UMEÅ UNIVERSITY MEDICAL DISSERTATIONS New series No. 991 ISBN 91-7305-962-5 ISSN 0346-6612

UMEÅ UNIVERSITY MEDICAL DISSERTATIONS
New series No. 991
ISBN 91-7305-962-5 ISSN 0346-6612
Department of Radiation Sciences, Oncology, Umeå University
Prostate Cancer and Inflammatory
Genes
Fredrik Lindmark
Umeå 2005
Copyright © 2005 by Fredrik Lindmark
ISSN 0346-6612
ISBN 91-7305-962-5
Printed by Print & Media, Umeå University, Umeå, 2005
To my Family
Prostate Cancer and Inflammatory Genes
Table of contents
Abstract, 3
Populärvetenskaplig sammanfattning, 5
Original studies, 7
List of Abbreviations, 8
Introduction, 9
Risk factors for prostate cancer, 10
Dietary factors, 10
Hormonal and other physiological factors, 11
Familial and genetic factors, 11
Inflammation and cancer, 15
The role of inflammation in the pathogenesis of prostate cancer, 17
Molecular pathology, 17
Epidemiology, 19
Genetics, 22
Cytokines in prostatic inflammation and prostate cancer, 24
Aims, 29
Material and methods, 30
Hereditary prostate cancer families used for mutation screening, 30
Patients with prostate cancer and controls, 30
The Northern Sweden Health and Disease Cohort, 30
CAPS, 30
Genetic analysis, 33
Genomic PCR, 33
Mutation screening, 33
Common sequence variants of the MSR-1 gene, 34
Association of MIC-1 sequence variants and prostate cancer, 35
Association of IL1-RN haplotype with prostate cancer risk, 36
Determination of MIC-1 serum levels, 38
Statistical analysis, 38
Tests for Hardy-Weinberg Equilibrium, 38
Association analysis, 39
Haplotype analysis, 39
Assessment of serum levels, 39
Results and comments, 40
Genetic analysis of MSR1 (Study I), 40
Genetic analysis of IL-1RN (Study II), 43
Genetic analysis of MIC-1 (Study III), 46
Analysis of MIC-1 serum levels (Study IV), 48
Discussion, 55
1
2
Prostate Cancer and Inflammatory Genes
Association studies, 55
Cytokine polymorphisms in prostate cancer, 58
Future perspectives, 61
Conclusions, 62
Acknowledgements, 63
References, 64
Original studies
I
II
III
IV
Prostate Cancer and Inflammatory Genes
3
Abstract
Prostate cancer remains a significant health
concern for men throughout the world.
Accumulating epidemiologic and molecular
evidence suggests that inflammation is an
important component in the aetiology of
prostate cancer. Supporting this hypothesis,
population studies have found an increased
risk of prostate cancer in men with a prior
history of certain sexually transmitted
infections or prostatitis. More general
evidence of a relationship between
inflammation and prostate cancer has been
provided by reports indicating that daily use
of non steroidal anti-inflammatory drugs
(NSAIDs) may be associated with a lower
incidence of prostate cancer. The exact
mechanism whereby inflammation might act
in tumour development and progression
remains to be elucidated, but is likely to be
complex. The genetic contribution to
inflammatory responses involved in the
development of prostate cancer has not yet
been extensively or systematically studied.
However, this thesis evaluates the role of
various inflammation-related genes in the
pathogenesis of prostate cancer.
The macrophage scavenger receptor 1
(MSR1) is a transmembrane protein that is
mainly expressed by macrophages. This
receptor
mediates
the
binding,
internalization and processing of a wide
range of macromolecules, and is suggested
to play a major role in the recognition and
clearance of pathogenic and damaged cells.
Recent reports have suggested MSR1 to be a
candidate gene for hereditary prostate
cancer. Therefore, we screened the MSR1
gene among men with hereditary prostate
cancer and identified 18 sequence variants.
One previously reported truncation
mutation was found more frequently in men
with prostate cancer than in unaffected men,
in accordance with previously published
results. However, the difference in
frequencies we found between these groups
was not statistically significant. In addition,
we genotyped five common polymorphisms
in MSR1 in 215 men with unselected
prostate cancer and 425 controls. No
association between any of the five common
variants and prostate cancer were found.
We then performed a comprehensive
genetic study using extensive populationbased case-control material to evaluate
possible associations between sequence
variants in inflammation-related genes and
prostate cancer. The first gene to be
examined was interleukin-1 receptor antagonist
(IL-1-RN), encoding a cytokine that plays an
important role in regulation of the
inflammatory response by binding to the IL1 receptor and thus inhibiting the binding of
the pro-inflammatory cytokines IL-1α and
IL-1β. Collectively, these three cytokines
exert a central role in the protection against
diverse lesions, ranging from microbial
colonisation to infection and malignant
transformation. The genetic analysis of IL1RN revealed that the most common
haplotype was significantly associated with
prostate cancer risk for patients with
prostate cancer, and further this association
appears to be stronger in cases with
advanced disease.
The macrophage inhibitory cytokine-1 (MIC1), a member of the transforming growth-
4
Prostate Cancer and Inflammatory Genes
factor-β superfamily has been shown to
exert diverse biological functions, including
regulation of macrophage activity in the
inflammatory response and both growth
inhibition and induction of apoptosis in
epithelial and other tumour cell lines. The
genetic analysis of MIC-1 revealed that a
seuqence variant (H6D) appears to be
associated with a decreased prostate cancer
risk. We also performed measurements of
MIC-1 serum levels among patients with
prostate cancer and healthy controls. These
data indicate that serum MIC-1 levels are
associated with an increased risk for prostate
cancer. Further, the clear relation between
clinical stage and MIC-1 level also suggest
that MIC-1 may be useful as a prognostic
factor, where high serum concentration is
associated with a poor prognosis.
In summary, our results provide further
support
for
the
assumption
that
polymorphisms in inflammatory genes play
critical roles in prostate cancer susceptibility.
Additional studies are needed to elucidate
the mechanisms whereby the demonstrated
variations contribute to prostate cancer
development.
Prostate Cancer and Inflammatory Genes
5
Populärvetenskaplig sammanfattning
Antalet män som insjuknar i prostatacancer
har ökat markant under de två senaste
decennierna, vilket lett till att den blivit den
vanligast diagnostiserade cancerformen
bland män i de flesta industrialiserade
länderna. År 2002 diagnostiserades 679,000
nya fall av prostatacancer världen över,
medan 221,000 män avled av samma
sjukdom. Orsaken till incidensökningen
beror delvis på förbättrade diagnosmetoder,
men detta förklarar inte hela stegringen utan
andra okända faktorer är också involverade.
De senaste decennierna har ett flertal studier
visat
att
inflammationsprocesser
i
prostatakörteln är en betydande faktor i
utvecklingen av prostatacancer. Den exakta
mekanismen
för
hur
inflammation
medverkar till utveckling och progression av
tumörer i prostatakörteln är fortfarande
höljd i dunkel men är antagligen en komplex
process.
Det mänskliga genomet består av ungefär
30000 olika gener. Alla dessa gener uppvisar
olika grad av strukturell variation mellan
olika individer. Denna variation kan i sin tur
leda till en förändrad funktion hos det
protein som en gen kodar för, eller att
mängden protein som produceras varierar.
Även gener involverade i inflammationsprocesser uppvisar en sådan genetisk
variation. Om denna variation har någon
betydelse
för
risken
att
utveckla
prostatacancer har inte tidigare blivit
utförligt studerat. I denna avhandling har vi
studerat hur genetisk variation i olika
inflammationsrelaterade gener påverkar
risken att utveckla prostatacancer. Tre gener,
vilka alla är involverade i reglering av
inflammationsresponsen eller kroppens
försvar mot invaderande patogener har blivit
utförligt studerade.
I det första arbetet undersöktes om
sekvensvariationer i en gen kallad Macrophage
Scavenger Receptor 1 (MSR1), kan påverka
risken att insjukna i prostatacancer. MSR1 är
ett protein lokaliserat i cellens membran och
är i huvudsak uttryckt av makrofager.
Proteinet fungerar som en receptor med
möjlighet att binda till sig en mängd olika
substanser,
som
lipopolysackarider
(fragment från bakterier), och oxiderade
lipoproteiner. Efter inbindning tas dessa upp
av den aktuella cellen. Funktionen hos
MSR1 är inte helt klarlagd men den är bland
annat involverad i igenkänning och
eliminering av patogener och skadade celler.
Tidigare studier i en amerikansk population
har visat att mutationer i denna gen skulle
kunna ha betydelse för utvecklingen av
prostatacancer. Vi screenade MSR1 genen
hos män med ärftlig prostatacancer och
identifierade ett antal sekvensvariationer. Ett
urval
av
dessa
sekvensvariationer
undersöktes bland 215 män med oselekterad
prostatacancer och 425 kontroller, men
ingen av dem medförde en förändrad risk att
insjukna i prostatacancer. Våra resultat
stödjer ej tidigare publicerade resultat där
sekvensvariationer i MSR1-genen skulle ha
betydelse för uppkomsten av prostatacancer.
I nästföljande studier använde vi oss av
ett
stort
populationsbaserat
fall/kontrollmaterial
med
780
prostatacancerfall och 1383 friska kontroller
för att studera om genetisk variation hos
inflammationsrelaterade gener medför en
ökad eller minskad risk att insjukna i
prostatacancer.
6
Prostate Cancer and Inflammatory Genes
Den första genen kallad Interleukin-1
receptor antagonist (IL1-RN), är ett lösligt
protein, en cytokin, som reglerar kroppens
inflammationsrespons genom att binda till
en Il-1 receptor och därigenom förhindra
inbindning av två andra cytokiner, IL-1α och
Il-1β,
som
normalt
driver
på
inflammationsresponsen. Tillsammans spelar
dessa tre cytokiner en central roll i kroppens
skydd mot många olika skador, från invasion
av mikrober till malign transformation.
Balansen mellan pådrivande och inhiberande
cytokiner bestämmer utvecklingen av en
inflammationsrespons.
Den
genetiska
analysen av IL-1RN visade att bärare av den
vanligast
förekommande
sekvenskombinationen (haplotypen) av IL1-RNgenen medför en ökad risk att insjukna i
prostatacancer.
Macrophage inhibitory cytokine-1 (MIC-1) är
en medlem i en stor familj av proteiner
kallade transforming growth factor β
superfamily, som har visat sig medverka i en
mängd olika viktiga biologiska funktioner,
inkluderat reglering av inflammationsresponsen, tillväxthämning, men också
induktion av apoptosmekanismer i olika
tumörcellinjer.
Den genetiska analysen av MIC-1 visade att
en genetisk variant i genen (H6D), medför
en minskad risk att insjukna i prostatacancer.
Vidare mättes nivåerna av MIC-1-proteinet i
serum hos patienter med prostatacancer och
hos friska män för att se om MIC-1 nivåerna
var förändrade hos patienter med
prostatacancer. Analyserna visade att
serumnivåerna var tydligt förhöjda hos
patienter med prostatacancer. Nivåerna var
också positivt korrelerade med ökande ålder
och tumörstadie. Resultaten indikerar att
MIC-1 skulle kunna vara en användbar
prognostisk faktor, där höga serumnivåer är
associerade med en dålig prognos.
Således visar våra resultat att genetisk
variation i inflammationsrelaterade gener har
betydelse för uppkomst av prostatacancer.
För att förstå med vilka mekanismer denna
variation kan påverka utvecklingen av cancer
är vidare studier nödvändiga. Vi fann också
att mätning av MIC-1-nivåer i serum skulle
kunna vara av kliniskt värde som
prognostisk markör vid prostatacancer.
Prostate Cancer and Inflammatory Genes
7
Original studies
This thesis is based on the following studies.
I. Lindmark F, Jonsson BA, Bergh A,
Stattin P, Zheng SL, Meyers DA,
Xu J, Grönberg H. Analysis of the
macrophage scavenger receptor 1
gene in swedish hereditary and
sporadic prostate cancer. Prostate.
