The value of serum tumor-associated autoantibodies in screening and diagnosis of gastric cancer

IF 2.9 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY Clinica Chimica Acta Pub Date : 2025-03-01 Epub Date: 2025-02-01 DOI:10.1016/j.cca.2025.120167
Kangjia Xiao , Chengxuan Xie , Yi Zhang , Meihua Kang , Yanchun Wang , Qingtian Li , Wenqian Dong , Hao Wang , Huaxing Wei , Yanping Hu , Baolong Wang , Renquan Lu
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Abstract

Objective

To investigate the clinical value of serum autoantibodies in the screening and diagnosis of gastric cancer.

Materials & methods

A total of 570 gastric cancer patients and 373 controls were enrolled in this study. Enzyme-linked immunosorbent assay (ELISA) was employed to quantitatively detect autoantibodies in the tested serum, and statistic modeling was conducted to analyze their relationships with various clinical and pathological parameters.

Results

The results of autoantibody detection in gastric cancer patients were significantly different from those of the control group. A combination of 7 autoantibodies, including CLDN18, CAGE1, CTAG1A, PBRM1, RASSF7, IMMP2L and COPB1, was selected for modeling (AUC = 0.885). The diagnostic specificity was approximately 0.86 when combined 7-TAAs with Helicobacter pylori, while the positive predictive value was increased to 0.94. The abnormal elevation of different TAAs proteins in gastric cancer patients is related to factors such as disease stage, tumor differentiation degree, and invasion depth.

Conclusion

The determination of serum autoantibody panel has clinical value in screening and prediction of gastric cancer, and can be used as an auxiliary index in clinical diagnosis. The combination of 7-TAAs and Helicobacter pylori can effectively improve the screening specificity and positive predictive value. The detection results of different proteins were related to the stage of disease, the degree of tumor differentiation and the depth of invasion.
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血清肿瘤相关自身抗体在胃癌筛查和诊断中的价值。
目的:探讨血清自身抗体在胃癌筛查和诊断中的临床价值。材料与方法:本研究共纳入570例胃癌患者和373例对照组。采用酶联免疫吸附法(ELISA)定量检测被试血清中的自身抗体,并建立统计模型,分析其与各项临床及病理参数的关系。结果:胃癌患者自身抗体检测结果与对照组有显著性差异。选择CLDN18、CAGE1、CTAG1A、PBRM1、RASSF7、IMMP2L、COPB1等7种自身抗体组合进行建模(AUC = 0.885)。7-TAAs联合幽门螺杆菌诊断特异性约为0.86,阳性预测值为0.94。胃癌患者不同TAAs蛋白异常升高与疾病分期、肿瘤分化程度、侵袭深度等因素有关。结论:血清自身抗体测定对胃癌的筛查和预测具有临床价值,可作为临床诊断的辅助指标。7-TAAs联合幽门螺杆菌可有效提高筛查特异性和阳性预测值。不同蛋白的检测结果与疾病分期、肿瘤分化程度及侵袭深度有关。
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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