作者感谢 Paola Suatoni、埃琳娜 Bertocchi、卡罗莱纳 Ninni、Annamaria Calanca 和 Chiara 卡斯特罗邦菲在审判和行政援助方面处理志愿人员;Jacomelli 和 Citterio 的数据管理。这项工作得到了意大利癌症研究协会的支持 [调查员赠款 No. 15928, 14318 至 GS, 12162 (特别方案 "癌症风险评估和早期诊断的创新工具", 5x1000)];意大利卫生部 [授予 No。RF-2010];格兰特 UO1 CA166905 来自美国国家癌症研究所。MB 得到了基金会 Pezcoller 奖学金的支持。

该协议是由我们机构的研究伦理委员会批准的. 
 1. 等离子样本采集 <ol> <li> 在室温下, 在采血管中收集10毫升的全血样品, 喷淋涂层的 K 2 EDTA 并贮存. 
	注意: 为了最小化溶血, 在2小时内分离血浆。不要将整个血液储存在低温 ( 即 , 4 和 #176; C), 以避免热休克和细胞裂解导致不 miRNA 释放. </li>
	<li> 在1小时内, 通过第一个离心步骤在 1258 x g 和4和 #176 中分离等离子体; C 为 10 min. </li>
	<li> 将血浆上清液转化为15毫升管, 小心避免与淋巴细胞环接触. </li>
	<li> 在 1258 x g 和4和 #176 上第二次离心等离子体; C 为10分钟. </li>
	<li> 分1毫升的血浆变成1.5 毫升的 cryovials, 避免在试管的底部收集血浆分数. </li>
	<li> 存储所有的等分在和 #8722; 80 和 #176; C, 除一个为溶血的评估。分子分析应在5周内进行. </li>
</ol> 2。分光光度法测定溶血性的研究 <ol> <li> 在等离子分离步骤之后, 在试管中, 在 1X PBS (, 如 、100和 #181 中, 对血浆样品进行1:10 稀释, 900 和 #181; l 1XPBS) 和混合质它. 
	注: 在分光光度测量前不应冷冻血浆样品, 因为样品的冻融 (特别是 lipemic 样品) 可以形成絮, 干扰光度分析. </li>
	<li> 使用紫外可见分光光度计读取 375 nm、414 nm、541 nm 和 576 nm 的吸光度, 并在 750 nm 和路径长度 10 mm 上进行基线校正. 使用1毫升 1x PBS 进行空白测量. </li>
	<li> 计算 414 nm 和375纳米的吸光度之间的比值; 如果高于 1.4, 则考虑样本溶血并重复抽取血液 (QC1 表 1 ). </li>
</ol> 3。血浆总 RNA 提取物 <ol> <li> 准备 1 Thioglycerol/均质 (OMG) 解决方案与20和 #181; L 1 Thioglycerol 每毫升均匀化溶液。由于 1-Thioglycerol 是粘性的, 仔细的吸管精确测量。在使用它之前, 在冰上或在2-10 ° #176 上冷却 OMG 解决方案. 
	注: 工作解决方案稳定在2-10 和 #176; C 为1月. </li>
	<li> 通过添加275和 #181 将冻干 dnasei I 挂起; 将核酸的水放入瓶中并轻轻混合 (不要漩涡)。作为一个视觉辅助, 添加5和 #181; L 蓝色染料的重组 dnasei I 和免除的解决方案, 以一次性等分在核酸自由管。存储重组 dnasei I 在-30 和 #176; c 到-10 和 #176; c. </li>
	<li> 从200和 #181 开始; l 等离子, 加入200和 #181; 我的冷冻 OMG 解决方案. </li>
	<li> 旋涡 15-30 s 以确保完全均匀化。如果发泡发生, 让样品沉淀在冰上. </li>
	<li> 添加200和 #181; 溶解缓冲液和 25 #181; 蛋白酶 K l 对匀浆样品和二十年代旋涡. </li>
	<li> 在37和 #176 预热的 thermomixer 中孵育样品15分钟; C. </li>
	<li> 在仪器的甲板托盘上为每个样品装一个墨盒, 并将 plugger 放在适当的位置. </li>
	<li> 将裂解液转移到仪器墨盒中的适当位置 </li>
	<li> 添加5和 #181; dnasei 我解决了墨盒中的正确位置. </li>
	<li> 在每个洗脱管的底座上添加60和 #181; L 核酸的无水. </li>
	<li> 选择 #34; miRNA 组织和 #34; 方法并开始自动净化运行。总 RNA 样品可以被存放在和 #8722; 80 和 #176; C. </li>
</ol> 4。Taq-based rt <ol> <li> 使用 Taq rt 底漆池与感兴趣的 rna 转换 RNA 与 Taq rna 反转录试剂盒的 cDNA. </li>
	<li> 准备12和 #181; 在1.5 毫升的离心管中, 根据试剂盒说明, 使用6和 #181; l 自定义 Taq rt 底漆池. </li>
	<li> 添加3和 #181; 最后一卷15和 #181 的总 RNA, l 和在冰中孵育5分钟. </li>
	<li> 在热循环上加载 RT 反应, 配置如下:16 和 #176; c 为30分钟、42和 #176; c 为 30 min、85和 #176; c 为5分钟, 并在4和 #176 处举行; c. 
	注: 该 cDNA 可存储在-15 至-20 和 #176; C 至少一周. </li>
</ol> 5。预放大 <ol> <li> 混合2.5 和 #181; 每台 RT 产品的 l 与12.5 和 #181; Taq 主混合2x、3.75 和 #181; l 自定义 Taq 池, 6.25 和 #181; l 核酸-免费水, 总容量为25和 #181; l. </li>
	<li> 根据以下热量剖面, 使用热循环执行放大反应:95、#176; c 为10分钟, 55 和 #176; c 为 2 min, 72 和 #176; c 为 2 min, 12 个周期95和 #176; c 为十五年代, 和60和 #176; c 为 4 min, 然后按住99.9 和 #176; c 为10分钟, 在4和 #176; c. </li>
	<li> 通过添加175和 #181 稀释产品; 0.1X TE, pH 值 8.0. 
	注: 稀释后的产品可存放在-15 至-20 #176; C 至少一周. </li>
</ol> 6。qPCR 对自定义 Taq 阵列 rna 卡的反应 <ol> <li> 使用384井 microfluidicCustom Taq 阵列 rna 卡来同时测量8样本中的24特定 rna (在重复时被发现) 的等离子水平。MiRBase ID (v21) 为 24 rna 是: has-miR-101-3p, has-miR-106a-5p, has-miR-126-3p, has-miR-133a-3p, has-miR-140-3p, has-miR-140-5p, has-miR-142-3p, has-miR-145-5p, has-miR-148b-3p, has-miR-15b-5p, has-miR-16-5p, has-miR-17-5p,has-miR-197-3p、has-miR-19b-3p、has-miR-21-5p、has-miR-221-3p、has-miR-28-3p、has-miR-30b-5p、has-miR-30c-5p、has-miR-320a、has-miR-451a、has-miR-486-5p、has-miR-660-5p 和 has-miR-92a-3p. </li>
	<li> 混合1.13 和 #181; 稀释后的前样品的 l, 56.25 和 #181; 2X Taq 通用主混合和55.69 和 #181; 核酸水在0.5 毫升管中. </li>
	<li> 在自定义 Taq 阵列 rna 卡上加载多达 8 PCR 反应组合. </li>
	<li> 311 x g 离心2分钟. </li>
	<li> 使用阵列卡封口机密封自定义卡. </li>
	<li> 运行实时反应, 使用实时 PCR 系统对循环参数进行修改: 94.5、#176; c 为10分钟, 40 循环97和 #176; c 为三十年代, 59.7 和 #176; c 为六十年代. </li>
</ol> 7。数据外推和比率生成 <ol> <li> 使用该软件获取原始 Ct 值, 设置自动基线以删除背景信号, 并为所有化验和样本确定一个固定阈值0.15。用较差的放大曲线和/或较差的被动参考信号去除斑点. </li>
	<li> 导出 #34 中的原始 ct 值; xls 和 #34; 格式化并使用两个重复项的 ct 平均值进行进一步分析. </li>
	<li> 关联 rna 和 #39; 表达式水平对临床研究样本的历史测量( 表 2 )。如果每个定制的微流控芯片上至少有50% 的样品产生了皮尔逊和 #39 的相关性和 #60; 97.5, 重复该卡 (QC2 在 表 1 中). </li>
	<li> 计算 #8722; #916; 在所有 rna 之间的 Cts, 相当于 miRNA 比率的 log2 值. </li>
</ol> 8。相关 miRNA 特征的溶血性评价 <ol> <li> 使用以下 miRNA 比率与各自的切断 (log2 值) 生成与溶血相关的 miRNA 签名, 用于短存储等离子样品 (1-5 周和 #8722; 80 和 #176; C):miR-126/451 #60; #8722; 0.07, 15 b/451 和 #60; #8722; 3.67, 221/451 和 #60; #8722; 3.18, 30 b/451 和 #60; #8722 1.1、126、486-5p、#60、#8722; 0.33、15、486-5p、#60、#8722、3.86、221、486-5、#60、#8722、3.17、30、486-5p、#60、#8722; 1.42、126/92、#60; 1.8,15 b/92 #60; #8722; 1.8, 221/92 a 和 #60; #8722; 1.04, 30 b/92 a 和 #60; 0.87, 126/16 和 #60; #8722; 2.85, 15 b/16 和 #60; #8722; 6.33, 221/16 和 #60; #8722; 5.9, 30 b/16 和 #60; #8722; 3.68. </li>
	<li> 分类为溶血样本, 其中至少50% 的比率 (8 出 16) 超过各自的截止 (QC3 在 表 1 ). </li>
</ol> 9。风险级别的定义: 高、中级和低 <ol> <li> 定义构成 MSC 的 miRNA 比率的四签名, 如所报告的 图 3 : 疾病风险 (RD)、侵袭性疾病风险 (RAD)、存在疾病 (PD) 和侵袭性疾病 (PAD) 的存在. </li>
	<li> 对于每个签名, 定义超短存储等离子样本 (1-5 周和 #8722; 80 和 #176; C) 超过各自截止值的比率。RD 和 PD 所需的超出比率为正数的 9, 为 27, 14 中的28用于 RAD 和 PAD ( 图 3 A ). </li>
	<li> 属性分别为每个样本的 MSC 风险等级如下: 低风险, 如果 rd 阴性的 和 #8745; PD 阴性 和 #8745; rad 阴性 和 #8745; 垫 阴性 ; 中级风险如果 rd pos 和 #8746;PD pos 和 #8745; rad 阴性 和 #8745; 填充 阴性 ;或高风险如果 RAD pos 和 #8746; PAD pos ( 图 3 B )。
</ol>