2004 May 1;59(2):132-40.
II. Lindmark F, Zheng SL, Wiklund F,
Augustsson Bälter F, Sun J, Chang
B, Hedelin M, Clark J, Johansson JE, Meyers DA, Adami HO, Isaacs
W, Grönberg H, Xu J. Interleukin-1
receptor antagonist haplotype
associated with prostate cancer risk.
Br J Cancer. 2005 Aug 22;93(4):4937.
Reprints are reproduced with the permission of the
respective publishers
III. Lindmark F, Zheng SL, Wiklund F,
Bensen J, Augustsson Bälter K,
Chang KA, Hedelin M, Clark J,
Stattin P, Meyers DA, Adami HO,
Isaacs W, Grönberg H, Xu J. H6D
polymorphism in macrophageinhibitory cytokine gene-1
associated with prostate cancer.
JNCI 2004 Aug 18;96(16):1248-54.
IV. Lindmark F, Wiklund F, Hunter M,
Xu J, Bälter K, Adami HO, Breit S,
Grönberg H. Serum levels of
macrophage inhibitory cytokine-1 in
prostate cancer cases and controls.
Manuscript
8
Prostate Cancer and Inflammatory Genes
List of Abbreviations
AR
BPH
BSA
CAPS
CHEK2
CEPH
CI
DHT
DNA
DZ
ELISA
fPSA
GSTP1
htSNP
HPC
HPLC
HPV
HWE
IL-1α
IL-1β
IL1-RN
LD
LPS
MIC-1
MSR1
MZ
Androgen receptor
Benign prostatic hyperplasia
Bovine serum albumin
Cancer prostate in Sweden
Checkpoint kinase 2
Centre d’Etude du
Polymorphisme Humain
Confidence interval
Dihydrotestosterone
Deoxyribonucleic acid
Dizygotic
Enzyme-linked
immunosorbent assay
free PSA
Glutathione-S-transferase P1
Haplotype tagging SNP
Hereditary prostate cancer
High performance liquid
chromatography
Human papilloma virus
Hardy Weinberg Equilibrium
Interleukin-1 alpha
Interleukin-1 beta
Interleukin-1 receptor
antagonist
Linkage disequilibrium
Lipopolysacharide
Macrophage inhibitory
cytokine-1
Macrophage scavenger
receptor 1
Monozygotic
NSHDC
OR
PCR
PIA
PIN
PSA
ROC
ROS
RNASEL
RNS
RR
SNP
SPC
SR-A
SRD5A2
STI
TEAA
TGF-β
TMHA
TNM
TNF-α
tPSA
VNTR
Northern Sweden health and
disease cohort
Odds ratio
Polymerase chain reaction
Proliferative inflammatory
atrophy
Prostatic intraepithelial
neoplasia
Prostate specific antigen
receiver operator
characteristic
Reactive oxygen species
Ribonuclease L gene
Reactive nitrogen
species
Risk ratio
Single nucleotide
polymorphism
Sporadic prostate cancer
Class A scavenger receptor
5α-Reductase type 2
Sexually transmitted
infection
Trietylammonium acetate
Transforming growth factor
β
Temperature modulated
heteroduplex analysis
Tumour-node-metastasis
Tumour necrosis factor α
total PSA
Variable number of tandem
repeats
Prostate Cancer and Inflammatory Genes
9
Introduction
In most developed countries, prostate
cancer is not only the most frequently
diagnosed malignancy in men, but also the
second leading cause of cancer-related
deaths in males. In 2002, an estimated
679,000 prostate cancer diagnoses were
made worldwide, accompanied by an
estimated 221,000 prostate cancer deaths
(Parkin et al., 2005). In Sweden, over 9000
new diagnoses of prostate cancer were
recorded in the year 2003, accounting for
35.3 % of cancer diagnoses among men that
year (fig.1). Further, 2350 men died from
this disease 2003. Although the incidence of
prostate cancer is increasing steadily in
almost all countries, the aetiology and
molecular mechanisms underlying the
development and progression of the disease
is still large unknown.
Prostate cancer is often regarded as a
disease of older men, but nearly a third of
men aged between 30 and 40 years have
been found to harbour small foci of prostate
cancer (Sakr et al., 1994). The majority of
these lesions are diagnosed at a much later
age or do not progress to clinically
detectable tumours within the lifetime of the
affected men. Cancer lesions can develop in
two different regions of the prostate gland,
most commonly (in ~80% of cases) in the
periphery zone, while most of the remaining
lesions are found in the transition zone,
which is located in the periurethral region
(McNeal, 1968, 1988). Prostate cancer is
commonly multifocal, i.e. there is generally
more than one tumour with different origins
in the prostate at the time of diagnosis
(McNeal, 1988). Each of these tumours can
show remarkable differences in gene
expression and behaviour, which are
associated with varying prognoses. In its
clinical form, prostate cancers are diagnosed
upon histological evaluation of needle
biopsy samples of prostate tissue, and
classified as either local or advanced. In
localized disease, the treatments range from
radical prostatectomy, radiotherapy and
application of anti-androgens to “watchful
waiting” (Afrin et al., 2000; Drachenberg,
2000). If the cancer has spread outside the
prostate, with lymph nodes and bone being
the most common sites for metastasis, the
most common treatment is surgical or
chemical castration, to lower androgen
levels, causing reductions in tumour growth
and symptomatic relief, but not a cure.
However, after one to two years most
tumours will relapse to an androgenindependent, but still androgen receptordependent, state that normally kills the
patient (Afrin et al., 2000; Drachenberg,
2000;
Feldman
et
al.,
2001).
10
Prostate Cancer and Inflammatory Genes
Figure 1. Cancer incidence in Sweden 2003. The ten most frequently specified
cancer sites among men, according to the National Board of Health and Welfare.
Risk factors for prostate cancer
The etiological factors associated with
prostate cancer are varied and particularly
poorly understood compared to other
common cancers.
The observation that prostate cancer risk
increases for Japanese immigrants to Hawaii
and Japanese immigrants to Los Angeles,
suggests that diet and environmental
differences play important roles (Shimizu et
al., 1991; Minami et al., 1993). However, the
increase is only to about 50% of the rate for
Caucasian people and to 25% of that for
African-American people in the USA,
suggesting that differences between ethnic
populations are substantial and that
differences in incidence rate cannot be
explained solely by differences in the
environment and lifestyle (Grönberg, 2003).
Dietary factors
Dietary habits are probably an important
factor that contributes to the geographic
variations in prostate cancer rates. A large
number of epidemiological studies have
investigated the association between dietary
factors and prostate cancer, but the findings
have been mixed.
Dietary fat. There is considerable
consistency across studies indicating that a
high intake of fat, especially total fat and
saturated fat, is a risk factor for prostate
cancer (Kolonel, 2001). The mechanisms
mediating the effects of fat on prostate
carcinogenesis are not known, but it is
hypothesized that the effect of dietary
factors, such as fat, may be mediated
through endogenous hormones (Bosland,
2000).
Phytoestrogens. Soy products contain
isoflavonoids that have been shown to have
a prophylactic effect on prostate cancer
(Holzbeierlein et al., 2005). People in Asian
countries eat more soy products than people
in Western countries and higher levels of
phytoestrogen metabolites have been
Prostate Cancer and Inflammatory Genes
observed in Asian men compared to
European men. This may provide a partial
explanation for the low incidence of prostate
cancer in Asia (Adlercreutz et al., 1993). Mice
studies with human androgen-sensitive
prostate cancer cells have shown that a diet
based on rye bread and soy protein reduces
tumour size and secreted PSA levels, while
increasing apoptosis, and may thus inhibit
tumour growth (Landström et al., 1998;
Bylund et al., 2000). A subsequent pilot study
of men with prostate cancer indicated that a
high intake of rye bread increases apoptosis
in prostate tumour cells (Bylund et al., 2003).
Vegetables and fruits. While chronic
consumption of animal fat and red meats
may promote prostate cancer, intake of
vegetables and fruit may protect against
prostate cancer development (Chan et al.,
2001). A large prospective study of 130,544
men found no association between the total
consumption of fruits and vegetables and
risks for prostate cancer among 1104
prostate cancer cases. However, it still
remains possible that there may be an
association with specific types of fruits and
vegetables (Key et al., 2004).
Vitamins and trace elements. A variety of
vitamins, trace elements have been
elucidated for their role in prostate cancer
pathogenesis, but the results of the
epidemiology studies are inconsistent (Chan
et al., 2001). A promising substance is
selenium; an essential, non-metallic trace
element that has been demonstrated to
promote apoptosis in prostate cancer cells
and, possibly, impairs their proliferation
through antiangiogenic activity. Selenium
intake has been significantly associated with
a decreased risk for prostate cancer, for a
review see Combs GF, 2004 (Combs, 2004).
11
Hormonal and other physiological
factors
The growth and development of the
prostate is dependent on androgens.
Ablation of androgens by surgical or medical
castration is an effective strategy in the
treatment of advanced prostate cancer.
Moreover,
men
with
congenital
abnormalities in androgen metabolism and
those who undergo castration before
puberty do not develop prostate cancer
(Haas et al., 1997).
Several epidemiologic studies have
evaluated the possible association between
plasma testosterone concentrations and
prostate cancer risk, but the results have
been inconsistent (Hsing, 2001). A recent
well designed study published in 2004
reported that high levels of circulating
testosterone are not associated with
increased prostate cancer risk (Stattin et al.,
2004). However, if testosterone is important
for the onset of prostate cancer, then it may
need to be measured in early adulthood,
years before the prostate cancer is actually
detected (Crawford, 2003).
Other factors such as smoking, weight,
alcohol consumption, physical activity,
socioeconomic status, and vasectomy have
also been evaluated for their role in prostate
pathogenesis, but the results have generally
indicated that they are not significant
(Grönberg, 2003).
Familial and genetic factors
Over the past two decades multiple pieces of
evidence have been accumulated supporting
the view that genetics plays a role in prostate
cancer susceptibility and pathogenesis.
However, the evidence also indicates that
12
Prostate Cancer and Inflammatory Genes
the genetic basis of prostate cancer is much
more complex than was initially anticipated.
Large families have been observed in which
prostate cancer cluster together. Early
observations were made in large families
collected and studied in Utah, but the first
description of familial aggregation of
prostate cancer was reported as far back as
1956, (MORGANTIG et al., 1956). This
initiated a series of case-control studies,
cohort studies, and twin studies that
generated evidence of a familial component.
Case-control and cohort studies
Several published reports have demonstrated
an increased risk for prostate cancer among
men with a positive family history for
prostate cancer. In 2003, Bruner et al.
published a meta-analysis of 16 case-control
studies and eight cohort studies supporting
this working theory, in which family history
was defined as cases where a father, brother,
any first- or second-degree relative or other
relative had been affected by prostate cancer
(Bruner et al., 2003). Pooled Risk ratios
(RRs) for men with any affected family
member, one affected first-degree relative
and one affected second-degree relative were
1.9 (95% CI, 1.6-2.2), 2.2 (95% CI, 2.1-2.4)
and 1.9 (95% CI, 1.6-2.3), respectively.
Further increases in RR have consistently
been observed (i) when more than one
relative is affected, (ii) as the closeness of the
affected relative to the unaffected individual
increases, and (iii) as the age of onset of the
affected cases decreases. Taken together,
this is all strong evidence for the
involvement of a genetic component in
familial disease.
Twin studies
The most straightforward way to estimate
the impact of genetic factors on the
development of prostate cancer is to analyze
its incidence in mono- and di-zygotic twins.
