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Genetics of Prostate Cancer (PDQ®)

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Identifying Genes and Inherited Variants Associated With Prostate Cancer Risk

Linkage Analyses
        Introduction to linkage analyses
        Susceptibility loci identified in linkage analyses
Case-Control Studies
        Genes interrogated in case-control studies
Admixture Mapping
Genome-wide Association Studies (GWAS)
        Overview
        Introduction to GWAS
        Candidate genes and susceptibility loci identified in GWAS
        Clinical application of GWAS findings
        GWAS and insight into the mechanism of prostate cancer risk
        Modified approaches to GWAS
        Conclusions
Inherited Variants Associated With Prostate Cancer Aggressiveness

Various research methods have been employed to uncover the landscape of genetic variation associated with prostate cancer. Specific methodologies inform of unique phenotypes or inheritance patterns. The sections below describe prostate cancer research utilizing various methods to highlight their role in uncovering the genetic basis of prostate cancer. In an effort to identify disease susceptibility genes, linkage studies are typically performed on high-risk extended families in which multiple cases of a particular disease have occurred. Typically, gene mutations identified through linkage analyses are rare in the population, highly penetrant in families, and have large effect sizes. The clinical role of mutations that are identified in linkage studies is a clearer one, establishing precedent for genetic testing for cancer with genes such as BRCA1 and BRCA2. (Refer to the BRCA1 and BRCA2 section in the Genes With Potential Clinical Relevance in Prostate Cancer Risk section of this summary for more information about these genes.) Genome-wide association studies (GWAS) are another methodology used to identify candidate loci associated with prostate cancer. Genetic variants identified from GWAS typically are common in the population and have modest effect sizes for prostate cancer risk. The clinical role of markers identified from GWAS is an active area of investigation. Case-control studies are useful in validating the findings of linkage studies and GWAS as well as for studying candidate gene alterations for association with prostate cancer risk, although the clinical role of findings from case-control studies needs to be further defined.

Linkage Analyses

Introduction to linkage analyses

The recognition that prostate cancer clusters within families has led many investigators to collect multiple-case families with the goal of localizing prostate cancer susceptibility genes through linkage studies.

Linkage studies are typically performed on high-risk kindreds in whom multiple cases of a particular disease have occurred in an effort to identify disease susceptibility genes. Linkage analysis statistically compares the genotypes between affected and unaffected individuals and looks for evidence that known genetic markers are inherited along with the disease trait. If such evidence is found (linkage), it provides statistical data that the chromosomal region near the marker also harbors a disease susceptibility gene. Once a genomic region of interest has been identified through linkage analysis, additional studies are required to prove that there truly is a susceptibility gene at that position. Linkage analysis is affected by the following:

  • Family size and having a sufficient number of family members who volunteer to contribute DNA.

  • The number of disease cases in each family.

  • Factors related to age at disease onset (e.g., utilization of screening).

  • Gender differences in disease risk (not relevant in prostate cancer but remains relevant in linkage analysis for other conditions).

  • Heterogeneity of disease in cases (e.g., aggressive vs. nonaggressive phenotype).

  • The accuracy of family history information.

Furthermore, because a standard definition of hereditary prostate cancer (HPC) has not been accepted, prostate cancer linkage studies have not used consistent criteria for enrollment.[1] One criterion that has been proposed is the Hopkins Criteria, which provides a working definition of HPC families.[2] Using the Hopkins Criteria, kindreds with prostate cancer need to fulfill only one of following criteria to be considered to have HPC:

  1. Three or more affected first-degree relatives (father, brother, son).
  2. Affected relatives in three successive generations of either maternal or paternal lineages.
  3. At least two relatives affected at age 55 years or younger.

Using these criteria, surgical series have reported that approximately 3% to 5% of men will be from a family with HPC.[2,3]

An additional issue in linkage studies is the high background rate of sporadic prostate cancer in the context of family studies. Because a man’s lifetime risk of prostate cancer is one in seven,[4] it is possible that families under study have men with both inherited and sporadic prostate cancer. Thus, men who do not inherit the prostate cancer susceptibility gene that is segregating in their family may still develop prostate cancer. Currently there are no clinical or pathological features of prostate cancer that will allow differentiation between inherited and sporadic forms of the disease. Similarly, there are limited data regarding the clinical phenotype or natural history of prostate cancer associated with specific candidate loci. Measurement of the serum prostate-specific antigen (PSA) has been used inconsistently in evaluating families used in linkage analysis studies of prostate cancer. In linkage studies, the definition of an affected man can be biased by the use of serum PSA screening as the rates of prostate cancer in families will differ between screened and unscreened families.

One way to address inconsistencies between linkage studies is to require inclusion criteria that defines clinically significant disease (e.g., Gleason score ≥7, PSA ≥20 ng/mL) in an affected man.[5-7] This approach attempts to define a homogeneous set of cases/families to increase the likelihood of identifying a linkage signal. It also prevents the inclusion of cases that may be considered clinically insignificant that were identified by screening in families.

Investigators have also incorporated clinical parameters into linkage analyses with the goal of identifying genes that may influence disease severity.[8,9] This type of approach, however, has not yet led to the identification of consistent linkage signals across datasets.[10,11]

Susceptibility loci identified in linkage analyses

Table 2 summarizes the proposed prostate cancer susceptibility loci identified in families with multiple prostate cancer–affected individuals. Conflicting evidence exists regarding the linkage to some of the loci described above. Data on the proposed phenotype associated with each locus are also limited, and the strength of repeated studies is needed to firmly establish these associations. Evidence suggests that many of these prostate cancer loci account for disease in a small subset of families, which is consistent with the concept that prostate cancer exhibits locus heterogeneity.

Table 2. Proposed Prostate Cancer Susceptibility Loci
Gene Location Candidate Gene Clinical Testing Proposed Phenotype Comments 
HPC1 (OMIM)/RNASEL (OMIM) [12-34]1q25RNASEL Not availableYounger age at prostate cancer diagnosis (<65 y)Evidence of linkage is strongest in families with at least five affected persons, young age at diagnosis, and male-to-male transmission.
Higher tumor grade (Gleason score)
More advanced stage at diagnosisRNASEL mutations have been identified in a few 1q-linked families.
PCAP (OMIM) [1,9,16,23,35-44]1q42.2–43NoneNot availableYounger age at prostate cancer diagnosis (<65 y) and more aggressive diseaseEvidence of linkage is strongest in European families.
HPCX (OMIM) [33,39,45-51]Xq27–28NoneNot availableUnknownMay explain observation that an unaffected man with an affected brother has a higher risk than an unaffected man with an affected father.
CAPB (OMIM) [37,52-54]1p36NoneNot availableYounger age at prostate cancer diagnosis (<65 y)Strongest evidence of linkage was initially described in families with both prostate and brain cancer; follow-up studies indicate that this locus may be associated specifically with early-onset prostate cancer but not necessarily with brain cancer.
One or more cases of brain cancer
HPC20 (OMIM) [39,55-58]20q13NoneNot availableLater age at prostate cancer diagnosisEvidence of linkage is strongest in families with late age at diagnosis, fewer affected family members, and no male-to-male transmission.
No male-to-male transmission
8p [23,40,59-67]8p21–23MSR1 Not availableUnknownIn a genomic region commonly deleted in prostate cancer.
8q [44,68-85,85-87]8q24NoneNot availableMore aggressive diseaseData in some reports suggest that the population-attributable risk may be higher for African American men than for men of European origin.

Other genetic loci discovered by linkage analysis

Genome-wide linkage studies of families with prostate cancer have identified several other loci that may harbor prostate cancer susceptibility genes, emphasizing the underlying complexity and genetic heterogeneity of this cancer. The chromosomal regions with modest-to-strong statistical significance (logarithm of the odds [LOD] score ≥2) include the following chromosomes:

Linkage analyses in various familial phenotypes

Linkage studies have also been performed in specific populations or with specific clinical parameters to identify population-specific susceptibility genes or genes influencing disease phenotypes.

