作者要感谢丹尼尔野生的援助，用于读取生产的手稿和援助。

<ol>
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作者什么都没有透露。

<html>如本手稿描述的两个NGS测试临床上所提供的最重要的实际考虑是质量控制。具体来说，仔细考虑必须支付的质量和提取的DNA量。这是为FFPE样品这往往是用可变的DNA产量高度退化尤其重要。异丙醇沉淀法，是为了最大限度地从FFPE样品DNA产率，为发现基于列的方法有时会导致有限的洗脱体积的DNA剪切开发。因此，大多数的当检体产生浓度太低或为测定太降​​解的时间，这是最有可能是由于该组织的大小，类型，或固定和不提取过程。对血液/骨髓样本，如果有一个提取失败，它通常是由于样品被hemodilute（ 即不具有足够数目的白细胞或肿瘤细胞在该拉伸的）或化学消融。 。NT"&gt;验证期间，进行DNA的质量和数量的可接受性截断应建立100的推荐输入 - 250纳克在测定通常使用;但是，如果DNA质量是好的，那么较低的输入量可以是成功的。此外，如果该DNA质量差（ 即 ，扩增的DNA的量小于100 - 250毫微克）然后较高的输入量可以提高测序结果的质量（因为扩增的DNA的量会达到推荐的输入） 。指标DNA的质量和数量应推进DNA插入文库制备之前被应用到每个样本，这些样本在一个"灰色地带"（ 见图2）应在实验室负责人或指定人员的自由裁量权运行。目前最好的办法预测如果测序过程中的DNA不会表现良好是执行基于定量PCR的测定法，允许输入DNA的定量和质量评估，这种方法解决了上述bioavailab在样本大小不同的片段，通过不同尺寸的片段（ 如 100个基点，150基点，200基点和300基点）和比较收益率的放大ility。 目前，文库制备涉及大量的手动步骤，其中在几个接合部之一的失误可导致库失败或以质量较差。微流体凝胶分析是唯一的QC步序之前检查库准备的问题。因此，有几个关键步骤，其中额外留心可以增加成功反应的概率。当务之急是保证正确的样品和寡核苷酸池用于每个样品。确保妥善记录每个样本包含96的一个独特的双索引的PCR引物对的组合，减少了样品混合起来的机会。此外，重要的是要保证过滤板（FPU）正确地排出;如果它不恰当漏这可能会导致EXTE图书馆准备nsion结扎一步次优执行，导致质量差的测序数据。库的QC后，重要的是，确保LNB1珠充分再悬浮并且LNB1 / LNA1溶液是作为该混合物的浓度使用，以确定文库的摩尔浓度将其添加到样品之前充分混合。最后，如​​果珠洗脱步骤导致库的次优量洗脱离珠粒会降低聚类密度，并可能导致库无法获得足够的平均覆盖率。相反地​​，过量图书馆，会导致质量较差的读取。因此，要在基于珠子的归一化步骤，以确保定序文库的最佳池和聚类一致是重要的。 除了文库制备，它是验证一个生物信息学管道，将产生从原始的，解复用FASTQ文件准确突变呼叫关键。选择一个因为有许多开源和市售的矫正器，变种呼叫者和NGS软件包，一个人必须要通过筛选定制的解决方案可能是费时。自定义算法将需要设计来提取基本性能统计数据，找出最逃避开源工具独特的经常性突变，并确定在每个位点的拷贝数状态。期间一个生物信息学流水线的验证过程中，重要的是要确定该达到或超过后质量过滤覆盖的两个最小深度（ 例如 ，一个最小的250读取）和最小等位基因频率变体的报告的截止值（ 例如 ，4个％）。因为这是一个复用基于扩增子的测定法，重要的是要确定最小平均覆盖深度（ 例如 ，1000倍），该库需要达到能够得到最低执行扩增到最小深度的读出。此外，该测定的多路复用性质确实Ç澳洲英语脱靶效应和这些"神器"将需要被发现，并在发射前全面审核。所描述的测定法的另一个重要的限制是需要的样品以包含在以达到验证最小等位基因频率大于10％的肿瘤。 低频，1％，FLT3插入的检测是证据表明人工审核仍然在这个过程中所希望的。即使有5％的等位基因频率的截止，一些重要的突变可能错过因而手动审查将是至关重要的，以确定这些变体。对于FLT3-ITD中 ，对所有AML患者进行外显子14目视检查，以确保低级别或大的插入/重复不会被忽视。此外，HER2外显子20插入，其通常是旁边的引物序列，需要人工干预。尽管有强大的生物信息学管道，一些变种可以去忽略它是具有硬砍的只是性质关闭上述大部分的统计数据。将需要更好的生物信息，以帮助缓解这个问题，因为将更好地文库制备和/或测序的方法，因为它是更有利的是含有较少的文物和误报甚至更低截止拥有高质量的数据。 检测和等位基因频率的解释可能是困难的，由于在肿瘤百分比确定和基因组的一些区域的扩增偏差的难度。此外，超过50％的等位基因频率可以被检测，如在壳体2观察到这被解释为杂合事件的损失，无论是由于正常的等位基因的丧失，导致突变体的明显增加读取，一个突变等位基因（ 例如 ，2突变体和一个正常复制）或其它机制的增益。这些机制可以通过利用阵列比较基因组杂交（aCGH 19）和/或一个SNP基因分型阵列阐明。20。 目前的目标富集方法依赖于任何低效杂交捕获或多重PCR技术的全日程序，导致需要对单个样品的测序更多的覆盖范围和更多的脱靶序列读取。预期在不久的将来对NGS分子肿瘤额外应用将包括更容易文库的制备方法，可以是完全自动化的，并且能够以非常低的量的DNA模板来处理样品（ 即 ，小于1毫微克）以及样品高度降解脱氧核糖核酸。为了应对这些挑战，大多数方法想必会基于PCR的，无论是作为一个多PCR的方法，或大规模并行单一PCR方法。此外，个别的扩增子的分子条形码已经显示出显着降低背景测序噪声，并将使样品的测试与肿瘤细胞的比例较低，以实现较低的等位基因频率并朝向捕获circulat移动ING肿瘤细胞。 在癌组织疾病相关的基因突变的检测一直是护理标准几十年。从历史上看，基因经常一次测试顺序，一个基因/外显子，具有通向测试序列的端部的突变的鉴定。 NGS的出现已经允许偏差较小的方法来测序以并联许多癌症导致了与肿瘤相关的多个突变的标识相关联的多个基因。 NGS的用于癌症检测的体细胞突变的临床应用日益明显。事实上，肿瘤样本的基于NGS-分析代表了一种新的模式，挑战传统的，单一的基因检测，但其临床效用是很清楚的。今天临床实验室有令人兴奋的机会，以结婚认真方法验证和测试的解释与这个强大技术的应用。

