CN102308003A - 前列腺癌甲基化分析法 - Google Patents

前列腺癌甲基化分析法 Download PDF

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CN102308003A
CN102308003A CN2009801316329A CN200980131632A CN102308003A CN 102308003 A CN102308003 A CN 102308003A CN 2009801316329 A CN2009801316329 A CN 2009801316329A CN 200980131632 A CN200980131632 A CN 200980131632A CN 102308003 A CN102308003 A CN 102308003A
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J·F·巴登
G·A·格林
J·帕恩特
S·W·曹
Y·王
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Abstract

本发明公开了一种用于对前列腺癌进行诊断或预后的分析法,所述方法整合了对GSTP、APC和RARβ2基因的超甲基化的检测并且可整合进诺模图法中。

Description

前列腺癌甲基化分析法
背景技术
本专利申请要求于2008年8月5日提交的美国临时申请No.61/086,218的权益。
血清前列腺特异性抗原(PSA)目前是前列腺癌筛选的监护标准。PSA检测特异性低下已显示可导致患者不必要的活检数量大并通常使可筛选的PSA范围局限于>4ng/mL的患者。
新分析法利用甲基化特异性PCR(MSP)来测定三种可指示前列腺癌存在的标志物(GSTP1、RARβ2和APC)的启动子区内的CpG岛甲基化(表观遗传修饰)。该分析法已经用在9个临床点采集的337份DRE后尿液样品(187份癌症及非典型样品/150份非癌症样品)进行了评价。患者年龄范围为40-75岁,并且PSA水平为2至10ng/mL。通过对活检组织进行组织学测定,在前列腺癌检测中观察到所述分析法的灵敏度为52%,特异性为81%。通过logistic回归算法,对该分析法得出曲线下面积(AUC)值为0.67。与单独的诺模图法(nomogram)或PCPT风险计算器比较,当将该分析法与诺模图法或PCPT风险计算器结合使用时,导致AUC增加(0.69和0.72)以及表现出统计显著性(p=0.008和0.043)。当一种(48%)、两种(60%)或三种(71%)标志物在同一受试者中为阳性时,该分析法的阳性预测值增加。当根据优化的分析方法制备一亚组180份DRE后尿液样品(103份癌症及非典型样品/非癌症样品77份)时,观察到灵敏度为60%,特异性为81%(AUC 0.72)。
发明内容
本发明涉及用于检测与前列腺癌相关的基因的超甲基化的分析法,包括用于检测GSTP1、APC、RARβ2或它们的组合的存在的试剂。
在本发明的另一个方面,所述试剂包括选自表1所列引物、探针和蝎型(scorpion)试剂的引物、探针或蝎型试剂。
在本发明的另一个方面,所述分析法与诺模图法结合使用,用于确定疑似前列腺癌患者的诊断或预后。
具体实施方式
包括对GSTP、APC和RARβ2标志物进行检测的超甲基化分析法在(例如)美国专利公开20080254455中进行了描述,藉此将该专利公开以引用的方式并入本文。这些分析法现已得到改善并可与其他诊断和风险因素指标结合使用。
在对由337名先前没有前列腺癌病史的明显健康的男性构成的群体的研究中,从9个不同的泌尿科临床点获得尿液样品。在规定的DRE后收集尿液样品(最多40mL),该DRE包括将前列腺表面按下0.5至1.0cm,并从基部向顶部以及从侧边向中线移动,每叶进行最少三次。将尿液收集容器的内容物转移进装有800μL 0.5M EDTA的50mL运输管中。收集后该输送管在2-8℃下最多保存三天并用标准的冰袋在晚上运输。
