A novel prostate cancer susceptibility locus at 19q13

Variations in genomic regions encoding long non-coding RNA genes associated with increased prostate cancer risk

From a single restriction fragment length polymorphism analysis to next generation sequencing analysis that screens the entire human genome, testing for genomic variations provides a great and robust approach to cancer testing. Non-coding RNAs have been shown to have a major impact on the development and progression of human cancers, including prostate cancer. However, the low stability of these molecules under laboratory conditions has made their clinical utility challenging, as in the case of PCA3 long non-coding RNA. Since testing for variations in genomic regions encoding non-coding RNAs offers a promising approach for cancer testing, identification and interpretation of single nucleotide polymorphisms associated with prostate cancer susceptibility is of great interest. Accordingly, here, for the first time, we review and discuss current available knowledge about genomic variation of long non-coding RNA molecules in prostate cancer.

Prostate cancer biology & genomics

Prostate Cancer is now the second biggest cause of cancer mortality in the UK. Media coverage has been rising, with some attributing to a rise in the cases diagnosed and treated in the NHS down to the “Fry and Turnbull effect”. Our understanding of prostate cancer has increased tremendously in the past decades, with advances in molecular biology and genomics driving the way to new treatments and diagnostics. This Special Edition of Translational Andrology and Urology 2019: Prostate Cancer Biology and Genomics aims to review the current state of prostate cancer genomics, proteomics, diagnostics and treatment.

Association study between common variations in some candidate genes and prostate adenocarcinoma predisposition through multi-stage approach in Iranian population

BACKGROUND

Prostate cancer is one of the five common cancers and has the second incidence rate and the third mortality rate in Iranian population. The purpose of this study was to evaluate the association of rs16901979, rs4242382 and rs1447295 on 8q24 locus, rs2735839 (KLK3 gene) and rs721048 (EHBP1 gene) with prostate adenocarcinoma through multi-stage approach to identify the polymorphisms associated with prostate cancer and use them as screening factors. Screening tests can identify people who may have a chance of developing the disease before detection and any symptoms.

METHODS

The case-control study included 103 cases (prostate adenocarcinoma) and 100 controls (benign prostatic hyperplasia). Tetra-primer ARMS-PCR was used to genotyping of each participant. A Multi-stage approach was used for efficient genomic study. In this method, a smaller number of people can be used. Chi-squared, Fisher's exact test and logistic regression were used to investigate the SNPs associated with prostate cancer and Gleason score.

RESULTS

In the first stage (59 men), the frequency of polymorphisms rs16901979, rs4242382, rs1447295, rs2735839 and rs721048 in the prostate adenocarcinoma group was evaluated compared to the control group (P-value < 0.3) in order to select meaningful polymorphisms. There was not any significant difference between genotype frequency rs16901979 (P = 0.671) and rs721048 (P = 0.474) in the case group compared to BPH. Therefore, these polymorphisms were eliminated, and in the second step (144 men), rs4242382, rs2735839 and rs1447295 were evaluated (P-value < 0.05). According to the total population (203 men), there was significant difference between genotype frequency rs4242382 (P = 0.001), rs2735839 (P = 0.000) and rs1447295 (P = 0.005) even after using Bonferroni correction (p = 0.016). The effect of these three polymorphisms on prostate cancer was not modified by age and PSA. There was a significant difference between the allelic frequency of A vs G (rs4242382, rs2735839) at all classes of Gleason score and A vs C (rs1447295) at Gleason score ≥ 8.

CONCLUSIONS

The results of this study for rs2735839, rs4242382 and rs1447295 indicate the association of these polymorphisms with prostate adenocarcinoma predisposition in Iranian population. Exposure effect is homogeneous between different ages and PSA level categories. These three polymorphisms should be studied in a larger population to confirm these results.

The prostate cancer risk variant rs55958994 regulates multiple gene expression through extreme long-range chromatin interaction to control tumor progression

Genome-wide association studies identified single-nucleotide polymorphism (SNP) rs55958994 as a significant variant associated with increased susceptibility to prostate cancer. However, the mechanisms by which this SNP mediates increased risk to cancer are still unknown. In this study, we show that this variant is located in an enhancer active in prostate cancer cells. Deletion of this enhancer from prostate tumor cells resulted in decreased tumor initiation, tumor growth, and invasive migration, as well as a loss of stem-like cells. Using a combination of capture chromosome conformation capture (Capture-C) and RNA sequencing, we identified genes on the same and different chromosomes as targets regulated by the enhancer. Furthermore, we show that expression of individual candidate target genes in an enhancer-deleted cell line rescued different aspects of tumorigenesis. Our data suggest that the rs55958994-associated enhancer affects prostate cancer progression by influencing expression of multiple genes via long-range chromatin interactions.

Biology and Clinical Implications of the 19q13 Aggressive Prostate Cancer Susceptibility Locus

Genome-wide association studies (GWAS) have identified rs11672691 at 19q13 associated with aggressive prostate cancer (PCa). Here, we independently confirmed the finding in a cohort of 2,738 PCa patients and discovered the biological mechanism underlying this association. We found an association of the aggressive PCa-associated allele G of rs11672691 with elevated transcript levels of two biologically plausible candidate genes, PCAT19 and CEACAM21, implicated in PCa cell growth and tumor progression. Mechanistically, rs11672691 resides in an enhancer element and alters the binding site of HOXA2, a novel oncogenic transcription factor with prognostic potential in PCa. Remarkably, CRISPR/Cas9-mediated single-nucleotide editing showed the direct effect of rs11672691 on PCAT19 and CEACAM21 expression and PCa cellular aggressive phenotype. Clinical data demonstrated synergistic effects of rs11672691 genotype and PCAT19/CEACAM21 gene expression on PCa prognosis. These results provide a plausible mechanism for rs11672691 associated with aggressive PCa and thus lay the ground work for translating this finding to the clinic.

Environmental factors and risk of aggressive prostate cancer among a population of New Zealand men - a genotypic approach

Prostate cancer is one of the most significant health concerns for men worldwide. Numerous researchers carrying out molecular diagnostics have indicated that genetic interactions with biological and behavioral factors play an important role in the overall risk and prognosis of this disease. Single nucleotide polymorphisms (SNPs) are increasingly becoming strong biomarker candidates to identify susceptibility to prostate cancer. We carried out a gene × environment interaction analysis linked to aggressive and non-aggressive prostate cancer (PCa) with a number of SNPs. By using this method, we identified the susceptible alleles in a New Zealand population, and examined the interaction with environmental factors. We have identified a number of SNPs that have risk associations both with and without environmental interaction. The results indicate that certain SNPs are associated with disease vulnerability based on behavioral factors. The list of genes with SNPs identified as being associated with the risk of PCa in a New Zealand population is provided in the graphical abstract.

