Publications by authors named "Colin S Cooper"

65 Publications

Convergence of Prognostic Gene Signatures Suggests Underlying Mechanisms of Human Prostate Cancer Progression.

Genes (Basel) 2020 07 16;11(7). Epub 2020 Jul 16.

Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.

The highly heterogeneous clinical course of human prostate cancer has prompted the development of multiple RNA biomarkers and diagnostic tools to predict outcome for individual patients. Biomarker discovery is often unstable with, for example, small changes in discovery dataset configuration resulting in large alterations in biomarker composition. Our hypothesis, which forms the basis of this current study, is that highly significant overlaps occurring between gene signatures obtained using entirely different approaches indicate genes fundamental for controlling cancer progression. For prostate cancer, we found two sets of signatures that had significant overlaps suggesting important genes ( < 10 for paired overlaps, hypergeometrical test). These overlapping signatures defined a core set of genes linking hormone signalling (HES6-AR), cell cycle progression (Prolaris) and a molecular subgroup of patients (PCS1) derived by Non Negative Matrix Factorization (NNMF) of control pathways, together designated as SIG-HES6. The second set (designated SIG-DESNT) consisted of the DESNT diagnostic signature and a second NNMF signature PCS3. Stratifications using SIG-HES6 (HES6, PCS1, Prolaris) and SIG-DESNT (DESNT) classifiers frequently detected the same individual high-risk cancers, indicating that the underlying mechanisms associated with SIG-HES6 and SIG-DESNT may act together to promote aggressive cancer development. We show that the use of combinations of a SIG-HES6 signature together with DESNT substantially increases the ability to predict poor outcome, and we propose a model for prostate cancer development involving co-operation between the SIG-HES6 and SIG-DESNT pathways that has implication for therapeutic design.
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http://dx.doi.org/10.3390/genes11070802DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397325PMC
July 2020

A novel stratification framework for predicting outcome in patients with prostate cancer.

Br J Cancer 2020 05 20;122(10):1467-1476. Epub 2020 Mar 20.

Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, Norfolk, UK.

Background: Unsupervised learning methods, such as Hierarchical Cluster Analysis, are commonly used for the analysis of genomic platform data. Unfortunately, such approaches ignore the well-documented heterogeneous composition of prostate cancer samples. Our aim is to use more sophisticated analytical approaches to deconvolute the structure of prostate cancer transcriptome data, providing novel clinically actionable information for this disease.

Methods: We apply an unsupervised model called Latent Process Decomposition (LPD), which can handle heterogeneity within individual cancer samples, to genome-wide expression data from eight prostate cancer clinical series, including 1,785 malignant samples with the clinical endpoints of PSA failure and metastasis.

Results: We show that PSA failure is correlated with the level of an expression signature called DESNT (HR = 1.52, 95% CI = [1.36, 1.7], P = 9.0 × 10, Cox model), and that patients with a majority DESNT signature have an increased metastatic risk (X test, P = 0.0017, and P = 0.0019). In addition, we develop a stratification framework that incorporates DESNT and identifies three novel molecular subtypes of prostate cancer.

Conclusions: These results highlight the importance of using more complex approaches for the analysis of genomic data, may assist drug targeting, and have allowed the construction of a nomogram combining DESNT with other clinical factors for use in clinical management.
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http://dx.doi.org/10.1038/s41416-020-0799-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217762PMC
May 2020

Development of a multivariable risk model integrating urinary cell DNA methylation and cell-free RNA data for the detection of significant prostate cancer.

Prostate 2020 05 9;80(7):547-558. Epub 2020 Mar 9.

Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, UK.

Background: Prostate cancer exhibits severe clinical heterogeneity and there is a critical need for clinically implementable tools able to precisely and noninvasively identify patients that can either be safely removed from treatment pathways or those requiring further follow up. Our objectives were to develop a multivariable risk prediction model through the integration of clinical, urine-derived cell-free messenger RNA (cf-RNA) and urine cell DNA methylation data capable of noninvasively detecting significant prostate cancer in biopsy naïve patients.

Methods: Post-digital rectal examination urine samples previously analyzed separately for both cellular methylation and cf-RNA expression within the Movember GAP1 urine biomarker cohort were selected for a fully integrated analysis (n = 207). A robust feature selection framework, based on bootstrap resampling and permutation, was utilized to find the optimal combination of clinical and urinary markers in a random forest model, deemed ExoMeth. Out-of-bag predictions from ExoMeth were used for diagnostic evaluation in men with a clinical suspicion of prostate cancer (PSA ≥ 4 ng/mL, adverse digital rectal examination, age, or lower urinary tract symptoms).

Results: As ExoMeth risk score (range, 0-1) increased, the likelihood of high-grade disease being detected on biopsy was significantly greater (odds ratio = 2.04 per 0.1 ExoMeth increase, 95% confidence interval [CI]: 1.78-2.35). On an initial TRUS biopsy, ExoMeth accurately predicted the presence of Gleason score ≥3 + 4, area under the receiver-operator characteristic curve (AUC) = 0.89 (95% CI: 0.84-0.93) and was additionally capable of detecting any cancer on biopsy, AUC = 0.91 (95% CI: 0.87-0.95). Application of ExoMeth provided a net benefit over current standards of care and has the potential to reduce unnecessary biopsies by 66% when a risk threshold of 0.25 is accepted.

Conclusion: Integration of urinary biomarkers across multiple assay methods has greater diagnostic ability than either method in isolation, providing superior predictive ability of biopsy outcomes. ExoMeth represents a more holistic view of urinary biomarkers and has the potential to result in substantial changes to how patients suspected of harboring prostate cancer are diagnosed.
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http://dx.doi.org/10.1002/pros.23968DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7383590PMC
May 2020

The landscape of viral associations in human cancers.

Nat Genet 2020 03 5;52(3):320-330. Epub 2020 Feb 5.

Division of Molecular Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, for which whole-genome and-for a subset-whole-transcriptome sequencing data from 2,658 cancers across 38 tumor types was aggregated, we systematically investigated potential viral pathogens using a consensus approach that integrated three independent pipelines. Viruses were detected in 382 genome and 68 transcriptome datasets. We found a high prevalence of known tumor-associated viruses such as Epstein-Barr virus (EBV), hepatitis B virus (HBV) and human papilloma virus (HPV; for example, HPV16 or HPV18). The study revealed significant exclusivity of HPV and driver mutations in head-and-neck cancer and the association of HPV with APOBEC mutational signatures, which suggests that impaired antiviral defense is a driving force in cervical, bladder and head-and-neck carcinoma. For HBV, HPV16, HPV18 and adeno-associated virus-2 (AAV2), viral integration was associated with local variations in genomic copy numbers. Integrations at the TERT promoter were associated with high telomerase expression evidently activating this tumor-driving process. High levels of endogenous retrovirus (ERV1) expression were linked to a worse survival outcome in patients with kidney cancer.
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http://dx.doi.org/10.1038/s41588-019-0558-9DOI Listing
March 2020

Methodology for the at-home collection of urine samples for prostate cancer detection.