<ol>
	<li>Siegel, R. L., Miller, K. D., Jemal, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cancer+Statistics,+2017.">Cancer Statistics, 2017.</a> CA Cancer J Clin. 67 (1), 7-30 (2017).</li><li>Malvezzi, 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=European+cancer+mortality+predictions+for+the+year+2017,+with+focus+on+lung+cancer.">European cancer mortality predictions for the year 2017, with focus on lung cancer.</a> Ann Oncol. , 10 (2017).</li><li>Miller, K. D., 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=Cancer+treatment+and+survivorship+statistics,+2016.">Cancer treatment and survivorship statistics, 2016.</a> CA Cancer J Clin. 66 (4), 271-289 (2016).</li><li>Kanne, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Screening+for+lung+cancer:+what+have+we+learned.">Screening for lung cancer: what have we learned.</a> AJR Am. J Roentgenol. 202 (3), 530-535 (2014).</li><li>Aberle, D. R., 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=Reduced+lung-cancer+mortality+with+low-dose+computed+tomographic+screening.">Reduced lung-cancer mortality with low-dose computed tomographic screening.</a> N Engl J Med. 365 (5), 395-409 (2011).</li><li>Wender, R., 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=American+Cancer+Society+lung+cancer+screening+guidelines.">American Cancer Society lung cancer screening guidelines.</a> CA Cancer J Clin. 63 (2), 107-117 (2013).</li><li>Molina-Vila, M. 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=Liquid+Biopsy+in+Non-Small+Cell+Lung+Cancer.">Liquid Biopsy in Non-Small Cell Lung Cancer.</a> Front Med (Lausanne). , 69 (2016).</li><li>Sozzi, G., Boeri, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Potential+biomarkers+for+lung+cancer+screening.">Potential biomarkers for lung cancer screening.</a> Transl Lung Cancer Res. 3 (3), 139-148 (2014).</li><li>Shepherd, F. A., Douillard, J. Y., Blumenschein, G. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immunotherapy+for+non-small+cell+lung+cancer:+novel+approaches+to+improve+patient+outcome.">Immunotherapy for non-small cell lung cancer: novel approaches to improve patient outcome.</a> J Thorac Oncol. 6 (10), 1763-1773 (2011).</li><li>Ajona, D., 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=Investigation+of+complement+activation+product+c4d+as+a+diagnostic+and+prognostic+biomarker+for+lung+cancer.">Investigation of complement activation product c4d as a diagnostic and prognostic biomarker for lung cancer.</a> J Natl Cancer Inst. 105 (18), 1385-1393 (2013).</li><li>Boyle, P., 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=Clinical+validation+of+an+autoantibody+test+for+lung+cancer.">Clinical validation of an autoantibody test for lung cancer.</a> Ann Oncol. 22 (2), 383-389 (2011).</li><li>Hayes, J., Peruzzi, P. P., Lawler, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+in+cancer:+biomarkers,+functions+and+therapy.">MicroRNAs in cancer: biomarkers, functions and therapy.</a> Trends Mol Med. , (2014).</li><li>Croce, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Causes+and+consequences+of+microRNA+dysregulation+in+cancer.">Causes and consequences of microRNA dysregulation in cancer.</a> Nat Rev Genet. 10 (10), 704-714 (2009).</li><li>Iorio, M. V., Croce, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNA+dysregulation+in+cancer:+diagnostics,+monitoring+and+therapeutics.+A+comprehensive+review.">MicroRNA dysregulation in cancer: diagnostics, monitoring and therapeutics. A comprehensive review.</a> EMBO Mol Med. 4 (3), 143-159 (2012).</li><li>Schwarzenbach, H., Nishida, N., Calin, G. A., Pantel, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+relevance+of+circulating+cell-free+microRNAs+in+cancer.">Clinical relevance of circulating cell-free microRNAs in cancer.</a> Nat Rev Clin Oncol. 11 (3), 145-156 (2014).</li><li>Mitchell, P. S., 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=Circulating+microRNAs+as+stable+blood-based+markers+for+cancer+detection.">Circulating microRNAs as stable blood-based markers for cancer detection.</a> Proc Natl Acad Sci U S A. 105 (30), 10513-10518 (2008).</li><li>Hanke, 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=A+robust+methodology+to+study+urine+microRNA+as+tumor+marker:+microRNA-126+and+microRNA-182+are+related+to+urinary+bladder+cancer.">A robust methodology to study urine microRNA as tumor marker: microRNA-126 and microRNA-182 are related to urinary bladder cancer.</a> Urol Oncol. 28 (6), 655-661 (2010).</li><li>Park, N. J., 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=Salivary+microRNA:+discovery,+characterization,+and+clinical+utility+for+oral+cancer+detection.">Salivary microRNA: discovery, characterization, and clinical utility for oral cancer detection.</a> Clin Cancer Res. 15 (17), 5473-5477 (2009).</li><li>Boeri, M., Pastorino, U., Sozzi, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Role+of+microRNAs+in+lung+cancer:+microRNA+signatures+in+cancer+prognosis.">Role of microRNAs in lung cancer: microRNA signatures in cancer prognosis.</a> Cancer J. 18 (3), 268-274 (2012).</li><li>Castoldi, 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=A+sensitive+array+for+microRNA+expression+profiling+(miChip)+based+on+locked+nucleic+acids+(LNA).">A sensitive array for microRNA expression profiling (miChip) based on locked nucleic acids (LNA).</a> RNA. 12 (5), 913-920 (2006).</li><li>Chen, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+quantification+of+microRNAs+by+stem-loop+RT-PCR.">Real-time quantification of microRNAs by stem-loop RT-PCR.</a> Nucleic Acids Res. 33 (20), 179 (2005).</li><li>Schulte, J. H., 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=Deep+sequencing+reveals+differential+expression+of+microRNAs+in+favorable+versus+unfavorable+neuroblastoma.">Deep sequencing reveals differential expression of microRNAs in favorable versus unfavorable neuroblastoma.</a> Nucleic Acids Res. 38 (17), 5919-5928 (2010).</li><li>Tiberio, P., Callari, M., Angeloni, V., Daidone, M. G., Appierto, V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Challenges+in+using+circulating+miRNAs+as+cancer+biomarkers.">Challenges in using circulating miRNAs as cancer biomarkers.</a> Biomed Res Int. , 731479 (2015).</li><li>Boeri, 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=Recent+advances+of+microRNA-based+molecular+diagnostics+to+reduce+false-positive+lung+cancer+imaging.">Recent advances of microRNA-based molecular diagnostics to reduce false-positive lung cancer imaging.</a> Expert Rev Mol Diagn. 15 (6), 801-813 (2015).</li><li>Benes, V., Castoldi, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expression+profiling+of+microRNA+using+real-time+quantitative+PCR,+how+to+use+it+and+what+is+available.">Expression profiling of microRNA using real-time quantitative PCR, how to use it and what is available.</a> Methods. 50 (4), 244-249 (2010).</li><li>Mestdagh, P., 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=Evaluation+of+quantitative+miRNA+expression+platforms+in+the+microRNA+quality+control+(miRQC)+study.">Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study.</a> Nat Methods. 11 (8), 809-815 (2014).</li><li>Pastorino, U., 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=Early+lung-cancer+detection+with+spiral+CT+and+positron+emission+tomography+in+heavy+smokers:+2-year+results.">Early lung-cancer detection with spiral CT and positron emission tomography in heavy smokers: 2-year results.</a> Lancet. 362 (9384), 593-597 (2003).</li><li>Boeri, 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=MicroRNA+signatures+in+tissues+and+plasma+predict+development+and+prognosis+of+computed+tomography+detected+lung+cancer.">MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer.</a> Proc Natl Acad Sci U S A. 108 (9), 3713-3718 (2011).</li><li>Sozzi, G., 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=Clinical+Utility+of+a+Plasma-Based+miRNA+Signature+Classifier+Within+Computed+Tomography+Lung+Cancer+Screening:+A+Correlative+MILD+Trial+Study.">Clinical Utility of a Plasma-Based miRNA Signature Classifier Within Computed Tomography Lung Cancer Screening: A Correlative MILD Trial Study.</a> J Clin Oncol. 32 (8), 768-773 (2014).</li><li>Pritchard, C. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Blood+cell+origin+of+circulating+microRNAs:+a+cautionary+note+for+cancer+biomarker+studies.">Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies.</a> Cancer Prev Res (Phila). 5 (3), 492-497 (2012).</li><li>Kirschner, M. B., 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=Haemolysis+during+sample+preparation+alters+microRNA+content+of+plasma.">Haemolysis during sample preparation alters microRNA content of plasma.</a> PLoS One. 6 (9), 24145 (2011).</li><li>Kirschner, M. B., 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+Impact+of+Hemolysis+on+Cell-Free+microRNA+Biomarkers.">The Impact of Hemolysis on Cell-Free microRNA Biomarkers.</a> Front Genet. 4 (94), (2013).</li><li>Fortunato, O., 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=Assessment+of+circulating+microRNAs+in+plasma+of+lung+cancer+patients.">Assessment of circulating microRNAs in plasma of lung cancer patients.</a> Molecules. 19 (3), 3038-3054 (2014).</li><li>Appierto, V., 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+lipemia-independent+NanoDrop((R))-based+score+to+identify+hemolysis+in+plasma+and+serum+samples.">A lipemia-independent NanoDrop((R))-based score to identify hemolysis in plasma and serum samples.</a> Bioanalysis. 6 (9), 1215-1226 (2014).</li><li>Kim, D. J., 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=Plasma+components+affect+accuracy+of+circulating+cancer-related+microRNA+quantitation.">Plasma components affect accuracy of circulating cancer-related microRNA quantitation.</a> J Mol Diagn. 14 (1), 71-80 (2012).</li><li>Kulstein, G., Marienfeld, R., Miltner, E., Wiegand, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automation+of+DNA+and+miRNA+co-extraction+for+miRNA-based+identification+of+human+body+fluids+and+tissues.">Automation of DNA and miRNA co-extraction for miRNA-based identification of human body fluids and tissues.</a> Electrophoresis. 37 (21), 2742-2750 (2016).</li><li>Schwarzenbach, H., da Silva, A. M., Calin, G., Pantel, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Data+Normalization+Strategies+for+MicroRNA+Quantification.">Data Normalization Strategies for MicroRNA Quantification.</a> Clin Chem. 61 (11), 1333-1342 (2015).</li><li>Schlosser, K., McIntyre, L. A., White, R. J., Stewart, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Customized+Internal+Reference+Controls+for+Improved+Assessment+of+Circulating+MicroRNAs+in+Disease.">Customized Internal Reference Controls for Improved Assessment of Circulating MicroRNAs in Disease.</a> PLoS ONE. 10 (5), 0127443 (2015).</li><li>Kroh, E. M., Parkin, R. K., Mitchell, P. S., Tewari, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+circulating+microRNA+biomarkers+in+plasma+and+serum+using+quantitative+reverse+transcription-PCR+(qRT-PCR).">Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR).</a> Methods. 50 (4), 298-301 (2010).</li><li>Wang, K., 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=Comparing+the+MicroRNA+spectrum+between+serum+and+plasma.">Comparing the MicroRNA spectrum between serum and plasma.</a> PLoS One. 7 (7), 41561 (2012).</li><li>Mestdagh, P., 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+novel+and+universal+method+for+microRNA+RT-qPCR+data+normalization.">A novel and universal method for microRNA RT-qPCR data normalization.</a> Genome Biol. 10 (6), 64 (2009).</li><li>Montani, 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=miR-Test:+A+Blood+Test+for+Lung+Cancer+Early+Detection.">miR-Test: A Blood Test for Lung Cancer Early Detection.</a> J Natl Cancer Inst. 19 (6), 063 (2015).</li><li>Sestini, S., 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=Circulating+microRNA+signature+as+liquid-biopsy+to+monitor+lung+cancer+in+low-dose+computed+tomography+screening.">Circulating microRNA signature as liquid-biopsy to monitor lung cancer in low-dose computed tomography screening.</a> Oncotarget. 20 (32), 32868-32877 (2015).</li><li>Verri, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mutational+Profile+from+Targeted+NGS+Predicts+Survival+in+LDCT+Screening-Detected+Lung+Cancers.">Mutational Profile from Targeted NGS Predicts Survival in LDCT Screening-Detected Lung Cancers.</a> J Thorac. Oncol. (17), 10 (2017).</li><li>Bianchi, 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+serum+circulating+miRNA+diagnostic+test+to+identify+asymptomatic+high-risk+individuals+with+early+stage+lung+cancer.">A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer.</a> EMBO Mol Med. 3 (8), 495-503 (2011).</li><li>Gyoba, J., Shan, S., Roa, W., Bedard, E. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diagnosing+Lung+Cancers+through+Examination+of+Micro-RNA+Biomarkers+in+Blood,+Plasma,+Serum+and+Sputum:+A+Review+and+Summary+of+Current+Literature.">Diagnosing Lung Cancers through Examination of Micro-RNA Biomarkers in Blood, Plasma, Serum and Sputum: A Review and Summary of Current Literature.</a> Int J Mol Sci. 17 (4), 494 (2016).</li></ol>

