Download Confirmation of Prostate Cancer Susceptibility Genes Using High

IV. APPLICATIONS PANEL
Confirmation of Prostate Cancer Susceptibility Genes
Using High-Risk Families
Gail P. Jarvik, Janet L. Stanford, Ellen L. Goode, Richard McIndoe, Suzanne Kolb,
Mark Gibbs, Leroy Hood, Elaine A. Ostrander
Prostate cancer is the most common nonsquamous cell cancer
and the second leading cause of cancer deaths among men in the
United States. In 1998, approximately 184 500 men in the United
States will be clinically diagnosed with prostate cancer and,
despite advances in treatment and screening, an estimated 39 000
men will die of the disease (1). Incidence rates increased sharply
from 1973 to 1992 (particularly among white men), with the
increase being attributed to screening and early detection of
tumors through the use of testing for prostate-specific antigen
(PSA) screening (2–4).
Little is known about the underlying causes of prostate cancer. A number of environmental risk factors have been considered, including industrial exposures, sexually transmitted
infectious agents, endocrine factors, and diet. High dietary fat
may be associated with invasive prostate cancer (5–9). Evidence
also suggests that vitamins D (10–12) and E (13) may have
protective effects. A cause–effect relationship has yet to be demonstrated in either of these cases, however, and no particular
environmental factor has been identified as a major cause of the
disease.
One of the strongest risk factors for prostate cancer identified
to date is a family history of disease, suggesting that genetic
factors play a role in prostate cancer susceptibility, etiology,
and progression. We discuss here the key factors that suggest
a role for prostate cancer susceptibility genes and the likely
features of such genes. We review findings that suggest that
there is a prostate cancer susceptibility gene at 1q24–25. Finally,
we discuss the results in our dataset and others with regard
to observed difficulties in confirming these initial findings of
linkage.
EPIDEMIOLOGIC ANALYSES
A number of epidemiologic studies demonstrate familial clustering of prostate cancer, suggesting the existence of underlying
Journal of the National Cancer Institute Monographs No. 26, 1999
genetic predisposition factors. A subset of those studies is summarized in Table 1 (14–21). In each study, family history was
evaluated as a risk factor for prostate cancer. When defining
exposure as a positive first-degree family history of prostate
cancer (father, brother, or sons), the frequency of exposure is
about threefold higher among case subjects than among control
subjects, with relative risk (RR) estimates across studies ranging
from 2.0 to 6.3. Two studies (22,23) have suggested that elevated risk may be associated with affected brothers but not with
affected fathers, suggesting a possible X chromosome or shared
childhood environment risk. Overall, men with two or more
first-degree-affected relatives have a fivefold to 11-fold increase
in risk compared with men without a family history of prostate
cancer (16,24,25). These studies also provide evidence that the
risk of prostate cancer in first-degree relatives of probands is
higher among patients with early, compared with late, ages at
diagnosis.
A genetic contribution to prostate cancer risk is also supported by twin studies. In one such analysis, Grönberg et al. (26)
analyzed the incidence of disease among 3840 male twin pairs
identified from the Swedish Twin Registry linked to the Swedish
Cancer Registry. The study population contained 458 cases of
prostate cancer. Results suggest a significant influence of genetics on prostate cancer with proband concordance rates of 0.19
for monozygotic twins and 0.043 for dizygotic twins. Subsequent studies (27,28) in these and additional cohorts confirmed
these initial observations.
MOLECULAR ANALYSIS
A number of loci on different chromosomes have been implicated in the etiology of prostate cancer. These results are not
mutually exclusive and suggest that multiple genes contribute to
the progression of prostate tumors and that some of these genes
may have redundant functions. Studies on allelic loss in sporadic
prostate tumors have been a common approach for identifying
regions likely to contain prostate cancer genes [e.g. (29–31)].
Affiliations of authors: G. P. Jarvik (Department of Medicine, Division of
Medical Genetics), E. L. Goode (Department of Epidemiology, School of Public
Health and Community Medicine), R. McIndoe, L. Hood (Department of Molecular Biotechnology), University of Washington Medical Center, Seattle; J. L.