Biotechniques 2020 02 29;68(2):65-71. Epub 2019 Nov 29.

Norwich Medical School, University of East Anglia, Norwich, UK.

Urine from patients with prostate cancer (PCa) contains gene transcripts that have been used for PCa diagnosis and prognosis. Historically, patient urine samples have been collected after a digital rectal examination of the prostate, which was thought necessary to boost the levels of prostatic secretions in the urine. We herein describe methodology that allows urine to be collected by patients at home and then posted to a laboratory for analysis. RNA yields and quality were comparable to those for post digital rectal examination urine, and there was improved sensitivity for the detection of transcripts by RT-PCR. The At-Home collection protocol has opened up the potential to perform large-scale PCa studies without the inconvenience, cost, discomfort and expense of patients having to visit the clinic.
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http://dx.doi.org/10.2144/btn-2019-0092DOI Listing
February 2020

SEPATH: benchmarking the search for pathogens in human tissue whole genome sequence data leads to template pipelines.

Genome Biol 2019 10 22;20(1):208. Epub 2019 Oct 22.

Norwich Medical School, University of East Anglia, Bob Champion Research and Education Building, Norwich, NR4 7UQ, UK.

Background: Human tissue is increasingly being whole genome sequenced as we transition into an era of genomic medicine. With this arises the potential to detect sequences originating from microorganisms, including pathogens amid the plethora of human sequencing reads. In cancer research, the tumorigenic ability of pathogens is being recognized, for example, Helicobacter pylori and human papillomavirus in the cases of gastric non-cardia and cervical carcinomas, respectively. As of yet, no benchmark has been carried out on the performance of computational approaches for bacterial and viral detection within host-dominated sequence data.

Results: We present the results of benchmarking over 70 distinct combinations of tools and parameters on 100 simulated cancer datasets spiked with realistic proportions of bacteria. mOTUs2 and Kraken are the highest performing individual tools achieving median genus-level F1 scores of 0.90 and 0.91, respectively. mOTUs2 demonstrates a high performance in estimating bacterial proportions. Employing Kraken on unassembled sequencing reads produces a good but variable performance depending on post-classification filtering parameters. These approaches are investigated on a selection of cervical and gastric cancer whole genome sequences where Alphapapillomavirus and Helicobacter are detected in addition to a variety of other interesting genera.

Conclusions: We provide the top-performing pipelines from this benchmark in a unifying tool called SEPATH, which is amenable to high throughput sequencing studies across a range of high-performance computing clusters. SEPATH provides a benchmarked and convenient approach to detect pathogens in tissue sequence data helping to determine the relationship between metagenomics and disease.
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http://dx.doi.org/10.1186/s13059-019-1819-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805339PMC
October 2019

A Four-Group Urine Risk Classifier for Predicting Outcome in Prostate Cancer Patients.

BJU Int 2019 May 20. Epub 2019 May 20.

Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, UK.

Objectives: To develop a risk classifier using urine-derived extracellular vesicle RNA (UEV-RNA) capable of providing diagnostic information of disease status prior to biopsy, and prognostic information for men on active surveillance (AS).

Patients And Methods: Post-digital rectal examination UEV-RNA expression profiles from urine (n = 535, multiple centres) were interrogated with a curated NanoString panel. A LASSO-based Continuation-Ratio model was built to generate four Prostate-Urine-Risk (PUR) signatures for predicting the probability of normal tissue (PUR-1), D'Amico Low-risk (PUR-2), Intermediate-risk (PUR-3), and High-risk (PUR-4) PCa. This model was applied to a test cohort (n = 177) for diagnostic evaluation, and to an AS sub-cohort (n = 87) for prognostic evaluation.

Results: Each PUR signature was significantly associated with its corresponding clinical category (p<0.001). PUR-4 status predicted the presence of clinically significant Intermediate or High-risk disease, AUC = 0.77 (95% CI: 0.70-0.84). Application of PUR provided a net benefit over current clinical practice. In an AS sub-cohort (n=87), groups defined by PUR status and proportion of PUR-4 had a significant association with time to progression (p<0.001; IQR HR = 2.86, 95% CI:1.83-4.47). PUR-4, when utilised continuously, dichotomised patient groups with differential progression rates of 10% and 60% five years post-urine collection (p<0.001, HR = 8.23, 95% CI:3.26-20.81).

Conclusion: UEV-RNA can provide diagnostic information of aggressive PCa prior to biopsy, and prognostic information for men on AS. PUR represents a new & versatile biomarker that could result in substantial alterations to current treatment of PCa patients. This article is protected by copyright. All rights reserved.
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http://dx.doi.org/10.1111/bju.14811DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851983PMC
May 2019

Transcriptional changes in prostate of men on active surveillance after a 12-mo glucoraphanin-rich broccoli intervention-results from the Effect of Sulforaphane on prostate CAncer PrEvention (ESCAPE) randomized controlled trial.

Am J Clin Nutr 2019 04;109(4):1133-1144

Quadram Institute Bioscience, Norwich, United Kingdom.

Background: Epidemiological evidence suggests that consumption of cruciferous vegetables is associated with reduced risk of prostate cancer progression, largely attributed to the biological activity of glucosinolate degradation products, such as sulforaphane derived from glucoraphanin. Because there are few therapeutic interventions for men on active surveillance for prostate cancer to reduce the risk of cancer progression, dietary approaches are an appealing option for patients.

Objective: We evaluated whether consumption of a glucoraphanin-rich broccoli soup for 1 y leads to changes in gene expression in prostate tissue of men with localized prostate cancer.

Methods: Forty-nine men on active surveillance completed a 3-arm parallel randomized double-blinded intervention study for 12 mo and underwent transperineal template biopsy procedures and dietary assessment at the start and end of the study. Patients received a weekly 300 mL portion of soup made from a standard broccoli (control) or from 1 of 2 experimental broccoli genotypes with enhanced concentrations of glucoraphanin, delivering 3 and 7 times that of the control, respectively. Gene expression in tissues from each patient obtained before and after the dietary intervention was quantified by RNA sequencing followed by gene set enrichment analyses.

Results: In the control arm, there were several hundred changes in gene expression in nonneoplastic tissue during the 12 mo. These were associated with an increase in expression of potentially oncogenic pathways including inflammation processes and epithelial-mesenchymal transition. Changes in gene expression and associated oncogenic pathways were attenuated in men on the glucoraphanin-rich broccoli soup in a dose-dependent manner. Although the study was not powered to assess clinical progression, an inverse association between consumption of cruciferous vegetables and cancer progression was observed.