临床肿瘤学标本下一代测序（NGS），为查明靶向基因变化和预测/预后分子标记的重要性越来越多的科学文献点已经成为过去几年更广泛的应用。多基因分析小组和疾病进展和复发两种上皮1,2和血液系统恶性肿瘤3全外显子组测序研究都凝固了肿瘤异质性的概念，并克隆演变。另外，与竞争技术如聚合酶链反应（PCR）或Sanger测序，NGS可以检测单个测定4中的所有临床相关的癌基因最基因组改变。 该中心最初有两个临床NGS板，自定义面板血液学（血红素-NGS面板）和一个现成的，货架癌症小组FFPE样品（固体NGS面板）推出个性化诊断（见<strong&gt;图1）。这些面板覆盖了选择的基因的临床相关的或高利息的区域;不是所有的基因或外显子完全覆盖。扩增子被探针杂交其次是延伸和连接产生的。目标区域使用PCR具有普遍的双索引引物进一步放大，允许多达96个样品进行汇集测序。 <img alt="图1" src="/files/ftp_upload/52758/52758fig1.jpg" /> 图1:在面板覆盖基因的列表中使用进行文库制备为自定义面板血液学33基因或关闭的，现成的扩增子癌症面板的47个基因（固NGS）（血红素-NGS面板）。不是所有的基因或外显子的覆盖全面，因为有些可能扩增子仅涵盖某些热点。 <a href="https://www.jove.com/files/ftp_upload/52758/52758fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。&lt;</a>/ A&gt; 为血红素-NGS面板内容是从多个来源，但围绕在先前描述为证明临床效用5高水平急性髓细胞白血病（AML）突变16个基因中心。固NGS面板与商业报道的体细胞突变的目录癌症（COSMIC）数据库6基于在一般癌症的基因突变目标区域产生的。 几个关键步骤表征整个工作流程，为临床NGS。临床医生订单试验后，病理学家确定以下用于肿瘤百分比和样品体积分析检体的充分性。在我们的机构，我们要求，由于该技术的背景测序错误率（"噪声"）和目标方法的效率为至少10％的肿瘤。如果组织是足够的检测，基因组DNA提取。然后将该DNA进行多个质量控制（QC）的步骤。如果DNA通过QC，产生和测序的扩增子文库。所得数据通过一个内部的生物信息学流水线进行分析。继生物信息学分析，变种人工审查，并结合之前解释的致病性到临床报告。下面我们描述了两个案例，通过这个严格的流程去，并最终导致临床管理的变化。 案例1 -急性髓系白血病 从病人A A骨髓活检诊断是反洗钱，没有成熟。细胞遗传学研究是对骨髓标本发出并表现出正常的雌性核型。出席者达95％循环爆炸，使外周血标本为血红素NGS面板上的个性化诊断测试发送。 急性髓性白血病（AML）是白血细​​胞的骨髓谱系的血液系统恶性肿瘤。检测在AML基因突变已成为预后和治疗越来越重要，复发性基因突变公认的发病机制和预后7重要。在NPM1和CEBPA突变与一个有利的预后风险相关，而在FLT3内部串联重复（场ITD）已与一个不太有利的结果8有关。越来越多的证据体支持的AML 9这些和其他突变的致病作用。 案例2 -肺腺癌 从患者B中的左锁骨上肿块活检证实肺腺癌。从福尔马林固定的石蜡包埋（FFPE）淋巴结肿块活检材料用于基因组试验（固NGS面板）被发送作为辊/卷发具有大于50％的肿瘤，以确定一个突变是否存在有针对性的治疗干预。 龙CANC器是在美国癌症相关死亡的主要原因，并分为两种主要类型，非小细胞肺癌（NSCLC）和小细胞肺癌（SCLC）。非小细胞肺癌，可以进一步定义为腺癌或鳞状细胞癌，基于病变的组织学。肺腺癌是肺癌最常见的亚型，在吸烟者和非吸烟者看到的，是不吸烟者10肺癌最常见的形式。肺腺癌的分子研究已经在多个癌基因11中确定突变。在吸烟者中确定的最常见驾驶员的突变是在KRAS基因和BRAF突变。在非吸烟者中最常见的突变是EGFR突变，以及涉及的基因ALK，RET和ROS1重排。肺肿瘤已与一个在框架的外显子20插入在基因ERBB2（HER2 / neu的）中描述。在何最常见的异常R 2 / neu的是该位点在乳腺癌的扩增为其中靶向治疗是可用的（曲妥单抗:针对HER2 / neu基因的人源化单克隆抗体）。即在2观察HER2 / neu基因外显子20插入-肺4％adenocarcimomas 12已经（分别为那替尼和西罗莫司脂化）13显示，联合治疗HER2 / neu和mTOR抑制剂部分缓解。

