To integrate multi-omics data to prioritize candidate susceptibility genes and evaluate their functional and clinical significance in prostate cancer pathogenesis.
Approach:
Data Integration: Integrated PCa GWAS summary statistics with GTEx v8 expression quantitative trait locus reference panels for cross-tissue and single-tissue transcriptome-wide association studies.
Candidate Signal Refinement: Refined candidate signals using conditional analysis, MAGMA, fastBAT gene-level tests, Summary data-based Mendelian randomization, and Bayesian colocalization.
Tumor-context Analysis: Incorporated tumor-context cis-eQTL evidence from TCGA-PRAD to prioritize regulatory signals retained in prostate cancer tissues.
Functional Assessment: Assessed prioritized candidates using transcriptomic datasets, Human Protein Atlas immunohistochemistry, single-cell RNA-seq analysis, histological grading, and genomic risk signatures.
Key Findings:
Identified 23 consensus candidate genes supported by multiple association frameworks.
MLPH was retained as the final prioritized candidate, with significant association of lead variant rs7582964 with MLPH expression in PRAD tumor tissues.
MLPH expression was upregulated in PCa tissues compared to normal prostate tissues.
MLPH expression correlated with histological differentiation and preoperative PSA levels.
Interpretation:
The study prioritizes MLPH as a candidate susceptibility gene for prostate cancer, linking its regulatory signal to tumor-context expression and clinically relevant molecular features.
Limitations:
The study primarily focused on European-ancestry populations, which may limit generalizability.
Complex patterns of linkage disequilibrium may hinder precise localization of candidate variants.
Conclusion:
MLPH may play a role in prostate cancer biology, particularly in relation to vesicle trafficking and tumor differentiation.
