Literature DB >> 23064873

HOXB13 is a susceptibility gene for prostate cancer: results from the International Consortium for Prostate Cancer Genetics (ICPCG).

Jianfeng Xu1, Ethan M Lange, Lingyi Lu, Siqun L Zheng, Zhong Wang, Stephen N Thibodeau, Lisa A Cannon-Albright, Craig C Teerlink, Nicola J Camp, Anna M Johnson, Kimberly A Zuhlke, Janet L Stanford, Elaine A Ostrander, Kathleen E Wiley, Sarah D Isaacs, Patrick C Walsh, Christiane Maier, Manuel Luedeke, Walther Vogel, Johanna Schleutker, Tiina Wahlfors, Teuvo Tammela, Daniel Schaid, Shannon K McDonnell, Melissa S DeRycke, Geraldine Cancel-Tassin, Olivier Cussenot, Fredrik Wiklund, Henrik Grönberg, Ros Eeles, Doug Easton, Zsofia Kote-Jarai, Alice S Whittemore, Chih-Lin Hsieh, Graham G Giles, John L Hopper, Gianluca Severi, William J Catalona, Diptasri Mandal, Elisa Ledet, William D Foulkes, Nancy Hamel, Lovise Mahle, Pal Moller, Isaac Powell, Joan E Bailey-Wilson, John D Carpten, Daniela Seminara, Kathleen A Cooney, William B Isaacs.   

Abstract

Prostate cancer has a strong familial component but uncovering the molecular basis for inherited susceptibility for this disease has been challenging. Recently, a rare, recurrent mutation (G84E) in HOXB13 was reported to be associated with prostate cancer risk. Confirmation and characterization of this finding is necessary to potentially translate this information to the clinic. To examine this finding in a large international sample of prostate cancer families, we genotyped this mutation and 14 other SNPs in or flanking HOXB13 in 2,443 prostate cancer families recruited by the International Consortium for Prostate Cancer Genetics (ICPCG). At least one mutation carrier was found in 112 prostate cancer families (4.6 %), all of European descent. Within carrier families, the G84E mutation was more common in men with a diagnosis of prostate cancer (194 of 382, 51 %) than those without (42 of 137, 30 %), P = 9.9 × 10(-8) [odds ratio 4.42 (95 % confidence interval 2.56-7.64)]. A family-based association test found G84E to be significantly over-transmitted from parents to affected offspring (P = 6.5 × 10(-6)). Analysis of markers flanking the G84E mutation indicates that it resides in the same haplotype in 95 % of carriers, consistent with a founder effect. Clinical characteristics of cancers in mutation carriers included features of high-risk disease. These findings demonstrate that the HOXB13 G84E mutation is present in ~5 % of prostate cancer families, predominantly of European descent, and confirm its association with prostate cancer risk. While future studies are needed to more fully define the clinical utility of this observation, this allele and others like it could form the basis for early, targeted screening of men at elevated risk for this common, clinically heterogeneous cancer.

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Year:  2012        PMID: 23064873      PMCID: PMC3535370          DOI: 10.1007/s00439-012-1229-4

Source DB:  PubMed          Journal:  Hum Genet        ISSN: 0340-6717            Impact factor:   4.132


Introduction

By sequencing coding regions of more than 200 genes in a previously identified region of linkage at 17q21–22 (Lange et al. 2003; Gillanders et al. 2004; Xu et al. 2005; Lange et al. 2007; Cropp et al. 2011) a rare but recurrent mutation (G84E) in HOXB13 was recently identified in four of 94 probands from prostate cancer families. (Ewing et al. 2012) The mutation co-segregated with prostate cancer in these four families and was found to be significantly more common among 5,083 unrelated prostate cancer patients (1.4 %) than control subjects (0.1 %) of European descent (p = 8.5 × 10−7) leading to odds ratio (OR) estimates of tenfold or more. In this initial report, the frequency of the mutation was higher in prostate cancer patients with early-onset disease (age at diagnosis ≤55 years old, 2.2 %) or with a positive family history (2.2 %), and most common in patients with both of these features (3.1 %). If confirmed, these findings provide support for the concept that rare, moderately penetrant mutations as well as common, low-penetrance prostate cancer risk-associated variants identified from genome-wide association studies (GWAS) (Gudmundsson et al. 2007a, b, 2008, 2009; Yeager et al. 2007, 2009; Thomas et al. 2008; Eeles et al. 2008, 2009; Sun et al. 2008; Xu et al. 2010; Kote-Jarai et al. 2011a; Takata et al. 2010; Akamatsu et al. 2012; Haiman et al. 2011) both contribute to prostate cancer risk. The identification and characterization of genetic variants reproducibly associated with substantial increases in prostate cancer risk would provide enhanced ability to identify men most likely to benefit from early disease screening. Prostate cancer demonstrates wide differences in incidence and mortality across populations within the United States and throughout the world. In an attempt to confirm and expand the observations of Ewing et al. (2012), we examined the frequency of HOXB13 G84E mutations in prostate cancer families across different ancestries and geographic regions. We genotyped this mutation and other known variants in HOXB13 in 2,443 hereditary prostate cancer families recruited by members of the International Consortium for Prostate Cancer Genetics (ICPCG), a large NCI-funded collaborative resource for studies of genetic susceptibility for hereditary prostate cancer.