<table border="0" cellpadding="0" cellspacing="0" width="1091">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:277px;">Genomic DNA ScreenTape</td>
			<td style="width:128px;">Agilent Technology</td>
			<td style="width:140px;">5067-5365</td>
			<td style="width:547px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Genomic DNA Reagents</td>
			<td>Agilent Technology</td>
			<td>5067-5366</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">High Sensitivity D1000 ScreenTape</td>
			<td>Agilent Technology</td>
			<td>5067-5584</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">High Sensitivity D1000 Reagents</td>
			<td>Agilent Technology</td>
			<td>5067-5585</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TapeStation 2200</td>
			<td>Agilent Technology</td>
			<td>G2965A</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TapeStation Analysis Software</td>
			<td>Agilent Technology</td>
			<td>A.01.04 or higher</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">96-well Tube Storage Racks</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">15/50 ml Tube Rack</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">96-well&#160; Plate Rack</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, single-channel, 0.5&#8211;2.5 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, single-channel, 1&#8211;10 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, single-channel, 2&#8211;20 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, single-channel, 10&#8211;100 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, single-channel, 20&#8211;200 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, single-channel, 100&#8211;1000 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Serological Pipettor</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Vortexer</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ice bucket</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Microcentrifuge (for tubes and strip tubes)</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Freezer, -20 &#176;C</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">4 &#176;C Refrigerator</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Water or Bead Bath</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="23">
			<td height="23" style="height:23px;">Incubator (37 oC)</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Serological Pipettes, 1 mL</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Serological Pipettes, 5 mL</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Serological Pipettes, 10 mL</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Serological Pipettes, 25 mL</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Gloves</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Razor Blades/Scaples</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">KimWipes</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">15 mL Conical Tube</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">50 mL Conical Tube</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Paper Towels</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">200 proof Ethanol</td>
			<td>Any Vendor</td>
			<td></td>
			<td>Store in Flammable Cabinet</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">2-Propanol (Isopropanol)</td>
			<td>Any Vendor</td>
			<td></td>
			<td>Store in Flammable Cabinet</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">25ml Reservoirs</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">10N NaOH</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, 8-channel, 1&#8211;10 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, 8-channel, 10&#8211;100 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pipette, 8-channel, 20&#8211;300 &#956;L</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ice Bucket</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Water Squirt Bottle</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Alcohol Squirt Bottle</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Lens Cleaning Paper</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Plates, 96-well PCR, Semi-Skirted</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Tube strips, 8-well, 0.2 mL</td>
			<td>Any Vendor</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Agencourt AMPure XP Beads</td>
			<td>Beckman Coulter</td>
			<td>A63881</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">BioShake IQ or 3000-T elm</td>
			<td>Bulldog Bio/Q.Instruments</td>
			<td>1808-0506/ 1808-0517</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DropPlate96 S - LabChipDS</td>
			<td>Caliper</td>
			<td align="right">128876</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DropPlate96 D - LabChipDS</td>
			<td>Caliper</td>
			<td align="right">132848</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DropSense96</td>
			<td>Caliper (Trinean)</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DropQuant Software</td>
			<td>Caliper (Trinean)</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Plate Sealing Film</td>
			<td>Denville</td>
			<td>B1212-5S</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Aluminum Seal Foil</td>
			<td>Denville</td>
			<td>B1212-6S</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nuclease-Free, Pure Water System</td>
			<td>EMD Millipore</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">5424 centrifuge</td>
			<td>Eppendorf</td>
			<td align="right">22621408</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">5804R centrifuge</td>
			<td>Eppendorf</td>
			<td align="right">22623508</td>
			<td>Both 15 ml tube and plate rotators, preferably a centrifuge that can go up to 2,500 x g.</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Safe-Lock Tube 1.5 mL, Natural</td>
			<td>Eppendorf</td>
			<td align="right">22431021</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">5 mL Tube, DNA LoBind Tube</td>
			<td>Eppendorf</td>
			<td align="right">30108310</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">5430R Centrifuge</td>
			<td>Eppendorf</td>
			<td>022620645</td>
			<td>Any plate rotator centrifuge will work</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Hybex Microsample Incubator</td>
			<td>Fisher Scientific</td>
			<td>1057-30-0</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Hybex 0.2 mL Tube Block</td>
			<td>Fisher Scientific</td>
			<td>1057-31-0</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TruSeq Amplicon &#8211; Cancer Panel</td>
			<td>Illumina</td>
			<td>FC-130-1008</td>
			<td>96 reactions</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TruSeq Custom Amplicon</td>
			<td>Illumina</td>
			<td>PE-940-1011</td>
			<td>96 reactions</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TruSeq Custom Amplicon Index Kit</td>
			<td>Illumina</td>
			<td>FC-130-1003</td>
			<td>96 Indices, 384 Samples</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MiSeq Reagent Kit v3, 500 Cycles</td>
			<td>Illumina</td>
			<td>MS-102-3003</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MiSeq Reagent Kit v2, 300 Cycles</td>
			<td>Illumina</td>
			<td>MS-102-2002</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MiSeq Reagent Kit v2, 500 Cycles</td>
			<td>Illumina</td>
			<td>MS-102-2003</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Experiment Manager</td>
			<td>Illumina</td>
			<td>1.3 or higher</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MiSeq Reporter</td>
			<td>Illumina</td>
			<td>2.0 or higher</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Sequencing Analysis Viewer</td>
			<td>Illumina</td>
			<td>1.8 or higher</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TruSeq Index Plate Fixture and Collar Kit</td>
			<td>Illumina</td>
			<td>FC-130-1007</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MiSeq v2</td>
			<td>Illumina</td>
			<td>SY-410-1003</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TruSeq Custom Amplicon Filter Plate</td>
			<td>Illumina</td>
			<td>FC-130-1006</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Index Adapter Replacement Caps</td>
			<td>Illumina</td>
			<td align="right">11294657</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit 2.0</td>
			<td>Invitrogen</td>
			<td>Q32866</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit 0.5 ml Tubes</td>
			<td>Invitrogen</td>
			<td>Q32856</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit dsDNA Broad Range Assay Kit</td>
			<td>Invitrogen</td>
			<td>Q32853</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DynaMa6-96 Magnetic Stand, Side Skirted</td>
			<td>Invitrogen</td>
			<td align="right">120.27</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">GeneAmp PCR System 9700 (gold/silver block)</td>
			<td>Life Technologies</td>
			<td>N8050200</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Gentra Puregene Blood Kit</td>
			<td>Qiagen</td>
			<td align="right">158489</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Deparaffinization Solution (16ml)</td>
			<td>Qiagen</td>
			<td align="right">19093</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Buffer ATL (4x50ml)</td>
			<td>Qiagen</td>
			<td align="right">939011</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Protein Precipitation Solution (50 ml)</td>
			<td>Qiagen</td>
			<td align="right">158910</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">DNA Hydration Solution (100ml)</td>
			<td>Qiagen</td>
			<td align="right">158914</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Glycogen Solution (500 &#956;l)</td>
			<td>Qiagen</td>
			<td align="right">158930</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qiagen Proteinase K</td>
			<td>Qiagen</td>
			<td align="right">19133</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Rnase (5ml)</td>
			<td>Qiagen</td>
			<td align="right">158924</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nuclease-Free Water (10 x 50 ml)&#160;</td>
			<td>Qiagen</td>
			<td align="right">129114</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Pestles</td>
			<td>USA Scientific</td>
			<td>1415-5390</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TipOne RPT 10 ul elongated filter pipet tips in sterilized racks, 10 racks of 96 tips (960 tips).</td>
			<td>USA Scientific</td>
			<td>1180-3810</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TipOne RPT 100 ul natural, beveled filter pipet tips in sterilized racks, 10 racks of 96 tips (960 tips)</td>
			<td>USA Scientific</td>
			<td>1180-1840</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TipOne RPT 200 &#956;l natural, beveled filter pipet tips in racks, sterilized racks, 10 racks of 96 tips (960 tips)</td>
			<td>USA Scientific</td>
			<td>1180-8810</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TipOne RPT 20 &#956;l natural, beveled filter pipet tips in racks, sterilized racks, 10 racks of 96 tips (960 tips)</td>
			<td>USA Scientific</td>
			<td>1180-1810</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TipOne RPT 1000 &#956;l natural, graduated XL filter pipet tips in</td>
			<td>USA Scientific</td>
			<td>1182-1830</td>
			<td></td>
		</tr>
	</tbody>
</table>