凯碧 Sozzi, 马蒂亚 Boeri, 乌戈·塞西 Pastorino 是发明三专利申请 Gensignia 生命科学, 关于 miRNA 签名在本文中披露。所有其余的作者都声明与所提交的工作没有利益冲突。

方法论工作流的陷阱和挑战 由于 BioMILD 是第一个前瞻性研究分析循环 rna 作为诊断工具, 阈值和切断用于数据分析是由追溯序列产生的。为了克服等离子体样品不同贮存间隔的问题, 可以对这些参数进行细化, 以达到提高 MSC 性能的目的。然而, 在开始 rna 分析之前, 需要仔细评估整个过程的几个方面, 如包含标准、样本收集和处理, 以及数据分析所采用的生物信息学算法。以下各节将重点讨论本文件中所描述的工作流的最关键点, 解决每一个步骤的主要问题, 然后提出克服这些问题的策略。
研究人口 BioMILD 筛选试验的报名标准为: 50-75 岁, 重电流或前 (少于10年) 吸烟者, 至少有30包年, 在5年内没有癌症病史。在这一人群中, 每年估计的肺癌患病率和发病率分别为1% 和0.7%。为了应用所提出的协议中所述的 MSC 测试, 所分析的种群应保持相似的特征。特别是, 上面描述的 QC2 步骤与从相似种群获得的给定历史数据进行比较。而在97.5 以下的相关性可能是技术问题的指示, 另一方面, 大多数人的循环 miRNA 水平的变化, 反映患肺癌的风险实际上是低于这个门槛。换言之, 如果 QC2 的步骤与此处报告的参数一起应用于罹患肺癌的高危人群, 它可能会排除可接受的样本。新的, 适当的参考参数, 然后应定义是特定的每个人口分析, 根据预期的结果。
血液收集和溶血 生物样品的收集是一个关键的分析步骤, 因为它可能会损害样品的质量和特征, 从而修改最终的分析结果。对于血样, 收集新鲜血液并尽快处理标本是很重要的。样品不应储存在4° c, 也不应冻结后, 血液撤退, 因为冻结和解冻通道可能导致细胞裂解 (溶血) 和 RNA 降解。为了减少溶血过程, 建议在2小时内分离血浆从血液收集31 。
溶血主要是由于红细胞 (红细胞) 的分解以及随之而来的在周围环境中释放其含量。这可能是一个问题的循环 rna 测试, 因为释放红细胞细胞内的内容戏剧性地改变了 rna 的轮廓在血液中, 可能影响准确性等离子体分析30。
能够识别血浆样品中的溶血程度也很小, 这对于基于循环 rna 的生物标记物的研究是至关重要的。溶血最初可以通过目视检查来评估, 因为在两个离心步骤之后, 等离子体的颜色可以从黄色到红色, 溶血样品。然而, 在分子生物标志物研究中, 单纯的视觉检查可能不够灵敏。
一个简单的, 分析的方法来识别溶血等离子体样品是分光光度测量的波长 (λ) = 414 nm 的主要氧峰值吸收, 经过适当调整的任何其他来源的干扰。为此, 我们将 414 nm 峰值归为 375 nm 的吸光度值, 这表明脂内容为33。或者, 或者更好的组合, 血脂-independenthemolysis 评分 (HS) 可以使用34。这个 spectrophotometrically-based 程序可以识别至少6.1 毫克/dL 的游离血红蛋白。否则, 溶血标本可以通过检测红细胞特异性 rna。因为即使是非常低的溶血百分率, 也能引起红细胞特异性 miRNA 水平的显著增加32, 纳et al.根据 16 rna 比值确定了特定的溶血相关特征, 可以有效血浆标本中溶血的分类33。所有上述的化验都可以结合使用, 因为吸光度比414/375 和/或 HS 是在一个分析阶段采用节省进一步的成本, 而测量溶血相关 rna 可用于 post-analytical 阶段作为质量控制步.
循环 rna 分离与 RNA 纯度 提取 RNA 程序是一个非常有影响的步骤, 成功的后续分析。从低输入样本, 如等离子体, 提取需要尽可能有效, 以确保准确的量化 rna。等离子体的特点是高浓度的许多蛋白质, 包括核酸, 和其他成分, 可以干扰下游酶反应的 RT-qPCR, 并可能影响循环 rna 检测。在这些类型的研究中使用了几种提取方法, 但总的来说, 有机萃取后, 硅 RNA 的丰富, 使清除等离子体抑制剂更好, 然后 TRIzol 单独35。然而, 在过去的几年中, 手工提取已被自动提取取代。与手动隔离协议相比, 自动系统的主要优点是具有较小的污染风险、较高的重现性和经济时间的使用。此外, 与手动协议36相比, 自动提取方法从血样中获得了最高的 miRNA 量和最高的效率。
正常化问题 血浆 miRNA 水平的正常化仍然是一个有争议的问题。事实上, 抽样质量或数量上的差异可能会干扰识别因疾病的存在或风险而导致的 rna 表达水平的真实变化, 从而导致模棱两可的数据解释和误导性结论。到目前为止, 缺乏共识导致了各种正常化战略37。
从等离子体样品中提取的总 rna 通常低于标准量化方法的阈值, 如紫外分光光度法或荧光分光光度法, 从而排除了 rna 质量标准化的38。因此, 应选择一个固定量而不是固定量的洗 RNA 作为 RT 反应39的输入。
用于组织样品 miRNA 分析的家政誊本, 如 RNU48 和 RNU6, 不适合于规范化的胞外 miRNA 测量, 因为它们都不能在循环中检测到, 因为核糖核酸介导的降解40,并且也以特定于疾病的方式进行解除管制37。目前尚不清楚是否有任何循环 rna 能有效地用作参考控制。例如, miR-16 经常被建议用于内务管理, 但 d不同研究表明, 它是解除管制的血浆样本的癌症患者28,37。此外, 溶血性对 miR-16 水平的影响很大30。
而对于高通量测定法, 在平均表达式值上测量数个 rna 和正则化通常是接受的41, 当需要分析有限数量的 rna 时, 不能应用这种规范化方法。为了绕过规范化问题, Boeri et al.以前建立了一个基于 24 rna28之间的对等比率的算法。这种方法, 尽管是非常有用的发展诊断工具, 并不容易允许区分有效改变 rna, 可能有一个作用, 肿瘤的发展, 从而确定 rna 作为功能校准器。另一项有效的战略, 由比安奇et al.所采用, 开发了一项血清和平试验, 用于肺癌早期检测, 是基于一组 6 "家政血清-rna" 的几何平均值的正常化, 这些样本之间的差别较小,患者的类别42。
miRNA-based 液体活检的特点及应用前景 等离子体理学硕士是一个分子无创试验研究的早期诊断肺癌的严重吸烟者。MSC 测试可以确定闭塞肺癌检测前的中间或高危对象, 具有高灵敏度 (SE, 87%) 和负预测值 (NPV, 99%)。具体地说, MSC 可以通过将假阳性结果减少到 3.7%, 从19.7% 闭塞单独29实现闭塞筛选。MSC 测试也表明, 只有在考虑肺癌患者的预后良好的表现, 并可以单独使用或与其他临床病理参数43,44相结合。潜在的, MSC 测试可以使肺癌诊断算法更具一致性, 从而减少筛选 cost-effectiveness。
除了 MSC 之外, 还报道了其他非侵入性的早期肺癌检测。比安奇et al。提出了一种基于 34 miRNA 签名45的循环和平测试, 然后将其减少为 13 miRNA 签名42。血清标本 fordiscovery 和验证从连续观察吸烟对象 (波斯菊) 闭塞筛选试验, 执行在欧洲肿瘤协会 (IEO, 米兰, 意大利)。在高危志愿者中, 和平号试验显示肺癌检测的准确性为78%。在13血清-rna 和24组成 MSC 之间, 只有 5 rna 是重叠的 (miR-92a、miR-30b、miR-30c、miR-148a 和 miR-140-5p)。这可能是由于不同类型的起始样品 (血清与血浆) 和数据的细化。事实上, 在和平号试验中, 作者选择了 6 rna 作为血清中的看家, 其中3个也包括在 MSC miRNA 比率 (miR-15b、miR-19b 和 miR-197) 中。然而, 血浆中的 MSC 和血清标本中的和平试验更深刻地证实了 miRNA-based 液活检在肺癌诊断中的应用。
在痰标本46上也对肺癌生物标志物的鉴定进行了 rna 分析。痰可以很容易地收集和 miRNA 表达水平似乎是非常稳定的。然而, 肺癌筛查志愿者年龄超过50-55 岁, 是重疾病的吸烟者, 如 COPD, 从而使痰难以获得。事实上, 在不同的体液中, 血浆是研究 rna (但不限于) 肺癌生物标志物的潜在作用的最佳选择之一。
总的来说, 本文件所述的程序可与各种疾病有关, 对所调查的病理类型没有限制 (从癌症、神经系统和心血管疾病或糖尿病), 并在临床应用 (诊断, 预后, 甚至治疗反应的生物标志物)。

