这项工作部分是由法国协会 Laurette Fugain、LigueContre 乐癌症 (北中心)、法国基金会 (白血病委员会)、SIRIC Oncolille 和法国国家癌症研究所支持的。

我们遵循欧洲为科学目的使用动物的标准。这项研究是由地方伦理委员会 (#3097 2015120414583482v3) 批准的。
1. 样品准备
<ol><li>以1.8 毫克每毫升骨髓的浓度为单位, 在含有抗凝血乙二甲酸 (EDTA) 的管中收集骨髓 (2 毫升). </li>
	<li>进行 Ficoll 分离, 密度梯度分离, 以隔离单个核细胞从红细胞和粒粒, 如下所为。稀释骨髓在3容量磷酸盐缓冲盐水 (PBS: 氯化钠137毫米, 氯化钾2.7 毫米, Na2HPO4 10mM,.2PO4 1.8 毫米)。仔细覆盖1体积的 Ficoll 与1体积稀释骨髓。旋转30分钟, 在 300 x g 没有刹车。将白色的 mononucleated 细胞层转移到新的无菌管中。</li>
	<li>清洗细胞两次在10毫升 PBS) 和离心机在 300 x g 5 分钟, 以消除污染的血清成分。</li>
</ol>2. 红血球的裂解 (红细胞)
<ol><li>将2毫升的裂解缓冲液 (氯化铵 0.8%) 添加到细胞颗粒中, 在室温下轻轻的涡旋, 在室温下孵育5分钟, 在 300 x g 处为5分钟。 注: 如有必要, 请重复此步骤。</li>
	<li>在 PBS 中洗涤细胞如前所述 (1.3)。</li>
</ol>3. 患者派生的异位移植。
<ol><li>用磁阴性选择 (CD3 T 和 CD20 B 淋巴细胞) 在 Ficoll 分离后和淋巴细胞耗尽后获得骨髓中的爆炸细胞。按照制造商的说明进行操作。</li>
	<li>将 5 x 106的 AML 爆炸细胞注入无条件核爆小鼠的尾部静脉。使用抑制装置, 以促进尾静脉注射。保持小鼠在常规条件下, 特别是在无病原条件下, 在任何时候, 使用个别通风笼和操纵下层流罩。每两个星期, 用60µL 的血液通过颌下腺收集方法使用红细胞压积毛细管。将毛细管放入5毫升圆底管。使用小的无菌纱布垫, 用温和的压力止血。用干净的注射器 Expulse 血液。</li>
	<li>添加1ml 的裂解缓冲液和孵育5min。然后离心机在 300 x g 5min. 用 PBS 和 centrifugre 清洗 300 x g 5 分钟。除去上清, 添加100µL PBS 与10% 牛血清白蛋白 (BSA) 染色3µL 抗人 CD45-FITC 和1µL 抗鼠 CD45-APC 和孵育在 4°c 30 分钟。</li>
	<li>在 PBS (2 毫升) 中用 10% BSA 和离心机在 300 x g 处清洗细胞颗粒5分钟。</li>
	<li>整除 1 x 106细胞每100µL 的 PBS 成流式细胞术管。</li>
	<li>用流式细胞术 (图 2A 和 B) 对 CD45 表达式 (人的vs小鼠) 进行嵌合体分析, 每两周进行一次植入调查。</li>
	<li>在牺牲 (外围爆炸计数大于70% 或严重的临床症状), 收集从粉碎脾和骨髓的单个核爆细胞, 冲洗胫骨和股骨与 PBS 如前所述的13。弄死小鼠颈椎脱位遵循国际准则。</li>
	<li>如果细胞颗粒含有红细胞, 则用裂解缓冲剂对红细胞进行裂解 (步骤 2.1)。</li>
	<li>在 PBS (2 毫升) 中清洗细胞颗粒两次, 10% BSA 和离心机在 300 x g 处5分钟。</li>
	<li>收集细胞和整除 1 x 106细胞每100µL 的 PBS 成流式细胞术管。</li>
</ol>4. 染色
<ol><li>添加共轭抗体 (见步骤 4.2) 和漩涡。室温下在黑暗中孵化出15分钟的细胞。</li>
	<li>使用以下面板进行人体主要或 PDX 样品, 包括10µL anti-CD36-FITC、5µL anti-CD19-ECD、5µL 反 CD33 PC5.5、µL anti-CD90-APC、5µL anti-CD34-AA700、5µL anti-CD45RA-APC-H7、5µL anti-CD38-Pacific 蓝、5µLanti-CD123-PC7 和2.5 µL 的 anti-CD45-KO。</li>
	<li>以 300 x g 为5分钟, 通过离心法洗涤2毫升 PBS 中的细胞, 去除未绑定抗体。</li>
	<li>在 PBS 的450µL 中重新悬浮细胞以进行最终的流细胞分析。</li>
</ol>5. 流式细胞术分析的浇口策略
<ol><li>在装有红色、蓝色和紫色激光器的流式细胞仪上进行数据采集 (至少50万个细胞)。验证每一天的细胞仪设置 1) 光学对准, 2) 射流系统, 3) 光学灵敏度, 4) 标准化使用 fluorospheres</li>
	<li>按照顺序的门控策略定义 CD38 表达式 (图 1)。<ol>
<li>使用正常骨髓标本中的细胞来定义 hematogones 或血浆细胞, 以此作为 CD38 表达的积极控制。 注意: 这个门是特别重要的, 以评估作为后续的假定的人口数量取决于它的定义。</li>
		<li>通过 CD45dim/SSC (侧散射) 低种群标准 (图 1A) 定义生理前体细胞 (正常的爆炸细胞)。在这个爆炸填充中, 定义显示 CD38++CD19+ 表型 (图 1B) 的 hematogones, 最后使用 CD36 和 CD33 表达式定义成髓细胞、monoblasts 和孵育(图 1C)。确定 hematogones 上的 CD34 表达式, 如中所示 (图 1E)。评估被定义为 P6-P10 的爆炸细胞中前体的几个亚群 (图 1D)。根据预设 CD38 门将爆炸细胞的 CD34 隔层分成 P6、P7、P8 祖亚群。确保 P8 车厢内含有与 hematogones 相同的 CD38 强度的爆炸, P6 包括 CD38-based 荧光减一 (CD38) 控制的细胞, FMO 细胞介于两个极端之间, P7表达式 (图 1D)。</li>
	</ol>
</li>
	<li>从 CD34+38 (P6) 门控单元格中, 使用 CD90 和 CD45RA 表达式 (图 1F) 将 HSC 与假定的。 注: HSC 表型为 CD34+CD38-CD90+CD45RA-多能祖细胞 (MPP) 被定义为 CD34+CD38-CD90-CD45RA。假定的 CD34+CD38-CD90dimCD45RA+ 表型是不成熟的, 下游人群较不发育的是淋巴引物祖 (LMPP) 定义为 CD34+CD38-CD90-CD45RA+。</li>
</ol>6. rt-pcr 监测
<ol><li>通过 RT PCR 监测 MRD 水平, 如前所述14。</li>
</ol>