next generation sequencing for the detection of actionable mutations in solid and liquid tumors

As our understanding of the driver mutations necessary for initiation and progression of cancers improves, we gain critical information on how specific molecular profiles of a tumor may predict responsiveness to therapeutic agents or provide knowledge about prognosis. At our institution a tumor genotyping program was established as part of routine clinical care, screening both hematologic and solid tumors for a wide spectrum of mutations using two next-generation sequencing (NGS) panels: a custom, 33 gene hematological malignancies panel for use with peripheral blood and bone marrow, and a commercially produced solid tumor panel for use with formalin-fixed paraffin-embedded tissue that targets 47 genes commonly mutated in cancer. Our workflow includes a pathologist review of the biopsy to ensure there is adequate amount of tumor for the assay followed by customized DNA extraction is performed on the specimen. Quality control of the specimen includes steps for quantity, quality and integrity and only after the extracted DNA passes these metrics an amplicon library is generated and sequenced. The resulting data is analyzed through an in-house bioinformatics pipeline and the variants are reviewed and interpreted for pathogenicity. Here we provide a snapshot of the utility of each panel using two clinical cases to provide insight into how a well-designed NGS workflow can contribute to optimizing clinical outcomes.

案例1 -血红素，NGS面板 从白血病外周血提取的DNA进行的足够质量和数量的（176毫微克/微升）用于血红素-NGS面板。覆盖的总体平均深度为4,933x（的1000倍覆盖范围的最低平均深度以上）。额外的运行统计数据见表3。以下250X覆盖了8个地区中，有3人因引物修剪不当（ 即引物序列没有正确删除，由于测序错误），1个是分析的一种假象，和其他4个是不同的基因，没有报告变体的外显子的部分区域。虽然我们的临床方案只包括报告至少250读取覆盖的变种，至少有100的所有数据都读导入到数据库中以供审查。 数据处理F-ROM中的生物信息学管道检测到三个报告，疾病相关的基因突变;的错义突变在FLT3，在IDH2的错义突变，并在NPM1移码突变。与他们的等位基因频率的外显子变异表4中进行了说明。在一个FLT3常见的突变是FLT3 -internal串联重复（ITD），这是不能自动我们的管道打了 ​​个电话，要求外显子14外显子14的目视检查目视检查FLT3的显示，在提交样品无插入或复制。该FLT3 I836del为1％的等位基因频率，并没有包含在最终的报告，因为它下跌5％最低验证等位基因频率之下。这种突变是不相同的DNA分子作为FLT3 D835Y变化上（ 即 ，在相同的扩增子区域观察到的，而不是在"顺式"中的任何测序的读操作），它是仅由.bam音响的人工审查观察验证p.D835Y变化，莱斯。两个FLT3突变的下部等位基因频率表明这些突变可以代表异质性和/或克隆演变;然而，差别可能是由于该扩增子或单核苷酸多态性（SNP）接近或重叠的影响该等位基因的扩增引物序列测定性能。 案例1血红素NGS面板结果与FLT3，IDH2和 NPM1 AML鉴定突变，AML。突变三种常见的突变基因FLT3的成人患者中约25％是观察到AML（COSMIC数据库17），均内部串联重复（场ITD）或错义突变在酪氨酸激酶结构域。该FLT3-ITD中是比较常见的基因突变，并与标准化疗反应差有关，而FLT3激酶D的预后意义omain点突变，如在此的AML患者，对预后14不明确的影响。异柠檬酸脱氢酶2（NADP +），线粒体（IDH2）是编码是在AML中常用的突变外遗传修饰的基因。在表观遗传修饰的突变是比较常见的白血病，在IDH1和DNMT3A突变占这一类基因，导致基因失调的其他突变。在基因为核磷蛋白（NPM1）突变的AML中最常见的获得性突变之一，并且通常被认为是良好的预后因素（在不存在FLT3的- ITD）。 NPM1和IDH2的共同的突变已在文献中被描述为一个有利的预后指标5，用89％的3年总存活率。相比的整体3年生存率时，这代表了显著存活益处野生型NPM1和31％IDH2。例如，标准的护理实践包括NPM 1突变分析和FLT3-ITD突变。在这种情况下，只有一个NPM1突变的检测将无法适当地分层患者风险，作为二次突变可以是有利的（ 例如，IDH2）或不利（ 例如 ，TET2），减少了用于减轻骨髓移植的信心。 案例2 -固NGS面板 从FFPE组织提取的DNA是足够的质量和数量的固体NGS面板，用252纳克/微升的浓度，并只有4％以下1000碱基对（bp）的DNA组成。后的数据分析覆盖的平均深度为9167读取（远高于1000提供了最小深度截止读取）低于250阅读深度没有地区。附加QC指标笑WN在表3中 。 通过生物 ​​信息学流水线处理的数据检测到两个疾病相关的突变:一个在帧插入在ERBB2（HER2 / neu基因 ）的外显子20和TP53的错义突变。所有与他们的等位基因频率的外显子的变体示于表5表示。在ERBB2插入实际上代表重复的串联（HER2 / neu的 ）序列，所反映的命名法。鉴定及测序的框架所需的插入人工审核确认通过IGV读取。检测的大于50％的突变频率，如图同时为TP53和的Her2 / neu的突变是暗示杂合事件（见讨论）的损失的。 