这项研究得到了日本促进科学学会 (15K08397) 对智明 Kahyo 的资助, 以及日本医学研究与发展署 (阿曼德) 的赠款 (927960719 号),为探索性研究提供的补助 (16K15256), 为促进全国大学管理费用赠款改革特别预算的相关项目支出 (1019253 号), 以及吸烟研究基金会, 以黑田东彦 Sugimura。作者感谢 Iwaizumi 博士和 Kurachi 博士的临床支持。出资人在编写手稿方面没有任何作用。图 3、图 4和表 4是根据 Kahyo等的文章改编和转载的。10, 征得 Elsevier 的许可。

研究设计由滨松大学医学院 (G-260-4) 的机构审查委员会批准。从病人和他的父母那里获得书面知情同意。
1. 基因组 DNA 的质量控制
注: 利用已建立的基于硅膜的 dna 纯化方法, 从外周血中提取基因组 dna (gDNA)。在下面的程序之前, 使用分光光度法测定 gDNA 的浓度。
<ol><li>在10–100µL 的浓度下制备 gDNA 样品。</li>
	<li>将10µL 的 DNA 样本缓冲区添加到8管带上。</li>
	<li>将1µL 的 DNA 阶梯或 gDNA 添加到试管中。使用微板块附件将混合物涡流1分钟。</li>
	<li>将管、凝胶装置和吸管贴入电泳仪 (材料表), 按 "开始" 按钮开始运行。 注: 电泳系统将自动操作, 一次点击开始按钮。</li>
	<li>确认在 electropherograms 上正确分配了 DNA 样本缓冲区中包含的较低标记。如果分配不正确, 请手动在软件的 "Electroherogram 模式" 中指定标记。 注: DNA 完整性号 (DIN) 将自动计算。DIN 值来自 DNA 完整性。高和低 DIN 值表示高度原封和强烈退化的 gDNA, 分别。</li>
	<li>指定软件 "区域模式" 中的 gDNA (> 200 bp) 的大小区域, 以自动计算 gDNA (> 200 bp) 的浓度。</li>
</ol>2. 底漆和探头设计
<ol><li>在以下条件下使用任何开放的访问工具计算熔化温度 (Tm) 值: 10–25基, 50 毫米 Na+/K+, 0.80 毫米 dNTPs, 3 毫米毫克2 + (材料表)。设计正向和反向引物, 放大含有目标等位基因的基因组区域, 其 Tm值约60摄氏度, 扩增子长度在 100–300 bp。 注: 请参阅表 1中的寡核苷酸浓度。</li>
	<li>根据以下条件设计了用于参考和变异等位基因的锁定核酸探针: (i) 1–6 LNAs 存在于每个探针中;(ii) 每个探针的 5 '-和 3 '-总站上分别存在荧光染料和淬火;(iii) 匹配和不匹配探针的 Tm值之间的区别是 > 10 °c;(iv) 匹配和不匹配探针的 Tm值分别高于引物 (例如, 向前底漆: 60.8 °c, 反向底漆: 59.8 °c, 参考等位基因探针 (匹配/不匹配): 62.6/45.3 °c, 变体等位基因探针 (匹配/不匹配): 61.7/50.5 °c]。Tm值是使用用于步骤2.1 的开放访问工具计算的。</li>
	<li>确保所设计的引物和探针不包含单核苷酸多态性, 频率为 > 0.1%, 由数据库确定 [例如, 单核苷酸态性数据库 (dbSNP)]。</li>
</ol>3. 数字 PCR
<ol><li>用 TE 缓冲器在表 1中描述的浓度中准备底漆、探针和 gDNA 库存解决方案, 并将它们存储在20–4°c。</li>
	<li>
将试剂在室温下混合, 总容积为15µL 到最后浓度, 如表1所述。
	<ol>
<li>在无模板控制 (NTC) 中添加3µL 的蒸馏水, 而不是 gDNA。</li>
		<li>准备3.5x 的 PCR 混合物的数量三个, 以解释吹打错误。</li>
	</ol>
</li>
	<li>将 PCR 混合物上下吸管混合。</li>
	<li>将加载平台设置在8管带上的芯片上, 并将其设置在自动加载机上。确保芯片与加载平台之间有联系。</li>
	<li>在平台上安装加载滑块, 并将滑块与装载机的塞子保持在一起。</li>
	<li>吸管15µL 的 PCR 混合物在平台附近的滑块尖端 (图 1A)。</li>
	<li>按加载程序的按钮 (大约1分钟) 运行加载程序。 注意: 如果在平台上保持少量 PCR 混合物, 这不是问题。可以按顺序重新运行加载程序。</li>
	<li>在密封增强剂的侧面槽中, 将带 PCR 混合物的芯片装入管内。推滑盖和顶盖的边缘, 以不打破芯片 (图 1B)。</li>
	<li>运行密封增强器 (约2分钟)。按顺序重新运行密封增强器1分钟, 如果液体的水坑仍然可见, 因为不完整的密封导致对正面信号的交叉污染 (图 1C和1D)。</li>
	<li>添加230µL 的密封液, 一个油基试剂, 到管。 注: 芯片现在应该浸入液体中。</li>
	<li>在热循环仪中设置管。运行热循环仪如表 2所述 (约2小时)。如果正分区分布不均匀 (图 1E), 则调整 PCR 的温度或持续时间。 注: 建议将坡道速度设置为约1摄氏度/秒。</li>
	<li>将管放在热循环仪中至少15分钟, 以减少基线噪音。 注意: 管子也可以在一夜之间被留下。甚至在第二天也检测到了荧光信号。</li>
	<li>在检测夹具上设置管, 将6毫升蒸馏水倒入夹具中。如果气泡在管子内外可见, 请清除它们 (图 1F和1G)。</li>
	<li>将夹具加载到检测器中, 然后在选择荧光、实验和示例/NTC 标签 (材料表) 后, 单击软件的 "运行" 按钮即可运行它。 注: 对八个具有默认强度的样本进行双色检测需要大约 4-5 分钟。</li>
	<li>确定位置图、直方图和2D 散点图。 注: iIf 的荧光强度的负面分区是高, 调整强度, 点击设置按钮的软件, 使其属于30–70范围内。</li>
	<li>使用以下公式计算变体等位基因分数 (VAF): <img alt="Equation 1" src="/files/ftp_upload/58199/58199eq1.jpg"> 在这里, Cv 和 Cr 分别是变体和参考等位基因的拷贝数。 注: 在基于泊松统计的软件程序中自动计算它们。</li>
</ol>4. PCR 产品的收集
<ol><li>从管子上取下密封液。</li>
	<li>将100µL 的 TE 缓冲器添加到管中。漩涡强烈为三十年代和简要地离心机管子。</li>
	<li>将 TE 溶液转移到另一管, 加入30µL 3 米醋酸钠和200µL 乙醇。</li>
	<li>冷却溶液在-20 摄氏度过夜。</li>
	<li>离心溶液为30分钟在 1.6万 x g和去除上清。</li>
	<li>添加300µL 80% 乙醇的管和涡。</li>
	<li>离心溶液为15分钟在 1.6万 x g和去除上清。使沉淀的空气干燥5分钟。</li>
	<li>在空气干燥后1–5µL 中溶解沉淀。</li>
	<li>如有必要, 可参照步骤 1, 使用电泳仪器评估产品尺寸。将溶液的1µL 对凝胶装置进行高灵敏度 (材料表)。</li>
</ol>