Subjects and methods

Study population

The ICPCG study cohort has been described in detail previously (Schaid and Chang 2005; Xu et al. 2005). Fifteen groups participated in the present study, including those from Europe [Finland (Tampere University), Sweden (Karolinska Institute), UK (Institute of Cancer Research and Royal Marsden NHS Foundation Trust, University of Cambridge, ACTANE), Germany (University of Ulm), and France (CeRePP)], North America (Fred Hutchinson Cancer Research Center, Johns Hopkins Hospital, Louisiana State University, Mayo Clinic, McGill University, Northwestern University, Stanford University, University of Michigan, and University of Utah), and Australia (University of Melbourne) (Supplementary Table 1). Each ICPCG group recruited its study population via different methods of pedigree ascertainment and utilized different methods to confirm prostate cancer diagnosis. In this study, men were considered “affected” if their prostate cancer diagnosis was confirmed by either medical records or death certificates. All other men were assigned as “unknown phenotype.” A total of 2,443 families were included in the study, including 6,422 affected men and 1,902 men without a prostate cancer diagnosis (unknown), and 1,803 women whose DNA samples were available (Supplementary Table 1). Research protocols and study documentation were approved by each group’s Institutional Review Board.

SNPs selection and genotyping

Five mutations in the HOXB13 gene, selected from the original paper of Ewing et al. (2012) and the ESP database (Exome Variant Server, NHLBI Exome Sequencing Project, Seattle, WA, USA (URL: http://evs.gs.washington.edu/EVS/) [1/2012]) were genotyped in the ICPCG dataset, including G84E (c.251G > A, rs138213197), T105I (c.314C > T, rs140492479), R217C (c.649C > T, rs13945791), R229G (c.685C > G), and T253P (c.757A > C). In addition, ten polymorphic SNPs (rs890435, rs2326017, rs7212669, rs8064938, rs3809773, rs1054072, rs8556, rs3809771, rs4793980, rs3110601) flanking the HOXB13 gene and spanning 108,191 base pairs (bp) from 46,719,399 to 46,827,590 (Build 37) were genotyped to estimate allele frequencies and haplotypes. The G84E mutation, due to a change in the second position of codon 84 (GGA → GAA), results in a nonconservative substitution in a conserved putative protein–protein binding motif of HOXB13 (Ewing et al. 2012). Genotyping was performed using the MassARRAY iPLEX (Sequenom, Inc., San Diego, CA, USA). Duplicates and negative controls were included in each 96-well plate to ensure quality control (QC). Genotyping was performed by technicians blinded to the sample status. The average concordance rate was 99.7 % for 6,300 genotypes among QC duplicates.

Statistical methods

Frequency of the G84E mutation was determined at either family level or individual level. At a family level, the proportion of families with at least one G84E mutation carrier was determined for the entire set as well as for each ICPCG group. The difference in the proportion among different ICPCG groups was tested using Chi-square with a degree of freedom (df) of 14. At an individual level, the proportion of G84E mutation carriers was compared among men with a diagnosis of prostate cancer (affecteds) and the remaining men within the families (unknowns). The difference of G84E mutation carrier rate between affected and unknown men was tested based on a marginal model that accounts for relatedness of subjects within families using generalized estimating equations (GEE). An exchangeable working correlation matrix was assumed. A family-based association test was performed to test association of the G84E mutation and other SNPs with prostate cancer by assessing over-transmission of alleles from parents to affected offspring using the computer program FBAT (Xu et al. 2002). Empirical variance test statistics were used to account for the correlation of transmitted alleles among multiple affected individuals in the same family. Haplotypes of each individual based on these 15 SNPs were estimated using Genehunter-plus (Kruglyak et al. 1996) and PLINK (Purcell et al. 2007). The haplotypes with the highest likelihood were selected. For subjects whose inferred haplotypes were different based on these two methods, manual inspection was performed to resolve the difference, with priority given to haplotypes based on linkage disequilibrium among markers in this study population.