固NGS小组结果2例肺腺癌检测突变我ÑERBB2（HER2 / neu基因 ）和TP53，两个基因通常不为作为当前标准- -关心对肺癌患者的一部分。HER2 / neu基因在肺癌， 表皮生长因子受体编码类似另一种常用的突变基因酪氨酸激酶受体测试。激活HER2 / neu基因外显子20插入在2观察-肺腺癌的4％，占多数肺癌观察HER2 / neu基因的突变，并且通常见于肿瘤而不在其他司机的基因如EGFR和ALK 12突变。有证据表明潜在的几行各种治疗方案的患者激活HER2 / neu基因的插入，包括联合治疗HER2 / neu和mTOR抑制剂13，并与化疗15结合的单克隆抗体曲妥珠单抗显著疾病控制部分缓解。发现一个TP53变化不是不合作MMON癌症，但在这个时候有没有可行的疗法。 <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td></td><td> 情况1 </td><td> 案例2 </td></tr><tr><td> 启动总读取 </td><td> 2215926 </td><td> 2129110 </td></tr><tr><td> 百分比读取映射 </td><td> 98.42％ </td><td> 98.29％ </td></tr><tr><td> 百分比读取目标 </td><td> 99.01％ </td><td> 97.29％ </td></tr><tr><td> 百分比目标读取过滤器后 </td><td> 97.60％ </td><td> 95.45％ </td></tr><tr><td> 可用的百分比读取 </td><td> 94.87％ </td><td> 91.79％ </td></tr><tr><td> 上述250X覆盖基地的百分比 </td><td> 98.40％ </td><td> 100％ </td></tr><tr><td> 的基础百分比波夫1000X覆盖</td><td> 95.90％ </td><td> 99.70％ </td></tr><tr><td> 覆盖下面250X -扩增子数 </td><td> 8 </td><td> 0 </td></tr></tbody></table> 表 3: 测序运行QC度量这是最重要的运行统计数据的汇总，不包括平均覆盖面，即用于数据审查，以确定是否库准备的样品已通过QC。整个过程是成功的，如果所有的百分数都在90％以上，但它是可能的，与SW1的夹带或UB1在FPU洗涤步骤或引物串音，能有较低的"百分比上目标"中的80的范围内 - 90％。如果&#39;百分比映射&#39;太低，这将表明细菌或其它DNA的污染，因为所有的样品应对准人类。当这些指标都低于80％，将样品标记为进一步的审查，以帮助确定如何为proceed和提高的过程。 <img alt="表4" src="/files/ftp_upload/52758/52758tbl4.jpg" /> 表4:案例1的结果检测致病，相关疾病，意义不明的变异（VUS），以上列出的5％等位基因频率的报告标准可能良性的外显子的变种<a href="https://www.jove.com/files/ftp_upload/52758/JoVE_Table_4.xlsx" target="_blank">，请点击此处下载此表。</a> <img alt="表5" src="/files/ftp_upload/52758/52758tbl5.jpg" /> 表5:案例2检测结果相关的致病性，疾病，意义不明的变异（VUS），高于5％的等位基因频率的呈报准则的报告中列出可能的良性外显子的变种<a href="https://www.jove.com/files/ftp_upload/52758/JoVE_Table_5.xlsx" target="_blank">，请点击此处下载此表</a>。 补充图1:基于扩增子-SampleSheet.csv的一个例子。 此片材传送到定序执行何种化学方法（在此情况下，扩增子），什么工作流（ 例如，GenerateFastq），什么应用与检测（ 例如，FastqOnly），有多少个碱基（或读取），以序列（在此情况下，186 bp的点¯x186碱基对），最后什么样品用某些索引相关联（在这种情况下，双索引）。被突出显示为黄色的部分可以改为无论实验者希望，但在这种情况下，实验室使用这些参数。 <a href="https://www.jove.com/files/ftp_upload/52758/SupplementaryFigure1.pdf" target="_blank">请点击此处下载这个数字。</a>

Watch this Scientific Journal Video about Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors at JoVE.com

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

This manuscript describes clinical protocols for two next-generation sequencing panels. One panel interrogates hematologic malignancies while the other panel targets genes commonly mutated in solid tumors. Molecular classification of driver mutations in human malignancies offers valuable prognostic and predictive information.

新一代测序为可操作的突变在固体和液体瘤检测

As our understanding of the driver mutations necessary for initiation and progression of cancers improves, we gain critical information on how specific ...

next-generation-sequencing-for-detection-actionable-mutations-solid

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JoVE Journal

Cancer Research

24.2K 次观看.  Perelman School of Medicine, University of Pennsylvania. This manuscript describes clinical protocols for two next-generation sequencing panels. One panel interrogates hematologic malignancies while the other panel targets genes commonly mutated in solid tumors. Molecular classification of driver mutations in human malignancies offers valuable prognostic and predictive information.