A genetic study and meta-analysis of the genetic predisposition of prostate cancer in a Chinese population

Prostate cancer predisposition has been extensively investigated in European populations, but there have been few studies of other ethnic groups. To investigate prostate cancer susceptibility in the under-investigated Chinese population, we performed single-nucleotide polymorphism (SNP) array analysis on a cohort of Chinese cases and controls and then meta-analysis with data from the existing Chinese prostate cancer genome-wide association study (GWAS). Genotyping 211,155 SNPs in 495 cases and 640 controls of Chinese ancestry identified several new suggestive Chinese prostate cancer predisposition loci. However, none of them reached genome-wide significance level either by meta-analysis or replication study. The meta-analysis with the Chinese GWAS data revealed that four 8q24 loci are the main contributors to Chinese prostate cancer risk and the risk alleles from three of them exist at much higher frequencies in Chinese than European populations. We also found that several predisposition loci reported in Western populations have different effect on Chinese men. Therefore, this first extensive single-nucleotide polymorphism study of Chinese prostate cancer in comparison with European population indicates that four loci on 8q24 contribute to a great risk of prostate cancer in a considerable large proportion of Chinese men. Based on those four loci, the top 10% of the population have six- or two-fold prostate cancer risk compared with men of the bottom 10% or median risk respectively, which may facilitate the design of prostate cancer genetic risk screening and prevention in Chinese men. These findings also provide additional insights into the etiology and pathogenesis of prostate cancer.

Germline genetic profiling in prostate cancer: latest developments and potential clinical applications

Familial and twin studies have demonstrated a significant inherited component to prostate cancer predisposition. Genome wide association studies have shown that there are 100 single nucleotide polymorphisms which have been associated with the development of prostate cancer. This review aims to discuss the scientific methods used to identify these susceptibility loci. It will also examine the current clinical utility of these loci, which include the development of risk models as well as predicting treatment efficacy and toxicity. In order to refine the clinical utility of the susceptibility loci, international consortia have been developed to combine statistical power as well as skills and knowledge to further develop models that could be used to predict risk and treatment outcomes.

Systematic enrichment analysis of potentially functional regions for 103 prostate cancer risk-associated loci

BACKGROUND

More than 100 prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) have been identified by genome wide association studies (GWAS). However, the molecular mechanisms are unclear for most of these SNPs.

METHODS

All reported PCa risk-associated SNPs reaching the genome-wide significance level of P < 1 × 10(-7) (index SNPs), as well as SNPs in linkage disequilibrium (LD, r(2) ≥ 0.5) with them were cataloged. Genomic regions with potentially functional impact were also identified, including UCSC annotated coding regions (exon and snoRNA/miRNA) and regulatory regions, as well as binding regions for transcription factors (TFs), histone modifications (HMs), DNase I hypersensitivity (DHSs), and RNA Polymerase IIA (POLR2A) defined by ChIP-Seq in prostate cell lines and tissues. Enrichment analysis was performed to test whether PCa risk-associated SNPs are located in these functional regions more than expected.

RESULTS

A total of 103 PCa risk-associated index SNPs and 7,244 SNPs in LD with these index SNPs were cataloged. Genomic regions with potentially functional impact, grouped in 30 different categories of functionalities, were identified. Enrichment analysis indicated that genomic regions in the following 15 categories were enriched for the PCa risk-associated SNPs: exons, CpG regions, 6 TFs (AR, ERG, FOXA1, HOXB13, CTCF, and NR3C1), 5 HMs (H3K4me1, H3K4me2, H3K4me3, H3K27AC, and H3T11P), DHSs and POLR2A. In contrast, significantly fewer PCa risk SNPs were mapped to binding regions for H3K27me3, a repressive chromatin marker.

CONCLUSIONS

The PCa risk-associated SNPs discovered to date may affect PCa risk through multiple different mechanisms, especially by affecting binding regions of TFs/HMs.

A genetic-based approach to personalized prostate cancer screening and treatment

PURPOSE OF REVIEW

Recent advances in sequencing technologies have allowed for the identification of genetic variants within germline DNA that can explain a significant portion of the genetic underpinnings of prostate cancer. Despite evidence suggesting that these genetic variants can be used for improved risk stratification, they have not yet been routinely incorporated into routine clinical practice. This review highlights their potential utility in prostate cancer screening.

RECENT FINDINGS

There are now almost 100 genetic variants, called single nucleotide polymorphisms (SNPs) that have been recently found to be associated with the risk of developing prostate cancer. In addition, some of these prostate cancer risk SNPs have also been found to influence prostate specific antigen (PSA) expression levels and potentially aggressive disease.

SUMMARY

Incorporation of panels of prostate cancer risk SNPs into clinical practice offers potential to provide improvements in patient selection for prostate cancer screening; PSA interpretation (e.g. by correcting for the presence of SNPs that influence PSA expression levels; decision for biopsy (using prostate cancer risk SNPs); and possibly the decision for treatment. A proposed clinical algorithm incorporating these prostate cancer risk SNPs is discussed.

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.

A simple-to-use method incorporating genomic markers into prostate cancer risk prediction tools facilitated future validation

OBJECTIVES

To incorporate single-nucleotide polymorphisms (SNPs) into the Prostate Cancer Prevention Trial Risk Calculator (PCPTRC).

STUDY DESIGN AND SETTING

A multivariate random-effects meta-analysis of likelihood ratios (LRs) for 30 validated SNPs was performed, allowing the incorporation of linkage disequilibrium. LRs for an SNP were defined as the ratio of the probability of observing the SNP in prostate cancer cases relative to controls and estimated by published allele or genotype frequencies. LRs were multiplied by the PCPTRC prior odds of prostate cancer to provide updated posterior odds.

RESULTS

In the meta-analysis (prostate cancer cases/controls = 386,538/985,968), all but two of the SNPs had at least one statistically significant allele LR (P < 0.05). The two SNPs with the largest LRs were rs16901979 [LR = 1.575 for one risk allele, 2.552 for two risk alleles (homozygous)] and rs1447295 (LR = 1.307 and 1.887, respectively).

CONCLUSION

The substantial investment in genome-wide association studies to discover SNPs associated with prostate cancer risk and the ability to integrate these findings into the PCPTRC allows investigators to validate these observations, to determine the clinical impact, and to ultimately improve clinical practice in the early detection of the most common cancer in men.

