Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention.
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.
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.
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.
This work was supported by Cancer Research UK (grant no. C8221/A29017).
EBioMedicine. 2024 Jun 14 [Epub ahead of print]
Trishna A Desai, Åsa K Hedman, Marios Dimitriou, Mine Koprulu, Sandy Figiel, Wencheng Yin, Mattias Johansson, Eleanor L Watts, Joshua R Atkins, Aleksandr V Sokolov, Helgi B Schiöth, Marc J Gunter, Konstantinos K Tsilidis, Richard M Martin, Maik Pietzner, Claudia Langenberg, Ian G Mills, Alastair D Lamb, Anders Mälarstig, Tim J Key, PRACTICAL Consortium , Ruth C Travis, Karl Smith-Byrne
Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom. Electronic address: ., External Science and Innovation, Pfizer Worldwide Research, Development and Medical, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden., MRC Epidemiology Unit, University of Cambridge, United Kingdom., University of Oxford, Nuffield Department of Surgical Sciences, Oxford, United Kingdom., Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France., Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA., Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom., Department of Surgical Sciences, Functional Pharmacology and Neuroscience Uppsala University, 75124, Uppsala, Sweden., Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC-WHO), Lyon, France; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, United Kingdom., Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London, W2 1PG, United Kingdom; Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece., Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; NIHR Bristol Biomedical Research Centre, Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, United Kingdom., MRC Epidemiology Unit, University of Cambridge, United Kingdom; Computational Medicine, Berlin Institute of HealthHealth (BIH) at Charité - Univeritätsmedizin- Universitätsmedizin Berlin, Berlin, Germany; Precision Healthcare University Research Institute, Queen Mary University of London, London, United Kingdom.