<ol>
	<li>Shlush, L. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tracing+the+origins+of+relapse+in+acute+myeloid+leukaemia+to+stem+cells.">Tracing the origins of relapse in acute myeloid leukaemia to stem cells.</a> Nature. , (2017).</li><li>Terwijn, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Leukemic+stem+cell+frequency:+a+strong+biomarker+for+clinical+outcome+in+acute+myeloid+leukemia.">Leukemic stem cell frequency: a strong biomarker for clinical outcome in acute myeloid leukemia.</a> PLoS One. 9 (9), e107587 (2014).</li><li>Jordan, C. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+interleukin-3+receptor+alpha+chain+is+a+unique+marker+for+human+acute+myelogenous+leukemia+stem+cells.">The interleukin-3 receptor alpha chain is a unique marker for human acute myelogenous leukemia stem cells.</a> Leukemia. 14 (10), 1777-1784 (2000).</li><li>van Rhenen, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+novel+AML+stem+cell+associated+antigen+CLL-1+aids+in+discrimination+between+normal+and+leukemic+stem+cells.">The novel AML stem cell associated antigen CLL-1 aids in discrimination between normal and leukemic stem cells.</a> Blood. 110 (7), 2659-2666 (2007).</li><li>Bonardi, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+proteomics+and+transcriptomics+approach+to+identify+leukemic+stem+cell+(LSC)+markers.">A proteomics and transcriptomics approach to identify leukemic stem cell (LSC) markers.</a> Mol Cell Proteomics. 12 (3), 626-637 (2013).</li><li>Kikushige, Y., Miyamoto, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+TIM-3+as+a+Leukemic+Stem+Cell+Surface+Molecule+in+Primary+Acute+Myeloid+Leukemia.">Identification of TIM-3 as a Leukemic Stem Cell Surface Molecule in Primary Acute Myeloid Leukemia.</a> Oncology. 89, 28-32 (2015).</li><li>Bonnet, D., Dick, J. 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作者没有什么可透露的。

通过流式细胞术对膜或细胞质标记进行准确和可重复的评估, 要求仪器设置每天都要经过验证, 以进行光学对准、射流系统的正常运行、光学灵敏度和标准化使用校准珠。
应用多参数流式细胞仪分析 CD90 和 CD45RA 检测 AML 中的爆炸细胞群是一种比较简单可靠的方法。这项分析的一个关键步骤是准确评估 CD38 在爆炸细胞中的表达, 以便正确地进行 CD34+CD38 的门控。CD38 强度的定义是使用正常的骨髓细胞专门对 hematogones 和/或血浆细胞 (CD38+)。其他标记的强度是使用同种控件确定的。
添加 CD45RA 和 CD90 是用来区分 HSC 与假定的。后者和不 HSC 可能是疾病复发的原因, 因此该协议是有兴趣的最小残留疾病监测使用流式细胞术板。在治疗过程中监测 aml 对改善风险分层和指导反洗钱治疗至关重要。不幸的是, 所有患者都不能使用合适的分子标记。因此, 通过流式细胞术进行的 MRD 监测对所有的 AML 病例都可能是可行的。尽管这种方法可能并不详尽无遗, 因为它 focalizes 了大多数的反洗钱案件, 这些病例有一个 CD34+CD38 祖和一个假定的群体。值得注意的是, 假定的内隔舱可能包括正常的祖细胞, 即 LMPP)。 此外, 我们不能排除有很少的情况下功能性的, 不遵循这种反常的表达模式。值得注意的是, 即使在被认为是 CD34 阴性的 NPM1-mutated AML 中, 我们也能检测出假定的。因此, 尽管反洗钱室的异质性和复杂性, 我们的方法可以作为一个生物标志性的化疗反应在反洗钱的后续行动。

