这项研究得到了全国儿童医院阿比盖尔·韦克斯纳研究所的高性能计算设施的支持。这项工作得到了美国国立卫生研究院国家癌症研究所[U54 CA231641至SLL，R01 CA183776至SLL]的支持;亚历克斯的柠檬水摊位基金会[ERT青年研究员奖];佩洛托尼亚[ERT奖学金];和国家卫生与医学研究委员会CJ Martin海外生物医学奖学金[APP1111032至KIP]。

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SLL作为Salarius Pharmaceuticals的顾问委员会成员和股东宣布存在利益冲突。SLL也是美国专利号的上市发明人。US 7，393，253 B2，"用于诊断和治疗尤文氏肉瘤的方法和组合物"和US 8，557，532，"耐药尤文氏肉瘤的诊断和治疗"。这不会改变我们对JoVE共享数据和材料的政策的遵守。

研究致癌转录因子的生化机制对于了解它们引起的疾病和设计新的治疗策略至关重要。在以染色体易位为特征的恶性肿瘤中尤其如此，导致融合转录因子。这些嵌合蛋白中包含的结构域可能与野生型蛋白质中存在的调节结构域缺乏有意义的相互作用，使在融合的背景下解释结构 - 功能信息的能力复杂化26，27，28。此外，许多这些致癌融合的特征是低复杂性的内在无序结构域10，13，29，30。
EWS结构域是这种本质无序结构域的一个例子，该域涉及各种致癌融合10。固有的无序性和重复性阻碍了理解EWS结构域所采用的分子机制的努力。先前研究结构 - 功能的努力在很大程度上诉诸于在报告基因测定的背景下或在细胞背景中使用不同的突变体，这些突变体无法概括相关的细胞背景，或者缺乏任何产生有意义的部分功能的结构变异11，17，25。此处介绍的方法解决了这些问题。在疾病相关细胞环境中进行结构-功能映射，下一代测序使转录组学谱分析能够在天然染色质的设置下评估转录因子功能。在EWS / FLI的DAF突变体的特定情况下，据报道DAF在使用分离的反应元件的报告基因测定中几乎没有活性，但在完整基因启动子的背景下显示活性，无论是在报告测定中还是在天然染色质中，都表明一个有趣的表型23。使用这里描述的方法更直接地解决了基因组中哪种类型的调节元件在疾病环境中反应最灵敏的问题。通过同时在其天然染色质环境中测试所有候选靶基因，转录组学方法更有可能识别具有部分功能的构建体。
使用与疾病相关的细胞背景的固有强度可能是这种技术的最大局限性。最重要的因素之一是为这些实验选择合适的细胞系统。许多来自具有特征性转录因子的恶性肿瘤的细胞系不容易耐受该转录因子的敲低，并且在许多情况下，特别是对于儿科癌症，真正的起源细胞仍然存在争议，并且癌基因在其他细胞背景中的表达是令人望而却步的毒性31，32 .在这些情况下，在不同的细胞背景中进行实验可能会有所帮助，只要研究人员在解释结果时要谨慎，并在更与疾病相关的细胞类型中适当地验证任何相关发现。
至关重要的是要仔细验证癌基因表达的稳定性和表型后果，并且只提交符合严格标准的测序样品。在这里，这包括用于确认敲低和挽救的蛋白质印迹，以及用于验证阳性对照的少量已知靶基因的qRT-PCR（图2）。同样重要的是，通过在每个批次中尽可能相似地仔细地进行细胞和RNA制备，尽可能减少批次变异性。
这里描述的方法在与其他类型的基因组数据配对时变得特别强大，这些数据与所研究的转录因子的全基因组功能有关。这种类型的结构功能分析的未来方向将扩展到包括ChIP-seq和ATAC-seq，以确定转录因子的结合以及染色质可及性的任何诱导变化。作为一套，这种类型的数据可以指出致癌转录因子的不同结构成分对功能的不同方面的贡献（即DNA结合与染色质修饰与共同调节剂招募）。总体而言，使用基于NGS的方法绘制融合转录因子的结构 - 功能关系可以揭示这些蛋白质致癌功能的生化决定因素的新见解。这对于进一步了解它们引起的疾病以及开发新的治疗策略非常重要。