肺癌是全世界最常见的癌症诊断, 占所有癌症诊断的25% 左右 (约为1。尽管过去2年来肺癌死亡率稳步下降, 主要是由于烟草使用减少, 但肺癌仍然是男性和女性癌症死亡的主要原因。在 2017年, 预计将占美国和欧洲癌症死亡总数的大约25% 和 20%, 分别为1,2。
由于症状通常不发生在早期的疾病, 大多数肺癌诊断在后期阶段。这导致有限的可能性为治疗干预和治疗的可怜的疗效3。因此, 许多科学努力的目的是确定一个有效的测试, 早期肺癌检测。
各种筛选试验表明, 胸部造影在肺癌筛查中没有价值, 而低剂量的计算机断层扫描 (闭塞) 是一种较好的工具, 与检测早期肺癌的 x 线造影相比4。此外, 它已显示 thatscreening 与使用闭塞降低肺癌死亡率高达 20%, 在当前和前重吸烟者5。这些数据支持在指南中定义的高危人群中使用肺癌筛查4,6。
值得注意的是, 在闭塞筛查的主要关注点中, 假阳性结果和 over-diagnosis 率都很高。因此, 科学界正在寻求克服这些问题的战略, 并提高闭塞筛选试验的特殊性。无创互补生物标记物的开发在这里是有用的。到目前为止, 有一个广泛的候选生物标志物的调查, 如 rna, 无细胞 DNA, 基因甲基化, 小蛋白质, 和其他7。
为生物标志物, 包括免疫反应生物标记和循环 rna, 是那些达到更高级的验证阶段8。免疫反应的生物标志物的基础上的知识, 免疫反应的细胞内和表面肿瘤抗原是建立在肺癌患者9。例如, Ajona et al.评估的作用 C4d, 退化产品的经典补充通路, 在诊断和预后的肺癌10。另外, 在非小细胞肺癌患者中, 一项商业上可用的自身抗体检测七例肿瘤相关抗原进行了验证, 并显示36% 的敏感性和91% 的特异性11。免疫反应生物标志物是有趣的, 但进一步的验证研究是需要的潜在临床应用。
rna 是一种内源性小编码 rna, 具有保存机制和大的功能意义, 遍布动物和植物王国。rna 的作用是调节蛋白质的翻译: 它们抑制了一大组靶基因的表达12。它已被充分证明, 改变 ofmiRNAs 的表达有助于大多数人类癌症的发病12,13,14。此外, 肿瘤和基质细胞释放 rna, 稳定通过其纳入微或通过协会的 RNA 结合蛋白, 进入体液, 如血浆和血清15,16, 尿17和唾液18。循环 rna 可以反映宿主反应和肿瘤及其微环境之间的动态相互作用19。这些观察结果使循环 rna 成为人类癌症检测的一种有前途的生物标志物。
循环 rna 可以通过使用不同的方法检测: 微阵列平台20, 定量逆转录 PCR (RT-qPCR)21, 和下一代测序 (NGS)14,22。基于上述技术的各种表达谱研究已经在过去的几年中得到了发展。微阵列是一种高通量的技术, 能够分析多达数以千计的 rna 在一个单一的化验。但与 RT qPCR 或 NGS 相比, 其动态范围和特异性都较低。此外, 微阵列是一种定量的方法, 因此需要进一步的实验验证。序列方法可以识别未知的 rna, 尤其适用于发现阶段。另一方面, NGS 方法仍然昂贵, 需要特殊设备和专家学, 因此限制了它们在大型验证队列和临床设置23中的使用。目前, RT qPCR 是在诊断/临床上下文24中用于循环 miRNA 检测的最采用的平台。有不同的 rt qPCR 技术可用于 rna 分析, 但茎环 rt, 其次是 TaqMan PCR 是最广泛使用的25。该技术具有极高的灵敏度和准确性 (单核苷酸鉴别), 具有较高的动态范围;但是, 它只允许检测已知的 rna。
rna 质量控制研究 (miRQC 研究) 由 Mestdagh et al.广泛调查了一些商业可利用的平台的特点, rna 分析基于三上述技术26。通过对 196 rna 在组织和血清样本中的分析, 对不同平台的性能进行了评估, 从重现性、灵敏度、准确性、特异性和差异表达的一致性等方面进行了评价。研究结果表明, 基于 NGS 和微阵列技术的平台具有较高的重现性和特异性, 但 RT qPCR 平台更准确、更灵敏, 检测率更高, 特别是对于低输入 RNA 样本, 如身体流体.因此, qPCR 似乎是最合适的方法, 在常规临床诊断的潜在应用。
在 2011年, Sozzi et al.分析了从参加第一闭塞 screeningtrial (INT IEO 试验)27和四 miRNA 签名组成的志愿者收集的血浆样本的 miRNA 分布情况, 其中24循环 rna 的对等比率生成。这些签名能够在闭塞疾病检测28之前, 对患有任何或致命性肺癌的患者的疾病自由个体进行鉴别。在另一篇论文中, 同一组第一次描述了 miRNA 签名分类器 (MSC), 通过结合四 miRNA 签名获得的分层患者的三级风险: 高、中级和低。它的临床效用是验证了在一个大型回顾组超过1000人参加了轻度筛选试验, 一项随机研究比较每年或两年一次的闭塞武器与观察臂29。事实上, msc 和闭塞的结合将闭塞假阳性率降低了大约5倍, 三 msc 风险组与整体生存相关。
后来, 在2013年在 "基金会 IRCCS 依国家工会 Tumori" (米兰, 它) 一个前瞻性的筛选试验 (BioMILD) 实施闭塞与等离子基础 MSC 测试启动。参加 BioMILD 试验的志愿者接受闭塞和血液提取, 立即处理, 用特制的微流控卡对 miRNA 进行分离。闭塞和 MSC 结果的组合定义了特定的筛选算法24。
在目前的工作中, BioMILD 试验中使用的整个方法学协议, 从血样采集, 到血浆分离, RNA 提取, 以及使用定制的 RT qPCR 微流控芯片的 24 rna 表达谱进行描述。由于高度的一致性和重现性, 这些程序也可用于发展 miRNA-based 液体活检在其他疾病。