急性髓系白血病 (AML) 是导致白血病相关死亡的最常见原因。首先, AML 是一种造血干细胞 (HSC) 的克隆病, 其特点是: 停止分化, 随后累积爆炸细胞, 减少功能性造血元件的生产。近年来, 通过使用下一代测序策略和显示肿瘤细胞内克隆进化的存在性, 建立了爆炸细胞种群的无性系异质性, 并表明其存在于1。
异质性延伸到白血病干细胞的存在。据推测, 这种动态细胞室的演变, 以克服各种选择压力强加在白血病的进展和治疗。因此, 对目前的化疗方案和介导的疾病复发有抵抗力, 其临床意义2。各种标记都被描述为特征 CD1233、CLL-14、CD975或 TIM-36等。CD34+CD38 的爆破细胞的隔室被认为是丰富的, 为7 , 但也包括正常的 HSC。CD90 和 CD45RA 表达式应用于 CD34+CD38 (P6) 隔间 (图 1) 允许隔离正常和恶性造血前体的几个阶段8。具体地说, 正常的 CD34+CD38-CD90+CD45RA-HSCs, 多能祖 (MPP) 像 CD34+CD38-CD90dimCD45RA 细胞和 CD34+CD38-CD90-CD45RA+ 淋巴引物多能祖 (LMPP) 细胞可以确定在大多数 AML 病例中,8 ,9。CD38 的平均荧光强度 (多边基金会) 在 CD34+ 细胞室中尤为重要。因为 CD38 强度定义了三个新的细胞间隔: CD38 阴性 (P6), CD38 暗淡 (P7) 和 CD38 明亮 (P8) (图 1)。CD38 可以通过 hematogones 和/或血浆细胞作为内部阳性控制来确定, 因为这些细胞强烈表达 CD38。
immunodeficient NOD/SCID/IL2Rγcnull (核供应集团) 鼠标模型广泛用于植入正常和恶性人类造血细胞10,11。采用系列异种移植方法对功能进行实验验证。通过大规模测序方法对这些研究进行了广泛的分析。然而, 与其主要的 aml (图 2) 相比, 反洗钱爆炸种群的嫁接和 HSC 免疫表型对核供应的小鼠的认识较少。
该方法的数量在本质上是低的, 因此, 识别和量化的研究是有挑战性的, 这里描述的方式可以作为一个流细胞分析诊断和临床随访评估化疗反应 (作为残留的可能引起 AML 复发)。存在的可显示阳性的最小残留疾病 (MRD)。迄今为止, 在反洗钱中的 MRD 监测主要依靠分子方法 (即, rt-pcr,)10,12。然而, 在本协议中, 我们通过多参数流式细胞术 2, 8 9, 在人类反洗钱的主要爆炸细胞中检测出几种 HSC/CD34 标记 (CD38、CD45RA、CD90) 的同时蛋白表达.这种抗体组合可应用于任何标准流式细胞仪实验室, 这种流动的 mrd 检测特别有趣, 当 MRD 的实时聚合酶链反应 (RT PCR) 是不可能的,即, 如果白血病特异分子标记在诊断 AML 样本中无法检测到。此外, 本议定书补充了更为敏感的分子 MRD 技术, 因为它旨在检测和量化代表功能细胞特征的异常造血祖细胞 (图 3)。
我们展示了如何用流式细胞术来量化三个造血祖群和不同成熟度的可供选择的隔间室, 而大多数临床实验室都有抗体。此外, 我们证实了这些细胞室在相应的病人派生移植 (PDX) 和治疗随访。