癌症的一个子集，包括许多儿童和青春期的恶性肿瘤，其特征在于染色体易位，产生新的融合癌基因1，2，3，4，5，6。由此产生的融合蛋白经常作为致癌转录因子起作用，协调转录调控的广泛变化以促进肿瘤发生7，8。具有这些易位的癌症通常具有安静的突变景观，除了特征性融合之外，很少有反复出现的基因组畸变4，9。因此，直接靶向融合蛋白是这些疾病中一种有吸引力的治疗策略。然而，这些致癌转录因子通常由低复杂性，内在无序，转录激活结构域与DNA结合结构域（DBD）融合10，11，12，13，14组成。这些蛋白质的内在无序结构域（IDD）和DBD都已被证明很难用传统的药理学方法靶向。因此，开发新的治疗方法需要更详细的分子理解这些融合所采用的机制，以异常地调节基因表达。
EWSR1的N端IDD部分通常融合到癌症中的DBD，包括尤文氏肉瘤中的EWS / FLI，弥漫性小圆细胞肿瘤中的EWS / WT1以及软部分10的透明细胞肉瘤中的EWS /ATF1。EWS IDD在每次聚变中的机制作用尚不清楚。EWS/ETS系列融合，特别是EWS/FLI，是迄今为止功能最突出的融合。EWS/ FLI协调全基因组表观遗传和转录变化，导致数千个基因的激活和抑制7，11，15，16。研究表明，IDD对于转录共激活子（如p300，WDR5和BAF复合物）以及共抑制子（如NuRD复合物）的招募很重要11，15，17。EWS IDD与FLI1的C端部分的融合赋予了FLI1的ETS DBD新的DNA结合特异性，使得融合癌蛋白（EWS / FLI）结合到基因组的重复GGAA-微卫星区域除了共识ETS基序18，19，20之外。结合共激活子募集功能，EWS/FLI的这种紧急DNA结合活性促进GGAA-微卫星远端到转录起始位点（TSS）（"增强子样"微卫星）的从头增强子形成，并招募RNA聚合酶II以促进在TSS（"启动子样"微卫星）近端的GGAA-微卫星（"启动子样"微卫星）的转录11，15，16，21。
综上所述，这些数据使我们假设EWS域内的离散元素有助于为不同类型的EWS / FLI结合位点招募不同的共同调节因子。然而，在EWS / FLI的EWS部分内辨别这些元素以及它们如何运作，受到该领域高度重复和无序性质的阻碍。在这里，我们利用先前在尤文氏肉瘤细胞中发表的敲低-拯救系统来功能性地绘制EWS IDD中的这些元素。在这个系统中，EWS / FLI使用靶向FLI1基因的3'UTR的shRNA耗尽，并且使用缺乏3'UTR7，17，22的不同EWS / FLI突变cDNA构建体来挽救表达。这些实验集中在具有各种缺失的构建体上，以绘制EWS IDD与重要致癌表型之间的结构 - 功能关系，包括GGAA-微卫星报告基因构建体的激活，集落形成测定以及EWS / FLI激活和抑制基因的靶向验证7，17，22.然而，这些研究未能在EWS / FLI的EWS IDD中发现离散子结构域，这些子结构域对于激活或抑制都非常重要。所有测试的构建体要么能够激活和抑制特定的靶基因，导致有效的菌落形成，要么无法调节任何EWS / FLI靶基因，导致菌落形成7，17，22的丧失。
通过广泛采用下一代测序实现的转录组学分析通常用于比较两种情况下的基因表达特征，通常在筛选或描述性研究的背景下。相反，我们希望利用使用RNA测序（RNA-seq）捕获全基因组表达数据的能力来表征IDD对转录因子功能的贡献。在这种情况下，RNA-seq与敲低-救援系统配对，以探索EWS结构域的结构-功能关系。这种方法适用于其他融合转录因子，包括其他EWS融合或功能知之甚少的野生型转录因子，并且与用于功能图谱研究的其他测定（例如报告测定或靶向qRT-PCR）相比具有多种优势。这些包括在相关染色质环境中测试功能的结构决定因素，在一次测定中测试多种类型的响应元件的能力（即，活化和抑制，GGAA-微卫星和非微卫星等），以及由此产生的更好地检测部分功能的能力。
这种方法的成功实施取决于基于细胞的系统，该系统捕获感兴趣的表型（在这种情况下，A673细胞具有shRNA介导的EWS / FLI耗尽），以及适合基于细胞的系统的表达载体中的一组突变体构建体（在这种情况下，pMSCV-hygro具有各种3x-FLAG标记的EWS / FLI突变体将通过逆转录病毒转导递送）。建议对基于CRISPR的耗竭构建体、基于shRNA的耗竭构建体和cDNA表达构建体进行病毒转导，并进行适当的选择以产生稳定的细胞系，而不是瞬时转染。当转录组学数据可以与转录因子定位相关的其他数据和其他表型读数（如果可用）配对时，结果的下游解释得到加强。
在本文中，我们应用这种方法来表征EWS / FLI14的DAF突变体的活性。DAF突变体在EWS / FLI 14的EWS IDD的重复区域中有17个酪氨酸至丙氨酸突变。这种特殊的EWS突变体以前曾被报道过，当与ATF1 DBD14融合时，它无法激活报告基因表达。然而，初步的qRT-PCR数据表明，该突变体能够激活EWS / FLI靶标 NR0B123的转录。这里描述的转录组学方法能够成功检测DAF突变体的部分功能。通过将这些转录组学数据与有关EWS / FLI结合和识别基序的信息配对，我们进一步表明DAF突变体在GGAA-微卫星重复时保持功能。这些结果将DAF确定为第一个部分功能的EWS / FLI突变体，并突出了非微卫星基因的功能对肿瘤发生很重要（如报道23）。这证明了这种转录组学结构 - 功能映射方法的强大功能，可以深入了解致癌转录因子的功能。