Stanford, S. Kolb (Division of Public Health Sciences), M. Gibbs, E. A. Ostrander (Clinical Research Division), Fred Hutchinson Cancer Research Center,
Seattle.
Correspondence to: Elaine A. Ostrander, Ph.D., Clinical Research Division,
Fred Hutchinson Cancer Research Center, 1100 Fairview Ave., N., D2-190,
Seattle, WA 98109-1024 (e-mail: [email protected]).
See “Notes” following “References.”
© Oxford University Press
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Data from many types of studies support the hypothesis that
strong familial components are involved in the etiology of
prostate cancer. One way to access such genes is through the
study of families with multiple affected family members and,
in particular, families with individuals affected comparatively early in life. Several prostate cancer susceptibility loci
have been described to date. Confirmation of the linkage and
estimation of the proportion of families who are linked in
large independent datasets is essential to understanding the
significance of susceptibility genes. We explore the methodology used to perform such studies and the factors that can
limit the ability to confirm linkage results. We report specifically the example of the HPC1 gene on 1q24–25. [Monogr
Natl Cancer Inst 1999;26:81–7]
Table 1. Epidemiologic studies of prostate cancer in relation to family history of prostate cancer
No. of subjects
Study, y (reference No.)
Krain, 1974 (14)
Fincham et al., 1990 (15)
Steinberg et al., 1990 (16)
Spitz et al., 1991 (17)
Hayes et al., 1995 (18)
Whittemore et al., 1995 (19)
Lesko et al., 1996 (20)
Ghadirian et al., 1991 (21)
Positive family history (%)
Estimated relative risk*
Case subjects
Control subjects
Case subjects
Control subjects
(95% CI or P)
221
382
691
378
972
1500
563
640
221
625
640
383
1294
1581
703
639
6.0
15.0
15.0
13.0
6.9
13.0
17.2
14.7
1.0
5.0
8.0
5.7
2.3
5.0
8.3
5.0
6.3 ( P<.01)
3.4 (2.2–5.3)
2.0 (1.2–3.3)
2.4 (1.3–4.5)
3.2 (2.0–5.0)
2.5 (1.9–3.3)
2.2 (1.5–3.0)
3.2 (2.1–5.1)
*CI ⳱ confidence interval.
COMPLEX SEGREGATION ANALYSIS
Complex segregation analysis (CSA) is useful for testing the
hypothesis that a mendelian locus substantially contributes to the
82
risk of a disease. CSA can give information about the likely
mode of inheritance and penetrance of prostate cancer susceptibility genes. It can also suggest subsets of families, or the
characteristics of men within families, whose disease is most
likely because of mutations in an inherited susceptibility gene.
CSA cannot, however, reliably distinguish the number of susceptibility loci nor can it provide information about the location
of susceptibility genes. CSA can provide estimates of the overall
frequency of mutant alleles with a specific set of characteristics,
the penetrance of these alleles, and other parameters of the transmission models that can be used in linkage analyses.
Several major CSAs of prostate cancer have been undertaken.
The first, undertaken by Carter et al. (24) analyzed data on 691
prostate cancer families, originally ascertained from consecutive
probands (mean age, 59.3 years) undergoing radical prostatectomy for primary clinically localized prostate cancer at The
Johns Hopkins University Hospital, Baltimore (MD) between
1982 and 1989. These data showed that early age of diagnosis
and multiple affected family members were the strongest predictors of risk in relatives. Their analysis also suggested that
autosomal dominant inheritance of a rare, highly penetrant allele(s) best accounted for the distribution of prostate cancer in
the families studied, with carriers having an 88% cumulative risk
of prostate cancer by age 85 years compared with only 5%
cumulative risk for noncarriers. These investigators proposed
that hereditary prostate cancer gene(s) account for about 43% of
prostate cancer with diagnosis before age 55 years and about 9%
of total prostate cancer.
Similar results have been obtained by Schaid et al. (43) with
the use of a family-history survey of cancer conducted for 5486
men, including 4288 probands (aged 38–84 years) who underwent a radical prostatectomy for clinically localized prostate
cancer at the Mayo Clinic between 1966 and 1987. This study
proposed a population frequency of 0.006 for a susceptibility
gene and a risk of 89% by age 85 years for carriers. This study,
however, suggested that autosomal dominant genes accounted
for a higher proportion of all prostate cancer—approximately
68% before age 60 years.