<table border="0" cellpadding="0" cellspacing="0" width="1146">
	<tbody>
		<tr height="20">
			<td height="20" style="height:21px;width:363px;">Pancoll</td>
			<td style="width:189px;">PAN-Biotech</td>
			<td style="width:128px;">P04-60500</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="75">
			<td height="75" style="height:75px;">RBC Lysis Buffer (10x)</td>
			<td>Ozyme</td>
			<td>BLE420301</td>
			<td style="width:467px;">RBC Lysis solution A : 8.29 g of NH4Cl + 0.037 g of Na2EDTA in 100 mL of sterile H2O and RBC Lysis solution B: 1 g of KHCO3 in 100 mL of sterile H2O</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">NOD/SCID/IL2R&#947;cnull&#160; (NSG)&#160; mice</td>
			<td>JACKSON LABORATORY</td>
			<td>Stock No: 005557</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">PBS</td>
			<td>Gibco by life technologies</td>
			<td>14190-144</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">AutoMACS Running Buffer &#8211; MACS Separation Buffer</td>
			<td>MACS Buffer Miltenybiotec</td>
			<td>130-091-221</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD36-FITC (clone FA6-152, Iotest)</td>
			<td>Beckman Coulter</td>
			<td>PN IM0766U</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD33-PC5.5 (clone D3HL60.251, Iotest)</td>
			<td>Beckman Coulter</td>
			<td>B36289</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD90-APC (clone 5E10)</td>
			<td>Biolegend</td>
			<td>328114</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD19-ECD (clone J3-119, Iotest)</td>
			<td>Beckman Coulter</td>
			<td>A07770</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD34-AA700 (clone 581, Iotest)</td>
			<td>Beckman Coulter</td>
			<td>B92417</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD45RA-APC-H7 (clone HI100)&#160;</td>
			<td>Beckton Dickinson</td>
			<td>560674</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD38-Pacific Blue (clone LSI98-4-3, Iotest)</td>
			<td>Beckman Coulter</td>
			<td>B92396</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD45-KO (clone J.33, Iotest)</td>
			<td>Beckman Coulter</td>
			<td>B36294</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD3-PE</td>
			<td>Beckman Coulter</td>
			<td>IM1451</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD20-PE</td>
			<td>Beckman Coulter</td>
			<td>A07747</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-CD123-PC7</td>
			<td>Beckman Coulter</td>
			<td>B13647</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Flow-Set</td>
			<td>Beckman Coulter</td>
			<td>A63492</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Flow-Check</td>
			<td>Beckman Coulter</td>
			<td>A63493</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Navios</td>
			<td>Beckman Coulter</td>
			<td>DS-14644A</td>
			<td style="width:467px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">LSR Fortessa X20</td>
			<td>BD Biosciences</td>
			<td></td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">CST BD</td>
			<td>BD Biosciences</td>
			<td>655051</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">FacsFlow&#160;</td>
			<td>BD Biosciences</td>
			<td>336911</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-hCD45-FITC</td>
			<td>Biolegend</td>
			<td>BLE304006</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">Anti-mCD45-APC</td>
			<td>Biolegend</td>
			<td>BLE103112</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">EasySep human PE selection kit</td>
			<td>Stem Cell Technologies</td>
			<td>18000</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:21px;">EasySep&#160; magnet&#160;</td>
			<td>Stem Cell Technologies</td>
			<td>18551</td>
			<td></td>
		</tr>
	</tbody>
</table>

flow cytometry to estimate leukemia stem cells in primary acute myeloid leukemia and in patient-derived-xenografts, at diagnosis and follow up

急性髓系白血病 (AML) 是一种异种, 如果不治疗, 致命的疾病。这是成人白血病相关死亡的最常见原因。首先, AML 是一种造血干细胞 (HSC) 的疾病, 其特点是: 停止分化, 随后聚集白血病爆炸细胞, 减少功能性造血元件的生产。异质性延伸到白血病干细胞的存在, 这一动态细胞室的演变, 以克服各种选择压力强加在白血病的进展和治疗。为了进一步定义非定常种群, 添加 CD90 和 CD45RA 允许在 CD34+CD38 细胞间区分正常的 HSCs 和多能祖。在这里, 我们概述了一个协议, 以检测几个假定的 CD34, CD38, CD45RA, CD90) 的人反洗钱的主要爆炸细胞, 多参数流式细胞术的同时表达。此外, 我们还展示了如何量化三个祖群体和一个假定的多项种群的成熟程度。我们证实了这些人群存在于相应的病人衍生的移植。这种检测方法和定量的假定的可用于临床随访的化疗反应 (i. e., 最小残留疾病), 因为残端细胞可能导致 AML 复发。

在这里, 我们提出了一个方法来确定祖细胞的正常和恶性人骨髓标本。我们从成功的 PDX 收集骨髓和脾脏, 并进行多参数流式细胞术, 如上文所述。我们比较了在诊断病人样本和相应的 PDX 之间的几个亚群, 特别是 CD34+CD38 祖室, 特别是丰富的假定的。我们发现, 与诊断病人样本相比, PDX 的 CD34+CD38 爆炸分数较高 (3.48% vs 0.53%,图 2C, D)。有趣的是, 我们发现在 PDX 中, 与主要患者样本 (2.76% vs 0.48%,图 2E, F) 相比, 假设的 (显示 CD34+CD38-CD90-CD45RA+ 表型) 的比例更高, 这表明可能会丰富恶性本鼠模型中的血液组织祖细胞。正常祖细胞分数的频率在 PDX 和患者样本之间没有差异。 此外, 我们研究了基于 CD34、CD38、CD90 和 CD45A (如本协议所述) 在两个不同的患者样本中的爆炸细胞祖群, 在诊断和治疗随访中确定了 MRD 的水平。在第一个患者, CD34+CD38 (P6) 分数从诊断的0.06% 增加到3.33% 在第一治疗随访 (图 3A, B)。相比之下, 在第一次治疗随访 (图 3C, D) 中, 第二个病人的 CD34+CD38 (P6) 分数从诊断的7.8% 降低到2.27%。相应地, 在第一个患者中, 假定的自诊断项分数从0% 增加到 0.65% (图 3A', B '), 第二个病人从6.57% 诊断到1.44% 在治疗随访中有所减少 (图 3C", D ')。同样, 由分子标记 (即 NPM1 突变 [第一个病人] 和 CBFB-MYH11 易位 [第二个病人]) 的 mrd 监测显示, 第一个病人 (0.8%) 与第二个病人 (0.05%) 相比, 第一次治疗的分子 mrd 减少了。后续点 (图 3E, G)。最后, 为了验证假定的 P6 是恶性的, 估计白血病相关抗原 CD123 和 CD33 的表达, 显示两名患者的 CD33 异常表达 (图 3F, G)。

