MATERIALS AND METHODS: A total of 175 subjects comprising 84 patients and 91 healthy individuals were recruited. Multiplex PCR was optimized to co-amplify DYS388, DYS435, DYS437, and DYS439 loci. All samples were genotyped for alleles of four DYS loci using a Genetic Analysis System.
RESULTS: Of all DYS loci, allele 10 (A) of DYS388 had a significantly lower incidence of disease in compare with other alleles of this locus, while a higher incidence of disease was found among males who had either allele 12 (C) of DYS388 or allele 14 (E) of DYS439. Moreover, a total of 47 different haplotypes comprising different alleles of four DYS loci were found among the whole study samples, of which haplotypes AABC and CAAA showed a lower and higher frequency among cases than controls, respectively.
CONCLUSIONS: It is likely that Malaysian males who belong to Y-lineages with either allele 12 of DYS388, allele 14 of DYS439, or haplotype CAAA are more susceptible to develop prostate cancer, while those belonging to lineages with allele 10 of DYS388 or haplotype AABC are more resistant to the disease.
OBJECTIVE: To report the first year's screening results for all men at enrollment in the study.
DESIGN, SETTING AND PARTICIPANTS: We recruited men aged 40-69 yr with germline BRCA1/2 mutations and a control group of men who have tested negative for a pathogenic BRCA1 or BRCA2 mutation known to be present in their families. All men underwent prostate-specific antigen (PSA) testing at enrollment, and those men with PSA >3 ng/ml were offered prostate biopsy.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: PSA levels, PCa incidence, and tumour characteristics were evaluated. The Fisher exact test was used to compare the number of PCa cases among groups and the differences among disease types.
RESULTS AND LIMITATIONS: We recruited 2481 men (791 BRCA1 carriers, 531 BRCA1 controls; 731 BRCA2 carriers, 428 BRCA2 controls). A total of 199 men (8%) presented with PSA >3.0 ng/ml, 162 biopsies were performed, and 59 PCas were diagnosed (18 BRCA1 carriers, 10 BRCA1 controls; 24 BRCA2 carriers, 7 BRCA2 controls); 66% of the tumours were classified as intermediate- or high-risk disease. The positive predictive value (PPV) for biopsy using a PSA threshold of 3.0 ng/ml in BRCA2 mutation carriers was 48%-double the PPV reported in population screening studies. A significant difference in detecting intermediate- or high-risk disease was observed in BRCA2 carriers. Ninety-five percent of the men were white, thus the results cannot be generalised to all ethnic groups.
CONCLUSIONS: The IMPACT screening network will be useful for targeted PCa screening studies in men with germline genetic risk variants as they are discovered. These preliminary results support the use of targeted PSA screening based on BRCA genotype and show that this screening yields a high proportion of aggressive disease.
PATIENT SUMMARY: In this report, we demonstrate that germline genetic markers can be used to identify men at higher risk of prostate cancer. Targeting screening at these men resulted in the identification of tumours that were more likely to require treatment.
OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.
DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.
RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.
CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.
PATIENT SUMMARY: We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.
METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR).
RESULTS: We observed no significant association between genetic variants and prostate cancer survival.
CONCLUSIONS: Common genetic variants with large impact on prostate cancer survival were not observed in this study.
IMPACT: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes.
METHODS: We used three single nucleotide polymorphisms (SNPs) (rs8176746, rs505922, and rs8176704) to determine ABO genotype in 2,774 aggressive prostate cancer cases and 4,443 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). Unconditional logistic regression was used to calculate age and study-adjusted odds ratios and 95% confidence intervals for the association between blood type, genotype, and risk of aggressive prostate cancer (Gleason score ≥8 or locally advanced/metastatic disease (stage T3/T4/N1/M1).
RESULTS: We found no association between ABO blood type and risk of aggressive prostate cancer (Type A: OR = 0.97, 95%CI = 0.87-1.08; Type B: OR = 0.92, 95%CI =n0.77-1.09; Type AB: OR = 1.25, 95%CI = 0.98-1.59, compared to Type O, respectively). Similarly, there was no association between "dose" of A or B alleles and aggressive prostate cancer risk.