Results

Among five previously observed mutations in HOXB13 (Ewing et al. 2012) two were observed in this study—R217C (rs13945791) and G84E (rs138213197). The rare R217C variant was found one time each in two families of European descent and did not co-segregate with prostate cancer. The G84E mutation was found in 283 subjects from 112 families of European descent, including 194 men with prostate cancer (Table 1). This represented 4.6 % of all 2,443 prostate cancer families and 4.8 % of 2,298 prostate cancer families of European descent. The proportion of families with at least one G84E mutation carrier differed significantly across the 15 ICPCG groups (P = 9.4 × 10−8). The proportion was highest in families from the Nordic countries of Finland (22.4 %) and Sweden (8.2 %) and lower in North America (0–6.1 %) and Australia (2.6 %). The G84E mutation was not found in families of any other race or ethnicity, including those of African (N = 58), Ashkenazi Jewish (N = 46), or other descent (N = 28). Obviously, larger numbers of families of these and other races and ethnicities will need to be examined to more fully characterize the population distribution of this mutation.
Table 1

G84E mutation of HOXB13 in prostate cancer families of International Consortium for Prostate Cancer Genetics (ICPCG)

No. of familiesNo. of families with G84E carriers (%)Subjects in families with at least one G84E carrier
AffectedUnknown (Men)Unknown (Women)
AllEuropean descentAllEuropean descent N No. of G84E carriers (%) N No. of G84E carriers (%) N N of G84E carriers (%)
Europe
 Finland, University of Tampere767617 (22.4 %)17 (22.4 %)5437 (69 %)6922 (31 %)9729 (30 %)
 Sweden, Umea University1101109 (8.2 %)9 (8.2 %)1713 (76 %)155 (33 %)134 (31 %)
 Germany, University of Ulm37837813 (3.4 %)13 (3.4 %)2119 (90 %)10 (0 %)20 (0 %)
 UK, ACTANE1451425 (3.4 %)5 (3.5 %)127 (58 %)10 (0 %)10 (0 %)
 France, CeRePP1591562 (1.3 %)2 (1.3 %)53 (60 %)10 (0 %)00
North America
 BC/CA/HI98836 (6.1 %)6 (7.2 %)2012 (60 %)71 (14 %)71 (14 %)
 Fred Hutchinson Cancer Research Center25524114 (5.5 %)14 (5.8 %)4525 (56 %)145 (36 %)162 (13 %)
 Johns Hopkins Hospitala 2341765 (2.1 %)5 (2.8 %)2014 (70 %)72 (29 %)104 (40 %)
 MAYO Clinic1851856 (3.2 %)6 (3.2 %)1510 (67 %)20 (0 %)00
 University of Michigana 31728211 (3.5 %)11 (3.9 %)3626 (72 %)134 (31 %)52 (40 %)
 McGill University18171 (5.9 %)1 (5.9 %)22 (100 %)0000
 North Western University33320 (0 %)0 (0 %)000000
 University of Utah34834821 (6 %)21 (6 %)13223 (17 %)62 (33 %)113 (27 %)
 Louisiana State University10100 (0 %)0 (0 %)000000
Australia
 Australia77732 (2.6 %)2 (2.7 %)33 (100 %)11 (100 %)32 (67 %)
Total2,4432,309112 (4.6 %)112 (4.9 %)382194 (51 %)13742 (31 %)16547 (28 %)
Totala 1,8921,85196 (5.0 %)96 (5.2 %)326154 (47 %)11736 (31 %)15041 (27 %)

aA subset of families from these centers were included in the original discovery report (Ewing et al. 2012). These total values reflect the results obtained after omitting all families from these two centers

G84E mutation of HOXB13 in prostate cancer families of International Consortium for Prostate Cancer Genetics (ICPCG) aA subset of families from these centers were included in the original discovery report (Ewing et al. 2012). These total values reflect the results obtained after omitting all families from these two centers In the 112 families with at least one G84E mutation carrier, the mutation was found in both affected and unaffected men. However, the carrier rate was significantly higher in affected men (194 of 382, 51 %) than other men in these families (i.e. men of unknown status [(42 of 137, 31 %), p = 9.9 × 10−8]) (Table 1). Using a statistical test that considered the relatedness of subjects within carrier families, the odds ratio (OR) for prostate cancer was 4.42 [95 % confidence interval (CI) 2.56–7.64] for the G84E mutation carriers. We repeated our analyses excluding families from the University of Michigan and Johns Hopkins Hospital, some of which were included in the initial report describing HOXB13 as a prostate cancer susceptibility gene (Ewing et al. 2012). In particular, the former study included HOXB13 G84E genotype data from only the youngest prostate cancer case in a subset of University of Michigan and Johns Hopkins Hospital families. The carrier rate in ICPCG families remained significantly higher in affected men (154 of 326, 47 %) than unknown men [(36 of 117, 31 %), P = 3.3 × 10−6] and the OR for prostate cancer was 4.3 [95 % confidence interval (CI) 2.32–7.96] for the G84E mutation carriers after excluding all families from these two institutions (Table 1). A mixed pattern of co-segregation of the G84E mutation with prostate cancer was found in these 112 families. While complete co-segregation was found in 34 families, incomplete co-segregation was more commonly observed, revealing genetic heterogeneity (affected but not carriers) and incomplete penetrance of the mutation (carriers but unaffected men). We also examined transmission of G84E mutation and alleles of other genotyped SNPs at the region in all 2,443 families using a family-based association test (Table 2). The risk allele (A) corresponding to the G84E mutation was observed to be transmitted significantly more often than expected from parents to affected sons (P = 6.5 × 10−6). A significant result was also observed when all families from the University of Michigan and Johns Hopkins Hospital were removed from this analysis (P = 1.2 × 10−4) (Supplementary Table 2), strongly indicating the G84E mutation is associated with prostate cancer risk.
Table 2

