Dataset Information

Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk.

ABSTRACT: Several blood protein biomarkers have been associated with prostate cancer risk. However, most studies assessed only a small number of biomarkers and/or included a small sample size. To identify novel protein biomarkers of prostate cancer risk, we studied 79,194 cases and 61,112 controls of European ancestry, included in the PRACTICAL/ELLIPSE consortia, using genetic instruments of protein quantitative trait loci for 1,478 plasma proteins. A total of 31 proteins were associated with prostate cancer risk including proteins encoded by GSTP1, whose methylation level was shown previously to be associated with prostate cancer risk, and MSMB, SPINT2, IGF2R, and CTSS, which were previously implicated as potential target genes of prostate cancer risk variants identified in genome-wide association studies. A total of 18 proteins inversely correlated and 13 positively correlated with prostate cancer risk. For 28 of the identified proteins, gene somatic changes of short indels, splice site, nonsense, or missense mutations were detected in patients with prostate cancer in The Cancer Genome Atlas. Pathway enrichment analysis showed that relevant genes were significantly enriched in cancer-related pathways. In conclusion, this study identifies 31 candidates of protein biomarkers for prostate cancer risk and provides new insights into the biology and genetics of prostate tumorigenesis. SIGNIFICANCE: Integration of genomics and proteomics data identifies biomarkers associated with prostate cancer risk.

SUBMITTER: Wu L

PROVIDER: S-EPMC6744971 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk.

Wu Lang L Shu Xiang X Bao Jiandong J Guo Xingyi X Kote-Jarai Zsofia Z Haiman Christopher A CA Eeles Rosalind A RA Zheng Wei W

Cancer research 20190723 18

Several blood protein biomarkers have been associated with prostate cancer risk. However, most studies assessed only a small number of biomarkers and/or included a small sample size. To identify novel protein biomarkers of prostate cancer risk, we studied 79,194 cases and 61,112 controls of European ancestry, included in the PRACTICAL/ELLIPSE consortia, using genetic instruments of protein quantitative trait loci for 1,478 plasma proteins. A total of 31 proteins were associated with prostate can ...[more]

PMID: 31337649

Similar Datasets

Project description:IntroductionObservational studies have reported a relationship between iron status and the risk of prostate cancer. However, it remains uncertain whether the association is causal or due to confounding or reverse causality. To further clarify the underlying causal relationship, we conducted a Mendelian randomization (MR) analysis.MethodsWe selected three genetic variants (rs1800562, rs1799945, and rs855791) closely correlated with four iron status biomarkers (serum iron, log-transformed ferritin, transferrin saturation, and transferrin) as instrumental variables. Summary statistics for prostate cancer were obtained from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome consortium including 79,148 cases and 61,106 controls of European ancestry. The inverse-variance weighted (IVW) method was conducted primarily to estimate the association of genetically predicted iron status and the risk of prostate cancer, supplemented with simple-median, weighted-median and maximum-likelihood methods as sensitivity analysis. MR-Egger regression was used to detect directional pleiotropy. We also conducted a meta-analysis of observational studies to assess the associations between iron status and the risk of prostate cancer.ResultsGenetically predicted increased iron status was associated with the decreased risk of prostate cancer, with odds ratio of 0.91 [95% confidence interval (CI): 0.84, 0.99; P = 0.035] for serum iron, 0.81 (95% CI: 0.65, 1.00; P = 0.046) for log- transformed ferritin, 0.94 (95% CI: 0.88, 0.99; P = 0.029) for transferrin saturation, and 1.15 (95% CI: 0.98, 1.35; P = 0.084) for transferrin (with higher transferrin levels representing lower systemic iron status), using the inverse-variance weighted method. Sensitivity analyses produced consistent associations, and MR-Egger regression indicated no potential pleiotropy. Our replication analysis based on FinnGen research project showed compatible results with our main analysis. Results from our meta-analysis similarly showed that serum ferritin [standardized mean difference (SMD): -1.25; 95% CI: -2.34, -0.16; P = 0.024] and transferrin saturation (SMD: -1.19; 95% CI: -2.34, -0.05; P = 0.042) were lower in patients with prostate cancer compared with that in controls.DiscussionOur study suggests a protective role of iron in the risk of prostate cancer, further investigations are required to clarify the underlying mechanisms.

Project description:PURPOSE: Prostate cancer is a bimodal disease with aggressive and indolent forms. Current prostate-specific-antigen testing and digital rectal examination screening provide ambiguous results leading to both under-and over-treatment. Accurate, consistent diagnosis is crucial to risk-stratify patients and facilitate clinical decision making as to treatment versus active surveillance. Diagnosis is currently achieved by needle biopsy, a painful procedure. Thus, there is a clinical need for a minimally-invasive test to determine prostate cancer aggressiveness. A blood sample to predict Gleason score, which is known to reflect aggressiveness of the cancer, could serve as such a test. MATERIALS AND METHODS: Blood mRNA was isolated from North American and Malaysian prostate cancer patients/controls. Microarray analysis was conducted utilizing the Affymetrix U133 plus 2·0 platform. Expression profiles from 255 patients/controls generated 85 candidate biomarkers. Following quantitative real-time PCR (qRT-PCR) analysis, ten disease-associated biomarkers remained for paired statistical analysis and normalization. RESULTS: Microarray analysis was conducted to identify 85 genes differentially expressed between aggressive prostate cancer (Gleason score ?8) and controls. Expression of these genes was qRT-PCR verified. Statistical analysis yielded a final seven-gene panel evaluated as six gene-ratio duplexes. This molecular signature predicted as aggressive (ie, Gleason score ?8) 55% of G6 samples, 49% of G7(3+4), 79% of G7(4+3) and 83% of G8-10, while rejecting 98% of controls. CONCLUSION: In this study, we have developed a novel, blood-based biomarker panel which can be used as the basis of a simple blood test to identify men with aggressive prostate cancer and thereby reduce the overdiagnosis and overtreatment that currently results from diagnosis using PSA alone. We discuss possible clinical uses of the panel to identify men more likely to benefit from biopsy and immediate therapy versus those more suited to an "active surveillance" strategy.

Dataset Information

Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk.

Publications

Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets