Grebenshchikov Ivan S, Studennikov Artem E, Ivanov Vadim I, Ivanova Natalia V, Titov Victor A, Vergbickaya Natalja E, Ustinov Valentin A
Federal State Scientific Institute, Federal Research Centre Coal and Coal Chemistry, Siberian Branch of the Russian Academy of Sciences, Institute of Human Ecology, Kemerovo, 650065, Russia.
Federal State Educational Institute of Higher Professional Education, Kemerovo State University, Kemerovo, 650043, Russia.
Oncotarget. 2019 Aug 20;10(49):5070-5081. doi: 10.18632/oncotarget.27126.
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.
多环芳烃引发的肺癌相关流行病学危险因素评估结果并不一致。为解决这一问题，我们针对根据人血清中针对多环芳烃的独特型和抗独特型抗体水平分类的肺癌新生物标志物进行了前瞻性评估。通过酶联免疫吸附测定法（ELISA）对557名肺癌患者和227名健康捐赠者的血清进行了这些抗体的分析。收集的数据按性别、吸烟情况和年龄重新分组并分析，作为肺癌风险因素的预测指标。此外，还按肺癌的分期和类型、手术及化疗情况对肺癌患者的数据进行了额外分析。建议使用独特型和抗独特型抗体的比例，而非分别区分它们各自的水平。健康人群中的水平比例比肺癌患者高3.32倍。这种方法得出了更精确的结果和很大的预后价值。构建了逻辑回归模型（曲线下面积[AUC]=0.9）和神经网络（AUC=0.95），以通过预测指标比较肺癌患者和健康捐赠者。从最初的ELISA数据中随机抽取的49人的ELISA数据以及作为肺癌风险组的52名煤矿工人的ELISA数据证实了逻辑回归模型。因此，针对多环芳烃的独特型和抗独特型抗体不仅显示出健康捐赠者和肺癌患者之间的差异，还在健康人群中引发了肺癌风险组。