Family-based association test for SNPs at HOXB13 region in ICPCG families

ChrPositionrs#GeneMutationRare alleleAllele frequencyNo. of informative familiesS-E(S)a Var(S) Z P
1746,719,399rs890435IntergenicG0.41509−7.38243.77−0.470.64
1746,720,565rs2326017IntergenicT0.334963.10248.240.200.84
1746,727,289rs7212669IntergenicG0.10244−4.89107.42−0.470.64
1746,780,829rs8064938IntergenicA0.16353−6.12136.42−0.520.60
1746,784,039rs3809773IntergenicA0.334851.42245.540.100.93
1746,799,812rs1054072PRACC0.47518−13.41268.62−0.820.41
1746.804,250HOXB13T253P00N/AN/AN/AN/A
1746,804,322HOXB13R229GG0.00011−0.400.16−1.000.32
1746,804,358rs139475791HOXB13R217CA0.00012−1.601.36−1.370.17
1746,805,590rs8556HOXB13T0.15342−10.77145.60−0.890.37
1746,805,642rs140492479HOXB13T105IA0.000121.641.411.380.17
1746,805,705rs138213197HOXB13G84EA0.023817.5015.074.516.53E−06
1746,807,919rs38097715′G0.06171−8.9264.24−1.110.27
1746,813,531rs47939805′T0.163062.22116.030.210.84
1746,827,590rs31106015′ C0.12274−7.46114.18−0.700.49

Based on an FBAT analysis of 2,437 pedigrees (10,217 nuclear families; 40,246 subjects)

aS-E(S) is the statistical score for the observed number of rare allele transmissions minus the statistical score for the expected number of transmissions

Family-based association test for SNPs at HOXB13 region in ICPCG families Based on an FBAT analysis of 2,437 pedigrees (10,217 nuclear families; 40,246 subjects) aS-E(S) is the statistical score for the observed number of rare allele transmissions minus the statistical score for the expected number of transmissions To assess association in our family set while adjusting for variable pedigree structures, we randomly selected one affected man (proband) in the second generation from each of 2,443 pedigrees and then counted the number of G84E carriers among probands, first-relatives, and second-degree relatives or higher (Table  3). The G84E mutation carrier rate among probands was 2.8 %. Among the first-degree relatives, the carrier rate was significantly higher in affected men (75 %) than in those with an unknown phenotype (48 %), P = 0.002, OR = 4.26 (95 % CI 1.69–10.75). Among the second-degree relatives or higher, the carrier rate was also significantly higher in affected men (58 %) than in unknown men (23 %), P = 0.004, OR = 4.81 (95 % CI 1.64–14.12).
Table 3

G84E HOXB13 mutation carriers among randomly selected affected probands and their relatives

Proband G84E CarrierG84E carriers in first-degree relativesG84E carriers in second-degree relatives or higher
AffectedUnknownOR (95 % CI) P valueAffectedUnknownOR (95 % CI) P value
Yes (51)56/75 (74.7 %)16/34 (47.6 %)4.26 (1.69–10.75)0.00211/19 (57.9 %)9/39 (23.1 %)4.81 (1.64–14.12)0.004
No (1,755)21/2,502 (0.8 %)3/759 (0.4 %)2.31 (0.82–6.51)0.1115/973 (1.5 %)6/651 (0.9 %)2.21 (0.39–12.71)0.37
G84E HOXB13 mutation carriers among randomly selected affected probands and their relatives The prostate cancer patients who carried the mutation had a wide spectrum of clinical disease, including cancers with high risk of disease progression (Table 4), as indicated by moderate to poor tumor differentiation (tumor grade of Gleason score 7 or higher) in over one-third of the cases with available data, and over one-quarter having non-organ confined disease at diagnosis (tumor stage T3 or higher). The mean age at diagnosis of carriers was 62.8 years. In comparison, the mean age at diagnosis for the 6,172 prostate cancer patients without the mutation was 64.4 years (P = 0.04; relatedness of subjects within families was considered). The mean age at last contact of G84E carriers without a prostate cancer diagnosis was 56.3.
Table 4