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作者没有什么可透露的。

DIN 值通常用于评估被破坏的 DNA (例如, gDNA 从福尔马林固定石蜡嵌入组织) 在定量或排序之前, 因为 gDNA 的高级退化可能导致低质量数据。因此, DIN 评估已成为人类 gDNA11质量控制的重要一步。因为在代表性实验使用的 gDNA 在它从血液提取以后被存放了在4°c 为4–11年, 它的 DIN 价值被确定了为质量控制在 dPCR 试验之前。如果材料被怀疑损坏, 则特别推荐此步骤。gDNA 的浓度也由电泳法测定。由于 dPCR 的动态范围不像 qPCR 由于分区的局限性而宽, gDNA 浓度的测量是成功 dPCR 检测的重要步骤。由于输入 DNA 的数量与 dPCR 测定中变异和参考等位基因的总拷贝数相关 (R-平方 = 0.935;表 4), 电泳对测定 dPCR 测定前的 gDNA 浓度有很重要的意义。
加载和密封过程是成功结果的重要步骤。确定在平台上适当安装 PCR 混合物并确保芯片与平台之间的接触是至关重要的 (图 1A)。从滑块中的 PCR 混合物的凸出可能导致芯片上的分布无效.确认在位置图上的正和负分区的分布也需要精确分析, 因为在泊松统计中假定 DNA 模板被随机分成1室。在代表性的结果中, 在整个芯片中分布有正的分区 (图 3)。这一结果符合泊松统计的要求, 反映了加载和密封程序是有效的。当在密封增强器中设置管时, 如果顶盖的中心部分被推得太强 (图 1B), 芯片可能会断裂。要避免这种情况, 请轻轻推顶盖的边缘。如果存在正分区的人工簇 (图 1D), 则由于分区之间的交叉污染, 复制编号可能会过高估计。如果表面上可见一滩液体 (如图 1C) (例如, 通过依次重新运行密封增强剂1分钟), 则应改进密封过程。如果正分区分布不均匀 (图 1E), 则由于密封液和水的放大或污染不足, 复制数可能被低估。pcr 条件应在这种情况下调整 [例如, 通过调整温度或 pcr 的持续时间 (步骤3.11 的协议), 或确保密封流体和水倒入夹具是干净的]。从浸泡在蒸馏水中的8管条中检测出荧光信号。如果气泡附着在管表面, 就有可能干扰信号检测 (图 1F)。因此, 气泡应该使用一个工具, 如细吸管提示清除。此外, 空气气泡可能形成的管道内, 当他们设置在夹具 (图 1G)。如果管子内的气泡足够大, 足以覆盖芯片, 它们也应该被清除。气泡可能会清除, 如果他们在室温下离开几分钟。
在 NTC 中可能检测到一些积极的分区。为了避免 DNA 模板的污染, 保持工作台的清洁, 如果可能的话, 用风扇过滤单元制造一个干净的空间。如果怀疑 DNA 模板的污染, 彻底清除空间和/或丢弃使用过的试剂。相比之下, 如果在 gDNA 存在时未检测到参考等位基因的阳性分区, 请重新确认 gDNA、底漆和探针的浓度。值得注意的是, 与常规 PCR (表 1)12相比, 引物在代表性实验中使用的浓度较低。在常规 PCR 中, 确定斜坡速率是非常重要的, 这种速度很少改变。
是什么使 dPCR 与芯片在一管格式独特的是分割 PCR 混合物内的通用8管条8,13。该系统不需要将分区腔转移到 PCR 管中, 从而降低了污染风险。还有一个优势, 在 dPCR 系统与芯片在一管格式;它需要 < 4 小时完成96化验, 在该 dPCR 系统, 而它需要至少5小时完成相同数量的化验, 以液滴为基础的 dPCR14。此外, 通用8管带允许使用传统的热循环仪, 不像另一个基于芯片的 dPCR15, 这需要一个热循环仪与扁平块。此外, 常规 PCR 的积累知识和试剂也可应用于 dPCR 系统。这将有助于扩大 dPCR 的应用。
应该指出的是, dPCR 有几个限制。在 dPCR 中, 与其他 dPCR 平台相比, 芯片的分区数相对较低。对芯片设备的进一步改进将需要增加动态范围, 这取决于分区的数量。由于通用管的内部空间有限, 因此需要对芯片设备进行突破性设计, 以增加分区数量。未来整个 dPCR 程序的自动化将大大减少人为错误, 从而产生更可靠的结果。由于其高吞吐量和高灵敏度的性质, dPCR 与芯片内管的格式有望被应用于处理一些样品的液体活检和环境 DNA。

