Your browser doesn't support javascript.
loading
Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects.
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.
Affiliation
  • Zhong H; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States.
  • Zhu J; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States.
  • Liu S; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States.
  • Ghoneim DH; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States.
  • Surendran P; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Papworth Road, Cambridge Biomedical Campus, Cambridge, CB2 0BB, United Kingdom.
  • Liu T; Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States.
  • Fahle S; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Papworth Road, Cambridge Biomedical Campus, Cambridge, CB2 0BB, United Kingdom.
  • Butterworth A; MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Papworth Road, Cambridge Biomedical Campus, Cambridge, CB2 0BB, United Kingdom.
  • Ashad Alam M; NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Papworth Road, Cambridge Biomedical Campus, Cambridge, CB2 0BB, United Kingdom.
  • Deng HW; Tulane Center for Biomedical Informatics and Genomics, Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, 1440 Canal Street, New Orleans, LA 70112, United States.
  • Yu H; Center for Outcomes Research, Ochsner Clinic Foundation, New Orleans, LA 70121, United States.
  • Wu C; Tulane Center for Biomedical Informatics and Genomics, Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, 1440 Canal Street, New Orleans, LA 70112, United States.
  • Wu L; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, 701 Ilalo Street, Honolulu, HI 96813, United States.
Hum Mol Genet ; 32(22): 3181-3193, 2023 11 03.
Article in En | MEDLINE | ID: mdl-37622920
ABSTRACT
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.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Prostatic Neoplasms Type of study: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans / Male Language: En Journal: Hum Mol Genet Journal subject: BIOLOGIA MOLECULAR / GENETICA MEDICA Year: 2023 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Prostatic Neoplasms Type of study: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans / Male Language: En Journal: Hum Mol Genet Journal subject: BIOLOGIA MOLECULAR / GENETICA MEDICA Year: 2023 Type: Article Affiliation country: United States