收到后,将运输管立即在4℃下以3000g离心10分钟,或分成等份然后在4℃下以3000g离心10分钟。将尿液样品分份既有助于样品制备优化又有助于整体性能的估计。弃去上清液并用冷PBS洗涤所得的沉淀颗粒。根据试剂盒包装所带说明书,用Gentra Puregene试剂盒(Qiagen,Germany)提取DNA并用Epitect试剂盒(Qiagen,Germany)修饰。将所有的样品以25μL体积洗脱。SmartCycler(Cepheid,Sunnyvale,CA)上用前列腺癌甲基化分析法对5μL修饰过的DNA进行分析。
选择三种甲基化标志物(GSTP1、RARB和APC)和内部对照β-肌动蛋白的引物和蝎型探针(Biosearch Technologies,Novato,CA)用于分两步的多重MSA分析法。第一步为扩增,由添加至SmartCap管(Cepheid,Sunnyvale,CA)的5μL扩增混合物、5μl酶混合物和5μL样品组成。所述酶混合物配制用于扩增步骤和检测步骤两者,并由8mM Tris-HCl pH 8.0、5mM KCl、0.005%BSA、0.6U/μL FastStart Taq DNA聚合酶和0.016%ProClin
Figure BPA00001310617200021
300组成。
扩增步骤循环如下:95℃5分钟,然后进行18个如下循环:95℃20秒、55℃30秒、70℃30秒,以及70℃5分钟。扩增混合物含有8种引物(对GSTP1、RARB、APC每种引物浓度为20nM,对于β-肌动蛋白引物浓度为16nM)、75mM D-海藻糖二水合物、0.1%Tween
Figure BPA00001310617200031
20溶液10%、25mM Tris-HCl pH 8.01M、1.75mM MgCl2溶液、1%DMSO、0.155mMdNTP混合物、0.016%ProClin
Figure BPA00001310617200032
300。
一旦扩增步骤完成,则从装置中移出SmartCap管。第二个步骤为检测步骤,由添加至SmartCap管的5μL检测混合物和5μl酶混合物组成。该分析循环如下:95℃5分钟,然后进行40个如下循环:95℃20秒,55℃30秒。完全如针对上述扩增混合物描述配制检测混合物,不同之处如下:4种引物,对于GSTP1、RARB、APC和β-肌动蛋白引物浓度各为200nM,4种蝎型探针,对于GSTP1、RARB、APC和β-肌动蛋白探针浓度各为200nM,以此代替8种引物。在每个循环,利用阴性(β-肌动蛋白)和阳性(GSTP1、APC、RARβ2)合成外部对照来确定分析法的有效性。
分类分析是基于研究人群中患者的已知活检结果。循环阈(Ct)值用于产生GSPT1、RARβ2和APC标志物的独立分析截断值。为了确定可引起DNA量不足的无结果试验比(No Test Rate,NTR),采用了β-肌动蛋白的Ct值截断值。如果所述3种甲基化标志物的组中有一种Ct值低于所确定的截断值,则该样品被视为甲基化阳性。Ct值高于所确定的样品则评为甲基化阴性。NTR根据β-肌动蛋白的Ct截断值计算。基于接收者工作特征曲线(ROC)分析计算接收者工作曲线下面积(AUC)值。采用MedCalc(MedCalcSoftware,Belgium)得出单标志物和多标志物分析的AUC值。对多标志物分析用MedCalc产生Logistic回归模型。
对该分析法评价其甄别前列腺癌患者和活检为阴性的患者的能力。活检阴性和阳性的男性中GSTP1、RARβ2和APC Ct值显著不同(分别是p=0.009、0.000和0.039)并表现出正ROC曲线。组合3种标志物,对于前列腺癌的检测,通过对活检组织的组织学结果确定,该分析法表现出52%的灵敏度和81%的特异性(正确检测出84例癌症和104例非癌症)。该分析法中的许多假阳性具有异常的DRE和/或为阳性的多种标志物。对假阳性的其中一种可能解释是在前列腺活检时的采样错误,或存在甲基化的但非癌性的前列腺细胞。采用全部3种标志物的logistic回归算法得到AUC值为0.67。通常将总血清PSA用作风险因素来确定应该进行前列腺活检的人。将PSA和所述前列腺癌甲基化分析进行比较。在该研究人群中PSA的ROC曲线分析表现的AUC为0.55,而与单独PSA比较时,该测定法表现出统计显著性(p=0.01)。更重要的是,通过单变量和多变量logistic回归模型两者,即使是在分析多风险因素时,该分析法也是前列腺癌的显著预测器(p=0.001)。