Translating genetic risk factors for prostate cancer to the clinic: 2013 and beyond

Prostate cancer (PrCa) is the most commonly diagnosed cancer in the male UK population, with over 40,000 new cases per year. PrCa has a complex, polygenic predisposition, due to rare variants such as BRCA and common variants such as single nucleotide polymorphisms (SNPs). With the introduction of genome-wide association studies, 78 susceptibility loci (SNPs) associated with PrCa risk have been identified. Genetic profiling could risk-stratify a population, leading to the discovery of a higher proportion of clinically significant disease and a reduction in the morbidity related to age-based prostate-specific antigen screening. Based on the combined risk of the 78 SNPs identified so far, the top 1% of the risk distribution has a 4.7-times higher risk of developing PrCa compared with the average of the general population.

Comprehensive functional annotation of 77 prostate cancer risk loci

Genome-wide association studies (GWAS) have revolutionized the field of cancer genetics, but the causal links between increased genetic risk and onset/progression of disease processes remain to be identified. Here we report the first step in such an endeavor for prostate cancer. We provide a comprehensive annotation of the 77 known risk loci, based upon highly correlated variants in biologically relevant chromatin annotations--we identified 727 such potentially functional SNPs. We also provide a detailed account of possible protein disruption, microRNA target sequence disruption and regulatory response element disruption of all correlated SNPs at r(2) ≥ 0.88%. 88% of the 727 SNPs fall within putative enhancers, and many alter critical residues in the response elements of transcription factors known to be involved in prostate biology. We define as risk enhancers those regions with enhancer chromatin biofeatures in prostate-derived cell lines with prostate-cancer correlated SNPs. To aid the identification of these enhancers, we performed genomewide ChIP-seq for H3K27-acetylation, a mark of actively engaged enhancers, as well as the transcription factor TCF7L2. We analyzed in depth three variants in risk enhancers, two of which show significantly altered androgen sensitivity in LNCaP cells. This includes rs4907792, that is in linkage disequilibrium (r(2) = 0.91) with an eQTL for NUDT11 (on the X chromosome) in prostate tissue, and rs10486567, the index SNP in intron 3 of the JAZF1 gene on chromosome 7. Rs4907792 is within a critical residue of a strong consensus androgen response element that is interrupted in the protective allele, resulting in a 56% decrease in its androgen sensitivity, whereas rs10486567 affects both NKX3-1 and FOXA-AR motifs where the risk allele results in a 39% increase in basal activity and a 28% fold-increase in androgen stimulated enhancer activity. Identification of such enhancer variants and their potential target genes represents a preliminary step in connecting risk to disease process.

Plateau effect of prostate cancer risk-associated SNPs in discriminating prostate biopsy outcomes

BACKGROUND

Additional prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) continue to be identified. It is unclear whether addition of newly identified SNPs improves the discriminative performance of biopsy outcomes over previously established SNPs.

METHODS

A total of 667 consecutive patients that underwent prostate biopsy for detection of PCa at Huashan Hospital and Changhai Hospital, Shanghai, China were recruited. Genetic scores were calculated for each patient using various combinations of 29 PCa risk-associated SNPs. Performance of these genetic scores for discriminating prostate biopsy outcomes were compared using the area under a receiver operating characteristic curve (AUC).

RESULTS

The discriminative performance of genetic score derived from a panel of all 29 SNPs (24 previous and 5 new) was similar to that derived from the 24 previously established SNPs, the AUC of which were 0.60 and 0.61, respectively (P = 0.72). When SNPs with the strongest effect on PCa risk (ranked based on contribution to the total genetic variance from an external study) were sequentially added to the models for calculating genetic score, the AUC gradually increased and peaked at 0.62 with the top 13 strongest SNPs. Under the 13-SNP model, the PCa detection rate was 21.52%, 36.74%, and 51.98%, respectively for men with low (<0.5), intermediate (0.5-1.5), and high (>1.5) genetic score, P-trend = 9.91 × 10(-6).

CONCLUSION

Genetic score based on PCa risk-associated SNPs implicated to date is a significant predictor of biopsy outcome. Additional small-effect PCa risk-associated SNPs to be discovered in the future are unlikely to further improve predictive performance.

Evaluation of reported prostate cancer risk-associated SNPs from genome-wide association studies of various racial populations in Chinese men

BACKGROUND

Several genome-wide association studies (GWAS) of prostate cancer (PCa) have identified many single nucleotide polymorphisms (SNPs) that are significantly associated with PCa risk in various racial groups. The objective of this study is to evaluate which of these SNPs are associated with PCa risk in Chinese men and estimate their strength of association.

METHODS

All SNPs that were reported to be associated with PCa risk in GWAS from populations of European, African American, Japanese, and Chinese descent were evaluated in 1,922 PCa cases and 2,175 controls selected from the Chinese Consortium for Prostate Cancer Genetics (ChinaPCa). A logistic regression analysis was used to estimate allelic odds ratios (ORs) of these SNPs for PCa.

RESULTS

Among the 53 SNPs, 50 were polymorphic in the Chinese population. Of which, 10 and 24 SNPs were significantly associated with PCa risk in Chinese men at P < 0.001 and <0.05, respectively. These 24 significant SNPs included 17, 5, and 2 SNPs that were originally discovered in European, Japanese, and Chinese descent, respectively. The estimated ORs ranged from 1.10 to 1.49 and the direction of association was consistent with previous studies. When ORs were estimated separately for PCa with Gleason score ≤7 and ≥8, a marginally significant difference in ORs was found only for two of the 24 SNPs (P = 0.02 and 0.04).

CONCLUSION

About half of PCa risk-associated SNPs identified in GWAS of various populations are associated with PCa risk in Chinese men. Information on PCa risk-associated SNPs and their ORs may facilitate risk assessment of PCa risk in Chinese men.

Prostate cancer risk-associated genetic markers and their potential clinical utility

Prostate cancer (PCa) is one of the most common cancers among men in Western developed countries and its incidence has increased considerably in many other parts of the world, including China. The etiology of PCa is largely unknown but is thought to be multifactorial, where inherited genetics plays an important role. In this article, we first briefly review results from studies of familial aggregation and genetic susceptibility to PCa. We then recap key findings of rare and high-penetrance PCa susceptibility genes from linkage studies in PCa families. We devote a significant portion of this article to summarizing discoveries of common and low-penetrance PCa risk-associated single-nucleotide polymorphisms (SNPs) from genetic association studies in PCa cases and controls, especially those from genome-wide association studies (GWASs). A strong focus of this article is to review the literature on the potential clinical utility of these implicated genetic markers. Most of these published studies described PCa risk estimation using a genetic score derived from multiple risk-associated SNPs and its utility in determining the need for prostate biopsy. Finally, we comment on the newly proposed concept of genetic score; the notion is to treat it as a marker for genetic predisposition, similar to family history, rather than a diagnostic marker to discriminate PCa patients from non-cancer patients. Available evidence to date suggests that genetic score is an objective and better measurement of inherited risk of PCa than family history. Another unique feature of this article is the inclusion of genetic association studies of PCa in Chinese and Japanese populations.

