Abstract 1033: Evaluation of autoantibodies to proteins encoded by cancer driver genes as biomarkers for prostate cancer
Authors: Qiu Cuipeng , Wang Xiao , Casiano Carlos A. , Zhang Jian-Ying 
Published: March 2024

Prostate cancer (PCa) is a complex disease driven by genomic alterations, and understanding the immune response to these alterations can provide valuable insights into its pathogenesis. This study aimed at exploring the immunogenicity of proteins encoded by PCa driver genes and identifying corresponding autoantibodies as potential PCa biomarkers. Bioinformatics analysis, enzyme-linked immunosorbent assay (ELISA), and immunohistochemistry (IHC) were conducted in this study. A comprehensive screening process involving bioinformatics analysis and published studies identified a set of PCa driver genes for further investigation. Three strategies were employed to identify candidate driver genes: (1) utilizing the IntOGen database (Martínez-Jiménez et.al, Nature Reviews Cancer 2020), nine cohorts comprising 1503 primary PCa patient samples were analyzed, resulting in the identification of 63 PCa driver genes, with the top 20 genes exhibiting high mutation rates and frequencies in these cohorts; (2) employing the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, 16 driver genes that were enriched in prostate cancer pathways were identified from the initial 63 genes; (3) referring to a published article (Dietlein et.al, Nature Genetics 2020), the top 17 driver genes that highly related to prostate cancer across 28 tumor types were selected. A final set of 15 PCa driver genes, which appeared in at least two of the screening strategies, were included in subsequent analyses. ELISA was then performed to assess the presence of autoantibodies targeting proteins encoded by these 15 PCa driver genes. Autoantibodies were evaluated using serum samples from 203 PCa patients and 93 normal controls. The results revealed that seven out of the 15 autoantibodies showed significantly elevated levels in the sera of PCa patients compared to normal controls. Notably, the autoantibody targeting SPOP (speckled-type POZ protein) exhibited the highest frequency of 42.4%, followed by the autoantibody to PTEN (phosphatase and tensin homolog) at 37.4% in the PCa group. Finally, the SPOP protein was analyzed by IHC on the prostate tissue microarray containing PCa tissues, prostate simple hyperplasia tissues, cancer adjacent prostate tissues, and normal prostate tissues further to explore the consistency of SPOP expression in antigen-antibody reactions. High expression of SPOP protein was found in the PCa tissues. These findings suggest that proteins encoded by PCa driver genes may possess immunogenic properties due to neoepitopes possibly generated by mutations, leading to the production of corresponding autoantibodies. Identifying specific autoantibodies associated with PCa driver genes could offer novel opportunities for discovering autoantibody-based biomarkers in PCa. Further validation of these autoantibodies is warranted to evaluate their diagnostic potential in PCa.

Citation Format: Cuipeng Qiu, Xiao Wang, Carlos A. Casiano, Jian-Ying Zhang. Evaluation of autoantibodies to proteins encoded by cancer driver genes as biomarkers for prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1033.