This is because monozygotic twins (MZ)
derive from the fission of a single fertilized
egg, thus they inherit identical genetic
material and the only genetic differences
between them originate from somatic
changes. By contrast, dizygotic (DZ) twins
derive from two distinct fertilized eggs and
thus have the same genetic relationship as
full siblings, although they may be more
“biologically” related because they share the
same prenatal intra-uterine experience. Since
the environmental factors affecting pairs of
MZ and DZ twins are generally very similar,
since they are usually raised in the same
environment, it is assumed that any
differences in concordance rates between
them solely reflect genetic factors. Two large
twin studies from America and Scandinavia
have been published and the results they
present show surprisingly consistency (Page
et al., 1997; Lichtenstein et al., 2000). Both
studies found that an MZ twin whose
brother has been reported as having had
prostate cancer is nearly four times more
likely to have prostate cancer than a DZ
twin whose brother has reportedly had
prostate cancer. Furthermore, Page et al. and
Lichtenstein et al. estimated that the
proportion of the risk of prostate cancer
that can be explained by heritable factors
was estimated to 57% and 42%, respectively.
Family-based segregation analyses
Further support for a genetic component in
prostate cancer comes from family-based
segregation analyses, which have been used
to derive models for the prevalence (rare,
Prostate Cancer and Inflammatory Genes
common), mode of inheritance (dominant,
recessive, autosomal, or sex chromosome
linked), and penetrance (the likelihood of
carriers developing the disease by a certain
age) of genes that may be involved in
familial prostate cancer. In 2004, Daniel
Schaid reviewed the eight segregation
analyses that had published thus far (Schaid,
2004). In summary, the segregation analysis
of prostate cancer give strongest support for
autosomal
dominant
inheritance
of
susceptibility genes, but there are also
evidence for autosomal recessive or Xlinked mode of inheritance, a model with 2
or 3 genes contributing to the disease and a
multifactorial
mode
of
inheritance.
Nevertheless, it has become obvious that
prostate cancer is most likely caused by a
number of genes – each with different
modes
of
inheritance,
population
frequencies, and penetrance.
Prostate cancer susceptibility genes
Although more than 40% of prostate cancer
cases are estimated to be an effect of genetic
variation (Lichtenstein et al., 2000), rare,
highly penetrant genes probably account a
minority of prostate cancer cases. Mutations
in high-penetrance susceptibility genes
increase the risk of cancer several fold, and
tumours with such mutations are often
called hereditary cancers. So far three highrisk candidate genes have been identified;
HPC/ELAC2 on 17p, RNASEL on 1q25,
and MSR1 on 8p22-23 (see descriptions
below). Attempts to confirm these findings
in different populations have been
problematic, and the importance of these
genes in prostate cancer pathogenesis is still
obscure (Schaid, 2004). Nevertheless, these
three genes clearly do not account for the
majority of hereditary prostate cancer cases.
13
Carriers of mutations of another gene,
BRCA2, are known to be at high risk of
breast and ovarian cancer, but BCRA2 has
also been implicated in prostate cancer
predisposition. A large collaborative study
from the Breast Cancer Linkage Consortium
estimated, based on a survey of 173 families
harbouring BRCA2 mutations, a relative risk
of 4.65 (95% CI, 3.48-6.22) for prostate
cancer in male BRCA2 gene carriers (The
Breast Cancer Linkage Consortium,
1999). However, since BRCA2 mutations
are rare in families with hereditary prostate
cancer, they only account for a very small
fraction of hereditary prostate cancers.
The discovery of highly penetrant
prostate cancer genes has coupled problems
for at least two major reasons. First, due to
the late onset of prostate cancer, it is
difficult to identify representatives of more
than two generations of a family that could
be included in molecular studies. Increases
in the number of generations that can be
examined increases the possibility of finding
relevant and true susceptibility loci that
affect prostate cancer risks. Another
significant problem is the lack of clear
distinguishing features between hereditary
and sporadic forms of the disease, making it
difficult to distinguish, within high-risk
pedigrees, men who have developed cancers
that are sporadic rather than due to an
inherited germline mutation (Rubin et al.,
2004).
Polymorphisms associated with prostate cancer
The remainder of the genetic influence is
most likely mediated by more common
genetic variants or polymorphisms. Lowpenetrance polymorphisms increase the risk
of cancer only modestly, but the prevalence
of such polymorphisms may be higher than
14
Prostate Cancer and Inflammatory Genes
the prevalence of mutations in highpenetrance susceptibility genes, and thus
their overall impact or attributable risk can
be substantial. The list of these variants is
long, but the major pathways currently
under investigation include those involved in
androgen action, DNA repair, carcinogen
metabolism, and inflammation pathways.
Numerous polymorphisms have already
been suggested to be associated with the risk
of prostate cancer.
Androgen receptor (AR). The most widely
studied polymorphic gene may be the
androgen receptor (AR) gene. The AR gene,
located on chromosome Xp11-12, encodes a
ligand-activated transcription factor that
mediates the androgenic response, and has
been shown to play an important role in
prostate development and function. Exon 1
of this gene contains two polymorphic
microsatellites: a highly polymorphic CAG
repeat and a less polymorphic GGC repeat.
Since the length of the polymorphic CAG
trinucleotide repeat has been shown to be
inversely correlated with the transcriptional
activity of the AR gene, it has been
hypothesized that variation in the length of
the repeat are also associated with variations
in prostate cancer risks. Several genetic
epidemiological studies have shown a
correlation between an increased risk of
prostate cancer and the presence of short
androgen-receptor CAG repeats, but other
studies have reported inconsistent results
(Simard et al., 2003). At present, no study
has detected any correlation between GGC
repeats and functional activity of the AR
gene. Furthermore analyses of the possible
association between GGC repeats and
prostate cancer have been inconclusive
(Gsur et al., 2004).
SRD5A2. The 5α-reductase type II gene
(SRD5A2) is a membrane protein of the
endoplasmatic reticulum that catalyzes the
conversion of testosterone into the more
active form androgen dihydrotestosterone
and maps to 2p22-23. SRD5A2 is primarily
expressed in androgen-sensitive cells of
genital tissues and the prostate gland.
Certain SRD5A2 polymorphisms may
contribute to different enzyme activities of
5α-reductase variants. A dinucleotide (TA)
repeat polymorphism in the untranslated
region of SRD5A2 has been identified.
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. Thus, these
alleles may increase the risk of prostate
cancer. (Coughlin et al., 2002)
In
addition,
two
nonsynonymous
polymorphisms, A49T and V89L, have been
identified. These two polymorphisms may
also alter the DHT levels and consequently
influence prostate cancer risks. However,
the evidence for prostate cancer risk
associated with these three SRD5A2 variants
has been conflicting (Ntais et al., 2003).
Other genes with sequence variants that
have suggested association with the risk of
prostate cancer include CHEK2 and the
vitamin D receptor (VDR) and 17αhydroxylase (CYP17) (Hughes et al., 2005).
However, a typical feature of many of these
genes is that highly conflicting findings
regarding their putative involvement in
prostate cancer have been published
(personal communication, Sara Lindström).
Thus, at the moment, none of the sequence
variants can be considered to be definitely
associated with prostate cancer.
In conclusion, a large number of studies
have evaluated the risk of dietary,
environmental and genetic risk factors, with
mixed results. Since all these risk factors are
likely
to
cluster
within
families,
discriminating genetic from non-genetic
Prostate Cancer and Inflammatory Genes
risks is difficult, especially since the
magnitude of the risks is similar for both
15
genetic and non-genetic risk factors (Schaid,
2004).
Inflammation and cancer
Various carcinomas (including cancers of
the liver, bladder, colon, stomach, and
oesophagus) have been shown to arise from
areas of infection and inflammation. Over
15% of all malignancies worldwide are
attributable to infectious agents, and
inflammation is a major component of these
chronic infections (Kuper et al., 2000).
Colon cancers arising in individuals with
inflammatory bowel disease (e.g. chronic
ulcerative colitis or Crohn’s disease) and
stomach cancers caused by chronic
Helicobacter pylori infection are among the
most intensively studied and well established
types of cancer associated with inflammation
of different origins (Coussens et al., 2002).
Inflammation involves the induction of
complex, coordinated chemical signals and
associated physiological processes following
injury that promote “healing” of damaged
tissues. Early responses include increases in
vascular permeability and activation,
together with the directed migration of
leukocytes (neutrophils, monocytes and
eosinophils) towards the site of injury, where
the ground-work is being laid for the
formation of a new extracellular matrix. The
directional migration is mediated by secreted
chemokines that form a concentration
gradient towards the site of inflammation.
The extracellular matrix provides the
structure upon which cells (fibroblasts and
endothelial cells) can migrate and proliferate,
regenerating new tissue and a vascular
network. In later stage of the inflammatory
response, the macrophages are the dominant
cell type, orchestrating and directing the
healing process. Normally, inflammation is a
self-limiting process due to the production
of anti-inflammatory cytokines that buffer
the effect of pro-inflammatory cytokines.
The cytokine/chemokine pattern persisting
at the inflammatory site is important in the
development
of
chronic
disease.
Dysregulation of any of the cooperating
factors can lead to prolonged inflammation
with chronic exposure to cytotoxic
mediators. (Coussens et al., 2002). Chronic
inflammation can be caused by a variety of
factors, including bacterial, viral, and
parasitic infections, chemical irritants, and
non-digestible particles, but often the
underlying cause is unknown. The longer the
inflammation persists, the higher the risk of
associated carcinogenesis (Shacter et al.,
2002).
At the site of inflammation, caused by
either wounding or infection, phagocytic
cells (e.g. neutrophils and macrophages)
generate reactive oxygen and nitrogen
substances, but these cells also synthesize
and secrete large quantities of growth factors
and a number of potent angiogenic factors,
cytokines, and proteases, all of which are
important mediators in the tissue
regeneration, but can also potentiate
neoplastic tumorigenesis. The focus of
interest has been the individual function of
the different mediators, but in the
inflammation response there is significant
interaction and synergy among them – for
example,
prostaglandins
induce
the
16
Prostate Cancer and Inflammatory Genes
expression of certain inflammatory cytokines
which can in turn, induce the production of
reactive oxygen and nitrogen species. The
following description summarises the role of
three types of inflammatory mediators in
inflammation and tumour development.
Reactive oxygen and nitrogen species.
At the site of inflammation activated
phagocytes produce large amounts of
reactive oxygen (ROS) and nitrogen species
(RNS). These substances are normally
produced in response to infection, killing
invading agents. Nevertheless, they can also
cause tissue damage and thereby act as
initiators of tumorigenesis. ROS and RNS
have been shown to alter protein structure
and function, cause lipid peroxidation, and
damage DNA, thereby contributing to the
carcinogenic process. ROS/RNS-induced
damage to DNA may result in mutagenesis
or altered expression of transcriptional
factors involved in carcinogenesis. Damage
may also occur to vital DNA repair
enzymes, altering their activity, which may
increase mutagenesis (Wiseman et al., 1996).
These processes can cumulatively lead to an
imbalance between the rate of mutagenesis
and the ability to repair mutations, resulting
in the accumulation of multiple mutations
and, thus, increases the risk for
carcinogenesis.
Prostaglandins. In addition to ROS and
RNS, prostaglandins are synthesized in large
amounts by inflammatory cells in response
to both acute and chronic inflammatory
stimuli. Prostaglandins are lipid mediators of
the inflammatory immune response that
have a wide range of physiological functions,
such as vasodilatation/constriction and
inhibition/enhancement of inflammatory
cell functions. Studies on humans and
animals have generated evidence that
suggesting that prostaglandins contribute to
the development of cancer (Shacter et al.,
2002). Two different cyclooxygenase (COX)
enzymes catalyse the rate-limiting first step
in prostaglandin synthesis. COX-1 is
constitutively expressed in most cell types,
while COX-2 is primarily expressed by
monocytes and macrophages during
inflammation. Long-term intake of nonsteriodal anti-inflammatory drugs (NSAIDs;
drugs that inhibit the activity of both COX1 and COX-2) have been shown to reduce
the incidence and progression of colon
caner (Baron et al., 2000), and similar effects
has been indicated for prostate cancer
(Basler et al., 2004). However, believing that
the tumour-repressing effect is mediated
solely
through
the
inhibition
of
cyclooxygenase activity is an over
simplification (Zha et al., 2004). Finally,
other metabolites derived from arachidonic
acid, such as leukotrienes and tromboxanes,
may also be important mediators in the
development of cancer, but the knowlegde
of these aspects is still very limited.