Linkage analysis in African American families

The African American Hereditary Prostate Cancer study conducted a genome-wide linkage study of 77 families with four or more affected men. Multipoint heterogeneity LOD (hLOD) scores of 1.3 to less than 2.0 were observed using markers that map to 11q22, 17p11, and Xq21. Analysis of the 16 families with more than six men with prostate cancer provided evidence for two additional loci: 2p21 (multipoint hLOD score = 1.08) and 22q12 (multipoint hLOD score = 0.91).[93,99] A smaller linkage study that included 15 African American hereditary prostate cancer families from the southeastern and southcentral Louisiana region identified suggestive linkage for prostate cancer at 2p16 (hLOD = 1.97) and 12q24 (hLOD = 2.21) using a 6,000 single nucleotide polymorphism (SNP) platform.[110] Further study including a larger number of African American families is needed to confirm these findings.

Linkage analysis in families with aggressive prostate cancer

In an effort to identify loci contributing to prostate cancer aggressiveness, linkage analysis was performed in families with one or more of the following: Gleason grade 7 or higher, PSA of 20 ng/mL or higher, regional or distant cancer stage at diagnosis, or death from metastatic prostate cancer before age 65 years. One hundred twenty-three families with two or more affected family members with aggressive prostate cancer were studied. Suggestive linkage was found at chromosome 22q11 (hLOD score = 2.18) and 22q12.3-q13.1 (hLOD score = 1.90).[5] These findings suggest that using a clinically defined phenotype may facilitate finding prostate cancer susceptibility genes. A fine-mapping study of 14 extended high-risk prostate cancer families has subsequently narrowed the genomic region of interest to an 880-kb region at 22q12.3.[106] An analysis of high-risk pedigrees from Utah provides an overview of this strategy.[111] A linkage analysis utilizing a higher resolution marker set of 6,000 SNPs was performed among 348 families from the International Consortium for Prostate Cancer Genetics with aggressive prostate cancer.[44] Aggressive disease was defined as Gleason score 7 or higher, invasion into seminal vesicles or extracapsular extension, pretreatment PSA level of 20 ng/mL or higher, or death from prostate cancer. The region with strongest evidence of linkage among aggressive prostate cancer families was 8q24 with LOD scores of 3.09–3.17. Additional regions of linkage included with LOD scores of 2 or higher included 1q43, 2q35, and 12q24.31. No candidate genes have been identified.

Linkage analysis in families with multiple cancers

In light of the multiple prostate cancer susceptibility loci and disease heterogeneity, another approach has been to stratify families based on other cancers, given that many cancer susceptibility genes are pleiotropic.[112] A genome-wide linkage study was conducted to identify a susceptibility locus that may account for both prostate cancer and kidney cancer in families. Analysis of 15 families with evidence of HPC and one or more cases of kidney cancer (pathologically confirmed) in a man with prostate cancer or in a first-degree relative of a man with prostate cancer revealed suggestive linkage with markers that mapped to an 8 cM region of chromosome 11p11.2-q12.2.[113] This observation awaits confirmation. Another genome-wide linkage study was conducted in 96 HPC families with one or more first-degree relatives with colon cancer. Evidence for linkage in all families was found in several regions, including 11q25, 15q14, and 18q21. In families with two or more cases of colon cancer, linkage was also observed at 1q31, 11q14, and 15q11-14.[112]

Summary of prostate cancer linkage studies

Linkage to chromosome 17q21-22 and subsequent fine-mapping and exome sequencing have identified recurrent mutations in the HOXB13 gene to account for a fraction of hereditary prostate cancer, particularly early-onset prostate cancer. The clinical utility of testing for HOXB13 mutations has not yet been defined. Furthermore, many linkage studies have mapped several prostate cancer susceptibility loci (Table 2), although the genetic alterations contributing to hereditary prostate cancer from these loci have not been consistently reproduced. With the evolution of high-throughput sequencing technologies, there will likely be additional highly penetrant genetic mutations identified to account for subsets of hereditary prostate cancer families.

Case-Control Studies

A case-control study involves evaluating factors of interest for association to a condition. The design involves investigation of cases with a condition of interest, such as a specific disease or gene mutation, compared with a control sample without that condition, but often with other similar characteristics (i.e., age, gender, and ethnicity). Limitations of case-control design with regard to identifying genetic factors include the following:[114,115]

  • Stratification of the population being studied. (Unknown population based genetic differences between cases and controls that could result in false positive associations.)[116]

  • Genetic heterogeneity. (Different alleles or loci that can result in a similar phenotype.)

  • Limitations of self-identified race or ethnicity and unknown confounding variables.

Additionally, identified associations may not always be valid, but they could represent a random association and, therefore, warrant validation studies.[114,115]

Genes interrogated in case-control studies

Androgen receptor gene

Androgen receptor (AR) gene variants have been examined in relation to both prostate cancer risk and disease progression. The AR is expressed during all stages of prostate carcinogenesis.[117] One study demonstrated that men with hereditary prostate cancer who underwent radical prostatectomy had a higher percentage of prostate cancer cells exhibiting expression of the AR and a lower percentage of cancer cells expressing estrogen receptor alpha than did men with sporadic prostate cancer. The authors suggest that a specific pattern of hormone receptor expression may be associated with hereditary predisposition to prostate cancer.[118]

Altered activity of the AR caused by inherited variants of the AR gene may influence risk of prostate cancer. The length of the polymorphic trinucleotide CAG and GGN microsatellite repeats in exon 1 of the AR gene (located on the X chromosome) have been associated with the risk of prostate cancer.[119,120] Some studies have suggested an inverse association between CAG repeat length and prostate cancer risk, and a direct association between GGN repeat length and risk of prostate cancer; however, the evidence is inconsistent.[117,119-129] A meta-analysis of 19 case-control studies demonstrated a statistically significant association between both short CAG length (odds ratio [OR], 1.2; 95% confidence interval [CI], 1.1–1.3) and short GGN length (OR, 1.3; 95% CI, 1.1–1.6) and prostate cancer; however, the absolute difference in number of repeats between cases and controls is less than one, leading the investigators to question whether these small, statistically significant differences are biologically meaningful.[130] Subsequently, the large multiethnic cohort study of 2,036 incident prostate cancer cases and 2,160 ethnically matched controls failed to confirm a statistically significant association (OR, 1.02; P = .11) between CAG repeat size and prostate cancer.[131] A study of 1,461 Swedish men with prostate cancer and 796 control men reported an association between AR alleles, with more than 22 CAG repeats and prostate cancer (OR, 1.35; 95% CI, 1.08–1.69; P = .03).[132]

An analysis of AR gene CAG and CGN repeat length polymorphisms targeted African American men from the Flint Men’s Health Study in an effort to identify a genetic modifier that might help explain the increased risk of prostate cancer in black versus white males in the United States.[133] This population-based study of 131 African American prostate cancer patients and 340 screened-negative African American controls showed no evidence of an association between shorter AR repeat length and prostate cancer risk. These results, together with data from three prior, smaller studies,[131,134,135] indicate that short AR repeat variants do not contribute significantly to the risk of prostate cancer in African American men.

Germline mutations in the AR gene (located on the X chromosome) have been rarely reported. The R726L mutation has been identified as a possible contributor to about 2% of both sporadic and familial prostate cancer in Finland.[136] This mutation, which alters the transactivational specificity of the AR protein, was found in 8 of 418 (1.91%) consecutive sporadic prostate cancer cases, 2 of 106 (1.89%) familial cases, and 3 of 900 (0.33%) normal blood donors, yielding a significantly increased prostate cancer OR of 5.8 for both case groups. A subsequent Finnish study of 38 early-onset prostate cancer cases and 36 multiple-case prostate cancer families with no evidence of male-to-male transmission revealed one additional R726L mutation in one of the familial cases and no new germline mutations in the AR gene.[137] These investigators concluded that germline AR mutations explain only a small fraction of familial and early-onset cases in Finland.