An additional segregation analysis was performed on a population-based sample of 2857 nuclear families ascertained
through an affected father diagnosed with prostate cancer in
Sweden between 1959 and 1963 (44). This analysis contrasts
with the studies by Carter et al. (24) and Schaid et al. (43), who
both studied hospital-based series of men whose disease was
treated with prostatectomy. Selection of probands by prostatectomy may bias selection toward men with less aggressive disJournal of the National Cancer Institute Monographs No. 26, 1999
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Thus far, loss of heterozygosity (LOH) in prostate tumors
has been documented for at least 11 different chromosomal
arms. Many of these regions have been identified repeatedly,
such as chromosomes 8 and 17 (32,33). Chromosome 17 is of
interest because it carries a number of genes postulated to have
a role in cancer, including the p53 and BRCA1 genes. Of interest, families that carry BRCA1 mutations have been reported
to be at increased risk for prostate cancer (RR 3.33; 95% confidence interval ⳱ 1.8–6.2) (34). Analyses of prostate cancer
cases drawn from a population-based, case–control study,
however, revealed little evidence that BRCA1 is a common
prostate cancer susceptibility gene (35). In 49 prostate cancer
cases who had either been diagnosed early in life (<53 years),
were diagnosed before age 65 years, and had first-degree family
history of breast cancer or an early onset family history of prostate cancer, only one germline BRCA1 mutation was observed.
There is a likely possibility that this single observation was
coincidental, as was the delAG1285 mutation that has been frequently observed in the population. This finding suggests that
LOH observed on chromosome 17q in many prostate tumors is
likely to be unrelated to the presence of germline mutations in
BRCA1.
Other techniques that highlight regions of interest include
chromosome transfer studies and comparative genome hybridization that implicate chromosomes 2, 12, 11, and 8 (36–39).
The data from chromosome 8 are particularly interesting because LOH studies also implicate chromosome 8. However, exhaustive linkage analysis of chromosome 8 by a variety of methods has yet to reveal a gene important in prostate cancer
predisposition (40–41).
The identity, penetrance, and role in cancer susceptibility of
each of the above postulated genes remain unknown. Two points
are clear, however. First, whereas the location and number of the
underlying prostate cancer susceptibility genes remain elusive,
collectively these studies argue that tumor suppression is a key
function of at least some prostate cancer genes [reviewed in
(42)]. Second, many of these genes are likely to be more important in prostate cancer progression and metastasis and do
not represent early events in the development of prostate cancer.
For the mapping of susceptibility genes, discussed below, analyses of families with a high incidence of prostate cancer are
needed.
ease, since metastatic disease is unlikely to be treated by prostatectomy. Grönberg et al. (44) reported that familial clustering
of prostate cancer was best explained by dominant alleles with a
population frequency of 0.0167 and a lifetime penetrance of
63%, slightly less than the penetrance proposed by Carter et al.
Nevertheless, the overall consistency in segregation analyses
derived from very different populations provide strong evidence
for highly penetrant autosomal dominant prostate cancer susceptibility genes.
PUTATIVE PROSTATE CANCER LOCUS
AT
1Q24–25
Journal of the National Cancer Institute Monographs No. 26, 1999
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In 1996, the location of a putative prostate cancer susceptibility locus (termed HPC1) on chromosome 1q24–25 was suggested by linkage analysis of 91 high-risk prostate cancer families from the United States and Sweden (40). A maximum
multipoint logarithm of the odds (LOD) score under the assumption of heterogeneity LOD (HLOD) ⳱ 5.43 (the proportion of
families linked, ␣ ⳱ 0.34), with the postulated locus being close
to marker D1S422. This study concluded that about 34% of
inherited prostate cancer could be attributed to an as yet unknown gene at 1q24–25. The above conclusions were strongly
supported by a nonparametric analysis using the program
GENEHUNTER (45) in which highly significant results were
obtained for multiple markers in this region.