视频: Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

The analysis of circulating tumor DNA (ctDNA) using next-generation sequencing (NGS) has become a valuable tool for the development of clinical oncology. However, the application of this method is challenging due to its low sensitivity in analyzing the trace amount of ctDNA in the blood. Furthermore, the method may generate false positive and negative results from this sequencing and subsequent analysis. To improve the feasibility and reliability of ctDNA detection in the clinic, here we present a technique which enriches rare mutations for sequencing, Enrich Rare Mutation Sequencing (ER-Seq). ER-Seq can distinguish a single mutation out of 1 x 107 wild-type nucleotides, which makes it a promising tool to detect extremely low frequency genetic alterations and thus will be very useful in studying disease heterogenicity. By virtue of the unique sequencing adapter&#39;s ligation, this method enables an efficient recovery of ctDNA molecules, while at the same time correcting for errors bidirectionally (sense and antisense). Our selection of 1021 kb probes enriches the measurement of target regions that cover over 95% of the tumor-related driver mutations in 12 tumors. This cost-effective and universal method enables a uniquely successful accumulation of genetic data. After efficiently filtering out background error, ER-seq can precisely detect rare mutations. Using a case study, we present a detailed protocol demonstrating probe design, library construction, and target DNA capture methodologies, while also including the data analysis workflow. The process to carry out this method typically takes 1-2 days.

This manuscript describes a technique for detecting mutations of low frequency in ctDNA, ER-Seq. This method is differentiated by its unique use of two-directional error correction, a special background filter, and efficient molecular acquirement.

利用下一代测序检测 CtDNA 中的稀有突变

The analysis of circulating tumor DNA (ctDNA) using next-generation sequencing (NGS) has become a valuable tool for the development of clinical oncology. ...

科研

癌症研究

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

The tumor immune microenvironment (TIME) has recently been recognized as a critical mediator of treatment response in solid tumors, especially for immunotherapies. Recent clinical advances in immunotherapy highlight the need for reproducible methods to accurately and thoroughly characterize the tumor and its associated immune infiltrate. Tumor enzymatic digestion and flow cytometric analysis allow broad characterization of numerous immune cell subsets and phenotypes; however, depth of analysis is often limited by fluorophore restrictions on panel design and the need to acquire large tumor samples to observe rare immune populations of interest. Thus, we have developed an effective and high throughput method for separating and enriching the tumor immune infiltrate from the non-immune tumor components. The described tumor digestion and centrifugal density-based separation technique allows separate characterization of tumor and tumor immune infiltrate fractions and preserves cellular viability, and thus, provides a broad characterization of the tumor immunologic state. This method was used to characterize the extensive spatial immune heterogeneity in solid tumors, which further demonstrates the need for consistent whole tumor immunologic profiling techniques. Overall, this method provides an effective and adaptable technique for the immunologic characterization of subcutaneous solid murine tumors; as such, this tool can be used to better characterize the tumoral immunologic features and in the preclinical evaluation of novel immunotherapeutic strategies.

Here we describe a method to separate and enrich components of the tumor immune and non-immune microenvironment in established subcutaneous tumors. This technique allows for the separate analysis of tumor immune infiltrate and non-immune tumor fractions which can permit comprehensive characterization of the tumor immune microenvironment.

肿瘤免疫和非免疫微环境在小鼠皮下肿瘤中的富集与鉴定

The tumor immune microenvironment (TIME) has recently been recognized as a critical mediator of treatment response in solid tumors, especially for ...

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular sub-classification and temporal monitoring of tumor response to therapy. Here, we describe our dPCR-based method for the detection of tumor somatic mutations in cell free DNA (cfDNA), readily available in&#160;patient biofluids. Although limited in the number of mutations that can be tested for in each assay, this method provides a high level of sensitivity and specificity. Monitoring of mutation abundance, as calculated by MAF, allows for the evaluation of tumor response to therapy, thereby providing a much-needed supplement to radiographic imaging.

Here, we present a protocol to detect tumor somatic mutations in circulating DNA present in patient biological fluids (biofluids). Our droplet digital polymerase chain reaction (dPCR)-based method enables quantification of the tumor mutation allelic frequency (MAF), facilitating a minimally invasive complement to diagnosis and temporal monitoring of tumor response.

患者生物流体中肿瘤相关循环DNA的检测与监测

Complications associated with upfront and repeat surgical tissue sampling present the need for minimally invasive platforms capable of molecular ...

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing

Gene fusions frequently contribute to the oncogenic phenotype of many different types of cancer. Additionally, the presence of certain fusions in samples from cancer patients often directly influences diagnosis, prognosis, and/or therapy selection. As a result, the accurate detection of gene fusions has become a critical component of clinical management for many disease types. Until recently, clinical gene fusion detection was predominantly accomplished through the use of single-gene assays. However, the ever-growing list of gene fusions with clinical significance has created a need for assessing fusion status of multiple genes simultaneously. Next generation sequencing (NGS)-based testing has met this demand through the ability to sequence nucleic acid in massively parallel fashion. Multiple NGS-based approaches that employ different strategies for gene target enrichment are now available for use in clinical molecular diagnostics, each with its own strengths and weaknesses. This article describes the use of anchored multiplex PCR (AMP)-based target enrichment and library preparation followed by NGS to assess for gene fusions in clinical solid tumor specimens. AMP is unique among amplicon-based enrichment approaches in that it identifies gene fusions regardless of the identity of the fusion partner. Detailed here are both the wet-bench and data analysis steps that ensure accurate gene fusion detection from clinical samples.

This article details the use of an anchored multiplex polymerase chain reaction-based library preparation kit followed by next-generation sequencing to assess for oncogenic gene fusions in clinical solid tumor samples. Both wet-bench and data analysis steps are described.