Characterization of SNPs associated with prostate cancer in men of Ashkenazic descent from the set of GWAS identified SNPs: impact of cancer family history and cumulative SNP risk prediction

BACKGROUND

Genome-wide association studies (GWAS) have identified multiple SNPs associated with prostate cancer (PrCa). Population isolates may have different sets of risk alleles for PrCa constituting unique population and individual risk profiles.

METHODS

To test this hypothesis, associations between 31 GWAS SNPs of PrCa were examined among 979 PrCa cases and 1,251 controls of Ashkenazic descent using logistic regression. We also investigated risks by age at diagnosis, pathological features of PrCa, and family history of cancer. Moreover, we examined associations between cumulative number of risk alleles and PrCa and assessed the utility of risk alleles in PrCa risk prediction by comparing the area under the curve (AUC) for different logistic models.

RESULTS

Of the 31 genotyped SNPs, 8 were associated with PrCa at p ≤ 0.002 (corrected p-value threshold) with odds ratios (ORs) ranging from 1.22 to 1.42 per risk allele. Four SNPs were associated with aggressive PrCa, while three other SNPs showed potential interactions for PrCa by family history of PrCa (rs8102476; 19q13), lung cancer (rs17021918; 4q22), and breast cancer (rs10896449; 11q13). Men in the highest vs. lowest quartile of cumulative number of risk alleles had ORs of 3.70 (95% CI 2.76-4.97); 3.76 (95% CI 2.57-5.50), and 5.20 (95% CI 2.94-9.19) for overall PrCa, aggressive cancer and younger age at diagnosis, respectively. The addition of cumulative risk alleles to the model containing age at diagnosis and family history of PrCa yielded a slightly higher AUC (0.69 vs. 0.64).

CONCLUSION

These data define a set of risk alleles associated with PrCa in men of Ashkenazic descent and indicate possible genetic differences for PrCa between populations of European and Ashkenazic ancestry. Use of genetic markers might provide an opportunity to identify men at highest risk for younger age of onset PrCa; however, their clinical utility in identifying men at highest risk for aggressive cancer remains limited.

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

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.

Using graded response model for the prediction of prostate cancer risk

Disease risk-associated single nucleotide polymorphisms (SNPs) identified from genome-wide association studies (GWAS) have the potential to be used for disease risk prediction. An important feature of these risk-associated SNPs is their weak individual effect but stronger cumulative effect on disease risk. To date, a stable summary estimate of the joint effect of genetic variants on disease risk prediction is not available. In this study, we propose to use the graded response model (GRM), which is based on the item response theory, for estimating the individual risk that is associated with a set of SNPs. We compare the GRM with a recently proposed risk prediction model called cumulative relative risk (CRR). Thirty-three prostate cancer risk-associated SNPs were originally discovered in GWAS by December 2009. These SNPs were used to evaluate the performance of GRM and CRR for predicting prostate cancer risk in three GWAS populations, including populations from Sweden, Johns Hopkins Hospital, and the National Cancer Institute Cancer Genetic Markers of Susceptibility study. Computational results show that the risk prediction estimates of GRM, compared to CRR, are less biased and more stable.

Association of prostate cancer risk with SNPs in regions containing androgen receptor binding sites captured by ChIP-On-chip analyses

BACKGROUND

Genome-wide association studies (GWAS) have identified approximately three dozen single nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. Despite the reproducibility of these associations, the molecular mechanism for most of these SNPs has not been well elaborated as most lie within non-coding regions of the genome. Androgens play a key role in prostate carcinogenesis. Recently, using ChIP-on-chip technology, 22,447 androgen receptor (AR) binding sites have been mapped throughout the genome, greatly expanding the genomic regions potentially involved in androgen-mediated activity.

METHODOLOGY/PRINCIPAL FINDINGS

To test the hypothesis that sequence variants in AR binding sites are associated with PCa risk, we performed a systematic evaluation among two existing PCa GWAS cohorts; the Johns Hopkins Hospital and the Cancer Genetic Markers of Susceptibility (CGEMS) study population. We demonstrate that regions containing AR binding sites are significantly enriched for PCa risk-associated SNPs, that is, more than expected by chance alone. In addition, compared with the entire genome, these newly observed risk-associated SNPs in these regions are significantly more likely to overlap with established PCa risk-associated SNPs from previous GWAS. These results are consistent with our previous finding from a bioinformatics analysis that one-third of the 33 known PCa risk-associated SNPs discovered by GWAS are located in regions of the genome containing AR binding sites.

CONCLUSIONS/SIGNIFICANCE

The results to date provide novel statistical evidence suggesting an androgen-mediated mechanism by which some PCa associated SNPs act to influence PCa risk. However, these results are hypothesis generating and ultimately warrant testing through in-depth molecular analyses.

Genome-wide two-locus epistasis scans in prostate cancer using two European populations

Approximately 40 single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk have been identified through genome-wide association studies (GWAS). However, these GWAS-identified PCa risk-associated SNPs can explain only a small proportion of heritability (~13%) of PCa risk. Gene-gene interaction is speculated to be one of the major factors contributing to the so-called missing heritability. To evaluate the gene-gene interaction and PCa risk, we performed a two-stage genome-wide gene-gene interaction scan using a novel statistical approach named "Boolean Operation-based Screening and Testing". In the first stage, we exhaustively evaluated all pairs of SNP-SNP interactions for ~500,000 SNPs in 1,176 PCa cases and 1,101 control subjects from the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) study. No SNP-SNP interaction reached a genome-wide significant level of 4.4E-13. The second stage of the study involved evaluation of the top 1,325 pairs of SNP-SNP interactions (P(interaction) <1.0E-08) implicated in CGEMS in another GWAS population of 1,964 PCa cases from the Johns Hopkins Hospital (JHH) and 3,172 control subjects from the Illumina iControl database. Sixteen pairs of SNP-SNP interactions were significant in the JHH population at a P(interaction) cutoff of 0.01. However, none of the 16 pairs of SNP-SNP interactions were significant after adjusting for multiple tests. The current study represents one of the first attempts to explore the high-dimensional etiology of PCa on a genome-wide scale. Our results suggested a list of SNP-SNP interactions that can be followed in other replication studies.