Although the initial report did not suggest any subgroup of
families that were more or less likely to be linked, a strong age
of diagnosis effect, with nearly all linked families having an
average age of diagnosis of less than 65 years has since been
noted. Specifically, Grönberg et al. (46) found that the 40 North
American families with an average age of diagnosis less than 65
years yielded a multipoint LOD score of 3.96, whereas the 39
families with an older age at diagnosis yielded a LOD score of
−0.84. Assuming heterogeneity, the proportion of families
linked was estimated as 66% for the 14 families with the earliest
average ages at diagnosis but decreased to 7% for the families
with the oldest ages at diagnosis. The majority of families contributing to the positive LOD score in each case were Caucasian.
Grönberg et al. (46,47) also reported that high-grade cancers
(grade 3) were more common in potentially linked families as
was advanced-stage disease. These latter two points have been
the topic of some dispute, however, with claims that the comparison of characteristics between putatively linked and unlinked families is faulty because of the use of an incorrect reference population (48).
It should be noted that conclusions regarding clinical characteristics of linked families are virtually impossible to make
with any certainty until the HPC1 gene is cloned. The presence
of a modestly positive LOD score, or even completely shared
haplotypes from the chromosomal region in question among
affected individuals, does not guarantee that the family is
“linked,” since such segregation will occur fortuitously some
percentage of the time. Conversely, there will be families with
low LOD scores but who have a mutation in the gene in question. The LOD scores may be low because of phenocopies, i.e.,
men who have acquired the same disease for “sporadic” reasons
unrelated to germline mutations for the gene in question. In
addition, because of variable penetrance of mutations, there will
be families in which carriers of the mutation develop the disease
at a point later in life then predicted by the statistical models or
not at all. Therefore, conclusions regarding clinical characteris-
tics of “linked families” will be best drawn from analyses of
families who are found to carry true germline mutations, following characterization of the causative gene.
Shortly after the mapping of HPC1, we described an analysis
(49) of 49 high-risk prostate cancer families for linkage to 1q24–
25 with the use of 10 highly polymorphic markers spanning the
proposed locus. These 49 families were representative of our
families as a whole, which were collected from the Prostate
Cancer Genetic Research Study (PROGRESS), a Seattle-based
study initiated in July 1995 to identify familial clusters of prostate cancer and, ultimately, inherited susceptibility genes. A tollfree number (1-800-777-3035) was established and distributed
via national advertising, media events, and mailings to support
groups and urologists to identify potential participants for their
suitability. Informed, written consent was obtained from each
study participant. The study and its consent and medical record
release forms were approved by the Institutional Review Board
of the Fred Hutchinson Cancer Research Center. Families were
selected for participation on the basis of the number of firstdegree relatives diagnosed with prostate cancer, the age at diagnosis of the affected relatives, and the number of living affected relatives from whom blood samples could be obtained. In
our first set of 49 families, we observed that the characteristics
of the families analyzed compared closely with those described
by Smith et al. (40). These PROGRESS families averaged 4.4
men affected per family (range, 3–9) and had an average age at
diagnosis of 65.9 years. Forty-six of the 49 PROGRESS families
were Caucasian.
Data were analyzed by use of parametric and nonparametric
methods. Two models were used for the parametric LOD score
method. The first model (“Hopkins model” or “Model A”) was
identical to that reported by Smith et al. (40), and the second
(“Seattle model” or “Model S1”) (49) was devised by us and
based on the age-dependent penetrance values that resulted from
the segregation analysis reported by Carter et al. (24). In addition, to protect against falsely rejecting linkage secondary to
model misspecification, we also performed a nonparametric
multipoint analysis with the use of the GENEHUNTER program
(45). In all cases, we observed no evidence for linkage in our
dataset in either two-point analyses (using any of 10 markers in
the region) or in the nonparametric analyses. No evidence for
linkage was observed in a heterogeneity analysis using HOMOG.