Cytokines. Cytokines are generally small
molecules that alter the behaviour of the
cells that secrete them and/or other cells,
generally within the heamatopoietic system.
They act in a in a complex coordinated
network in which they initiate or suppress
their own synthesis as well as that of other
cytokines and cytokine receptors. The
complexity arises from the fact that there is
often substantial overlap and redundancy
between the functions of individual
cytokines (Howell et al., 2002). In response
to both antigen-specific and non-specific
stimuli, inflammatory cells secret a wide
array of cytokines, which play critical roles in
the generation of both pro- and antiinflammatory immune responses. For
example, cytokines such as TNFα and IL-1
are usually classed as key pro-inflammatory
cytokines, while cytokines such as IL-10 are
anti-inflammatory. The balance between the
Prostate Cancer and Inflammatory Genes
effects of pro-inflammatory and antiinflammatory cytokines determines the
outcome of the inflammatory process.
Cytokines can contribute to cancer
development in several ways. TNFα has
been shown to enhance the formation of
ROS by inflammatory cells, and thereby
increase the risk for DNA damage and
inhibition of DNA repair in tumour cells.
Other
mechanisms
include
direct
stimulation of cell growth, induction of
angiogenesis,
and
recruitment
of
inflammatory neutrophils (Shacter et al.,
2002). In addition, an imbalance of pro- and
anti-inflammatory cytokines, caused by point
mutations or polymorphisms, may prevent
the normal self-limiting nature of the
immune response, leading to prolonged
17
inflammation with chronic exposure to
cytotoxic mediators.
In conclusion, multiple pieces of
evidence
have
demonstrated
that
inflammatory cells have powerful effects on
tumour development, but recruitment of
inflammatory cells may also be inhibitory to
tumour development, and may represent an
attempt by the host to suppress tumour
growth. This process requires further
evaluation. One approach is to elucidate
whether functional polymorphisms in genes
that regulate inflammatory processes, such
as cytokines, confer altered risks for
developing cancer or are potential
prognostic factors. See (Shacter et al., 2002)
and
(Coussens et al., 2002) for a
comprehensive review.
The role of inflammation in the pathogenesis of prostate cancer
Although it has been established that
chronic inflammation plays a causative role
in the development of many human cancers,
the contribution of inflammatory processes
to the development of prostate cancer has
not been extensively studied. However, data
from
epidemiological,
genetic
epidemiological and molecular pathology
studies have been accumulated recently
suggesting that inflammatory processes are
also involved in the development of prostate
cancer.
The
chronic
inflammatory
microenvironment, characterized by the
accumulation
of
macrophages
and
lymphocytes, is extremely common in the
tissue stroma and epithelium of the prostate
and may support both the initiation and
progression of prostate cancer (Lucia et al.,
2004). The following description highlights
connections
between
inflammatory
processes and the development of prostate
cancer.
Molecular pathology
Focal areas of epithelial atrophy in the
prostate were first observed by pathologists
more than fifty years ago (FRANKSLM,
1954; Rich, 1979). Atrophy of the prostate is
identified as a reduction in the volume of
the glands and can be divided into two
major patterns: diffuse and focal. Diffuse
atrophy is a reduction that involves the
entire prostate and is caused by a decreased
level of circulating androgens. Focal atrophy,
on the other hand, occurs primarily, but not
exclusively, in the outer part of the gland,
where prostate cancer normally arises
18
Prostate Cancer and Inflammatory Genes
(McNeal, 1988; Feneley et al., 1996; Ruska et
al., 1998; De Marzo et al., 1999). Focal
atrophy is not related to reduced levels of
circulating androgens, compared with
normal prostatic epithelium, and the
condition is highly proliferative without any
increase in apoptosis. Focal atrophy is often
associated with acute or chronic
inflammation, reflected by infiltration of
inflammatory
cells
(lymphocytes,
macrophages and polymorphonuclear cells)
(Ruska et al., 1998; De Marzo et al., 1999).
Due to the combined findings of high
proliferation indices and inflammatory
infiltrations seen in these lesions, the term
proliferative inflammatory atrophy, or PIA,
was introduced (De Marzo et al., 1999). The
underlying causes of PIA lesions are still not
clearly understood, but they may arise either
as a consequence of epithelial damage (from
infection, ischemia, or toxin exposure) or as
a direct consequence of inflammatory
oxidant damage to the epithelium (Platz et
al., 2004).
Accumulating
evidence
from
morphological, immunohistochemical and
genetic studies have provided support for
the concept that PIA lesions may be
precursors to prostate cancer, partly because
the vast majority of such lesions are found
adjacent to or near early adenocarcinomas or
high
grade
prostatic
intraepithelial
neoplasms, or both (Feneley et al., 1996; De
Marzo et al., 1999; Putzi et al., 2000). Further
support for the hypothesis comes from the
fact that PIA shares several molecular
alterations found in both Prostate
Intraepithelial Neoplasia (PIN) and prostate
cancer. Nakayama et al. reported that
approximately 6% of PIA lesions show
evidence of somatic hypermethylation of the
GSTP1 gene promoter (Nakayama et al.,
2003). Correspnding levels of GSTP1
hypermethylation in PIN lesions and
prostate cancer tissue are approximately
70% and 90%, respectively (Jerónimo et al.,
2001; Lin et al., 2001).
In
addition,
chromosome
8
abnormalities, which are common in
prostate cancer, have been found in areas of
PIA lesions. Acquired somatic chromosome
8 abnormalities have been noted in about
1% of normal prostate tissue, 4% of PIA
lesions, and about 6% of adenocarcinomas
(Shah et al., 2001). Other studies have
reported p53 mutations in 5% of PIA
lesions, a rate similar to that seen in highgrade PIN, compared to 20% of prostate
cancer cases (Tsujimoto et al., 2002). Thus,
these are genetic changes that are associated
with PIN and prostate cancer.
De Marzo et al. examined expression
patterns of three molecular markers
implicated in prostatic carcinogenesis: p27,
Bcl-1 and GSTP1 (De Marzo et al., 1999).
p27 is a cyclin-dependent kinase inhibitor
whose expression suppresses the cell cycle
and is usually reduced in prostatic
adenocarcinomas and high-grade PIN. The
cited authors reported a down-regulation of
p27 in PIA. They also observed an increase
in Bcl-2 expression, as previously reported
by Ruska et al. (Ruska et al., 1998), which is
consistent with the very low levels of
apoptosis. Moreover, they found increased
levels of GSTP1 in many lesions suggesting,
together with the elevated levels of GSTA1
and COX-2 reported in other studies
(Parsons et al., 2001; Zha et al., 2004), that a
stress-induced response has occurred in
these cells. Accumulating evidence also
indicates that many of the atrophic luminal
cells in PIA represent a form of intermediate
epithelial cell with high proliferative activity.
These cells share features of both basal and
luminal secretory cells, and hence are
postulated to be targets of neoplastic
Prostate Cancer and Inflammatory Genes
transformation in the prostate (van Leenders
et al., 2003).
Even though PIA lesions may be an early
histological precursor to prostate cancer, it is
important to note that some studies have
not found an association between PIA and
prostate cancer (De Marzo et al., 2003) and,
moreover, not all cancers occur within or in
the vicinity of PIA. In fact, PIA may simply
indicate an intraprostatic environment that
favours to prostate cancer development.
Nevertheless, further studies are needed to
elucidate the relationship between focal
atrophy and cancer in the prostate.
Chronic
inflammation,
with
a
predomination
of
lymphocytes
and
macrophages, is extremely common in the
prostate.
However,
examination
of
prostatectomy specimens seldom shows
inflammatory infiltrates in the malignant
tissue, whereas directly adjacent benign
tissue can be heavily infiltrated (Lucia et al.,
2004). To date, the relationship between
lymphocytic infiltration in the tumour and
progression of tumour development in the
prostate is uncertain, but the results from
two studies evaluating the connection
between inflammatory infiltration and
survival indicate that lymphoid aggregates
within the tumour are associated with a poor
outcome in patients with prostate cancer
(Irani et al., 1999; McArdle et al., 2004).
Furthermore, increased macrophage activity
in the tumour has also been found to be
related to poor prognosis in prostate cancer
(Lissbrant et al., 2000). Why the presence of
increased in lymphocytic aggregates would
be associated with poor cancer specific
survival rates remains unexplained.
Epidemiology
Prostatitis and prostate cancer. Prostatitis
is a common urological disorder worldwide;
19
2-10% of men experience it during their
lifetime (Habermacher et al., 2005). The
clinical presentation is characterised by
uncomfortable symptoms, such as dysuria,
and rectal and suprapubic pain (Roberts et
al., 1998) Prostatitis is classified into four
categories: I, acute bacterial; II, chronic
bacterial; III, chronic nonbacterial/chronic
pelvic pain syndrome; and IV, asymptomatic
prostatitis. Both acute bacterial prostatitis
(which is usually caused by Escherichia coli)
and chronic bacterial prostatitis (caused by
E. coli and several other infectious agents)
are normally treated with antibiotics.
Chronic non-bacterial prostatitis/chronic
pelvic pain syndrome, is the most common
form, affecting 90-95% of patients with
prostatitis. Men with this type of prostatitis
may experience symptoms for weeks to
years, and current therapy has limited
success in alleviating the pain that the
patients
experience.
Asymptomatic
prostatitis is a histological diagnosis of
prostate inflammation that is found
subsequent to pathological examination of
the prostate tissue. This category is found in
a significant number of patients;
epidemiologic studies have estimated the
prevalence to be as high as 32.2% in a
population of men with elevated PSA (van
Leenders et al., 2003).
Several case-control studies have
investigated the association between prostate
cancer and prostatitis, with variable results.
In 2002, Dennis et al. performed a metaanalysis of 11 case-control studies that
evaluate the possible relationship between
prostatitis and prostate cancer. The metaanalysis found an increased risk of prostate
cancer among men with a history of clinical,
or symptomatic prostatitis (OR=1.6; 95%
CI, 1.0-2.4), particularly in population-based
case-control studies (OR=1.8; 95% CI, 1.13.0) (Dennis et al., 2002b). However, the
20
Prostate Cancer and Inflammatory Genes
complexities involved in diagnosing
prostatitis and the risks for potential recall
or detection bias when performing
association studies between prostatitis and
prostate cancer make the analyses of the
results problematic. The results could reflect
an effect of detection bias, since patients
with prostatitis may be more likely to be
monitored by a urologist and thus more
likely to be screened for prostate cancer, or
the results could reflect a recall bias, since
patients with prostate cancer may try to
remember more about potential exposure
than controls do (Dennis et al., 2002b).
Epidemiological studies investigating the
possible association between prostatitis and
prostate cancer have relied on patient
reports for information on prostatitis
history. Therefore, there are serious
problems in using studies of this type to
identify valid relationships between category
IV prostatitis and prostate cancer. The
reason why inflammation leads to symptoms
in some men but not others are not known.
It is possible that a distinguishing feature
between symptomatic and asymptomatic
prostatitis may be the anatomical localisation
of the prostatic inflammation. Inflammation
in the peri-urethtral region, or transition
zone, may be more likely to manifest in
urinary symptoms and pain than
inflammation in the outer areas of the gland,
or the peripheral zone, where prostate
cancer more commonly develops (Palapattu
et al., 2004).
In addition, according to two
epidemiological studies, the prevalence of
prostatitis correlates with the prevalence of
prostate cancer worldwide, with rates of
prostatitis and prostate cancer being much
higher in North America than Asia (Roberts
et al., 1998; Tan et al., 2002).