Conclusion: Consuming glucoraphanin-rich broccoli soup affected gene expression in the prostate of men on active surveillance, consistent with a reduction in the risk of cancer progression. This trial was registered at clinicaltrials.gov as NCT01950143.
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http://dx.doi.org/10.1093/ajcn/nqz012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6462431PMC
April 2019

epiCaPture: A Urine DNA Methylation Test for Early Detection of Aggressive Prostate Cancer.

JCO Precis Oncol 2019 14;2019. Epub 2019 Jan 14.

University College Dublin.

Purpose: Liquid biopsies that noninvasively detect molecular correlates of aggressive prostate cancer (PCa) could be used to triage patients, reducing the burdens of unnecessary invasive prostate biopsy and enabling early detection of high-risk disease. DNA hypermethylation is among the earliest and most frequent aberrations in PCa. We investigated the accuracy of a six-gene DNA methylation panel (Epigenetic Cancer of the Prostate Test in Urine [epiCaPture]) at detecting PCa, high-grade (Gleason score greater than or equal to 8) and high-risk (D'Amico and Cancer of the Prostate Risk Assessment] PCa from urine.

Patients And Methods: Prognostic utility of epiCaPture genes was first validated in two independent prostate tissue cohorts. epiCaPture was assessed in a multicenter prospective study of 463 men undergoing prostate biopsy. epiCaPture was performed by quantitative methylation-specific polymerase chain reaction in DNA isolated from prebiopsy urine sediments and evaluated by receiver operating characteristic and decision curves (clinical benefit). The epiCaPture score was developed and validated on a two thirds training set to one third test set.

Results: Higher methylation of epiCaPture genes was significantly associated with increasing aggressiveness in PCa tissues. In urine, area under the receiver operating characteristic curve was 0.64, 0.86, and 0.83 for detecting PCa, high-grade PCa, and high-risk PCa, respectively. Decision curves revealed a net benefit across relevant threshold probabilities. Independent analysis of two epiCaPture genes in the same clinical cohort provided analytical validation. Parallel epiCaPture analysis in urine and matched biopsy cores showed added value of a liquid biopsy.

Conclusion: epiCaPture is a urine DNA methylation test for high-risk PCa. Its tumor specificity out-performs that of prostate-specific antigen (greater than 3 ng/mL). Used as an adjunct to prostate-specific antigen, epiCaPture could aid patient stratification to determine need for biopsy.
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http://dx.doi.org/10.1200/PO.18.00134DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383793PMC
January 2019

ORIF versus arthroplasty for open proximal humerus fractures: Nationwide Inpatient Sample data between 1998 and 2013.

J Orthop Traumatol 2018 Aug 22;19(1):12. Epub 2018 Aug 22.

Department of Orthopaedic Surgery and Rehabilitation Medicine, State University of New York, Downstate Medical Center, 450 Clarkson Avenue, Box 30, Brooklyn, NY, 11203, USA.

Background: Limited data exists in analyzing open reduction and internal fixation (ORIF) and arthroplasty in the management of open proximal humerus fractures. We analyzed differences in hospital course between these procedures, patient demographics, complication rate, length of stay, hospital charges, and mortality rate.

Materials And Methods: This is a retrospective review of the Nationwide Inpatient Sample database. ICD-9 codes identified patients hospitalized for open proximal humerus fractures from 1998 to 2013 who underwent ORIF or shoulder arthroplasty (hemi-, total, or reverse). Demographics and in-hospital complications were compared. Logistic regression controlling for age, gender, and Deyo index tested the impact of ORIF vs ARTH on any complications.

Results: Seven hundred thirty patients were included (ORIF, n = 662 vs ARTH, n = 68). ORIF patients were younger (p < 0.001), more likely to be males (p < 0.001), and had a lower Deyo score (p = 0.012). Both groups had comparable complication rates (21.4% vs 18.0%, p = 0.535), lengths of stay (7.86 days vs 7.44 days, p = 0.833), hospital charges ($76,998 vs $64,133, p = 0.360), and mortality rates (0.2% vs 0%, p = 0.761). Type of surgery was not a predictor of any complications (OR = 0.67 [95% CI 0.33-1.35], p = 0.266), extended length of stay (OR = 1.01 [95% CI 0.58-1.78], p = 0.967), or high hospital charges (OR = 1.39 [95% CI 0.68-2.86], p = 0.366).

Conclusion: We revealed no differences in hospital course between ORIF and arthroplasty for management of open proximal humerus fractures. Although differences in demographics existed, no differences in complication rates, length of stay, hospital charges and mortality rates were noted. Future studies can evaluate the long-term outcomes of these procedures.

Level Of Evidence: Level III.
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http://dx.doi.org/10.1186/s10195-018-0503-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6103959PMC
August 2018

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets.

Nat Genet 2018 05 16;50(5):682-692. Epub 2018 Apr 16.

The Institute of Cancer Research, London, UK.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.
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http://dx.doi.org/10.1038/s41588-018-0086-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372064PMC
May 2018

Appraising the relevance of DNA copy number loss and gain in prostate cancer using whole genome DNA sequence data.

PLoS Genet 2017 Sep 25;13(9):e1007001. Epub 2017 Sep 25.

Norwich Medical School, University of East Anglia, Norwich, Norfolk, United Kingdom.

A variety of models have been proposed to explain regions of recurrent somatic copy number alteration (SCNA) in human cancer. Our study employs Whole Genome DNA Sequence (WGS) data from tumor samples (n = 103) to comprehensively assess the role of the Knudson two hit genetic model in SCNA generation in prostate cancer. 64 recurrent regions of loss and gain were detected, of which 28 were novel, including regions of loss with more than 15% frequency at Chr4p15.2-p15.1 (15.53%), Chr6q27 (16.50%) and Chr18q12.3 (17.48%). Comprehensive mutation screens of genes, lincRNA encoding sequences, control regions and conserved domains within SCNAs demonstrated that a two-hit genetic model was supported in only a minor proportion of recurrent SCNA losses examined (15/40). We found that recurrent breakpoints and regions of inversion often occur within Knudson model SCNAs, leading to the identification of ZNF292 as a target gene for the deletion at 6q14.3-q15 and NKX3.1 as a two-hit target at 8p21.3-p21.2. The importance of alterations of lincRNA sequences was illustrated by the identification of a novel mutational hotspot at the KCCAT42, FENDRR, CAT1886 and STCAT2 loci at the 16q23.1-q24.3 loss. Our data confirm that the burden of SCNAs is predictive of biochemical recurrence, define nine individual regions that are associated with relapse, and highlight the possible importance of ion channel and G-protein coupled-receptor (GPCR) pathways in cancer development. We concluded that a two-hit genetic model accounts for about one third of SCNA indicating that mechanisms, such haploinsufficiency and epigenetic inactivation, account for the remaining SCNA losses.
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http://dx.doi.org/10.1371/journal.pgen.1007001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5628936PMC
September 2017

DESNT: A Poor Prognosis Category of Human Prostate Cancer.

