵育在37℃下5分钟。轻轻敲击板的边缘与板打跑细胞。加入50μl补充的DMEM和直至细胞形成单细胞悬浮液，通过移液混合细胞。 </li><li>通过清洁表面和玻璃盖，用70％的乙醇制备血球。 </li><li>将玻璃盖玻片上计数室，并加盖直到"牛顿环折射"可以在盖玻片边缘和血球间可见。 注意:这些表明，盖玻片已正确地坚持的血球。 </li><li>轻轻吸取20微升细胞悬浮液的盖玻片下，通过毛细管运动填充计数室。将血球下放大10倍的显微镜和可视化的网格布局的计数室。 </li><li>算上在网格布局的4外广场的细胞。为了提高精确度，如果需要的附加 ​​外正方形重复计数，或者直到计数已经达到70 - 100细胞14,15。 <ol><li> （如果使用的话）每平方×稀释因子的平均细胞数×10 4:计算每毫升的细胞浓度如下</li></ol></li><li>重复步骤2.1-2.8，每24小时96小时后播种。 </li></ol> 3.确定细胞增殖使用基于发光的分析注意:这是一个终点测量。一旦所述试剂加入到细胞中，板只能使用一次定量。 <ol><li>解冻发光试剂在22℃水浴中30分钟。 </li><li>轻轻颠倒瓶子以获得均匀混合混合试剂。 </li><li>平衡接种细胞的一个板（来自步骤1.5）在室温30分钟。 </li><li>加入100μl发光试剂的每个孔中。混合内容上轨道摇床2分钟。允许板在室温下孵育10分钟。 </li><li>使用多模式平板阅读器软件设置发光实验。 <ol><li>开启多模板读数器和打开软件。在"任务管理器"，选择"实验"和"创建new&#39;.Select&#39;文件&#39;从侧面工具条，并根据"协议"选项卡中，选择"程序"。 </li><li>选择"格尼尔96平底&#39;板型，并选中"使用盖子"框。在选择"读法"盒子"读"的行动。选择"发光"的检测方法。点击"确定"。 </li><li>在阅读的步骤中，选择"全板"选项卡下要扫描的井，并选择井作为空白孔。 </li><li>设置过滤器设置为空过滤器（ 例如 ，插头，EM:孔镜:无）。将增益设置为135，每孔0.5秒的积分时间和6.5毫米的读高度。点击"确定"保存设置发光读。 </li></ol></li><li>执行发光读<ol><li>通过选择"仪器控制"选项卡弹出板夹，然后点击"板块out&#39;.Place 96孔板上板架，确保盖子上。通过点击&#39;板&#39;下&#39;的仪器控制"选项卡中关闭板固定器。点击&#39;现在读"从工具栏进行发光读。 </li><li>导出的每个的相对发光单位（RLU）测量很好地用于进一步分析电子表格。 </li></ol></li><li>重复步骤3.1-3.6种子细胞后，细胞增殖记录每24小时最多96个小时。 </li></ol> 4.确定细胞计数使用细胞成像仪<ol><li>使用多模式信元成像软件建立细胞成像实验<ol><li>打开多模式电池成像仪和开放日E软件。 </li><li>在"任务管理器"，选择"实验"标签和"创建new&#39;.On的"文件"工具栏上，单击"协议"选项卡，打开"程序"tab.Select"设定温度"的行动。孵化器设置为"开"和设定温度为37℃，请与接下来"框，然后再继续"预热"。点击"确定"保存设置。 </li><li>选择"读"的行动。点击"图像"检测方法，选择"端点/动力学"读类型和"过滤器"光学类型。上盘点击满盘&#39;标签&#39;的OK&#39;.Click&#39;，选择井成像。点击"确定"保存设置。 </li><li>从下拉"目标"选项中选择2.5X目标。在"频道"选项卡，选择两个渠道:GFP 469，525和明视野。检查两个通道"自动"曝光，并选择自动曝光好。 </li><li>要确定AUTØ聚焦设置，选择"自动对焦"，然后单击"选项"。对于自动对焦选项，选择"扫描，然后自动对焦"的方法。点击"确定"保存设置。 </li><li>设置的水平和垂直距离的井（微米）中心偏移到0.Select扫描每孔的多个图像在一个3×2的蒙太奇，以水平间距（微米）= 2881和垂直间距（微米）= 2127。点击"确定"保存设置程序。 注:请参见表2读取参数。 </li></ol></li><li>在板块选择执行读取实验<ol><li>点击"仪器控制"选项卡，选择"积垢"function.Place在板架96孔板，确保盖子上。根据"仪器控制"选项卡，选择功能"中板"。从板选项卡中选择"立即阅读。重复阅读每24小时最多96小时后播种。 </li></ol></li><li>细胞计数分析使用细胞成像软件。 <ol><li>为了分析图像，单击"数据"选项卡上的成像板，选择"图片[GFP 469，525 +明场]&#39;。双击一个很好成像。 </li><li>点击加载图像。选择"分析"，然后选择要分析蒙太奇的单一形象。点击"OK&#39;.Check了"绿色荧光蛋白"的唯一通道，并设置参数表3所列。点击"开始"，以参数适用于成像单元。 </li><li>观察细胞计数掩模放置在成像单元，它被用来确定每幅图像的细胞计数。点击整个实验成像每块板"应用更改"和维护这些设置。 </li><li>一旦回到成像板，单击"数据"下拉菜单，选择"细胞计数"。这将产生每孔的总细胞计数。 </li><li>通过点击进行​​进一步的分析Ø"导出"选项卡上导出所有的数据到电子表格˚F每孔的细胞计数。 </li></ol></li></ol>

