ArticleEBioMedicine2024
Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics.
Article in EBioMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Early-Onset Prostate Cancer: Epidemiology, Risk Factors, Biology, Clinical Features, Management, and Early Detection.MedComm · 2026Review
- Spatial transcriptomics in cancer research: insights into tumorigenesis, diagnosis and therapeutics.Cell death discovery · 2026Review
- Evaluating the Impact of Putative Metformin Targets on Cancer Outcomes: A Drug-Target Mendelian Randomization Study.Diabetes, obesity & metabolism · 2026Article
- Identification of ephrin-A1-EphA2 signalling as a potential target for fracture prevention.Nature communications · 2026Article
- Proteome-wide association study of prostate cancer risk across populations.Nature communications · 2025Article
- Uncovering Novel Susceptible Genes and Therapeutic Targets of Prostate Cancer: a Multi-omics Study Integrating Summary-based Mendelian Randomization Analysis and Molecular Docking.Biological procedures online · 2025Article
- Identification of prostate cancer potential therapeutic targets and virtual drug screening through combined Mendelian randomization study, Bayesian colocalization and molecular docking.Discover oncology · 2025Article
- The causal association between psoriasis and 32 types of cancer: a mendelian randomization study.Discover oncology · 2025Article
- New therapeutic targets and mechanisms of papillary thyroid carcinoma identified by multi-omics analysis.Discover oncology · 2025Article
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- Proteome-wide Mendelian randomization identifies causal plasma proteins in prostate cancer development.Human genomics · 2025Article
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- Integrative Analysis of GEO Datasets and Mendelian Randomization Reveals a Potential Role ofISOC1 in Renal Cell Carcinoma.Journal of Cancer · 2025Article
- Milk Thistle (Current medicinal chemistry · 2025Review
- Spatial proteomics and transcriptomics characterization of tissue and multiple cancer types including decalcified marrow.Cancer biomarkers : section A of Disease markers · 2025Article
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Abstract
backgroundUnderstanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention.
methodsWe investigated the association of 2002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomisation (MR) and colocalisation. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalisation were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumour tissue to assess their role in tumour aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets.
findingsWe identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which the majority replicated where data were available. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirmed an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also found an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions.
interpretationOur findings emphasise the importance of proteomics for improving our understanding of prostate cancer aetiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumours. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.
fundingThis work was supported by Cancer Research UK (grant no. C8221/A29017).
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