Susceptibility loci associated with prostate cancer progression and mortality

Does androgenic alopecia aggravate the risk of prostate cancer? Evidence from Mendelian randomization

Background

Epidemiological reports indicate a potential association between androgenic alopecia (AGA) and increased prostate cancer (PC) prevalence, but conflicting reports also exist. This study aims to elucidate the causality of AGA on PC risk using Mendelian randomization (MR) analysis.

Materials and methods

Two-sample MR analyses utilized public genome-wide association studies summary data for single-nucleotide polymorphisms associated with AGA. Four statistical methods were used: inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode, with IVW as the preliminary estimation method. Additionally, sensitivity analyses were conducted to address pleiotropic bias.

Results

Genetically proxied AGA did not demonstrate a causal effect on PC risk (IVW P > 0.05). Consistently, complementary methods yielded results aligned with IVW.

Conclusions

Our MR analysis indicates no causal relationship between genetically predicted AGA and PC risk, suggesting that observed associations in epidemiological studies may not be causal.

Evaluation of HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1 polymorphisms associated with prostate cancer in samples of patients from HUPE-UERJ

PURPOSE

Prostate cancer (PCa) is the leading cause of death among men in 48 countries. Genetic alterations play a significant role in PCa carcinogenesis. For the hypothesis of this research, five unique polymorphisms (SNP) were investigated in different genes that showed to be associated in different ways with PCa: rs4430796, rs2735839, rs4792311, rs12329760, and rs28931588, respectively for the genes HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1.

PATIENTS AND METHODS

Blood samples from 426 subjects were evaluated: 290 controls (161 females and 129 males) and 136 PCa patients. SNP were determined by real-time polymerase chain reaction. TaqMan SNP genotyping assay. In the control samples, the SNPs were defined in association with the self-reported ethnicity, and in 218 control samples with markers with ancestry indicators. The genes were in Hardy-Weinberg equilibrium. One hundred and seventy control samples were matched by ethnicity for comparison with the PCa samples.

RESULTS

The G allele at rs28931588 was monomorphic in both patients and controls studied. Significant differences were observed in allelic and genotypic frequencies between the control and Pca samples in rs2735839 (KLK3; p = 0.002 and χ2  = 8.73 and p = 0.01, respectively), by the global frequency and in the dominant model rs2735839_GG (odds ratio [OR] = 0.51, p = 0.02). AA and GA genotypes at rs4792311 (ELAC2) were more frequent in patients with Gleason 7(4 + 3), 8, and 9 (n = 37%-59.7%) compared to patients with Gleason 6 and 7(3 + 4) (n = 26%-40.0%) conferring a protective effect on the GG genotype (OR = 0.45, p = 0.02). The same genotype showed an OR = 2.71 (p = 0.01) for patients with low severity. The HNF1B-KLK3-ELAC2-TMPRSS2-ERG haplotypes: GAAT, AAAT, GAGT, and AAGT were more frequent in patients with Pca with OR ranging from 4.65 to 2.48.

CONCLUSIONS

Higher frequencies of risk alleles were confirmed in the SNPs, KLK3 rs2735839_A, ELAC2 rs4792311_A, and TMPRSS2 rs12329760_T in patients with Pca. Rs2735839_A was associated with risk of Pca and rs4792311_A with severity and Gleason score of 7(4 + 3) or greater. There is a need for careful observation of rs2735839 and rs4792311 in association with the prostatic biopsy due to the increased risk of Pca.

Inherited risk assessment and its clinical utility for predicting prostate cancer from diagnostic prostate biopsies

BACKGROUND

Many studies on prostate cancer (PCa) germline variants have been published in the last 15 years. This review critically assesses their clinical validity and explores their utility in prediction of PCa detection rates from prostate biopsy.

METHODS

An integrative review was performed to (1) critically synthesize findings on PCa germline studies from published papers since 2016, including risk-associated single nucleotide polymorphisms (SNPs), polygenic risk score methods such as genetic risk score (GRS), and rare pathogenic mutations (RPMs); (2) exemplify the findings in a large population-based cohort from the UK Biobank (UKB); (3) identify gaps for implementing inherited risk assessment in clinic based on experience from a healthcare system; (4) evaluate available GRS data on their clinical utility in predicting PCa detection rates from prostate biopsies; and (5) describe a prospective germline-based biopsy trial to address existing gaps.

RESULTS

SNP-based GRS and RPMs in four genes (HOXB13, BRCA2, ATM, and CHEK2) were significantly and consistently associated with PCa risk in large well-designed studies. In the UKB, positive family history, RPMs in the four implicated genes, and a high GRS (>1.5) identified 8.12%, 1.61%, and 17.38% of men to be at elevated PCa risk, respectively, with hazard ratios of 1.84, 2.74, and 2.39, respectively. Additionally, the performance of GRS for predicting PCa detection rate on prostate biopsy was consistently supported in several retrospective analyses of transrectal ultrasound (TRUS)-biopsy cohorts. Prospective studies evaluating the performance of all three inherited measures in predicting PCa detection rate from contemporary multiparametric MRI (mpMRI)-based biopsy are lacking. A multicenter germline-based biopsy trial to address these gaps is warranted.

CONCLUSIONS

The complementary performance of three inherited risk measures in PCa risk stratification is consistently supported. Their clinical utility in predicting PCa detection rate, if confirmed in prospective clinical trials, may improve current decision-making for prostate biopsy.

SNPs at SMG7 Associated with Time from Biochemical Recurrence to Prostate Cancer Death

BACKGROUND

A previous genome-wide association study identified several loci with genetic variants associated with prostate cancer survival time in two cohorts from Sweden. Whether these variants have an effect in other populations or if their effect is homogenous across the course of disease is unknown.

METHODS

These variants were genotyped in a cohort of 1,298 patients. Samples were linked with age, PSA level, Gleason score, cancer stage at surgery, and times from surgery to biochemical recurrence to death from prostate cancer. SNPs rs2702185 and rs73055188 were tested for association with prostate cancer-specific survival time using a multivariate Cox proportional hazard model. SNP rs2702185 was further tested for association with time to biochemical recurrence and time from biochemical recurrence to death with a multi-state model.

RESULTS

SNP rs2702185 at SMG7 was associated with prostate cancer-specific survival time, specifically the time from biochemical recurrence to prostate cancer death (HR, 2.5; 95% confidence interval, 1.4-4.5; P = 0.0014). Nine variants were in linkage disequilibrium (LD) with rs2702185; one, rs10737246, was found to be most likely to be functional based on LD patterns and overlap with open chromatin. Patterns of open chromatin and correlation with gene expression suggest that this SNP may affect expression of SMG7 in T cells.

CONCLUSIONS

The SNP rs2702185 at the SMG7 locus is associated with time from biochemical recurrence to prostate cancer death, and its LD partner rs10737246 is predicted to be functional.

IMPACT

These results suggest that future association studies of prostate cancer survival should consider various intervals over the course of disease.