<ol>
	<li>Lane, D. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cancer.+p53,+guardian+of+the+genome.">Cancer. p53, guardian of the genome.</a> Nature. 358 (6381), 15-16 (1992).</li><li>Olivier, M., Hollstein, M., Hainaut, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TP53+mutations+in+human+cancers:+origins,+consequences,+and+clinical+use.">TP53 mutations in human cancers: origins, consequences, and clinical use.</a> Cold Spring Harb Perspect Biol. 2 (1), a001008 (2010).</li><li>Olivier, 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=The+clinical+value+of+somatic+TP53+gene+mutations+in+1,794+patients+with+breast+cancer.">The clinical value of somatic TP53 gene mutations in 1,794 patients with breast cancer.</a> Clin Cancer Res. 12 (4), 1157-1167 (2006).</li><li>Bourdon, J. 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=p53+isoforms+can+regulate+p53+transcriptional+activity.">p53 isoforms can regulate p53 transcriptional activity.</a> Genes Dev. 19 (18), 2122-2137 (2005).</li><li>Avery-Kiejda, K. 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=Small+molecular+weight+variants+of+p53+are+expressed+in+human+melanoma+cells+and+are+induced+by+the+DNA-damaging+agent+cisplatin.">Small molecular weight variants of p53 are expressed in human melanoma cells and are induced by the DNA-damaging agent cisplatin.</a> Clin Cancer Res. 14 (6), 1659-1668 (2008).</li><li>Avery-Kiejda, K. A., Morten, B., Wong-Brown, M. W., Mathe, A., Scott, R. 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+relative+mRNA+expression+of+p53+isoforms+in+breast+cancer+is+associated+with+clinical+features+and+outcome.">The relative mRNA expression of p53 isoforms in breast cancer is associated with clinical features and outcome.</a> Carcinogenesis. 35 (3), 586-596 (2014).</li><li>Weber, K., Bartsch, U., Stocking, C., Fehse, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+multicolor+panel+of+novel+lentiviral+&amp;#34;gene+ontology&amp;#34;+(LeGO)+vectors+for+functional+gene+analysis.">A multicolor panel of novel lentiviral &amp;#34;gene ontology&amp;#34; (LeGO) vectors for functional gene analysis.</a> Mol Ther. 16 (4), 698-706 (2008).</li><li>Riss, T. L., Moravec, R. A., Celis, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Cell Biology. , 25-31 (2006).</li><li>Ng, K. W., Leong, D. T., Hutmacher, D. 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+challenge+to+measure+cell+proliferation+in+two+and+three+dimensions.">The challenge to measure cell proliferation in two and three dimensions.</a> Tissue Eng. 11 (1-2), 182-191 (2005).</li><li>Riss, T. L., Moravec, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+multiple+assay+endpoints+to+investigate+the+effects+of+incubation+time,+dose+of+toxin,+and+plating+density+in+cell-based+cytotoxicity+assays.">Use of multiple assay endpoints to investigate the effects of incubation time, dose of toxin, and plating density in cell-based cytotoxicity assays.</a> Assay Drug Dev Technol. 2 (1), 51-62 (2004).</li><li>Butzler, M., Worzella, T., Hungriano, M., Osorio, F., Hanegraaff, I., Cowan, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Automated cytotoxicity profiling using the CyBi-FeliX instrument, cell health assays and thaw-and-use cells. , (2014).</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> CellTiter-Glo 2.0 Assay Technical Manual #403. , (2015).</li><li>Banks, P., Brescia, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Application Guide: Automated Digital Microscopy. , (2015).</li><li>Bastidas, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Cell Counting with Neubauer Chamber: Basic Hemocytometer Usage. , (2016).</li><li>Bastidas, O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> , (2012).</li><li>Riss, T. L., Moravec, R., Niles, A. L., Sittampalam, G. S., Coussens, N. P., Nelson, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell+Viability+Assays.">Cell Viability Assays.</a> Assay Guidance Manual[Internet]. , (2013).</li><li>Quent, V. M., Loessner, D., Friis, T., Reichert, J. C., Hutmacher, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discrepancies+between+metabolic+activity+and+DNA+content+as+tool+to+assess+cell+proliferation+in+cancer+research.">Discrepancies between metabolic activity and DNA content as tool to assess cell proliferation in cancer research.</a> J Cell Mol Med. 14 (4), 1003-1013 (2010).</li><li>Crane, J., Mittar, D., Soni, D., McIntyre, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Cell Cycle Analysis Using the BD BrdU FITC Assay on the BD FACSVerse System. , 1-12 (2011).</li></ol>