Eur Urol Focus 2018 12 6;4(6):842-850. Epub 2017 Mar 6.

Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, UK. Electronic address:

Background: A critical problem in the clinical management of prostate cancer is that it is highly heterogeneous. Accurate prediction of individual cancer behaviour is therefore not achievable at the time of diagnosis leading to substantial overtreatment. It remains an enigma that, in contrast to breast cancer, unsupervised analyses of global expression profiles have not currently defined robust categories of prostate cancer with distinct clinical outcomes.

Objective: To devise a novel classification framework for human prostate cancer based on unsupervised mathematical approaches.

Design, Setting, And Participants: Our analyses are based on the hypothesis that previous attempts to classify prostate cancer have been unsuccessful because individual samples of prostate cancer frequently have heterogeneous compositions. To address this issue, we applied an unsupervised Bayesian procedure called Latent Process Decomposition to four independent prostate cancer transcriptome datasets obtained using samples from prostatectomy patients and containing between 78 and 182 participants.

Outcome Measurements And Statistical Analysis: Biochemical failure was assessed using log-rank analysis and Cox regression analysis.

Results And Limitations: Application of Latent Process Decomposition identified a common process in all four independent datasets examined. Cancers assigned to this process (designated DESNT cancers) are characterized by low expression of a core set of 45 genes, many encoding proteins involved in the cytoskeleton machinery, ion transport, and cell adhesion. For the three datasets with linked prostate-specific antigen failure data following prostatectomy, patients with DESNT cancer exhibited poor outcome relative to other patients (p=2.65×10, p=4.28×10, and p=2.98×10). When these three datasets were combined the independent predictive value of DESNT membership was p=1.61×10 compared with p=1.00×10 for Gleason sum. A limitation of the study is that only prediction of prostate-specific antigen failure was examined.

Conclusions: Our results demonstrate the existence of a novel poor prognosis category of human prostate cancer and will assist in the targeting of therapy, helping avoid treatment-associated morbidity in men with indolent disease.

Patient Summary: Prostate cancer, unlike breast cancer, does not have a robust classification framework. We propose that this failure has occurred because prostate cancer samples selected for analysis frequently have heterozygous compositions (individual samples are made up of many different parts that each have different characteristics). Applying a mathematical approach that can overcome this problem we identify a novel poor prognosis category of human prostate cancer called DESNT.
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http://dx.doi.org/10.1016/j.euf.2017.01.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5669460PMC
December 2018

Identification of FBXL4 as a Metastasis Associated Gene in Prostate Cancer.

Sci Rep 2017 07 11;7(1):5124. Epub 2017 Jul 11.

Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.

Prostate cancer is the most common cancer among western men, with a significant mortality and morbidity reported for advanced metastatic disease. Current understanding of metastatic disease is limited due to difficulty of sampling as prostate cancer mainly metastasizes to bone. By analysing prostate cancer bone metastases using high density microarrays, we found a common genomic copy number loss at 6q16.1-16.2, containing the FBXL4 gene, which was confirmed in larger series of bone metastases by fluorescence in situ hybridisation (FISH). Loss of FBXL4 was also detected in primary tumours and it was highly associated with prognostic factors including high Gleason score, clinical stage, prostate-specific antigen (PSA) and extent of disease, as well as poor patient survival, suggesting that FBXL4 loss contributes to prostate cancer progression. We also demonstrated that FBXL4 deletion is detectable in circulating tumour cells (CTCs), making it a potential prognostic biomarker by 'liquid biopsy'. In vitro analysis showed that FBXL4 plays a role in regulating the migration and invasion of prostate cancer cells. FBXL4 potentially controls cancer metastasis through regulation of ERLEC1 levels. Therefore, FBXL4 could be a potential novel prostate cancer suppressor gene, which may prevent cancer progression and metastasis through controlling cell invasion.
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http://dx.doi.org/10.1038/s41598-017-05209-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505985PMC
July 2017

Detection of prostate cancer-specific transcripts in extracellular vesicles isolated from post-DRE urine.

Prostate 2017 Jun 17;77(9):990-999. Epub 2017 Apr 17.

Department of Urology, Emory University School of Medicine, Atlanta, Georgia.

Background: The measurement of gene expression in post-digital rectal examination (DRE) urine specimens provides a non-invasive method to determine a patient's risk of prostate cancer. Many currently available assays use whole urine or cell pellets for the analysis of prostate cancer-associated genes, although the use of extracellular vesicles (EVs) has also recently been of interest. We investigated the expression of prostate-, kidney-, and bladder-specific transcripts and known prostate cancer biomarkers in urine EVs.

Methods: Cell pellets and EVs were recovered from post-DRE urine specimens, with the total RNA yield and quality determined by Bioanalyzer. The levels of prostate, kidney, and bladder-associated transcripts in EVs were assessed by TaqMan qPCR and targeted sequencing.

Results: RNA was more consistently recovered from the urine EV specimens, with over 80% of the patients demonstrating higher RNA yields in the EV fraction as compared to urine cell pellets. The median EV RNA yield of 36.4 ng was significantly higher than the median urine cell pellet RNA yield of 4.8 ng. Analysis of the post-DRE urine EVs indicated that prostate-specific transcripts were more abundant than kidney- or bladder-specific transcripts. Additionally, patients with prostate cancer had significantly higher levels of the prostate cancer-associated genes PCA3 and ERG.

Conclusions: Post-DRE urine EVs are a viable source of prostate-derived RNAs for biomarker discovery and prostate cancer status can be distinguished from analysis of these specimens. Continued analysis of urine EVs offers the potential discovery of novel biomarkers for pre-biopsy prostate cancer detection.
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http://dx.doi.org/10.1002/pros.23355DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5907935PMC
June 2017

Prostate cancer risk regions at 8q24 and 17q24 are differentially associated with somatic TMPRSS2:ERG fusion status.

Hum Mol Genet 2016 12;25(24):5490-5499

Institute of Human Genetics, University of Ulm, Ulm, Germany.