<table>
	<tbody>
		<tr>
			<td>Wet Lab Reagents</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>anti-FLI rabbit pAb</td>
			<td>Abcam</td>
			<td>ab15289</td>
			<td>1:500</td>
		</tr>
		<tr>
			<td>anti-lamin B1 rabbit pAb</td>
			<td>Abcam</td>
			<td>ab16048</td>
			<td>1:2000</td>
		</tr>
		<tr>
			<td>Cell-based system for introduction of mutant constructs</td>
			<td></td>
			<td></td>
			<td>Determined by cell system used</td>
		</tr>
		<tr>
			<td>Cryotubes</td>
			<td></td>
			<td></td>
			<td>For viral aliquots</td>
		</tr>
		<tr>
			<td>DMEM</td>
			<td>Corning Cellgro</td>
			<td>10-013-CV</td>
			<td>For viral production</td>
		</tr>
		<tr>
			<td>Fetal bovine serum</td>
			<td>Gibco</td>
			<td>16000-044</td>
			<td>For viral production</td>
		</tr>
		<tr>
			<td>G418</td>
			<td>ThermoFisher</td>
			<td>10131027</td>
			<td>For viral production</td>
		</tr>
		<tr>
			<td>HEK293-EBNAs</td>
			<td>ATCC</td>
			<td>CRL-10852</td>
			<td>For viral production</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Gibco</td>
			<td>15630106</td>
			<td></td>
		</tr>
		<tr>
			<td>Hygromycin B</td>
			<td>ThermoFisher</td>
			<td>10687010</td>
			<td></td>
		</tr>
		<tr>
			<td>M2 anti-FLAG mouse mAb</td>
			<td>Sigma</td>
			<td>F3165</td>
			<td>1:2000</td>
		</tr>
		<tr>
			<td>Near IR-secondary antibodies</td>
			<td>Li-Cor</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Optimem</td>
			<td>Gibco</td>
			<td>31985062</td>
			<td>For viral production</td>
		</tr>
		<tr>
			<td>Penicillin/Streptomycin/Glutamine</td>
			<td>Gibco</td>
			<td>10378-016</td>
			<td>For viral production</td>
		</tr>
		<tr>
			<td>Polybrene</td>
			<td>Sigma</td>
			<td>TR-1003-G</td>
			<td>For viral transduction</td>
		</tr>
		<tr>
			<td>Puromycin</td>
			<td>Sigma</td>
			<td>P8833</td>
			<td>Stored at 2 mg/mL stock</td>
		</tr>
		<tr>
			<td>RNeasy Plus kit</td>
			<td>Qiagen</td>
			<td>74136</td>
			<td>Has gDNA removal columns</td>
		</tr>
		<tr>
			<td>Selection reagents</td>
			<td></td>
			<td></td>
			<td>As dictated by cell system used</td>
		</tr>
		<tr>
			<td>Sodium Pyruvate</td>
			<td>Gibco</td>
			<td>11360-070</td>
			<td>For viral production</td>
		</tr>
		<tr>
			<td>Tissue culture media</td>
			<td></td>
			<td></td>
			<td>Determined by cell system used</td>
		</tr>
		<tr>
			<td>TransIT-LT1</td>
			<td>Mirus</td>
			<td>MIR 2304</td>
			<td>For viral production</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Software</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Access to HPC environment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>AnnotationDbi</td>
			<td></td>
			<td></td>
			<td>1.38.2</td>
		</tr>
		<tr>
			<td>Cairo</td>
			<td></td>
			<td></td>
			<td>1.5-10</td>
		</tr>
		<tr>
			<td>DESeq2</td>
			<td></td>
			<td></td>
			<td>1.16.1</td>
		</tr>
		<tr>
			<td>genefilter</td>
			<td></td>
			<td></td>
			<td>1.58.1</td>
		</tr>
		<tr>
			<td>ggbiplot</td>
			<td></td>
			<td></td>
			<td>0.55</td>
		</tr>
		<tr>
			<td>ggplot2</td>
			<td></td>
			<td></td>
			<td>3.1.1</td>
		</tr>
		<tr>
			<td>org.Hs.eg.db</td>
			<td></td>
			<td></td>
			<td>3.4.1</td>
		</tr>
		<tr>
			<td>pheatmap</td>
			<td></td>
			<td></td>
			<td>1.0.12</td>
		</tr>
		<tr>
			<td>PuTTY</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>R</td>
			<td></td>
			<td></td>
			<td>3.4.0</td>
		</tr>
		<tr>
			<td>RColorBrewer</td>
			<td></td>
			<td></td>
			<td>1.1-2</td>
		</tr>
		<tr>
			<td>reshape2</td>
			<td></td>
			<td></td>
			<td>1.4.3</td>
		</tr>
		<tr>
			<td>rgl</td>
			<td></td>
			<td></td>
			<td>0.100.19</td>
		</tr>
		<tr>
			<td>R-studio</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>STAR</td>
			<td></td>
			<td></td>
			<td>Version 2.6 or later</td>
		</tr>
		<tr>
			<td>sva</td>
			<td></td>
			<td></td>
			<td>3.24.4</td>
		</tr>
		<tr>
			<td>TrimGalore!</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>WinSCP</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

mapping the structure-function relationships of disordered oncogenic transcription factors using transcriptomic analysis

许多癌症的特征在于染色体易位，导致致癌融合转录因子的表达。通常，这些蛋白质包含与另一种蛋白质的DNA结合结构域（DBD）融合的内在无序结构域（IDD），并协调广泛的转录变化以促进恶性肿瘤。这些融合通常是它们引起的癌症中唯一反复出现的基因组畸变，使它们成为有吸引力的治疗靶点。然而，靶向致癌转录因子需要更好地了解低复杂性IDD在其功能中所起的机制作用。EWSR1 的 N 端结构域是一种 IDD，涉及多种致癌融合转录因子，包括 EWS/FLI、EWS/ATF 和 EWS/WT1。在这里，我们使用RNA测序来研究EWS结构域的结构特征，这些结构域对Ewing肉瘤中EWS / FLI的转录功能很重要。首先进行shRNA介导的尤文氏肉瘤细胞内源性融合的消耗，该细胞与各种EWS突变体构建体的异位表达配对。然后使用RNA测序来分析表达这些构建体的细胞的转录组，以表征与EWS结构域突变相关的功能缺陷。通过将转录组学分析与先前发表的有关EWS / FLI DNA结合基序和基因组定位的信息以及转化能力的功能测定相结合，我们能够确定对肿瘤发生重要的EWS / FLI的结构特征，并定义一组对尤文氏肉瘤至关重要的EWS / FLI靶基因。本文证明了使用RNA测序作为绘制致癌转录因子内在无序结构域的结构 - 功能关系的方法。

