Immune System Alterations in the Development of Three Urological Cancers: Insights from Large-Sample Mendelian...

Background: Urological cancers (UCs) greatly impact global public health. While immunity plays an important role, the contribution of specific immune cell traits to the development of UCs remains unclear. In our study, we employed Mendelian randomization (MR) to elucidate the causal relationship between 731 immune cell traits and three common UCs, namely kidney cancer (KC), bladder cancer (BC), and prostate cancer (PC). Methods: In our research, we adopted and preprocessed the statistics of 731 immune cell types from the GWAS Catalog. The data of three common UCs were acquired from two databases, FinnGen and IEU. Five MR analysis models, including random-effect inverse-variance weighted, weighted median, MR Egger, weighted mode, and simple mode, were used to assess the association between 731 immune cell traits and UCs. Subsequently, a meta-analysis of the IVW method was performed, and the significant results were analyzed using the reverse MR method. Sensitivity analyses, including leave-one-out analysis, were also performed. Results: When analyzing the two datasets separately, 25, 41, and 23 immune phenotypes were found to be significantly associated with BC, PC, and KC, respectively. When applying meta-analysis, the combined results showed that a total of 18 immune cell types manifested the significant association, including 4 and 14 immune cell traits regarding BC and PC, respectively. Utilizing reverse MR analysis on the combined results, we found that two immune cell traits, namely lymphocyte absolute cell counts and CX3CR1 on CD14+ CD16- monocytes, showed a reverse causal relationship with PC. Conclusions: Our research depicts the immune landscape for these three common UCs, highlighting their strong genetic associations with immune cells. It provides valuable insights for identifying the systemic immunological context of cancer susceptibility and the development of blood-based immunological biomarkers and therapeutic targets.