A study of genomic DNA from 60 multiple-case African American (n = 30) and white (n = 30) families identified a novel missense germline AR mutation, T559S, in three affected members of a black sibship and none in the white families. No functional data were presented to indicate that this mutation was clearly deleterious. This was reported as a suggestive finding, in need of additional data.[138]

Steroid 5-alpha-reductase 2 gene (SRD5A2)

Molecular epidemiology studies have also examined genetic polymorphisms of the steroid 5-alpha-reductase 2 gene, which is also involved in the androgen metabolism cascade. Two isozymes of 5-alpha-reductase exist. The gene that codes for 5-alpha-reductase type II (SRD5A2) is located on chromosome 2. It is expressed in the prostate, where testosterone is converted irreversibly to dihydrotestosterone (DHT) by 5-alpha-reductase type II.[139] Evidence suggests that 5-alpha-reductase type II activity is reduced in populations at lower risk of prostate cancer, including Chinese and Japanese men.[140,141]

A polymorphism in the untranslated region of the SRD5A2 gene may also be associated with prostate cancer risk.[142] Ten alleles fall into three families that differ in the number of TA dinucleotide repeats.[139,143] Although no clinical significance for these polymorphisms has yet been determined, some TA repeat alleles may promote an elevation of enzyme activity, which may in turn increase the level of DHT in the prostate.[117,139] A subsequent meta-analysis failed to detect a statistically significant association between prostate cancer risk and the TA repeat polymorphism, although a relationship could not be definitively excluded.[144] This meta-analysis also examined the potential roles of two coding variants: A49T and V89L. An association with V89L was excluded, and the role for A49T was found to have at most a modest effect on prostate cancer susceptibility. Bias or chance could account for the latter observation. A study of 1,461 Swedish men with prostate cancer and 796 control men reported an association between two variants in SRD5A2 and prostate cancer risk (OR, 1.45; 95% CI, 1.01–2.08; OR, 1.49; 95% CI, 1.03–2.15).[132] Another meta-analysis of 25 case-control studies, including 8,615 cases and 9,089 controls, found no overall association between the V89L polymorphism and prostate cancer risk. In a subgroup analysis, men younger than 65 years (323 cases and 677 controls) who carried the LL genotype had a modest association with prostate cancer (LL vs. VV, OR, 1.70; 95% CI, 1.09–2.66 and LL vs. VV+VL, OR, 1.75; 95% CI, 1.14–2.68).[145] A subsequent systematic review and meta-analysis including 27 nonfamilial case-control studies found no statistically significant association between either the V89L or A49T polymorphisms and prostate cancer risk.[146]

Polymorphisms in several genes involved in the biosynthesis, activation, metabolism, and degradation of androgens (CYP17, CYP3A4, CYP19A1, and SRD5A2) and the stimulation of mitogenic and antiapoptotic activities (IGF-1 and IGFBP-3) of normal prostate cells were examined for association with prostate cancer in 131 African American cases and 342 controls. While allele frequencies did not differ between cases and controls regarding three SNPs in the CYP17 gene (rs6163, rs6162, and rs743572), heterozygous genotypes of these SNPs were found to be associated with a reduced risk (OR, 0.56; 95% CI, 0.35–0.88; OR, 0.57; 95% CI, 0.36–0.90; OR, 0.55; 95% CI, 0.35–0.88, respectively). Evidence suggestive of an association between SNP rs5742657 in intron 2 of IGF-1 was also found (OR, 1.57; 95% CI, 0.94–2.63).[147] Additional studies are needed to confirm these findings.

Estrogen receptor-beta gene

Other investigators have explored the potential contribution of the variation in genes involved in the estrogen pathway. A Swedish population study of 1,415 prostate cancer cases and 801 age-matched controls examined the association of SNPs in the estrogen receptor-beta (ER-beta) gene and prostate cancer. One SNP in the promoter region of ER-beta, rs2987983, was associated with an overall prostate cancer risk of 1.23 and 1.35 for localized disease.[148] This study awaits replication.

E-cadherin gene

Germline mutations in the tumor suppressor gene E-cadherin (also called CDH1) cause a hereditary form of gastric carcinoma. A SNP designated -160→A, located in the promoter region of E-cadherin, has been found to alter the transcriptional activity of this gene.[149] Because somatic mutations in E-cadherin have been implicated in the development of invasive malignancies in a number of different cancers,[150] investigators have searched for evidence that this functionally significant promoter might be a modifier of cancer risk. A meta-analysis of 47 case-control studies in 16 cancer types included ten prostate cancer cohorts (3,570 cases and 3,304 controls). The OR of developing prostate cancer among risk allele carriers was 1.33 (95% CI, 1.11–1.60). However, the authors of the study noted that there are sources of bias in the dataset, stemming mostly from the small sample sizes of individual cohorts.[151] Additional studies are required to determine whether this finding is reproducible and biologically and clinically important.

Toll-like receptor genes

There is a great deal of interest in the possibility that chronic inflammation may represent an important risk factor in prostate carcinogenesis.[152] The family of toll-like receptors has been recognized as a critical component of the intrinsic immune system,[153] one which recognizes ligands from exogenous microbes and a variety of endogenous substrates. This family of genes has been studied most extensively in the context of autoimmune disease, but there also have been a series of studies that have analyzed genetic variants in various members of this pathway as potential prostate cancer risk modifiers.[154-158] The results have been inconsistent, ranging from decreased risk, to null association, to increased risk.

One study was based upon 1,414 incident prostate cancer cases and 1,414 age-matched controls from the American Cancer Society Cancer Prevention Study II Nutrition Cohort.[159] These investigators genotyped 28 SNPs in a region on chromosome 4p14 that includes TLR-10, TLR-1, and TLR-6, three members of the toll-like receptor gene cluster. Two TLR-10 SNPs and four TLR-1 SNPs were associated with significant reductions in prostate cancer risk, ranging from 29% to 38% for the homozygous variant genotype. A more detailed analysis demonstrated these six SNPs were not independent in their effect, but rather represented a single strong association with reduced risk (OR, 0.55; 95% CI, 0.33–0.90). There were no significant differences in this association when covariates such as Gleason score, history of benign prostatic hypertrophy, use of nonsteroidal anti-inflammatory drugs, and body mass index were taken into account. This is the largest study undertaken to date and included the most comprehensive panel of SNPs evaluated in the 4p14 region. While these observations provide a basis for further investigation of the toll-like receptor genes in prostate cancer etiology, inconsistencies with the prior studies and lack of information regarding what the biological basis of these associations might be warrant caution in interpreting the findings.

Other genes and polymorphisms interrogated for risk

SNPs in genes involved in the steroid hormone pathway have previously been studied in sporadic and familial prostate cancer using a sample of individuals with primarily Caucasian ancestry.[160] Another study evaluated 116 tagging SNPs located in 12 genes in the steroid hormone pathway for risk of prostate cancer in 886 cases and 1,566 controls encompassing non-Hispanic white men, Hispanic white men, and African American men.[161] The genes included CYP17, HSD17B3, ESR1, SRD5A2, HSD3B1, HSD3B2, CYP19, CYP1A1, CYP1B1, CYP3A4, CYP27B1, and CYP24A1. Several SNPs in CYP19 were associated with prostate cancer risk in all three populations. Analysis of SNP-SNP interactions involving SNPs in multiple genes revealed a seven-SNP interaction involving HSD17B3, CYP19, and CYP24A1 in Hispanic whites (P = .001). In non-Hispanic whites, an interaction of four SNPs in HSD3B2, HSD17B3, and CYP19 was found (P < .001). In African Americans, SNPs within SRD5A2, HSD17B3, CYP17, CYP27B1, CYP19, and CYP24A1 showed a significant interaction (P = .014). In non-Hispanic whites, a cumulative risk of prostate cancer was observed for men carrying risk alleles at three SNPs in HSD3B2 and CYP19 (OR, 2.20; 95% CI, 1.44–3.38; P = .0003). In Hispanic whites, a cumulative risk of prostate cancer was observed for men carrying risk alleles at two SNPs in CYP19 and CYP24A1 (OR, 4.29; 95% CI, 2.11–8.72; P = .00006). While this study did not evaluate all potentially important SNPs in genes in the steroid hormone pathway, it demonstrates how studies can be performed to evaluate multigenic effects in multiple populations to assess the contribution to prostate cancer risk.