初步的qRT-PCR数据表明，一种名为DAF的EWS / FLI突变体在EWS的重复和无序区域具有特异性酪氨酸至丙氨酸突变，保持了激活EWS / FLI靶基因的能力，但未能抑制关键靶基因23。为了更好地理解EWS域中的这些残基与EWS/FLI功能之间的关系，使用了上述描述并在 图1 中概述的协议。A673尤文氏肉瘤细胞被病毒转导，用shRNA靶向 FLI1的3'UTR，导致内源性EWS/FLI的消耗。经过4天的选择，用不同3XFLAG标记的EWS/FLI突变体的病毒转导挽救了EWS/FLI功能，以空载体为对照，无需救援。一种缺乏EWS结构域的非功能突变体（称为Δ22）被用作阴性对照，野生型EWS/ FLI（称为wtEF）被用作阳性对照（图2A）。DAF 被用作测试构造，但如果需要，可以使用多个测试构造。选择细胞另外10天以使构建表达稳定，然后收集RNA（使用gDNA去除步骤），蛋白质和菌落形成测定。收集了四个重复项，并显示有效敲低和挽救的具有代表性的qRT-PCR和蛋白质印迹如图 2B-D所示。应该注意的是，DAF拯救的细胞未能形成 如图2E所示的集落，表明致癌转化受损。
在完成重复验证和表型测定后，RNA被提交给全国儿童医院的基因组医学研究所进行文库制备和下一代测序，并收集了约5000万个150-bp配对端读数。数据以 fastq.gz 文件的形式返回。使用TrimGalore从这些文件中删除低质量的读数，STAR用于将读数与人类基因组hg19对齐并计算每个基因的读数。hg19 用于与下游分析中使用的 EWS/FLI 的其他精选数据集兼容。这些读取计数被合并到所有样本的单个计数矩阵中，其中前6行如图 3所示。
计数最初通过DESeq2运行，没有批量归一化，但是，对样品到样品距离的目视检查显示了潜在的混杂批效应，如图4A中的红色箭头突出显示所示。这可能是由于培养物中细胞的通过和每批处理的差异而引入的生物变异性引起的。批处理效果的归一化是使用 ComBat 执行的，通常建议使用。批量归一化数据的样品到样品距离如图4B所示。在批量归一化之后，DESeq2用于生成相对于基线的三个结构（wtEF，Δ22和DAF）的转录谱。请注意，虽然"亲本"A673细胞（模拟敲低和模拟救援，此处称为"iLuc"）包括在差异分析中，但本实验的参考是EWS / FLI耗尽的细胞，称为iEF细胞。通过将iLuc样品与iEF进行比较，可以生成内源性蛋白质的转录谱，这可能对了解救援系统的工作原理感兴趣，但这不是此特定分析的目标。为突变体生成的转录谱包括iEF的正（wtEF）和阴性（Δ22）对照，因此这些应作为其他突变体的基准。这很重要，因为本例中的阳性对照没有完全概括内源性EWS / FLI的功能，如其他地方7，23所讨论的那样。
图5中的主成分分析（PCA）表明，DAF的转录谱介于wtEF和Δ22之间，证实了部分功能。此外，样本中1000个最可变基因的分层聚类表明，DAF未能抑制EWS / FLI靶基因，仅部分保留了基因激活活性，如图6A和图S5所示。ToppGene分析表明，DAF激活的基因类别在功能上与DAF无功能的EWS / FLI激活靶标不同（图6B）。有趣的是，wtEF拯救的激活基因的功能，但不是DAF，似乎与转录控制和染色质调节有关。根据集落形成测定的结果，应进一步分析来自该核心基因特征的基因在EWS / FLI介导的肿瘤发生中的作用。EWS / FLI介导的基因抑制的重要性之前已经描述过17。
众所周知，EWS/FLI对GGAA-微卫星重复元素19、22具有独特的结合亲和力，并且这些元素的结合驱动下游基因调控11、15、18、20、22。这些微卫星的特征在于与激活或抑制有关，并且要么靠近（<5 kb）TSS，要么远端到（>5 kb）TSS25。此外，还有一些EWS / FLI调控的基因具有高亲和力（HA）ETS基序，与TSS23近端。为了进一步分析DAF功能的特征以及DAF能够挽救哪些类型的EWS/FLI激活基因，分析了与这些不同类别相关的基因的差异表达。有趣的是，DAF最能够拯救GGAA-微卫星激活基因，但无法拯救HA位点附近的激活基因，如图7所示。从分层聚类中可以看出，DAF 无法拯救跨主题类的 EWS/FLI 介导的压制。这些数据表明，DAF保留了EWS的足够结构特征，可以与GGAA微卫星结合并从TSS的近端和远端激活。这可能是由于完整的SYGQ域被认为对GGAA重复的EWS / FLI活动很重要。这些数据还表明，DAF中突变的特定酪氨酸在HA位点的EWS / FLI介导的基因调控以及基因抑制中起着重要作用，但知之甚少，这突出了进一步研究的一个重要领域。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61564/61564fig01.jpg"> 图 1：工作流。描述通过转录组学执行结构-功能映射的分步过程。细胞首先准备表达结构 - 功能映射所需的结构套件。表达后，收获细胞的RNA和蛋白质，并测定相关表型。验证了结构的表达，并重复该过程3-4次以收集独立的生物学重复。然后将RNA提交用于下一代测序（NGS）。收到数据后，对数据进行质量修整、对齐，并计算每个成绩单的计数。使用DESeq2控制批处理效应，并确定转录组学特征和差异表达。可以合并分层聚类和下游分析，集成其他组学数据集和不同的路径或功能分析。 <a href="https://www.jove.com/files/ftp_upload/61564/61564fig01large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61564/61564fig02.jpg"> 图2：构建体表达和相关测定的验证。（A） 示意图，描述了本例中测试的结构。（B） 免疫印迹对内源性 EWS/FLI 的敲低和 3X-FLAG 标记构建体表达的验证。（C，D）通过qRT-PCR验证EWS/FLI（C）活化靶基因NR0B1和（D）抑制靶基因TGFBR2的构建活性。数据以平均 +/- 标准差表示。P值是用Tukey诚实显著性检验计算的。* p < 0.05， ** p < 0.01， *** p < 0.005 （E） 用于评估构建体转化活性的软琼脂测定的菌落计数。