OncoPan®: An NGS-Based Screening Methodology to Identify Molecular Markers for Therapy and Risk Assessment in Pancreatic Ductal Adenocarcinoma

Pancreatic cancer has a high morbidity and mortality with the majority being PC ductal adenocarcinomas (PDAC). Whole genome sequencing provides a wide description of genomic events involved in pancreatic carcinogenesis and identifies putative biomarkers for new therapeutic approaches. However, currently, there are no approved treatments targeting driver mutations in PDAC that could produce clinical benefit for PDAC patients. A proportion of 5–10% of PDAC have a hereditary origin involving germline variants of homologous recombination genes, such as Mismatch Repair (MMR), STK11 and CDKN2A genes. Very recently, BRCA genes have been demonstrated as a useful biomarker for PARP-inhibitor (PARPi) treatments. In this study, a series of 21 FFPE PDACs were analyzed using OncoPan®, a strategic next-generation sequencing (NGS) panel of 37 genes, useful for identification of therapeutic targets and inherited cancer syndromes. Interestingly, this approach, successful also on minute pancreatic specimens, identified biomarkers for personalized therapy in five PDAC patients, including two cases with HER2 amplification and three cases with mutations in HR genes (BRCA1, BRCA2 and FANCM) and potentially eligible to PARPi therapy. Molecular analysis on normal tissue identified one PDAC patient as a carrier of a germline BRCA1 pathogenetic variant and, noteworthy, this patient was a member of a family affected by inherited breast and ovarian cancer conditions. This study demonstrates that the OncoPan® NGS-based panel constitutes an efficient methodology for the molecular profiling of PDAC, suitable for identifying molecular markers both for therapy and risk assessment. Our data demonstrate the feasibility and utility of these NGS analysis in the routine setting of PDAC molecular characterization.

KLK3 germline mutation I179T complements DNA repair genes for predicting prostate cancer progression

BACKGROUND

Germline mutations in DNA repair genes and KLK3 have been associated with adverse prostate cancer (PCa) outcomes in separate studies but never jointly. The objective of this study is to simultaneously assess these two types of germline mutations.

METHODS

Germline rare pathogenic mutations (RPMs) in 9 commonly tested DNA repair genes and KLK3 variants were tested for their associations with PCa progression in two PCa cohorts: (1) hospital-based PCa patients treated with radical surgery at the Johns Hopkins Hospital (JHH, N = 1943), and (2) population-based PCa patients in the UK Biobank (UKB, N = 10,224). Progression was defined as metastasis and/or PCa-specific death (JHH) and PCa-specific death (UKB). RPMs of DNA repair genes were annotated using the American College of Medical Genetics recommendations. Known KLK3 variants were genotyped. Associations were tested using a logistic regression model adjusting for genetic background (top ten principal components).

RESULTS

In the JHH, 3.2% (59/1,843) of patients had RPMs in 9 DNA repair genes; odds ratio (OR, 95% confidence interval) for progression was 2.99 (1.6-5.34), P < 0.001. In comparison, KLK3 I179T mutation was more common; 9.7% (189/1,943) carried the mutation, OR = 1.6 (1.05-2.37), P = 0.02. Similar results were found in the UKB. Both types of mutations remained statistically significant in multivariable analyses. In the combined cohort, compared to patients without any mutations (RPMs-/KLK3-), RPMs-/KLK3+ patients had modestly increased risk for progression [OR = 1.54 (1.15-2.02), P = 0.003], and RPMs+/KLK3+ patients had greatly increased risk for progression [OR = 5.41 (2.04-12.99), P < 0.001]. Importantly, associations of mutations with PCa progression were found in patients with clinically defined low- or intermediate risk for disease progression.

CONCLUSIONS

Two different cohorts consistently demonstrate that KLK3 I179T and RPMs of nine commonly tested DNA repair genes are complementary for predicting PCa progression. These results are highly relevant to PCa germline testing and provide critical information for KLK3 I179T to be considered in guidelines.

Genetic variant located on chromosome 17p12 contributes to prostate cancer onset and biochemical recurrence

The genetic contribution to prostate cancer (PC) onset and clinical heterogeneity has an important impact on the disease stratification accuracy. Despite the fact that radical prostatectomy (RP) is an effective treatment for localized PC, a considerable number of individuals develop biochemical recurrence (BCR) following surgery. In the present study, we decided to investigate the significance of genetic variability in a homogeneous group of Romanian men and to determine if genotyping could provide information regarding the possible implications of rs4054823 susceptibility loci in PC progression and outcome. A total of 78 samples from both PC and benign prostatic hyperplasia (BPH) patients were genotyped. The genotype frequencies were examined to see if there was a link between the 17p12 SNP and PC disease. When compared to the BPH group, the PC group had a significantly higher frequency of the T risk variant (P = 0.0056) and TT genotype (P = 0.0164). Subsequent analysis revealed that the TT genotype had a significantly higher frequency among younger PC patients based on their age at diagnosis and that it was related with a greater probability of BCR (P = 0.02). According to our findings, the TT genotype appears to be a risk factor for early-onset PC and a potential predictor for BCR after RP.

KLK4T2 Is a Hormonally Regulated Transcript from the KLK4 Locus

The human kallikrein-related peptidase 4 (KLK4) and the transcribed pseudogene KLKP1 are reported to be highly expressed in the prostate. When trying to clone transcripts of KLKP1, we partly failed. Instead, we identified an androgen-regulated transcript, KLK4T2, which appeared to be a splice variant of KLK4 that also contained exons of KLKP1. Expression analysis of KLK4, KLK4T2, and KLKP1 transcripts in prostate cancer cell lines showed high levels of KLKP1 transcripts in the nucleus and in unfractionated cell extract, whereas it was almost completely absent in the cytoplasmatic fraction. This was in contrast to KLK4 and KLK4T2, which displayed high to moderate levels in the cytoplasm. In patient cohorts we found significantly higher expression of both KLK4T2 and KLK4 in benign prostatic hyperplasia compared to both primary prostate cancer and bone metastasis. Analysis of tissue panels demonstrated the highest expression of KLK4T2 in the prostate, but in contrast to the classical KLK4, relatively high levels were also found in placenta. So far, the function of KLK4T2 is still to be explored, but the structure of the translation product indicated that it generates a 17.4 kDa intracellular protein with possible regulatory function.

Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

Prostate cancer risk prediction using a polygenic risk score

Hereditary factors have a strong influence on prostate cancer (PC) risk and poorer outcomes, thus stratification by genetic factors addresses a critical need for targeted PC screening and risk-adapted follow-up. In this Finnish population-based retrospective study 2283 clinically diagnosed and 455 screen-detected patients from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC), 2400 healthy individuals have been involved. Individual genetic risk through establishment of a polygenic risk score based on 55 PC risk SNPs identified through the Finnish subset of the Collaborative Oncological Gene-Environment Study was assessed. Men with PC had significantly higher median polygenic risk score compared to the controls (6.59 vs. 3.83, P < 0.0001). The polygenic risk score above the control median was a significant predictor of PC (OR 2.13, 95% CI 1.90-2.39). The polygenic risk score predicted the risk of PC with an AUC of 0.618 (95% CI 0.60-0.63). Men in the highest polygenic risk score quartile were 2.8-fold (95% CI 2.4-3.30) more likely to develop PC compared with men in the lowest quartile. In the FinRSPC cohort, a significantly higher percentage of men had a PSA level of ≥ 4 ng/mL in polygenic risk score quartile four compared to quartile one (18.7% vs 8.3%, P < 0.00001). Adding the PRS to a PSA-only model contributed additional information in predicting PC in the FinRSPC model. Results strongly suggest that use of the polygenic risk score would facilitate the identification of men at increased risk for PC.

Aggressive prostate cancer phenotype and genome-wide association studies: where are we now?