作者宣称，他们没有竞争的经济利益。

在这个协议中进行了检查三个不同测量在培养细胞的细胞增殖的方法。每一种方法是有能力的细胞增殖的可再现和精确的测量的超过96小时，并且结果是每个测试的方法之间比较的（ 图2和3）。同时基于发光的测定法和细胞成像方法所产生的最强大的结果，是表示之后96小时在细胞增殖的线性增加（ 图2b，c） 所示 。此外，随着时间的推移细胞成?...

肿瘤抑制基因，p53基因，是一个数字的细胞过程，包括细胞周期停滞，细胞凋亡和衰老1的一个重要调节器。它是负责维持基因组稳定性，因此对于维持细胞死亡和细胞生长的平衡是至关重要的。 p53基因的突变是在癌症常见并且是p53的失活的主要原因，导致不受控制的细 ​​胞增殖2。有趣的是，在p53基因突变只占乳腺癌3的大约25％，这表明其他机制负责p53功能的丧失。最近发现的p53同种型已被证明在许多人类癌症中过表达，并能调节p53功能4,5。我们以前曾表明，p53的同种型，Δ40p53，是在乳腺癌中最高度表达的同种型，并且在乳腺癌细胞中显著上调，相比正常相邻做卷烟时UE 6。在此之后，我们稳定转导的人乳腺癌细胞系MCF-7中使用LEGO-IG2-普罗+载体（GFP +）7以过表达Δ40p53。这些细胞被用来研究是否高Δ40p53表达增加乳腺癌细胞的细胞增殖率。 有体外测定8,9-培养细胞的细胞增殖的许多直接和间接的方法。这些都可以无论是作为连续测量随着时间的推移，或作为端点检测10进行。传统的方法仍然是有用的，诸如使用血球细胞计数。该测定法是一种成本低，细胞数的直接测量，但它确实依赖于大细胞计数和高技能训练，以尽量减少计数误差和大的标准偏差。以执行与高通量格式兼容的测量的需要已经导致多孔板测定法的发展。这些基于发光的测定measu再根据正比于电池11,12的代谢活性的发光信号的细胞数。最近，引进高含量的成像平台已经允许其监控细胞增殖，同时提供定量和定性的表型数据采集新的工具，包括各种系统13。所有的这些方法提供途径来测量细胞生长，或者通过连续测量或端点测定法，和每个具有与问候灵敏度，可以通过样品的数字，和小单元信息的范围内的优点和缺点，它们都可以相应地称量取决于所研究的问题。 这个协议描述了测量细胞增殖在体外 ，具有利用灵敏度，重复性和多井板格式的不同范围的每个方法三种不同的方法。该协议的目的是比较使用一个血球计数的茶MBER，一个基于发光的细胞生存力测定法，和细胞成像仪，在细胞增殖超过96小时时间过程的测定。要做到这一点，载体转导的细胞（MCF-7-LEGO）的生长相比转导至过表达Δ40p53（MCF-7-Δ40p53）细胞，使用三种不同的细胞密度。细胞增殖测定每24小时的多达96小时。发现每一种方法有它自己的优点和缺点，并且根据实验的目的，每一个仍然是对增殖的速率提供信息的有价值的方法。