<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56976/56976fig1.jpg"> 图 1: 用于生理前体和反洗钱爆炸的浇口策略.密度图与门的生理前体显示的正常骨髓。(A) 根据所有 mononucleated 细胞的 CD45dimSSClow 表型对爆炸细胞进行浇注。(B) hematogones (CD38+CD19+) 的门控, 用于验证 CD38 阳性。(C). 基于 CD33 和 CD36 的正常成髓细胞、monoblasts 和孵育的浇注策略。(D) 可以将爆炸细胞分离成 CD34+ 祖亚群, 并将 CD38 表达式应用到 P6 (CD34+CD38)、P7 (CD34+CD38dim)、P8 (CD34+CD38+) 细胞室中。(E) 基于 CD34 和 CD38 表达式的 hematogones 的门控, 验证 CD38 的积极性。(G) 使用 CD90 和 CD45RA 的表达式 (如前面所述的9) 来确定 HSC、MPP、LMPP 和假定的。注意, 没有检测到, 因为这是一个正常的骨髓样本。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56976/56976fig1large.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/56976/56976fig2.jpg"> 图 2: 通过多参数流式细胞术, 在患者和相应的患者衍生的异种异体 (PDX) 中爆炸细胞祖群。(A-B)PDX 的嵌合体分析。(A) 鼠和人的爆炸首先由大小和结构定义 (FSC, SSC)。(B) 随后, 人与小鼠 CD45 染色的百分比表明 xenoengraftment 和白血病负担。CD34+CD38 (C) 主诊断和 (D) PDX AML 样品之间的百分比比较。对 (E) 主 AML 和 (F) PDX 之间假定的 CD34+CD38-CD90-CD45RA+ 的比较。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56976/56976fig2large.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/56976/56976fig3.jpg"> 图 3: 在两个患者的诊断和缓解诱导治疗后, 对最小残留疾病 (MRD) 检测的爆炸细胞祖群.两个典型患者 (A、C) 诊断和 (B、D) 缓解诱导治疗后的 CD34+CD38 细胞细胞亚群的流动分析。图 (A ' D ') 说明了各自的 P6 门, 其中包含了两名患者在诊断和最初治疗后的假定的内化。在 (E, G) 中显示的是对这两名患者在五月期间 (NPM1 突变和 CBFß-MYH11 基因融合) 使用的分子标记的最小残留疾病 (MRD) 分析。(F, G)白血病相关抗原 CD123 和 CD33 在 P6 的表达, 显示 CD33 的异常表达。<a href="//cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/56976/56976fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up at JoVE.com

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up

通过流式细胞术, 我们勾勒出一种检测白血病干细胞标记物同时表达的协议。我们展示了如何量化三个祖群体和一个假定的多项种群的成熟程度。我们证实了这些人群存在于相应的病人衍生的移植。

流式细胞仪估测原发性急性髓系白血病和患者源性移植中白血病干细胞的诊断和随访

Acute myeloid leukemia (AML) is a heterogeneous, and if not treated, fatal disease. It is the most common cause of leukemia-associated mortality in ...

flow-cytometry-to-estimate-leukemia-stem-cells-primary-acute-myeloid

Nanyang Technological University

Research

JoVE Journal

Cancer Research

13.8K 次观看.  CHU Lille. 通过流式细胞术, 我们勾勒出一种检测白血病干细胞标记物同时表达的协议。我们展示了如何量化三个祖群体和一个假定的多项种群的成熟程度。我们证实了这些人群存在于相应的病人衍生的移植。

视频: Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

Response criteria in acute myeloid leukemia (AML) has recently been re-established, with morphologic examination utilized to determine whether patients have achieved complete remission (CR). Approximately half of the adult patients who entered CR will relapse within 12 months due to the outgrowth of residual AML cells in the bone marrow. The quantitation of these remaining leukemia cells, known as minimal or measurable residual disease (MRD), can be a robust biomarker for the prediction of these relapses. Moreover, retrospective analysis of several studies has shown that the presence of MRD in the bone marrow of AML patients correlates with poor survival. Not only is the total leukemic population, reflected by cells harboring a leukemia associated immune-phenotype (LAIP), associated with clinical outcome, but so is the immature low frequency subpopulation of leukemia stem cells (LSC), both of which can be monitored through flow cytometry MRD or MRD-like approaches. The availability of sensitive assays that enable detection of residual leukemia (stem) cells on the basis of disease-specific or disease-associated features (abnormal molecular markers or aberrant immunophenotypes) have drastically improved MRD assessment in AML. However, given the inherent heterogeneity and complexity of AML as a disease, methods for sampling bone marrow and performing MRD and LSC analysis should be harmonized when possible. In this manuscript we describe a detailed methodology for adequate bone marrow aspirate sampling, transport, sample processing for optimal multi-color flow cytometry assessment, and gating strategies to assess MRD and LSC to aid in therapeutic decision making for AML patients.

Detection of minimal or measurable residual disease (MRD) is an important prognostic biomarker for refining risk assessment and predicting relapse in acute myeloid leukemia (AML). These comprehensive guidelines and recommendations with best practices for consistent and accurate identification and detection of MRD, may aid in making effective AML treatment decisions.