More general evidence of a relationship
between inflammation and prostate cancer
was provided by reports of an association
between the use of anti-inflammatory drugs
(NSAIDs) and prostate cancer risk.
However, the results have been inconsistent
(Basler et al., 2004). The most interesting
data showing an inverse association with
NSAID use come from a large (n=1362)
population-based longitudinal study in
Olmsted County, MN, USA, the results of
which suggest that daily use of NSAIDs may
be associated with a lower incidence of
prostate cancer among ³60-year-old men
(RR 0.45; 95% CI, 0.28-0.73) (Roberts et al.,
2002). Furthermore, the inverse association
with NSAID use increased with increasing
age.
Sexually transmitted infections and
prostate cancer. Sexually transmitted
infections (STIs) have long been
hypothesized to increase the risk for
prostate cancer. STIs are theorized to
increase the risk of prostate cancer by
causing inflammation of the prostate, which
may in turn lead to the initiation of
carcinogenesis (Nelson et al., 2003). Several
studies have investigated the potential
association between prostate cancer and
STIs, using various approaches, including
self-reports, serology, and detection of
infectious agents in the prostate.
Self-report: In a meta-analysis (Dennis et al.,
2002a) reviewed 36 independent analytical
studies, published between 1971 and 2000,
that measured some aspect of sexual activity
in relation to prostate cancer. The data
suggest there was an elevated relative risk of
prostate cancer among men who reported a
history of any STI (RR=1.44; 95% CI, 1.241.66). The risk associated with syphilis alone
was higher (RR=2.30; 95% CI, 1.34-3.94),
while the risk associated with gonorrhoea
was not as strong as that for the presence of
all STIs (RR=1.36; 95% CI, 1.15 -1.61). The
association between prostate cancer and
Prostate Cancer and Inflammatory Genes
STIs was further supported by RR
increasing with increasing frequency of
sexual activity (RR=1.20; 95% CI, 1.111.30), for men reporting more than 30 sexual
partners (RR=1.27; 95% CI, 1.08-1.49), and
for men who visited prostitutes (RR=1.19;
95% CI, 1.01-1.41).
Recently, Taylor et al. performed a new
meta-analysis, including 29 case-control
studies, which corroborated the previous
findings (Taylor et al., 2005). The study
demonstrated a signficantly elevated OR for
prostate cancer for all STIs (OR=1.48, 95%
CI 1.26-1.73), and for gonorrhea (OR=1.35;
95% CI, 1.05-1.83). However, the results
should be interpreted with caution, since
most of these studies were retrospective
case-control studies, and thus may have
been affected by bias in recall between cases
and controls. Also, a history of STIs may
not be causally associated with prostate
cancer, but may be simply be a surrogate for
other lifestyle risk factors for prostate cancer
(Platz et al., 2004) Furthermore, since these
two meta-analyses, a number of studies have
been published reporting inconsistent
association between STIs and prostate
cancer risk (Giles et al., 2003; Fernández et
al., 2005; Patel et al., 2005).
Serological markers: Several epidemiological
studies have also reported associations
between prostate cancer and circulating
serum IgG antibodies against agents
infecting the genito-urinary tract. One study
reported an increased risk for prostate
cancer among men who showed serological
evidence of syphilis (OR=1.8; 95% CI, 1.03.5) (Hayes et al., 2000), while studies
investigating possible serological links
between Chlamydia trachomatis and
prostate cancer reported null results (Dillner
et al., 1998). Five studies investigating
possible associations between human
papilloma virus (HPV) and prostate cancer
21
have found variable results, ranging from no
association to statistically significantly higher
risks for HPV-seropositive men (reviewed in
(Palapattu et al., 2004)).
The meta-analysis by Taylor et al. also
examined the associations between HPV
infection and prostate cancer risk detected in
ten studies using either serological or PCRbased evidence of HPV infections. The
results showed an OR of 1.39 (95% CI,
1.13-1.71). Notably, while HPV is known to
be an oncogenic virus, its influence on
prostate carcinogenesis may be independent
of inflammation.
Detection of infectious agents in prostate tissue:
Several studies have investigated the
presence of infectious agents in the prostate
tissue. Various viruses and bacteria have
been found, but the results have been
inconsistent, possibly due to methodological
differences (such as differences in the tissue
handling and detection methods), or
possible contamination from agents in areas
close to the prostate, e.g., the urethra. It is
also worth noting that STIs detected in the
prostate cancer tissues could have been
acquired
after
the
initiation
of
carcinogenesis. Furthermore, the failure to
detect infectious agents in the prostate tissue
does not necessarily mean that such agents
play no role in prostate carcinogenesis, as
some may be cleared after causing damage
(Platz et al., 2004). Human papilloma viruses,
human herpes virus-8, Herpes simplex virus2, cytomegalovirus and Epstein-Barr virus
are some of the agents that have been
found, see the review by Palapattu et al. for
further information (Palapattu et al., 2004).
In 2005, Cohen and co-workers
performed an exploratory study to detect the
presence of bacterial agents in prostate
tissue from patients with prostate cancer
(Cohen et al., 2005). They reported a
predominant presence of the gram-positive
22
Prostate Cancer and Inflammatory Genes
bacterium Propionibacterium acnes, which
moreover showed a positive association with
prostatic inflammation. P. acnes is a slowgrowing microbe that is known to be a
potent stimulant of the immune system, and
it is highly resistant to killing and
degradation by human neutrophils and
monocytes, a characteristic which allows it
to establish long-term low-grade infections
that may persist for years to decades. A
independent study using
PCR-based
technique, found P.acnes twice as common
in prostate tissue from patients with benign
prostatic hyperplasia that later developed
cancer compared to those that did not
(personal communication, Oleg Alexyev).
Genetics
As described above, multiple pieces of
evidence have been accumulated supporting
the view that genetic factors play a role in
prostate
cancer
susceptibility
and
pathogenesis. Unlike some carcinomas such
as those of the colon (Klump et al., 2004)
and pancreas cancer (Jaffee et al., 2002),
where relatively common somatic genetic
alterations are observed (e.g. mutations in
p53 and K-ras), gene mutations in prostate
cancer display a great deal of heterogeneity,
not only from case to case, but also from
lesion to lesion in a single cases. The
heterogeneity of genomic defects in prostate
cancer suggests that prostate cancers may
arise as a consequence of either chronic or
prolonged exposure to genome-damaging
stresses, defective maintenance of genome
integrity, or a combination of both, and thus
no single dominant molecular pathway is
responsible for prostate carcinogenesis (De
Marzo et al., 2004).
To date, a substantial number of
germline prostate cancer susceptibility genes
as well as somatic genome alterations have
been identified, some of which indicate that
inflammation may be an important mediator
in the development of prostate cancer. The
following sections summarise some of the
germline and somatic genomic changes
suggesting that infection or inflammation of
the prostate contributes to the development
of prostate cancer.
GSTP1
GSTPs represent a superfamily of enzymes
that play an important role in detoxification
by catalyzing the conjugation of many
hydrophobic and electrophilic compounds
with reduced glutathione. GSTP1 appears to
act as a “caretaker” gene, defending prostate
cells against genome damage mediated by
carcinogens. In the normal prostate
epithelium,
GSTP1
is
expressed
predominantly in basal cells, but not in the
columnar secretory cells, although the
enzyme may be induced in columnar
epithelial cells that are subjected to genomedamaging stresses. An elevated level of
GSTP1 is a histological characteristic of
proliferative inflammatory atrophy, strongly
indicating that a stress-induced response has
been induced in these cells (De Marzo et al.,
1999). GSTP1 can undergo somatic
alterations, especially hypermethylation of
CpG islands of regulatory sequences at the
GSTP1 locus, which prevents the
transcription
of
GSTP1.
Abnormal
hypermethylation of CpG islands of
regulatory sequences at the GSTP1 locus is
associated with decreased transcriptional
activity. Such hypermethylation occurs in
many types of human cancers (Jones et al.,
2002), it has been reported to be the most
common somatic genome alteration in
prostate cancer and it represents an early
event in neoplastic transformation. The
hypermethylation occurs in approximately
70% of PIN lesions and in over 90% of
Prostate Cancer and Inflammatory Genes
prostate carcinomas, but not in normal
prostate tissue or benign prostatic
hyperplasia (Jerónimo et al., 2001; Lin et al.,
2001).
Recent published data have suggested
that heterocyclic amine carcinogens present
in well-done meat as well as oxidants may be
detoxified by GSTP1 (Nelson et al., 2001).
Experimental studies in which LNCaP cells
(that do not normally express GSTP1) have
been modified to express GSTP1, show that
cells expressing GSTP1 more readily
withstand DNA damage when exposed to
promutagenic substances and oxidative
stress, compared to unmodified LNCaP cells
(Nelson et al., 2001, 2002). However, in
response to oxidant stress, unmodified
LNCaP cells survive better than LNCaP
cancer cells that have been modified to
express high levels of GSTP1. Thus, for
LNCaP prostate cancer cells, loss of the
GSTP1 function appears to increase genome
damage and decrease cell mortality rates
following exposure to oxidants. This finding
of tolerance to oxidative genomic damage in
the absence of functional GSTP1 may be a
clue regarding the function of somatic
GSTP1 inactivation in prostate cancer
progression (Palapattu et al., 2004).
MSR1
In 2001, Xu et al. published a study with
suggestive linkage to chromosome 8p22-23
among 159 families (Xu et al., 2001). Further
mutation screening studies of hereditary
prostate cancer families identified a number
of mutations in the macrophage scavenger
receptor 1 gene (MSR1) that co-segregate
with prostate cancer (Xu et al., 2002).
MSR1 is a large 11-exon gene located on
chromosome 8p22, an area that is frequently
lost in prostate cancer (Matsumoto et al.,
1990). It encodes a Class A scavenger
23
receptor (MSR1, also known as SR-A, an
important component of the innate immune
system), which occurs in three different
isoforms (I, II, and III) generated by
alternative splicing of a single 11-exon
mRNA. Isoforms I and II are functional
while isoform III is a non-functional protein
acting as a dominant negative isoform by
blocking modified low-density lipoprotein
uptake (Gough et al., 1998). The functional
MSR1 protein is a trimeric transmembrane
molecule composed of three identical
protein chains. It has six distinct structural
domains: the amino-terminal cytoplasmic
domain, a transmembrane domain, a spacer
domain, an α-helical coiled coil domain, a
collagenous domain, and the scavenger
receptor, cysteine-rich, carboxy-terminal
domain (Kodama et al., 1990). MSR1 shows
unusually broad ligand-binding properties. It
binds a diverse array of macromolecules
including bacterial lipopolysaccharide and
lipoteiochic acid, and both oxidized highdensity lipoprotein and low-density
lipoprotein in the serum (Platt et al., 2001).
The function of the receptor in vivo is still
not entirely clear, but studies have suggested
that these receptors may play a role in
macrophage–host
cell
interactions,
macrophage
adhesion
to
substrata,
endocytosis of ligands, and the recognition
and clearance of foreign pathogenic
substances and damaged or apoptotic cells
(Platt et al., 2001).
The MSR1 receptor is mainly expressed
in macrophages and related cells, and its
expression is regulated by a number of
factors including cytokines such as M-CSF,
IFNg, and TNFα (Shirai et al., 1999). Mice
that are deficient in MSR1 are highly
susceptible to infection by Listeria
monocytogenes, Staphylococcus aureus, and herpes
simplex type 1 (Thomas et al., 2000; Ishiguro
et al., 2001), which may be relevant in
24
Prostate Cancer and Inflammatory Genes
prostate cancer susceptibility, since an
infectious aetiology of prostate cancer has
been proposed. Moreover, areas within the
prostate that show evidence of inflammation
are often populated by macrophages that
express MSR1 (Nelson et al., 2003).