<table><tbody><tr><td>Dulbecco&#039;s Modified Eagle Medium, no phenol-red</td><td>ThermoFisher Scientific</td><td>21063-045</td><td>Supplemented with 10% FBS, 200 mM L-glutamine, 2 &amp;micro;g/ml insulin and 1 &amp;micro;g/ml puromycin</td></tr><tr><td>L-glutamine solution (100x)</td><td>ThermoFisher Scientific</td><td>25030-081</td><td></td></tr><tr><td>Insulin solution human</td><td>Sigma-Aldrich</td><td>I9278-5ML</td><td></td></tr><tr><td>Fetal bovine serum (FBS)</td><td>Bovogen Biologicals</td><td>SFBS-F-500ml</td><td></td></tr><tr><td>Puromycin dihydrochloride</td><td>Sigma-Aldrich</td><td>P9620-10ML</td><td></td></tr><tr><td>0.5% trypsin-EDTA solution (10x)</td><td>ThermoFisher Scientific</td><td>15400-054</td><td>Dilute to 2x in DPBS</td></tr><tr><td>Dulbecco&#039;s Phosphate Buffered Saline (DPBS) (1x)</td><td>ThermoFisher Scientific</td><td>30028-02</td><td></td></tr><tr><td>Tissue culture flask, 75 cm&lt;sup&gt;2 &lt;/sup&gt;growth area</td><td>Greiner Bio-One</td><td>658175</td><td></td></tr><tr><td>Scepter 2.0 Cell Counter</td><td>Merck Millipore</td><td></td><td>Automated cell counter</td></tr><tr><td>96 well multiwell plate, flat bottom</td><td>Nunc</td><td>167008</td><td></td></tr><tr><td>Improved Neubauer Hemocytometer</td><td>BOECO Germany</td><td>BOE 01</td><td></td></tr><tr><td>Olympus IX51 inverted microscope</td><td>Olympus</td><td>IX51</td><td></td></tr><tr><td>CellTiter-Glo 2.0 Assay</td><td>Promega</td><td>G9242</td><td>Luminescence-based assay</td></tr><tr><td>Cytation 3 Cell Imaging Multi-Mode Reader</td><td>BioTek</td><td></td><td>Plate reader for luminescence, fluorescence and brightfield cell imaging</td></tr><tr><td>Gen5 Data Analysis Software</td><td>BioTek</td><td>GEN5</td><td></td></tr></tbody></table>

comparison of three different methods for determining cell proliferation in breast cancer cell lines

Measuring cell proliferation can be performed by a number of different methods, each with varying levels of sensitivity, reproducibility and compatibility with high-throughput formatting. This protocol describes the use of three different methods for measuring cell proliferation in vitro including conventional hemocytometer counting chamber, a luminescence-based assay that utilizes the change in the metabolic activity of viable cells as a measure of the relative number of cells, and a multi-mode cell imager that measures cell number using a counting algorithm. Each method presents its own advantages and disadvantages for the measurement of cell proliferation, including time, cost and high-throughput compatibility. This protocol demonstrates that each method could accurately measure cell proliferation over time, and was sensitive to detect growth at differing cellular densities. Additionally, measurement of cell proliferation using a cell imager was able to provide further information such as morphology, confluence and allowed for a continual monitoring of cell proliferation over time. In conclusion, each method is capable of measuring cell proliferation, but the chosen method is user-dependent.