P值是用Tukey诚实显著性检验计算的。* p < 0.05， ** p < 0.01， *** p < 0.005.此图改编自 Theisen 等人23<a href="https://www.jove.com/files/ftp_upload/61564/61564fig02large.jpg" target="_blank">请单击此处查看此图的放大版本。</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/61564/61564fig03.jpg"> 图 3：用于分析的最终整理计数数据。计数文件前6行的屏幕截图，其中包含要进行批量归一化和分析的所有样本的基因计数。 <a href="https://www.jove.com/files/ftp_upload/61564/61564fig03large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61564/61564fig04v3.jpg"> 图 4：样本到样本距离热图。（A） 样本到样本距离图，显示原始计数数据的样本聚类。按批次和按样品聚类的样品用红色箭头表示。（B） 使用 ComBat 进行批量归一化后的样品到样品距离图。此处，来自所有仿行的样本独立于批处理聚集在一起。 <a href="https://www.jove.com/files/ftp_upload/61564/61564fig04large.jpg" target="_blank">请点击此处查看此图的放大版本。</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/61564/61564fig05.jpg"> 图 5：差异表达分析的结果。（A） 为所有样品生成的转录组学特征的主体成分分析（PCA）图显示了强烈的样品内聚类，并表明DAF在阳性（wtEF）和阴性（Δ22）对照之间是中间的。（B） 火山图显示与每个构造中基因的 log2FoldChange 对图的 -log（p-值）。调整后 p 值< 0.05 且|log2（FoldChange）|> 1 被视为显著的，并以红色显示。面板5B改编自Theisen等人，请<a href="https://www.jove.com/files/ftp_upload/61564/61564fig05large.jpg" target="_blank">点击此处查看此图的放大版本。</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/61564/61564fig06.jpg"> 图6：用于识别基因类别的分层聚类。（A） 所有构建体中前 1000 个最可变基因的分层聚类和基线 iEF 显示 DAF 部分挽救了 EWS/FLI 介导的基因激活。（B） 来自ToppGene的基因本体（分子功能）结果显示了被DAF拯救或未获救的EWS/ FLI激活基因的功能富集。图6B改编自Theisen等人，请<a href="https://www.jove.com/files/ftp_upload/61564/61564fig06large.jpg" target="_blank">点击此处查看此图的放大版本。</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/61564/61564fig07.jpg"> 图7：对不同结构的不同转录因子响应元素的详细分析：（A）示意图，通过将其他可用数据集与此处的转录组学配置文件相结合，描述了用于生成面板（B）和（C）的数据处理。（B，C）汇编显示了对不同类别的直接EWS/FLI-（B）激活和（C）抑制目标的救援。纳入的基因仅是内源性EWS/FLI可检测差异表达的基因。在每个饼图中，灰色描绘了未被构建体拯救的基因部分。红色表示被差异激活的基因部分，蓝色表示被差异抑制的基因部分。此图改编自 Theisen 等人23<a href="https://www.jove.com/files/ftp_upload/61564/61564fig07large.jpg" target="_blank">请单击此处查看此图的放大版本。</a>
图 S1：将 fastq.gz 文件加载到 HPC 环境中，进行修整和对齐。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig01.jpg" target="_blank">请点击此处下载此图。</a>
图 S2：整理样本中的读取计数并使用 ComBat 运行批处理规范化。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig02.jpg" target="_blank">请点击此处下载此图。</a>
图 S3：运行 DESeq2 并提取差异表达分析的结果。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig03.jpg" target="_blank">请点击此处下载此图。</a>
图 S4：分析输出。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig04.jpg" target="_blank">请点击此处下载此图。</a>
图S5：用于识别基因类别的分层聚类： 所有构建体中前1000个最可变基因的分层聚类，基线iEF分类为 k 个聚类。在本例中 k=7，但此参数由用户设置，如图 S4D所示。 <a href="https://cloudflare.jove.com/files/ftp_upload/61564/61564supfig05.jpg" target="_blank">请点击此处下载此图。</a>
表S1：具有簇注释的基因列表（Ensembl基因ID）。<a href="https://cloudflare.jove.com/files/ftp_upload/61564/Table_S1.xlsx" target="_blank">请点击此处下载此表格。</a>