Molecular and epidemiological differences have been described between TMPRSS2:ERG fusion-positive and fusion-negative prostate cancer (PrCa). Assuming two molecularly distinct subtypes, we have examined 27 common PrCa risk variants, previously identified in genome-wide association studies, for subtype specific associations in a total of 1221 TMPRSS2:ERG phenotyped PrCa cases. In meta-analyses of a discovery set of 552 cases with TMPRSS2:ERG data and 7650 unaffected men from five centers we have found support for the hypothesis that several common risk variants are associated with one particular subtype rather than with PrCa in general. Risk variants were analyzed in case-case comparisons (296 TMPRSS2:ERG fusion-positive versus 256 fusion-negative cases) and an independent set of 669 cases with TMPRSS2:ERG data was established to replicate the top five candidates. Significant differences (P < 0.00185) between the two subtypes were observed for rs16901979 (8q24) and rs1859962 (17q24), which were enriched in TMPRSS2:ERG fusion-negative (OR = 0.53, P = 0.0007) and TMPRSS2:ERG fusion-positive PrCa (OR = 1.30, P = 0.0016), respectively. Expression quantitative trait locus analysis was performed to investigate mechanistic links between risk variants, fusion status and target gene mRNA levels. For rs1859962 at 17q24, genotype dependent expression was observed for the candidate target gene SOX9 in TMPRSS2:ERG fusion-positive PrCa, which was not evident in TMPRSS2:ERG negative tumors. The present study established evidence for the first two common PrCa risk variants differentially associated with TMPRSS2:ERG fusion status. TMPRSS2:ERG phenotyping of larger studies is required to determine comprehensive sets of variants with subtype-specific roles in PrCa.
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http://dx.doi.org/10.1093/hmg/ddw349DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5418832PMC
December 2016

Pedicle Reduction Osteotomy in the Upper Cervical Spine: Technique, Case Report and Review of the Literature.

Int J Spine Surg 2015 27;9:57. Epub 2015 Oct 27.

SUNY Downstate Medical Center, New York, NY.

Objective: To present a case report of the correction of a degenerative cervical 45-degree kyphosis centered at C4 with a single stage PSO.

Summary Of Background Data: Correction of a fixed cervical kyphosis is a surgical challenge that is frequently managed with a combination of anterior and posterior surgical procedures. An alternative the three stage operation is a single stage pedicle subtraction osteotomy (PSO). A PSO releases the posterior, middle and anterior columns of the spine by resecting the facet joints, pedicles, and a portion of the vertebral body at the apex of a kyphosis through a posterior approach.

Methods: This was a case report of a patient who had degenerative cervical 45 degree kyphosis and was corrected with a single stage pedicle subtraction osteotomy. We did a literature review to provide information on current techniques to treat these patients.

Results: With careful resection of the lateral mass and decompression of the vertebral artery by removal of the posterior margin of the foramen transversarium the upper cervical pedicles can be accessed and a PSO can be performed. The vertebral arteries were not obstructed or kinked with posterior reduction of the PSO in this case.

Conclusions: A closing wedge PSO is a useful tool for correcting fixed kyphotic deformities in the upper cervical spine. Further studies are necessary to evaluate the long-term outcomes in these patients.
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http://dx.doi.org/10.14444/2057DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657605PMC
November 2015

Prostate Single Nucleotide Polymorphism Provides a Crucial Clue to Cancer Aggression in Active Surveillance Patients.

Eur Urol 2016 Feb 9;69(2):229-30. Epub 2015 Oct 9.

School of Biological Sciences, University of East Anglia, Norwich, UK.

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http://dx.doi.org/10.1016/j.eururo.2015.09.038DOI Listing
February 2016

Building Data-Driven Pathways From Routinely Collected Hospital Data: A Case Study on Prostate Cancer.

JMIR Med Inform 2015 Jul 10;3(3):e26. Epub 2015 Jul 10.

School of Computing Sciences, University of East Anglia, Norwich, United Kingdom.

Background: Routinely collected data in hospitals is complex, typically heterogeneous, and scattered across multiple Hospital Information Systems (HIS). This big data, created as a byproduct of health care activities, has the potential to provide a better understanding of diseases, unearth hidden patterns, and improve services and cost. The extent and uses of such data rely on its quality, which is not consistently checked, nor fully understood. Nevertheless, using routine data for the construction of data-driven clinical pathways, describing processes and trends, is a key topic receiving increasing attention in the literature. Traditional algorithms do not cope well with unstructured processes or data, and do not produce clinically meaningful visualizations. Supporting systems that provide additional information, context, and quality assurance inspection are needed.

Objective: The objective of the study is to explore how routine hospital data can be used to develop data-driven pathways that describe the journeys that patients take through care, and their potential uses in biomedical research; it proposes a framework for the construction, quality assessment, and visualization of patient pathways for clinical studies and decision support using a case study on prostate cancer.

Methods: Data pertaining to prostate cancer patients were extracted from a large UK hospital from eight different HIS, validated, and complemented with information from the local cancer registry. Data-driven pathways were built for each of the 1904 patients and an expert knowledge base, containing rules on the prostate cancer biomarker, was used to assess the completeness and utility of the pathways for a specific clinical study. Software components were built to provide meaningful visualizations for the constructed pathways.

Results: The proposed framework and pathway formalism enable the summarization, visualization, and querying of complex patient-centric clinical information, as well as the computation of quality indicators and dimensions. A novel graphical representation of the pathways allows the synthesis of such information.

Conclusions: Clinical pathways built from routinely collected hospital data can unearth information about patients and diseases that may otherwise be unavailable or overlooked in hospitals. Data-driven clinical pathways allow for heterogeneous data (ie, semistructured and unstructured data) to be collated over a unified data model and for data quality dimensions to be assessed. This work has enabled further research on prostate cancer and its biomarkers, and on the development and application of methods to mine, compare, analyze, and visualize pathways constructed from routine data. This is an important development for the reuse of big data in hospitals.
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http://dx.doi.org/10.2196/medinform.4221DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4526987PMC
July 2015

The evolutionary history of lethal metastatic prostate cancer.

Nature 2015 Apr 1;520(7547):353-357. Epub 2015 Apr 1.

Institute of Biosciences and Medical Technology, BioMediTech, University of Tampere and Fimlab Laboratories, Tampere University Hospital, Tampere, Finland.

