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Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics.
- Source :
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EBioMedicine [EBioMedicine] 2024 Jul; Vol. 105, pp. 105168. Date of Electronic Publication: 2024 Jun 14. - Publication Year :
- 2024
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Abstract
- Background: Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention.<br />Methods: We 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.<br />Findings: We 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.<br />Interpretation: Our 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.<br />Funding: This work was supported by Cancer Research UK (grant no. C8221/A29017).<br />Competing Interests: Declaration of interests This work was supported by Cancer Research UK (grant no. C8221/A29017). Anders Mälarstig, Åsa Hedman, and Marios Dimitriou are employees of Pfizer Inc. Anders Mälarstig declares stock options for Pfizer Inc. Alastair D. Lamb is Section Editor for Prostate Cancer and Web, British Journal of Urology International.<br /> (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
- Subjects :
- Humans
Male
Risk Factors
Genome-Wide Association Study
Biomarkers, Tumor genetics
Transcriptome
Genetic Predisposition to Disease
Gene Expression Profiling
Polymorphism, Single Nucleotide
Odds Ratio
Proteome
Age of Onset
Prostatic Neoplasms genetics
Prostatic Neoplasms pathology
Prostatic Neoplasms metabolism
Mendelian Randomization Analysis
Proteomics methods
Subjects
Details
- Language :
- English
- ISSN :
- 2352-3964
- Volume :
- 105
- Database :
- MEDLINE
- Journal :
- EBioMedicine
- Publication Type :
- Academic Journal
- Accession number :
- 38878676
- Full Text :
- https://doi.org/10.1016/j.ebiom.2024.105168