A meta-analysis of the relationship between eight polymorphisms in six genes (MTHFR, MTR, MTHFD1, SLC19A1, SHMT1, and FOLH1) from the folate pathway was conducted by pooling data from eight case-control studies, four GWAS, and a nested case-control study named Prostate Testing for Cancer and Treatment in the United Kingdom. Numbers of tested subjects varied among these polymorphisms, with up to 10,743 cases and 35,821 controls analyzed. The report concluded that known common folate-pathway SNPs do not have significant effects on prostate cancer susceptibility in white men.[162]

Four SNPs in the p53 pathway (three in genes regulating p53 function including MDM2, MDM4, and HAUSP and one in p53) were evaluated for association with aggressive prostate cancer in a hospital-based prostate cancer cohort of men with Caucasian ethnicity (N = 4,073).[163] However, a subsequent meta-analysis of case-control studies that focused on MDM2 (T309G) and prostate cancer risk revealed no association.[164] Therefore, the biologic basis of the various associations identified requires further study.

Table 3 summarizes additional case-control studies that have assessed genes that are potentially associated with prostate cancer susceptibility.

Table 3. Case-Control Studies in Genes With Some Association With Prostate Cancer Risk
Gene Location Study Population Controls Prostate Cancer Associations Comments  
AJ = Ashkenazi Jewish; CI = confidence interval; HR = hazard ratio; OMIM = Online Mendelian Inheritance in Man; OR = odds ratio; PSA = prostate-specific antigen; SNP = single nucleotide polymorphism.
AMACR (OMIM)5p13.3Zheng et al. (2002) [165]159 U.S. men with familial prostate cancer and 245 men with sporadic prostate cancer211 men without prostate cancer who are participants in a prostate cancer screening programNot assessedGenotype frequencies that compared familial prostate cancer cases to unaffected controls found four missense variants associated with familial prostate cancer (M9V, G1157D, S291L, and K277E).
Daugherty et al. (2007) [166]1,318 U.S. men aged <55 y with prostate cancer (1,211 non-Hispanic whites and 107 non-Hispanic blacks) unselected for family history1,842 U.S. men without prostate cancer who participated in a prostate cancer screening program (1,433 non-Hispanic whites and 409 non-Hispanic blacks)No association was detected between any of the SNPs (M9V, IVS+169G>T, D175G, S201L, Q239H, IVS4+3803C>G, and K277E) and prostate cancer.Risk of prostate cancer was reduced in men who regularly used ibuprofen who also had specific alleles in four SNPs (M9V, D175G, S201L, and K77E) or a specific six-SNP haplotype (TGTGCG).
Levin et al. (2007) [167]449 U.S. white men with familial prostate cancer from 332 familial and early-onset prostate cancer families394 unaffected brothers of the men with prostate cancerSNP rs3195676 (M9V):
OR, 0.58 (95% CI, 0.38–0.90; P = .01 for a recessive model)
NBS1 (OMIM)8q21Hebbring et al. (2006) [168]1,819 U.S. and European men with familial prostate cancer from 909 families and 1,218 U.S. and European men with sporadic prostate cancer697 controls consisting of a mix of U.S. and European population-based controls and unaffected men from prostate cancer families657del5 was not detected in the control population; therefore, testing for an association was not possible.657del5 had a carrier frequency of 0.22% (2 of 909) for familial prostate cancer and 0.25% (3 of 1,218) for sporadic prostate cancer.
Cybulski et al. (2013) [169]3,750 Polish men with prostate cancer3,956 Polish men with no history of cancer675del5: OR, 2.5 (95% CI, 1.5–4.0; P = .0003)NBS1 mutations were associated with a higher mortality (HR, 1.85) and lower 5-year survival (HR, 2.08).
Prostate cancer diagnosed <60 y: OR, 3.1 (95% CI, 1.5–6.4; P = .003)
Familial prostate cancer: OR, 4.3 (95% CI, 2.0–9.0; P = .0001)
KLF6 (OMIM)10p15Narla et al. (2005) [170]1,253 U.S. men with sporadic prostate cancer and 882 men with familial prostate cancer from 294 unrelated families1,276 men with no cancer historyIVS1-27G>A:
Familial cases: OR, 1.61 (95% CI, 1.20–2.16; P = .01)
Sporadic cases: OR, 1.41 (95% CI, 1.08–2.00; P = .01)
Bar-Shira et al. (2006) [171]402 Israeli men with prostate cancer (251 AJ, 151 non-AJ)300 Israeli women aged 20–45 y (200 AJ, 100 non-AJ)IVS1-27G>A:
AJ only: OR, 0.60 (95% CI, 0.35–1.03; P = .047)
Combined cohort: OR, 0.64 (95% CI, 0.42–0.98; P = .047)
EMSY (OMIM)11q13.5Nurminen et al. (2011) [172]Initial Screen: 184 Finnish men with familial prostate cancer923 male blood donors from the Finnish Red Cross with no cancer historyIVS6-43A>G:IVS6-43A>G also associated with increased risk of aggressive prostate cancer (PSA ≥20 or Gleason score ≥7) in cases unselected for family history (OR, 6.5; 95% CI, 1.5–28.4; P = .002).
Validation: 2,113 unselected prostate cancer casesFamilial cases: OR, 7.5 (95% CI, 1.3–45.5; P = .02)
CHEK2 (OMIM)22q12.1Dong et al. (2003) [173]84 prostate cancer tumors; 92 prostate cancer tumors diagnosed in men younger than 59 y; 400 U.S. men with prostate cancer and no prostate cancer family history; 298 men with prostate cancer from 149 families (two men per family)510 U.S. men without prostate cancer with a negative prostate cancer screening exam18 CHEK2 mutations were identified in 4.8% (28 of 578) of prostate cancer patients, 0 of 423 unaffected men, and 9 of 149 prostate cancer families.157T was detected in equal numbers of cases and controls and was therefore reported to likely represent a polymorphism.
Cybulski et al. (2013) [169]3,750 Polish men with prostate cancer3,956 Polish men with no history of cancerAny CHEK2 mutation: OR, 1.9 (95% CI, 1.6–2.2; P < .0001)
Prostate cancer diagnosed <60 y: OR, 2.3 (95% CI, 1.8–3.1; P < .0001)
Familial prostate cancer: OR, 2.7 (95% CI, 2.0–3.7; P < .0001)

Case-control studies assessed site-specific prostate cancer susceptibility in the following genes: EMSY, KLF6, AMACR, NBS1, CHEK2, AR, SRD5A2, ER-beta, E-cadherin, and the toll-like receptor genes. These studies have been complicated by the later-onset nature of the disease and the high background rate of prostate cancer in the general population. In addition, there is likely to be real, extensive locus heterogeneity for HPC, as suggested by both segregation and linkage studies. In this respect, HPC resembles a number of the other major adult-onset hereditary cancer syndromes, in which more than one gene can produce the same or very similar clinical phenotype (e.g., hereditary breast/ovarian cancer, Lynch syndrome, hereditary melanoma, and hereditary renal cancer). The clinical validity and utility of genetic testing for any of these genes based solely on evidence for HPC susceptibility has not been established.