Cancers emerge from an ongoing Darwinian evolutionary process, often leading to multiple competing subclones within a single primary tumour. This evolutionary process culminates in the formation of metastases, which is the cause of 90% of cancer-related deaths. However, despite its clinical importance, little is known about the principles governing the dissemination of cancer cells to distant organs. Although the hypothesis that each metastasis originates from a single tumour cell is generally supported, recent studies using mouse models of cancer demonstrated the existence of polyclonal seeding from and interclonal cooperation between multiple subclones. Here we sought definitive evidence for the existence of polyclonal seeding in human malignancy and to establish the clonal relationship among different metastases in the context of androgen-deprived metastatic prostate cancer. Using whole-genome sequencing, we characterized multiple metastases arising from prostate tumours in ten patients. Integrated analyses of subclonal architecture revealed the patterns of metastatic spread in unprecedented detail. Metastasis-to-metastasis spread was found to be common, either through de novo monoclonal seeding of daughter metastases or, in five cases, through the transfer of multiple tumour clones between metastatic sites. Lesions affecting tumour suppressor genes usually occur as single events, whereas mutations in genes involved in androgen receptor signalling commonly involve multiple, convergent events in different metastases. Our results elucidate in detail the complex patterns of metastatic spread and further our understanding of the development of resistance to androgen-deprivation therapy in prostate cancer.
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http://dx.doi.org/10.1038/nature14347DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4413032PMC
April 2015

Analysis of the genetic phylogeny of multifocal prostate cancer identifies multiple independent clonal expansions in neoplastic and morphologically normal prostate tissue.

Nat Genet 2015 Apr 2;47(4):367-372. Epub 2015 Mar 2.

Urological Research Laboratory, Cancer Research UK Cambridge Research Institute, Cambridge, UK.

Genome-wide DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of three men. Mutations were present at high levels in morphologically normal tissue distant from the cancer, reflecting clonal expansions, and the underlying mutational processes at work in morphologically normal tissue were also at work in cancer. Our observations demonstrate the existence of ongoing abnormal mutational processes, consistent with field effects, underlying carcinogenesis. This mechanism gives rise to extensive branching evolution and cancer clone mixing, as exemplified by the coexistence of multiple cancer lineages harboring distinct ERG fusions within a single cancer nodule. Subsets of mutations were shared either by morphologically normal and malignant tissues or between different ERG lineages, indicating earlier or separate clonal cell expansions. Our observations inform on the origin of multifocal disease and have implications for prostate cancer therapy in individual cases.
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http://dx.doi.org/10.1038/ng.3221DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4380509PMC
April 2015

HES5 silencing is an early and recurrent change in prostate tumourigenesis.

Endocr Relat Cancer 2015 Apr 5;22(2):131-44. Epub 2015 Jan 5.

Cancer Research UK Cambridge InstituteUniversity of Cambridge, Cambridge, CB2 0RE, UKDivision of Genetics and EpidemiologyThe Institute of Cancer Research, Sutton, UKDepartment of Biological Sciences and School of MedicineUniversity of East Anglia, Norwich, UKRoyal Marsden NHS Foundation TrustLondon and Sutton, UKDepartments of PathologyUrologySurgical OncologyAddenbrooke's Hospital, Hills Road, Cambridge, UK

Prostate cancer is the most common cancer in men, resulting in over 10 000 deaths/year in the UK. Sequencing and copy number analysis of primary tumours has revealed heterogeneity within tumours and an absence of recurrent founder mutations, consistent with non-genetic disease initiating events. Using methylation profiling in a series of multi-focal prostate tumours, we identify promoter methylation of the transcription factor HES5 as an early event in prostate tumourigenesis. We confirm that this epigenetic alteration occurs in 86-97% of cases in two independent prostate cancer cohorts (n=49 and n=39 tumour-normal pairs). Treatment of prostate cancer cells with the demethylating agent 5-aza-2'-deoxycytidine increased HES5 expression and downregulated its transcriptional target HES6, consistent with functional silencing of the HES5 gene in prostate cancer. Finally, we identify and test a transcriptional module involving the AR, ERG, HES1 and HES6 and propose a model for the impact of HES5 silencing on tumourigenesis as a starting point for future functional studies.
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http://dx.doi.org/10.1530/ERC-14-0454DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335379PMC
April 2015

Benzo pyrene-induced DNA adducts and gene expression profiles in target and non-target organs for carcinogenesis in mice.

BMC Genomics 2014 Oct 8;15:880. Epub 2014 Oct 8.

Analytical and Environmental Sciences Division, MRC-PHE Centre for Environment & Health, King's College London, Franklin-Wilkins Building, 150 Stamford Street, London, SE1 9NH, UK.

Background: Gene expression changes induced by carcinogens may identify differences in molecular function between target and non-target organs. Target organs for benzo[a]pyrene (BaP) carcinogenicity in mice (lung, spleen and forestomach) and three non-target organs (liver, colon and glandular stomach) were investigated for DNA adducts by 32P-postlabelling, for gene expression changes by cDNA microarray and for miRNA expression changes by miRNA microarray after exposure of animals to BaP.

Results: BaP-DNA adduct formation occurred in all six organs at levels that did not distinguish between target and non-target. cDNA microarray analysis showed a variety of genes modulated significantly by BaP in the six organs and the overall gene expression patterns were tissue specific. Gene ontology analysis also revealed that BaP-induced bioactivities were tissue specific; eight genes (Tubb5, Fos, Cdh1, Cyp1a1, Apc, Myc, Ctnnb1 and Cav) showed significant expression difference between three target and three non-target organs. Additionally, several gene expression changes, such as in Trp53 activation and Stat3 activity suggested some similarities in molecular mechanisms in two target organs (lung and spleen), which were not found in the other four organs. Changes in miRNA expression were generally tissue specific, involving, in total, 21/54 miRNAs significantly up- or down-regulated.

Conclusions: Altogether, these findings showed that DNA adduct levels and early gene expression changes did not fully distinguish target from non-target organs. However, mechanisms related to early changes in p53, Stat3 and Wnt/β-catenin pathways may play roles in defining BaP organotropism.
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http://dx.doi.org/10.1186/1471-2164-15-880DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4209037PMC
October 2014

Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array.