Clinicopathologic variables of prostate cancers in HOXB13 G84E carriers

No. of patients % of patients
Tumor grade (Gleason Score)
 ≤66763.2 
 73230.2 
 843.8 
 ≥932.8 
Tumor stage
 T1c or lower4739.2 
 T24134.2 
 T3 or higher3226.7 
Metastasis at diagnosis
 Yes43.1 
Serum PSA level at diagnosis
 ≤104948.0 
 11–202524.5 
 ≥202827.5 
Age at diagnosis
 ≤552418.6 
 56–8010581.4 
 ≥8000.0 
Death from prostate cancer
 Yes97.0 
Clinicopathologic variables of prostate cancers in HOXB13 G84E carriers Finally, to assess a potential founder effect for the G84E mutation, we estimated haplotypes based on the 15 genotyped SNPs in this region. The mutation (allele A) of G84E was predicted to be on eight different haplotypes. However, 95 % (269 out of 283) of the occurrences were predicted to be on a single rare haplotype (frequency of 2 %). Among the 269 G84E mutation carriers predicted to carry the common haplotype, 83 were from Finland while the remaining were from 12 other ICPCG groups. One individual from Finland was homozygous for all 15 markers, allowing unambiguous assignment of the haplotype. This individual was diagnosed with moderately differentiated (Gleason 7), clinically localized prostate cancer at age 60. We note that the genotype data for all 269 G84E mutation carriers were consistent with a single shared haplotype spanning the 15 genotyped SNPs (i.e. there were no SNPs that had homozygous genotypes for opposite alleles among the 269 carriers) and it is possible that with additional genotype data the most likely haplotype configuration for G84E carriers would be a single founder haplotype.

Discussion

By evaluating germline mutations of the HOXB13 gene in 2,433 prostate cancer families from the ICPCG, this study confirmed the observation that the G84E mutation is significantly associated with prostate cancer in subjects of European descent with family history of the disease. The results remained significant when families used in the original report were not included in the analysis, providing independent confirmation of the original finding. Although there is a large degree of variability in the number of individuals sampled per pedigree in the ICPCG, approximately 5 % of prostate cancer families had at least one member with the G84E mutation. These results are consistent with the hypothesis that HOXB13 G84E is a prostate cancer susceptibility allele that significantly increases the risk of prostate cancer. The search for hereditary prostate cancer genes has been challenging due to a number of factors including the late-onset nature of the disease and the high background rate of sporadic disease in the general population. Although rare variants of other genes such as RNASEL (Carpten et al. 2002), MSR1 (Xu et al. 2002), and ELAC2 (Tavtigian et al. 2001) have been previously identified in prostate cancer families and proposed as prostate cancer susceptibility alleles, follow-up studies have not supported their candidacy. On the other hand, mutations in BRCA2 have been reproducibly associated with prostate cancer risk (Edwards et al. 2003), but their frequency is low in prostate cancer families (Agalliu et al. 2007; Kote-Jarai et al. 2011b). More recently, GWAS studies have led to the identification of over 40 prostate cancer risk-associated SNPs that have been replicated in multiple study populations. These variants are common in the general population (5 % or higher), confer low risk with ORs, typically in the range of 1.1–1.4 (Gudmundsson et al. 2007a, b, 2008, 2009; Yeager et al. 2007, 2009; Thomas et al. 2008; Eeles et al. 2008, 2009; Sun et al. 2008; Xu et al. 2010; Kote-Jarai et al. 2011a; Takata et al. 2010; Akamatsu et al. 2012; Haiman et al. 2011), and have been estimated to account for ~25 % of the risk associated with a positive family history (Kote-Jarai et al. 2011a). Although more common prostate cancer risk-associated variants are likely to be identified in the future, rare variants with larger effects have been proposed as an alternative mechanism to account for ‘missing inheritance’ (Iyengar and Elston 2007; Bodmer and Bonilla 2008). In this respect, the establishment of a rare and moderate- to high-penetrance mutation in HOXB13 as a prostate cancer susceptibility allele provides empirical evidence for this alternative hypothesis. Indeed, like colorectal and breast cancer, at least some significant fraction of prostate cancer risk is conferred by this class of coding sequence variants. The estimated frequency of the HOXB13 G84E mutation in prostate cancer families is influenced by the number of individuals in any given family as well as family structure. For example, some extended families, particularly in the Utah collection, have more than 100 subjects and have multiple affected generations. Similarly, estimated ORs for G84E in relation to prostate cancer risk are impacted by the mixed degrees of relatedness among relatives, as the covariance matrices used in the GEE models do not explicitly account for family structure. The analysis presented in Table 3 was designed to provide better odds ratio estimates for first- and second-degree relatives of G84E carriers. Of interest, the carrier rate was lower among second-degree affected relatives (58 %) compared with first-degree affected relatives (75 %), suggesting the presence of genetic heterogeneity across families. The OR estimates from our analyses should be interpreted only in the context of the current study. We note that the odds ratios are calculated based on many “controls” that have limited phenotype information; most have not been screened for disease or screening results are missing. Further, familial controls not currently affected by prostate cancer are more likely to develop disease in the future compared with randomly selected men from the general population given the strong history of disease in these families. Finally, our familial cases are more likely to carry moderate to high penetrance risk alleles compared with typical unselected prostate cancer cases. Large population-based studies that include screened men will be necessary to obtain more accurate measures of G84E mutation frequency and penetrance. As we observed, the frequency of G84E mutations are likely population specific. Our results implicate a geographical frequency gradient of the G84E mutation across the European continent, with the mutation being more common in Nordic countries, notably Finland. This finding highlights the strength of the current study as family-based association methods provide the strongest protection against type I error due to population stratification. It remains to be seen how various analytic methods (e.g. those based on principal components that capture the major sources of genetic variation between subjects across common genetic variants) will protect against population stratification when analyzing uncommon genetic variants that disproportionately occur in specific European-derived populations in case–control settings. In summary, analysis of the large ICPCG family collection establishes the HOXB13 G84E allele as a reproducible risk factor for prostate cancer. Our identification of a common haplotype among the majority of HOXB13 G84E carriers indicates that there is a founder effect with a higher frequency of the mutant allele in Nordic populations. Additional studies using population-based case–control and/or familial samples will be useful to define the penetrance of this mutation, which will have important clinical implications for families that carry the G84E mutation. Below is the link to the electronic supplementary material. Supplementary material 1 (DOCX 346 kb) Supplementary material 2 (DOCX 614 kb)
  32 in total