Admixture Mapping

Admixture mapping is a method used to identify genetic variants associated with traits and/or diseases in individuals with mixed ancestry.[174] This approach is most effective when applied to individuals whose admixture was recent and consists of two populations who had previously been separated for thousands of years. The genomes of such individuals are a mosaic, comprised of large blocks from each ancestral locale. The technique takes advantage of a difference in disease incidence in one ancestral group compared with another. Genetic risk loci are presumed to reside in regions enriched for the ancestral group with higher incidence. Successful mapping depends on the availability of population-specific genetic markers associated with ancestry, and on the number of generations since admixture.[175,176]

Admixture mapping is a particularly attractive method for identifying genetic loci associated with increased prostate cancer risk among African Americans. African American men are at higher risk of developing prostate cancer than are men of European ancestry, and the genomes of African American men are mosaics of regions from Africa and regions from Europe. It is therefore hypothesized that inherited variants accounting for the difference in incidence between the two groups must reside in regions enriched for African ancestry. In prostate cancer admixture studies, genetic markers for ancestry were genotyped genome-wide in African American cases and controls in a search for areas enriched for African ancestry in the men with prostate cancer. Admixture studies have identified the following chromosomal regions associated with prostate cancer:

An advantage of this approach is that recent admixtures result in long stretches of linkage disequilibrium (up to hundreds of thousands of base pairs) of one particular ancestry.[178] As a result, fewer markers are needed to search for genetic variants associated with specific diseases, such as prostate cancer, than the number of markers needed for successful GWAS.[175] (Refer to the GWAS section of this summary for more information.)

Genome-wide Association Studies (GWAS)

Overview
  • GWAS can identify inherited genetic variants that influence risk of disease.

  • For complex diseases, such as prostate cancer, risk of developing the disease is the product of multiple genetic and environmental factors; each individual factor contributes relatively little to overall risk.

  • To date, GWAS have discovered dozens of genetic variants associated with prostate cancer risk.

  • Individuals can be genotyped for all known prostate cancer risk markers relatively easily; but, to date, studies have not demonstrated that this information contributes substantially to variables commonly used to assess risk, such as family history.

  • The clinical relevance of variants identified from GWAS remains unclear.

Introduction to GWAS

Genome-wide searches have successfully identified susceptibility alleles for many complex diseases,[179] including prostate cancer. This approach can be contrasted with linkage analysis, which searches for genetic risk variants co-segregating within families that have a high prevalence of disease. Linkage analyses are designed to uncover rare, highly penetrant variants that segregate in predictable heritance patterns (e.g., autosomal dominant, autosomal recessive, X-linked, and mitochondrial). GWAS, on the other hand, are best suited to identify multiple, common, low-penetrance genetic polymorphisms. GWAS are conducted under the assumption that the genetic underpinnings of complex phenotypes, such as prostate cancer, are governed by many alleles, each conferring modest risk. Most genetic polymorphisms genotyped in GWAS are common, with minor allele frequencies greater than 1% to 5% within a given ancestral population (e.g., men of European ancestry). GWAS survey all common inherited variants across the genome, searching for alleles that are associated with incidence of a given disease or phenotype.[180,181] The strong correlation between many alleles located close to one another on a given chromosome (called linkage disequilibrium) allows one to “scan” the genome without having to test all tens of millions of known SNPs. GWAS can test approximately 1 million SNPs and ascertain almost all common inherited variants in the genome.

In a GWAS, allele frequency is compared for each SNP between cases and controls. Promising signals–in which allele frequencies deviate significantly in case and control populations–are validated in replication cohorts. In order to have adequate statistical power to identify variants associated with a phenotype, large numbers of cases and controls, typically thousands of each, are studied. Because 1 million SNPs are typically evaluated in a GWAS, false-positive findings are expected to occur frequently whenstandard statistical thresholds are used. Therefore, stringent statistical rules are used to declare a positive finding, usually using a threshold of P < 1 × 10-7.[182-184]

To date, approximately 80 variants associated with prostate cancer have been identified by well-powered GWAS and validated in independent cohorts (see Table 4). These studies have revealed convincing associations between specific inherited variants and prostate cancer risk. However, the findings should be qualified with a few important considerations:

  1. GWAS reported thus far have been designed to identify relatively common genetic polymorphisms. It is very unlikely that an allele with high frequency in the population by itself contributes substantially to cancer risk. This, coupled with the polygenic nature of prostate tumorigenesis, means that the contribution by any single variant identified by GWAS to date is quite small, generally with an OR for disease risk of less than 1.5. In addition, despite extensive genome-wide interrogation of common polymorphisms in tens of thousands of cases and controls, GWAS findings to date do not account for even half of the genetic component of prostate cancer risk.[185,186]

  2. Variants uncovered by GWAS are not likely to be the ones directly contributing to disease risk. As mentioned above, SNPs exist in linkage disequilibrium blocks and are merely proxies for a set of variants—both known and previously undiscovered—within a given block. The causal allele is located somewhere within that linkage disequilibrium block.

  3. Admixture by groups of different ancestry can confound GWAS findings (i.e., a statistically significant finding could reflect a disproportionate number of subjects in the cases versus controls, rather than a true association with disease). Therefore, GWAS subjects, by design, comprise only one ancestral group. As a result, many populations remain underrepresented in genome-wide analyses–notably African Americans, whose risk of prostate cancer is among the highest in the world.

The implications of these points are discussed in greater detail below. Additional detail can be found elsewhere.[187]

Candidate genes and susceptibility loci identified in GWAS

In 2006, two genome-wide studies seeking associations with prostate cancer risk converged on the same chromosomal locus, 8q24. Using a technique called admixture mapping, a 3.8 megabase (Mb) region emerged as significantly involved with risk in African American men.[69] In another study, linkage analysis of 323 Icelandic prostate cancer cases also revealed an 8q24 risk locus.[68] Detailed genotyping of this region and an association study for prostate cancer risk in three case-control populations in Sweden, Iceland, and the United States revealed specific 8q24 risk markers: a SNP, rs1447295, and a microsatellite polymorphism, allele-8 at marker DG8S737.[68] The population-attributable risk of prostate cancer from these alleles was 8%. The results were replicated in an African American case-control population, and the population attributable risk was 16%.[68] These results were confirmed in several large, independent cohorts.[70-73,80-83,188] Subsequent GWAS independently converged on another risk variant at 8q24, rs6983267.[73-75] Fine mapping, genotyping a large number of variants densely packed within a region of interest in many cases and controls, was performed across 8q24 targeting the variants most significantly associated with prostate cancer risk. Across multiple ethnic populations, three distinct 8q24 risk loci were described: region 1 (containing rs1447295) at 128.54–128.62 Mb, region 2 at 128.14–128.28 Mb, and region 3 (containing rs6983267) at 128.47–128.54 Mb.[75] Variants within each of these three regions independently confer disease risk with ORs ranging from 1.11 to 1.66. In 2009, two separate GWAS uncovered two additional risk regions at 8q24. In all, approximately nine genetic polymorphisms, all independently associated with disease, reside within five distinct 8q24 risk regions.[86,87]

Since the discovery of prostate cancer risk loci at 8q24, other chromosomal risk loci similarly have been identified by multistage GWAS comprised of thousands of cases and controls and validated in independent cohorts. The most convincing associations reported to date for men of European ancestry are included in Table 4. The association between risk and allele status for each variant listed in Table 4 reached genome-wide statistical significance in more than one independent cohort.