More recently, we have expanded our dataset to include 150
families (Table 2; 144 Caucasian and six non-Caucasian) and
undertaken a closer examination at this locus with the use of
three linkage models: the Seattle model (49), the model described by Smith et al. (40), and a model used in a recent linkage
analysis published by Grönberg et al. (46). These complete results (50), including features of the families analyzed, are similarly negative with no evidence for linkage with a subset of
families at 1q24–25. Table 3 presents the results from the 150
multiplex prostate cancer families described in Table 2 for one
marker, D1S518, which defines the HPC1 locus. The results are
highly negative with all models and all values of ␪, as well for
all other markers analyzed (50).
One consideration in this analysis is the degree to which the
families analyzed mimic those described by Smith et al. (40).
The mean age of diagnosis of the genotyped affected men is 65.9
years, and the average number of affected men per family is 4.2
(Table 3). These figures are comparable to that of Smith et al.
Table 2. Characteristics of 150 prostate cancer families from the PROGRESS study*
Caucasian
Characteristic
Total group
Non-Caucasian
艋65 y
艋65 y
>65 y
>65 y
No. of affected men
637
275
328
26
8
No. of genotyped affected men
509
219
263
20
7
Average No. of affected men per
family (range)
Mean age at diagnosis of genotyped affected
men per family (range)
4.2
(3–9)
4.3
(3–9)
4.1
(3–8)
6.5
(4–9)
4.0
(3–5)
65.9
(50.8–78.0)
62.0
(50.8–66.0)†
69.5
(65.0–78.0)
62.2
(57.7–63.7)
69.3
(67.0–71.7)
*PROGRESS ⳱ Prostate Cancer Genetic Research Study.
†Men genotyped at 1q24 are not identical to the overall set of affected men samples.
Table 3. LOD* scores for 150 prostate cancer families using three transmission models at 1q for marker D1S518
S1 (49)
A (40)
B (46)
0.00
0.02
0.04
0.08
0.10
0.20
0.30
0.40
−30.98
−84.51
−12.46
−24.28
−50.94
−10.25
−19.41
−37.47
−8.51
−12.66
−22.72
−5.92
−10.24
−18.04
−4.93
−3.25
−5.65
−1.84
−0.74
−1.38
−0.54
−0.08
−0.17
−0.09
*LOD ⳱ logarithm of the odds.
(40) in the description of families collected by investigators at
The Johns Hopkins University.
LOCUS HETEROGENEITY
LINKAGE
AND
POWER
TO
DETECT
The inability to robustly replicate the findings of Smith et al.
(40) suggests that locus heterogeneity issues for HPC1 are still
not well understood. There may be diagnostic differences between datasets or it may be that a prostate cancer gene at 1q24–
25 accounts for significantly less than 34% of disease in “highrisk” families nationwide. How much less is unclear. In our
dataset, we have undertaken an analysis to estimate the power to
detect linkage. Conservative computations suggest a high power
to detect a hereditary prostate cancer (HPC) locus (or loci) by
use of a multistep analysis strategy in this large dataset. Power
calculations for two-point (one marker and HPC) LOD method
analyses were done with 1000 replications with the use of the
computer package SIMLINK (51,52). The simulations computed the probability of detecting certain LOD scores, given the
autosomal dominant model of HPC transmission discussed
above, the minimum pedigree structures, and the DNA samples
available. The computations presented are conservative in sev-
eral ways. They used only the pedigree structure that was available in the time of initial ascertainment. Much more data have
been collected on many families in the intervening months. The
power analysis also assumed a polymorphism information content (PIC) of 0.7 for the marker loci. A marker with a PIC of 0.8,
as several of the markers in the HPC region have, would confer
additional power. Another consideration is that, in the case of
HPC1, we are conducting a confirmation study with dense markers and, therefore, expect ␪ to be small. Table 4 calculates power
for ␪ ⳱ 0.00 and 0.05. For the HPC1 region, the power analysis
for ␪ ⳱ 0.00 is reasonable.
Finally, at the time power analyses were completed, only 114
families were collected, half of which had a mean age of familial
prostate cancer less than 65 years and half of which had a mean
age of 65 years or greater. The most recent molecular analyses
were done with 150 families, approximately half of whom have
a mean age under 65 years, using the age-dependent penetrance
model (Seattle model) we have described previously. Despite
these caveats, power analysis of 114 families indicates acceptable power to detect linkage, even if a locus accounted for less
than 35% of prostate cancer in the dataset. Application of these
findings argues that, at least in this dataset, significantly less
than 35% of families are linked to 1q24–25.
