Screening of Autoantibodies in Serum of Renal Cancer Patients Based on Human Proteome Microarray

Abstract Background: The autoantibody in the patient's serum can be used as a marker for the diagnosis of cancer, and the differences of autoantibodies are closely related to the changes of their target proteins. The human proteome microarray platform can be used for the screening of autoantibodies.Methods: In this study, 16 renal cancer (RC) patients were taken as a disease group, and the same number of healthy people was selected as a healthy control (HC) group. The protein microarray containing 16,152 proteins was used to detect the possible differences of autoantibodies IgG and IgM in the sera between the RC group and HC group. The screening criteria for autoantibodies and their target proteins are: fold change > 1.2, p-value < 0.05, positive ratio of RC > 30% and positive ratio of HC < 10%. Then the screened target proteins were used for cluster analysis of functions and pathways by PANTHER, DAVID and STRING. Results: Through the comparative analysis of the microarray results, there were 139 types of IgG and 43 types of IgM autoantibody significantly higher in RC than in the HC, and the highly responsive autoantibodies can be candidate biomarkers, such as anti-BCAS4-IgG and anti-RCN1-IgM. There were 159 IgG and 261 IgM autoantibodies that were significantly changed between the RC and the HC. The target proteins BCAS4 and RCN1 may be RC-related antigen and proteins such as GAP43 and CCT8 may be RC-related or RC-specific antigen. The functional clustering results showed those target proteins were mainly directed against the MAPK signaling pathway, Antigen processing: ubiquitination & proteasome degradation, Cargo recognition for clathrin-mediated endocytosis, etc. Conclustions: The high-content human proteome microarray platform can effectively screen autoantibodies in serum as candidate markers for renal cancer, and their corresponding target proteins can lay the foundation for the study of renal cancer.