Prostatic trypsin-like kallikrein-related peptidases (KLKs) and other prostate-expressed tryptic proteinases as regulators of signalling via proteinase-activated receptors (PARs)

The prostate is a site of high expression of serine proteinases including members of the kallikrein-related peptidase (KLK) family, as well as other secreted and membrane-anchored serine proteinases. It has been known for some time that members of this enzyme family elicit cellular responses by acting directly on cells. More recently, it has been recognised that for serine proteinases with specificity for cleavage after arginine and lysine residues (trypsin-like or tryptic enzymes) these cellular responses are often mediated by cleavage of members of the proteinase-activated receptor (PAR) family - a four member sub-family of G protein-coupled receptors. Here, we review the expression of PARs in prostate, the ability of prostatic trypsin-like KLKs and other prostate-expressed tryptic enzymes to cleave PARs, as well as the prostate cancer-associated consequences of PAR activation. In addition, we explore the dysregulation of trypsin-like serine proteinase activity through the loss of normal inhibitory mechanisms and potential interactions between these dysregulated enzymes leading to aberrant PAR activation, intracellular signalling and cancer-promoting cellular changes

A Kallikrein 15 (KLK15) single nucleotide polymorphism located close to a novel exon shows evidence of association with poor ovarian cancer survival.

BACKGROUND: KLK15 over-expression is reported to be a significant predictor of reduced progression-free survival and overall survival in ovarian cancer. Our aim was to analyse the KLK15 gene for putative functional single nucleotide polymorphisms (SNPs) and assess the association of these and KLK15 HapMap tag SNPs with ovarian cancer survival. RESULTS: In silico analysis was performed to identify KLK15 regulatory elements and to classify potentially functional SNPs in these regions. After SNP validation and identification by DNA sequencing of ovarian cancer cell lines and aggressive ovarian cancer patients, 9 SNPs were shortlisted and genotyped using the Sequenom iPLEX Mass Array platform in a cohort of Australian ovarian cancer patients (N = 319). In the Australian dataset we observed significantly worse survival for the KLK15 rs266851 SNP in a dominant model (Hazard Ratio (HR) 1.42, 95% CI 1.02-1.96). This association was observed in the same direction in two independent datasets, with a combined HR for the three studies of 1.16 (1.00-1.34). This SNP lies 15 bp downstream of a novel exon and is predicted to be involved in mRNA splicing. The mutant allele is also predicted to abrogate an HSF-2 binding site. CONCLUSIONS: We provide evidence of association for the SNP rs266851 with ovarian cancer survival. Our results provide the impetus for downstream functional assays and additional independent validation studies to assess the role of KLK15 regulatory SNPs and KLK15 isoforms with alternative intracellular functional roles in ovarian cancer survival.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

OBJECTIVES: To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. DESIGN: Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. SETTING: Multiple institutions that were members of international PRACTICAL consortium. PARTICIPANTS: All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men. MAIN OUTCOME MEASURES: Prediction with hazard score of age of onset of aggressive cancer in validation set. RESULTS: In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score. CONCLUSIONS: Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa

Risk Analysis of Prostate Cancer in PRACTICAL, a Multinational Consortium, Using 25 Known Prostate Cancer Susceptibility Loci.

BACKGROUND: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. METHODS: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. RESULTS: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4-57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2-5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). CONCLUSIONS: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. IMPACT: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs.D F. Easton was recipient of the CR-UK grant C1287/A10118. R A. Eeles was recipient of the CR-UK grant C5047/A10692 and B E. Henderson was recipient of the NIH grant 1U19CA148537-01This is the author accepted manuscript. The final version is available via AACR at http://cebp.aacrjournals.org/content/early/2015/04/02/1055-9965.EPI-14-0317.long

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

A Plasma Biomarker Panel of Four MicroRNAs for the Diagnosis of Prostate Cancer

© 2018 The Author(s). Prostate cancer is diagnosed in over 1 million men every year globally, yet current diagnostic modalities are inadequate for identification of significant cancer and more reliable early diagnostic biomarkers are necessary for improved clinical management of prostate cancer patients. MicroRNAs (miRNAs) modulate important cellular processes/pathways contributing to cancer and are stably present in body fluids. In this study we profiled 372 cancer-associated miRNAs in plasma collected before (∼60% patients) and after/during commencement of treatment (∼40% patients), from age-matched prostate cancer patients and healthy controls, and observed elevated levels of 4 miRNAs - miR-4289, miR-326, miR-152-3p and miR-98-5p, which were validated in an independent cohort. The miRNA panel was able to differentiate between prostate cancer patients and controls (AUC = 0.88). Analysis of published miRNA transcriptomic data from clinical samples demonstrated low expression of miR-152-3p in tumour compared to adjacent non-malignant tissues. Overexpression of miR-152-3p increased proliferation and migration of prostate cancer cells, suggesting a role for this miRNA in prostate cancer pathogenesis, a concept that was supported by pathway analysis of predicted miR-152-3p target genes. In summary, a four miRNA panel, including miR-152-3p which likely targets genes with key roles in prostate cancer pathogenesis, has the potential to improve early prostate cancer diagnosis

Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation.

