| Literature DB >> 32443439 |
Keyan Wang1, Miao Li2, Jiejie Qin1, Guiying Sun1, Liping Dai2, Peng Wang1, Hua Ye1, Jianxiang Shi2, Lin Cheng3, Qian Yang1, Cuipeng Qiu1, Di Jiang2, Xiao Wang2, Jianying Zhang1,2.
Abstract
Substantial evidence manifests the occurrence of autoantibodies to tumor-associated antigens (TAAs) in the early stage of hepatocellular carcinoma (HCC), and previous studies have mainly focused on known TAAs. In the present study, protein microarrays based on cancer driver genes were customized to screen TAAs. Subsequently, autoantibodies against selected TAAs in sera were tested by enzyme-linked immunosorbent assays (ELISA) in 1175 subjects of three independent datasets (verification dataset, training dataset, and validation dataset). The verification dataset was used to verify the results from the microarrays. A logistic regression model was constructed within the training dataset; seven TAAs were included in the model and yielded an area under the receiver operating characteristic curve (AUC) of 0.831. The validation dataset further evaluated the model, exhibiting an AUC of 0.789. Remarkably, as the aggravation of HCC increased, the prediction probability (PP) of the model tended to decrease, the trend of which was contrary to alpha-fetoprotein (AFP). For AFP-negative HCC patients, the positive rate of this model reached 67.3% in the training dataset and 50.9% in the validation dataset. Screening TAAs with protein microarrays based on cancer driver genes is the latest, fast, and effective method for finding indicators of HCC. The identified anti-TAA autoantibodies can be potential biomarkers in the early detection of HCC.Entities:
Keywords: autoantibodies; biomarker; cancer driver gene; hepatocellular carcinoma (HCC); protein microarray
Year: 2020 PMID: 32443439 DOI: 10.3390/cancers12051271
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639