Several germ-line mutations in MSR1
have been linked to prostate cancer in some
families with hereditary prostate cancer. In
the mutation screening study by Xu et al., six
rare missense and one nonsense mutation
(R293X) were detected in MSR1 (Xu et al.,
2002). A family-based linkage and
association test indicated that these
mutations cosegregate with prostate cancer
(P=0.0007). Of these mutations, the
nonsense mutation R293X was detected in
approximately 2.5% of men with non-HPC
compared to a 0.4% of unaffected men
(P=0.05). In a follow-up study of 301 nonHPC cases and 250 controls, by the same
group, five common variants within MSR1
were found, with statistically significant
differences in allele and haplotype
frequencies (Xu et al., 2003).
A number of other independent studies
have evaluated the association between
prostate cancer and the MSR1 gene, and the
generated data have created doubt
concerning the role of MSR1 sequence
variants in prostate cancer susceptibility
(Miller et al., 2003; Seppälä et al., 2003; Wang
et al., 2003).
RNASEL
RNASEL is a constitutively expressed latent
endoribonuclease that mediates the antiviral
and proapoptotic activities of the interferoninducible 2-5A system. Once activated by
interferon, cells containing a functional
RNASEL gene produce an enzyme that
degrades single-stranded RNA, leading to
apoptosis (Silverman, 2003). Defects in the
RNASEL gene have been shown to result
in reduced immunity to viral infections and
cancer (Hassel et al., 1993).
A genome-wide scan for linkage in
prostate cancer families found evidence for a
prostate cancer susceptibility locus on
chromosome 1q24-25 (Smith et al., 1996). In
2002, Cartpen et al. identified RNASEL as a
candidate gene for the HPC1 locus through
a positional cloning and candidate approach.
A truncating mutation (E265X) and an
initiation codon mutation (M1I) were
reported to co-segregate within two specific
prostate cancer families (Carpten et al.,
2002). In addition to the rare mutations, a
number of relatively common RNASEL
variants have been associated with prostate
cancer risk. There is some confirmatory
evidence for the association between
variants of RNASEL and prostate cancer
risk (Rennert et al., 2002), but other studies
have showed no association (Wang et al.,
2002; Kotar et al., 2003; Wiklund et al., 2004).
In summary, the role of RNASEL in the
pathogenesis is still very unclear, due to
inconsistencies in the association studies.
However, as Palapattu et el. mention in a
review from 2004, it is tempting to speculate
that genetic variants of the RNASEL gene
increase the risk for prostate cancer only in
the presence of some environmental factor
(e.g. viral infection) that may vary between
different study populations (Palapattu et al.,
2004).
Cytokines in prostatic inflammation
and prostate cancer
As described above, cytokines are a diverse
group of intracellular signalling peptides and
glycoproteins that regulate local and
systemic inflammatory and immune
Prostate Cancer and Inflammatory Genes
responses. Several pro- and antiinflammatory cytokines have been identified
in patients with prostatic inflammation and
prostate cancer, and their roles have been
studied. In 1998, Alexander et al. measured
the levels of the pro-inflammatory cytokines
TNFα and IL-1β in the semen of men with
chronic prostatitis and compared them with
levels in normal men (Alexander et al., 1998).
They found that men with prostatitis had
higher mean levels of TNFα and IL-1β than
normal men, as would be expected in an
ongoing inflammatory response. These
results were confirmed by Nadler and coworkers, who showed that IL-1β was
measurable in ~90% of patients with type
III and type IV prostatitis, but rarely
detectable in controls (Nadler et al., 2000).
The level of TNFα could be measured in
both cases and controls, but levels were
significantly elevated in patients with type
III and type IV prostatitis.
Genetic polymorphisms that alter
cytokine gene expression or protein function
could have an important impact on prostatic
inflammation and the further development
of prostate cancer. A polymorphism in the
promoter of the anti-inflammatory cytokine
IL-10 has been identified; and the IL-10 1082 AA genotype is associated with low
IL-10 production. In a study by Shoskes et
al., patients with chronic prostatitis were
found to have higher proportions of the
allele associated with low IL-10 production
compared to controls, indicating a proinflammatory state in those patients
(reviewed in Pontari M and Ruggieri M
(Pontari et al., 2004)).
Only a few studies have examined the
association between prostate cancer risk and
sequence variants in cytokine genes such as
TNFα, IL-8 and IL-10 (McCarron et al.,
2002). In the cited study, cytokine sequence
variants (IL-1β-511, IL-8-251, IL-10-1082,
25
TNFα-308, and VEGF-1154) were analyzed
among 247 prostate cancer cases and 263
controls. The results showed that IL-8-251
TT and VEGF-1154 AA genotypes were
lower among patients compared with
controls (OR=0.66; 95%, CI 0.44-0.99 and
OR=0.45; 95% CI, 0.24-0.86, respectively),
whereas the IL-10-1082 AA genotype was
significantly increased in patients compared
with controls (OR=1.78; 95% CI, 1.14-2.77).
Although the influence of cytokine
polymorphism on prostatic inflammation
and prostate cancer is likely to be complex,
the few relevant studies published to date
indicate that SNPs in cytokine genes may
have a significant impact on disease
development. These results also highlight
the critical need to further elucidate the
impact of cytokines and their sequence
variants on prostate cancer susceptibility.
MIC-1
The type β transforming growth factor
(TGF-β) superfamily has more than 40
members, which are involved in regulation
of many cellular functions and biological
processes, including proliferation, apoptosis,
extracellular matrix secretion and adhesion,
terminal differentiation, and development
(Derynck et al., 1997).
To identify novel molecules that
participate in the local inflammatory
response, Bootcov et al. subtracted cDNA
library enriched for genes associated with
macrophage activation. The following
screening resulted in the identification of a
novel transforming growth factor β
superfamily
cytokine,
designated
macrophage inhibitory cytokine-1 (MIC-1).
The MIC-1 gene, located on 19p13, is about
6 kb long and is composed of two exons.
The protein is synthesized as a 308 amino
26
Prostate Cancer and Inflammatory Genes
acid long precursor molecule. The
propeptide is separated from the mature
protein by a furin-like protease acting on a
conserved cleavage site at amino acids 193196. Following processing, the mature
protein of 112-aa is secreted as a disulfidelinked homodimer. The mature protein
subunits contain a conserved pattern of
seven cysteine residues, which is a hallmark
of the TGF-β superfamily (Bootcov et al.,
1997). Since MIC-1 is a secretory protein it
can function in cells secreting it as well as in
their neighbouring cells (i.e. in both
autocrine and paracrine fashions). It has
been reported that MIC-1 activity (like that
of TGF-β), requires an intact signalling
pathway mediated by type I and type II
TGF-β receptors, as well as receptor
activated Smad4 (Tan et al., 2000).
The MIC-1 gene is also known by various
names, including growth/differentiation
factor-15 (GDF-15) (Böttner et al., 1999),
placental bone morphogenetic protein
(PLAB) (Hromas et al., 1997; Thomas et al.,
2001), prostate-derived factor (PDF)
(Paralkar et al., 1998), and the non-steroidal
anti-inflammatory
drug-activated
gene
(NAG-1). Like many TGF-β superfamily
cytokines, MIC-1 is expressed very widely,
but under resting conditions the placenta is
the only tissue expressing large amounts of
MIC-1 (Fairlie et al., 1999). Small amounts of
MIC-1 mRNA have been detected in
epithelial cells in the kidney, pancreas, colon,
and prostate as well as macrophages.
However, in cases of inflammation, injury or
malignancy,
MIC-1
expression
is
dramatically increased.
Shortly after cloning of the MIC-1 gene,
a polymorphism was identified, resulting
from alteration of the basic amino acid
histidine (H), to the acidic amino acid
aspartic acid (D), located at position 6 of the
mature MIC-1 protein, next to the cysteine
at position 7 that has been indicated to be
important for the stability of this protein
(Fairlie et al., 2001). Due to the differences in
the properties of these two amino acids, this
change may alter the stability of the protein
and thus the function of MIC-1. Some
studies have examined the possible
relationship between MIC-1 genotypes and
different diseases, including cancer, with
variable results. A study by Brown et al.
indicated that the presence of the HH
genotype of MIC-1 was associated with a
decreased risk of metastasis of colorectal
caner at presentation of the disease, but it
should be noted that the numbers of
patients in the investigated groups were
relatively small (Brown et al., 2003).
It has been shown that MIC-1 has
diverse biological functions in distinct
cellular contexts. A number of direct and
indirect lines of evidence suggest there is a
link between MIC-1 and cancer. The
promoter region of this gene contains two
p53 target sites; and a number of studies
have demonstrated that MIC-1 is strongly
induced by transactivation of p53 (Kannan et
al., 2000; Li et al., 2000; Tan et al., 2000). A
well-studied function of p53 is its activity as
a transcription factor, regulating genes
whose products are involved in a variety of
cellular processes including growth arrest,
apoptosis, senescence and genome stability
(Ko et al., 1996). Loss-of-function of DNA
target recognition by mutated p53 is an
important step in cell transformation, and
over 50% of human cancers contain various
inactivated p53 mutants (Hollstein et al.,
1994). This indicates that some of the genes
that are transactivated by p53, including
MIC-1, may play an important role in the
development of cancers. Furthermore, two
studies by Tan et al. (Tan et al., 2000) and Li
et al. (Li et al., 2000) both show that MIC-1
inhibits tumour cell growth through the
Prostate Cancer and Inflammatory Genes
TGF-β signalling pathway following
activation by p53.
More direct evidence for links between
MIC-1 and cancer, have been obtained from
serial analysis of gene expression, which has
indicated that MIC-1 is highly expressed in
both prostate cancer and benign prostatic
hyperplasia tissue compared to normal
prostate tissue, with a higher expression in
cancer tissue than benign prostatic
hyperplasia tissue (Welsh et al., 2001, 2003;
Nakamura et al., 2003). A recently published
exploratory proteomic analysis of prostate
cancer tissue and benign prostatic
hyperplasia tissue originating from the same
prostate tissue block supports this
expression pattern (Hood et al., 2005).
Elevated MIC-1 expression is also coupled
with a number of other cancers, including
colon, breast, and pancreas cancers
(Buckhaults et al., 2001; Koopmann et al.,
2004; Wollmann et al., 2005).
Analyses of serum samples of patients
have indicated that there is a relationship
between elevated serum MIC-1 and the
metastatic progression of colorectal, prostate
and breast (Welsh et al., 2003) (Brown et al.,
2003). MIC-1 levels are also elevated in the
serum of patients with pancreatic ductal
cancer (Koopmann et al., 2004). These
findings have led to the suggestion that
measurement of MIC-1 levels may be useful
for the diagnosis and surveillance of cancer.
Serum MIC-1 levels can be markedly
elevated in metastatic cancer and seem to
parallel the stage and extent of disease,
particularly in colorectal cancer (Brown et al.,
2003). Furthermore, despite the relationship
between elevated serum MIC-1 levels and
metastatic progression, a number of studies
have shown MIC-1 to have an
antitumorigenic function, since it induces
apoptosis and inhibits proliferation of
several tumour cell lines. Liu et al.
27
demonstrated that overexpression of MIC-1
in prostate cancer cell lines reduces cell
adhesion and induces apoptosis (Liu et al.,
2003). These findings are supported by
observations of increased rates of apoptotic
death in mammary carcinoma cells where
MIC-1 is overexpressed (Li et al., 2000;
Graichen et al., 2002). Moreover, Baek et al.
showed that NSAIDs that inhibit tumour
development also induce colon cancer cells
to undergo apoptosis, mediated by
autocrine/paracrine induction of MIC-1
(Baek et al., 2001).
Apart from playing an important role in
inhibiting tumour progression, MIC-1 has
been shown to exert anti-inflammatory
effects by inhibiting the late phase of
macrophage activation (Bootcov et al., 1997).