<table style="border-collapse:collapse;width:570pt" width="760">
	<colgroup>
		<col style="width:162pt" width="216" />
		<col style="width:122pt" width="162" />
		<col style="width:89pt" width="119" />
		<col style="width:197pt" width="263" />
	</colgroup>
	<tbody>
		<tr height="21" style="height:15.75pt">
			<td class="xl25" height="21" style="width:162pt;height:15.75pt" width="216">&#160;1x PBS&#160;</td>
			<td class="xl26" style="width:122pt" width="162">Lonza</td>
			<td class="xl26" style="width:89pt" width="119">BE-17-516</td>
			<td class="xl23" style="width:197pt" width="263"></td>
		</tr>
		<tr height="63" style="height:47.25pt">
			<td class="xl21" height="63" style="width:162pt;height:47.25pt" width="216">20xTE Buffer, pH 8.0</td>
			<td class="xl26" style="width:122pt" width="162">Molecular probe</td>
			<td class="xl26" style="width:89pt" width="119">T11493</td>
			<td class="xl22" style="width:197pt" width="263">Dilute the 20X stock solution to have the final concentration of&#160; 0,1X in Nuclease-free water</td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">Nuclease-free water&#160;</td>
			<td class="xl26" style="width:122pt" width="162"></td>
			<td class="xl26" style="width:89pt" width="119"></td>
			<td class="xl23"></td>
		</tr>
		<tr height="126" style="height:94.5pt">
			<td class="xl21" height="126" style="width:162pt;height:94.5pt" width="216">Maxwell RSC miRNA Tissue Kit&#160;</td>
			<td class="xl26" style="width:122pt" width="162">Promega</td>
			<td class="xl26" style="width:89pt" width="119">AS1460</td>
			<td class="xl21" style="width:197pt" width="263">The kit contains Homogenization Solution, DNase I, Proteinase K, Lysis Buffer and cartridges. For 1-Thioglycerol, inhalation and contact with skin and eyes should be avoided. Use it under a Fume Cabinet.</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">TaqMan MicroRNA Reverse Transcription Kit&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl26" style="width:89pt" width="119">4366596</td>
			<td class="xl23"></td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">Custom TaqMan RT Primer Pool&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl26" style="width:89pt" width="119">4459649</td>
			<td class="xl23"></td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">TaqMan PreAmp Master Mix 2X&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl26" style="width:89pt" width="119">4391128</td>
			<td class="xl23"></td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">Custom TaqMan&#160; PreAmp pool&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl26" style="width:89pt" width="119">4459657</td>
			<td class="xl23"></td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">TaqMan Universal Master Mix II, No UNG 2x&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl26" style="width:89pt" width="119">4440048</td>
			<td class="xl23"></td>
		</tr>
		<tr height="63" style="height:47.25pt">
			<td class="xl21" height="63" style="width:162pt;height:47.25pt" width="216">Custom TaqMan Array MicroRNA Cards&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl26" style="width:89pt" width="119">4449137</td>
			<td class="xl22" style="width:197pt" width="263">Bring the Custom TaqMan Array MicroRNA Cards to room temperature before to load samples</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">Vacutainer Safety-Lock Blood Collection Set&#160;</td>
			<td class="xl26" style="width:122pt" width="162">Becton Dickinson</td>
			<td class="xl26" style="width:89pt" width="119">367286-364815</td>
			<td class="xl23"></td>
		</tr>
		<tr height="46" style="height:34.5pt">
			<td class="xl21" height="46" style="width:162pt;height:34.5pt" width="216">Vacutainer plastic spray-coated K2EDTA tube.&#160;</td>
			<td class="xl26" style="width:122pt" width="162">Becton Dickinson</td>
			<td class="xl26" style="width:89pt" width="119">366643</td>
			<td class="xl23">Lavender BD Hemogard closure&#160;</td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">Cuvette PS semi-micro&#160;</td>
			<td class="xl22" style="width:122pt" width="162">VWR/PBI</td>
			<td class="xl22" style="width:89pt" width="119">&#160;643-0326</td>
			<td class="xl23">Light path 10 mm</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">NanoDrop 2000c UV-VIS Spectrophotometer</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl22" style="width:89pt" width="119"></td>
			<td class="xl23"></td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">Cryogenic vials 1.5 ml&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Sigma-Aldrich</td>
			<td class="xl22" style="width:89pt" width="119">Z359033</td>
			<td class="xl23"></td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">Centrifuge 5810R&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Eppendorf</td>
			<td class="xl22" style="width:89pt" width="119"></td>
			<td class="xl24" style="width:197pt" width="263">Bring the centrifuge to 4 &#176;C before starting plasma collection</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">Heraeus Multifuge 3S+ Centrifuge</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl22" style="width:89pt" width="119">D-37520</td>
			<td class="xl23"></td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">Vortex Mixer</td>
			<td class="xl22" style="width:122pt" width="162">Velp Scientifica</td>
			<td class="xl22" style="width:89pt" width="119">F202A0173</td>
			<td class="xl23"></td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">ThermoMixer T- shaker</td>
			<td class="xl23">Euroclone&#160;</td>
			<td class="xl23">A00564</td>
			<td class="xl28" style="width:197pt" width="263">Bring the Thermo Mixer to 37 &#176;C before starting RNA&#160; extraction</td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">Maxwell RSC Instrument</td>
			<td class="xl22" style="width:122pt" width="162">Promega</td>
			<td class="xl22" style="width:89pt" width="119">AS4500</td>
			<td class="xl23"></td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl21" height="42" style="width:162pt;height:31.5pt" width="216">GeneAmp PCR System 9700 thermo-cycler&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl22" style="width:89pt" width="119"></td>
			<td class="xl23"></td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">ViiA 7 Real-Time PCR System&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl22" style="width:89pt" width="119"></td>
			<td class="xl23"></td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">ViiA 7 RUO software&#160;</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl22" style="width:89pt" width="119"></td>
			<td class="xl23"></td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl21" height="21" style="width:162pt;height:15.75pt" width="216">Arrey Card Staker/Sealer</td>
			<td class="xl22" style="width:122pt" width="162">Thermo Fisher</td>
			<td class="xl26" style="width:89pt" width="119">4331770</td>
			<td class="xl23"></td>
		</tr>
	</tbody>
</table>

microrna based liquid biopsy: the experience of the plasma mirna signature classifier (msc) for lung cancer screening

发展的微创试验, 如液体活检, 在早期肺癌的临床前阶段检测是至关重要的, 以改善这一致命疾病的结果。rna (rna) 是组织特异性, 小, 编码 rna 调节基因表达, 这可能作为生物信号的细胞外信使从相声之间的肿瘤及其周围的微环境。因此, 他们可以代表早期发现肺癌的理想候选者。在这项工作中, 提出了一个方法工作流程的前瞻性验证的循环 miRNA 测试使用定制的微流控卡和定量实时 PCR 在血浆样本的志愿者参加了肺癌筛选试验。此外, 由于与溶血相关的 rna 的释放和更一般的技术问题可能影响分析, 也提出了标准操作程序中包括的质量控制步骤。该协议是可重现的, 并提供可靠的定量结果;然而, 在使用大型临床系列时, 应慎重评估分析和分析特征。

BioMILD 试验是一个前瞻性的研究, 早期发现肺癌的目的是测试的效率, 联合闭塞理学硕士的方法, 作为一线筛选试验的大量吸烟者的人群。在 miRNA 测试的基础上, 每位志愿者都有一个风险等级, 评估24血浆循环 rna 的比值。由于主要报告的30,31,32, 溶血是分析循环 miRNA 的一个关键问题, 因为由于血液细胞的非特异性释放 rna, 可能会得到假结果。在建议的方法工作流中, 描述了一个分析质量控制步骤 (QC1 在表 1中) 来识别溶血, 从而 non-analyzable 了等离子体样本。图 1报告了分光光度分析的溶血 (图 1a) 和 non-hemolyzed (图 1B) 等离子体样本, 其各自的 A414/A375 值。在临床上, 分子测试的结果是志愿者管理的关键, 这种 QC1 允许重复血液取样, 在大多数情况下, 恢复样本。
在分子处理后, 应准确评估 RT qPCR 的性能, 以确定任何技术问题。图 2a显示由于被动参考信号较差而导致性能低下的 RT qPCR。在这种情况下, 建议重新加载放大产品到新的微流控卡。当 RT qPCR 执行良好时, 如图 2B中所示, 该卡继续进行第一个 post 分析质量控制步骤, 以确保 miRNA 表达式值与历史测量 (QC2 在表 1中) 相媲美。如果 QC2 步骤失败, 在反转转录或放大反应中可能会出现技术问题, 而且从反向转录开始, 重复整个分子处理是很方便的。
最后一个质量控制步骤 (QC3 在表 1中) 也在分子水平上评估溶血。将4个红细胞特异性 rna (mir-16、mir-451、mir-486-5p 和 mir-92a) 的表达水平与 4 non-hemolysis 相关 rna (mir-126、mir-15b、mir-221 和 mir-30b) 进行比较, 生成与溶血相关的 miRNA 签名, 由16 (4 x 4) miRNA 比。阳性样本被归类为溶血, 而负样本则按照协议9节和图 3中的描述进行最终的 MSC 风险级别分类。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56326/56326fig1.jpg"> 
图 1:分光光度法测定新鲜血浆样品.分光光度剖面 (A) 2 溶血和 (B) 2 non-hemolyzed 等离子体样品, 测量波长 A414 和 A375 之间的吸收率。<a href="//ecsource.jove.com/files/ftp_upload/56326/56326fig1large.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/56326/56326fig2.jpg"> 
图 2: RT-qPCR 在微流控卡分析中的性能.放大和多组分的地块比较 (A) 差和 (B) 优质微流控卡。所有 24 rna 和一个单一的例证 miRNA 在每个小组报告。多分量图说明了在这些 RT-qPCR 反应中发生的被动参考信号。<a href="//ecsource.jove.com/files/ftp_upload/56326/56326fig2large.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/56326/56326fig3.jpg"> 
图 3:风险分层的 MSC 算法.有代表性的结果, 考虑到6血浆样本志愿者参加 BioMILD 筛选试验。(A) miRNA 比率 "疾病风险 (RD) 的签名、侵袭性疾病的风险 (RAD)、疾病存在 (PD)、侵袭性疾病 (PAD) 的存在以及对应的截止值 (log2), 用于存储在-80 ° c 处的等离子体样品至少1周, 最多5周。(B) 将四签名与高 (H)、中级 (I) 和低 (L) 级 MSC 风险级别的分层分析样本组合在一起。<a href="//ecsource.jove.com/files/ftp_upload/56326/56326fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>