1.  Description of the International Consortium For Prostate Cancer Genetics, and failure to replicate linkage of hereditary prostate cancer to 20q13.

Authors:  Daniel J Schaid; Bao Li Chang
Journal:  Prostate       Date:  2005-05-15       Impact factor: 4.104

2.  Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against type 2 diabetes.

Authors:  Julius Gudmundsson; Patrick Sulem; Valgerdur Steinthorsdottir; Jon T Bergthorsson; Gudmar Thorleifsson; Andrei Manolescu; Thorunn Rafnar; Daniel Gudbjartsson; Bjarni A Agnarsson; Adam Baker; Asgeir Sigurdsson; Kristrun R Benediktsdottir; Margret Jakobsdottir; Thorarinn Blondal; Simon N Stacey; Agnar Helgason; Steinunn Gunnarsdottir; Adalheidur Olafsdottir; Kari T Kristinsson; Birgitta Birgisdottir; Shyamali Ghosh; Steinunn Thorlacius; Dana Magnusdottir; Gerdur Stefansdottir; Kristleifur Kristjansson; Yu Bagger; Robert L Wilensky; Muredach P Reilly; Andrew D Morris; Charlotte H Kimber; Adebowale Adeyemo; Yuanxiu Chen; Jie Zhou; Wing-Yee So; Peter C Y Tong; Maggie C Y Ng; Torben Hansen; Gitte Andersen; Knut Borch-Johnsen; Torben Jorgensen; Alejandro Tres; Fernando Fuertes; Manuel Ruiz-Echarri; Laura Asin; Berta Saez; Erica van Boven; Siem Klaver; Dorine W Swinkels; Katja K Aben; Theresa Graif; John Cashy; Brian K Suarez; Onco van Vierssen Trip; Michael L Frigge; Carole Ober; Marten H Hofker; Cisca Wijmenga; Claus Christiansen; Daniel J Rader; Colin N A Palmer; Charles Rotimi; Juliana C N Chan; Oluf Pedersen; Gunnar Sigurdsson; Rafn Benediktsson; Eirikur Jonsson; Gudmundur V Einarsson; Jose I Mayordomo; William J Catalona; Lambertus A Kiemeney; Rosa B Barkardottir; Jeffrey R Gulcher; Unnur Thorsteinsdottir; Augustine Kong; Kari Stefansson
Journal:  Nat Genet       Date:  2007-07-01       Impact factor: 38.330

3.  Parametric and nonparametric linkage analysis: a unified multipoint approach.

Authors:  L Kruglyak; M J Daly; M P Reeve-Daly; E S Lander
Journal:  Am J Hum Genet       Date:  1996-06       Impact factor: 11.025

4.  Genome-wide association study identifies five new susceptibility loci for prostate cancer in the Japanese population.

Authors:  Ryo Takata; Shusuke Akamatsu; Michiaki Kubo; Atsushi Takahashi; Naoya Hosono; Takahisa Kawaguchi; Tatsuhiko Tsunoda; Johji Inazawa; Naoyuki Kamatani; Osamu Ogawa; Tomoaki Fujioka; Yusuke Nakamura; Hidewaki Nakagawa
Journal:  Nat Genet       Date:  2010-08-01       Impact factor: 38.330

5.  Two percent of men with early-onset prostate cancer harbor germline mutations in the BRCA2 gene.

Authors:  Stephen M Edwards; Zsofia Kote-Jarai; Julia Meitz; Rifat Hamoudi; Questa Hope; Peter Osin; Rachel Jackson; Christine Southgate; Rashmi Singh; Alison Falconer; David P Dearnaley; Audrey Ardern-Jones; Annette Murkin; Anna Dowe; Jo Kelly; Sue Williams; Richard Oram; Margaret Stevens; Dawn M Teare; Bruce A J Ponder; Simon A Gayther; Doug F Easton; Rosalind A Eeles
Journal:  Am J Hum Genet       Date:  2002-12-09       Impact factor: 11.025

6.  Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study.