The majority of prostate cancer (PCa) is indolent, however, a percentage of patients are initially diagnosed with metastatic disease, for which there is a worse prognosis. There is a lack of biomarkers to identify men at greater risk for developing aggressive PCa. Genome-wide association studies (GWAS) scan the genome to search associations of SNPs with specific traits, like cancer. To date, eight GWAS have resulted in the reporting of 16 SNPs associated with aggressive PCa (p < 5.00 × 10^-2). Still, validation studies need to be conducted to confirm the obtained results as GWAS can generate false-positive results. Furthermore, post-GWAS studies provide a better understanding of the functional consequences.

Kallikarein-related peptidase 3 common genetic variant and the risk of prostate cancer

Kallikarein-related peptidase 3 (KLK3) gene polymorphisms seem to play a role in susceptibility to prostate cancer (PC). The purpose of this study was to investigate the association between rs2735839 polymorphism of KLK3 gene and risk of PC in an Iranian population. In this case-control study, rs2735839 was genotyped in 532 patients with PC and 602 controls with benign prostate hyperplasia (BPH) using polymerase chain reaction-restriction fragment length polymorphism assay. The frequency of GG, AG, and AA genotypes of KLK3 polymorphism was 24.6% and 76.2%, 46.6% and 21.7%, and 28.8% and 2.1%, in patients with BPH and PC, respectively (P < 0.001). The frequency of G allele in patients with BPH and PC was 47.9% and 87%, respectively (odds ratio: 7.31; confidence interval: 5.88-9.10; P < 0.001). Patients with AG and GG genotypes had a higher total serum level of prostate-specific antigen (PSA) compared to those with AA genotype (P < 0.001). Patients with this polymorphism had higher risk of tumor with higher grade (P = 0.23), advanced stage (P = 0.11), perineural invasion (P = 0.07), and vascular invasion (P = 0.07) compared to those without it but this difference was not statistically significant. Based on our results, KLK3 gene polymorphism was associated with the risk of PC. Higher levels of PSA in the presence of KLK3 polymorphism in patients with PC indicated that rs2735839 polymorphism could be a risk factor for increased levels of PSA.

Prostate Cancer Risk-Associated Single-Nucleotide Polymorphism Affects Prostate-Specific Antigen Glycosylation and Its Function

BACKGROUND

Genetic association studies have reported single-nucleotide polymorphisms (SNPs) at chromosome 19q13.3 to be associated with prostate cancer (PCa) risk. Recently, the rs61752561 SNP (Asp84Asn substitution) in exon 3 of the kallikrein-related peptidase 3 (KLK3) gene encoding prostate-specific antigen (PSA) was reported to be strongly associated with PCa risk (P = 2.3 × 10^-8). However, the biological contribution of the rs61752561 SNP to PCa risk has not been elucidated.

METHODS

Recombinant PSA protein variants were generated to assess the SNP-mediated biochemical changes by stability and substrate activity assays. PC3 cell-PSA overexpression models were established to evaluate the effect of the SNP on PCa pathogenesis. Genotype-specific correlation of the SNP with total PSA (tPSA) concentrations and free/total (F/T) PSA ratio were determined from serum samples.

RESULTS

Functional analysis showed that the rs61752561 SNP affects PSA stability and structural conformation and creates an extra glycosylation site. This PSA variant had reduced enzymatic activity and the ability to stimulate proliferation and migration of PCa cells. Interestingly, the minor allele is associated with lower tPSA concentrations and high F/T PSA ratio in serum samples, indicating that the amino acid substitution may affect PSA immunoreactivity to the antibodies used in the clinical immunoassays.

CONCLUSIONS

The rs61752561 SNP appears to have a potential role in PCa pathogenesis by changing the glycosylation, protein stability, and PSA activity and may also affect the clinically measured F/T PSA ratio. Accounting for these effects on tPSA concentration and F/T PSA ratio may help to improve the accuracy of the current PSA test.

Genome-wide Scan Identifies Role for AOX1 in Prostate Cancer Survival

BACKGROUND

Most men diagnosed with prostate cancer have low-risk cancers. How to predict prostate cancer progression at the time of diagnosis remains challenging.

OBJECTIVE

To identify single nucleotide polymorphisms (SNPs) associated with death from prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS

Blood samples from 11 506 men in Sweden were collected during 1991-1996. Of these, 1053 men were diagnosed with prostate cancer and 245 died from the disease. Stage and grade at diagnosis and outcome information were obtained, and DNA from all cases was genotyped.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

A total of 6 126 633 SNPs were tested for association with prostate-cancer-specific survival time using a Cox proportional hazard model, adjusted for age, stage, and grade at diagnosis. A value of 1×10-6 was used as suggestive significance threshold. Positive candidate SNPs were tested for association with gene expression using expression quantitative trait locus analysis.

RESULTS AND LIMITATIONS

We found 12 SNPs at seven independent loci associated with prostate-cancer-specific survival time. One of 6 126 633 SNPs tested reached genome-wide significance (p<5×10-8) and replicated in an independent cohort: rs73055188 (p=5.27×10-9, per-allele hazard ratio [HR]=2.27, 95% confidence interval [CI] 1.72-2.98) in the AOX1 gene. A second SNP reached a suggestive level of significance (p<1×10-6) and replicated in an independent cohort: rs2702185 (p=7.1×10-7, per-allele HR=2.55, 95% CI=1.76-3.69) in the SMG7 gene. The SNP rs73055188 is correlated with AOX1 expression levels, which is associated with biochemical recurrence of prostate cancer in independent cohorts. This association is yet to be validated in other ethnic groups.

CONCLUSIONS

The SNP rs73055188 at the AOX1 locus is associated with prostate-cancer-specific survival time, and AOX1 gene expression level is correlated with biochemical recurrence of prostate cancer.

PATIENT SUMMARY

We identify two genetic markers that are associated with prostate-cancer-specific survival time.

Impact of Occupational Exposures and Genetic Polymorphisms on Recurrence and Progression of Non-Muscle-Invasive Bladder Cancer

Introduction: Additional or better markers are needed to guide the clinical monitoring of patients with non-muscle-invasive bladder cancer (NMIBC). Aim: To investigate the influence of occupational exposures and genetic polymorphisms on recurrence and progression of NMIBC. Methods: The study includes 160 NMIBC patients. We collected on questionnaire information on demographic variables, lifetime smoking history, lifetime history of occupational exposure to aromatic amines and polycyclic aromatic hydrocarbons. Genetic polymorphism (glutathione S-transferase M1; T1; P1 (GSTM1; GSTT1; GSTP1); N-acetyltransferase 1; 2 (NAT1; NAT2); cytochrome P450 1B1 (CYP1B1); sulfotransferase 1A1 (SULT1A1); myeloperoxidase (MPO); catechol-O-methyltransferase (COMT); manganese superoxide dismutase (MnSOD); NAD(P)H:quinone oxidoreductase (NQO1); X-ray repair cross-complementing group 1; 3 (XRCC1; XRCC3) and xeroderma pigmentosum complementation group (XPD)) was assessed in peripheral blood lymphocytes. DNA adducts were evaluated by 32P-postlabeling. Predictors of recurrence (histological confirmation of a newly found bladder tumor) and progression (transition of tumor from low-grade to high-grade and/or increase in TNM stage) were identified by multivariate Cox proportional hazard regression with stepwise backward selection of independent variables. Hazard ratios (HR) with 95% confidence interval (95%CI) and two-tail probability of error (p-value) were estimated. Results: The risk of BC progression decreased with the homozygous genotype “ValVal” of both COMT and MnSOD (HR = 0.195; 95%CI = 0.060 to 0.623; p = 0.006). The results on BC recurrence were of borderline significance. No occupational exposure influenced recurrence or progression. Conclusion: Our results are supported by experimental evidence of a plausible mechanism between cause (ValVal genotype of both MnSOD and COMT) and effect (decreased progression of tumor in NMIBC patients). The genetic polymorphisms associated with better prognosis may be used in clinic to guide selection of treatment for patients initially diagnosed with NMIBC. However, external validation studies are required.