定量 PCR (qPCR) 经常用于量化人类遗传变异, 包括单核苷酸变异 (SNVs) 和 DNA 拷贝数变异 (CNVs)。在 qPCR 中, 在每管中进行聚合酶反应的方式与常规终点 PCR 方法相同, 在每个热循环后从管中获得放大信号。相比之下, 在 dPCR, 这意味着终点 dPCR 在本报告中, PCR 混合物被加载到许多微观室, 称为分区, 其中 DNA 模板是存在或缺席的限制稀释, 和每一个包含 PCR 混合物的分区被评估为完全 PCR 后阴性或阳性。虽然很容易估计在负分区中没有 dna 模板, 但目前尚不清楚阳性分区中有多少个 dna 模板拷贝。因此, 在正分区中的 DNA 模板数根据泊松分布估计, 使用来自负分区1的计数。与 qPCR 相比, dPCR 成本更高, 动态范围更小, 但是这种方法能够实现绝对量化, 并提供更高的灵敏度和更精确的2。
dPCR 的主要应用之一是对下一代测序识别的变种进行验证。特别是在罕见变型的情况下, 这意味着低变型分数, 验证是至关重要的, 因为排序错误可能发生在3。虽然 qPCR 是验证 SNVs 和 CNVs 的有用工具, 但与 dPCR 相比, 它们的灵敏度较低。因此, dPCR 技术对处理稀有变种的遗传研究是有需求的。最近, 经液体活检发现的罕见变种与癌症的特点, 如耐药性, 已成为分子诊断和治疗的热门话题4。dPCR 技术似乎适合于液体活检研究, 预计在不久的将来将有重要的临床应用, 尽管有关动态范围和成本的改进仍需实施。
商业可用的 dPCR 技术大致可以分为液滴和基于芯片的平台;不同的是 DNA 模板是如何划分5,6,7。在 dPCR 与管状芯片的格式, PCR 混合物由毛细管作用分配到芯片上的分区。芯片是建立在八管条, 许多实验室工作人员将已经熟悉, 因此, 八样品可以处理一次8。在阅读步骤中, 通过检测芯片的整个图像而不是每个分区来处理96个样本需要 < 1 小时。由于 dPCR 与其他 dPCR 系统相比具有较高的吞吐量, 因此, 可用性和生产率是其用户的主要优势。
在本报告中, 以零星家族性腺瘤性息肉病患者的APC基因体细胞嵌合体为典型病例, 并比较 dPCR 和结果。本报告的主要目的是要清楚地量化一个单一核苷酸变体使用 dPCR 与芯片在一管格式。我们希望这份报告能帮助感兴趣的研究人员为自己的工作采用 dPCR 平台。

<table border="0" cellpadding="0" cellspacing="0" style="width:772px;" width="771">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">QIAamp DNA Blood Maxi Kit</td>
			<td style="width:147px;">Qiagen</td>
			<td style="width:188px;">51194</td>
			<td style="width:291px;">Before Protocol 1: Extraction of genomic DNA</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">NanoDrop 1000</td>
			<td style="width:147px;">ThermoFisher SCIENTIFIC</td>
			<td style="width:188px;">ND-8000</td>
			<td>Before Protocol 1: Spectrophotometer</td>
		</tr>
		<tr height="81">
			<td height="81" style="height:81px;width:147px;">8-strip tube</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">401428</td>
			<td>Protocol 1</td>
		</tr>
		<tr height="98">
			<td height="98" style="height:98px;width:147px;">Genomic DNA sample buffer</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">5067-5366</td>
			<td style="width:291px;">Protocol 1: 
			A component of Genomic DNA Screen Tape Assay</td>
		</tr>
		<tr height="83">
			<td height="83" style="height:83px;width:147px;">DNA ladder</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">5067-5366</td>
			<td style="width:291px;">Protocol 1: 
			A component of Genomic DNA Screen Tape Assay</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">MS3 Basic Small Shaker</td>
			<td style="width:147px;">IKA</td>
			<td style="width:188px;">3617000</td>
			<td>Protocol 1: Vortex mixer</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Genomic DNA ScreenTape</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">5067-5365</td>
			<td>Protocol 1: Gel device</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">2200 TapeStation system</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">G2965AA</td>
			<td>Protocol 1: Electrophoresis instrument</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">TapeStation Analysis Software</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">Bundled with G2965AA</td>
			<td>Protocol 1: Analysis software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:147px;">DNA oligo primers</td>
			<td style="width:147px;">IDT</td>
			<td style="width:188px;">Custom order</td>
			<td>Protocol 2</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:147px;">LNA probes</td>
			<td style="width:147px;">IDT</td>
			<td style="width:188px;">Custom order</td>
			<td>Protocol 2</td>
		</tr>
		<tr height="51">
			<td height="51" style="height:51px;width:147px;">Software tool</td>
			<td style="width:147px;">IDT</td>
			<td style="width:188px;">Web site: http://biophysics.idtdna.com/</td>
			<td>Protocol 2</td>
		</tr>
		<tr height="70">
			<td height="70" style="height:70px;width:147px;">dbSNP database</td>
			<td style="width:147px;">NCBI</td>
			<td style="width:188px;">Web site: https://www.ncbi.nlm.nih.gov/projects/SNP/</td>
			<td>Protocol 2</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">TE buffer</td>
			<td style="width:147px;">ThermoFisher SCIENTIFIC</td>
			<td style="width:188px;">12090015</td>
			<td>Protocol 3</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">DNase/RNase-Free Distilled Water</td>
			<td style="width:147px;">ThermoFisher SCIENTIFIC</td>
			<td style="width:188px;">10977015</td>
			<td>Protocol 3 (Table 1)</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Digital PCR Probe Mastermix</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12013</td>
			<td style="width:291px;">Protocol 3 (Table 1): 2xPCR Master Mix 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Sealing Fluid</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12005</td>
			<td style="width:291px;">Protocol 3: Sealing fluid 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity JN Solution</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12006</td>
			<td style="width:291px;">Protocol 3 (Table 1): 20xdPCR solution 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Tube-strip</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12007</td>
			<td style="width:291px;">Protocol 3: Chip-in-a-tube 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Sample Loading Kit</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">12008</td>
			<td style="width:291px;">Protocol 3: Loading platform and slider 
			A component of #10011</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Auto Loader</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">11002</td>
			<td style="width:291px;">Protocol 3: Auto loader 
			A component of #10001</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Sealing Enhancer</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">11003</td>
			<td style="width:291px;">Protocol 3: Sealing enhancer 
			A component of #10001</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">Clarity Reader</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">11004</td>
			<td style="width:291px;">Protocol 3: Reader 
			A component of #10001</td>
		</tr>
		<tr height="46">
			<td height="46" style="height:46px;width:147px;">Life Eco Thermal Cycler</td>
			<td style="width:147px;">Bioer Technology</td>
			<td style="width:188px;">TC-96GHbC</td>
			<td>Protocol 3: Thermal cycler</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:147px;">Clarity Software</td>
			<td style="width:147px;">JN Medsys</td>
			<td style="width:188px;">Bundled with #10001</td>
			<td style="width:291px;">Protocol 3: Analysis software</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:147px;">High Sensitivity D1000 screen tape</td>
			<td style="width:147px;">Agilent Technologies</td>
			<td style="width:188px;">5067-5584</td>
			<td>Protocol 4: Gel device for high sensitivity</td>
		</tr>
	</tbody>
</table>

