Widely-used screening and diagnostic methods are not suitable for preventive screening, and high-throughput technologies based on serum biomarkers are needed.
We screened 501 serum samples, including 224 lung cancer (LC), 126 disease control (DC), and 151 healthy donor (HC) samples for new serum autoantibodies as biomarkers in the early diagnosis of lung cancer. In phase I, we used HuProtTM microarrays to perform preliminary serum antibody screening on 24 LC and 24 HC samples. In phase II, we screened 60 LC, 60 DC, and 60 HC serum samples using focused arrays constructed with 22 of the candidate autoantibody biomarkers screened out in phase I.
After data modeling and validation, we selected four potential early LC protein biomarker candidates, IL2RB, CENPB, TP53, and XAGE1A, with individual specificities >90% and sensitivities ranging from 21.2% to 32.2%. These four biomarkers had a specificity of >90% and a sensitivity of >65.5% for early LC when they combined in a panel. Further evaluation of these four biomarker candidates using ELISA assays and 273 serum samples (140 LC, 66 DC, and 67 HC) gave similar results (specificity of >91.7%, sensitivity >61.43%).
IL2RB, CENPB, TP53, and XAGE1A combined biomarker panel holds potential for rapid screening and improving the diagnosis of early-stage LC, thus potentially also improving its prognosis.
目的:广泛使用的筛查和诊断方法不适用于预防性筛查,需要基于血清生物标志物的高通量技术。
方法:我们筛选了501份血清样本,包括224例肺癌(LC),126个疾病对照(DC)和151个健康供体(HC)样品,用于新的血清自身抗体作为肺癌早期诊断的生物标志物。在第一阶段,我们使用HuProtTM微阵列对24例LC和24例HC样本进行了初步血清抗体筛选.在第二阶段,我们筛选了60个LC,60个DC和60个HC血清样本,使用在I期筛选出的22个候选自身抗体生物标志物构建的聚焦阵列。
结果:数据建模和验证后,我们选择了四种潜在的早期LC蛋白生物标志物,IL2RB,CENPB,TP53和XAGE1A,个体特异性>90%,敏感性为21.2%至32.2%。当它们在一组中组合时,这四种生物标志物对于早期LC具有>90%的特异性和>65.5%的灵敏度。使用ELISA测定法和273份血清样品(140LC,66DC和67HC)给出了相似的结果(特异性>91.7%,灵敏度>61.43%)。
结论:IL2RB,CENPB,TP53和XAGE1A联合生物标志物组具有快速筛查的潜力,可以改善早期LC的诊断,因此也有可能改善其预后。