Identification of tumor-antigen signatures and immune subtypes for mRNA vaccine selection in muscle-invasive bladder cancer.

Background: Muscle-invasive bladder cancer continues to lack reliable diagnostic and prognostic biomarkers. Recently, tumor vaccines targeting specific molecules have emerged as a promising treatment in inhibiting tumor progression, which was rekindled under the background of coronavirus disease-2019 pandemic. However, the application of mRNA vaccine targeting muscle-invasive bladder cancer-specific antigens remains limited, and there has been a lack of comprehensive studies or validations to identify suitable patient subgroups for vaccination. This study aims to explore novel muscle-invasive bladder cancer antigen signatures to identify patients most likely to benefit from vaccination.

Methods: Gene expression profiles of muscle-invasive bladder cancer samples, along with corresponding clinical data, were retrieved from the Cancer Genome Atlas Program. The least absolute shrinkage and selection operator model was applied to develop signatures for stratifying muscle-invasive bladder cancer patients. Prognostic accuracy of each factor was assessed using receiver operating characteristic analysis. Tumor Immune Estimation Resource was employed to visualize the relationship between the proportion of antigen-presenting cells and the expression of selected genes. The CIBERSORT and WGCNA R packages were used to identify differences in immune infiltration levels across muscle-invasive bladder cancer subgroups. Additionally, the STRING database and Cytoscape were used to construct the protein-protein interaction network. CCK-8 and colony formation assays were employed in invitro experiments.

Results: A total of 49 potential tumor antigens were identified. Using least absolute shrinkage and selection operator Cox regression, 14 tumor antigens were selected to develop a risk evaluation signature. The risk score signature can serve as a valuable tool for predicting the outcomes of muscle-invasive bladder cancer patients. Based on differential clinical, molecular, and immune-related gene profiles, muscle-invasive bladder cancer patients were classified into 2 subtypes: the immune "cold" subtype (immune score 1) and the immune "hot" subtype (immune score 2). The immune score signature, developed using a logistic score model, effectively distinguishes between patients more likely to belong to immune score 1 or 2. Notably, patients with a high risk score exhibited a higher proportion of immune score 2 compared to those with a low risk score. Additionally, the prognostic accuracy was significantly enhanced when the risk score and immune score were combined. Different tumor subtypes displayed distinct immune landscapes and signaling pathways. Moreover, novel tumor antigens associated with oxidative stress were identified.

Conclusion: The risk score and immune score signatures based on tumor antigens have identified potential effective neo-antigens for the development of mRNA vaccines targeting muscle-invasive bladder cancer. Patients with low risk score and immune score 1 subtype are more likely to benefit from mRNA vaccination. Additionally, this study highlights the critical role of oxidative stress in modulating the efficacy of the mRNA vaccine.