研究测定培养细胞的增殖，-Δ40p53MCF-7转导的细胞的细胞增殖的不同的方法进行比较的非转导的MCF-7-LEGO乳腺癌细胞系。进行了比较，三种方法-分析-在本示意图中概括的常规血球方法，细胞活力发光测定和细胞成像（ 图1）。每种方法都有优点和缺点，以精确地测量随着时间的推移细胞计数，而最有效的方法取决于实验的终点的要求和可以为一个细胞群获取的?...

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Comparison of Three Different Methods for Determining Cell Proliferation in Breast Cancer Cell Lines

This protocol describes the use of three different methods for analyzing cell proliferation in breast cancer cell lines. This includes the use of conventional cell counting, luminescence-based cell viability, and cell counting through the use of a cell imager. Each offers advantages for the reproducible measurement of cell proliferation.

的三种不同方法对乳腺癌细胞株确定细胞增殖的比较

Measuring cell proliferation can be performed by a number of different methods, each with varying levels of sensitivity, reproducibility and compatibility ...

comparison-three-different-methods-for-determining-cell-proliferation

Research

JoVE Journal

Biology

19.4K 次观看.  Hunter Medical Research Institute. This protocol describes the use of three different methods for analyzing cell proliferation in breast cancer cell lines. This includes the use of conventional cell counting, luminescence-based cell viability, and cell counting through the use of a cell imager. Each offers advantages for the reproducible measurement of cell proliferation.

视频: Comparison of Three Different Methods for Determining Cell Proliferation in Breast Cancer Cell Lines

Assessing Cell Viability and Death in 3D Spheroid Cultures of Cancer Cells

Three-dimensional spheroids of cancer cells are important tools for both cancer drug screens and for gaining mechanistic insight into cancer cell biology. The power of this preparation lies in its ability to mimic many aspects of the in vivo conditions of tumors while being fast, cheap, and versatile enough to allow relatively high-throughput screening. The spheroid culture conditions can recapitulate the physico-chemical gradients in a tumor, including the increasing extracellular acidity, increased lactate, and decreasing glucose and oxygen availability, from the spheroid periphery to its core. Also, the mechanical properties and cell-cell interactions of in vivo tumors are in part mimicked by this model. The specific properties and consequently the optimal growth conditions, of 3D spheroids, differ widely between different types of cancer cells. Furthermore, the assessment of cell viability and death in 3D spheroids requires methods that differ in part from those employed for 2D cultures. Here we describe several protocols for preparing 3D spheroids of cancer cells, and for using such cultures to assess cell viability and death in the context of evaluating the efficacy of anticancer drugs.

Here, we present several simple methods for evaluating viability and death in 3D cancer cell spheroids, which mimic the physico-chemical gradients of in vivo tumors much better than the 2D culture. The spheroid model, therefore, allows evaluation of the cancer drug efficacy with improved translation to in vivo conditions.

评估癌细胞3D球形培养中的细胞活力和死亡

Three-dimensional spheroids of cancer cells are important tools for both cancer drug screens and for gaining mechanistic insight into cancer cell biology. ...

科研

癌症研究

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 ...

Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment

Multicellular tumor spheroid (MCTSs) models have demonstrated increasing utility for in vitro study of cancer progression and drug discovery. These relatively simple avascular constructs mimic key aspects of in vivo tumors, such as 3D structure and pathophysiological gradients. MCTSs models can provide insights into cancer cell behavior during spheroid development and in response to drugs; however, their requisite size drastically limits the tools used for non-destructive assessment. Optical Coherence Tomography structural imaging and Imaris 3D analysis software are explored for rapid, non-destructive, and label-free measurement of regional cell density within MCTSs. This approach is utilized to assess MCTSs over a 4-day maturation period and throughout an extended 5-day treatment with Trastuzumab, a clinically relevant anti-HER2 drug. Briefly, AU565 HER2+ breast cancer MCTSs were created via liquid overlay with or without the addition of Matrigel (a basement membrane matrix) to explore aggregates of different morphologies (thicker, disk-like 2.5D aggregates or flat 2D aggregates, respectively). Cell density within the outer region, transitional region, and inner core was characterized in matured MCTSs, revealing a cell-density gradient with higher cell densities in core regions compared to outer layers. The matrix addition redistributed cell density and enhanced this gradient, decreasing outer zone density and increasing cell compaction in the cores. Cell density was quantified following drug treatment (0 h, 24 h, 5 days) within progressively deeper 100 &#181;m zones to assess potential regional differences in drug response. By the final timepoint, nearly all cell death appeared to be constrained to the outer 200 &#181;m of each aggregate, while cells deeper in the aggregate appeared largely unaffected, illustrating regional differences in the drug response, possibly due to limitations in drug penetration. The current protocol provides a unique technique to non-destructively quantify regional cell density within dense cellular tissues and measure it longitudinally.