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes

High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ–confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene signatures for the 2 disease states and a gene signature distinguishing the 2 patient groups. In addition, the analysis revealed molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways include the androgen, apoptosis, and insulinlike growth factor signaling pathways. This analysis established putative functional bridges between GWAS discoveries and the biological pathways involved in primary organ–confined and metastatic prostate cancer.

Prostate cancer heterogeneity: Discovering novel molecular targets for therapy

Prostate cancer (PCa) shows a broad spectrum of biological and clinical behavior, which represents the epiphenomenon of an extreme genetic heterogeneity. Recent genomic profiling studies have deeply improved the knowledge of the genomic landscape of localized and metastatic PCa. The AR and PI3K/Akt/mTOR signaling pathways are the two most frequently altered, representing therefore interestingly targets for therapy. Moreover, somatic or germline aberrations of DNA repair genes (DRGs) have been observed at high frequency, supporting the potential role of platinum derivatives and PARP inhibitors as effective therapeutic strategies. In the future, the identification of driver mutations present at a specific stage of the disease, the classification PCa based on specific molecular alterations, and the selection of the most appropriate therapy based on biomarkers predictors of response represent the foundations for an increasingly more accurate personalized medicine.

Genome-wide association study of prostate-specific antigen levels identifies novel loci independent of prostate cancer

Prostate-specific antigen (PSA) levels have been used for detection and surveillance of prostate cancer (PCa). However, factors other than PCa—such as genetics—can impact PSA. Here we present findings from a genome-wide association study (GWAS) of PSA in 28,503 Kaiser Permanente whites and 17,428 men from replication cohorts. We detect 40 genome-wide significant (P<5 × 10⁻⁸) single-nucleotide polymorphisms (SNPs): 19 novel, 15 previously identified for PSA (14 of which were also PCa-associated), and 6 previously identified for PCa only. Further analysis incorporating PCa cases suggests that at least half of the 40 SNPs are PSA-associated independent of PCa. The 40 SNPs explain 9.5% of PSA variation in non-Hispanic whites, and the remaining GWAS SNPs explain an additional 31.7%; this percentage is higher in younger men, supporting the genetic basis of PSA levels. These findings provide important information about genetic markers for PSA that may improve PCa screening, thereby reducing over-diagnosis and over-treatment.

Prostate-specific antigen is used as a biomarker of prostate cancer, but levels can be affected by other factors not related to cancer. Here, the authors find genes associated with prostate specific antigen levels in healthy men, which could be used to reduce over-diagnosis and over-treatment.

Beyond prostate-specific antigen: utilizing novel strategies to screen men for prostate cancer

PURPOSE OF REVIEW

The purpose of this article is to review blood and urine tests that are currently available and under investigation for a role in prostate cancer screening and detection.

RECENT FINDINGS

Compared with total prostate-specific antigen (PSA) alone, its combination with percentage free-to-total PSA contributes greater specificity for prostate cancer, and is a component of two newer blood tests called the 4kScore and Prostate Health Index. All three tests improve the prediction of high-grade disease and are commercially available options to aid in initial or repeat prostate biopsy decisions. PCA3 is a urinary marker that is currently available for repeat prostate biopsy decisions. Although PCA3 alone has inferior prediction of clinically significant disease and requires collection of urine after digital rectal examination, it may be combined with other clinical variables or other urine markers like TMPRSS2:ERG to improve performance. Little data are available to support a role for single nucleotide polymorphisms or other investigational markers in early detection.

SUMMARY

Several commercially available blood and urine tests have been shown to improve specificity of PSA for high-grade prostate cancer. Use of such tests would decrease unnecessary biopsy and overdiagnosis of indolent disease. Biopsy of men with moderately elevated PSA without use of such a reflex test should be discouraged.

The complexity of prostate cancer: genomic alterations and heterogeneity

Although prostate cancer is the most common malignancy to affect men in the Western world, the molecular mechanisms underlying its development and progression remain poorly understood. Like all cancers, prostate cancer is a genetic disease that is characterized by multiple genomic alterations, including point mutations, microsatellite variations, and chromosomal alterations such as translocations, insertions, duplications, and deletions. In prostate cancer, but not other carcinomas, these chromosome alterations result in a high frequency of gene fusion events. The development and application of novel high-resolution technologies has significantly accelerated the detection of genomic alterations, revealing the complex nature and heterogeneity of the disease. The clinical heterogeneity of prostate cancer can be partly explained by this underlying genetic heterogeneity, which has been observed between patients from different geographical and ethnic populations, different individuals within these populations, different tumour foci within the same patient, and different cells within the same tumour focus. The highly heterogeneous nature of prostate cancer provides a real challenge for clinical disease management and a detailed understanding of the genetic alterations in all cells, including small subpopulations, would be highly advantageous.

Germline determinants of clinical outcome of cutaneous melanoma

Cutaneous melanoma (CM) is the most lethal form of skin cancer. Despite the constant increase in melanoma incidence, which is in part due to incremental advances in early diagnostic modalities, mortality rates have not improved over the last decade and for advanced stages remain steadily high. While conventional prognostic biomarkers currently in use find significant utility for predicting overall general survival probabilities, they are not sensitive enough for a more personalized clinical assessment on an individual level. In recent years, the advent of genomic technologies has brought the promise of identification of germline DNA alterations that may associate with CM outcomes and hence represent novel biomarkers for clinical utilization. This review attempts to summarize the current state of knowledge of germline genetic factors studied for their impact on melanoma clinical outcomes. We also discuss ongoing problems and hurdles in validating such surrogates, and we also project future directions in discovery of more powerful germline genetic factors with clinical utility in melanoma prognostication.

The identification of trans-associations between prostate cancer GWAS SNPs and RNA expression differences in tumor-adjacent stroma

Here we tested the hypothesis that SNPs associated with prostate cancer risk, might differentially affect RNA expression in prostate cancer stroma. The most significant 35 SNP loci were selected from Genome Wide Association (GWA) studies of ~40,000 patients. We also selected 4030 transcripts previously associated with prostate cancer diagnosis and prognosis. eQTL analysis was carried out by a modified BAYES method to analyze the associations between the risk variants and expressed transcripts jointly in a single model. We observed 47 significant associations between eight risk variants and the expression patterns of 46 genes. This is the first study to identify associations between multiple SNPs and multiple in trans gene expression differences in cancer stroma. Potentially, a combination of SNPs and associated expression differences in prostate stroma may increase the power of risk assessment for individuals, and for cancer progression.

An analysis of the association between prostate cancer risk loci, PSA levels, disease aggressiveness and disease-specific mortality

BACKGROUND

Genome-wide association studies have identified multiple single-nucleotide polymorphsims (SNPs) associated with prostate cancer (PCa). Although these SNPs have been clearly associated with disease risk, their relationship with clinical outcomes is less clear. Our aim was to assess the frequency of known PCa susceptibility alleles within a single institution ascertainment and to correlate risk alleles with disease-specific outcomes.

