CN113358872A - 用于评估肿瘤免疫治疗疗效的标志物组及系统 - Google Patents

用于评估肿瘤免疫治疗疗效的标志物组及系统 Download PDF

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CN113358872A
CN113358872A CN202110621855.6A CN202110621855A CN113358872A CN 113358872 A CN113358872 A CN 113358872A CN 202110621855 A CN202110621855 A CN 202110621855A CN 113358872 A CN113358872 A CN 113358872A
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王雪萍
刘万里
邢珊
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Sun Yat Sen University Cancer Center
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Abstract

本发明公开了用于评估肿瘤免疫治疗疗效的标志物组及系统。发明人研究发现，基于H3Cit，IL‑8和CRP这3个指标建立的评估肿瘤免疫治疗疗效的数学模型，在治疗前可以很好地评估肿瘤患者免疫治疗的疗效，为精准免疫治疗方案的确定提供新的筛选指标，提高患者的治疗效果。当cut‑off定为0.512，灵敏度为80.6%时，特异性可达92.3%，阳性预测值91.3%，阴性预测值82.6%，显著高于H3Cit(灵敏度：66.7%；特异性：84.6%；AUC：0.765)，IL‑8(灵敏度：64.5%；特异性79.3%：AUC：0.755),CRP(灵敏度：66.7%；特异性：89.7%；AUC：0.826)任何一个指标单独的诊断效能。

Description

用于评估肿瘤免疫治疗疗效的标志物组及系统
技术领域
本发明涉及医疗领域，具体涉及免疫治疗疗效评估，特别涉及用于评估免疫治疗疗效的标志物组及系统。
背景技术
免疫系统与恶性肿瘤之间存在复杂的生物调控网络。由于肿瘤细胞独特广泛的变异特点，免疫系统和肿瘤之间经常达到平衡—肿瘤耐受，免疫检查点失调成为肿瘤耐受的主要原因之一[1]。因此，免疫检查点抑制剂(Immune checkpoint inhibitor,ICI)疗法，包括抗PD-1/PD-L1和抗CTLA-4疗法，都可以增强有效T细胞的活性，抑制肿瘤微环境中的免疫抑制。ICI疗法彻底改变了晚期肿瘤的系统性治疗，包括黑素瘤、非小细胞肺癌(NSCLC)、肾癌和头颈鳞状细胞癌。与常规治疗相比，ICI治疗有更好的生存时间和预后效果[2]。到目前为止，FDA批准的用于PD-1/PD-L1的ICI有5种，包括pembrolizumab和nivolumab(抗PD-1)以及atezolizumab、durvalumab和avelumab(抗PD-L1)，大量临床试验也证实，并非所有的患者都对ICI治疗有效，仍有很大部分患者治疗后进展，并且，即使刚开始用药有效，有的患者仍在用药后进展，但发生这种情况的具体原因还不完全清楚。从总体上看肿瘤患者对抗PD-1/PD-L1治疗的有效率只20％左右。大部分的病人不能从中获益，即原发性耐药；部分有效治疗的患者在治疗一段时间后也会出现疾病进展，即继发性耐药，同时价格昂贵且治疗本身具有毒副作用[3]。因此，寻找有效的生物标志物精准筛选获益人群成为近年来免疫治疗研究领域的热点问题，也是提高免疫检查点抑制剂疗效的一种方法[4]。