Watch this Scientific Journal Video about Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis at JoVE.com

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

内在无序结构域对致癌融合转录因子功能很重要。为了治疗靶向这些蛋白质，需要更详细地了解这些结构域所采用的调节机制。在这里，我们使用转录组学来绘制尤文氏肉瘤中内在无序的EWS结构域的重要结构特征。

使用转录组学分析绘制无序致癌转录因子的结构-功能关系

Many cancers are characterized by chromosomal translocations which result in the expression of oncogenic fusion transcription factors. Typically, these ...

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Research

JoVE Journal

Cancer Research

2.6K 次观看.  Abigail Wexner Research Institute at Nationwide Children's Hospital. 内在无序结构域对致癌融合转录因子功能很重要。为了治疗靶向这些蛋白质，需要更详细地了解这些结构域所采用的调节机制。在这里，我们使用转录组学来绘制尤文氏肉瘤中内在无序的EWS结构域的重要结构特征。

视频: Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Identification and Characterization of Metastatic Factors by Gene Transfer into the Novel RIP-Tag; RIP-tva Murine Model

Metastatic cancer accounts for 90% of deaths in patients with solid tumors. There is an urgent need to better understand the drivers of cancer metastasis and to identify novel therapeutic targets. To investigate molecular events that drive the progression from primary cancer to metastasis, we have developed a bitransgenic mouse model, RIP-Tag; RIP-tva. In this mouse model, the rat insulin promoter (RIP) drives the expression of the SV40 T antigen (Tag) and the receptor for subgroup A avian leukosis virus (tva) in pancreatic &#946; cells. The mice develop pancreatic neuroendocrine tumors with 100% penetrance through well-defined stages that are similar to human tumorigenesis, with stages including hyperplasia, angiogenesis, adenoma, and invasive carcinoma. Because RIP-Tag; RIP-tva mice do not develop metastatic disease, genetic alterations that promote metastasis can be identified easily. Somatic gene transfer into tva-expressing, proliferating pancreatic &#946; premalignant lesions is achieved through intracardiac injection of avian retroviruses harboring the desired genetic alteration. A titer of &#62;1 x 108 infectious units per ml is considered appropriate for in vivo infection. In addition, avian retroviruses can infect cell lines derived from tumors in RIP-Tag; RIP-tva mice with high efficiency. The cell lines can also be used to characterize the metastatic factors. Here we demonstrate how to utilize this mouse model and cell lines to assess the functions of candidate genes in tumor metastasis.

Identification and Characterization of Metastatic Factors by Gene Transfer into the Novel RIP-Tag; RIP-tva Murine Model

We present a protocol to demonstrate a novel somatic gene transfer system utilizing RIP-Tag; RIP-tva mouse model to study the function of genes in metastasis. The avian retroviruses are delivered intracardiacally to ensure gene transfer into pre-malignant, noninvasive lesions of pancreatic &#946; cells in adult mice.

转移因子的鉴定和表征转移到新的RIP 标签;tva小鼠模型

Metastatic cancer accounts for 90% of deaths in patients with solid tumors. There is an urgent need to better understand the drivers of cancer metastasis ...

科研

癌症研究

Using CRISPR/Cas9 Gene Editing to Investigate the Oncogenic Activity of Mutant Calreticulin in Cytokine Dependent Hematopoietic Cells

Clustered regularly interspaced short palindromic repeats (CRISPR) is an adaptive immunity system in prokaryotes that has been repurposed by scientists to generate RNA-guided nucleases, such as CRISPR-associated (Cas) 9 for site-specific eukaryotic genome editing. Genome engineering by Cas9 is used to efficiently, easily and robustly modify endogenous genes in many biomedically-relevant mammalian cell lines and organisms. Here we show an example of how to utilize the CRISPR/Cas9 methodology to understand the biological function of specific genetic mutations. We model calreticulin (CALR) mutations in murine interleukin-3 (mIL-3) dependent pro-B (Ba/F3) cells by delivery of single guide RNAs (sgRNAs) targeting the endogenous Calr locus in the specific region where insertion and/or deletion (indel) CALR mutations occur in patients with myeloproliferative neoplasms (MPN), a type of blood cancer. The sgRNAs create double strand breaks (DSBs) in the targeted region that are repaired by non-homologous end joining (NHEJ) to give indels of various sizes. We then employ the standard Ba/F3 cellular transformation assay to understand the effect of physiological level expression of Calr mutations on hematopoietic cellular transformation. This approach can be applied to other genes to study their biological function in various mammalian cell lines.

Targeted gene editing using CRISPR/Cas9 has greatly facilitated the understanding of the biological functions of genes. Here, we utilize the CRISPR/Cas9 methodology to model calreticulin mutations in cytokine-dependent hematopoietic cells in order to study their oncogenic activity.

利用 CRISPR/Cas9 基因编辑研究细胞因子依赖性造血细胞中突变钙的致癌活性

Clustered regularly interspaced short palindromic repeats (CRISPR) is an adaptive immunity system in prokaryotes that has been repurposed by scientists to ...

Simple and Rapid Method to Obtain High-quality Tumor DNA from Clinical-pathological Specimens Using Touch Imprint Cytology

It is critical to determine the mutational status in cancer before administration and treatment of specific molecular targeted drugs for cancer patients. In the clinical setting, formalin-fixed paraffin-embedded (FFPE) tissues are widely used for genetic testing. However, FFPE DNA is generally damaged and fragmented during the fixation process with formalin. Therefore, FFPE DNA is sometimes not adequate for genetic testing because of low quality and quantity of DNA. Here we present a method of touch imprint cytology (TIC) to obtain genomic DNA from cancer cells, which can be observed under a microscope. Cell morphology and cancer cell numbers can be evaluated using TIC specimens. Furthermore, the extraction of genomic DNA from TIC samples can be completed within two days. The total amount and quality of TIC DNA obtained using this method was higher than that of FFPE DNA. This rapid and simple method allows researchers to obtain high-quality DNA for genetic testing (e.g., next generation sequencing analysis, digital PCR, and quantitative real time PCR) and to shorten the turnaround time for reporting results.