Watch this Scientific Journal Video about MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening at JoVE.com

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening

在这里, 我们提出了在 BioMILD 筛选试验中采用的详细的协议, 以执行循环 rna 签名分类器测试早期肺癌的检测。

基于 rna 的液体活检: 血浆 miRNA 特征分类器 (MSC) 在肺癌筛查中的经验

The development of a minimally invasive test, such as liquid biopsy, for early lung cancer detection in its preclinical phase is crucial to improve the ...

microrna-based-liquid-biopsy-experience-plasma-mirna-signature

Research

JoVE Journal

Cancer Research

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening

15.5K 次观看.  Fondazione IRCCS Istituto Nazionale dei Tumori. 在这里, 我们提出了在 BioMILD 筛选试验中采用的详细的协议, 以执行循环 rna 签名分类器测试早期肺癌的检测。

视频: MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening

Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery of the next generation of novel drug targets. It is becoming apparent that more complex models of cancer are required to fully appreciate the contributing factors that drive tumorigenesis in vivo and increase the efficacy of novel therapies that make the transition from pre-clinical models to clinical trials.
Here we present a methodology for generating uniform and reproducible tumor spheroids that can be subjected to siRNA functional screening. These spheroids display many characteristics that are found in solid tumors that are not present in traditional two-dimension culture. We show that several commonly used breast cancer cell lines are amenable to this protocol. Furthermore, we provide proof-of-principle data utilizing the breast cancer cell line BT474, confirming their dependency on amplification of the epidermal growth factor receptor HER2 and mutation of phosphatidylinositol-4,5-biphosphate 3-kinase (PIK3CA) when grown as tumor spheroids. Finally, we are able to further investigate and confirm the spatial impact of these dependencies using immunohistochemistry.

Identifying novel drug targets that transition from pre-clinical testing to human trials is a scientific priority. To that end, here we describe a functional genomics approach for examining the impact of gene depletion on cancer cell line spheroids, which more appropriately model human cancers in vivo.

利用功能基因组筛选识别在肿瘤细胞球体培养潜在的新药物靶标

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery ...

科研

癌症研究

Flow Cytometry-based Drug Screening System for the Identification of Small Molecules That Promote Cellular Differentiation of Glioblastoma Stem Cells

Glioblastoma (GBM) is the most common and most lethal primary brain tumor in adults, causing roughly 14,000 deaths each year in the U.S. alone. Median survival following diagnosis is less than 15 months with maximal surgical resection, radiation, and temozolomide chemotherapy. The challenges inherent in developing more effective GBM treatments have become increasingly clear, and include its unyielding invasiveness, its resistance to standard treatments, its genetic complexity and molecular adaptability, and subpopulations of GBM cells with phenotypic similarities to normal stem cells, herein referred to as glioblastoma stem cells (GSCs). Because GSCs are required for tumor growth and progression, differentiation-based therapy represents a viable treatment modality for these incurable neoplasms. 
The following protocol describes a collection of procedures to establish a high throughput screening platform aimed at the identification of small molecules that promote GSC astroglial differentiation. At the core of the system is a glial fibrillary acidic protein (GFAP) differentiation reporter-construct. The protocol contains the following general procedures: (1) establishing GSC differentiation reporter lines; (2) testing/validating the relevance of the reporter to GSC self-renewal/clonogenic capacity; and (3) high-capacity flow-cytometry based drug screening. 
The screening platform provides a straightforward and inexpensive approach to identify small molecules that promote GSCs differentiation. Furthermore, utilization of libraries of FDA-approved drugs holds the potential for the identification of agents that can be repurposed more rapidly. Also, therapies that promote cancer stem cell differentiation are expected to work synergistically with current "standard of care" therapies that have been shown to target and eliminate primarily more differentiated cancer cells.

An efficient screening protocol is presented for the identification of small molecules that promote astroglial differentiation in glioblastoma stem cells (GSCs). The assay is based on a stem cell differentiation reporter whereby the expression of the enhanced GFP (eGFP) is driven by the human GFAP promoter.

流动 Cytometry-based 药物筛选系统对促进细胞分化胶质母细胞瘤小分子的鉴定

Glioblastoma (GBM) is the most common and most lethal primary brain tumor in adults, causing roughly 14,000 deaths each year in the U.S. alone. Median ...

Practical Considerations in Studying Metastatic Lung Colonization in Osteosarcoma Using the Pulmonary Metastasis Assay

The pulmonary metastasis assay (PuMA) is an ex vivo lung explant and closed cell culture system that permits researchers to study the biology of lung colonization in osteosarcoma (OS) by fluorescence microscopy. This article provides a detailed description of the protocol, and discusses examples of obtaining image data on metastatic growth using widefield or confocal fluorescence microscopy platforms. The flexibility of the PuMA model permits researchers to study not only the growth of OS cells in the lung microenvironment, but also to assess the effects of anti-metastatic therapeutics over time. Confocal microscopy allows for unprecedented, high-resolution imaging of OS cell interactions with the lung parenchyma. Moreover, when the PuMA model is combined with fluorescent dyes or fluorescent protein genetic reporters, researchers can study the lung microenvironment, cellular and subcellular structures, gene function, and promoter activity in metastatic OS cells. The PuMA model provides a new tool for osteosarcoma researchers to discover new metastasis biology and assess the activity of novel anti-metastatic, targeted therapies.

The goal of this article is to provide a detailed description of the protocol for the pulmonary metastasis assay (PuMA). This model permits researchers to study metastatic osteosarcoma (OS) cell growth in lung tissue using a widefield fluorescence or confocal laser-scanning microscope.

应用肺转移法研究骨肉瘤转移性肺定植的实用思考

The pulmonary metastasis assay (PuMA) is an ex vivo lung explant and closed cell culture system that permits researchers to study the biology of lung ...

