Integrating analysis of multi-omics summary data identifies novel plasma protein biomarkers and drug targets for bladder cancer

Abstract

The plasma proteins are an important source of therapeutic targets. This study aims to address the diagnostic and therapeutic challenges of bladder cancer (BC) by using Mendelian randomization (MR) with a large sample size from multiple centers to identify the plasma proteins which are causally related to the pathogenesis of BC. Followed by merging nine plasma protein datasets from six studies, a total of 5538 plasma proteins and three BC datasets (ieu-b-4874, ukb-b-8193, FinnGen_R11_C3_ BLADDER_EXALL) were used to perform proteome‑wide MR to estimate the contribution of plasma proteins to BC, separately. To ensure the robustness of the results, Veen intersection operation on MR results revealed that 14 meaningful candidate pathogenic plasma proteins (ANKRD27, BIN1, FAHD1, IL17RB, MRPL21, PPT1, PSCA, SLC16A3, SLURP1, SPON2, TACSTD2, TMEM87B, YWHAB) were obtain from three datasets. Then, we validated these proteins through various methods, including meta-analysis, reverse MR, Bayesian co-localization analysis and summary-data-based MR (SMR), and pathogenic plasma proteins were divided into three layers according to the validation confidence. We then performed single-cell transcriptome analysis (Registration number: GSE222315), which showed that 13/14 candidate plasma proteins were expressed and 12 proteins were differentially expressed in at least one cell type. Finally, protein–protein interactions (PPI) analysis and druggability evaluation were performed to explore the relationship between the interaction of plasma protein markers and existing cancer drug targets. Summarily, our research uncovered 14 plasma protein biomarkers linked to BC risk, offering novel perspectives on the etiology and potential targets for developing screening biomarkers and therapeutic drugs for BC.