Authors:
Rosalind A Eeles Ali Amin Al Olama Sara Benlloch Edward J Saunders Daniel A Leongamornlert Malgorzata Tymrakiewicz Maya Ghoussaini Craig Luccarini Joe Dennis Sarah Jugurnauth-Little Tokhir Dadaev David E Neal Freddie C Hamdy Jenny L Donovan Ken Muir Graham G Giles Gianluca Severi Fredrik Wiklund Henrik Gronberg Christopher A Haiman Fredrick Schumacher Brian E Henderson Loic Le Marchand Sara Lindstrom Peter Kraft David J Hunter Susan Gapstur Stephen J Chanock Sonja I Berndt Demetrius Albanes Gerald Andriole Johanna Schleutker Maren Weischer Federico Canzian Elio Riboli Tim J Key Ruth C Travis Daniele Campa Sue A Ingles Esther M John Richard B Hayes Paul D P Pharoah Nora Pashayan Kay-Tee Khaw Janet L Stanford Elaine A Ostrander Lisa B Signorello Stephen N Thibodeau Dan Schaid Christiane Maier Walther Vogel Adam S Kibel Cezary Cybulski Jan Lubinski Lisa Cannon-Albright Hermann Brenner Jong Y Park Radka Kaneva Jyotsna Batra Amanda B Spurdle Judith A Clements Manuel R Teixeira Ed Dicks Andrew Lee Alison M Dunning Caroline Baynes Don Conroy Melanie J Maranian Shahana Ahmed Koveela Govindasami Michelle Guy Rosemary A Wilkinson Emma J Sawyer Angela Morgan David P Dearnaley Alan Horwich Robert A Huddart Vincent S Khoo Christopher C Parker Nicholas J Van As Christopher J Woodhouse Alan Thompson Tim Dudderidge Chris Ogden Colin S Cooper Artitaya Lophatananon Angela Cox Melissa C Southey John L Hopper Dallas R English Markus Aly Jan Adolfsson Jiangfeng Xu Siqun L Zheng Meredith Yeager Rudolf Kaaks W Ryan Diver Mia M Gaudet Mariana C Stern Roman Corral Amit D Joshi Ahva Shahabi Tiina Wahlfors Teuvo L J Tammela Anssi Auvinen Jarmo Virtamo Peter Klarskov Børge G Nordestgaard M Andreas Røder Sune F Nielsen Stig E Bojesen Afshan Siddiq Liesel M Fitzgerald Suzanne Kolb Erika M Kwon Danielle M Karyadi William J Blot Wei Zheng Qiuyin Cai Shannon K McDonnell Antje E Rinckleb Bettina Drake Graham Colditz Dominika Wokolorczyk Robert A Stephenson Craig Teerlink Heiko Muller Dietrich Rothenbacher Thomas A Sellers Hui-Yi Lin Chavdar Slavov Vanio Mitev Felicity Lose Srilakshmi Srinivasan Sofia Maia Paula Paulo Ethan Lange Kathleen A Cooney Antonis C Antoniou Daniel Vincent François Bacot Daniel C Tessier Zsofia Kote-Jarai Douglas F Easton

Nat Genet 2013 Apr;45(4):385-91, 391e1-2

The Institute of Cancer Research, Sutton, UK.

Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10(-8)). More than 70 prostate cancer susceptibility loci, explaining ∼30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.
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http://dx.doi.org/10.1038/ng.2560DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3832790PMC
April 2013

A meta-analysis of genome-wide association studies to identify prostate cancer susceptibility loci associated with aggressive and non-aggressive disease.

Authors:
Ali Amin Al Olama Zsofia Kote-Jarai Fredrick R Schumacher Fredrik Wiklund Sonja I Berndt Sara Benlloch Graham G Giles Gianluca Severi David E Neal Freddie C Hamdy Jenny L Donovan David J Hunter Brian E Henderson Michael J Thun Michael Gaziano Edward L Giovannucci Afshan Siddiq Ruth C Travis David G Cox Federico Canzian Elio Riboli Timothy J Key Gerald Andriole Demetrius Albanes Richard B Hayes Johanna Schleutker Anssi Auvinen Teuvo L J Tammela Maren Weischer Janet L Stanford Elaine A Ostrander Cezary Cybulski Jan Lubinski Stephen N Thibodeau Daniel J Schaid Karina D Sorensen Jyotsna Batra Judith A Clements Suzanne Chambers Joanne Aitken Robert A Gardiner Christiane Maier Walther Vogel Thilo Dörk Hermann Brenner Tomonori Habuchi Sue Ingles Esther M John Joanne L Dickinson Lisa Cannon-Albright Manuel R Teixeira Radka Kaneva Hong-Wei Zhang Yong-Jie Lu Jong Y Park Kathleen A Cooney Kenneth R Muir Daniel A Leongamornlert Edward Saunders Malgorzata Tymrakiewicz Nadiya Mahmud Michelle Guy Koveela Govindasami Lynne T O'Brien Rosemary A Wilkinson Amanda L Hall Emma J Sawyer Tokhir Dadaev Jonathan Morrison David P Dearnaley Alan Horwich Robert A Huddart Vincent S Khoo Christopher C Parker Nicholas Van As Christopher J Woodhouse Alan Thompson Tim Dudderidge Chris Ogden Colin S Cooper Artitaya Lophatonanon Melissa C Southey John L Hopper Dallas English Jarmo Virtamo Loic Le Marchand Daniele Campa Rudolf Kaaks Sara Lindstrom W Ryan Diver Susan Gapstur Meredith Yeager Angela Cox Mariana C Stern Roman Corral Markus Aly William Isaacs Jan Adolfsson Jianfeng Xu S Lilly Zheng Tiina Wahlfors Kimmo Taari Paula Kujala Peter Klarskov Børge G Nordestgaard M Andreas Røder Ruth Frikke-Schmidt Stig E Bojesen Liesel M FitzGerald Suzanne Kolb Erika M Kwon Danielle M Karyadi Torben Falck Orntoft Michael Borre Antje Rinckleb Manuel Luedeke Kathleen Herkommer Andreas Meyer Jürgen Serth James R Marthick Briony Patterson Dominika Wokolorczyk Amanda Spurdle Felicity Lose Shannon K McDonnell Amit D Joshi Ahva Shahabi Pedro Pinto Joana Santos Ana Ray Thomas A Sellers Hui-Yi Lin Robert A Stephenson Craig Teerlink Heiko Muller Dietrich Rothenbacher Norihiko Tsuchiya Shintaro Narita Guang-Wen Cao Chavdar Slavov Vanio Mitev Stephen Chanock Henrik Gronberg Christopher A Haiman Peter Kraft Douglas F Easton Rosalind A Eeles

Hum Mol Genet 2013 Jan 12;22(2):408-15. Epub 2012 Oct 12.

Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Worts Causeway, Cambridge CB1 8RN, UK.

Genome-wide association studies (GWAS) have identified multiple common genetic variants associated with an increased risk of prostate cancer (PrCa), but these explain less than one-third of the heritability. To identify further susceptibility alleles, we conducted a meta-analysis of four GWAS including 5953 cases of aggressive PrCa and 11 463 controls (men without PrCa). We computed association tests for approximately 2.6 million SNPs and followed up the most significant SNPs by genotyping 49 121 samples in 29 studies through the international PRACTICAL and BPC3 consortia. We not only confirmed the association of a PrCa susceptibility locus, rs11672691 on chromosome 19, but also showed an association with aggressive PrCa [odds ratio = 1.12 (95% confidence interval 1.03-1.21), P = 1.4 × 10(-8)]. This report describes a genetic variant which is associated with aggressive PrCa, which is a type of PrCa associated with a poorer prognosis.
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http://dx.doi.org/10.1093/hmg/dds425DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526158PMC
January 2013

Prognostic value of blood mRNA expression signatures in castration-resistant prostate cancer: a prospective, two-stage study.