目前，研究者们进行了许多针对PD-1/PD-L1抗体疗效预测标志物的深入研究，多种生物标志物已被用于预测免疫检查点抑制剂的治疗效果，主要包括以下两类：
第一，肿瘤新抗原负荷相关的分子标志。
错配修复缺陷(dMMR)/高微卫星不稳定性(MSI-H)：是存在于细胞中的高保守的DNA修复基因功能缺陷，导致细胞无法修复错配碱基，形成MSI-H。2010年5月，FDA批准Pembrolizumab用于之前治疗进展、没有其他令人满意的治疗选择的、MSI-H或dMMR的实体瘤患者[5]。一项抗PD-1抗体药物临床试验纳入41例晚期结直肠癌及其他肿瘤患者，对患者基因状态与临床疗效分析的结果表明，dMMR患者的客观缓解率(ORR)和无进展生存率分别为40％和78％，而无修复缺陷的患者为0％、11％[6]。对于肿瘤治疗而言，这是不依据肿瘤来源而根据分子标志物区分药物适应证的先例。
肿瘤突变负荷(TMB)：TMB是肿瘤细胞携带突变基因的定量评估方法。研究表明ICI治疗有效率与TMB成线性关系。TMB有望成为下一个被批准的ICI疗效预测标志物[7]。Hellmann等通过对75例接受PD-1单抗和CTLA-4单抗联合治疗的患者进行全外显子测序,多因素分析显示高TMB的患者接受联合治疗的ORR和生存率高TMB中等或较低的患者[8]。
综上所述，由于dMMR/MSI和TMB尚未进行大规模临床验证，其诊断效能还有待进一步验明确。另外无研究报道其用于PD-1/PD-L1抗体疗效预测灵敏度和特异度，仍有待进一步研究，且DNA检测技术复杂昂贵，不易于临床普遍开展。
第二，肿瘤炎症微环境相关的分子标志。
肿瘤细胞PD-L1的表达:大量前期研究结果显示，随着PD-L1的表达升高，患者预后改善，疗效提高(11,12)，PD-L1的表达是预测ICI疗效合理的生物标志物。Keynote001[9]研究结果表明，使用PD-1单抗的高表达PD-L1(>50％)患者的ORR可达45.2％，而PD-L1表达<1％的患者仅有10.7％。PD-L1的表达已被FDA推荐为使用PD-1单抗的非小细胞肺癌患者的伴随诊断,但临床实践中部分PD-L1低表达的患者也能从ICI治疗中获益,因此仅依靠PD-L1表达进行患者筛选是不够的。
肿瘤浸润性淋巴细胞(TIL):TIL是指在肿瘤组织中分离出来的浸润淋巴细胞，其数量和功能状态可以反应宿主的免疫状态。回顾性研究表明，TIL(尤其是CD8+T细胞)与患者的免疫疗效之间具有相关性，Tumeh等对使用PD-1单抗治疗的黑色素瘤患者的研究分析发现,肿瘤实质及边缘CD8+TIL密度越高，其治疗反应越好。前期研究表明，除了的数量外，TIL的分布和种类也可能对ICI的治疗产生影响，但尚需进一步探讨[10,11]。
γ干扰素(IFN-γ)等血清标志物:由于肿瘤特异性T细胞可以产生IFN-γ，一项抗PD-L1抗体Durvalumab治疗肺癌的Ⅱ期研究中发现,IFN-γmRNA表达增高，疗效越好[12]。Kikuchi等[13]在直肠癌中研究表明下调IFN-γ受体的表达与PD-1治疗进展有关。此外，有报道称IFN-γ通路蛋白的突变可通过IFN-γ的暴露导致PD-L1表达下降，在这种情况下使用抗PD-1/PD-L1抗体是无效的[14]。但血清中IFN-γ影响因素较多，其评估疗效的灵敏度和特异度较低。
此外，还有研究表明，血清中中性粒细胞淋巴细胞比值(NLR)、血小板淋巴细胞比值(PLR)和乳酸脱氢酶(LDH)等与PD-1治疗的反应性有关，但结论尚有争议[15,16]。且由于其整体效果并不理想，要么不够可靠，要么适用的范围较窄，目前尚未广泛应用于临床
采用以上策略从血清中筛选新的疗效评估标志物各有其优缺点，尚不能满足临床上ICI治疗效果的评估。因此，探索新的策略来筛选更好的ICI疗效评估血清诊断标志物仍有必要。
瓜氨酸组蛋白H3(Citrulline histone H3，H3Cit)是中性粒细胞胞外诱捕网(Neutrophil extracellular traps，NETs)的主要构成蛋白质，在肿瘤中的作用，特别是免疫治疗中的作用尚不明确。