使用锚定多路聚合酶链反应的致癌基因融合检测,随后进行下一代测序

Gene fusions frequently contribute to the oncogenic phenotype of many different types of cancer. Additionally, the presence of certain fusions in samples ...

Generation of Orthotopic Pancreatic Tumors and Ex vivo Characterization of Tumor-Infiltrating T Cell Cytotoxicity

In vivo models of pancreatic cancer provide invaluable tools for studying disease dynamics, immune infiltration and new therapeutic strategies. The orthotopic murine model can be performed on large cohorts of immunocompetent mice simultaneously, is relatively inexpensive and preserves the cognate tissue microenvironment. The quantification of T cell infiltration and cytotoxic activity within orthotopic tumors provides a useful indicator of an antitumoral response.
This protocol describes the methodology for surgical generation of orthotopic pancreatic tumors by injection of a low number of syngeneic tumor cells resuspended in 5 &#181;L basement membrane directly into the pancreas. Mice bearing orthotopic tumors take approximately 30 days to reach endpoint, at which point tumors can be harvested and processed for characterization of tumor-infiltrating T cell activity. Rapid enzymatic digestion using collagenase and DNase allows a single-cell suspension to be extracted from tumors. The viability and cell surface markers of immune cells extracted from the tumor are preserved; therefore, it is appropriate for multiple downstream applications, including flow-assisted cell sorting of immune cells for culture or RNA extraction, flow cytometry analysis of immune cell populations. Here, we describe the ex vivo stimulation of T cell populations for intracellular cytokine quantification (IFN&#947; and TNF&#945;) and degranulation activity (CD107a) as a measure of overall cytotoxicity. Whole-tumor digests were stimulated with phorbol myristate acetate and ionomycin for 5 h, in the presence of anti-CD107a antibody in order to upregulate cytokine production and degranulation. The addition of brefeldin A and monensin for the final 4 h was performed to block extracellular transport and maximize cytokine detection. Extra- and intra-cellular staining of cells was then performed for flow cytometry analysis, where the proportion of IFN&#947;+, TNF&#945;+ and CD107a+ CD4+ and CD8+ T cells was quantified.
This method provides a starting base to perform comprehensive analysis of the tumor microenvironment.

Generation of Orthotopic Pancreatic Tumors and Ex vivo Characterization of Tumor-Infiltrating T Cell Cytotoxicity

This protocol describes the surgical generation of orthotopic pancreatic tumors and the rapid digestion of freshly isolated murine pancreatic tumors. Following digestion, viable immune cell populations can be used for further downstream analysis, including ex vivo stimulation of T cells for intracellular cytokine detection by flow cytometry.

正交胰腺肿瘤的产生与肿瘤渗透T细胞细胞毒性的外体特征

In vivo models of pancreatic cancer provide invaluable tools for studying disease dynamics, immune infiltration and new therapeutic strategies. The ...

Analysis of Side Population in Solid Tumor Cell Lines

Cancer stem cells (CSCs) are an important cause of tumor growth, metastasis, and recurrence. Isolation and identification of CSCs are of great significance for tumor research. Currently, several techniques are used for the identification and purification of CSCs from tumor tissues and tumor cell lines. Separation and analysis of side population (SP) cells are two of the commonly used methods. The methods rely on the ability of CSCs to rapidly expel fluorescent dyes, such as Hoechst 33342. The efflux of the dye is associated with the ATP-binding cassette (ABC) transporters and can be inhibited by ABC transporter inhibitors. Methods for staining cultured tumor cells with Hoechst 33342 and analyzing the proportion of their SP cells by flow cytometry are described. This assay is convenient, fast, and cost-effective. Data generated in this assay can contribute to a better understanding of the effect of genes or other extracellular and intracellular signals on the stemness properties of tumor cells.

A convenient, fast, and cost-effective method to measure the proportion of side population cells in solid tumor cell lines is presented.

固体肿瘤细胞系侧面人口分析

Cancer stem cells (CSCs) are an important cause of tumor growth, metastasis, and recurrence. Isolation and identification of CSCs are of great ...

Modeling Primary Bone Tumors and Bone Metastasis with Solid Tumor Graft Implantation into Bone

Primary bone tumors or bone metastasis from solid tumors result in painful osteolytic, osteoblastic, or mixed osteolytic/osteoblastic lesions. These lesions compromise bone structure, increase the risk of pathologic fracture, and leave patients with limited treatment options. Primary bone tumors metastasize to distant organs, with some types capable of spreading to other skeletal sites. However, recent evidence suggests that with many solid tumors, cancer cells that have spread to bone may be the primary source of cells that ultimately metastasize to other organ systems. Most syngeneic or xenograft mouse models of primary bone tumors involve intra-osseous (orthotopic) injection of tumor cell suspensions. Some animal models of skeletal metastasis from solid tumors also depend on direct bone injection, while others attempt to recapitulate additional steps of the bone metastatic cascade by injecting cells intravascularly or into the organ of the primary tumor. However, none of these models develop bone metastasis reliably or with an incidence of 100%. In addition, direct intra-osseous injection of tumor cells has been shown to be associated with potential tumor embolization of the lung. These embolic tumor cells engraft but do not recapitulate the metastatic cascade. We reported a mouse model of osteosarcoma in which fresh or cryopreserved tumor fragments (consisting of tumor cells plus stroma) are implanted directly into the proximal tibia using a minimally invasive surgical technique. These animals developed reproducible engraftment, growth, and, over time, osteolysis and lung metastasis. This technique has the versatility to be used to model solid tumor bone metastasis and can readily employ grafts consisting of one or multiple cell types, genetically-modified cells, patient-derived xenografts, and/or labeled cells that can be tracked by optical or advanced imaging. Here, we demonstrate this technique, modeling primary bone tumors and bone metastasis using solid tumor graft implantation into bone.