Obtaining high-quality genomic DNA from tumor tissues is an essential first step for analyzing genetic alterations using next generation sequencing. In this article, we present a simple and rapid method to enrich tumor cells and obtain intact DNA from touch imprint cytology specimens.

用触印细胞学方法快速获得临床病理标本中高质量肿瘤 DNA

It is critical to determine the mutational status in cancer before administration and treatment of specific molecular targeted drugs for cancer patients. ...

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of associated loci. In addition, the presence of specific modifications has been used to determine the position and identity non-coding functional elements such as enhancers. In recent years, chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) has become a powerful tool in determining the genome-wide profiles of individual histone modifications. However, it has become increasingly clear that the combinatorial patterns of chromatin modifications, referred to as Chromatin States, determine the identity and nature of the associated genomic locus. Therefore, workflows consisting of robust high-throughput (HT) methodologies for profiling a number of histone modification marks, as well as computational analyses pipelines capable of handling myriads of ChIP-Seq profiling datasets, are needed for comprehensive determination of epigenomic states in large number of samples. The HT-ChIP-Seq workflow presented here consists of two modules: 1) an experimental protocol for profiling several histone modifications from small amounts of tumor samples and cell lines in a 96-well format; and 2) a computational data analysis pipeline that combines existing tools to compute both individual mark occupancy and combinatorial chromatin state patterns. Together, these two modules facilitate easy processing of hundreds of ChIP-Seq samples in a fast and efficient manner. The workflow presented here is used to derive chromatin state patterns from 6 histone mark profiles in melanoma tumors and cell lines. Overall, we present a comprehensive ChIP-seq workflow that can be applied to dozens of human tumor samples and cancer cell lines to determine epigenomic aberrations in various malignancies.

Here, we describe an optimized high-throughput ChIP-sequencing protocol and computational analyses pipeline for the determination of genome-wide chromatin state patterns from frozen tumor tissues and cell lines.

肿瘤组织中高通量芯片测序的染色质状态全基因组图谱集成平台

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of ...

An Oncogenic Hepatocyte-Induced Orthotopic Mouse Model of Hepatocellular Cancer Arising in the Setting of Hepatic Inflammation and Fibrosis

The absence of a clinically relevant animal model addressing the typical immune characteristics of hepatocellular cancer (HCC) has significantly impeded elucidation of the underlying mechanisms and development of innovative immunotherapeutic strategies. To develop an ideal animal model recapitulating human HCC, immunocompetent male C57BL/6J mice first receive a carbon tetrachloride (CCl4) injection to induce liver fibrosis, then receive histologically-normal oncogenic hepatocytes from young male SV40 T antigen (TAg)-transgenic mice (MTD2) by intra-splenic (ISPL) inoculation. Androgen generated in recipient male mice at puberty initiates TAg expression under control of a liver-specific promoter. As a result, the transferred hepatocytes become cancer cells and form tumor masses in the setting of liver fibrosis/cirrhosis. This novel model mimics human HCC initiation and progression in the context of liver fibrosis/cirrhosis and reflects the most typical features of human HCC including immune dysfunction.

Here, we describe the development of a clinically relevant murine model of liver cancer recapitulating the typical immune features of hepatocellular cancer (HCC).

在肝炎症和纤维化环境中产生的肝细胞癌的致癌肝细胞诱导正交小鼠模型

The absence of a clinically relevant animal model addressing the typical immune characteristics of hepatocellular cancer (HCC) has significantly impeded ...

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 ...

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Differential gene expression analysis is an important technique for understanding disease states. The machine learning algorithm CorEx has shown utility in analyzing differential expression of groups of genes in tumor RNA-seq in a way that may be helpful for advancing precision oncology. However, CorEx produces many factors that can be challenging to analyze and connect to existing understanding. To facilitate such connections, we have built a website, CorExplorer, that allows users to interactively explore the data and answer common questions related to its analysis. We trained CorEx on RNA-seq gene expression data for four tumor types: ovarian, lung, melanoma, and colorectal. We then incorporated corresponding survival, protein-protein interactions, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments, and heatmaps into the website for association with the factor graph visualization. Here we employ example protocols to illustrate use of the database for comprehending the significance of the learned tumor factors in the context of this external data.

We introduce the CorExplorer web portal, an resource for exploration of tumor RNA sequencing factors found by the machine learning algorithm CorEx (Correlation Explanation), and show how factors can be analyzed relative to survival, database annotations, protein-protein interactions, and one another to gain insight into tumor biology and therapeutic interventions.

分析肿瘤基因表达因子与CorExplorer门户网站

Differential gene expression analysis is an important technique for understanding disease states. The machine learning algorithm CorEx has shown utility ...