METHODS

We genotyped 1354 individuals treated for localised PCa between June 1988 and December 2007. Blood samples were prospectively collected and de-identified before being genotyped and matched to phenotypic data. We investigated associations between 61 SNPs and disease-specific end points using multivariable analysis and also determined if SNPs were associated with PSA at diagnosis.

RESULTS

Seven SNPs showed associations on multivariable analysis (P<0.05), rs13385191 with both biochemical recurrence (BR) and castrate metastasis (CM), rs339331 (BR), rs1894292, rs17178655 and rs11067228 (CM), and rs11902236 and rs4857841 PCa-specific mortality. After applying a Bonferroni correction for number of SNPs (P<0.0008), the only persistent significant association was between rs17632542 (KLK3) and PSA levels at diagnosis (P=1.4 × 10(-5)).

CONCLUSIONS

We confirmed that rs17632542 in KLK3 is associated with PSA at diagnosis. No significant association was seen between loci and disease-specific end points when accounting for multiple testing. This provides further evidence that known PCa risk SNPs do not predict likelihood of disease progression.

The prostate cancer susceptibility variant rs2735839 near KLK3 gene is associated with aggressive prostate cancer and can stratify gleason score 7 patients

PURPOSE

Gleason score (GS) 7 prostate cancer is a heterogeneous disease with different clinical behavior. We sought to identify genetic biomarkers that may predict the aggressiveness of GS 7 diseases.

EXPERIMENTAL DESIGN

We genotyped 72 prostate cancer susceptibility SNPs identified in genome-wide association studies in 1,827 white men with histologically confirmed prostate adenocarcinoma. SNPs associated with disease aggressiveness were identified by comparing high-aggressive (GS ≥8) and low-aggressive (GS ≤6) cases. The significant SNPs were then tested to see whether they could further stratify GS 7 prostate cancer.

RESULTS

Three SNPs-rs2735839, rs10486567, and rs103294-were associated with biopsy-proven high-aggressive (GS ≥8) prostate cancer (P < 0.05). Furthermore, the frequency of the variant allele (A) at rs2735839 was significantly higher in patients with biopsy-proven GS 4+3 disease than in those with GS 3 + 4 disease (P = 0.003). In multivariate logistic regression analysis, patients carrying the A allele at rs2735839 exhibited a 1.85-fold (95% confidence interval, 1.31-2.61) increased risk of being GS 4 + 3 compared with those with GS 3 + 4. The rs2735839 is located 600 base pair downstream of the KLK3 gene (encoding PSA) on 19q13.33 and has been shown to modulate PSA level, providing strong biologic plausibility for its association with prostate cancer aggressiveness.

CONCLUSIONS

We confirmed the association of the rs2735839 with high-aggressive prostate cancer (GS ≥8). Moreover, we reported for the first time that rs2735839 can stratify GS 7 patients, which would be clinically important for more accurately assessing the clinical behavior of the intermediate-grade prostate cancer and for tailoring personalized treatment and posttreatment management.

Characterization of the Glycosylation Site of Human PSA Prompted by Missense Mutation using LC-MS/MS

Prostate specific antigen (PSA) is currently used as a diagnostic biomarker for prostate cancer. It is a glycoprotein possessing a single glycosylation site at N69. During our previous study of PSA N69 glycosylation, additional glycopeptides were observed in the PSA sample that were not previously reported and did not match glycopeptides of impure glycoproteins existing in the sample. This extra glycosylation site of PSA is associated with a mutation in KLK3 genes. Among single nucleotide polymorphisms (SNPs) of KLKs families, the rs61752561 in KLK3 genes is an unusual missense mutation resulting in the conversion of D102 to N in PSA amino acid sequence. Accordingly, a new N-linked glycosylation site is created with an N102MS motif. Here we report the first qualitative and quantitative glycoproteomic study of PSA N102 glycosylation site by LC-MS/MS. We successfully applied tandem MS to verify the amino acid sequence possessing N102 glycosylation site and associated glycoforms of PSA samples acquired from different suppliers. Among the three PSA samples, HexNAc2Hex5 was the predominant glycoform at N102, while HexNAc4Hex5Fuc1NeuAc1 or HexNAc4Hex5Fuc1NeuAc2 was the primary glycoforms at N69. D102 is the first amino acid of "kallikrein loop", which is close to a zinc-binding site and catalytic triad. The different glycosylation of N102 relative to N69 might be influenced by the close vicinity of N102 to these functional sites and steric hindrance.

Associations of prostate cancer risk variants with disease aggressiveness: results of the NCI-SPORE Genetics Working Group analysis of 18,343 cases

Genetic studies have identified single nucleotide polymorphisms (SNPs) associated with the risk of prostate cancer (PC). It remains unclear whether such genetic variants are associated with disease aggressiveness. The NCI-SPORE Genetics Working Group retrospectively collected clinicopathologic information and genotype data for 36 SNPs which at the time had been validated to be associated with PC risk from 25,674 cases with PC. Cases were grouped according to race, Gleason score (Gleason ≤ 6, 7, ≥ 8) and aggressiveness (non-aggressive, intermediate, and aggressive disease). Statistical analyses were used to compare the frequency of the SNPs between different disease cohorts. After adjusting for multiple testing, only PC-risk SNP rs2735839 (G) was significantly and inversely associated with aggressive (OR = 0.77; 95 % CI 0.69-0.87) and high-grade disease (OR = 0.77; 95 % CI 0.68-0.86) in European men. Similar associations with aggressive (OR = 0.72; 95 % CI 0.58-0.89) and high-grade disease (OR = 0.69; 95 % CI 0.54-0.87) were documented in African-American subjects. The G allele of rs2735839 was associated with disease aggressiveness even at low PSA levels (<4.0 ng/mL) in both European and African-American men. Our results provide further support that a PC-risk SNP rs2735839 near the KLK3 gene on chromosome 19q13 may be associated with aggressive and high-grade PC. Future prospectively designed, case-case GWAS are needed to identify additional SNPs associated with PC aggressiveness.

Prostate Cancer Genetics: A Review

Over the past decades, research has focussed on identifying the genetic underpinnings of prostate cancer. It has been recognized that a number of forms of genetic changes coupled with epigenetic and gene expression changes can increase the prediction to develop prostate cancer. This review outlines the role of somatic copy number alterations (SCNAs), structural rearrangements, point mutations, and single nucleotide polymorphisms (SNPs) as well as miRNAs. Identifying relevant genetic changes offers the ability to develop novel biomarkers to allow early and accurate detection of prostate cancer as well as provide risk stratification of patients following their diagnosis. The concept of personalized or individualized medicine has gained significant attention. Therefore, a better understanding of the genetic and metabolic pathways underlying prostate cancer development offers the opportunity to explore new therapeutic interventions with the possibility of offering patient-specific targeted therapy.