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.This work was supported by NIH fellowship F32 GM106584 (AG), NIH grants R01 MH101244(A.G.), R01 CA188392 (B.P.), U01 CA194393(B.P.), R01 GM107427 (M.L.F.), R01 CA193910 (M.L.F./M.P.) and Prostate Cancer Foundation Challenge Award (M.L.F./M.P.). This study makes use of data generated by the Wellcome Trust Case Control Consortium and the Wellcome Trust Sanger Institute. A full list of the investigators who contributed to the generation of the Wellcome Trust Case Control Consortium data is available on www.wtccc.org.uk. Funding for the Wellcome Trust Case Control Consortium project was provided by the Wellcome Trust under award 076113. This study makes use of data generated by the UK10K Consortium. A full list of the investigators who contributed to the generation of the data is available online (http://www.UK10K.org). The PRACTICAL consortium was supported by the following grants: European Commission's Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175), Cancer Research UK Grants C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, C16913/A6135 and The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative Grant: no. 1 U19 CA 148537-01 (the GAME-ON initiative); Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007 and C5047/A10692), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112—the GAME-ON initiative), the Department of Defense (W81XWH-10-1-0341), A Linneus Centre (Contract ID 70867902), Swedish Research Council (grant no K2010-70X-20430-04-3), the Swedish Cancer Foundation (grant no 09-0677), grants RO1CA056678, RO1CA082664 and RO1CA092579 from the US National Cancer Institute, National Institutes of Health; US National Cancer Institute (R01CA72818); support from The National Health and Medical Research Council, Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204, 940394 and 614296); NIH grants CA63464, CA54281 and CA098758; US National Cancer Institute (R01CA128813, PI: J.Y. Park); Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2–2009; DFNI-B01/28/2012); Cancer Research UK grants [C8197/A10123] and [C8197/A10865]; grant code G0500966/75466; NIHR Health Technology Assessment Programme (projects 96/20/06 and 96/20/99); Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466 and The NCRI, UK; The US Dept of Defense award W81XWH-04-1-0280; Australia Project Grant [390130, 1009458] and Enabling Grant [614296 to APCB]; the Prostate Cancer Foundation of Australia (Project Grant [PG7] and Research infrastructure grant [to APCB]); NIH grant R01 CA092447; Vanderbilt-Ingram Cancer Center (P30 CA68485); Cancer Research UK [C490/A10124] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge; Competitive Research Funding of the Tampere University Hospital (9N069 and X51003); Award Number P30CA042014 from the National Cancer Institute.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/0.1038/ncomms1097

A plasma biomarker panel of four MicroRNAs for the diagnosis of prostate cancer

Prostate cancer is diagnosed in over 1 million men every year globally, yet current diagnostic modalities are inadequate for identification of significant cancer and more reliable early diagnostic biomarkers are necessary for improved clinical management of prostate cancer patients. MicroRNAs (miRNAs) modulate important cellular processes/pathways contributing to cancer and are stably present in body fluids. In this study we profiled 372 cancer-associated miRNAs in plasma collected before (~60% patients) and after/during commencement of treatment (~40% patients), from age-matched prostate cancer patients and healthy controls, and observed elevated levels of 4 miRNAs - miR-4289, miR-326, miR-152-3p and miR-98-5p, which were validated in an independent cohort. The miRNA panel was able to differentiate between prostate cancer patients and controls (AUC = 0.88). Analysis of published miRNA transcriptomic data from clinical samples demonstrated low expression of miR-152-3p in tumour compared to adjacent non-malignant tissues. Overexpression of miR-152-3p increased proliferation and migration of prostate cancer cells, suggesting a role for this miRNA in prostate cancer pathogenesis, a concept that was supported by pathway analysis of predicted miR-152-3p target genes. In summary, a four miRNA panel, including miR-152-3p which likely targets genes with key roles in prostate cancer pathogenesis, has the potential to improve early prostate cancer diagnosis.Farhana Matin, Varinder Jeet, Leire Moya, Luke A. Selth, Suzanne Chambers, Australian Prostate Cancer BioResource, Judith A. Clements and Jyotsna Batr