Table 4. Prostate Cancer Susceptibility Loci Identified Through GWAS in Men of European Ancestry
SNP Chromosomal Locus Nearest Known Gene Within 100 kb Region Study Citations ORa 
rs12185821p21KCNN3 Intronic[186]1.06
rs42457391q32MDM4 Exonic/Coding[186]0.91
rs101874242p11GGCX Intergenic[185]1.06–1.19
rs7210482p15EHBP1 Intronic[189]1.15
rs14656182p21THADA Intronic[190]1.16–1.20
rs119022362p25GRHL1 Intronic[186]1.07
rs126212782q31ITGA6 Intronic[190]1.32–1.47
rs22928842q37MLPH Intronic[191]1.14
rs37715702q37FARP2 Intronic[186]1.12
rs26607533p12VGLL3 Intergenic[192]1.11–1.48
rs76116943q13SIDT1 Intronic[186]0.91
rs109348533q21EEFSEC Intronic[193]1.12
rs67639313q23ZBTB38 Intronic[191]1.04–1.18
rs109366323q26CLDN11 Intergenic[185]1.08–1.28
rs18942924q13AFM Intronic[186]0.91
rs125004264q22PDLIM5 Intronic[190]1.14–1.17
rs17021918Intronic[190]1.12–1.25
rs76796734q24TET2 Intergenic[190]1.15–1.37
rs21218755p12FGF10 Intronic[185]1.05–1.11
rs22426525p15TERT Intronic[191]1.15–1.39
rs68698415q35BOD1 Intergenic[186]1.07
rs1300676p21CCHCR1 Exonic/Coding[191]1.05–1.20
rs3096702NOTCH4 Intergenic[186]1.07
rs22736696q21ARMC2 Intronic[186]1.07
rs19334886q25RSG17 Intronic[186]0.89
rs9364554SLC22A3 Intronic[192]1.17–1.26
rs104865677p15JAZF1 Intronic[194,195]1.12–1.35
rs121551727p21NoneIntergenic[186]1.11
rs64656577q21LMTK2 Intronic[192]1.03–1.19
rs29286798p21SLC25A37 Intergenic[190]1.16–1.26
rs1512268NKX3-1 Intergenic[190]1.13–1.28
rs11135910EBF2 Intronic[186]1.11
rs100869088q24NoneIntergenic[87]1.14–1.25
rs7841060Intergenic[86]1.19
rs13254738Intergenic[75]1.11
rs16901979Intergenic[74,195]1.31–1.66
rs16902094Intergenic[193]1.21
rs445114Intergenic[193]1.14
rs620861Intergenic[86,87]1.11–1.28
rs6983267Intergenic[73,75,87,194,195]1.13–1.42
rs7000448Intergenic[75]1.14
rs1447295Intergenic[68,73,74,195]1.29–1.72
rs1099399410q11MSMB Intergenic[192,195]1.15–1.42
rs385069910q24TRIM8 Intronic[186]0.91
rs496241610q26CTBP2 Intronic[194]1.17–1.20
rs712790011p15TH Intergenic[190]1.29–1.40
rs1122856511q13MYEOV Intergenic[193]1.23
rs7931342Intergenic[192]1.19–1.25
rs10896449Intergenic[195,196]1.09–1.20
rs12793759Intergenic[196]1.04–1.18
rs10896438Intergenic[196]1.02–1.12
rs1156881811q22MMP7 Intergenic[186]0.91
rs90277412q13KRT8 Intergenic[191]1.17
rs10875943TUBA1C Intergenic[185]1.02–1.18
rs127088412q24NoneIntergenic[186]1.07
rs800827014q22FERMT2 Intronic[186]0.89
rs714152914q24RAD51B Intergenic[186]1.09
rs68423217p13VPS53 Intergenic[186]1.10
rs1164974317q12HNF1B Intronic[195,197,198]0.86–1.28
rs4430796Intronic[102,195,197,198]0.87–1.12
rs7405696Intronic[198]1.11
rs4794758Intronic[198]0.88
rs1016990Intronic[198]1.07
rs3094509Intronic[198]1.06
rs1165049417q21ZNF652 Intergenic[186]1.15
rs185996217q24NoneIntergenic[102,195]1.17–1.20
rs724199318q23SALL3 Intergenic[186]0.92
rs810247619q13PPP1R14A Intergenic[193]1.12
rs2735839KLK3 Intergenic[192]1.25–1.72
rs17632542KLK3 Intergenic[199]0.62–0.76
rs242734520q13RBBP8NL Intergenic[186]0.94
rs6062509ZGPAT Intronic[186]0.89
rs575916722q13BIK Intergenic[190]1.14–1.20
rs5945619Xp11NUDT11 Intergenic[192,195]1.19–1.46
rs2405942Xp22SHROOM2 Intronic[186]0.88
rs5919432Xq12AR Intergenic[191]1.06–1.14

GWAS = genome-wide association studies; OR = odds ratio; SNP = single nucleotide polymorphism.
aORs are reported as a range across the various stages of GWAS discovery and validation when available.

GWAS in populations of non-European ancestry

Most prostate cancer GWAS data generated to date have been derived from populations of European descent. This shortcoming is profound, considering that linkage disequilibrium structure, SNP frequencies, and incidence of disease differ across ancestral groups. To provide meaningful genetic data to all patients, well-designed, adequately powered GWAS must be aimed at specific ethnic groups. Most work in this regard has focused on African American, Chinese, and Japanese men. The most convincing associations reported to date for men of non-European ancestry are included in Table 5. The association between risk and allele status for each variant listed in Table 5 reached genome-wide statistical significance in more than one independent cohort.

Table 5. Prostate Cancer Susceptibility Loci Identified Through Genome-wide Association Studies (GWAS) in Men of Non-European Ancestry
SNP  Chromosomal Locus Nearest Known Gene Within 100 kb Region Study Citations  ORa 
African American Population
rs169019798q24NoneIntergenic[200]1.00–1.57
rs6983267Intergenic[200]0.83–2.43
rs7839365Intergenic[201]1.16–1.18
rs753228Intergenic[201]1.41–1.43
rs4871008Intergenic[201]1.15–1.19
rs1456315Intergenic[201]1.23–1.27
rs10098156Intergenic[201]1.26–1.30
rs6987409Intergenic[201]1.33–1.42
rs13282506Intergenic[201]1.25–1.28
rs7812429Intergenic[201]1.30–1.31
rs4313118Intergenic[201]1.16–1.17
rs1447295Intergenic[69]1.05
DG85737Intergenic[69]1.05
rs721010017q21ZNF652 Intronic[202]1.40–1.67
Chinese Population
rs8178269q31.2RAD23B-KLF4 Intergenic[203]1.33–1.43
rs10329419q13.4LILRA3 Intergenic[203]1.25–1.40
Japanese Population
rs20288982p11GGCX Intronic[204]0.96–1.22
rs133851912p24C2orf43 Intronic[205]1.12–1.22
rs20551093p11.2NoneIntergenic[204]1.15–1.33
rs26607533p12.1NoneIntergenic[206]1.42
rs126539465p15NoneIntergenic[205]1.23–1.31
rs19838916p21FOXP4 Intronic[205]1.11–1.23
rs3393316q22RFX6 and GPRC6AIntronic[205]1.18–1.22
rs132547388q24NoneIntergenic[206]1.59
rs6983561Intergenic[206]1.81
rs100090154Intergenic[206]1.41
rs225200410q26NoneIntergenic[204]1.12–1.23
rs193878111q12FAM111A Intergenic[204]1.11–1.25
rs960007913q22NoneIntergenic[205]1.17–1.19
rs443079617q12NoneIntronic[206]1.51

OR = odds ratio; SNP = single nucleotide polymorphism.
aORs are reported as a range across the various stages of GWAS discovery and validation when available.

The African American population is of particular interest because American men with African ancestry are at higher risk of prostate cancer than any other group. In addition, inherited variation at the 8q24 risk locus appears to contribute to differences in African American and European American incidence of disease.[69] A handful of studies have sought to determine whether GWAS findings in men of European ancestry are applicable to men of African ancestry. One study interrogated 28 known prostate cancer risk loci via fine mapping in 3,425 African American cases and 3,290 African American controls.[201] On average, risk allele frequencies were 0.05 greater in African Americans than in European Americans. Of the 37 known risk SNPs analyzed, 18 replicated in the African American population were significantly associated with prostate cancer at P ≤ .05 (the study was underpowered to properly assess nine of the remaining 19 SNPs). For seven risk regions (2p24, 2p15, 3q21, 6q22, 8q21, 11q13, and 19q13), fine mapping identified SNPs in the African American population more strongly associated with risk than the index SNPs reported in the original European-based GWAS. Fine mapping of the 8q24 region revealed four SNPs associated with disease that are substantially more common in African Americans. The SNP most strongly correlated with disease among African Americans (rs6987409) is not strongly correlated with a European risk allele and may account for a portion of increased risk in the African American population. In all, the risk SNPs identified in this study are estimated to represent 11% of total inherited risk.