The Establishment of a Lung Colonization Assay for Circulating Tumor Cell Visualization in Lung Tissues

Metastasis is the major cause of cancer death. The role of circulating tumor cells (CTCs) in promoting cancer metastasis, in which lung colonization by CTCs critically contributes to early lung metastatic processes, has been vigorously investigated. As such, animal models are the only approach that captures the full systemic process of metastasis. Given that problems occur in previous experimental designs for examining the contributions of CTCs to blood vessel extravasation, we established an in vivo lung colonization assay in which a long-term-fluorescence cell-tracer, carboxyfluorescein succinimidyl ester (CFSE), was used to label suspended tumor cells and lung perfusion was performed to clear non-specifically trapped CTCs prior to lung removal, confocal imaging, and quantification. Polymeric fibronectin (polyFN) assembled on CTC surfaces has been found to mediate lung colonization in the final establishment of metastatic tumor tissues. Here, to specifically test the requirement of polyFN assembly on CTCs for lung colonization and extravasation, we performed short term lung colonization assays in which suspended Lewis lung carcinoma cells (LLCs) stably expressing FN-shRNA (shFN) or scramble-shRNA (shScr) and pre-labeled with 20 &#956;M of CFSE were intravenously inoculated into C57BL/6 mice. We successfully demonstrated that the abilities of shFN LLC cells to colonize the mouse lungs were significantly diminished in comparison to shScr LLC cells. Therefore, this short-term methodology may be widely applied to specifically demonstrate the ability of CTCs within the circulation to colonize the lungs.

An animal model is needed to decipher the role of circulating tumor cells (CTCs) in promoting lung colonization during cancer metastasis. Here, we established and successfully performed an in vivo assay to specifically test the requirement of polymeric fibronectin (polyFN) assembly on CTCs for lung colonization.

肺定植法在肺部组织循环肿瘤细胞可视化中的建立

Metastasis is the major cause of cancer death. The role of circulating tumor cells (CTCs) in promoting cancer metastasis, in which lung colonization by ...

Elastic Staining on Paraffin-embedded Slides of pT3N0M0 Gastric Cancer Tissue

The elastic lamina, which is usually located in the sub-mesothelial layer, adjacent to the peritoneum mesothelial cells, is amphiphilic on hematoxylin and eosin (H&amp;E) staining but can be visualized through elastic staining. One of the important benefits of elastic staining is that it makes it easy to determine whether tumor cells have invaded beyond the elastic lamina. This helps in examining the extent of peritoneal surface invasion, thereby distinguishing the pT3 and pT4 stages in gastrointestinal cancer. In this study, we present a protocol to identify elastic fibers in the formalin-fixed, paraffin-embedded pT3N0M0 gastric cancer tissue sections. We prepare 5-&#181;m paraffin sections fixed on slides, and then all the slides are deparaffinated and rehydrated during the staining procedure. Subsequently, all the sections are oxidized by potassium permanganate, bleached by oxalic acid, stained by elastic staining, and counterstained by Van Gieson's. Finally, we examine the effect of staining; elastic lamina is stained blue-black and collagen fibers are stained red, while the cancer cells are stained in varying shades of yellow. We also describe in detail the methods used for determining the positional relationship between cancer cells and elastic lamina. This method is simple, low-cost, and widely applicable in the identification of peritoneal surface invasion in gastrointestinal cancer because of its outstanding selectivity for elastic fibers and authentic results.

Here, we present a protocol of elastic staining to identify elastic fibers in pT3N0M0 gastric cancer tissues on formalin-fixed, paraffin-embedded sections. Subsequently, we describe a method to determine whether tumor cells invade beyond the elastic lamina.

pT3N0M0 胃癌组织石蜡嵌入幻灯片上的弹性染色

The elastic lamina, which is usually located in the sub-mesothelial layer, adjacent to the peritoneum mesothelial cells, is amphiphilic on hematoxylin and ...

Using Human Induced Pluripotent Stem Cells for the Generation of Tumor Antigen-specific T Cells

The generation and expansion of functional T cells in vitro can lead to a broad range of clinical applications. One such use is for the treatment of patients with advanced cancer. Adoptive T cell transfer (ACT) of highly enriched tumor antigen-specific T cells has been shown to cause durable regression of metastatic cancer in some patients. However, during expansion, these cells may become exhausted or senescent, limiting their effector function and persistence in vivo. Induced pluripotent stem cell (iPSC) technology may overcome these obstacles by leading to in vitro generation of large numbers of less differentiated tumor antigen-specific T cells. Human iPSC (hiPSC) have the capacity to differentiate into any type of somatic cell, including lymphocytes, which retain the original T cell receptor (TCR) genomic rearrangement when a T cell is used as a starting cell. Therefore, reprogramming of human tumor antigen-specific T cells to hiPSC followed by redifferentiation to T cell lineage has the potential to produce rejuvenated tumor antigen-specific T cells. Described here is a method for generating tumor antigen-specific CD8&#945;&#946;+ single positive (SP) T cells from hiPSC using OP9/DLL1 co-culture system. This method is a powerful tool for in vitro T cell lineage generation and will facilitate the development of in vitro derived T cells for use in regenerative medicine and cell-based therapies.

This article describes a method to generate functional tumor antigen-specific induced pluripotent stem cell-derived CD8&#945;&#946;+ single positive T cells using OP9/DLL1 co-culture system.

利用人类诱导多能干细胞生成肿瘤抗原特异性T细胞

The generation and expansion of functional T cells in vitro can lead to a broad range of clinical applications. One such use is for the treatment of ...

Perfusion and Inflation of the Mouse Lung for Tumor Histology

The ability to evaluate lung histology is critical for the fields of lung cancer research and cancer metastasis. It is equally important to perform necropsies rapidly and efficiently from studies without sacrificing the quality of the tissues procured. The goal of this protocol is to present a method to rapidly perfuse, inflate, and fix mouse lungs for downstream histological analysis. This method does not standardize lung inflation; thus, it does not require any special procedures or equipment and instead simply instills fixative directly through the trachea following perfusion through the heart. This allows for sufficient estimation of tumor size, histology, and scoring. This also allows for the collection of frozen tissue prior to lung tissue fixation. This method is limited in that it does not allow for later morphometric quantification of the lung; however, it is more than sufficient for lung tumor analysis from genetically engineered mouse models (GEMMs), syngeneic models, as well as xenograft tumor and metastasis studies.

The purpose of this method is to present a simple and efficient method for the perfusion, inflation, and fixation of mouse lungs for the examination of lung tumor pathology and evaluation of metastases to the lung.

肿瘤病理学鼠肺的灌注和膨胀

The ability to evaluate lung histology is critical for the fields of lung cancer research and cancer metastasis. It is equally important to perform ...

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 ...

Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging

Metastatic spread of cancer is an unfortunate consequence of disease progression, aggressive cancer subtypes, and/or late diagnosis. Brain metastases are particularly devastating, difficult to treat, and confer a poor prognosis. While the precise incidence of brain metastases in the United States remains hard to estimate, it is likely to increase as extracranial therapies continue to become more efficacious in treating cancer. Thus, it is necessary to identify and develop novel therapeutic approaches to treat metastasis at this site. To this end, intracranial injection of cancer cells has become a well-established method in which to model brain metastasis. Previously, the inability to directly measure tumor growth has been a technical hindrance to this model; however, increasing availability and quality of small animal imaging modalities, such as magnetic resonance imaging (MRI), are vastly improving the ability to monitor tumor growth over time and infer changes within the brain during the experimental period. Herein, intracranial injection of murine mammary tumor cells into immunocompetent mice followed by MRI is demonstrated. The presented injection approach utilizes isoflurane anesthesia and a stereotactic setup with a digitally controlled, automated drill and needle injection to enhance precision, and reduce technical error. MRI is measured over time using a 9.4 Tesla instrument in The Ohio State University James Comprehensive Cancer Center Small Animal Imaging Shared Resource. Tumor volume measurements are demonstrated at each time point through use of ImageJ. Overall, this intracranial injection approach allows for precise injection, day-to-day monitoring, and accurate tumor volume measurements, which combined greatly enhance the utility of this model system to test novel hypotheses on the drivers of brain metastases.

Intracranial brain metastasis modeling is complicated by an inability to monitor tumor size and response to treatment with precise and timely methods. The presented methodology couples intracranial tumor injection with magnetic resonance imaging analysis, which when combined, cultivates precise and consistent injections, enhanced animal monitoring, and accurate tumor volume measurements.

通过颅内注射和磁共振成像对大脑转移进行建模

Metastatic spread of cancer is an unfortunate consequence of disease progression, aggressive cancer subtypes, and/or late diagnosis. Brain metastases are ...

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

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

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

癌症患者血浆样本中无细胞DNA检测

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