Evaluation of circulating plasma proteins in prostate cancer using mendelian randomization
- Long Cheng 1,2,3, Zeming Qiu 1,2,3, Xuewu Wu 1,2,3, Zhilong Dong 4,5,6,7
- Long Cheng 1,2,3, Zeming Qiu 1,2,3, Xuewu Wu 1,2,3
- 1Department of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730000, Gansu, China.
- 2Institute of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730030, Gansu, China.
- 3Gansu Province Clinical Research Center for urinary system disease, Lanzhou, 730030, Gansu, China.
- 4Department of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730000, Gansu, China. dzl19780829@163.com.
- 5Institute of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730030, Gansu, China. dzl19780829@163.com.
- 6Gansu Province Clinical Research Center for urinary system disease, Lanzhou, 730030, Gansu, China. dzl19780829@163.com.
- 7Department of Urology, The Second Hospital & Clinical School, Lanzhou University, Lanzhou, 730000, Gansu, China. dzl19780829@163.com.
- 0Department of Urology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, 730000, Gansu, China.
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View abstract on PubMed
Summary
This summary is machine-generated.This study identified nine plasma proteins linked to increased prostate cancer (PCa) risk and four to decreased risk. Several proteins show potential as drug targets for PCa, with some influenced by lifestyle factors.
Area Of Science
- Proteomics
- Genetics
- Oncology
Background
- Plasma proteins are crucial for identifying cancer diagnostic and therapeutic targets.
- Understanding causal links between plasma proteins and prostate cancer (PCa) is essential.
Purpose Of The Study
- To investigate causal associations between plasma proteins and PCa.
- To explore downstream effects of plasma proteins and identify upstream modulators.
Main Methods
- Proteome-wide Mendelian randomization was employed to assess causal effects.
- Summary-statistics-based Mendelian Randomization (SMR) and colocalization analyses identified gene-PCa associations.
- Phenome-wide and lifestyle factor analyses explored downstream phenotypes and upstream modulators.
Main Results
- Nine proteins showed a positive genetic association with PCa risk; four showed an inverse association.
- ZG16B, PEX14, and NAPG were identified as potential PCa drug targets.
- Ten plasma proteins were found to be potentially modulated by lifestyle factors.
Conclusions
- Plasma proteins are genetically associated with PCa risk.
- Identified proteins represent potential therapeutic targets for PCa.
- Findings enhance understanding of PCa's molecular basis, prevention, and treatment.
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