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Idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbon in human blood serum are new biomarkers of lung cancer

机译:抗人血清中多环芳烃的独特型和抗独特型抗体是肺癌的新生物标志物

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摘要

Evaluation of epidemiologic risk factor in relation to lung cancer invoked by polycyclic aromatic hydrocarbons has been inconsistent. To address this issue, we conducted a prospective evaluation of new biomarkers for lung cancer classified according levels of idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbons in human blood serum. The blood serums of 557 lung cancer patients and 227 healthy donors were analysis of these antibodies by ELISA. Collected data were regrouped and analyzed by gender, smoking, and age as predictors of risk lung cancer factors. Also, the data of lung cancer patients were additionally analyzed by stages and types of lung cancer, surgery, and chemotherapy. It was suggested to use ratio of idiotypic and anti-idiotypic antibodies rather than distinguish level each of them separately. The ratio of levels in healthy people was 3.32 times higher than in lung cancer patients. This approach gave more precisely results and great prognostic value. The logistic regression model (AUC = 0.9) and neural networks (AUC = 0.95) were built to compare lung cancer patients and healthy donors by predictors. The ELISA data of 49 people random sampled from the originally ELISA data and ELISA data of 52 coal miners as a group of lung cancer risk were confirmed logistic regression model. So, suggested idiotypic and anti-idiotypic antibodies against polycyclic aromatic hydrocarbons were not only shown difference between healthy donors and lung cancer patients also elicited group of lung cancer risk among healthy people.
机译:多环芳烃引起的与肺癌有关的流行病学危险因素评价一直不一致。为了解决这个问题,我们对肺癌的新生物标志物进行了前瞻性评估,该标志物是根据人血清中针对多环芳烃的独特型和抗独特型抗体的水平分类的。通过ELISA分析了557名肺癌患者和227名健康供体的血清。对收集的数据进行重新分组,并按性别,吸烟和年龄进行分析,以预测危险的肺癌因素。此外,还根据肺癌的分期和类型,手术和化疗对肺癌患者的数据进行了分析。建议使用独特型抗体和抗独特型抗体的比例,而不是分别区分它们各自的水平。健康人的水平比率比肺癌患者高3.32倍。该方法可提供更准确的结果,并具有良好的预后价值。建立了逻辑回归模型(AUC = 0.9)和神经网络(AUC = 0.95),以通过预测变量比较肺癌患者和健康供体。从原本的ELISA数据和作为一组肺癌风险的52名煤矿工人的ELISA数据中随机抽取49人的ELISA数据,证实了logistic回归模型。因此,建议的针对多环芳烃的独特型和抗独特型抗体不仅显示出健康供体之间的差异,而且肺癌患者也引发了健康人群中的肺癌风险。

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