Since MIC-1 is a potent p53 target gene and
has anti-inflammatory activity, it has been
suggested that increased p53 expression in
inflammatory tissues may reflect a tissue
defence mechanism that triggers a signalling
pathway, leading to activation of MIC-1 and
ultimately inhibition of inflammation (Tan et
al., 2000). Understanding of the biological
function of MIC-1 in the prostate may help
delineate its role in prostatic physiology and
pathobiology.
IL-1RN
The interleukin-1 (IL-1) family consists of
three different cytokines; the two
proinflammatory cytkines IL-1α and IL-1β,
and the IL-1 inhibitor, IL- 1 receptor
antagonist (IL-1RN) (Dinarello, 1994). The
IL-1RN gene is located on the long arm of
human chromosome 2 at band 2q14.2 in
close proximity to the genes coding for IL1α and IL-1β, distributed over 430 kb
(Steinkasserer et al., 1992). IL-1α, IL-1β and
IL-1RN are all produced in a wide variety of
28
Prostate Cancer and Inflammatory Genes
cells - including monocytes, macrophages,
neutrophils and epithelial cells of many
organs (Arend et al., 1998) – and they bind
to the same IL-1 receptors. IL-1α and IL-1β
are pro-inflammatory cytokines, and their
binding to the receptors initiates a cascade
of events leading to the recruitment and
activation of macrophages and neutrophils,
vascular dilation and fever, and a potent proinflammatory immune response (Dinarello,
1988). When the anti-inflammatory cytokine
IL-1RN binds to the same receptors the
activity of IL-1α/β is blocked. Consequently,
the biological function of IL-1α and IL-1β
cytokines is neutralized in both physiological
and pathophysiological immune and
inflammatory responses. The relative levels
of IL-1RN, IL-1α and IL-1β at an
inflammatory site determine whether a proinflammatory response will be initiated and
persist or will be terminated (McIntyre et al.,
1991). Typically, the level of IL-1RN
increases in the later stages of inflammatory
events, thereby promoting their termination
and limiting the risks that inflammation will
become chronic and cause damage to
healthy cells (Granowitz et al., 1991). The
central role of the IL-1 system is protection
against many different types of lesion,
ranging from microbial colonisation to
infection and malignant transformation
(Witkin et al., 2002).
In the second intron of IL1-RN, there is
a variable number of tandem repeat
(VNTR), consisting of two to six copies of a
86-bp sequence (Tarlow et al., 1993). The
frequency of the individual alleles varies
among different ethnic and geographical
populations, but allele 1 (containing four
repeats) is always the most common allele,
while the less common allele 2 (containing
two repeats) has been associated with a
variety of human diseases. Several studies
have shown that people with allele 2 of the
VNTR have a more prolonged and severe
pro-inflammatory immune response than
usual, and that carriers of this genotype
more efficiently combat microbial infection
or colonization (Hu et al., 2005). The
majority of studies relating IL-1RN gene
polymorphisms to disease have focused on
patients with autoimmune diseases or
disorders
associated
with
chronic
inflammation, including inflammatory bowel
disease, psoriasis, lichen sclerosus, and
multiple sclerosis (Witkin et al., 2002). A
number of studies have evaluated the
presence of the VNTR in malignant
diseases, and the results have been
conflicting rather than conclusive. Studies
from Caucasian populations have shown
that homozygous carriage of allele 2 is
associated with an increased risk of gastric
cancer (El-Omar et al., 2000; Machado et al.,
2001; Glas et al., 2004), however this
association was not replicated in Asian
populations (Wu et al., 2003; Zeng et al.,
2003; Chang et al., 2005). In addition to
gastric cancer, a few studies have evaluated
possible links between VNTR and risks of
other kinds of cancers. Recently, Sehouli et
al. found in a case-control study of 162
women with ovarian cancer and 121
controls
that
patients
who
were
heterozygous for allele 2 had a significantly
higher risk for ovarian cancer (Sehouli et al.,
2003).
Although the role of genetic variation in
IL-1RN has been investigated in many types
of cancers, the role of IL-1RN
polymorphisms
in
prostate
cancer
pathogenesis has not been examined.
Prostate Cancer and Inflammatory Genes
29
Aims
The specific aims of the work underlying this thesis were:
ü To investigate whether mutations in
the Macrophage Scavenger Receptor 1
gene influence the risk of prostate
cancer in both Swedish families
with hereditary prostate cancer and
in a cohort of unselected prostate
cancer.
ü To evaluate the possible role of
genetic sequence variants in the
Macrophage Inhibitory Cytokine-1 gene
on prostate cancer risk in a Swedish
population.
ü To evaluate the possible role of
genetic sequence variants in the
Interleukin-1 Receptor Antagonist gene
on prostate cancer risk in a Swedish
population.
ü To study the serum levels of MIC-1
in relation to prostate cancer and
MIC-1 genotypes and whether MIC1 levels are associated with prostate
cancer risk.
30
Prostate Cancer and Inflammatory Genes
Material and methods
Hereditary prostate cancer families used for mutation screening
(Study I)
Since 1995 our research group has been
identifying (mainly on the basis of referrals
from urologists and oncologists) and
collecting information on Swedish families
with a history of HPC. In the analysis of the
Macrophage Scavenger Receptor I gene we
examined material from 83 of these families.
The 83 families included in this study
had an average of 4.5 affected men/family
and the mean age of diagnosis was 67 years.
Nearly two-thirds of the cases were
diagnosed before PSA measurement was
introduced as a diagnostic tool in Sweden.
The majority of the cases (79%) had clinical
symptoms at diagnosis and 60% of the cases
were diagnosed with advanced or metastatic
disease.
Patients with prostate cancer and controls (Studies I, II, III, IV)
The Northern Sweden Health and
Disease Cohort
In study I, we used a study population from
Northern Sweden Health and Disease
Cohort (NSHDC) to test for associations
between eight selected sequence variants and
prostate cancer risk. The design of the
NSHDC has been presented in detail before
(Stattin et al., 2000). For this study 215
incident cases of prostate cancer were
identified by cross-reference to cancer and
all-cause mortality registries. Data on patient
and tumour characteristics were obtained
through medical records. Two control
subjects were selected for each case subject
from all members who were alive and free
of cancer at the time of diagnosis of the case
in each subcohort, and matched the index
case subject in terms of sex, age (± 6
months), and date (± 2 months) at
recruitment. Controls were randomly
selected from each group of eligible subjects
if more than two subjects matched the
identified case. If fewer suitable control
subjects were found by this procedure, less
than two control subjects was accepted. We
identified 425 eligible control subjects, with
an average age of 66 years at the time of
recruitment in this study. All participants
were residents of the county of
Västerbotten.
CAPS
For the association analyses in Studies II,
III, IV we utilized men included in the
population-based CAPS (CAncer of the
Prostate in Sweden) case-control study. The
Prostate Cancer and Inflammatory Genes
case participants, diagnosed for prostate
cancer between January 2001 and September
2002, were recruited from four of the six
regional cancer registries that cover the
entire population of Sweden. Each of these
registries serves one health care region
(Northern, Central, Stockholm, and South
Eastern) and they collectively encompass
approximately 6 million inhabitants (67% of
Sweden’s population). The source-persontime was divided into two age–specific study
groups. The first group included men 35-65
years of age, living in all regions mentioned
above. The second study base included men
66-79 years of age at the time of the study
entry, living only in the central and northern
region. Swedish law requires both the
attending physician and pathologist to report
newly diagnosed cancer cases to the cancer
registries. Therefore, the registries include
records of almost 100% of all cancers
diagnosed in Sweden. The cases were linked
to the National Prostate Cancer Registry and
clinical information on aspects such as TNM
(tumour-node-metastasis) stage, Gleason
sum, PSA level at the time of diagnosis,
methods of diagnosis and primary treatment
were obtained for 95.3% of the cases. The
cases were then classified as either
Localised (T1-2, N0/NX, M0/MX, Grade
I-II/Gleason sum 2-7, and PSA<100) or
Advanced (having or being prone to
progressive disease; T3/4 or N+ or M+ or
Grade III or Gleason sum 8-10 or
PSA>100). For cases where at least one
reported family member with prostate
cancer a more detailed family history of
prostate cancer was obtained through
31
additional questionnaires and record linkage
to the Swedish Cancer Registry or medical
records. The families were subsequently
classified as hereditary prostate cancer
families, where three or more relatives had
prostate cancer (52 cases), or familial
prostate cancer families: where two relatives
had prostate cancer (130 cases). In total
1961 prostate cancer cases were invited for
participation in the CAPS study, of those
1444 (73.6%) approved to participate by
donating a blood sample and answering the
questionnaire. At the time of the studies in
this thesis DNA was available for 1383 of
the cases who accepted to participate.
Control subjects were randomly selected
from the continuously updated Swedish
Population Registry, frequency matched
according to the expected age distribution
(within five years), geographic origin of the
cases and sex. Of the 1697 randomly
selected controls that were invited for
participation in the study, 866 (52.0%)
accepted to participate with blood donation
and questionnaire. At the time of the studies
in this thesis DNA was available for 780 of
the controls that approved to participate.
Mean age (age at diagnosis for case patients
and age at inclusion for control subjects) for
the cases and controls were 66.6 and 67.9
years, respectively. Blood (4 x 10 ml) was
collected from all cases and controls and
separated into serum, plasma, and buffy
coat. A detailed description of the study
sample is presented in Study III. Clinical
characteristics of the prostate cancer cases in
the study are summarized in Table 1.
Prostate Cancer and Inflammatory Genes
32
Table 1. Clinical characteristics of the 1383 cases with prostate cancer included in
the CAPS study.
Age
45-65 (n=704)
Number (%)
66-80 (n=679)
Number (%)
T-stage
T0
T1
T2
T3
T4
TX
3
259
234
144
20
44
N-stage
N0
N1
NX
157 (22.3)
26 (3.7)
521 (74.0)
66 (9.7)
19 (2.8)
594 (87.5)
M-stage
M0
M1
MX
328 (46.6)
67 (9.5)
309 (43.9)
250 (3.8)
64 (9.4)
365 (53.8)
Gleason score
<=4
5
6
7
8
9
10
Missing
29
79
236
177
53
40
7
83
(4.1)
(11.2)
(33.5)
(25.1)
(7.5)
(5.7)
(1.0)
(11.8)
24
63
185
188
70
37
3
109
(3.5)
(9.3)
(27.2)
(27.7)
(10.3)
(5.4)
(0.4)
(16.1)
Tumour grade
GI
GII
GIII
GX
35
154
70
445
(5.0)
(21.9)
(9.9)
(63.2)
34
151
72
422
(5.0)
(22.2)
(10.6)
(62.2)
PSA levels
<4
4-9.99
10-19.99
20-49.99
50-99.99
>=100
Missing
49
264
139
92
49
64
47
(7.0)
(37.5)
(19.7)
(13.1)
(7.0)
(9.1)
(6.7)
26
169
152
128
77
87
40
(3.8)
(24.9)
(22.4)
(18.9)
(11.3)
(12.8)
(5.9)
(0.4)
(36.8)
(33.2)
(20.5)
(2.8)
(6.3)
3
200
208
207
28
33
(0.4)
(29.5)
(30.6)
(30.5)
(4.1)
(4.9)
Prostate Cancer and Inflammatory Genes
33
Genetic analysis
Genomic PCR (Studies I and II)
For the mutation screening in Study I and
genotyping of the VNTR in IL1-RN (Study
II), intron complementary primer pairs that
could amplify all exons, exon-intron
junctions, the promoter region, and 3´-UTR
in the MSR1 and the VNTR in IL-1RN were
used for amplification from genomic DNA.
