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- Desai, Trishna A., et al.
(författare)
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Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics
- 2024
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 105
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Tidskriftsartikel (refereegranskat)abstract
- Background Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention. 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 -speci fi c 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. Findings We identi fi ed 20 proteins genetically linked to prostate cancer risk (14 for overall [8 speci fi c], 7 for aggressive [3 speci fi c], and 8 for early onset disease [2 speci fi c]), 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 con fi rmed 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 identi fi ed MSMB as the genome-wide top -most predictive gene to distinguish benign regions from high grade cancer regions that comparatively had fi ve -fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk also mapped to existing therapeutic interventions. Interpretation Our fi ndings 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 bene fi t 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.
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2. |
- Smith-Byrne, Karl, et al.
(författare)
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Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers
- 2024
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 15:1
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Tidskriftsartikel (refereegranskat)abstract
- Circulating proteins can reveal key pathways to cancer and identify therapeutic targets for cancer prevention. We investigate 2,074 circulating proteins and risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) using cis protein Mendelian randomisation and colocalization. We conduct additional analyses to identify adverse side-effects of altering risk proteins and map cancer risk proteins to drug targets. Here we find 40 proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment: 2.27, 1.88-2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [0.79, 0.73-0.85]. We also identify potential adverse effects of protein-altering interventions to reduce cancer risk, such as hypertension. Additionally, we report 18 proteins associated with cancer risk that map to existing drugs and 15 that are not currently under clinical investigation. In sum, we identify protein-cancer links that improve our understanding of cancer aetiology. We also demonstrate that the wider consequence of any protein-altering intervention on well-being and morbidity is required to interpret any utility of proteins as potential future targets for therapeutic prevention.
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