A genome-wide search for loci interacting with known prostate cancer risk-associated genetic variants

Genome-wide association studies (GWAS) have identified ∼30 single-nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. To test the hypothesis that other sequence variants in the genome may interact with those 32 known PCa risk-associated SNPs identified from GWAS to affect PCa risk, we performed a systematic evaluation among three existing PCa GWAS populations: CAncer of the Prostate in Sweden population, a Johns Hopkins Hospital population, and the Cancer Genetic Markers of Susceptibility population, with a total sample size of 4723 PCa cases and 4792 control subjects. Meta-analysis of the interaction term between each of those 32 SNPs and SNPs in the genome was performed in three PCa GWAS populations. The most significant interaction detected was between rs12418451 in MYEOV and rs784411 in CEP152, with a P(interaction) of 1.15 × 10(-7) in the meta-analysis. In addition, we emphasized two pairs of interactions with potential biological implication, including an interaction between rs7127900 near insulin-like growth factor-2 (IGF2)/IGF2AS and rs12628051 in TNRC6B, with a P(interaction) of 3.39 × 10(-6) and an interaction between rs7679763 near TET2 and rs290258 in SYK, with a P(interaction) of 1.49 × 10(-6). Those results show statistical evidence for novel loci interacting with known risk-associated SNPs to modify PCa risk. The interacting loci identified provide hints on the underlying molecular mechanism of the associations with PCa risk for the known risk-associated SNPs. Additional studies are warranted to further confirm the interaction effects detected in this study.

Base excision repair pathway genes polymorphism in prostate and bladder cancer risk in North Indian population

PURPOSE

Carcinogens causes DNA damage, including oxidative lesions that are removed efficiently by the base excision repair (BER) pathway. Variations in BER genes may reduce DNA repair capacity, leading to development of urological cancers.

METHODS

This study included 195 prostate cancer (PCa) and 212 bladder cancer (BC) patients and 250 controls who had been frequency matched by age, sex, and ethnicity. We genotyped XRCC1 Exon 6 (C>T), 9 (G>A), 10 (G>A), OGG1 Exon 7 (C>G) and APE1 Exon 5 (T>G) genes polymorphism using PCR-RFLP and ARMS.

RESULTS

GA of XRCC1 Exon 9 demonstrated increased risk with PCa as well as in BC (p=0.001; p=0.006). Similarly variant containing genotype revealed association with PCa (p=0.031). Haplotype of XRCC1 also associated with significant risk for PCa and BC. The APE1 GG genotype showed a decreased risk of BC (OR=0.25; p=0.017). Variant genotype GG of OGG1 demonstrated significant risk with BC (p=0.028).

CONCLUSIONS

Our observations suggested increased risk for PCa and BC in case of GA genotype for XRCC1, and variant GG in case of OGG1. However APE1 GG genotype conferred a protective association with BC susceptibility. Larger studies and the more SNPs in the same pathway are needed to verify these findings.

Genome-wide association study identifies new prostate cancer susceptibility loci

Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have identified at least 30 distinct loci associated with small differences in risk. We conducted a GWAS in 2782 advanced PrCa cases (Gleason grade ≥ 8 or tumor stage C/D) and 4458 controls with 571 243 single nucleotide polymorphisms (SNPs). Based on in silico replication of 4679 SNPs (Stage 1, P < 0.02) in two published GWAS with 7358 PrCa cases and 6732 controls, we identified a new susceptibility locus associated with overall PrCa risk at 2q37.3 (rs2292884, P= 4.3 × 10(-8)). We also confirmed a locus suggested by an earlier GWAS at 12q13 (rs902774, P= 8.6 × 10(-9)). The estimated per-allele odds ratios for these loci (1.14 for rs2292884 and 1.17 for rs902774) did not differ between advanced and non-advanced PrCa (case-only test for heterogeneity P= 0.72 and P= 0.61, respectively). Further studies will be needed to assess whether these or other loci are differentially associated with PrCa subtypes.

A genome-wide survey over the ChIP-on-chip identified androgen receptor-binding genomic regions identifies a novel prostate cancer susceptibility locus at 12q13.13

BACKGROUND

The molecular mechanisms for the genome-wide association studies (GWAS)-identified prostate cancer (PCa) risk-associated single-nucleotide polymorphisms (SNP) remain largely unexplained. One recent finding that the PCa risk SNPs are enriched in genomic regions containing androgen receptor (AR)-binding sites has suggested altered AR signaling as a potentially important mechanism.

METHODS

To explore novel associations by leveraging this knowledge, we utilized a meta-analysis previously done over SNPs harbored in ChIP-on-chip identified AR-binding genomic regions using the GWAS data from the Johns Hopkins Hospital (JHH) and the Cancer Genetic Markers of Susceptibility (CGEMS) study, and subsequently evaluated the top associations in a third population from the CAncer of the Prostate in Sweden (CAPS) study.

RESULTS

One SNP (rs4919743: G>A), located at the KRT8 locus at 12q13.13 which encodes a keratin protein (K8) long used as a prostate epithelial malignancy marker and implicated in the tumorigenesis of several cancer types, was identified to be associated with PCa risk. The frequency of its minor "A" allele was consistently higher in PCa cases than in controls in all three study populations, with a combined OR of 1.22 (95% CI: 1.13-1.32) and an overall P value of 4.50 × 10(-7) (Bonferroni corrected, P = 0.006).

CONCLUSION

We have identified a novel genetic locus that is associated with PCa risk.

IMPACT

This study illustrated the great potential of prior biological knowledge in facilitating the search for novel disease-associated genetic loci. This finding warrants further replication in other studies.

Human polymorphisms at long non-coding RNAs (lncRNAs) and association with prostate cancer risk

Long non-coding RNAs (lncRNAs), representing a large proportion of non-coding transcripts across the human genome, are evolutionally conserved and biologically functional. At least one-third of the phenotype-related loci identified by genome-wide association studies (GWAS) are mapped to non-coding intervals. However, the relationships between phenotype-related loci and lncRNAs are largely unknown. Utilizing the 1000 Genomes data, we compared single-nucleotide polymorphisms (SNPs) within the sequences of lncRNA and protein-coding genes as defined in the Ensembl database. We further annotated the phenotype-related SNPs reported by GWAS at lncRNA intervals. Because prostate cancer (PCa) risk-related loci were enriched in lncRNAs, we then performed meta-analysis of two existing GWAS for discovery and an additional sample set for replication, revealing PCa risk-related loci at lncRNA regions. The SNP density in regions of lncRNA was similar to that in protein-coding regions, but they were less polymorphic than surrounding regions. Among the 1998 phenotype-related SNPs identified by GWAS, 52 loci were located directly in lncRNA intervals with a 1.5-fold enrichment compared with the entire genome. More than a 5-fold enrichment was observed for eight PCa risk-related loci in lncRNA genes. We also identified a new PCa risk-related SNP rs3787016 in an lncRNA region at 19q13 (per allele odds ratio = 1.19; 95% confidence interval: 1.11-1.27) with P value of 7.22 × 10(-7). lncRNAs may be important for interpreting and mining GWAS data. However, the catalog of lncRNAs needs to be better characterized in order to fully evaluate the relationship of phenotype-related loci with lncRNAs.