Lancet Oncol 2012 Nov 9;13(11):1114-24. Epub 2012 Oct 9.

Drug Development Unit, The Royal Marsden NHS Foundation Trust, Sutton, UK.

Background: Biomarkers are urgently needed to dissect the heterogeneity of prostate cancer between patients to improve treatment and accelerate drug development. We analysed blood mRNA expression arrays to identify patients with metastatic castration-resistant prostate cancer with poorer outcome.

Methods: Whole blood was collected into PAXgene tubes from patients with castration-resistant prostate cancer and patients with prostate cancer selected for active surveillance. In stage I (derivation set), patients with castration-resistant prostate cancer were used as cases and patients under active surveillance were used as controls. These patients were recruited from The Royal Marsden Hospital NHS Foundation Trust (Sutton, UK) and The Beatson West of Scotland Cancer Centre (Glasgow, UK). In stage II (validation-set), patients with castration-resistant prostate cancer recruited from the Memorial Sloan-Kettering Cancer Center (New York, USA) were assessed. Whole-blood RNA was hybridised to Affymetrix U133plus2 microarrays. Expression profiles were analysed with Bayesian latent process decomposition (LPD) to identify RNA expression profiles associated with castration-resistant prostate cancer subgroups; these profiles were then confirmed by quantative reverse transcriptase (qRT) PCR studies and correlated with overall survival in both the test-set and validation-set.

Findings: LPD analyses of the mRNA expression data divided the evaluable patients in stage I (n=94) into four groups. All patients in LPD1 (14 of 14) and most in LPD2 (17 of 18) had castration-resistant prostate cancer. Patients with castration-resistant prostate cancer and those under active surveillance comprised LPD3 (15 of 31 castration-resistant prostate cancer) and LDP4 (12 of 21 castration-resistant prostate cancer). Patients with castration-resistant prostate cancer in the LPD1 subgroup had features associated with worse prognosis and poorer overall survival than patients with castration-resistant prostate cancer in other LPD subgroups (LPD1 overall survival 10·7 months [95% CI 4·1-17·2] vs non-LPD1 25·6 months [18·0-33·4]; p<0·0001). A nine-gene signature verified by qRT-PCR classified patients into this LPD1 subgroup with a very low percentage of misclassification (1·2%). The ten patients who were initially unclassifiable by the LPD analyses were subclassified by this signature. We confirmed the prognostic utility of this nine-gene signature in the validation castration-resistant prostate cancer cohort, where LPD1 membership was also associated with worse overall survival (LPD1 9·2 months [95% CI 2·1-16·4] vs non-LPD1 21·6 months [7·5-35·6]; p=0·001), and remained an independent prognostic factor in multivariable analyses for both cohorts.

Interpretation: Our results suggest that whole-blood gene profiling could identify gene-expression signatures that stratify patients with castration-resistant prostate cancer into distinct prognostic groups.

Funding: AstraZeneca, Experimental Cancer Medicine Centre, Prostate Cancer Charity, Prostate Cancer Foundation.
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http://dx.doi.org/10.1016/S1470-2045(12)70372-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878433PMC
November 2012

Novel, gross chromosomal alterations involving PTEN cooperate with allelic loss in prostate cancer.

Mod Pathol 2012 Jun 30;25(6):902-10. Epub 2012 Mar 30.

The Institute of Cancer Research, Sutton, Surrey, UK.

There is increasing evidence that multiple chromosomal rearrangements occur in prostate cancer. PTEN loss is considered to be a key event in prostate carcinogenesis but the mechanisms of loss remain to be fully elucidated. We hypothesised that gross rearrangements may exist that cause disruption of the PTEN gene in the absence of genomic deletion. We therefore designed a novel fluorescence in situ hybridisation (FISH) assay with probes overlying regions 3' and 5' of PTEN and a third probe overlying the gene. We aimed to identify both genomic deletions and gross rearrangements of PTEN that would be overlooked by previously reported single-probe FISH assays. We proceeded to evaluate a tissue microarray with radical prostatectomy and trans-urethral resection of the prostate specimens from 187 patients. We identified PTEN genomic loss in 45/150 (30%) radical prostatectomy patients and 16/37 (43%) trans-urethral resection of the prostate patients. Importantly, our assay detected novel chromosomal alterations in the PTEN gene (characterised by splitting of FISH signals) in 13 tumours (6.9% of all prostate cancers; 21% of PTEN-lost cancers). All PTEN-rearranged tumours had genomic loss at the other allele and had no expression of PTEN by immunohistochemistry. PTEN-rearranged tumours were significantly more likely to have an underlying ERG rearrangement. Our assay differentiated loss of the probe overlying PTEN in isolation or in combination with either one of or both the probes overlying the 3' and 5' regions. This gave an indication of the size of genomic loss and we observed considerable inter-tumoural heterogeneity in the extent of genomic loss in PTEN-lost tumours. In summary, gross rearrangements of the PTEN locus occur in prostate cancer and can be detected by a 'break-apart' FISH assay. This observation could explain the absence of PTEN protein expression in a subgroup of tumours previously classified as having heterozygous genomic loss using single-probe traditional FISH assays.
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http://dx.doi.org/10.1038/modpathol.2011.207DOI Listing
June 2012

siRNA knockdown of ribosomal protein gene RPL19 abrogates the aggressive phenotype of human prostate cancer.

PLoS One 2011 22;6(7):e22672. Epub 2011 Jul 22.

Section of Cellular Pathology and Molecular Genetics, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom.

We provide novel functional data that posttranscriptional silencing of gene RPL19 using RNAi not only abrogates the malignant phenotype of PC-3M prostate cancer cells but is selective with respect to transcription and translation of other genes. Reducing RPL19 transcription modulates a subset of genes, evidenced by gene expression array analysis and Western blotting, but does not compromise cell proliferation or apoptosis in-vitro. However, growth of xenografted tumors containing the knocked-down RPL19 in-vivo is significantly reduced. Analysis of the modulated genes reveals induction of the non-malignant phenotype principally to involve perturbation of networks of transcription factors and cellular adhesion genes. The data provide evidence that extra-ribosomal regulatory functions of RPL19, beyond protein synthesis, are critical regulators of cellular phenotype. Targeting key members of affected networks identified by gene expression analysis raises the possibility of therapeutically stabilizing a benign phenotype generated by modulating the expression of an individual gene and thereafter constraining a malignant phenotype while leaving non-malignant tissues unaffected.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0022672PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3142177PMC
December 2011