digital polymerase chain reaction assay for the genetic variation in a sporadic familial adenomatous polyposis patient using the chip-in-a-tube format

对人类遗传变异的定量分析对于了解肿瘤等严重疾病的分子特征至关重要。由于数字聚合酶链反应 (PCR) 能够精确量化 DNA 拷贝数变体, 它们正成为检测稀有遗传变异的重要工具, 如耐药性突变。预计在不久的将来, 使用数字 PCR (dPCR) 的分子诊断将在临床实践中得到应用;因此, 如何有效地进行 dPCR 的人类遗传物质是一个热门话题。在这里, 我们介绍了一种检测腺瘤型息肉样大肠杆菌(APC) 体细胞嵌合体的方法, 使用 dPCR 与芯片内管格式, 这使得八 dPCR 反应同时进行。在填充和密封的反应混合物在芯片上应注意。本文演示如何避免对正分区的过度和低估。此外, 我们提出了一个简单的程序, 从芯片上的分区收集 dPCR 产品, 然后可以用来确认具体放大。我们希望这种方法的报告将有助于促进 dPCR 与芯片内管方法在遗传学研究。

根据上述的程序, 我们回顾了一个有零星家族性腺瘤性息肉病患者的APC基因的体细胞嵌合体。在先前的一项研究中, 834 + 2T > c 的变异是在病人身上发现的, 但在他们的父母中却没有, 使用了桑格测序和9。表 3显示了代表性结果中使用的引物和探头的设计。基因组 DNA 从先证者、父母和六健康捐献者的血液中提取。九 gDNA 样品的 DIN 值范围到 6.7–7.9 (图 2和表 4)。分别用家族和十六进制作为 C 和 T 等位基因的荧光染料。位置图上的绿色和黄色斑点分别代表了两个正则和六角正的分块 (数字 3A)。蓝色斑点代表了两个家族和十六进制的负分区。黑色背景对应于未添加反应混合物的分区。在先证者中发现了 c 和 T 等位基因的许多阳性分区, 而在先证者的父亲或 NTC 中检测到 c 等位基因的阳性分区很少, 而后者则未发现 T 等位基因的阳性分区。在二维 (2 维) 散点图上, C 和 T 等位基因之间的信号分离是明确的, 而十六进制和家族的最正信号是相互排斥的 (图 3B)。VAF 的先证者是 13.2%, 这是类似于确定使用的 (12.7%)(表 4)。先证者的父母和健康的捐赠者的 VAFs 是 < 0.1%。APC c. 834 + 2T > c 突变的检测极限被估计为 0.3%, 使用3x 的重复测量的标准偏差与总 gDNA10的10–11。
834 + 2T > c 扩增子的 dPCR 检测量预测为 123 bp。为了确认 dPCR 产品被放大为一个单一的波段, dPCR 产品收集从测定芯片。使用电泳, 一个单一的波段被清楚地检测, 和产品的大小是一致的预测 (图 4)。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58199/58199fig1.jpg"> 图 1: dPCR 用管状芯片的格式进行检测的注意事项.(A) 本小组展示如何在自动加载机中设置8管条。(B) 本小组显示碎薯条。(C) 此面板显示了在 (i) 加载和 (ii) 密封后芯片表面的情况。(iii) 在密封不完全的情况下, 可看到液体的水坑。(D) 本小组显示在交叉污染情况下的位置图。(E) 本小组在分配不均的情况下显示了立场图。(F) 本小组展示了管表面气泡如何浸入水中。(G) 此面板显示管内的气泡。在整个图中, 黑白箭头分别表示破碎的芯片碎片和气泡。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58199/58199fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/58199/58199fig2.jpg"> 图 2: 代表血液 gDNA 的 electropherograms.Electropherograms 的血液 gDNA 与 DIN 值6.7 和7.9 分别显示在上部和底部的面板上。星号表示较低的标记。DIN: DNA 完整性数字。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58199/58199fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58199/58199fig3.jpg"> 图 3: APC体细胞嵌合体的代表性结果使用 dPCR 与芯片在 a 管格式.(a) scatterplots 的位置图和 (B) 无模板控制 (NTC)、先证者和父亲的情况显示在这里。十六进制和 FAM 分别对应于参考和变异的等位基因。垂直和水平线分别表示十六进制和 FAM 强度的阈值。这个数字已经从 Kahyo等。10.<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58199/58199fig3large.jpg" target="_blank">请点击这里查看这个数字的更大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/58199/58199fig4.jpg"> 图 4: 从测定芯片中收集 dPCR 产品.收集和浓缩的 dPCR 产品均受到电泳。预测的目标大小为 123 bp。这个数字已经从 Kahyo等。10. NTC: 无模板控制。<a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58199/58199fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<table fo:keep-together.within-page="1"><tbody>
<tr>
<td>试剂</td>
			<td>浓度 的库存解决方案</td>
			<td>容量 (ul)</td>
			<td>最终浓度</td>
			<td>推荐 最终浓度</td>
		</tr>
<tr>
<td>DNase/RNase 无水蒸馏水</td>
			<td>-</td>
			<td>1.75</td>
			<td>-</td>
			<td>-</td>
		</tr>
<tr>
<td>2x PCR 大师组合</td>
			<td>-</td>
			<td>7。5</td>
			<td>-</td>
			<td>-</td>
		</tr>
<tr>
<td>主要等位基因的低噪声探针</td>
			<td>2微米</td>
			<td>0。5</td>
			<td>66.7 毫微米</td>
			<td>3.33–100 nM</td>
		</tr>
<tr>
<td>小等位基因的低噪声探头</td>
			<td>2微米</td>
			<td>0。5</td>
			<td>66.7 毫微米</td>
			<td>3.33–100 nM</td>
		</tr>
<tr>
<td>前进底漆</td>
			<td>1微米</td>
			<td>0。5</td>
			<td>33.3 毫微米</td>
			<td>3.33–50.0 nM</td>
		</tr>
<tr>
<td>反向底漆</td>
			<td>1微米</td>
			<td>0。5</td>
			<td>33.3 毫微米</td>
			<td>3.33–50.0 nM</td>
		</tr>
<tr>
<td>20x dPCR 解决方案</td>
			<td>-</td>
			<td>0.75</td>
			<td>-</td>
			<td>-</td>
		</tr>
<tr>
<td>gDNA</td>