Replication of GWAS "Hits" by Race for Breast and Prostate Cancers in European Americans and African Americans

In this study, we assessed association of genome-wide association studies (GWAS) “hits” by race with adjustment for potential population stratification (PS) in two large, diverse study populations; the Carolina Breast Cancer Study (CBCS; N total = 3693 individuals) and the University of Pennsylvania Study of Clinical Outcomes, Risk, and Ethnicity (SCORE; N total = 1135 individuals). In both study populations, 136 ancestry information markers and GWAS “hits” (CBCS: FGFR2, 8q24; SCORE: JAZF1, MSMB, 8q24) were genotyped. Principal component analysis was used to assess ancestral differences by race. Multivariable unconditional logistic regression was used to assess differences in cancer risk with and without adjustment for the first ancestral principal component (PC1) and for an interaction effect between PC1 and the GWAS “hit” (SNP) of interest. PC1 explained 53.7% of the variance for CBCS and 49.5% of the variance for SCORE. European Americans and African Americans were similar in their ancestral structure between CBCS and SCORE and cases and controls were well matched by ancestry. In the CBCS European Americans, 9/11 SNPs were significant after PC1 adjustment, but after adjustment for the PC1 by SNP interaction effect, only one SNP remained significant (rs1219648 in FGFR2); for CBCS African Americans, 6/11 SNPs were significant after PC1 adjustment and after adjustment for the PC1 by SNP interaction effect, all six SNPs remained significant and an additional SNP now became significant. In the SCORE European Americans, 0/9 SNPs were significant after PC1 adjustment and no changes were seen after additional adjustment for the PC1 by SNP interaction effect; for SCORE African Americans, 2/9 SNPs were significant after PC1 adjustment and after adjustment for the PC1 by SNP interaction effect, only one SNP remained significant (rs16901979 at 8q24). We show that genetic associations by race are modified by interaction between individual SNPs and PS.

Chromosome 8 markers of metastatic prostate cancer in African American men: gain of the MIR151 gene and loss of the NKX3-1 gene

BACKGROUND

Radical prostatectomy (RP) is not curative if patients have undetected metastatic prostate cancer. Markers that indicate the presence of metastatic disease would identify men who may benefit from systemic adjuvant therapy. Our approach was to analyze the primary tumors of men with metastatic disease versus organ-confined disease to identify molecular changes that distinguish between these groups.

METHODS

Patients were identified based on long-term follow-up of serum prostate specific antigen (PSA) levels following RP. We compared the tumors of African American (AA) men with undetectable serum PSA for >9 year after RP (good outcome) versus those of AA men with a rising PSA and recurrence after radiation or androgen ablation or both (poor outcome). We used real-time quantitative PCR to assay gene copy number alterations in tumor DNA relative to patient-matched non-tumor DNA isolated from paraffin-embedded tissue. We assayed several genes located in the specific regions of chromosome 8p and 8q that frequently undergo loss and/or gain, respectively, in prostate cancer, and the androgen receptor gene at Xq12.

RESULTS

Gain of the MIR151 gene at 8q24.3 (in 33% of poor outcome vs. 6% of good outcome tumors) and/or loss of the NKX3-1 gene at 8p21.2 (in 39% of poor outcome vs. 11% of good outcome tumors) affected 67% of poor outcome tumors, compared to only 17% of good outcome tumors.

CONCLUSIONS

Copy number gain of the MIR151 gene and/or loss of the NKX3-1 gene in the primary tumor may indicate the presence of metastatic disease.

Early detection of prostate cancer with emphasis on genetic markers

BACKGROUND

The recent advances in genomic research have made it possible to identify several new genomic-based biomarkers for prostate cancer. In this review we evaluate these new markers and speculate about future scenarios.

RESULTS

Today 35 single nucleotide polymorphisms (SNPs) have been identified and independently validated to associate with prostate cancer. These SNPs are common in the population (>5%) but the effect of these SNPs in these regions on prostate cancer risk is modest with odds ratios typically ranging between 1.1 and 1.3. It is estimated that these markers explain 25% of the familial risk of prostate cancer. However, it is anticipated that additional 50-75 prostate cancer SNPs will be identified in the near future. The SNPs associated with prostate cancer so far are not associated with disease stage or outcome. There are several efforts to identify germline genetic markers that can be used as prognostic markers. There are also tumor-based methods that are promising in identifying new genetic markers that can be easily measured in plasma or urine.

CONCLUSION

There are several new "genetic" markers that in the near future might be used in clinical routine. These markers are easy to measure and stable over time. However the challenge is not only to identify new biomarkers but the real test is to validate new biomarkers in several large well-characterized patient populations. This validation must be done together will all other known biomarkers at the same time as it not likely that one single marker is enough, but a panel of different markers. Today 2010 there are over 19 000 publications in the area of biomarkers and prostate cancer, but only one biomarker, PSA, is used in the clinic today!

Prostate cancer risk alleles significantly improve disease detection and are associated with aggressive features in patients with a "normal" prostate specific antigen and digital rectal examination

BACKGROUND

Several reports suggest that a combination of risk alleles may be associated with prostate cancer (CaP) risk and tumor features. However, their ability to detect CaP and tumor characteristics in patients with a "normal" PSA (<4 ng/ml) and non-suspicious digital rectal examination (DRE) remains to be determined.

METHODS

We examined 203 men of European ancestry with clinical stage T1c CaP diagnosed at a "normal" PSA and 611 healthy volunteer controls. The genotypes for 17 different risk alleles were compared between CaP cases and controls. Additional analyses were used to compare the pathologic features between carriers and non-carriers (defined using best-fit genetic model) of these variants.

RESULTS

All risk alleles were present at an increased frequency in cases with "normal" PSA values and DRE compared to controls. Amongst CaP patients, carriers of an increasing number of genetic risk factors (i.e., alleles and positive family history) were at a significantly increased risk of CaP (P-trend <0.001). Specifically, men with >10 genetic risk factors had an 11.2-fold risk (95% CI 4.3-29.2) of having the disease compared to men with ≤5 variants. There also was a higher frequency of many the variants amongst men with adverse pathologic features.

CONCLUSIONS

A substantial proportion of biopsy-detectable CaP occurs in men with "normal" PSA levels and negative DRE. In this population, CaP risk alleles and family history are significantly associated with CaP risk and may help predict aggressive disease. Future studies are warranted to determine the utility of incorporating these variants into CaP screening programs.