测定急性髓系白血病可测残留病和白血病干细胞的骨髓标本和过程综合协议

Response criteria in acute myeloid leukemia (AML) has recently been re-established, with morphologic examination utilized to determine whether patients ...

科研

癌症研究

Preparation of Primary Acute Lymphoblastic Leukemia Cells in Different Cell Cycle Phases by Centrifugal Elutriation

The ability to synchronize cells has been central to advancing our understanding of cell cycle regulation. Common techniques employed include serum deprivation; chemicals which arrest cells at different cell cycle phases; or the use of mitotic shake-off which exploits their reduced adherence. However, all of these have disadvantages. For example, serum starvation works well for normal cells but less well for tumor cells with compromised cell cycle checkpoints due to oncogene activation or tumor suppressor loss. Similarly, chemically-treated cell populations can harbor drug-induced damage and show stress-related alterations. A technique which circumvents these problems is counterflow centrifugal elutriation (CCE), where cells are subjected to two opposing forces, centrifugal force and fluid velocity, which results in the separation of cells on the basis of size and density. Since cells advancing through the cycle typically enlarge, CCE can be used to separate cells into different cell cycle phases. Here we apply this technique to primary acute lymphoblastic leukemia cells. Under optimal conditions, an essentially pure population of cells in G1 phase and a highly enriched population of cells in G2/M phases can be obtained in excellent yield. These cell populations are ideally suited for studying cell cycle-dependent mechanisms of action of anticancer drugs and for other applications. We also show how modifications to the standard procedure can result in suboptimal performance and discuss the limitations of the technique. The detailed methodology presented should facilitate application and exploration of the technique to other types of cells.

This protocol describes the use of centrifugal elutriation to separate primary acute lymphoblastic leukemia cells into different cell cycle phases.

离心淘洗制备不同细胞周期的原发性急性淋巴细胞白血病细胞

The ability to synchronize cells has been central to advancing our understanding of cell cycle regulation. Common techniques employed include serum ...

Isolation and Characterization of Tumor-initiating Cells from Sarcoma Patient-derived Xenografts

The existence and importance of tumor-initiating cells (TICs) have been supported by increasing evidence during the past decade. These TICs have been shown to be responsible for tumor initiation, metastasis, and drug resistance. Therefore, it is important to develop specific TIC-targeting therapy in addition to current chemotherapy strategies, which mostly focus on the bulk of non-TICs. In order to further understand the mechanism behind the malignancy of TICs, we describe a method to isolate and to characterize TICs in human sarcomas. Herein, we show a detailed protocol to generate patient-derived xenografts (PDXs) of human sarcomas and to isolate TICs by fluorescence-activated cell sorting (FACS) using human leukocyte antigen class I (HLA-1) as a negative marker. Also, we describe how to functionally characterize these TICs, including a sphere formation assay and a tumor formation assay, and to induce differentiation along mesenchymal pathways. The isolation and characterization of PDX TICs provide clues for the discovery of potential targeting therapy reagents. Moreover, increasing evidence suggests that this protocol may be further extended to isolate and characterize TICs from other types of human cancers.

We describe a detailed protocol for the isolation of tumor-initiating cells from human sarcoma patient-derived xenografts by fluorescence-activated cell sorting, using human leukocyte antigen-1 (HLA-1) as a negative marker, and for the further validation and characterization of these HLA-1-negative tumor-initiating cells.

来自沙柯玛患者衍生异种移植物的肿瘤启动细胞的分离和表征

The existence and importance of tumor-initiating cells (TICs) have been supported by increasing evidence during the past decade. These TICs have been ...

Immunoglobulin Gene Sequence Analysis In Chronic Lymphocytic Leukemia: From Patient Material To Sequence Interpretation

During B cell maturation, the complex process of immunoglobulin (IG) gene V(D)J recombination coupled with somatic hypermutation (SHM) gives rise to a unique DNA sequence within each individual B cell. Since B cell malignancies result from the clonal expansion of a single cell, IG genes represent a unique molecular signature common to all the malignant cells within an individual patient; thus, IG gene rearrangements can be used as clonal markers. In addition to serving as an important clonal identifier, the IG gene sequence can act as a &#39;molecular timeline&#39; since it is associated with specific developmental stages and hence reflects the history of the B cell involved in the neoplastic transformation. Moreover, for certain malignancies, in particular chronic lymphocytic leukemia (CLL), the IG gene sequence holds prognostic and potentially predictive capabilities. That said, extrapolating meaningful conclusions from IG gene sequence analysis would be impossible if robust methods and tools were not available to aid in their analysis. This article, drawing on the vast experience of the European Research Initiative on CLL (ERIC), details the technical aspects and essential requirements necessary to ensure reliable and reproducible IG gene sequence analysis in CLL, a test that is now recommended for all CLL patients prior to treatment. More specifically, the various analytical stages are described ranging from the identification of the clonotypic IG gene rearrangement and the determination of the nucleotide sequence to the accurate clinical interpretation of the IG gene sequence data.

Herein, we present a protocol that details the technical aspects and essential requirements to ensure robust IG gene sequence analysis in patients with chronic lymphocytic leukemia (CLL), based on the accumulated experience of the European Research initiative on CLL (ERIC).