在诺模图法或预测算法中组合多种分析因素而不是单独的PSA在已公开的文献中是不断增长的趋势,用以使有效性和效率更高。示出了所述前列腺癌甲基化分析法与由PSA、DRE结果和患者年龄组成的通常使用的诺模图法和PCPT风险计算器的比较。从253名受试者获得关于PCPT风险计算器参数的信息。使用诺模图的logistic回归算法导致AUC值为0.61。有趣的是,PCPT风险计算器导致AUC为0.67。当与诺模图或PCPT风险计算器比较时,所述前列腺癌甲基化分析法在统计上不显著(分别是p=0.150和0.935)。然而,当与单独的诺模图法或PCPT计算器比较时,该分析法结合诺模图法或PCPT风险计算器改善了AUC(分别是0.69和0.72)并表现出统计显著性(分别是p=0.008和0.043)。为了进一步评估该前列腺癌症甲基化分析法,评估了来自各临床点的数据。当对ROC曲线进行独立分析时,不同临床点和所测总群体之间的差别不显著。
该分析法的预测值受GSTP1、RARβ2和APC标志物的高度特异性的影响。当根据具有1、2或3种阳性标志物对患者群组分类时,该分析法性能的阳性预测值(PPV)改善(48%-71%)。这暗示,当该分析法中存在2种或多种标志物时,患有癌症的可能性更高。
该前列腺细胞甲基化分析法的预测价值的重点在于该分析法的高度特异性。这可归因于与基于表达的分析法比较采用的MSP方法。该分析法的标志物表现出高度特异性,分别是90%、89%和95%。该分析法优于PCA3标志物的另一个优点是该3基因多重分析法使得在患者呈现多种标志物时临床医师能具有更高置信水平的独特性质。当在同一受试者中一种(48%)、两种(60%)或三种(71%)标志物是阳性的时,患病率在25%下所观察到的该分析法的PPV改善。
用于提供分析法评分的算法是基于甲基化特异性PCR(MSP)Ct值的线性组合的逻辑函数。该模型使个体具有更高的或更低的风险值,这样更容易作出判定。具体来讲,“高”分值(>60.00)将具有>3.0的似然比,“低”分值(<29.00)将具有<0.35的似然比。该评分使患者能给其医生提供关于活检阳性可能性的更多信息。
■分值=100×1/[1+exp(线性Ct组合)],
■其中“线性Ct组合”是根据试验数据形成:
■1.7887+(-0.0686×GSTP1_Ct)+(-0.03947×RARb2_Ct)+(-0.01263×APC_Ct)+(0.09862×b-actin_Ct)
测定法评分在与其他已知的风险因素组合时在预测阳性前列腺活检中将是一个在统计上显著的因素。所述风险因素将包括年龄、前列腺癌家族史、PSA水平、种族和先前的阴性前列腺活检。
当在CpGM和CpGU DNA上评价标志物时,与最初的可行性设计相比表1中的设计显示了改善的特异性。CpGM与CpGU相比Ct值差异越大,所述标志物设计的特异性更高。
表1.3种甲基化标志物(GSTP1、RARβ2和APC)和内部对照(β-肌动 蛋白)的引物和Scorpion TM 探针序列
Figure BPA00001310617200051
初始的GSTP1蝎型设计的非正常折叠物可充当taq裂解的底物,这导致较于新GSTP1设计引起背景发生稳定偏移的猝灭分子的降解。新设计改善了整体的性能。

Claims (4)

1.一种用于检测与前列腺癌相关的基因的超甲基化的试剂盒,所述试剂盒包含用于检测GSTP1、APC、RARβ2或它们的组合存在的试剂,其中所述试剂包括选自表1所列引物、探针和蝎型试剂的引物、探针或蝎型试剂。
2.一种对前列腺癌进行诊断或预后的方法,所述方法包括用试剂检测GSTP1、APC、RARβ2基因或它们的组合的超甲基化,所述试剂包括选自表1所列引物、探针和蝎型试剂的引物、探针或蝎型试剂。
3.根据权利要求2所述的方法,其中将所述超甲基化分析与前列腺癌诊断或预后的其他风险因素或指标结合使用。
4.根据权利要求3所述的方法,其中其他风险因素包括在诺模图中。
CN2009801316329A 2008-08-05 2009-08-05 前列腺癌甲基化分析法 Pending CN102308003A (zh)

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CN102308003A (zh) 前列腺癌甲基化分析法

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