Association of GWAS-identified lung cancer susceptibility loci with survival length in patients with small-cell lung cancer treated with platinum-based chemotherapy

Genetic variants have been shown to affect length of survival in cancer patients. This study explored the association between lung cancer susceptibility loci tagged by single-nucleotide polymorphisms (SNPs) identified in the genome-wide association studies and length of survival in small-cell lung cancer (SCLC). Eighteen SNPs were genotyped among 874 SCLC patients and Cox proportional hazards regression was used to examine the effects of genotype on survival length under an additive model with age, sex, smoking status and clinical stage as covariates. We identified 3 loci, 20q13.2 (rs4809957G >A), 22q12.2 (rs36600C >T) and 5p15.33 (rs401681C >T), significantly associated with the survival time of SCLC patients. The adjusted hazard ratio (HR) for patients with the rs4809957 GA or AA genotype was 0.80 (95% CI, 0.66–0.96; P = 0.0187) and 0.73 (95% CI, 0.55–0.96; P = 0.0263) compared with the GG genotype. Using the dominant model, the adjusted HR for patients carrying at least one T allele at rs36600 or rs401681 was 0.78 (95% CI, 0.63–0.96; P = 0.0199) and 1.29 (95% CI, 1.08–1.55; P = 0.0047), respectively, compared with the CC genotype. Stratification analyses showed that the significant associations of these 3 loci were only seen in smokers and male patients. The rs4809957 SNP was only significantly associated with length of survival of patients with extensive-stage but not limited-stage tumor. These results suggest that some of the lung cancer susceptibility loci might also affect the prognosis of SCLC.

Genetic variants within endothelial nitric oxide synthase gene and prostate cancer: a meta-analysis

Several variants within gene-encoding endothelial isoform of nitric oxide synthase have been reported to confer prostate cancer (PCa) susceptibility and/or progression. Nevertheless, studies referring to this issue have yielded inconsistent results. In order to elucidate the involvement of these variants in prostate carcinogenesis, we have conducted a meta-analysis of previously published case-control and relevant case-only studies. Eleven studies comprising in total 3,806 cases and 4,466 controls were included in the meta-analysis which yielded evidence of association of rs2070744 (ORCC = 1.43, 95% CI 1.04-1.97; p = 0.03) and intron 4a/b variant (ORab+aa = 1.47, 95% CI 1.00-2.14; p = 0.05) with PCa risk under recessive and dominant model, respectively. Furthermore, PCa patients carrying 4a/b a allele were found to have an increased risk of cancer progression to a less differentiated form, characterized by a high Gleason score (OR = 2.29, 95% CI 1.51-3.49; p < 0.01) and to higher TNM stage (OR = 2.55, 95% CI 1.71-3.81; p < 0.01). These results support the involvement of NOS3 variants in molecular pathogenesis of PCa.

Genetic variation in DNA repair pathways and risk of non-Hodgkin's lymphoma

Molecular and genetic evidence suggests that DNA repair pathways may contribute to lymphoma susceptibility. Several studies have examined the association of DNA repair genes with lymphoma risk, but the findings from these reports have been inconsistent. Here we provide the results of a focused analysis of genetic variation in DNA repair genes and their association with the risk of non-Hodgkin's lymphoma (NHL). With a population of 1,297 NHL cases and 1,946 controls, we have performed a two-stage case/control association analysis of 446 single nucleotide polymorphisms (SNPs) tagging the genetic variation in 81 DNA repair genes. We found the most significant association with NHL risk in the ATM locus for rs227060 (OR = 1.27, 95% CI: 1.13-1.43, p = 6.77×10(-5)), which remained significant after adjustment for multiple testing. In a subtype-specific analysis, associations were also observed for the ATM locus among both diffuse large B-cell lymphomas (DLBCL) and small lymphocytic lymphomas (SLL), however there was no association observed among follicular lymphomas (FL). In addition, our study provides suggestive evidence of an interaction between SNPs in MRE11A and NBS1 associated with NHL risk (OR = 0.51, 95% CI: 0.34-0.77, p = 0.0002). Finally, an imputation analysis using the 1,000 Genomes Project data combined with a functional prediction analysis revealed the presence of biologically relevant variants that correlate with the observed association signals. While the findings generated here warrant independent validation, the results of our large study suggest that ATM may be a novel locus associated with the risk of multiple subtypes of NHL.

Prostate cancer (PCa) risk variants and risk of fatal PCa in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium

BACKGROUND

Screening and diagnosis of prostate cancer (PCa) is hampered by an inability to predict who has the potential to develop fatal disease and who has indolent cancer. Studies have identified multiple genetic risk loci for PCa incidence, but it is unknown whether they could be used as biomarkers for PCa-specific mortality (PCSM).

OBJECTIVE

To examine the association of 47 established PCa risk single-nucleotide polymorphisms (SNPs) with PCSM.

DESIGN, SETTING, AND PARTICIPANTS

We included 10 487 men who had PCa and 11 024 controls, with a median follow-up of 8.3 yr, during which 1053 PCa deaths occurred.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The main outcome was PCSM. The risk allele was defined as the allele associated with an increased risk for PCa in the literature. We used Cox proportional hazards regression to calculate the hazard ratios of each SNP with time to progression to PCSM after diagnosis. We also used logistic regression to calculate odds ratios for each risk SNP, comparing fatal PCa cases to controls.

RESULTS AND LIMITATIONS

Among the cases, we found that 8 of the 47 SNPs were significantly associated (p<0.05) with time to PCSM. The risk allele of rs11672691 (intergenic) was associated with an increased risk for PCSM, while 7 SNPs had risk alleles inversely associated (rs13385191 [C2orf43], rs17021918 [PDLIM5], rs10486567 [JAZF1], rs6465657 [LMTK2], rs7127900 (intergenic), rs2735839 [KLK3], rs10993994 [MSMB], rs13385191 [C2orf43]). In the case-control analysis, 22 SNPs were associated (p<0.05) with the risk of fatal PCa, but most did not differentiate between fatal and nonfatal PCa. Rs11672691 and rs10993994 were associated with both fatal and nonfatal PCa, while rs6465657, rs7127900, rs2735839, and rs13385191 were associated with nonfatal PCa only.

CONCLUSIONS

Eight established risk loci were associated with progression to PCSM after diagnosis. Twenty-two SNPs were associated with fatal PCa incidence, but most did not differentiate between fatal and nonfatal PCa. The relatively small magnitudes of the associations do not translate well into risk prediction, but these findings merit further follow-up, because they may yield important clues about the complex biology of fatal PCa.

PATIENT SUMMARY

In this report, we assessed whether established PCa risk variants could predict PCSM. We found eight risk variants associated with PCSM: One predicted an increased risk of PCSM, while seven were associated with decreased risk. Larger studies that focus on fatal PCa are needed to identify more markers that could aid prediction.

Prognostic relevance of urinary bladder cancer susceptibility loci

In the last few years, susceptibility loci have been identified for urinary bladder cancer (UBC) through candidate-gene and genome-wide association studies. Prognostic relevance of most of these loci is yet unknown. In this study, we used data of the Nijmegen Bladder Cancer Study (NBCS) to perform a comprehensive evaluation of the prognostic relevance of all confirmed UBC susceptibility loci. Detailed clinical data concerning diagnosis, stage, treatment, and disease course of a population-based series of 1,602 UBC patients were collected retrospectively based on a medical file survey. Kaplan-Meier survival analyses and Cox proportional hazard regression were performed, and log-rank tests calculated, to evaluate the association between 12 confirmed UBC susceptibility variants and recurrence and progression in non-muscle invasive bladder cancer (NMIBC) patients. Among muscle-invasive or metastatic bladder cancer (MIBC) patients, association of these variants with overall survival was tested. Subgroup analyses by tumor aggressiveness and smoking status were performed in NMIBC patients. In the overall NMIBC group (n = 1,269), a statistically significant association between rs9642880 at 8q24 and risk of progression was observed (GT vs. TT: HR = 1.08 (95% CI: 0.76-1.54), GG vs. TT: HR = 1.81 (95% CI: 1.23-2.66), P for trend = 2.6 × 10(-3)). In subgroup analyses, several other variants showed suggestive, though non-significant, prognostic relevance for recurrence and progression in NMIBC and survival in MIBC. This study provides suggestive evidence that genetic loci involved in UBC etiology may influence disease prognosis. Elucidation of the causal variant(s) could further our understanding of the mechanism of disease, could point to new therapeutic targets, and might aid in improvement of prognostic tools.

