Identification of tumor-antigen signatures and immune subtypes for messenger RNA vaccine selection in advanced clear cell renal cell carcinoma.

BACKGROUND

Advanced clear cell renal cell carcinoma still lacks reliable diagnostic and prognostic biomarkers. Recently, tumor vaccines targeting specific molecules have been proposed as a promising treatment in mitigating tumor progression, which was rekindled under the background of the COVID-19 pandemic. However, the application of messenger RNA vaccine against advanced clear cell renal cell carcinoma antigens remains stagnant, and no subgroup of patients deemed suitable for vaccination has been extensively studied or validated. Our study aims to explore novel advanced clear cell renal cell carcinoma antigen signatures to select suitable patients for vaccination.

METHODS

Gene expression profiles of advanced clear cell renal cell carcinoma samples and their corresponding clinical data were retrieved from The Cancer Genome Atlas. The least absolute shrinkage and selection operator model was applied to develop signatures to stratify patients with advanced clear cell renal cell carcinoma. Receiver operating characteristic analysis was used to compare the prognostic accuracy of each factor. Tumor Immune Estimation Resource was used to visualize the relationship between the proportion of antigen-presenting cells and the expression of filtered genes. The "CIBERSORT" and "WGCNA" R Packages were employed to ascertain disparities in immune infiltration levels between advanced clear cell renal cell carcinoma subgroups. The Search Tools for the Retrieval of Interacting Genes database and Cytoscape were used to construct the protein-protein interaction network. CCK-8 and colony formation assays were included in the invitro experiment.

RESULTS

In total, 244 potential tumor antigens were identified. Using the least absolute shrinkage and selection operator Cox regression, 21 tumor antigens were selected for developing a risk evaluation signature. The risk score signature can be a useful tool to predict the outcome of advanced clear cell renal cell carcinoma patients. According to the differential clinical, molecular, and immune-related genes, we divided advanced clear cell renal cell carcinoma patients into the immune "cold" subtype and immune "hot" subtype. By developing a logistic score, the immune subtype signature can better distinguish a patient more likely to be immune "cold" subtype or immune "hot" subtype. Interestingly, patients with high risk scores had a higher proportion of immune "hot" subtype than those with a low risk score. Furthermore, the prognostic value was significantly improved when combining risk score and immune subtype. Distinct immune landscapes and signal pathways were observed between different tumor subtypes. Finally, novel tumor antigens related to oxidative stress were identified.

CONCLUSION

The tumor-antigens-based risk score and immune subtype signatures identified potentially effective neo-antigens for advanced clear cell renal cell carcinoma messenger RNA vaccine development, and patients with low risk scores and immune "cold" subtype tumors are more prone to benefit from messenger RNA vaccination. Furthermore, our study highlights the significant role of oxidative stress in determining the efficacy of the messenger RNA vaccine.