The present protocol develops an image-based technique for rapid, non-destructive, and label-free regional cell density and viability measurement within 3D tumor aggregates. Findings revealed a cell-density gradient, with higher cell densities in core regions than outer layers in developing aggregates and predominantly peripheral cell death in HER2+ aggregates treated with Trastuzumab.

药物治疗后肿瘤聚集体内区域细胞密度的无损评估

Multicellular tumor spheroid (MCTSs) models have demonstrated increasing utility for in vitro study of cancer progression and drug discovery. These ...

Preparation and Analysis of In Vitro Three Dimensional Breast Carcinoma Surrogates

Three dimensional (3D) culture is a more physiologically relevant method to model cell behavior in vitro than two dimensional culture. Carcinomas, including breast carcinomas, are complex 3D tissues composed of cancer epithelial cells and stromal components, including fibroblasts and extracellular matrix (ECM). Yet most in vitro models of breast carcinoma consist only of cancer epithelial cells, omitting the stroma and, therefore, the 3D architecture of a tumor in vivo. Appropriate 3D modeling of carcinoma is important for accurate understanding of tumor biology, behavior, and response to therapy. However, the duration of culture and volume of 3D models is limited by the availability of oxygen and nutrients within the culture. Herein, we demonstrate a method in which breast carcinoma epithelial cells and stromal fibroblasts are incorporated into ECM to generate a 3D breast cancer surrogate that includes stroma and can be cultured as a solid 3D structure or by using a perfusion bioreactor system to deliver oxygen and nutrients. Following setup and an initial growth period, surrogates can be used for preclinical drug testing. Alternatively, the cellular and matrix components of the surrogate can be modified to address a variety of biological questions. After culture, surrogates are fixed and processed to paraffin, in a manner similar to the handling of clinical breast carcinoma specimens, for evaluation of parameters of interest. The evaluation of one such parameter, the density of cells present, is explained, where ImageJ and CellProfiler image analysis software systems are applied to photomicrographs of histologic sections of surrogates to quantify the number of nucleated cells per area. This can be used as an indicator of the change in cell number over time or the change in cell number resulting from varying growth conditions and treatments.

Preparation and Analysis of In Vitro Three Dimensional Breast Carcinoma Surrogates

We demonstrate a method to generate 3D breast cancer surrogates, which can be cultured using a perfusion bioreactor system to deliver oxygen and nutrients. Following growth, surrogates are fixed and processed to paraffin for evaluation of parameters of interest. The evaluation of one such parameter, cell density, is explained.

制备及分析<em&gt;体外</em&gt;三维乳腺癌代理项

Three dimensional (3D) culture is a more physiologically relevant method to model cell behavior in vitro than two dimensional culture. Carcinomas, ...

生物工程

离子通道治疗实体瘤的药理学靶向

Screening Ion Channels in Cancer Cells

Ion channels are critical for cell development and maintaining cell homeostasis. The perturbation of ion channel function contributes to the development of a broad range of disorders or channelopathies. Cancer cells utilize ion channels to drive their own development, as well as to improve as a tumor and to assimilate in a microenvironment that includes various non-cancerous cells. Furthermore, increases in levels of growth factors and hormones within the tumor microenvironment can result in enhanced ion channel expression, which contributes to cancer cell proliferation and survival. Thus, the pharmacological targeting of ion channels is potentially a promising approach to treating solid malignancies, including primary and metastatic brain cancers. Herein, protocols to characterize the function of ion channels in cancerous cells and approaches to analyze modulators of ion channels to determine their impact on cancer viability are described. These include staining a cell(s) for an ion channel(s), testing the polarized state of mitochondria, establishing ion channel function using electrophysiology, and performing viability assays to assess drug potency.