CONCLUSIONS: ABO blood type was not associated with risk of aggressive prostate cancer.
SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
MATERIALS AND METHODS: MicroRNA software predicted that miR21 targets VCL while miR29a targets CX3CL1. Twenty benign prostatic hyperplasia (BPH) and 16 high grade CaP formalinfixed paraffin embedded (FFPE) specimens were analysed. From the bone scan results, high grade CaP samples were further classified into CaP with no BM and CaP with BM. Transient transfection with respective microRNA inhibitors was done in both RWPE1 (normal) and PC3 cell lines. QPCR was performed in all FFPE samples and transfected cell lines to measure VCL and CX3CL1 levels.
RESULTS: QPCR confirmed that VCL messenger RNA (mRNA) was significantly down regulated while CX3CL1 was upregulated in all FFPE specimens. Transient transfection with microRNA inhibitors in PC3 cells followed by qPCR of the targeted genes showed that VCL mRNA was significantly up regulated while CX3CL1 mRNA was significantly downregulated compared to the RWPE1 case.
CONCLUSIONS: The downregulation of VCL in FFPE specimens is most likely regulated by miR21 based on the in vitro evidence but the exact mechanism of how miR21 can regulate VCL is unclear. Upregulated in CaP, CX3CL1 was found not regulated by miR29a. More microRNA screening is required to understand the regulation of this chemokine in CaP with bone metastasis. Understanding miRNAmRNA interactions may provide additional knowledge for individualized study of cancers.
METHODS: To this end, we undertook a pilot genome-wide CNV analysis approach in 36 subjects (18 patients with high-grade PCa and 18 controls that were matched by age and ethnicity) in search of more accurate biomarkers that could potentially explain susceptibility toward high-grade PCa. We conducted this study using the array comparative genomic hybridization technique. Array results were validated in 92 independent samples (46 high-grade PCa, 23 benign prostatic hyperplasia, and 23 healthy controls) using polymerase chain reaction-based copy number counting method.
RESULTS: A total of 314 CNV regions were found to be unique to PCa subjects in this cohort (P<0.05). A log2 ratio-based copy number analysis revealed 5 putative rare or novel CNV loci or both associated with susceptibility to PCa. The CNV gain regions were 1q21.3, 15q15, 7p12.1, and a novel CNV in PCa 12q23.1, harboring ARNT, THBS1, SLC5A8, and DDC genes that are crucial in the p53 and cancer pathways. A CNV loss and deletion event was observed at 8p11.21, which contains the SFRP1 gene from the Wnt signaling pathway. Cross-comparison analysis with genes associated to PCa revealed significant CNVs involved in biological processes that elicit cancer pathogenesis via cytokine production and endothelial cell proliferation.
CONCLUSION: In conclusion, we postulated that the CNVs identified in this study could provide an insight into the development of advanced PCa.
METHODS: PSAV was calculated using logistic regression to determine if PSA or PSAV predicted the result of prostate biopsy (PB) in men with elevated PSA values. Cox regression was used to determine whether PSA or PSAV predicted PSA elevation in men with low PSAs. Interaction terms were included in the models to determine whether BRCA status influenced the predictiveness of PSA or PSAV.
RESULTS: 1634 participants had ⩾3 PSA readings of whom 174 underwent PB and 45 PrCas diagnosed. In men with PSA >3.0 ng ml-l, PSAV was not significantly associated with presence of cancer or high-grade disease. PSAV did not add to PSA for predicting time to an elevated PSA. When comparing BRCA1/2 carriers to non-carriers, we found a significant interaction between BRCA status and last PSA before biopsy (P=0.031) and BRCA2 status and PSAV (P=0.024). However, PSAV was not predictive of biopsy outcome in BRCA2 carriers.
CONCLUSIONS: PSA is more strongly predictive of PrCa in BRCA carriers than non-carriers. We did not find evidence that PSAV aids decision-making for BRCA carriers over absolute PSA value alone.