			<td>3.33 ng/ul</td>
			<td>3</td>
			<td>666页/ul</td>
			<td>20 pg/μL–2,000 pg/ul1
</td>
		</tr>
</tbody></table>表 1: 用于 dPCR 化验的试剂.1取决于预期的精度和灵敏度。
<table fo:keep-together.within-page="1"><tbody>
<tr>
<td>步</td>
			<td>温度</td>
			<td>时间</td>
			<td>周期</td>
		</tr>
<tr>
<td>初始变性</td>
			<td>95°c</td>
			<td>5米</td>
			<td>1</td>
		</tr>
<tr>
<td>变性 退火和延伸</td>
			<td>95°c 58°c</td>
			<td>五十年代 九十年代</td>
			<td>42</td>
		</tr>
<tr>
<td>最终扩展名</td>
			<td>70°c</td>
			<td>5米</td>
			<td>1</td>
		</tr>
</tbody></table>表 2: 热循环仪条件。
<table fo:keep-together.within-page="1"><tbody>
<tr>
<td>名字</td>
			<td>序列1</td>
			<td>Tm值2</td>
		</tr>
<tr>
<td>前进底漆</td>
			<td>5 '-GGTCAAGGAGTGGGAGAAATC-3′</td>
			<td>60.8 °c</td>
		</tr>
<tr>
<td>反向底漆</td>
			<td>5 '-TCTTAGAACCATCTTGCTTCATACT-3′</td>
			<td>59.8 °c</td>
		</tr>
<tr>
<td>T 等位基因的低噪声放大探针</td>
			<td>5 '-十六进制-ATTT [A] CCTGACCA-IBFQ-3 '</td>
			<td>匹配: 62.6 °c 不匹配: 45.3 °c</td>
		</tr>
<tr>
<td>C 等位基因的低噪声探针</td>
			<td>5 '-TTT [G] CCTGACC-IBFQ-3 '</td>
			<td>匹配: 61.7 °c 不匹配: 50.5 °c</td>
		</tr>
</tbody></table>表 3: 引物和探头的设计.1带下划线和括号内的字母分别是低噪声放大和目标变量。2根据协议的步骤2计算。
<table fo:keep-together.within-page="1"><tbody>
<tr>
<td></td>
			<td></td>
			<td></td>
			<td></td>
			<td>3</td>
			<td colspan="4">dPCR4</td>
		</tr>
<tr>
<td rowspan="2">样品1</td>
			<td rowspan="2">组织</td>
			<td rowspan="2">输入 DNA (ng)</td>
			<td rowspan="2">DIN2</td>
			<td rowspan="2">VAF (%)</td>
			<td rowspan="2">变体 (副本)</td>
			<td rowspan="2">参考 (复印件)</td>
			<td colspan="2">VAF (%)</td>
		</tr>
<tr>
<td>意味 着</td>
			<td>Rsd</td>
		</tr>
<tr>
<td>Ntc</td>
			<td>-</td>
			<td>-</td>
			<td>-</td>
			<td>-</td>
			<td>1.23</td>
			<td>0</td>
			<td>N/A</td>
			<td>N/A</td>
		</tr>
<tr>
<td>先证者</td>
			<td>血</td>
			<td>11。3</td>
			<td>7。6</td>
			<td>12。7</td>
			<td>379</td>
			<td>2.48 x 103
</td>
			<td>13。2</td>
			<td>0.0353</td>
		</tr>
<tr>
<td>父亲</td>
			<td>血</td>
			<td>10。3</td>
			<td>7。7</td>
			<td>0.0167</td>
			<td>1.08</td>
			<td>3.42 x 103
</td>
			<td>0.0341</td>
			<td>0.439</td>
		</tr>
<tr>
<td>母亲</td>
			<td>血</td>
			<td>10。8</td>
			<td>7。6</td>
			<td>0.0136</td>
			<td>0.956</td>
			<td>3.04 x 103
</td>
			<td>0.0313</td>
			<td>0.637</td>
		</tr>
<tr>
<td>Donor-1</td>
			<td>血</td>
			<td>11。7</td>
			<td>7。3</td>
			<td>-</td>
			<td>1.64</td>
			<td>3.01x 103
</td>
			<td>0.0543</td>
			<td>0.414</td>
		</tr>
<tr>
<td>Donor-2</td>
			<td>血</td>
			<td>10。5</td>
			<td>7。6</td>
			<td>-</td>
			<td>1.06</td>
			<td>2.90 x 103
</td>
			<td>0.0406</td>
			<td>0.539</td>
		</tr>
<tr>
<td>Donor-3</td>
			<td>血</td>
			<td>17。6</td>
			<td>7。9</td>
			<td>-</td>
			<td>4.24</td>
			<td>5.65 x 103
</td>
			<td>0.0713</td>
			<td>0.783</td>
		</tr>
<tr>
<td>Donor-4</td>
			<td>血</td>
			<td>12。3</td>
			<td>7。6</td>
			<td>-</td>
			<td>2.38</td>
			<td>4.16 x 103
</td>
			<td>0.0666</td>
			<td>0.557</td>
		</tr>
<tr>
<td>Donor-5</td>
			<td>血</td>
			<td>19。2</td>
			<td>7</td>
			<td>-</td>
			<td>1.48</td>
			<td>6.79 x 103
</td>
			<td>0.0213</td>
			<td>0.571</td>
		</tr>
<tr>
<td>Donor-6</td>
			<td>血</td>
			<td>14。4</td>
			<td>6。7</td>
			<td>-</td>
			<td>3.44</td>
			<td>4.67 x 103
</td>
			<td>0.0728</td>
			<td>0.729</td>
		</tr>
</tbody></table>表 4: dPCR 测定结果APC躯体嵌合体.1NTC: 无模板控制;捐献者: 健康的捐献者。2DIN: DNA 完整性数字。3Iwaizumi等。9、嗡嗡声基因组 2 15057 (2015)。4实验以三项、独立重复的3x 进行;数据表示为均值;区署: 相对标准差;不适用。表已从 Kahyo等修改。10。

Watch this Scientific Journal Video about Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format at JoVE

Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format

数字聚合酶链反应 (PCR) 是一个有用的工具, 高灵敏度检测单核苷酸变种和 DNA 复制数变种。在这里, 我们展示了测量人类基因组中稀有变种的关键考虑因素, 使用数字 PCR 技术与芯片内管格式。

数字聚合酶链反应法测定零星家族性腺瘤性息肉病患者的基因变异

The quantitative analysis of human genetic variation is crucial for understanding the molecular characteristics of serious medical conditions, such as ...

digital-polymerase-chain-reaction-assay-for-genetic-variation

Research

JoVE Journal

Cancer Research

10.8K 次观看.  Hamamatsu University School of Medicine. 数字聚合酶链反应 (PCR) 是一个有用的工具, 高灵敏度检测单核苷酸变种和 DNA 复制数变种。在这里, 我们展示了测量人类基因组中稀有变种的关键考虑因素, 使用数字 PCR 技术与芯片内管格式。

视频: Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format

The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics

Drosophila melanogaster has emerged as a powerful experimental system for functional and mechanistic studies of tumor development and progression in the context of a whole organism. Sophisticated techniques to generate genetic mosaics facilitate induction of visually marked, genetically defined clones surrounded by normal tissue. The clones can be analyzed through diverse molecular, cellular and omics approaches. This study describes how to generate fluorescently labeled clonal tumors of varying malignancy in the eye/antennal imaginal discs (EAD) of Drosophila larvae using the Mosaic Analysis with a Repressible Cell Marker (MARCM) technique. It describes procedures how to recover the mosaic EAD and brain from the larvae and how to process them for simultaneous imaging of fluorescent transgenic reporters and antibody staining. To facilitate molecular characterization of the mosaic tissue, we describe a protocol for isolation of total RNA from the EAD. The dissection procedure is suitable to recover EAD and brains from any larval stage. The fixation and staining protocol for imaginal discs works with a number of transgenic reporters and antibodies that recognize Drosophila proteins. The protocol for RNA isolation can be applied to various larval organs, whole larvae, and adult flies. Total RNA can be used for profiling of gene expression changes using candidate or genome-wide approaches. Finally, we detail a method for quantifying invasiveness of the clonal tumors. Although this method has limited use, its underlying concept is broadly applicable to other quantitative studies where cognitive bias must be avoided.

The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics

This protocol demonstrates how to generate fluorescently marked, genetically defined clonal tumors in the Drosophila eye/antennal imaginal discs (EAD). It describes how to dissect the EAD and brain from the third instar larvae and how to process them to visualize and quantify gene expression changes and tumor invasiveness.

该<em&gt;果蝇</em&gt;成虫盘瘤模型:基因的表达与肿瘤侵袭性的可视化和定量遗传马赛克

Drosophila melanogaster has emerged as a powerful experimental system for functional and mechanistic studies of tumor development and progression in the ...

科研

癌症研究

A Comprehensive Procedure to Evaluate the In Vitro Performance of the Putative Hemangioblastoma Neovascularization Using the Spheroid Sprouting Assay

The inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene plays a crucial role in the development of hemangioblastomas (HBs) within the human central nervous system (CNS). However, both the cytological origin and the evolutionary process of HBs (including neovascularization) remain controversial, and anti-angiogenesis for VHL-HBs, based on classic HB angiogenesis, have produced disappointing results in clinical trials. One major obstacle to the successful clinical translation of anti-vascular treatment is the lack of a thorough understanding of neovascularization in this vascular tumor. In this article, we present a comprehensive procedure to evaluate in vitro whether classic tumor angiogenesis exists in HBs, as well as its role in HBs. With this procedure, researchers can accurately understand the complexity of HB neovascularization and identify the function of this common form of angiogenesis in HBs. These protocols can be used to evaluate the most promising anti-vascular therapy for tumors, which has high translational potential either for tumors treatment or for aiding in the optimization of the anti-angiogenic treatment for HBs in future translations. The results highlight the complexity of HB neovascularization and suggest that this common form angiogenesis is only a complementary mechanism in HB neovascularization.

