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Autoantibodies as biomarkers for colorectal cancer: A systematic review, meta-analysis, and bioinformatics analysis.
The International Journal of Biological Markers ( IF 2.3 ) Pub Date : 2019-10-05 , DOI: 10.1177/1724600819880906
Hejing Wang 1 , Xiaojin Li 1 , Donghu Zhou 1 , Jian Huang 1
Affiliation  

Colorectal cancer is a very common cancer worldwide. Serum tumor-associated autoantibodies (TAAbs), especially the anti-p53 autoantibody, may be promising biomarkers to detect early-stage colorectal cancer. This study aimed to identify all known autoantibodies and their value in colorectal cancer diagnosis, as well as exploring the underlying connections and mechanisms through a bioinformatics analysis. Databases were used to select available articles of TAAbs in colorectal cancer. In a meta-analysis of the anti-p53 autoantibody, the diagnostic odds ratio and area under the curve (AUC) of the summary receiver-operating characteristic (SROC) curve were calculated using Stata 12.0 and Meta-Disc 1.4. We identified 73 articles including 199 single autoantibodies and 42 multiple autoantibodies. The maximum value of Youden's index was 0.76, combining c-MYC, p53, cyclin B1, p62, Koc, IMP1, and survivin. The diagnostic odds ratio for anti-p53 autoantibody at all stages was 10.86 (95% CI 8.40, 14.06) with low heterogeneity (I2 = 40.3%) and the AUC of the SROC curve was 0.82. For the anti-p53 autoantibody in early-stage colorectal cancer, the diagnostic odds ratio was 4.82 (95% CI 2.95, 7.87) with heterogeneity (I2 = 7.9%) and the AUC of the SROC curve was 0.72. Eighty-seven autoantibodies were selected for bioinformatics analyses. We found that the most enriched functional terms and protein-protein interactions may relate to the mechanism of autoantibody generation. In summary, our study summarized the diagnostic value of TAAbs in colorectal cancer, either as single molecules or in combination. Bioinformatics analyses may be a new approach to explore the mechanism of autoantibody generation.

中文翻译:

自身抗体作为结直肠癌的生物标志物:系统评价,荟萃分析和生物信息学分析。

大肠癌是全世界非常普遍的癌症。血清肿瘤相关自身抗体(TAAbs),特别是抗p53自身抗体,可能是检测早期结直肠癌的有前途的生物标志物。这项研究旨在鉴定所有已知的自身抗体及其在结直肠癌诊断中的价值,并通过生物信息学分析探索潜在的联系和机制。数据库用于选择大肠癌中TAAb的可用文章。在抗p53自身抗体的荟萃分析中,使用Stata 12.0和Meta-Disc 1.4计算了汇总接收者操作特征(SROC)曲线的诊断比值比和曲线下面积(AUC)。我们鉴定了73篇文章,包括199个单一自身抗体和42个多重自身抗体。尤登指数的最大值是0.76,结合c-MYC,p53,cyclin B1,p62,Koc,IMP1和survivin。抗p53自身抗体在所有阶段的诊断优势比为10.86(95%CI 8.40,14.06),异质性低(I2 = 40.3%),SROC曲线的AUC为0.82。对于早期结直肠癌中的抗p53自身抗体,诊断比值比为4.82(95%CI 2.95,7.87),且异质性(I2 = 7.9%),SROC曲线的AUC为0.72。选择了八十七种自身抗体进行生物信息学分析。我们发现最丰富的功能术语和蛋白质-蛋白质相互作用可能与自身抗体生成的机制有关。总而言之,我们的研究总结了TAAb在大肠癌中的诊断价值,无论是单分子还是组合形式。
更新日期:2019-11-01
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