Facteurs de risques génétiques associés à la patho-biologie du vieillissement prostatique

Les pathologies du vieillissement prostatique (cancer de la prostate, hyperplasie bénigne de la prostate, déficit androgénique lié à l'âge) sont fréquentes, représentant un problème de santé publique. Leur prévalence s'accroit au gré du vieillissement de la population. Si leur coïncidence épidémiologique est claire, les liens physiopathologiques les unissant restent mal connus. Grâce aux progrès de la génétique, et notamment les associations d'étude du génome entier, la quantification du risque génétique du cancer de la prostate sporadique a été documentée par la découverte de loci de susceptibilité. Néanmoins, l'utilisation de ces marqueurs en pratique courante n'a pas fait la preuve de sa rentabilité, dans le complexe débat du dépistage du cancer de la prostate. La prédisposition génétique au vieillissement pathologique bénin de la prostate, en particulier vers l'HBP, est encore très peu étudiée. De plus amples travaux sont nécessaires pour caractériser la genèse et l'évolution du vieillissement prostatique. Du point de vue du traitement, la prise en charge diagnostique du vieillissement prostatique évolue avec de nouveaux biomarqueurs. Le poids respectif de ces outils diagnostiques multiples reste à déterminer avec un triple objectif : (i) mettre en place des arbres de décision permettent de cibler les biopsies prostatiques, (ii) intégrer à la prise en charge diagnostique les pathologies bénignes comme l'HBP dont le bilan, le traitement et le suivi sont connexes à la problématique du CaP et (iii) considérer tout au long de la prise en charge les pathologies associées tel le syndrome métabolique, dans l'objectif d'une démarche multidisciplinaire.Prostatic diseases due to ageing of the prostate gland (prostate cancer, benign prostatic hyperplasia, late onset hypogonadism) are frequent, and represent a major public health issue. Their prevalence gets higher along the ageing of the population in western countries. If an epidemiological link can be stated between these three diseases, the underlying pathophysiology remains unclear. With recent innovation in human genetics, notably genome wide association studies, the risk of non hereditary prostate cancer has been documented by the identification of susceptibility loci. However, the utility of these genetic markers in a clinical practice environment has not been yet established regarding the complex issue of prostate cancer screening. Genetic predisposition to benign prostate ageing, particularly BPH, has not been extensively studied. Additional investigations are necessary to adequately document the initial phase and evolution of the ageing prostate. From the therapeutic point of view, new biomarkers are about to modify the diagnosis of prostatic ageing. The respective role of each of these new diagnostic tools should be determined with a triple goal. First, improve decision making leading to prostatic biopsies. Then, proceed to integrative therapy of prostatic diseases (prostate cancer but also benign prostatic hyperplasia), and finally consider associated conditions, such as metabolic syndrome, to improve the level of care of the ageing male via a multidisciplinary approach.PARIS-JUSSIEU-Bib.électronique (751059901) / SudocSudocFranceF

Influence of statin use on clinicopathological characteristics of localized prostate cancer and outcomes obtained after radical prostatectomy: a single center study

To assess the impact of statin use on biochemical recurrence (BCR) of prostate cancer after radical prostatectomy (RP)

Promoter hypermethylation of HS3ST2, SEPTIN9 and SLIT2 combined with FGFR3 mutations as a sensitive/specific urinary assay for diagnosis and surveillance in patients with low or high-risk non-muscle-invasive bladder cancer

International audienceBackgroundNon-muscle-invasive bladder cancer (NMIBC) is a high incidence form of bladder cancer (BCa), where genetic and epigenetic alterations occur frequently. We assessed the performance of associating a FGFR3 mutation assay and a DNA methylation analysis to improve bladder cancer detection and to predict disease recurrence of NMIBC patients.MethodsWe used allele specific PCR to determine the FGFR3 mutation status for R248C, S249C, G372C, and Y375C. We preselected 18 candidate genes reported in the literature as being hypermethylated in cancer and measured their methylation levels by quantitative multiplex-methylation specific PCR. We selected HS3ST2, SLIT2 and SEPTIN9 as the most discriminative between control and NMIBC patients and we assayed these markers on urine DNA from a diagnostic study consisting of 167 NMIBC and 105 controls and a follow-up study consisting of 158 NMIBC at diagnosis time’s and 425 at follow-up time. ROC analysis was performed to evaluate the diagnostic accuracy of each assay alone and in combination.ResultsFor Diagnosis: Using a logistic regression analysis with a model consisting of the 3 markers’ methylation values, FGFR3 status, age and known smoker status at the diagnosis time we obtained sensitivity/specificity of 97.6 %/84.8 % and an optimism-corrected AUC of 0.96. With an estimated BCa prevalence of 12.1 % in a hematuria cohort, this corresponds to a negative predictive value (NPV) of 99.6 %. For Follow-up: Using a logistic regression with FGFR3 mutation and the CMI at two time points (beginning of the follow-up and current time point), we got sensitivity/specificity/NPV of 90.3 %/65.1 %/97.0 % and a corrected AUC of 0.84. We also tested a thresholding algorithm with FGFR3 mutation and the two time points as described above, obtaining sensitivity/specificity/NPV values of, respectively, 94.5 %/75.9 %/98.5 % and an AUC of 0.82.ConclusionsWe showed that combined analysis of FGFR3 mutation and DNA methylation markers on urine can be a useful strategy in diagnosis, surveillance and for risk stratification of patients with NMIBC. These results provide the basis for a highly accurate noninvasive test for population screening and allowing to decrease the frequency of cystoscopy, an important feature for both patient quality of life improvement and care cost reduction

Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures

Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx®, Decipher®, Prostadiag®) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses

Soluble Isoforms of Vascular Endothelial Growth Factor Are Predictors of Response to Sunitinib in Metastatic Renal Cell Carcinomas

Angiogenesis is the target of several agents in the treatment of malignancies, including renal cell carcinoma (RCC). There is a real need for surrogate biomarkers that can predict selection of patients who may benefit from antiangiogenic therapies, prediction of disease outcome and which may improve the knowledge regarding mechanism of action of these treatments. Tyrosine kinase inhibitors (TKI) have proven efficacy in metastatic RCC (mRCC). However, the molecular mechanisms underlying the clinical response to these drugs remain unclear.The present study aimed to identify molecular biomarkers associated with the response to sunitinib, a Tyrosine kinase inhibitor. To evaluate this relationship, primary tumors from 23 metastatic RCC patients treated by sunitinib were analyzed for a panel of 16 biomarkers involved in tumor pathways targeted by sunitinib, using real-time quantitative reverse-transcriptase PCR. Nine of the 23 patients (39%) responded to sunitinib. Among transcripts analyzed, only the levels of vascular endothelial growth factor (VEGF) soluble isoforms (VEGF(121) and VEGF(165)) were associated with the response to sunitinib (P = 0.04 for both). Furthermore, the ratio of VEGF soluble isoforms (VEGF(121)/VEGF(165)) was significantly associated with prognosis (P = 0.02).This preliminary study provides a promising tool that might help in the management of metastatic RCC, and could be extended to other tumors treated by TKI

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

Post hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case-Control Sequencing Studies

Rare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single-marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden-type approaches attempt to identify aggregation of RVs across case-control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large-scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway-level RV analysis results from a prostate cancer (PC) risk case-control sequencing study. Finally, we discuss potential extensions and future directions of this work

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Supplemental Data Supplemental Data include one figure and five tables and can be found with this article online at http://dx.doi.org/10.1016/j.ajhg.2016.08.016. Supplemental Data Document S1. Figure S1 and Tables S1–S5 Download Document S2. Article plus Supplemental Data Download Web Resources ClinVar, https://www.ncbi.nlm.nih.gov/clinvar/ dbNSFP, https://sites.google.com/site/jpopgen/dbNSFP Human Gene Mutation Database, http://www.hgmd.cf.ac.uk/ REVEL, https://sites.google.com/site/revelgenomics/ SwissVar, http://swissvar.expasy.org/ The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10−12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies <0.5%. The area under the receiver operating characteristic curve (AUC) for REVEL was 0.046–0.182 higher in an independent test set of 935 recent SwissVar disease variants and 123,935 putatively neutral exome sequencing variants and 0.027–0.143 higher in an independent test set of 1,953 pathogenic and 2,406 benign variants recently reported in ClinVar than the AUCs for other ensemble methods. We provide pre-computed REVEL scores for all possible human missense variants to facilitate the identification of pathogenic variants in the sea of rare variants discovered as sequencing studies expand in scale

Genome-wide association of familial prostate cancer cases identifies evidence for a rare segregating haplotype at 8q24.21

Previous genome-wide association studies (GWAS) of prostate cancer risk focused on cases unselected for family history and have reported over 100 significant associations. The International Consortium for Prostate Cancer Genetics (ICPCG) has now performed a GWAS of 2511 (unrelated) familial prostate cancer cases and 1382 unaffected controls from 12 member sites. All samples were genotyped on the Illumina 5M+exome single nucleotide polymorphism (SNP) platform. The GWAS identified a significant evidence for association for SNPs in six regions previously associated with prostate cancer in population-based cohorts, including 3q26.2, 6q25.3, 8q24.21, 10q11.23, 11q13.3, and 17q12. Of note, SNP rs138042437 (p = 1.7e−8) at 8q24.21 achieved a large estimated effect size in this cohort (odds ratio = 13.3). 116 previously sampled affected relatives of 62 risk-allele carriers from the GWAS cohort were genotyped for this SNP, identifying 78 additional affected carriers in 62 pedigrees. A test for an excess number of affected carriers among relatives exhibited strong evidence for co-segregation of the variant with disease (p = 8.5e−11). The majority (92 %) of risk-allele carriers at rs138042437 had a consistent estimated haplotype spanning approximately 100 kb of 8q24.21 that contained the minor alleles of three rare SNPs (dosage minor allele frequencies <1.7 %), rs183373024 (PRNCR1), previously associated SNP rs188140481, and rs138042437 (CASC19). Strong evidence for co-segregation of a SNP on the haplotype further characterizes the haplotype as a prostate cancer pre-disposition locus