慢性淋巴细胞白血病免疫球蛋白基因序列分析: 从患者材料到序列解释

During B cell maturation, the complex process of immunoglobulin (IG) gene V(D)J recombination coupled with somatic hypermutation (SHM) gives rise to a ...

A Chromatin Immunoprecipitation Assay to Identify Novel NFAT2 Target Genes in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is characterized by the expansion of malignant B cell clones and represents the most common leukemia in western countries. The majority of CLL patients show an indolent course of the disease as well as an anergic phenotype of their leukemia cells, referring to a B cell receptor unresponsive to external stimulation. We have recently shown that the transcription factor NFAT2 is a crucial regulator of anergy in CLL. A major challenge in the analysis of the role of a transcription factor in different diseases is the identification of its specific target genes. This is of&#160;great significance for the elucidation of pathogenetic mechanisms and potential therapeutic interventions. Chromatin immunoprecipitation (ChIP) is a classic technique to demonstrate protein-DNA interactions and can, therefore, be used to identify direct target genes of transcription factors in mammalian cells. Here, ChIP was used to identify LCK as a direct target gene of NFAT2 in human CLL cells. DNA and associated proteins are crosslinked using formaldehyde and subsequently sheared by sonication into DNA fragments of approximately 200-500 base pairs (bp). Cross-linked DNA fragments associated with NFAT2 are then selectively immunoprecipitated from cell debris using an &#945;NFAT2 antibody. After purification, associated DNA fragments are detected via quantitative real-time PCR (qRT-PCR). DNA sequences with evident enrichment represent regions of the genome which are targeted by NFAT2 in vivo. Appropriate shearing of the DNA and the selection of the required antibody are particularly crucial for the successful application of this method. This protocol is ideal for the demonstration of direct interactions of NFAT2 with target genes. Its major limitation is the difficulty to employ ChIP in large-scale assays analyzing the target genes of multiple transcription factors in intact organisms.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western world. NFAT transcription factors are important regulators of development and activation in numerous cell types. Here, we present a protocol for the use of chromatin immunoprecipitation (ChIP) in human CLL cells to identify novel target genes of NFAT2.

一种检测慢性淋巴细胞白血病新 nfat2 靶基因的染色质免疫沉淀法

Chronic lymphocytic leukemia (CLL) is characterized by the expansion of malignant B cell clones and represents the most common leukemia in western ...

Assessment of the Metabolic Profile of Primary Leukemia Cells

The metabolic requirement of cancer cells can negatively influence survival and treatment efficacy. Nowadays, pharmaceutical targeting of metabolic pathways is tested in many types of tumors. Thus, characterization of cancer cell metabolic setup is inevitable in order to target the correct pathway to improve the overall outcome of patients. Unfortunately, in a majority of cancers, the malignant cells are quite difficult to obtain in higher numbers and the tissue biopsy is required. Leukemia is an exception, where a sufficient number of leukemic cells can be isolated from the bone marrow. Here, we provide a detailed protocol for the isolation of leukemic cells from leukemia patients bone marrow and subsequent analysis of their metabolic state using extracellular flux analyzer. Leukemic cells are isolated by the density gradient, which does not affect their viability. The next cultivation step helps them to regenerate, thus the metabolic state measured is the state of cells in optimal conditions. This protocol allows achieving consistent, well-standardized results, which could be used for the personalized therapy.

Here we present a protocol for the isolation of leukemic cells from leukemia patients bone marrow and analysis of their metabolic state. Assessment of the metabolic profile of primary leukemia cells could help to better characterize the demand of primary cells and could lead up to more personalized medicine.

原发性白血病细胞代谢谱的评价

The metabolic requirement of cancer cells can negatively influence survival and treatment efficacy. Nowadays, pharmaceutical targeting of metabolic ...

Flow Cytometric Analysis of Mitochondrial Reactive Oxygen Species in Murine Hematopoietic Stem and Progenitor Cells and MLL-AF9 Driven Leukemia

We present a flow cytometric approach for analyzing mitochondrial ROS in various live bone marrow (BM)-derived stem and progenitor cell populations from healthy mice as well as mice with AML driven by MLL-AF9. Specifically, we describe a two-step cell staining process, whereby healthy or leukemia BM cells are first stained with a fluorogenic dye that detects mitochondrial superoxides, followed by staining with fluorochrome-linked monoclonal antibodies that are used to distinguish various healthy and malignant hematopoietic progenitor populations. We also provide a strategy for acquiring and analyzing the samples by flow cytometry. The entire protocol can be carried out in a timeframe as short as 3-4 h. We also highlight the key variables to consider as well as the advantages and limitations of monitoring ROS production in the mitochondrial compartment of live hematopoietic and leukemia stem and progenitor subpopulations using fluorogenic dyes by flow cytometry. Furthermore, we present data that mitochondrial ROS abundance varies among distinct healthy HSPC sub-populations and leukemia progenitors and discuss the possible applications of this technique in hematologic research.

We describe a method for using multiparameter flow cytometry to detect mitochondrial reactive oxygen species (ROS) in murine healthy hematopoietic stem and progenitor cells (HSPCs) and leukemia cells from a mouse model of acute myeloid leukemia (AML) driven by MLL-AF9.