Characterizing associations and SNP-environment interactions for GWAS-identified prostate cancer risk markers--results from BPC3

Genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade) and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10⁻²⁸). Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test), where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade < 8) tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined.

Meta-analysis of genome-wide and replication association studies on prostate cancer

BACKGROUND

Genome-wide and replication association studies (GWAs) have identified multiple loci at which common variants modestly influence the risk of developing prostate cancer (PCa). To enhance the power to identify loci associated with PCa, we constructed a meta-analysis of GWAs on PCa.

METHODS

Articles evaluating the effects of genome-wide SNPs on PCa were identified by searching the PubMed database. After extraction of relevant data, main and subgroup meta-analyses were performed to assess the effects of relevant SNPs on PCa.

RESULTS

21 eligible articles containing 71 subgroups were included in this meta-analysis. Significant associations were found between 31 SNPs and PCa. They were rs445114, rs620861, rs983085, rs1016343, rs1447295, rs1859962, rs2660753, rs2710646, rs2735839, rs3760511, rs4242382, rs4430796, rs4962416, rs5945572, rs5945619, rs6470494, rs6501455, rs6983267, rs6983561, rs7000448, rs7214479, rs7501939, rs7920517, rs7931342, rs9364554, rs9623117, rs10090154, rs10486567, rs10896449, rs10993994, and rs16901979. The weighted odds ratios for above SNPs ranged between 0.64 and 1.88 (all P < 0.05). Subgroup analysis further indicated that the significant associations of some SNPs existed only in specific ancestry population (P < 10⁻⁵).

CONCLUSIONS

The current meta-analysis demonstrated the moderate effects of above 31 SNPs on PCa and 14 independent PCa risk loci were identified.

Prostate cancer risk-associated variants reported from genome-wide association studies: meta-analysis and their contribution to genetic Variation

BACKGROUND

Genome-wide association studies (GWAS) have led to the discovery of multiple single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk. These SNPs may potentially be used for risk prediction. To date, there is not a stable estimate of their effect on PCa risk and their contribution to the genetic variation both of which are important for future risk prediction.

METHODS

A literature review was conducted to identify SNPs associated with PCa risk with the following criteria: (1) GWAS in the Caucasian population; (2) SNPs with P-value <1.0×10(-6); and (3) one SNP from each independent LD block. A meta-analysis was performed to estimate combined odds ratio (OR) and its 95% confidence interval (CI) for the identified SNPs. The proportion of total genetic variance that is attributable by each of these SNPs was also estimated.

RESULTS

Thirty PCa risk-associated SNPs were identified. These SNPs had OR estimates between 1.12 and 1.47 except for marker rs16901979 (OR=1.80). Significant heterogeneity in OR estimates was found among different studies for 13 SNPs. The proportion of total genetic variance attributed by each SNP ranged between 0.2% and 0.9%. These 30 SNPs explained ∼13.5% of the total genetic variance of PCa risk in the Caucasian population.

CONCLUSION

This study provides more stable OR estimates for PCa risk-associated SNPs, which is an important baseline for the effect of these SNPs in risk prediction. These SNPs explain a considerable proportion of genetic variance, however, the majority of genetic variance has yet to be explained.

Validation of genome-wide prostate cancer associations in men of African descent

BACKGROUND

Genome-wide association studies (GWAS) have identified numerous prostate cancer susceptibility alleles, but these loci have been identified primarily in men of European descent. There is limited information about the role of these loci in men of African descent.

METHODS

We identified 7,788 prostate cancer cases and controls with genotype data for 47 GWAS-identified loci.

RESULTS

We identified significant associations for SNP rs10486567 at JAZF1, rs10993994 at MSMB, rs12418451 and rs7931342 at 11q13, and rs5945572 and rs5945619 at NUDT10/11. These associations were in the same direction and of similar magnitude as those reported in men of European descent. Significance was attained at all reported prostate cancer susceptibility regions at chromosome 8q24, including associations reaching genome-wide significance in region 2.

CONCLUSION

We have validated in men of African descent the associations at some, but not all, prostate cancer susceptibility loci originally identified in European descent populations. This may be due to the heterogeneity in genetic etiology or in the pattern of genetic variation across populations.

IMPACT

The genetic etiology of prostate cancer in men of African descent differs from that of men of European descent.

Prostate cancer genomics: can we distinguish between indolent and fatal disease using genetic markers?

Prostate cancer is one of the most heritable cancers in men, and recent genome-wide association studies have revealed numerous genetic variants associated with disease. The risk variants identified using case-control designs that compared unaffected individuals with all types of patients with prostate cancer show little or no ability to discriminate between indolent and fatal forms of this disease. This suggests different genetic components are involved in the initiation as compared with the prognosis of prostate cancer. Future studies contrasting patients with more and less aggressive disease, and exploring association with disease progression and prognosis, should be more effective in detecting genetic risk factors for prostate cancer outcome.

Genetic prostate cancer risk assessment: common variants in 9 genomic regions are associated with cumulative risk

PURPOSE

Five genetic variants along chromosomes 8q24 and 17q have a cumulative association with prostate cancer risk. Our research group previously reported an association between these variants and clinicopathological characteristics. More recently 4 additional prostate cancer susceptibility variants were identified on chromosomes 2p15, 10q11, 11q13 and Xp11. We performed cumulative risk assessment incorporating all 9 genetic variants and determined the relationship of the new variants to clinicopathological tumor features.

MATERIALS AND METHODS

The genotype of 9 variants was determined in 687 men of European ancestry who underwent radical prostatectomy from 2002 to 2008 and in 777 healthy volunteer controls. We compared the incidence of these variants in prostate cancer cases and controls, and assessed their cumulative risk. We also determined the relationship of carrier status for the 4 new variants and clinicopathological tumor features.

RESULTS

Prostate cancer cases had an increased incidence of all 9 risk variants compared to controls. A cumulative model including the 9 single nucleotide polymorphisms provided greater prostate cancer risk stratification than a model restricted to the original 5 single nucleotide polymorphisms described. Specifically men with 6 or more variants were at greater than 6-fold increased risk for prostate cancer. Although 2p15 and 11q13 carriers were more likely to have aggressive features, other clinicopathological features were similar in carriers and noncarriers.

CONCLUSIONS

Genetic variants located in 9 regions have a cumulative association with prostate cancer risk. Identification of an increasing number of single nucleotide polymorphisms may provide greater understanding of their combined relationship with CaP risk and disease aggressiveness.