IL-8作为一种炎性趋化因子，已被证明具有诱导肿瘤细胞PD-L1表达、抑制肿瘤细胞凋亡、促进肿瘤细胞EMT进程、促进肿瘤微环境血管生成、招募免疫抑制性细胞等功能，对肿瘤免疫治疗产生重要影响，但是IL-8本身的预测免疫治疗疗效的价值并不大。
C反应蛋白(CRP)是最早发现并突出的一种急性时相蛋白，它是一个敏感却非特异性的炎症和组织损伤标记物，在各种恶性肿瘤患者血清中均有着不同水平的升高。
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发明内容
本发明的目的在于克服现有技术的不足，提供一种用于评估免疫治疗疗效的标志物组及系统。
本发明所采取的技术方案是：
本发明的第一个方面，提供：
用于评估肿瘤免疫治疗疗效的标志物组，所述标志物组至少包括H3Cit、IL-8和CRP共计3个蛋白。
在一些实例中，所述标志物组由H3Cit、IL-8和CRP共计3个蛋白构成。
在一些实例中，所述肿瘤选自结直肠癌、鼻咽癌或肺癌。
在一些实例中，所述免疫治疗为免疫检查点抑制剂-抗PD-1/PD-L1治疗。
本发明的第二个方面，提供：
组合物在制备肿瘤免疫治疗疗效评估试剂中的应用，所述组合物可以定量待测样本中H3Cit、IL-8和CRP的蛋白表达量。
在一些实例中，待测样本为外周血血清样本。
在一些实例中，所述肿瘤选自结直肠癌、鼻咽癌或肺癌。
在一些实例中，所述免疫治疗为免疫检查点抑制剂-抗PD-1/PD-L1治疗。
本发明的第三个方面，提供：
一种用于评估肿瘤免疫治疗疗效的系统，包括：
蛋白浓度检测装置：用于检测患者样本中的H3Cit、IL-8和CRP的含量；
免疫治疗疗效评估装置：根据H3Cit、IL-8和CRP的含量，评估免疫治疗疗效；
结果输出装置：输出免疫治疗疗效评估结果。
在一些实例中，评估免疫治疗疗效的公式通过回归分析得到。
在一些实例中，评估免疫治疗疗效的公式为：
风险值＝3.0933×H3Cit+2.0124×IL-8+3.1292×CRP–11.1842
式中，H3Cit表达量的单位为ng/ml、IL-8表达量的单位为pg/ml、CRP表达量的单位为mg/L。
在一些实例中，待测样本为外周血全血样本或血清样本。
在一些实例中，所述肿瘤选自结直肠癌、鼻咽癌或肺癌。
在一些实例中，所述免疫治疗为免疫检查点抑制剂-抗PD-1/PD-L1治疗。
本发明的有益效果是：
本发明的一些实例，可以通过检测血清中H3Cit，IL-8和CRP的含量，基于H3Cit，IL-8和CRP这3个指标建立了评估肿瘤免疫治疗疗效的数学模型，此数学模型预测免疫治疗可能无效的AUC为0.943。当cut-off定为0.512，灵敏度为80.6％时，特异性可达92.3％，阳性预测值91.3％，阴性预测值82.6％，显著高于H3Cit(灵敏度：66.7％；特异性：84.6％；AUC：0.765)，IL-8(灵敏度：64.5％；特异性79.3％：AUC：0.755),CRP(灵敏度：66.7％；特异性：89.7％；AUC：0.826)任何一个指标单独的诊断效能，见图7。
本发明一些评估肿瘤免疫治疗疗效系统的实例，可用于治疗前预评估肿瘤患者免疫治疗的疗效，为精准免疫治疗方案的确定提供新的筛选指标，提高患者的治疗效果。
附图说明
图1是ICI治疗的CRC患者NLR预后分析图；
图2是结直肠癌患者外周血、癌组织和癌旁组织中性粒细胞和NETs的情况；A.中性粒细胞瑞氏染色；B.中性粒细胞DAPI染色；C.NETs DAPI染色；D.中性粒细胞在肿瘤组织浸润情况；F.中性粒细胞在癌旁正常组织浸润情况；
图3是42例免疫治疗无效患者和29例免疫治疗有效患者人血清H3Cit，IL-8和CRP浓度比较情况；