Some of the risk variants identified in Table 5 have also been found to confer risk in men of European ancestry. These include rs16901979, rs6983267, and rs1447295 at 8q24 in African Americans and rs13254738 in Japanese populations. Additionally, the Japanese rs4430796 at 17q12 and rs2660753 at 3p12 have also been observed in men of European ancestry. However, the vast majority of the variants identified in these studies reveal novel variants that are unique to that specific ethnic population. These results confirm the importance of evaluating SNP associations in different ethnic populations. Considerable effort is still needed to fully annotate genetic risk in these and other populations.

Clinical application of GWAS findings

Because the variants discovered by GWAS are markers of risk, there has been great interest in using genotype as a screening tool to predict the development of prostate cancer. In an attempt to determine the potential clinical value of risk SNP genotype, cases of prostate cancer (n = 2,893) were identified from four cancer registries in Sweden. Controls (n = 1,781) were randomly selected from the Swedish Population Registry and were matched to cases by age and geographic region.[78] Known risk SNPs from 8q24, 17q12, and 17q24.3 were analyzed (rs4430796 at 17q12, rs1859962 at 17q24.3, rs16901979 at 8q24 [region 2], rs6983267 at 8q24 [region 3], and rs1447295 at 8q24 [region 1]). ORs for prostate cancer for men carrying any combination of one, two, three, or four or more genotypes associated with prostate cancer were estimated by comparing them with men carrying none of the associated genotypes using logistic regression analysis. Men who carried one to five risk alleles had an increasing likelihood of having prostate cancer compared with men carrying none of the alleles (P = 6.75 × 10-27). After controlling for age, geographic location, and family history of prostate cancer, men carrying four or more of these alleles had a significant elevation in risk of prostate cancer (OR, 4.47; 95% CI, 2.93–6.80; P = 1.20 × 10-13). When family history was added as a risk factor, men with five or more factors (five SNPs plus family history) had an even stronger risk of prostate cancer (OR, 9.46; 95% CI, 3.62–24.72; P = 1.29 × 10-8). The population-attributable risks (PARs) for these five SNPs were estimated to account for 4% to 21% of prostate cancer cases in Sweden, and the joint PAR for prostate cancer of the five SNPs plus family history was 46%.

A second study assessed prostate cancer risk associated with a family history of prostate cancer in combination with various numbers of 27 risk alleles identified through four prior GWAS. Two case-control populations were studied, the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial (PLCO) in the United States (1,172 cases and 1,157 controls) and the Cancer of the Prostate in Sweden (CAPS) study (2,899 cases and 1,722 controls). The highest risk of prostate cancer from the CAPS population was observed in men with a positive family history and greater than 14 risk alleles (OR, 4.92; 95% CI, 3.64–6.64). Repeating this analysis in the PLCO population revealed similar findings (OR, 3.88; 95% CI, 2.83–5.33).[207]

However, the proportion of men carrying large numbers of the risk alleles was low. While ORs were impressively high for this subset, they do not reflect the utility of genotyping the overall population. Receiver operating characteristic curves were constructed in these studies to measure the sensitivity and specificity of certain risk profiles. The area under the curve (AUC) was 0.61 when age, geographic region, and family history were used to assess risk. When genotype of the five risk SNPs at chromosomes 8 and 17 were introduced, a very modest AUC improvement to 0.63 was detected.[78] The addition of more recently discovered SNPs to the model has not appreciably improved these results.[208] While genotype may inform risk status for the small minority of men carrying multiple risk alleles, testing of the known panel of prostate cancer SNPs is currently of questionable clinical utility.[209]

Another study incorporated 10,501 prostate cancer cases and 10,831 controls from multiple cohorts (including PLCO) and genotyped each individual for 25 prostate cancer risk SNPs. Age and family history data were available for all subjects. Genotype data helped discriminate those who developed prostate cancer from those who did not. However, similar to the series above, discriminative ability was modest and only compelling at the extremes of risk allele distribution in a relatively small subset population; younger subjects (men aged 50 to 59 years) with a family history of disease who were in 90th percentile for risk allele status had an absolute 10-year risk of 6.7% compared with an absolute 10-year risk of 1.6% in men in the 10th percentile for risk allele status.[210]

In July 2012, the Agency for Healthcare Research and Quality (AHRQ) published a report that sought to address the clinical utility of germline genotyping of prostate cancer risk markers discovered by GWAS.[209] Largely on the basis of the evidence from the studies described above, AHRQ concluded that established prostate cancer risk SNPs have “poor discriminative ability” to identify individuals at risk of developing the disease. Similarly, the authors of another study estimated that the contribution of GWAS polymorphisms in determining the risk of developing prostate cancer will be modest, even as meta-analyses or larger studies uncover additional “common” risk alleles (alleles carried by >1%–5% of individuals within the population).[211]

GWAS findings to date account for only a fraction of heritable risk of disease. Research is ongoing to uncover the remaining portion of genetic risk. This includes the discovery of rarer alleles with higher ORs for risk. For example, a consortium led by deCODE genetics in Iceland performed whole-genome sequencing of 2,500 Icelanders and identified approximately 32.5 million variants, including millions of rare variants (carried by <1% of the population). These variants were analyzed in 5,141 prostate cancer cases and 54,444 controls (genotypes were imputed in cases in which they had not been genotyped in previous analyses). In addition to previously reported risk alleles at 8q24 and 17q12, significant associations with prostate cancer were observed for two rare 8q24 SNPs—the minor allele (the G allele) of rs183373024 (OR, 2.69; P = 1.5 × 10−23) and the minor allele (the A allele) of rs188140481 (OR, 2.88; P = 1.5 × 10−22).[212] These results were validated in independent cohorts of European cases and controls. The frequencies of the risk alleles of these two variants in controls ranged from 0.1% to 1.1% and were lowest in southern Europe and highest in northern Europe. These data, in which risk alleles had high ORs compared with previous GWAS, demonstrate that the bulk of inherited risk may reside in rare alleles.

In addition, other genetic polymorphisms, such as copy number variants, are becoming increasingly amenable to testing. As the full picture of inherited prostate cancer risk becomes more complete, it is hoped that germline information will become clinically useful.

GWAS and insight into the mechanism of prostate cancer risk

Notably, almost all reported prostate cancer risk alleles reside in nonprotein coding regions of the genome, and the underlying biological mechanism of disease susceptibility remains unclear. Hypotheses explaining the mechanism of inherited risk include the following:

  • Risk alleles discovered by GWAS are in linkage disequilibrium with exonic variants that directly influence gene products.
  • Risk alleles do in fact reside in areas of transcription, but transcription at these sites has not yet been annotated.
  • Risk alleles reside within regulatory elements and genotype within these areas influence activity of distal genes.[213]

The 8q24 risk locus, which contains multiple prostate cancer risk alleles and risk alleles for other cancers, has been the focus of intense study. c-MYC, a known oncogene, is the closest known gene to the 8q24 risk regions, although it is located hundreds of kb away. Given this significant distance, SNPs within c-MYC are not in linkage disequilibrium with the 8q24 prostate cancer risk variants. One study examined whether 8q24 prostate cancer risk SNPs are in fact located in areas of previously unannotated transcription, and no transcriptional activity was uncovered at the risk loci.[214] Attention turned to the idea of distal gene regulation. Interrogation of the epigenetic landscape at the 8q24 risk loci revealed that the risk variants are located in areas that bear the marks of genetic enhancers, elements that influence gene activity from a distance.[215-217] To identify a prostate cancer risk gene, germline DNA from 280 men undergoing prostatectomy for prostate cancer was genotyped for all known 8q24 risk SNPs. Genotypes were tested for association with the normal prostate and prostate tumor RNA expression levels of genes located within one Mb of the risk SNPs. No association was detected between expression of any of the genes, including c-MYC, and risk allele status in either normal epithelium or tumor tissue. Another study, using normal prostate tissue from 59 patients, detected an association between an 8q24 risk allele and the gene PVT1, downstream from c-MYC.[218] Nonetheless, c-MYC, with its substantial involvement in many cancers, remains a prime candidate. A series of experiments in prostate cancer cell lines demonstrated that chromatin is configured in such a way that the 8q24 risk variants lie in close proximity to c-MYC, even though they are quite distant in linear space. These data implicate c-MYC despite the absence of expression data.[216,218] Further work at 8q24 and similar analyses at other prostate cancer risk loci are ongoing.