Assessment of association between common variants at 17q12 and prostate cancer risk-evidence from Serbian population and meta--analysis

This study aimed to evaluate possible association between genotypes and alleles of two 17q12 polymorphisms (rs3760511 and rs7501939) and prostate cancer (PCa) risk and progression. Two hundred seventy-one patients with PCa, 261 patients with benign prostatic hyperplasia (BPH), and 171 controls were included in the study. Single nucleotide polymorphisms (SNPs) were genotyped by using PCR followed by restriction fragment length (PCR-RFLP) analysis. We conducted meta-analysis of published studies regarding association of these SNPs with PCa risk. Evidence of positive association between the AC genotype of the SNP rs3760511 and BPH risk for the best-fitting overdominant model of association (BPH vs. controls comparison, p = 0.026; odds ratio [OR] = 1.58; 95% confidence interval [95%CI] 1.05-2.36) were obtained. The association between T allele of rs7501939 and PCa risk was determined in PCa versus controls comparison (p = 0.0032; OR = 0.66, 95%CI 0.50-0.87) with the best-fitting model of inheritance being log-additive. This variant was also found to be associated with the risk of BPH (p = 0.0023; OR = 0.65, 95%CI 0.49-0.86). We found no association between parameters of PCa progression and the analyzed SNPs. Meta-analysis showed strong association between these variants and PCa risk. Our study shows association between SNPs at locus 17q12 and the risk of prostatic diseases in Serbian population. At the same time, results of meta-analysis suggest the association of these SNPs with PCa risk.

The genetic epidemiology of prostate cancer and its clinical implications

Worldwide, familial and epidemiological studies have generated considerable evidence of an inherited component to prostate cancer. Indeed, rare highly penetrant genetic mutations have been implicated. Genome-wide association studies (GWAS) have also identified 76 susceptibility loci associated with prostate cancer risk, which occur commonly but are of low penetrance. However, these mutations interact multiplicatively, which can result in substantially increased risk. Currently, approximately 30% of the familial risk is due to such variants. Evaluating the functional aspects of these variants would contribute to our understanding of prostate cancer aetiology and would enable population risk stratification for screening. Furthermore, understanding the genetic risks of prostate cancer might inform predictions of treatment responses and toxicities, with the goal of personalized therapy. However, risk modelling and clinical translational research are needed before we can translate risk profiles generated from these variants into use in the clinical setting for targeted screening and treatment.

Imaging and Markers as Novel Diagnostic Tools in Detecting Insignificant Prostate Cancer: A Critical Overview

Recent therapeutic advances for managing low-risk prostate cancer include the active surveillance and focal treatment. However, locating a tumor and detecting its volume by adequate sampling is still problematic. Development of predictive biomarkers guiding individual therapeutic choices remains an ongoing challenge. At the same time, prostate cancer magnetic resonance imaging is gaining increasing importance for prostate diagnostics. The high morphological resolution of T2-weighted imaging and functional MRI methods may increase the specificity and sensitivity of diagnostics. Also, recent studies founded an ability of novel biomarkers to identify clinically insignificant prostate cancer, risk of progression, and association with poor differentiation and, therefore, with clinical significance. Probably, the above mentioned methods would improve tumor characterization in terms of its volume, aggressiveness, and focality. In this review, we attempted to evaluate the applications of novel imaging techniques and biomarkers in assessing the significance of the prostate cancer.

Melanoma risk loci as determinants of melanoma recurrence and survival

Background

Steadily high melanoma mortality rates urge for the availability of novel biomarkers with a more personalized ability to predict melanoma clinical outcomes. Germline risk variants are promising candidates for this purpose; however, their prognostic potential in melanoma has never been systematically tested.

Methods

We examined the effect of 108 melanoma susceptibility single nucleotide polymorphisms (SNPs), associated in recent GWAS with melanoma and melanoma-related phenotypes, on recurrence-free survival (RFS) and overall survival (OS), in 891 prospectively accrued melanoma patients. Cox proportional hazards models (Cox PH) were used to test the associations between 108 melanoma risk SNPs and RFS and OS adjusted by age at diagnosis, gender, tumor stage, histological subtype and other primary tumor characteristics.

Results

We identified significant associations for rs7538876 (RCC2) with RFS (HR = 1.48, 95% CI = 1.20-1.83, p = 0.0005) and rs9960018 (DLGAP1) with both RFS and OS (HR = 1.43, 95% CI = 1.07-1.91, p = 0.01, HR = 1.52, 95% CI = 1.09-2.12, p = 0.01, respectively) using multivariable Cox PH models. In addition, we developed a logistic regression model that incorporates rs7538876, rs9960018, primary tumor histological type and stage at diagnosis that has an improved discriminatory ability to classify 3-year recurrence (AUC = 82%) compared to histological type and stage alone (AUC = 78%).

Conclusions

We identified associations between melanoma risk variants and melanoma outcomes. The significant associations observed for rs7538876 and rs9960018 suggest a biological implication of these loci in melanoma progression. The observed predictive patterns of associated variants with clinical end-points suggest for the first time the potential for utilization of genetic risk markers in melanoma prognostication.

Current status of biomarkers for prostate cancer

Prostate cancer (PCa) is a leading cause of cancer-related death of men globally. Since its introduction, there has been intense debate as to the effectiveness of the prostate specific antigen (PSA) test as a screening tool for PCa. It is now evident that the PSA test produces unacceptably high rates of false positive results and is not prognostic. Here we review the current status of molecular biomarkers that promise to be prognostic and that might inform individual patient management. It highlights current efforts to identify biomarkers obtained by minimally invasive methods and discusses current knowledge with regard to gene fusions, mRNA and microRNAs, immunology, and cancer-associated microparticles.

Assessment of possible association between rs3787016 and prostate cancer risk in Serbian population

Recent study, which included meta-analysis of two genome-wide association studies (GWAS), followed by a replication, identified the association between single nucleotide polymorphism (SNP) rs3787016 at 19p13 and prostate cancer (PCa) risk. Considering possible genetic differences between populations, we conducted the study in order to evaluate the association of this polymorphism with prostate cancer risk in Serbian population. 261 samples of peripheral blood were obtained from the patients with PCa and 257 samples from patients with benign prostatic hyperplasia (BPH). 106 volunteers who gave samples of bucal swabs comprised the control group. For individuals diagnosed with PCa clinicopathological characteristics including serum prostate-specific antigen (PSA) level at diagnosis, Gleason score (GS) and clinical stage were determined. Genotypization of rs3787016 was performed by using Taqman(®) SNP Genotyping Assay. The differences in alelle and genotype frequencies between analyzed groups of subjects were performed by using PLINK, SPSS 17.0 for Windows and SNPStats statistical software. No significant association of rs3787016 with PCa risk was determined comparing allele and genotype frequencies among group of patients diagnosed with PCa and the control group, as well as among groups of patients with PCa and BPH. Also, no evidence of association of rs3787016 with PCa risk was shown using tests for association under dominant and recessive genetic models. SNP rs3787016 showed no significant association with standard prognostic parameters regarding PCa progression, nor with the risk of disease progression assessed according to two different risk classification systems.