图4是血清H3Cit，IL-8和CRP构建的免疫治疗疗效评估模型；
图5是H3Cit，IL-8和CRP免疫治疗疗效评估模型的校准曲线；
图6是H3Cit，IL-8和CRP及构建免疫治疗疗效评估模型的决策曲线；
图7是H3Cit，IL-8和CRP及构建免疫治疗疗效评估模型的ROC曲线。
具体实施方式
本发明的第一个方面，提供：
用于评估肿瘤免疫治疗疗效的标志物组，所述标志物组至少包括H3Cit、IL-8和CRP共计3个蛋白。
在一些实例中，所述标志物组由H3Cit、IL-8和CRP共计3个蛋白构成。
本发明的实验数据表明，使用H3Cit、IL-8和CRP作为标志物，已经可以获得很好的评估准确性和特异性。在此基础上，通过增加其他独立的评估标志物，有望进一步提高其准确性和特异性。出于降低成本的考虑，可以仅使用H3Cit、IL-8和CRP作为标志物对免疫治疗的疗效进行评估。
在一些实例中，所述肿瘤选自结直肠癌、鼻咽癌或肺癌。
在一些实例中，所述免疫治疗为免疫检查点抑制剂-抗PD-1/PD-L1治疗。
本发明的第二个方面，提供：
组合物在制备肿瘤免疫治疗疗效评估试剂中的应用，所述组合物可以定量待测样本中H3Cit、IL-8和CRP的蛋白表达量。
组合物可以由常用的蛋白表达量检测试剂组成，包括但不限于免疫荧光染色、ELISA等。
在一些实例中，待测样本为外周血全血样本或血清样本。这些样本易于获得。
在一些实例中，所述肿瘤选自结直肠癌、鼻咽癌或肺癌。
在一些实例中，所述免疫治疗为免疫检查点抑制剂-抗PD-1/PD-L1治疗。
本发明的第三个方面，提供：
一种用于评估肿瘤免疫治疗疗效的系统，包括：
蛋白浓度检测装置：用于检测患者样本中的H3Cit、IL-8和CRP的含量；
免疫治疗疗效评估装置：根据H3Cit、IL-8和CRP的含量，评估免疫治疗疗效；
结果输出装置：输出免疫治疗疗效评估结果。
在一些实例中，评估免疫治疗疗效的公式通过回归分析得到。
在一些实例中，评估免疫治疗疗效的公式为：
风险值＝3.0933×H3Cit+2.0124×IL-8+3.1292×CRP–11.1842
式中，H3Cit表达量的单位为ng/ml、IL-8表达量的单位为pg/ml、CRP表达量的单位为mg/L。
在一些实例中，待测样本为外周血全血样本或血清样本。
在一些实例中，所述肿瘤选自结直肠癌、鼻咽癌或肺癌。
在一些实例中，所述免疫治疗为免疫检查点抑制剂-抗PD-1/PD-L1治疗。
下面结合实验，进一步说明本发明的技术方案。
新型诊断标志物的筛选
1.我们前期回顾性研究125例CRC患者ICI治疗前血常规指标，Kaplan-Meier分析发现患者中性粒细胞/淋巴细胞比值(NLR)与患者5年OS密切相关，NLR比值高的患者预后差(图1)，提示中性粒细胞与ICI治疗预后密切相关。
2.收集CRC患者外周全血标本，分别用瑞氏染色和免疫荧光染色法(DAPI)对外周血标本中中性粒细胞和NETs进行定位。NETs由PMA(500nM)刺激中性粒细胞4h产生，同时该患者免疫组化显示中性粒细胞的大量浸润(图2)。
3.收集本院CRC患者ICI治疗前血清标本：评估患者ICI的疗效；收集临床资料(姓名，性别，年龄，诊断，PD-1开始时间，PD-1治疗方案，TNM分期，转移数量，转移部位，病理类型，吸烟，饮酒，BMI等表1.)；ELISA检测其中CRC患者血清NETs相关指标水平：H3Cit，IL-8,IL-18,IL-18BP,EDIL3,CK-18,Tie-2,Ang-2,PD-L1；收集患者相关炎症指标。在ICI治疗有效组和进展组的血清中采用两独立样本比较的秩和检验比较，最终筛选出两组差异具有统计学意义(P<0.05)的指标：年龄，H3Cit，IL-8,GLB,CRP,SAA。
表1、患者的人口统计学和基线临床特征
Figure BDA0003099900160000081