Authors:  Zsofia Kote-Jarai; Ali Amin Al Olama; Graham G Giles; Gianluca Severi; Johanna Schleutker; Maren Weischer; Daniele Campa; Elio Riboli; Tim Key; Henrik Gronberg; David J Hunter; Peter Kraft; Michael J Thun; Sue Ingles; Stephen Chanock; Demetrius Albanes; Richard B Hayes; David E Neal; Freddie C Hamdy; Jenny L Donovan; Paul Pharoah; Fredrick Schumacher; Brian E Henderson; Janet L Stanford; Elaine A Ostrander; Karina Dalsgaard Sorensen; Thilo Dörk; Gerald Andriole; Joanne L Dickinson; Cezary Cybulski; Jan Lubinski; Amanda Spurdle; Judith A Clements; Suzanne Chambers; Joanne Aitken; R A Frank Gardiner; Stephen N Thibodeau; Dan Schaid; Esther M John; Christiane Maier; Walther Vogel; Kathleen A Cooney; Jong Y Park; Lisa Cannon-Albright; Hermann Brenner; Tomonori Habuchi; Hong-Wei Zhang; Yong-Jie Lu; Radka Kaneva; Ken Muir; Sara Benlloch; Daniel A Leongamornlert; Edward J Saunders; Malgorzata Tymrakiewicz; Nadiya Mahmud; Michelle Guy; Lynne T O'Brien; Rosemary A Wilkinson; Amanda L Hall; Emma J Sawyer; Tokhir Dadaev; Jonathan Morrison; David P Dearnaley; Alan Horwich; Robert A Huddart; Vincent S Khoo; Christopher C Parker; Nicholas Van As; Christopher J Woodhouse; Alan Thompson; Tim Christmas; Chris Ogden; Colin S Cooper; Aritaya Lophatonanon; Melissa C Southey; John L Hopper; Dallas R English; Tiina Wahlfors; Teuvo L J Tammela; Peter Klarskov; Børge G Nordestgaard; M Andreas Røder; Anne Tybjærg-Hansen; Stig E Bojesen; Ruth Travis; Federico Canzian; Rudolf Kaaks; Fredrik Wiklund; Markus Aly; Sara Lindstrom; W Ryan Diver; Susan Gapstur; Mariana C Stern; Roman Corral; Jarmo Virtamo; Angela Cox; Christopher A Haiman; Loic Le Marchand; Liesel Fitzgerald; Suzanne Kolb; Erika M Kwon; Danielle M Karyadi; Torben Falck Orntoft; Michael Borre; Andreas Meyer; Jürgen Serth; Meredith Yeager; Sonja I Berndt; James R Marthick; Briony Patterson; Dominika Wokolorczyk; Jyotsna Batra; Felicity Lose; Shannon K McDonnell; Amit D Joshi; Ahva Shahabi; Antje E Rinckleb; Ana Ray; Thomas A Sellers; Hui-Yi Lin; Robert A Stephenson; James Farnham; Heiko Muller; Dietrich Rothenbacher; Norihiko Tsuchiya; Shintaro Narita; Guang-Wen Cao; Chavdar Slavov; Vanio Mitev; Douglas F Easton; Rosalind A Eeles
Journal:  Nat Genet       Date:  2011-07-10       Impact factor: 38.330

7.  Germline mutations in HOXB13 and prostate-cancer risk.

Authors:  Charles M Ewing; Anna M Ray; Ethan M Lange; Kimberly A Zuhlke; Christiane M Robbins; Waibhav D Tembe; Kathleen E Wiley; Sarah D Isaacs; Dorhyun Johng; Yunfei Wang; Chris Bizon; Guifang Yan; Marta Gielzak; Alan W Partin; Vijayalakshmi Shanmugam; Tyler Izatt; Shripad Sinari; David W Craig; S Lilly Zheng; Patrick C Walsh; James E Montie; Jianfeng Xu; John D Carpten; William B Isaacs; Kathleen A Cooney
Journal:  N Engl J Med       Date:  2012-01-12       Impact factor: 91.245

8.  Genome-wide association and replication studies identify four variants associated with prostate cancer susceptibility.

Authors:  Julius Gudmundsson; Patrick Sulem; Daniel F Gudbjartsson; Thorarinn Blondal; Arnaldur Gylfason; Bjarni A Agnarsson; Kristrun R Benediktsdottir; Droplaug N Magnusdottir; Gudbjorg Orlygsdottir; Margret Jakobsdottir; Simon N Stacey; Asgeir Sigurdsson; Tiina Wahlfors; Teuvo Tammela; Joan P Breyer; Kate M McReynolds; Kevin M Bradley; Berta Saez; Javier Godino; Sebastian Navarrete; Fernando Fuertes; Laura Murillo; Eduardo Polo; Katja K Aben; Inge M van Oort; Brian K Suarez; Brian T Helfand; Donghui Kan; Carlo Zanon; Michael L Frigge; Kristleifur Kristjansson; Jeffrey R Gulcher; Gudmundur V Einarsson; Eirikur Jonsson; William J Catalona; Jose I Mayordomo; Lambertus A Kiemeney; Jeffrey R Smith; Johanna Schleutker; Rosa B Barkardottir; Augustine Kong; Unnur Thorsteinsdottir; Thorunn Rafnar; Kari Stefansson
Journal:  Nat Genet       Date:  2009-09-20       Impact factor: 38.330