Molecular epidemiology and its current clinical use in cancer management

The revelation of the entire human DNA sequence in 2001, and the launching of the international haplotype map (HapMap) project, made the identification of common markers of disease possible, dramatically transforming molecular epidemiology. In recent years, the development of, and discoveries within, human genome research have been rapid, highlighted by the current explosion of genome-wide association studies (GWAS). GWAS aim at finding germline changes that increase cancer risk. An equally important and rapid development had been seen in cancer genomics, with great strides being made in our understanding of somatic mutations that allow and accompany cancer development. In this review we discuss whether it is currently possible to use these new discoveries to aid the reduction of cancer mortality by reducing risk of disease, improving prognosis, and keeping complications due to treatment to a minimum. Findings from GWAS have mostly been used to predict risk, but there is the potential to use them for prognostication and even treatment prediction. Expression arrays have identified prognostic patterns for breast cancer, but few reliable patterns are available for treatment prediction. More importantly, virtually no genetic signatures are available to predict morbidity from treatment. Thus, there is a need to bring different biological techniques together and integrate them with existing clinical oncological care for a simultaneous risk and outcome assessment.

Replication of prostate cancer risk loci on 8q24, 11q13, 17q12, 19q33, and Xp11 in African Americans

BACKGROUND

Prostate cancer (Pca) is a common malignancy that disproportionately affects African American men (AA). Recently there have been several genome-wide association studies (GWAS) implicating new prostate cancer risk loci along chromosomes 2, 3, 6, 7, 8, 10, 11, 12, 17, 19, and X in populations of European ancestry. Given the higher incidence and mortality for AAs, and differences in allele frequencies and haplotype structures between African and European descent populations, it is important to assess the impact of these candidate risk loci in AAs.

METHODS

Here we evaluated 20 single nucleotide polymorphisms (SNPs) associated with prostate cancer risk in recent GWAS studies, in AA prostate cancer cases and controls.

RESULTS

We replicated five of the SNPs in our AA population, rs10896449 on 11q13.2 (P = 0.009), rs2735839 on 19q33.33 region, (P = 0.04), rs443076 on chromosome 17q12 (P = 0.008), rs5945572 on Xp11.22 (P = 0.05), as well as the rare variant specific to west African ancestry, bd11934905 in region 2 of 8q24 (P = 1 x 10(-4)).

CONCLUSIONS

While we were able to replicate a few of the previous GWAS SNPs, we were not able to confirm the vast majority of these associations in our AA population. This finding further supports the need to perform GWAS and additional fine mapping in AAs to locate additional susceptibility loci.

Inherited genetic variant predisposes to aggressive but not indolent prostate cancer

Autopsy studies suggest that most aging men will develop lesions that, if detected clinically, would be diagnosed as prostate cancer (PCa). Most of these cancers are indolent and remain localized; however, a subset of PCa is aggressive and accounts for more than 27,000 deaths in the United States annually. Identification of factors specifically associated with risk for more aggressive PCa is urgently needed to reduce overdiagnosis and overtreatment of this common disease. To search for such factors, we compared the frequencies of SNPs among PCa patients who were defined as having either more aggressive or less aggressive disease in four populations examined in the Genetic Markers of Susceptibility (CGEMS) study performed by the National Cancer Institute. SNPs showing possible associations with disease severity were further evaluated in an additional three independent study populations from the United States and Sweden. In total, we studied 4,829 and 12,205 patients with more and less aggressive disease, respectively. We found that the frequency of the TT genotype of SNP rs4054823 at 17p12 was consistently higher among patients with more aggressive compared with less aggressive disease in each of the seven populations studied, with an overall P value of 2.1 x 10(-8) under a recessive model, exceeding the conservative genome-wide significance level. The difference in frequency was largest between patients with high-grade, non-organ-confined disease compared with those with low-grade, organ-confined disease. This study demonstrates that inherited variants predisposing to aggressive but not indolent PCa exist in the genome, and suggests that the clinical potential of such variants as potential early markers for risk of aggressive PCa should be evaluated.

Individual and cumulative effect of prostate cancer risk-associated variants on clinicopathologic variables in 5,895 prostate cancer patients

BACKGROUND

More than a dozen single nucleotide polymorphisms (SNPs) have been associated with prostate cancer (PCa) risk from genome-wide association studies (GWAS). Their association with PCa aggressiveness and clinicopathologic variables is inconclusive.

METHODS

Twenty PCa risk SNPs implicated in GWAS and fine mapping studies were evaluated in 5,895 PCa cases treated by radical prostatectomy at Johns Hopkins Hospital, where each tumor was uniformly graded and staged using the same protocol.

RESULTS

For 18 of the 20 SNPs examined, no statistically significant differences (P > 0.05) were observed in risk allele frequencies between patients with more aggressive (Gleason scores > or =4 + 3, or stage > or =T3b, or N+) or less aggressive disease (Gleason scores < or =3 + 4, and stage < or =T2, and N0). For the two SNPs that had significant differences between more and less aggressive disease rs2735839 in KLK3 (P = 8.4 x 10(-7)) and rs10993994 in MSMB (P = 0.046), the alleles that are associated with increased risk for PCa were more frequent in patients with less aggressive disease. Since these SNPs are known to be associated with PSA levels in men without PCa diagnoses, these latter associations may reflect the enrichment of low grade, low stage cases diagnosed by contemporary disease screening with PSA.

CONCLUSIONS

The vast majority of PCa risk-associated SNPs are not associated with aggressiveness and clinicopathologic variables of PCa. Correspondingly, they have minimal utility in predicting the risk for developing more or less aggressive forms of PCa.

Prostate cancer risk associated loci in African Americans

Four genome-wide association studies, all in populations of European descent, have identified 20 independent single nucleotide polymorphisms (SNP) in 20 regions that are associated with prostate cancer risk. We evaluated these 20 SNPs in a combined African American (AA) study, with 868 prostate cancer patients and 878 control subjects. For 17 of these 20 SNPs, implicated risk-associated alleles were found to be more common in these AA cases than controls, significantly more than expected under the null hypothesis (P = 0.03). Two of these 17 SNPs, located at 3p12, and region 2 at 8q24, were significantly associated with prostate cancer risk (P < 0.05), and only SNP rs16901979 at region 2 of 8q24 remained significant after accounting for 20 tests. A multivariate analysis of additional SNPs across the broader 8q24 region revealed three independent prostate cancer risk-associated SNPs, including rs16901979, rs13254738, and rs10086908. The first two SNPs were approximately 20 kb apart and the last SNP, a novel finding from this study, was approximately 100 kb centromeric to the first two SNPs. These results suggest that a systematic evaluation of regions harboring known prostate cancer risk SNPs implicated in other races is an efficient approach to identify risk alleles for AA. However, studies with larger numbers of AA subjects are needed, and this will likely require a major collaborative effort to combine multiple AA study populations.