Bone metastasis models do not develop metastasis uniformly or with a 100% incidence. Direct intra-osseous tumor cell injection can result in embolization of the lung. We present our technique modeling primary bone tumors and bone metastasis using solid tumor graft implantation into bone, leading to reproducible engraftment and growth.

通过实体瘤移植植入骨模拟原发性骨肿瘤和骨转移

Primary bone tumors or bone metastasis from solid tumors result in painful osteolytic, osteoblastic, or mixed osteolytic/osteoblastic lesions. These ...

Detection of Cell-Free DNA in Blood Plasma Samples of Cancer Patients

Identifying mutations in tumors of cancer patients is a very important step in disease management. These mutations serve as biomarkers for tumor diagnosis as well as for the treatment selection and its response in cancer patients. The current gold standard method for detecting tumor mutations involves a genetic test of tumor DNA by means of tumor biopsies. However, this invasive method is difficult to be performed repeatedly as a follow-up test of the tumor mutational repertoire. Liquid biopsy is a new and emerging technique for detecting tumor mutations as an easy-to-use and non-invasive biopsy approach.
Cancer cells multiply rapidly. In parallel, numerous cancer cells undergo apoptosis. Debris from these cells are released into a patient&#8217;s circulatory system, together with finely fragmented DNA pieces, called cell-free DNA (cfDNA) fragments, which carry tumor DNA mutations. Therefore, for identifying cfDNA based biomarkers using liquid biopsy technique, blood samples are collected from the cancer patients, followed by the separation of plasma and buffy coat. Next, plasma is processed for the isolation of cfDNA, and the respective buffy coat is processed for the isolation of a patient&#39;s genomic DNA. Both nucleic acid samples are then checked for their quantity and quality; and analyzed for mutations using next-generation sequencing (NGS) techniques.
In this manuscript, we present a detailed protocol for liquid biopsy, including blood collection, plasma, and buffy coat separation, cfDNA and germline DNA extraction, quantification of cfDNA or germline DNA, and cfDNA fragment enrichment analysis.

In this paper we present a detailed protocol for non-invasive liquid biopsy technique, including blood collection, plasma and buffy coat separation, cfDNA and germline DNA extraction, quantification of cfDNA or germline DNA, and cfDNA fragment enrichment analysis.

癌症患者血浆样本中无细胞DNA检测

Identifying mutations in tumors of cancer patients is a very important step in disease management. These mutations serve as biomarkers for tumor diagnosis ...

Generation of Zebrafish Larval Xenografts and Tumor Behavior Analysis

Zebrafish larval xenografts are being widely used for cancer research to perform in vivo and real-time studies of human cancer. The possibility of rapidly visualizing the response to anti-cancer therapies (chemo, radiotherapy, and biologicals), angiogenesis and metastasis with single cell resolution, places the zebrafish xenograft model as a top choice to develop preclinical studies.

The zebrafish larval xenograft assay presents several experimental advantages compared to other models, but probably the most striking is the reduction of size scale and consequently time. This reduction of scale allows single cell imaging, the use of a relatively low number of human cells (compatible with biopsies), medium-high-throughput drug screenings, but most importantly enables a significant reduction of the time of the assay. All these advantages make the zebrafish xenograft assay extremely attractive for future personalized medicine applications.

Many zebrafish xenograft protocols have been developed with a wide diversity of human tumors; however, a general and standardized protocol to efficiently generate zebrafish larval xenografts is still lacking. Here we provide a step-by-step protocol, with tips to generate xenografts and guidelines for tumor behavior analysis, whole-mount immunofluorescence, and confocal imaging quantification.

Here, we provide a step-by-step protocol, with tips to generate xenografts and guidelines for tumor behavior analysis, whole-mount immunofluorescence, and confocal imaging quantification.

斑马鱼拉瓦尔异种草和肿瘤行为分析的一代

Zebrafish larval xenografts are being widely used for cancer research to perform in vivo and real-time studies of human cancer. The possibility of rapidly ...

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Multiplexing enables the assessment of several markers on the same tissue while providing spatial context. Spatial Omics technologies allow both protein and RNA multiplexing by leveraging photo-cleavable oligo-tagged antibodies and probes, respectively. Oligos are cleaved and quantified from specific regions across the tissue to elucidate the underlying biology. Here, the study demonstrates that automated custom antibody visualization protocols can be utilized to guide ROI selection in conjunction with spatial proteomics assays. This specific method did not show acceptable performance with spatial transcriptomics assays. The protocol describes the development of a 3-plex immunofluorescent (IF) assay for marker visualization on an automated platform, using tyramide signal amplification (TSA) to amplify the fluorescent signal from a given protein target and increase the antibody pool to choose from. The visualization protocol was automated using a thoroughly validated 3-plex assay to ensure quality and reproducibility. In addition, the exchange of DAPI for SYTO dyes was evaluated to allow imaging of TSA-based IF assays on the spatial profiling platform. Additionally, we tested the ability of selecting small ROIs using the spatial transcriptomics assay to allow the investigation of highly-specific areas of interest (e.g., areas enriched for a given cell type). ROIs of 50 &#181;m and 300 &#181;m diameter were collected, which corresponds to approximately 15 cells and 100 cells, respectively. Samples were made into libraries and sequenced to investigate the capability to detect signals from small ROIs and profile-specific regions of the tissue. We determined that spatial proteomics technologies highly benefit from automated, standardized protocols to guide ROI selection. While this automated visualization protocol was not compatible with spatial transcriptomics assays, we were able to test and confirm that specific cell populations can successfully be detected even in small ROIs with the standard manual visualization protocol.

Here, we describe a protocol for fine-tuning regions of interest (ROIs) for Spatial Omics technologies to better characterize the tumor microenvironment and identify specific cell populations. For proteomics assays, automated customized protocols can guide ROI selection, while transcriptomics assays can be fine-tuned utilizing ROIs as small as 50 &#181;m.

组织中蛋白质和RNA表达的空间分析:一种微调虚拟显微切割的方法

Multiplexing enables the assessment of several markers on the same tissue while providing spatial context. Spatial Omics technologies allow both protein ...