9.  Evidence for two independent prostate cancer risk-associated loci in the HNF1B gene at 17q12.

Authors:  Jielin Sun; Siqun Lilly Zheng; Fredrik Wiklund; Sarah D Isaacs; Lina D Purcell; Zhengrong Gao; Fang-Chi Hsu; Seong-Tae Kim; Wennuan Liu; Yi Zhu; Pär Stattin; Hans-Olov Adami; Kathleen E Wiley; Latchezar Dimitrov; Jishan Sun; Tao Li; Aubrey R Turner; Tamara S Adams; Jan Adolfsson; Jan-Erik Johansson; James Lowey; Bruce J Trock; Alan W Partin; Patrick C Walsh; Jeffrey M Trent; David Duggan; John Carpten; Bao-Li Chang; Henrik Grönberg; William B Isaacs; Jianfeng Xu
Journal:  Nat Genet       Date:  2008-08-31       Impact factor: 38.330

10.  Multiple loci identified in a genome-wide association study of prostate cancer.

Authors:  Gilles Thomas; Kevin B Jacobs; Meredith Yeager; Peter Kraft; Sholom Wacholder; Nick Orr; Kai Yu; Nilanjan Chatterjee; Robert Welch; Amy Hutchinson; Andrew Crenshaw; Geraldine Cancel-Tassin; Brian J Staats; Zhaoming Wang; Jesus Gonzalez-Bosquet; Jun Fang; Xiang Deng; Sonja I Berndt; Eugenia E Calle; Heather Spencer Feigelson; Michael J Thun; Carmen Rodriguez; Demetrius Albanes; Jarmo Virtamo; Stephanie Weinstein; Fredrick R Schumacher; Edward Giovannucci; Walter C Willett; Olivier Cussenot; Antoine Valeri; Gerald L Andriole; E David Crawford; Margaret Tucker; Daniela S Gerhard; Joseph F Fraumeni; Robert Hoover; Richard B Hayes; David J Hunter; Stephen J Chanock
Journal:  Nat Genet       Date:  2008-02-10       Impact factor: 38.330

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  85 in total

1.  G84E mutation in HOXB13 is firmly associated with prostate cancer risk: a meta-analysis.

Authors:  Hang Huang; Bing Cai
Journal:  Tumour Biol       Date:  2013-09-13

2.  Is prostate cancer a Lynch syndrome cancer?

Authors:  Aung Ko Win
Journal:  Asian J Androl       Date:  2013-07-01       Impact factor: 3.285

Review 3.  A multiparametric approach to improve upon existing prostate cancer screening and biopsy recommendations.

Authors:  Brian T Helfand; Carly A Conran; Jianfeng Xu; William J Catalona
Journal:  Curr Opin Urol       Date:  2017-09       Impact factor: 2.309

4.  Familial prostate cancer and HOXB13 founder mutations: geographic and racial/ethnic variations.

Authors:  Henry T Lynch; Trudy G Shaw
Journal:  Hum Genet       Date:  2012-09-22       Impact factor: 4.132

5.  The 2013 Genetics Society of America Medal: Elaine A. Ostrander.

Authors:  John Schimenti; Marnie Halpern
Journal:  Genetics       Date:  2013-05       Impact factor: 4.562

6.  Cancer Progress and Priorities: Prostate Cancer.

Authors:  Kevin H Kensler; Timothy R Rebbeck
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-02       Impact factor: 4.254

7.  Familial prostate cancer.

Authors:  Veda N Giri; Jennifer L Beebe-Dimmer
Journal:  Semin Oncol       Date:  2016-08-18       Impact factor: 4.929

Review 8.  Prostate cancer in young men: an important clinical entity.

Authors:  Claudia A Salinas; Alex Tsodikov; Miriam Ishak-Howard; Kathleen A Cooney
Journal:  Nat Rev Urol       Date:  2014-05-13       Impact factor: 14.432

Review 9.  Collaborative cancer epidemiology in the 21st century: the model of cancer consortia.

Authors:  Michael R Burgio; John P A Ioannidis; Brett M Kaminski; Eric Derycke; Scott Rogers; Muin J Khoury; Daniela Seminara
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-09-17       Impact factor: 4.254

10.  The role of germline mutations in the BRCA1/2 and mismatch repair genes in men ascertained for early-onset and/or familial prostate cancer.

Authors:  Sofia Maia; Marta Cardoso; Paula Paulo; Manuela Pinheiro; Pedro Pinto; Catarina Santos; Carla Pinto; Ana Peixoto; Rui Henrique; Manuel R Teixeira
Journal:  Fam Cancer       Date:  2016-01       Impact factor: 2.375

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