Identification and Validation of Novel Serum Autoantibody Biomarkers for Early Detection of Colorectal Cancer and Advanced Adenoma.

Abstract

Background: Colorectal cancer (CRC) comprises a large proportion of malignant tumors, and early detection of CRC is critical for effective treatment and optimal prognosis. We aimed to discover and validate serum autoantibodies for early detection of CRC. Methods: Combined with CRC-associated autoantibodies discovered by serological proteome and multiplex analyses, 26 predefined autoantibodies were evaluated in 315 samples (130 CRCs, 75 advanced adenomas, and 110 healthy controls) by protein microarray analysis. Autoantibodies with potential detection value were verified by enzyme-linked immunosorbent assays (ELISAs). Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the accuracy of the biomarkers. Results: Four serum autoantibodies (ALDH1B1, UQCRC1, CTAG1, and CENPF) showed statistically different levels between patients with advanced neoplasm (CRC or advanced adenoma) and controls in microarray analysis, which were validated by ELISAs. Among the four biomarkers, the ALDH1B1 autoantibody showed the highest detection value with area under the curve (AUC) values of 0.70 and 0.74 to detect CRC and advanced adenoma with sensitivities of 75.68 and 62.31% and specificities of 63.06 and 73.87%, respectively. By combining the four biomarkers, the performance was improved with an AUC of 0.79 to detect CRC and advanced adenomas. Conclusion: The ALDH1B1 autoantibody has a good potential for early detection of CRC and advanced adenoma, and measuring serum autoantibodies against tumor-associated antigens may improve detection of early CRC.

• Authors: Hejing Wang, Bei Zhang, Xiaojin Li, Donghu Zhou, Yanmeng Li, Siyu Jia, Saiping Qi, Anjian Xu, Xiaomu Zhao, Jin Wang, Zhigang Bai, Bangwei Cao, Ni Li, Min Dai, Hongda Chen, Jian Huang
• Journal: Frontiers in oncology (Front Oncol) Vol. 10 Pg. 1081 ( 2020) ISSN: 2234-943X [Print] Switzerland
• PMID: 32793472 (Publication Type: Journal Article)
• Copyright: Copyright © 2020 Wang, Zhang, Li, Zhou, Li, Jia, Qi, Xu, Zhao, Wang, Bai, Cao, Li, Dai, Chen and Huang.