A Comprehensive Procedure to Evaluate the In Vitro Performance of the Putative Hemangioblastoma Neovascularization Using the Spheroid Sprouting Assay

This paper presents a comprehensive procedure to evaluate in vitro whether classic tumor angiogenesis exists in hemangioblastomas (HBs) and its role in HBs. The results highlight the complexity of HB-neovascularization and suggest that this common form of angiogenesis is only a complementary mechanism in the HB-neovascularization.

用球形发芽法评价 Hemangioblastoma 新生血管的体外性能的综合程序

The inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene plays a crucial role in the development of hemangioblastomas (HBs) within the human ...

Modeling Osteosarcoma Using Li-Fraumeni Syndrome Patient-derived Induced Pluripotent Stem Cells

Li-Fraumeni syndrome (LFS) is an autosomal dominant hereditary cancer disorder. Patients with LFS are predisposed to a various type of tumors, including osteosarcoma--one of the most frequent primary non-hematologic malignancies in the childhood and adolescence. Therefore, LFS provides an ideal model to study this malignancy. Taking advantage of iPSC methodologies, LFS-associated osteosarcoma can be successfully modeled by differentiating LFS patient iPSCs to mesenchymal stem cells (MSCs), and then to osteoblasts--the cells of origin for osteosarcomas. These LFS osteoblasts recapitulate oncogenic properties of osteosarcoma, providing an attractive model system for delineating the pathogenesis of osteosarcoma. This manuscript demonstrates a protocol for the generation of iPSCs from LFS patient fibroblasts, differentiation of iPSCs to MSCs, differentiation of MSCs to osteoblasts, and in vivo tumorigenesis using LFS osteoblasts. This iPSC disease model can be extended to identify potential biomarkers or therapeutic targets for LFS-associated osteosarcoma.

Here, we present a protocol for the generation of induced pluripotent Stem Cells (iPSCs) from Li-Fraumeni Syndrome (LFS) patient derived fibroblasts, differentiation of iPSCs via mesenchymal stem cells (MSCs) to osteoblasts, and modeling in vivo tumorigenesis using LFS patient-derived osteoblasts.

应用 Fraumeni 综合征诱导多潜能干细胞建模骨肉瘤

Li-Fraumeni syndrome (LFS) is an autosomal dominant hereditary cancer disorder. Patients with LFS are predisposed to a various type of tumors, including ...

Patient-derived Heterogeneous Xenograft Model of Pancreatic Cancer Using Zebrafish Larvae as Hosts for Comparative Drug Assessment

Patient-derived tumor xenograft (PDX) and cell-derived tumor xenograft (CDX) are important techniques for preclinical assessment, medication guidance and basic cancer researches. Generations of PDX models in traditional host mice are time-consuming and only working for a small proportion of samples. Recently, zebrafish PDX (zPDX) has emerged as a unique host system, with the characteristics of small-scale and high efficiency. Here, we describe an optimized methodology for generating a dual fluorescence-labeled tumor xenograft model for comparative chemotherapy assessment in zPDX models. Tumor cells and fibroblasts were enriched from freshly-harvested or frozen pancreatic cancer tissue at different culture conditions. Both cell groups were labeled by lentivirus expressing green or red fluorescent proteins, as well as an anti-apoptosis gene BCL2L1. The transfected cells were pre-mixed and co-injected into the 2 dpf larval zebrafish that were then bred in modified E3 medium at 32 &#176;C. The xenograft models were treated by chemotherapy drugs and/or BCL2L1 inhibitor, and the viabilities of both tumor cells and fibroblasts were investigated simultaneously. In summary, this protocol allows researchers to quickly generate a large amount of zPDX models with a heterogeneous tumor microenvironment and provides a longer observation window and a more precise quantitation in assessing the efficiency of drug candidates.

This protocol describes optimization procedures in a virus-based dual fluorescence-labeled tumor xenograft model using larval zebrafish as hosts. This heterogeneous xenograft model mimics the tissue composition of pancreatic cancer microenvironment in vivo and serves as a more precise tool for assessing drug responses in personalized zPDX (zebrafish patient-derived xenograft) models.

患者衍生的胰腺癌异质异种移植模型,使用斑马鱼幼虫作为比较药物评估的宿主

Patient-derived tumor xenograft (PDX) and cell-derived tumor xenograft (CDX) are important techniques for preclinical assessment, medication guidance and ...

Droplet Digital TRAP (ddTRAP): Adaptation of the Telomere Repeat Amplification Protocol to Droplet Digital Polymerase Chain Reaction

The telomere repeat amplification protocol (TRAP) is the most widely used assay to detect telomerase activity within a given a sample. The polymerase chain reaction (PCR)-based method allows for robust measurements of enzyme activity from most cell lysates. The gel-based TRAP with fluorescently labeled primers limits sample throughput, and the ability to detect differences in samples is restricted to two fold or greater changes in enzyme activity. The droplet digital TRAP, ddTRAP, is a highly sensitive approach that has been modified from the traditional TRAP assay, enabling the user to perform a robust analysis on 96 samples per run and obtain absolute quantification of the DNA (telomerase extension products) input within each PCR. Therefore, the newly developed ddTRAP assay overcomes the limitations of the traditional gel-based TRAP assay and provides a more efficient, accurate, and quantitative approach to measuring telomerase activity within laboratory and clinical settings.

Droplet Digital TRAP ddTRAP: Adaptation of the Telomere Repeat Amplification Protocol to Droplet Digital Polymerase Chain Reaction

We successfully converted the standard telomere repeat amplification protocol (TRAP) assay to be employed in droplet digital polymerase chain reactions. This new assay, called ddTRAP, is more sensitive and quantitative, allowing for better detection and statistical analysis of telomerase activity within various human cells.