Additional insights are emerging regarding the potential interaction between SNPs identified from GWAS and prostate cancer susceptibility gene regulation. One study found that a SNP at 6q22 lies within a binding region for HOXB13. Through multiple functional approaches, the T allele of this SNP (rs339331) was found to enhance binding of HOXB13, leading to allele-specific upregulation of RFX6, which correlates with prostate cancer progression and severity.[219] Thus, this study supports the hypothesis that risk alleles identified from GWAS may play a role in regulating or modifying gene expression and therefore impact prostate cancer risk.

Modified approaches to GWAS

A 2012 study used a novel approach to identify polymorphisms associated with risk.[220] On the basis of the well-established principle that the AR plays a prominent role in prostate tumorigenesis, the investigators targeted SNPs that reside at sites where the AR binds to DNA. They leveraged data from previous studies that mapped thousands of AR binding sites genome-wide in prostate cancer cell lines to select SNPs to genotype in the Johns Hopkins Hospital cohort of 1,964 cases and 3,172 controls and the Cancer Genetic Markers of Susceptibility cohort of 1,172 cases and 1,157 controls. This modified GWAS revealed a SNP (rs4919743) located at the KRT8 locus at 12q13.13—a locus previously implicated in cancer development—associated with prostate cancer risk, with an OR of 1.22 (95% CI, 1.13–1.32). The study is notable for its use of a reasonable hypothesis and prior data to guide a genome-wide search for risk variants.

Conclusions

Although the statistical evidence for an association between genetic variation at these loci and prostate cancer risk is overwhelming, the clinical relevance of the variants and the mechanism(s) by which they lead to increased risk are unclear and will require further characterization. Additionally, these loci are associated with very modest risk estimates and explain only a fraction of overall inherited risk. Further work will include genome-wide analysis of rarer alleles catalogued via sequencing efforts, such as the 1000 Genomes Project.[221] Disease-associated alleles with frequencies of less than 1% in the population may prove to be more highly penetrant and clinically useful. In addition, further work is needed to describe the landscape of genetic risk in non-European populations. Finally, until the individual and collective influences of genetic risk alleles are evaluated prospectively, their clinical utility will remain difficult to fully assess.

Inherited Variants Associated With Prostate Cancer Aggressiveness

Prostate cancer is clinically heterogeneous. Many cases are indolent and are successfully managed with observation alone. Other cases are quite aggressive and prove deadly. Several variables are used to determine prostate cancer aggressiveness at the time of diagnosis, such as Gleason score and PSA, but these are imperfect. Additional markers are needed, as sound treatment decisions depend on accurate prognostic information. Germline genetic variants are attractive markers since they are present, easily detectable, and static throughout life. Several studies have interrogated inherited variants that may distinguish indolent and aggressive prostate cancer. Several of these studies identified polymorphisms associated with aggressiveness, after adjusting for commonly used clinical variables, and are reviewed in the Table 6.

Findings to date regarding inherited risk of aggressive disease are considered preliminary. Further work is needed to validate findings and assess prospectively.

Like studies of the genetics of prostate cancer risk, initial studies of inherited risk of aggressive prostate cancer focused on polymorphisms in candidate genes. Next, as GWAS revealed prostate cancer risk SNPs, several research teams sought to determine whether certain risk SNPs were also associated with aggressiveness (see table below). There has been great interest in launching more unbiased, genome-wide searches for inherited variants associated with indolent versus aggressive prostate cancer. While GWAS designed explicitly for disease aggressiveness have been initiated, most genome-wide analyses to date have relied on datasets previously generated to evaluate prostate cancer risk. The cases from these case-control cohorts were divided into aggressive and nonaggressive subgroups then compared with each other and/or with the control (nonprostate cancer) subjects. Several associations between germline markers and prostate cancer aggressiveness have been reported. However, there remains no accepted set of germline markers that clearly provides prognostic information beyond that provided by more traditional variables at the time of diagnosis.

Table 6. Inherited Variants Associated With Prostate Cancer Aggressiveness
Source of Associated Polymorphism  Variant Phenotype  Controls  Associated Allele/Genotype and Strength of Association Reference 
CI = confidence interval; GWAS = genome-wide association study; HR = hazard ratio; N- = lymph node–negative; N+ = lymph node–positive; OR = odds ratio; PSA = prostate-specific antigen; SNP = single nucleotide polymorphism.
Target gene – CASP8D302HPSA level >50 ng/mL or metastasis or Gleason 8–10 (n = 796)Men without prostate cancer (n = 2,060)H allele: OR, 0.67 (95% CI, 0.54–0.83)[222]
Target gene – CCL21181 A/GBiopsy Gleason >7 (n = 705)Biopsy Gleason ≤7 (n = 3,031)AA genotype: OR, 1.47 (95% CI, 1.08–2.01)[223]
Target gene – MDM2rs2279744 G/TBiopsy Gleason >7 (n = 1,028)Biopsy Gleason ≤7 (n = 645)TT genotype: OR, 1.51 (95% CI, 1.11–2.05)[163]
GWAS risk SNPrs2735839 A/GGleason ≥4+3 or T3b or N+ (n = 1,253)Gleason ≤4+3 and <T3b and N- (n = 4,233)A allele (more aggressive prostate cancer) and G allele (less aggressive prostate cancer): OR, 1.38 (95% CI, 1.21–1.56)[224]
Gleason ≥8 (n = 1,388)Gleason <8 (n = 7,549)A allele (more aggressive prostate cancer) and G allele (less aggressive prostate cancer): OR, 1.07 (95% CI, 0.95–1.19)[225]
Prostate cancer–specific death (n = 580)Nonprostate cancer death or survival at last follow-up (n = 3,365)A allele (more aggressive prostate cancer) and G allele (less aggressive prostate cancer): OR, 1.26 (95% CI, 1.05–1.52)[226]
Gleason ≥8 or PSA >20 ng/mL or Gleason 7 and cT3–cT4 (n = 212)Gleason <7 and cT1–cT2 and PSA <10 ng/mL (n = 469)G allele: OR, 0.8 (95% CI, 0.6–0.9)[227]
Target gene – LEPRrs1137100 A/GProstate cancer–specific death (n = 501)Nonprostate cancer death or survival at last follow-up (n = 2,374)G allele: HR, 0.82 (95% CI, 0.67–1.00)[228]
Target gene – IL4rs2070874 C/TProstate cancer–specific death (n = 501)Nonprostate cancer death or survival at last follow-up (n = 2,374)T allele: HR, 1.27 (95% CI, 1.04–1.56)[228]
Target gene – CRY1rs10778534 C/TProstate cancer–specific death (n = 501)Nonprostate cancer death or survival at last follow-up (n = 2,374)C allele: HR, 1.23 (95% CI, 1.00–1.51)[228]

In independent retrospective series (see Table 6) the prostate cancer risk allele at rs2735839 (G) was associated with less aggressive disease. This risk allele has also been associated with higher PSA levels.[192,229] A hypothesis explaining the association between the nonrisk allele (A) and more aggressive disease is that those carrying the A allele generally have lower PSA levels and are sent for prostate biopsy less often. They subsequently may be diagnosed later in the natural history of the disease, resulting in poorer outcomes.

To definitively identify the inherited variants associated with prostate cancer aggressiveness, GWAS focusing on prostate cancer subjects with poor disease-related outcomes are needed. Genome-wide surveys for aggressiveness variants have been attempted, although these were underpowered to detect polymorphisms with ORs lower than 2.0.[230,231] As these data are generated and validated, inherited variants may become valuable in accurately determining prostate cancer prognosis and establishing a treatment plan.

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