作者聚焦:探索离子通道在癌症中的作用:表征和可能的治疗方法 

The pharmacological targeting of ion channels is a promising approach to treating solid tumors. Detailed protocols are provided for characterizing ion channel function in cancer cells and assaying the effects of ion channel modulators on cancer viability.

筛选癌细胞中的离子通道

Ion channels are critical for cell development and maintaining cell homeostasis. The perturbation of ion channel function contributes to the development ...

Rapid Quantification of Mitogen-induced Blastogenesis in T Lymphocytes for Identifying Immunomodulatory Drugs

Lymphocyte proliferation in response to antigenic or mitogenic stimulation is a readily quantifiable phenomenon useful for testing immunomodulatory (i.e., immunosuppressive or immunostimulatory) chemical compounds and biologics. One of the earliest steps during mitogenesis is cell enlargement or blastogenic transformation, whereupon the cell volume increases before division. It is usually detectable in the first several hours of T-lymphocyte stimulation. Here, we describe a rapid method to quantify blastogenesis in T lymphocytes isolated from mouse spleens and human peripheral blood mononuclear cells (PBMCs) using an automated cell counter. Various commonly used proliferation assays for the most part are laborious and only reflect the overall population effect rather than individual cellular effects within a population. In contrast, the presented automated cell counter assay provides rapid, direct, and precise measurements of cell diameters that can be used for assessing the effectiveness of various mitogens and immunomodulatory drugs in vitro.

T-lymphocyte mitogenesis is accompanied by blastogenic transformation, whereupon the cell volume enlarges before cell division. Here, we describe a method to quantify blastogenesis in T lymphocytes using an automated cell counter with the capability of measuring cell diameters.

T淋巴细胞有丝分裂原诱导芽生的快速定量辨识免疫调节药物

Lymphocyte proliferation in response to antigenic or mitogenic stimulation is a readily quantifiable phenomenon useful for testing immunomodulatory (i.e., ...

免疫与感染

Analysis of Cell Cycle Position in Mammalian Cells

The regulation of cell proliferation is central to tissue morphogenesis during the development of multicellular organisms. Furthermore, loss of control of cell proliferation underlies the pathology of diseases like cancer. As such there is great need to be able to investigate cell proliferation and quantitate the proportion of cells in each phase of the cell cycle. It is also of vital importance to indistinguishably identify cells that are replicating their DNA within a larger population. Since a cell&prime;s decision to proliferate is made in the G1 phase immediately before initiating DNA synthesis and progressing through the rest of the cell cycle, detection of DNA synthesis at this stage allows for an unambiguous determination of the status of growth regulation in cell culture experiments.
DNA content in cells can be readily quantitated by flow cytometry of cells stained with propidium iodide, a fluorescent DNA intercalating dye. Similarly, active DNA synthesis can be quantitated by culturing cells in the presence of radioactive thymidine, harvesting the cells, and measuring the incorporation of radioactivity into an acid insoluble fraction. We have considerable expertise with cell cycle analysis and recommend a different approach. We Investigate cell proliferation using bromodeoxyuridine/fluorodeoxyuridine (abbreviated simply as BrdU) staining that detects the incorporation of these thymine analogs into recently synthesized DNA. Labeling and staining cells with BrdU, combined with total DNA staining by propidium iodide and analysis by flow cytometry1 offers the most accurate measure of cells in the various stages of the cell cycle. It is our preferred method because it combines the detection of active DNA synthesis, through antibody based staining of BrdU, with total DNA content from propidium iodide. This allows for the clear separation of cells in G1 from early S phase, or late S phase from G2/M. Furthermore, this approach can be utilized to investigate the effects of many different cell stimuli and pharmacologic agents on the regulation of progression through these different cell cycle phases.
In this report we describe methods for labeling and staining cultured cells, as well as their analysis by flow cytometry. We also include experimental examples of how this method can be used to measure the effects of growth inhibiting signals from cytokines such as TGF-&beta;1, and proliferative inhibitors such as the cyclin dependent kinase inhibitor, p27KIP1. We also include an alternate protocol that allows for the analysis of cell cycle position in a sub-population of cells within a larger culture5. In this case, we demonstrate how to detect a cell cycle arrest in cells transfected with the retinoblastoma gene even when greatly outnumbered by untransfected cells in the same culture. These examples illustrate the many ways that DNA staining and flow cytometry can be utilized and adapted to investigate fundamental questions of mammalian cell cycle control.

