摘要
肺癌是对人类健康构成威胁最大的恶性肿瘤之一,实现肺癌的早期诊断可以大幅提高肺癌病人的生存率。呼吸诊断直接检测肺部呼出气体相关成分的改变,可以成为新型,无创,便捷的诊断手段。寻找可做呼吸诊断的肺癌标志物可能为肺癌的早期诊断提供关键步骤。
本研究在呼出气体中挥发性有机物VOCs,以及呼出气体冷凝物EBC中肺癌标志物的检测方法进行了研究,主要包括以下内容：
采用固相微萃取-气相色谱-质谱联用系统分析88例肺癌患者、70例肺良性疾病患者、85例正常健康人呼出气体中VOCs的表达,筛选出26种肺癌特征性VOCs。证明此组VOCs对肺癌病人与对照组有具有可分性,并优化选择了十六醛,8-已基十五烷,十九醇,2,5-叔丁基4-甲基苯酚,十三烷,十五酮,十三酮七种标志物建立肺癌诊断的模型。达到88.5%的正确率,其中敏感度为88.2%(假阴性率为11.8%),特异度为88.6%(假阳性率为11.4%)。此模型可作为肺癌早期诊断和筛查的手段。
用固相微萃取-气相色谱-质谱联用系统,检测肺癌组织以及肺癌细胞株新陈代谢气体中VOCs,并以正常肺组织和正常支气管上皮细胞株为对照,研究其VOCs表达差异。检测腺癌细胞株A549、小细胞癌细胞株NCI-H446、鳞癌细胞株SK-MES-1培养液顶空气体中的VOCs,测得十五酮,十九烷,二十烷有较高表达。检测18例原发性肺癌患者的手术标本顶空VOCs,并以癌旁正常组织作对照,测得癸烷、十五酮、十九烷、二十烷等12种VOCs较癌旁正常肺组织高表达。与呼吸诊断征性VOCs相比,细胞水平上的特异性VOCs均属于烷烃类和含氧有机物,并有相同的特特异性VOC如十五酮,但不完全一致。表明肿瘤细胞逐步代谢与呼吸气体中特征性VOCs有关,但并非单一决定因素。
对呼出气冷凝物EBC中的肺癌标志物的检测进行了初步探索,选择癌胚抗原CEA作为冷凝物中的待测物。设计了简易冷凝物采集装置收集呼吸冷凝物果。研究了LAPS(光寻址电位传感器)的原理,完成LAPS器件封装和测试系统的搭建,进行了LAPS器件特性曲线的测试。设计基于LAPS的免疫传感器测定CEA的检测方法。用过碘酸钠法制备了脲酶联CEA抗体,用双抗体夹心的酶免疫方法测定标样CEA,用上述LAPS器件系统进行测试,Ⅰ-Ⅴ曲线指示氢离子浓度下降。证明了基于LAPS的免疫传感器用于呼吸冷凝物中CEA检测的可行性。
Lung cancer is one of the most threatening malignant tumors of human health. Early diagnosis significantly improves the survival rate of patients with lung cancer. Breath detection could be a new, non-invasive and convenient diagnosis method. And the research of biomarkers for lung cancer in the exhale breath provides a key step in the early diagnosis of lung cancer.
This paper reports research for lung cancer markers in the detection of volatile organic compounds (VOCs) in exhale breath and exhale breath condensate (EBC) which is as followed.
This paper analyzed VOCs in the exhaled breath of 243 samples by solid-phase micro-extraction and gas chromatography-mass spectroscopy technique (SPME-GCMS) system, including 88 samples of lung cancer,70 samples of lung benign disease and 85 samples of health person.26 characteristic VOCs of lung cancer were screened for further statistical approaches to demonstrate the separability between patients group and control group. A diagnostic model for lung cancer was set up based on 7 selected characteristic VOCs. This model achieved a correct rate of 88.5% with a sensitivity of 88.2% (false negative rate of 11.8%) and a specificity of 88.6% (false positive rate of 11.4%).This diagnostic model can be used as a screening method for high-risk groups.
The detection of VOCs in lung cancer tissue and lung cancer cell metabolism was conducted using SPME-GCMS system, while chose the normal lung tissue and the primary human bronchial epithelial cell as contrast. As the result it has been found, 2-pentadecanone,nonadecane and eicosane were detected in all the three lung cancer cell lines A549, NCI-H446 and SK-MES-1. By comparing the difference of VOCs in the eighteen lung cancer tissues, it was found out that twelve VOCs such as decane, 2-pentadecanone, nonadecane and eicosane had greater concentration.
Meanwhile, the relation between the characteristic VOCs screened from patients with lung cancer and lung cancer cell lines was analyzed. There was certain overlap in the characteristic VOCs (2-pentadecanone), but not exactly the same. This result indicated that tumor cell metabolism is related with characteristic VOCs, but not the only determining factor.
This paper makes preliminary research in the detection of lung cancer markers in EBC and chose Carcinoembryonic antigen (CEA) as the biomarker of lung cancer in EBC. A design of the determination of CEA was proposed based on light addressable potentiometric sensor (LAPS), and its performance on the collection of EBCs has been evaluated. The principle of LAPS measurement, along with the test result of hydrogen ion was also analyzed. Urease-CEA antibody was prepared and the process for the detection of CEA using sandwich technic method has been simulated in microloan ELISA plates. Finally a primary experiment has been conducted to demonstrate the feasibility of the detection of CEA in EBC using LAPS.
引文
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