Table 4. Power analysis of 114 Caucasian families with mean age of diagnosis <65 years*
% linked
<65 y
% linked
total dataset
100
50
90
45
80
40
70
35
␪
Expected
LOD
Probability
LOD > 1
Probability
LOD > 1.5
Probability
LOD > 2
Probability
LOD > 3
0
0.05
0
0.05
0
0.05
0
0.05
11.448
7.264
7.264
4.751
4.581
3.132
2.741
1.915
1.000
0.999
0.999
0.988
0.988
0.929
0.908
0.749
1.000
0.996
0.996
0.956
0.952
0.832
0.744
0.542
1.000
0.993
0.993
0.905
0.890
0.684
0.590
0.353
1.000
0.975
0.975
0.816
0.789
0.495
0.399
0.202
*LOD ⳱ logarithm of the odds.
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Recombination fraction
Model
(reference No.)
COMPARATIVE ANALYSES
EFFECTS
OF
HETEROGENEITY
There is currently linkage evidence for four familial prostate
cancer loci (40,57,59–61). Because these loci do not account for
more than one half of the families reported, other loci are likely
to exist. Locus heterogeneity dramatically influences the power
to map. This can be seen by examining the fall in expected LOD
score as heterogeneity increases. Table 5 demonstrates the tradeoff between sample size, heterogeneity, and power in the simulation studies for our late-diagnosis families. Total sample sizes
of 116 and half that, 58 families, are examined. It can be seen
that increasing the proportion of families linked to the locus of
interest from 60% to 70% or from 70% to 80% results in a nearly
Table 5. Caucasian families with mean age of diagnosis for genotyped
affected men >65 years*
No. of
families
Linked, %
␪
Max
LOD
Probability
LOD > 1
Probability
LOD > 2
Probability
LOD > 3
116
90
116
80
116
70
116
60
58
100
58
90
58
80
58
70
0
0.05
0
0.05
0
0.05
0
0.05
0
0.05
0
0.05
0
0.05
0
0.05
9.362
6.124
5.915
4.030
3.585
2.441
2.064
1.443
7.071
4.608
4.608
3.127
3.100
2.111
1.833
1.294
1.000
1.000
1.000
0.981
0.971
0.876
0.796
0.643
0.999
0.992
0.992
0.922
0.912
0.754
0.663
0.510
0.999
0.977
0.976
0.850
0.762
0.515
0.402
0.220
0.995
0.932
0.932
0.761
0.730
0.472
0.413
0.240
0.998
0.931
0.923
0.699
0.578
0.290
0.212
0.081
0.972
0.770
0.770
0.473
0.451
0.221
0.161
0.077
*LOD ⳱ logarithm of the odds.
Journal of the National Cancer Institute Monographs No. 26, 1999
CONFOUNDING FACTORS
We believe that the two factors that most likely complicate
locus heterogeneity issues in the mapping of prostate cancer
genes are PSA testing and race. PSA came into common usage
as a diagnostic tool in 1988. Because different datasets have
collected men spanning different diagnosis years, the proportion
of men with less aggressive disease who were diagnosed by PSA
and categorized simply as “affected” likely differs (perhaps significantly) between datasets and within individual strata. A
weighting factor based on the level of PSA in the linkage analyses may shed light on this issue, as may stratification by tumor
stage and grade.
Whether or not race is an issue for HPC1 analysis remains
unclear. Only two families in the Seattle dataset were AfricanAmerican. It is clear that prostate cancer is more frequent among
U.S. blacks than whites (62) and that it is lowest in Asian men.