图3是42例免疫治疗无效患者和29例免疫治疗有效患者人血清H3Cit，IL-8和CRP浓度比较情况；从图中可以看出，患者血清H3Cit，IL-8和CRP浓度与ICI免疫治疗疗效密切相关。
数学诊断模型的建立与验证
1.用Forward Condition方法作Binary Logistic回归分析6个指标中最佳组合评估免疫治疗疗效，按P值小于0.05的标准筛选出三个指标：H3Cit，IL-8和CRP,并建立评估免疫治疗疗效数学模型。评估免疫治疗疗效的公式为：
风险值＝3.0933×H3Cit+2.0124×IL-8+3.1292×CRP–11.1842
式中，H3Cit表达量的单位为ng/ml、IL-8表达量的单位为pg/ml、CRP表达量的单位为mg/L。
图4是血清H3Cit，IL-8和CRP构建的免疫治疗疗效评估模型。从图中可以看出，血清高浓度H3Cit，IL-8和CRP的患者ICI治疗疗效差，此数学模型可用于预测免疫治疗。
图5是H3Cit，IL-8和CRP免疫治疗疗效评估模型的校准曲线。从图中可以看出，此数学模型在疗效评估的实际预测值与理论预测值拟合情况良好。
图6是H3Cit，IL-8和CRP及构建免疫治疗疗效评估模型的决策曲线。从图中可以看出，此数学模型预测ICI免疫治疗疗效明显优于单个指标。
图7是H3Cit，IL-8和CRP及构建免疫治疗疗效评估模型的ROC。从图中可以看出，此数学模型免疫治疗可能无效的AUC为0.943，明显高于单个指标的AUC。
此数学模型预测免疫治疗可能无效的AUC为0.943。当cut-off定为0.512，灵敏度为80.6％时，特异性可达92.3％，阳性预测值91.3％，阴性预测值82.6％。
发明人从免疫治疗无效和免疫治疗有效患者治疗前血清中找到评估免疫治疗疗效的血清标志物：H3Cit，IL-8，CRP。建立的数学诊断模型可用于治疗前预评估肿瘤患者免疫治疗的疗效，为精准免疫治疗方案的确定提供新的筛选指标，提高患者的治疗效果。
以上是对本发明所作的进一步详细说明，不可视为对本发明的具体实施的局限。对于本发明所属技术领域的普通技术人员来说，在不脱离本发明构思的简单推演或替换，都在本发明的保护范围之内。

Claims (10)

1.用于评估肿瘤免疫治疗疗效的标志物组，所述标志物组至少包括H3Cit、IL-8和CRP共计3个蛋白。
2.根据权利要求1所述的标志物组，其特征在于：所述标志物组由H3Cit、IL-8和CRP共计3个蛋白构成。
3.根据权利要求1所述的标志物组，其特征在于：所述肿瘤选自结直肠癌、鼻咽癌或肺癌。
4.根据权利要求1所述的标志物组，其特征在于：所述免疫治疗为免疫检查点抑制剂-抗PD-1/PD-L1治疗。
5.组合物在制备肿瘤免疫治疗疗效评估试剂中的应用，所述组合物可以定量待测样本中H3Cit、IL-8和CRP的蛋白表达量。
6.根据权利要求5所述的应用，其特征在于：待测样本为血清样本。
7.根据权利要求5所述的应用，其特征在于：所述肿瘤选自结直肠癌、鼻咽癌和肺癌。
8.一种用于评估肿瘤免疫治疗疗效的系统，包括：
蛋白浓度检测装置：用于检测患者样本中的H3Cit、IL-8和CRP的含量；
免疫治疗疗效评估装置：根据H3Cit、IL-8和CRP的含量，评估免疫治疗疗效；
结果输出装置：输出免疫治疗疗效评估结果。
9.根据权利要求8所述的系统，其特征在于：评估免疫治疗疗效的公式通过回归分析得到。
10.根据权利要求8所述的系统，其特征在于：评估免疫治疗疗效的公式为：
风险值 = 3.0933×H3Cit+ 2.0124×IL-8+ 3.1292 ×CRP– 11.1842
式中，H3Cit表达量的单位为ng/ml、IL-8表达量的单位为pg/ml、CRP表达量的单位为mg/L。
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