Determining the cell cycle position of a population of cells, or understanding how signals affect proliferation, can be readily measured by flow cytometry using this protocol. We report a simple experimental approach to staining cells and quantifying their position in the cell cycle.

在哺乳动物细胞中细胞周期位置分析

The regulation of cell proliferation is central to tissue morphogenesis during the development of multicellular organisms. Furthermore, loss of control of ...

生物学

Optimized Staining and Proliferation Modeling Methods for Cell Division Monitoring using Cell Tracking Dyes

Fluorescent cell tracking dyes, in combination with flow and image cytometry, are powerful tools with which to study the interactions and fates of different cell types in vitro and in vivo.1-5 Although there are literally thousands of publications using such dyes, some of the most commonly encountered cell tracking applications include monitoring of:
<ol>
	<li>stem and progenitor cell quiescence, proliferation and/or differentiation6-8</li>
	<li>antigen-driven membrane transfer9 and/or precursor cell proliferation3,4,10-18 and</li>
	<li>immune regulatory and effector cell function1,18-21.</li>
</ol>
Commercially available cell tracking dyes vary widely in their chemistries and fluorescence properties but the great majority fall into one of two classes based on their mechanism of cell labeling. "Membrane dyes", typified by PKH26, are highly lipophilic dyes that partition stably but non-covalently into cell membranes1,2,11. "Protein dyes", typified by CFSE, are amino-reactive dyes that form stable covalent bonds with cell proteins4,16,18. Each class has its own advantages and limitations. The key to their successful use, particularly in multicolor studies where multiple dyes are used to track different cell types, is therefore to understand the critical issues enabling optimal use of each class2-4,16,18,24.
The protocols included here highlight three common causes of poor or variable results when using cell-tracking dyes. These are:
<ol>
	<li>Failure to achieve bright, uniform, reproducible labeling. This is a necessary starting point for any cell tracking study but requires attention to different variables when using membrane dyes than when using protein dyes or equilibrium binding reagents such as antibodies.</li>
	<li>Suboptimal fluorochrome combinations and/or failure to include critical compensation controls. Tracking dye fluorescence is typically 102 - 103 times brighter than antibody fluorescence. It is therefore essential to verify that the presence of tracking dye does not compromise the ability to detect other probes being used.</li>
	<li>Failure to obtain a good fit with peak modeling software. Such software allows quantitative comparison of proliferative responses across different populations or stimuli based on precursor frequency or other metrics. Obtaining a good fit, however, requires exclusion of dead/dying cells that can distort dye dilution profiles and matching of the assumptions underlying the model with characteristics of the observed dye dilution profile.</li>
</ol>
Examples given here illustrate how these variables can affect results when using membrane and/or protein dyes to monitor cell proliferation.

Successful use of cell tracking dyes to monitor immune cell function and proliferation involves several critical steps. We describe methods for: 1) obtaining bright, uniform, reproducible label-ing with membrane dyes; 2) selecting fluorochromes and data acquisition conditions; and 3) choosing a model to quantify cell proliferation based on dye dilution.

的三种不同方法对乳腺癌细胞株确定细胞增殖的比较

摘要

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此视频中的章节

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人类乳腺上皮细胞致癌转化的体外评价

药物治疗后肿瘤聚集体内区域细胞密度的无损评估

制备及分析

筛选癌细胞中的离子通道

筛选癌细胞中的离子通道

筛选癌细胞中的离子通道

T淋巴细胞有丝分裂原诱导芽生的快速定量辨识免疫调节药物

在哺乳动物细胞中细胞周期位置分析

优化细胞分裂监测细胞示踪染料的染色和扩散建模方法