Although the majority of families contributing to the HPC1 linkage results are Caucasian in all datasets, in the work described
by Cooney (53), several African-American families contributed
to the observation of linkage, with a maximum NPL Z score at
marker D1S158 of 1.39 (P ⳱ .0848). There was also an overrepresentation of African-American families contributing to the
positive LOD score in the original report of Smith et al. (40) as
well, generating the hypothesis that the gene at 1q24–25 may be
more important for prostate cancer susceptibility in AfricanAmerican than in Caucasian families. In part, because the results
in individual families are not strong enough to conclude linkage
of that family to the 1q24–25 region, our understanding of any
differential effect of the HPC1 locus awaits larger collections of
non-Caucasian families.
CONCLUSIONS
The confirmation of the HPC1 locus has not been uneventful.
The mixed results found by several groups who have tried to
confirm this linkage are likely the result of population differences in the samples and a lower proportion of families being
linked than was originally estimated. The mixed results do not
necessarily indicate that this linkage is a false positive, rather
that the HPC1 gene may be differentially important for families
with different epidemiologic or clinical characteristics. It remains for the HPC1 gene to be cloned and sequenced before
most families whose disease is positively because of mutations
in HPC1 can be unambiguously identified.
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The strong HPC1 linkage observed by Smith et al. (40) has
proven challenging to replicate in other datasets, with mixed
results generated by seemingly similar sets of families. By applying nonparametric analyses with the use of GENEHUNTER
to studies of families with significant numbers of affected young
men, data from Cooney et al. (53) and Hsieh et al. (54) weakly
confirm the observations of Smith et al., with nonparametric
linkage scores of 1.72 and 1.83, respectively, and P values of
.045 and .036. The significance of NPL scores with P values in
the .03–.05 range for a confirmation result is debatable. In a
detailed discussion on this topic, Lander and Kruglyak (55) have
suggested that a nominal P value of .01 should be required for
confirmatory evidence of linkage, since such studies still involve
searching over an interval. That P values <.05 were seen in two
distinct datasets, however, strengthen the argument for confirmation in these datasets. The percentage of linked families in the
overall datasets cannot be estimated from these analyses but will
be much less than 34%.
In contrast to the above, Eeles et al. (56) and Berthon et al.
(57) found no evidence for linkage at this locus. Eeles et al.
reported an NPL score of 0.72 with a P value of .22 in 35
families with four affected men. In these same families, the
HLOD ⳱ 0.20, with ␣ ⳱ 20%. The HLOD for the larger dataset
of 136 families was 0.01, ␣ ⳱ 4%, suggesting that only 4% of
the families were linked to the HPC1 locus. Virtually identical
negative data have been presented by Thibodeau et al. (58).
50% drop in the sample size for required equivalent power. This
demonstrates the advantage obtained if homogeneous subsets
can be constructed for linkage testing. For prostate cancer, families have been divided by age of diagnosis, ethnicity, and density
or severity of disease. Homogeneous subsets may also be improved by stratifying on the LOD score at other putative loci.
Alternately, linkage methods in which two or more loci may be
jointly considered may be advantageous when locus heterogeneity is suspected within a sample.
The problem of heterogeneity also sheds light on how different samples, ascertained in different ways, may enrich their collection for certain clinical features and, therefore, may have
different mixes of susceptibility loci and would result in the
differential ability to map each locus between samples. This is
the reason that the characteristics of samples must be compared
when linkage found in one dataset cannot be confirmed in another dataset.
The confirmation of this and of future loci will be aided by
increasing homogeneity in subgroup analysis, which relies on
better characterization of the high-risk families. For these reasons, we plan to continue collection of extensive medical
and family history data on all affected and unaffected men in
PROGRESS families and increase our ascertainment of nonCaucasian families.
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NOTES
Supported by Public Health Service training grant 5T32CA09168 from the
National Cancer Institute, National Institutes of Health, Department of Health
and Human Services (to E. L. Goode); awards from the CaPCURE Foundation
(to J. L. Stanford, L. Hood, and E. A. Ostrander); and with additional support
from the Fred Hutchinson Cancer Research Center (to E. L. Goode). G. P. Jarvik
is the recipient of awards from the Markey Foundation and the Pew Scholars
Program.
We thank the participating PROGRESS families, whose generosity and cooperation made this investigation possible. We also thank Cassandra Neal for her
expert technical expertise and Michael Brannan and Laurie Hunter for their work
in accruing PROGRESS families.
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