Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects

• Published in: Human molecular genetics Vol. 32; no. 22; pp. 3181 - 3193
• Main Authors: Zhong, Hua, Zhu, Jingjing, Liu, Shuai, Ghoneim, Dalia H, Surendran, Praveen, Liu, Tao, Fahle, Sarah, Butterworth, Adam, Ashad Alam, Md, Deng, Hong-Wen, Yu, Herbert, Wu, Chong, Wu, Lang
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 03.11.2023
• Subjects: BASIC BIOLOGICAL SCIENCES; biological markers; Biomarkers, Tumor - genetics; Blood Proteins - genetics; genes; genetics; Humans; Male; Original; p-chloroamphetamine; passive cutaneous anaphylaxis; patient-controlled analgesia; posterior cerebral artery; principal component analysis; prostate cancer; Prostatic Neoplasms - genetics; prostate cancer; protein biomarker; risk; genetics
• ISSN: 0964-6906; 1460-2083; 1460-2083
• DOI: 10.1093/hmg/ddad139

Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. We developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.