Identification of Transcription Factor Regulators using Medium-Throughput Screening of Arrayed Libraries and a Dual-Luciferase-Based Reporter

Transcription factors can alter the expression of numerous target genes that influence a variety of downstream processes making them good targets for anti-cancer therapies. However, directly targeting transcription factors is often difficult and can cause adverse side effects if the transcription factor is necessary in one or more adult tissues. Identifying upstream regulators that aberrantly activate transcription factors in cancer cells offers a more feasible alternative, particularly if these proteins are easy to drug. Here, we describe a protocol that can be used to combine arrayed medium-scale lentiviral libraries and a dual-luciferase-based transcriptional reporter assay to identify novel regulators of transcription factors in cancer cells. Our approach offers a quick, easy, and inexpensive way to test hundreds of genes in a single experiment. To demonstrate the use of this approach, we performed a screen of an arrayed lentiviral RNAi library containing several regulators of Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), two transcriptional co-activators that are the downstream effectors of the Hippo pathway. However, this approach could be modified to screen for regulators of virtually any transcription factor or co-factor and could also be used to screen CRISPR/CAS9, cDNA, or ORF libraries.

To identify novel regulators of transcription factors, we developed an approach to screen arrayed lentiviral or retroviral RNAi libraries using a dual-luciferase-based transcriptional reporter assay. This approach offers a quick and relatively inexpensive way to screen hundreds of candidates in a single experiment.

使用阵列库的中等通量筛选和基于双 Luciferase 的分录报告器识别转录因子稳压器

Transcription factors can alter the expression of numerous target genes that influence a variety of downstream processes making them good targets for ...

Evaluating Cell Death Using Cell-Free Supernatant of Probiotics in Three-Dimensional Spheroid Cultures of Colorectal Cancer Cells

This manuscript describes a protocol to evaluate cancer cell deaths in three dimensional (3D) spheroids of multicellular types of cancer cells using supernatants from Lactobacillus fermentum cell culture, considered as probiotics cultures. The use of 3D cultures to test Lactobacillus cell-free supernatant (LCFS) are a better option than testing in 2D monolayers, especially as L. fermentum can produce anti-cancer effects within the gut. L. fermentum supernatant was identified to possess increased anti-proliferative effects against several colorectal cancer (CRC) cells in 3D culture conditions. Interestingly, these effects were strongly related to the culture model, demonstrating the notable ability of L. fermentum to induce cancer cell death. Stable spheroids were generated from diverse CRCs (colorectal cancer cells) using the protocol presented below. This protocol of generating 3D spheroid is time saving and cost effective. This system was developed to easily investigate the anti-cancer effects of LCFS in multiple types of CRC spheroids. As expected, CRC spheroids treated with LCFS strongly induced cell death during the experiment and expressed specific apoptosis molecular markers as analyzed by qRT-PCR, western blotting, and FACS analysis. Therefore, this method is valuable for exploring cell viability and evaluating the efficacy of anti-cancer drugs.

Here methods are presented to understand anti-cancer effects of Lactobacillus cell-free supernatant (LCFS). Colorectal cancer cell lines show cell deaths when treated with LCFS in 3D cultures. The process of generating spheroids can be optimized depending on the scaffold and the analysis methods presented are useful for evaluating the involved signaling pathways.

在结肠直肠癌细胞的三维球体培养物中使用无细胞益生菌超常剂评估细胞死亡

This manuscript describes a protocol to evaluate cancer cell deaths in three dimensional (3D) spheroids of multicellular types of cancer cells using ...

Isolating Human Peripheral Blood Mononuclear Cells and CD4+ T cells from S&#233;zary Syndrome Patients for Transcriptomic Profiling

Cutaneous T-cell lymphomas (CTCL) are derived from the transformation and uncontrolled proliferation of mature skin-homing T cells, and mycosis fungoides (MF) and S&#233;zary syndrome (SS) represent the most common subtypes. Despite a number of studies on characterizing gene expression, genetic alterations, and epigenetic abnormalities of CTCL, the molecular pathogenesis of MF/SS remains unclear. MF refers to the more common CTCL with a skin-predominance, and is usually limited to skin, whereas&#160;SS is an aggressive leukemic variant of CTCL with widespread skin involvement and is characterized by neoplastic distribution mainly involving blood, skin, and lymph node. Focusing on clinical practice, the identification of gene expression biomarkers has&#160;enormous potential to improve diagnosis and treatment of MF/SS. Indeed, recent transcriptomic studies have identified potential diagnostic biomarkers from differences in gene expression between normal and malignant T cells, which may improve our understanding of SS biology, and reveal potential therapeutic targets. This manuscript describes a detailed reproducible protocol for the isolation of peripheral blood mononuclear cells from fresh whole blood from patients diagnosed with SS, selection of CD4+ memory T cells (CD4+CD45RO+ T cells), chemical stimulation, and preparation of RNA suitable for transcriptomic profiling to discover novel prognostic molecular markers to gain additional insight in disease etiology. The stimulation using chemical agonist to activate nuclear regulation provides more specific assessment for pathways important in the dynamic transcription regulation and gene expression and eliminates confounding defects that may arise from upstream signaling defects arising from TCR antigen loss at the cell membrane. The data obtained from comparison of transcriptome of unstimulated to stimulated SS T cells unmasks functional regulatory gene expression defects not evident from analysis of quiescent unstimulated cells. Furthermore, the method outlined from this approach can be adapted for studying T cell gene expression defects in other T cell immune diseases.

We present a simple protocol for the isolation of peripheral blood mononuclear cells from whole blood obtained from patients diagnosed with S&#233;zary Syndrome, followed by selection of CD4+ T cells, their stimulation with phorbol12-myristate13-acetate and A23187 ionophore, and preparation of RNA for transcriptomic profiling.

从Sézary综合征患者中分离人外周血单核细胞和CD4 + T细胞以进行转录组学分析

Cutaneous T-cell lymphomas (CTCL) are derived from the transformation and uncontrolled proliferation of mature skin-homing T cells, and mycosis fungoides ...