液滴数字 TRAP (ddTRAP): 对端粒重复放大协议的适应性, 以实现液滴数字聚合酶链反应

The telomere repeat amplification protocol (TRAP) is the most widely used assay to detect telomerase activity within a given a sample. The polymerase ...

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 ...

Enhanced Viability for Ex vivo 3D Hydrogel Cultures of Patient-Derived Xenografts in a Perfused Microfluidic Platform

Patient-derived xenografts (PDX), generated when resected patient tumor tissue is engrafted directly into immunocompromised mice, remain biologically stable, thereby preserving molecular, genetic, and histological features, as well as heterogeneity of the original tumor. However, using these models to perform a multitude of experiments, including drug screening, is prohibitive both in terms of cost and time. Three-dimensional (3D) culture systems are widely viewed as platforms in which cancer cells retain their biological integrity through biochemical interactions, morphology, and architecture. Our team has extensive experience culturing PDX cells in vitro using 3D matrices composed of hyaluronic acid (HA). In order to separate mouse fibroblast stromal cells associated with PDXs, we use rotation culture, where stromal cells adhere to the surface of tissue culture-treated plates while dissociated PDX tumor cells float and self-associate into multicellular clusters. Also floating in the supernatant are single, often dead cells, which present a challenge in collecting viable PDX clusters for downstream encapsulation into hydrogels for 3D cell culture. In order to separate these single cells from live cell clusters, we have employed density step gradient centrifugation. The protocol described here allows for the depletion of non-viable single cells from the healthy population of cell clusters that will be used for further in vitro experimentation. In our studies, we incorporate the 3D cultures in microfluidic plates which allow for media perfusion during culture. After assessing the resultant cultures using a fluorescent image-based viability assay of purified versus non-purified cells, our results show that this additional separation step substantially reduced the number of non-viable cells from our cultures.

This protocol demonstrates methods to enable extended in vitro culture of patient-derived xenografts (PDX). One step enhances overall viability of multicellular cluster cultures in 3D hydrogels, through straightforward removal of non-viable single cells. A secondary step demonstrates best practices for PDX culture in a perfused microfluidic platform.

在全融合微流体平台中增强患者衍生异种移植物的外体 3D 水凝胶培养物的生存能力

Patient-derived xenografts (PDX), generated when resected patient tumor tissue is engrafted directly into immunocompromised mice, remain biologically ...

Pathological Analysis of Lung Metastasis Following Lateral Tail-Vein Injection of Tumor Cells

Metastasis, the primary cause of morbidity and mortality for most cancer patients, can be challenging to model preclinically in mice. Few spontaneous metastasis models are available. Thus, the experimental metastasis model involving tail-vein injection of suitable cell lines is a mainstay of metastasis research. When cancer cells are injected into the lateral tail-vein, the lung is their preferred site of colonization. A potential limitation of this technique is the accurate quantification of the metastatic lung tumor burden. While some investigators count macrometastases of a pre-defined size and/or include micrometastases following sectioning of tissue, others determine the area of metastatic lesions relative to normal tissue area. Both of these quantification methods can be exceedingly difficult when the metastatic burden is high. Herein, we demonstrate an intravenous injection model of lung metastasis followed by an advanced method for quantifying metastatic tumor burden using image analysis software. This process allows for investigation of multiple end-point parameters, including average metastasis size, total number of metastases, and total metastasis area, to provide a comprehensive analysis. Furthermore, this method has been reviewed by a veterinary pathologist board-certified by the American College of Veterinary Pathologists (SEK) to ensure accuracy.

Intravenous injection of cancer cells is often used in metastasis research, but the metastatic tumor burden can be difficult to analyze. Herein, we demonstrate a tail-vein injection model of metastasis and include a novel approach to analyze the resulting metastatic lung tumor burden.

肿瘤细胞外侧尾静脉注射后肺转移的病理分析

Metastasis, the primary cause of morbidity and mortality for most cancer patients, can be challenging to model preclinically in mice. Few spontaneous ...

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

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

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

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

使用患者源性肿瘤类器官的高通量 体外 检测

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

数字聚合酶链反应法测定零星家族性腺瘤性息肉病患者的基因变异

摘要

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该

用球形发芽法评价 Hemangioblastoma 新生血管的体外性能的综合程序

应用 Fraumeni 综合征诱导多潜能干细胞建模骨肉瘤

患者衍生的胰腺癌异质异种移植模型,使用斑马鱼幼虫作为比较药物评估的宿主

液滴数字 TRAP (ddTRAP): 对端粒重复放大协议的适应性, 以实现液滴数字聚合酶链反应

患者生物流体中肿瘤相关循环DNA的检测与监测

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

在全融合微流体平台中增强患者衍生异种移植物的外体 3D 水凝胶培养物的生存能力

肿瘤细胞外侧尾静脉注射后肺转移的病理分析

使用患者源性肿瘤类器官的高通量体外检测

数字聚合酶链反应法测定零星家族性腺瘤性息肉病患者的基因变异

摘要

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该

用球形发芽法评价 Hemangioblastoma 新生血管的体外性能的综合程序

应用 Fraumeni 综合征诱导多潜能干细胞建模骨肉瘤

患者衍生的胰腺癌异质异种移植模型,使用斑马鱼幼虫作为比较药物评估的宿主

液滴数字 TRAP (ddTRAP): 对端粒重复放大协议的适应性, 以实现液滴数字聚合酶链反应

患者生物流体中肿瘤相关循环DNA的检测与监测

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

在全融合微流体平台中增强患者衍生异种移植物的外体 3D 水凝胶培养物的生存能力

肿瘤细胞外侧尾静脉注射后肺转移的病理分析

使用患者源性肿瘤类器官的高通量 体外 检测

使用患者源性肿瘤类器官的高通量体外检测