木尿造血干细胞和祖细胞和MLL-AF9驱动白血病线粒体反应氧物种的流细胞学分析

We present a flow cytometric approach for analyzing mitochondrial ROS in various live bone marrow (BM)-derived stem and progenitor cell populations from ...

Subcellular Fractionation of Primary Chronic Lymphocytic Leukemia Cells to Monitor Nuclear/Cytoplasmic Protein Trafficking

Nuclear export of macromolecules is often deregulated in cancer cells. Tumor suppressor proteins, such as p53, can be rendered inactive due to aberrant cellular localization disrupting their mechanism of action. The survival of chronic lymphocytic leukaemia (CLL) cells, among other cancer cells, is assisted by the deregulation of nuclear to cytoplasmic shuttling, at least in part through deregulation of the transport receptor XPO1 and the constitutive activation of PI3K-mediated signaling pathways. It is essential to understand the role of individual proteins in the context of their intracellular location to gain a deeper understanding of the role of such proteins in the pathobiology of the disease. Furthermore, identifying processes that underlie cell stimulation and the mechanism of action of specific pharmacological inhibitors, in the context of subcellular protein trafficking, will provide a more comprehensive understanding of the mechanism of action. The protocol described here enables the optimization and subsequent efficient generation of nuclear and cytoplasmic fractions from primary chronic lymphocytic leukemia cells. These fractions can be used to determine changes in protein trafficking between the nuclear and cytoplasmic fractions upon cell stimulation and drug treatment. The data can be quantified and presented in parallel with immunofluorescent images, thus providing robust and quantifiable data.

This protocol enables the optimization and subsequent efficient generation of nuclear and cytoplasmic fractions from primary chronic lymphocytic leukemia cells. These samples are used to determine protein localization as well as changes in protein trafficking that take place between the nuclear and cytoplasmic compartments upon cell stimulation and drug treatment.

原发性慢性淋巴细胞白血病细胞的细胞次细胞分段监测核/细胞质蛋白贩运

Nuclear export of macromolecules is often deregulated in cancer cells. Tumor suppressor proteins, such as p53, can be rendered inactive due to aberrant ...

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts

We present here an integrative approach for testing efficacy of targeted therapies that combines the next generation sequencing technolo-gies, therapeutic target analyses and drug response monitoring using patient derived xenografts (PDX). This strategy was validated using ovarian tumors as an example. The mate-pair next generation sequencing (MPseq) protocol was used to identify structural alterations and followed by analysis of potentially targetable alterations. Human tumors grown in immunocompromised mice were treated with drugs selected based on the genomic analyses. Results demonstrated a good correlation between the predicted and the observed responses in the PDX model. The presented approach can be used to test the efficacy of combination treatments and aid personalized treatment for patients with recurrent cancer, specifically in cases when standard therapy fails and there is a need to use drugs off label.

Here we present a protocol to test the efficacy of targeted therapies selected based on the genomic makeup of a tumor. The protocol describes identification and validation of structural DNA rearrangements, engraftment of patients&#8217; tumors into mice and testing responses to corresponding drugs.

使用结构DNA改变分析和患者衍生异种移植测试癌症的靶向疗法

We present here an integrative approach for testing efficacy of targeted therapies that combines the next generation sequencing technolo-gies, therapeutic ...

Two Flow Cytometric Approaches of NKG2D Ligand Surface Detection to Distinguish Stem Cells from Bulk Subpopulations in Acute Myeloid Leukemia

Within the same patient, absence of NKG2D ligands (NKG2DL) surface expression was shown to distinguish leukemic subpopulations with stem cell properties (so called leukemic stem cells, LSCs) from more differentiated counterpart leukemic cells that lack disease initiation potential although they carry similar leukemia specific genetic mutations. NKG2DL are biochemically highly diverse MHC class I-like self-molecules. Healthy cells in homeostatic conditions generally do not express NKG2DL on the cell surface. Instead, expression of these ligands is induced upon exposure to cellular stress (e.g., oncogenic transformation or infectious stimuli) to trigger elimination of damaged cells via lysis through NKG2D-receptor-expressing immune cells such as natural killer (NK) cells. Interestingly, NKG2DL surface expression is selectively suppressed in LSC subpopulations, allowing these cells to evade NKG2D-mediated immune surveillance. Here, we present a side-by-side analysis of two different flow cytometry methods that allow the investigation of NKG2DL surface expression on cancer cells i.e., a method involving pan-ligand recognition and a method involving staining with multiple antibodies against single ligands. These methods can be used to separate viable NKG2DL negative cellular subpopulations with putative cancer stem cell properties from NKG2DL positive non-LSC.

We present two different staining protocols for NKG2D ligand (NKG2DL) detection in human primary acute myeloid leukemia (AML) samples. The first approach is based on a fusion protein, able to recognize all known and potentially yet unknown ligands, while the second protocol relies on the addition of multiple anti-NKG2DL antibodies.

NKG2D 利甘德表面检测的两种流细胞学方法，以区分干细胞与急性骨髓性白血病中的散装亚群

Within the same patient, absence of NKG2D ligands (NKG2DL) surface expression was shown to distinguish leukemic subpopulations with stem cell properties ...