Prostate cancer: germline prediction for a commonly variable malignancy

What's known on the subject? and What does the study add? Prostate cancer is a heterogeneous disease and biomarkers to predict its incidence and subsequent clinical behaviour are needed to tailor screening, prevention and therapeutic strategies. Rare mutations in genes such as BRCA1, BRCA2 and HOXB13 can affect prostate cancer incidence and/or clinical behaviour. Genome wide association studies (GWAS) have identified more common genetic variations that explain an estimated 20% of familial prostate cancer risk. In this review, we focus on the potential of germline genetic variation to provide biomarkers for prostate cancer screening, prevention and management. We discuss how germline genetics may have a role in treatment selection if reliable pharmacogenetic predictors of efficacy and toxicity can be identified. We have outlined possible mechanisms for including germline investigation in future prostate cancer clinical trials.

OBJECTIVES

• Prostate cancer is a heterogeneous disease and biomarkers to predict its incidence and subsequent clinical behaviour are needed to tailor screening, prevention and therapeutic strategies. • In this review we focus on the potential of germline genetic variation to provide these biomarkers.

METHODS

• We review the published literature on germline genetics in prostate cancer and examine the possibility of including germline genetic biomarkers in future prostate cancer clinical trials.

RESULTS

• Rare mutations in genes such as BRCA1, BRCA2 and HOXB13 can affect prostate cancer incidence and/or clinical behaviour. • Genome-wide association studies (GWAS) have identified more common genetic variations that explain an estimated 20% of familial prostate cancer risk. • Germline genetics may have a role in treatment selection, if reliable pharmacogenetic predictors of efficacy and toxicity can be identified.

CONCLUSION

• This rapidly emerging area of prostate cancer research may provide answers to current clinical conundrums in the prostate cancer treatment paradigm. We have outlined possible mechanisms for including germline investigation in future prostate cancer clinical trial design.

Variation in IL10 and other genes involved in the immune response and in oxidation and prostate cancer recurrence

BACKGROUND

To evaluate the association of variation in genes involved in immune response, including IL10, production and detoxification of reactive oxygen species, and repair of oxidative DNA damage with risk of recurrence after surgery for localized prostate cancer.

METHODS

We conducted a nested case-control study of men who had a radical prostatectomy in 1993 to 2001. A total of 484 recurrence cases and 484 controls were matched on age, race, and pathologic stage and grade. Germline DNA was extracted from paraffin-embedded unaffected lymph nodes. We genotyped candidate single-nucleotide polymorphisms (SNP) in IL10, CRP, GPX1, GSR, GSTP1, hOGG1, IL1B, IL1RN, IL6, IL8, MPO, NOS2, NOS3, SOD1, SOD2, SOD3, TLR4, and TNF and tagging SNPs in IL10, CRP, GSR, IL1RN, IL6, NOS2, and NOS3. We used conditional logistic regression to estimate OR and 95% confidence intervals (CI).

RESULTS

The minor allele (A) in IL10 rs1800872, known to produce less interleukin-10 (IL-10), was associated with a higher risk of recurrence (OR = 1.76, 95% CI: 1.00-3.10), and the minor allele (G) in rs1800896, known to produce more IL-10, was associated with a lower risk of recurrence (OR = 0.66, 95% CI: 0.48-0.91). We also observed associations for candidate SNPs in CRP, GSTP1, and IL1B. A common IL10 haplotype and 2 common NOS2 haplotypes were associated with recurrence.

CONCLUSION

Variation in IL10, CRP, GSTP1, IL1B, and NOS2 was associated with prostate cancer recurrence independent of pathologic prognostic factors.

IMPACT

This study supports that genetic variation in immune response and oxidation influence prostate cancer recurrence risk and suggests genetic variation in these pathways may inform prognosis.

Genetic predisposition to early recurrence in clinically localized prostate cancer

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: Currently available nomograms to predict preoperative risk of early biochemical recurrence (EBCR) after radical prostatectomy are solely based on classic clinicopathological variables. Despite providing useful predictions, these models are not perfect. Indeed, most researchers agree that nomograms can be improved by incorporating novel biomarkers. In the last few years, several single nucleotide polymorphisms (SNPs) have been associated with prostate cancer, but little is known about their impact on disease recurrence. We have identified four SNPs associated with EBCR. The addition of SNPs to classic nomograms resulted in a significant improvement in terms of discrimination and calibration. The new nomogram, which combines clinicopathological and genetic variables, will help to improve prediction of prostate cancer recurrence.

OBJECTIVES

To evaluate genetic susceptibility to early biochemical recurrence (EBCR) after radical prostatectomy (RP), as a prognostic factor for early systemic dissemination. To build a preoperative nomogram to predict EBCR combining genetic and clinicopathological factors.

PATIENTS AND METHODS

We evaluated 670 patients from six University Hospitals who underwent RP for clinically localized prostate cancer (PCa), and were followed-up for at least 5 years or until biochemical recurrence. EBCR was defined as a level prostate-specific antigen >0.4 ng/mL within 1 year of RP; preoperative variables studied were: age, prostate-specific antigen, clinical stage, biopsy Gleason score, and the genotype of 83 PCa-related single nucleotide polymorphisms (SNPs). Univariate allele association tests and multivariate logistic regression were used to generate predictive models for EBCR, with clinicopathological factors and adding SNPs. We internally validated the models by bootstrapping and compared their accuracy using the area under the curve (AUC), net reclassification improvement, integrated discrimination improvement, calibration plots and Vickers' decision curves.

RESULTS

Four common SNPs at KLK3, KLK2, SULT1A1 and BGLAP genes were independently associated with EBCR. A significant increase in AUC was observed when SNPs were added to the model: AUC (95% confidence interval) 0.728 (0.674-0.784) vs 0.763 (0.708-0.817). Net reclassification improvement showed a significant increase in probability for events of 60.7% and a decrease for non-events of 63.5%. Integrated discrimination improvement and decision curves confirmed the superiority of the new model.

CONCLUSIONS

Four SNPs associated with EBCR significantly improved the accuracy of clinicopathological factors. We present a nomogram for preoperative prediction of EBCR after RP.

The genetics of cancer risk

One hundred years ago, decades before the discovery of the structure of DNA, debate raged regarding how human traits were passed from one generation to the next. Phenotypes, including risk of disease, had long been recognized as having a familial component. Yet it was difficult to reconcile genetic segregation as described by Mendel with observations exhaustively documented by Karl Pearson and others regarding the normal distribution of human characteristics. In 1918, R. A. Fisher published his landmark article, "The Correlation Between Relatives on the Supposition of Mendelian Inheritance," bridging this divide and demonstrating that multiple alleles, all individually obeying Mendel's laws, account for the phenotypic variation observed in nature.Since that time, geneticists have sought to identify the link between genotype and phenotype. Trait-associated alleles vary in their frequency and degree of penetrance. Some minor alleles may approach a frequency of 50% in the human population, whereas others are present within only a few individuals. The spectrum for penetrance is similarly wide. These characteristics jointly determine the segregation pattern of a given trait, which, in turn, determine the method used to map the trait. Until recently, identification of rare, highly penetrant alleles was most practical. Revolutionary studies in genomics reported over the past decade have made interrogation of most of the spectrum of genetic variation feasible.The following article reviews recent discoveries in the genetic basis of inherited cancer risk and how these discoveries inform cancer biology and patient management. Although this article focuses on prostate cancer, the principles are generic for any cancer and, indeed, for any trait.