Mutation screening (Study I)
The analysis of the MSR-1 gene was started
by screening the entire coding sequence including exon-intron junctions, promoter
regions and 5´- and 3´-untranslated regions for mutations by Temperature Modulated
Heteroduplex Analysis (TMHA) using High
Performance
Liquid
Chromatography
(HPLC) and a DNA-binding column
(DNAsepTM). This technique is based on the
principle that heteroduplexes formed
between mutated DNA and normal DNA
molecules can be distinguished from
homoduplexes consisting entirely of normal
DNA molecules, by a differences in their
elution profiles at a given optimized
temperature. The experimental procedure
includes two main steps:
First, the nucleic acids of interest (for
example PCR-products) are denatured at
95°C for 5 minutes, then gradually
reannealed by reducing the temperature to
20°C over 50 minutes, a process that enables
formation
of
mismatched
DNA
(heteroduplexes).
The
samples
are
subsequently bound to the column using
trietylammonium acetate (TEAA). The
binding strength of nucleic acids to the
column is proportional to the number of ion
pairs formed between the negatively charged
nucleic acids and the positively charged
TEAA ions absorbed to the stationary
phase.
The second step is elution of the nucleic
acids bound to the column using a linear
gradient of Acetonitrile, which weakens the
bonding between the column and TEAA by
competive hydrophobic interactions and
thus releases the nucleic acids. The helical
nature of the duplex is disrupted in the
heteroduplexes due to the presence of
incorrect base pairing at the site of the
mutation, which reduces the number of ionpairing bonds with the column and thus
results in the heteroduplex eluting earlier (at
a lower acetonitrile concentration) than the
homoduplex (Figure 2). This approach to
detecting heteroduplexes is most suitable
when screening for rare mutations and
mutations, for which homozygotes of the
rare allele are unlikely to be present. Since
this was our aim, we did not modify the
method to enable common polymorphisms
(for which homozygotes of both alleles are
likely to present in the study population) to
be detected. A detailed description of the
method is presented elsewhere (Xiao et al.,
2001).
The sequence variants identified using
the HPLC analyses were confirmed by direct
sequencing. The amplicon of interest was
amplified from corresponding genomic
DNA. PCR products were purified and then
sequenced with a dye terminator kit. To
ensure high sequence quality, all fragments
were sequenced from both directions.
Primers used for amplification of the PCR
product were used as sequencing primers.
Prostate Cancer and Inflammatory Genes
34
Wild type
Wild
type
Homoduplexes
Mutant
Homoduplexes
heat
cool
heat
cool
AT
Heteroduplexes
A C G T
AT GC
AT
A T GC
10
Intensity (mV)
Intensity (mV)
3
9
8
7
6
5
4
3
2
1
2
1
0
0
2
4
Retention
time
(min)6
8
0
-0,2
0,8
Retention time (min)
1,8
2,8
3,8
4,8
5,8
6,8
Figure 2. Schematic illustration over homo/heteroduplex formation and the following
elution profiles.
Common sequence variants of the
MSR-1 gene (Study I)
Five common sequence variants identified
of the MSR-1 gene together with three rare
mutations were further evaluated for
possible association with prostate cancer
risk. For the genotyping of the five common
SNPs (PRO3, INDEL1, IVS5-57, P275A,
and INDEL7) and the rare nonsense
mutation (R293X), the MassARRAY system
was used (SEQUENOM, Inc. Valencia, CA).
PCR reactions were performed in a total
volume of 5 µl with 10 ng of genomic
DNA, 2.5 mM of MgCl2, 0.1 U of
HotStarTaq
polymerase,
(QIAGEN
Inc.Valencia, CA), 200 µM of each dNTP
and 200 nM of each primer. The PCR
conditions were as follows: 95°C for 15
minutes followed by 45 cycles of 95°C for
20 seconds, 50°C for 30 seconds and 72°C
for 1 minute with a final extension of 72°C
for 3 minutes. The hME reactions were
performed in a total volume of 9 µl with 50
µM of each d/ddNTP, 0.063 U/µl of
Thermo
Sequenase
(both
from
SEQUENOM, Inc.) and 600 nM of
extension primer. The cycling conditions
were 94°C for 2 minutes followed by 55
cycles of 94°C for 5 seconds, 52°C for 5
seconds and 72°C for 5 seconds. After
cleaning up the hME reaction products with
SpectroCLEAN
the
products
were
transferred to a SpectroCHIP using
SpectroPOINT, and then scanned through
SepctroREADER. Genotyping was done
using
SpectroTYPER
(all
from
SEQUENOM, Inc.).
In addition to the MassARRAY
genotyping system we utilized HPLC
analyses (described above) to genotype the
two splice site mutations located adjacent to
exon 4. Since both were rare among the
HPC families and we did not expect any
homozygotes of the rare allele HPLC was a
suitable method.
Prostate Cancer and Inflammatory Genes
Association of MIC-1 sequence
variants and prostate cancer (Study
III)
To fully elucidate possible associations
between prostate cancer risk and SNPs in
the inflammatory gene MIC-1, the following
approach was used. First, the target region
for selection of SNPs was defined as 2 kb of
the promoter plus all exons, introns, and the
3’UTR. The SNP information for this region
was obtained from public databases (NCBI
dbSNP, and SNPer) or from data obtained
by re-sequencing samples from 24 control
subjects when detailed SNP information was
not publicly available. Two criteria were use
to select SNPs for further analyses:
1) the minor allele frequency had to be
at least 5%, at a resolution of 1 SNP
per kb of DNA across the genome
region of MIC-1. The density of the
selected SNPs was chosen to ensure
that they sufficiently reflected the
haplotype block pattern throughout
the genome (Wall et al., 2003).
2) all SNPs that lead to an amino acid
substitution, since such changes are
more likely to have an effect on
prostate cancer susceptibility and
pathogenesis.
From the public database, six SNPs
(Exon1+25,
Exon1+142,
IVS1+904,
IVS1+1809, Exon2+2423, 3’-UTR+2816)
located in the exons, introns and 3’UTR
were selected. In addition, two SNPs
(MIC1-1576, and MIC1-893) located in the
promoter region that fulfilled the criteria
were selected by the re-sequencing samples
from 24 randomly selected CAPS controls
(Figure 3).
DNA from 94 control subjects selected
at random from CAPS was genotyped with
respect to the eight chosen SNPs using a 5’
35
nuclease assay with TaqMan MGB probes.
The SNP genotyping assays were designed
using Applied Biosystems’ Assay-by-Design
service (Applied Biosystems Inc., Foster
City, CA). All reactions were performed in
25 µl mixtures consisting of 10 ng genomic
DNA, 900 nM of each primer, 200 nM of
each probe and 12.5 µl of TaqMan universal
master-mix. PCR cycling conditions were as
follows, 50°C for 2 min, 95°C for 10 min
followed by 40 cycles of 92°C for 15 sec and
60°C for 1 min. The samples were analyzed
using an ABI 7700 sequence detection
system. For quality control, two CEPH
DNA samples and additional water blanks
were included on each 96-well plate.
Following the first genotyping, the SNP
MIC1-1576 was excluded from further
analysis since it deviated significantly from
HWE (p=0.003). Haplotype frequencies for
the remaining seven SNPs were estimated
using the statistical method proposed by
Stephens et al. (2001), as implemented in the
computer
program
PHASE
(http://www.stats.ox.ac.uk/mathgen/softwa
re.html). A subset of “Haplotype Tagging
SNPs” that could uniquely represent at least
95% of the haplotype information observed
among the 94 control individuals was
selected using the computer software
htSNP2
(http://wwwgene.cimr.cam.ac.uk/clayton/software/stata
). Four SNPs (Exon1 +25, Exon1 +142,
IVS1 +1809, and Exon2 +2423 (H6D)) that
captured 98.6% of the haplotype variation
among the 94 controls were selected as
haplotype tagging SNPs. Each of these four
SNPs was in HWE among both the cases
and controls. These four htSNPs were
genotyped for all 1383 cases and 780
controls from the CAPS study. The
genotyping was performed using the
MassARRAY system (SEQUENOM Inc.,
Valencia, CA), described in detail above.
36
Prostate Cancer and Inflammatory Genes
The DNA samples were labelled blindly and
shipped from Umeå University, Sweden, to
the core genotyping laboratory in the Center
for Human Genomics, Wake Forest
University, USA. In total, 37 controls from
the CEPH foundation (1331-01, 1331-02),
and 29 blind repeats were spread among the
DNA samples. In addition, every DNA plate
contained two water blanks.
Association of Interleukin-1 receptor
antagonist haplotype with prostate
cancer risk (Study II)
The procedure described above for selecting
MIC-1 sequence variants for analysis was
also used to select SNPs of the IL1-RN
gene. In total, 16 SNPs and two repeats (the
86-bp VNTR and an 8-bp repeat) were
identified by scrutinizing public databases
(NCBI dbSNP, and SNPper) (Figure 3).
Three different methods were used for
genotyping.
First, the 16 identified SNPs and the 8bp repeat were genotyped in 94 control
subjects using a 5’ nuclease assay with
TaqMan MGB probes. The SNP genotyping
assays were designed using the Assay-byDesign service (Applied Biosystems Inc.,
Foster City, CA) and the samples were
analyzed using an ABI 7700 sequence
detection system. Since it was not possible
to design a 5’ nuclease assay for the 86-bp
VNTR in intron 2, it was genotyped by
temperature
modulated
heteroduplex
analysis using a High Performance Liquid
Chromatography system, performed as
described above (Study I). Haplotypes of
these SNPs were estimated using a Markov
Chain
Monte
Carlo
approach
as
implemented in the PHASE software
package
(http://www.stats.ox.ac.uk/mathgen/softwa
re.html). Haplotype-tagging SNPs, which
captured at least 95% of the haplotype
variation among the 94 controls, were
selected using the htSNP2 computer
program
(wwwgene.cimr.cam.ac.uk/clayton/software/stat).
Four htSNPs were identified and they were
genotyped in all 1383 cases and 779
controls. The htSNPs (rs878972, rs315934,
rs3087263, rs315951) were then genotyped
using
the
MassARRAY
system
(SEQUENOM, Inc. Valencia, CA).
Prostate Cancer and Inflammatory Genes
37
1 kb
H6D 2423 C/G
2423 C/G
2816 C/G
1809 G/T
Haplotype-tagging
SNPs (htSNPs)
1809 G/T
904 A/G
V9L 25 C/G
S48T 142 A/T
25 C/G
142 A/T
-893 T/C
-1576 A/G
MIC-1
1 kb
14992G/C
10173G/A
3701A/G
4696C/G
5351T/C
6429-/+
8111G/A
8599C/T
9726A/G
10173G/A
10909A/G
11864A/C
12985C/T
13875T/G
14992G/C
15818A/G
8111G/A
2118C/A
Haplotype-tagging
SNPs (htSNPs)
-12C/G
618A/C
1631G/A
2118C/A
-1129C/T
IL1-RN
Figure 3. A) Single nucleotide polymorphisms (SNPs) of the Macrophage Inhibitory
Cyokine-1 gene and Interleukin-1 Receptor Antagonist gene. The diagrams of the genes
show exons (marked in red), the location of selected SNPs (relative to the transcriptional
start site) and SNPs that result in an amino acid substitution. Arrows represent
transcription start sites. B) Location of the haplotype-tagging SNPs that were selected to
represent at least 95% of the haplotype information.
38
Prostate Cancer and Inflammatory Genes
Determination of MIC-1 serum levels (Study IV)
MIC-1 serum levels were determined by a
MIC-1 sandwich ELISA, using the mouse
monoclonal antibody (MAb) 13C4H3 for
antigen capture and a sheep polyclonal
antibody (PAb), 233B3-P, for detection. The
optimum concentration of both antibodies
was determined and then used for all
subsequent
studies.
Ninety-six-well
Maxisorp ELISA plates were coated with
MAb 13C4H3 supernatant diluted 1:5 (final
concentration, approximately 20 ng/mL) in
coating buffer at 4°C for 24 hours. The
plates were then washed three times with
300 mL/well 1% (wt/vol) BSA in PBS for 2
h at 37°C. rhMIC-1 standards, tissue culture
supernatant and patient serum were then
added to the plates (100 mL/well) and
incubated for 1 h at 37°C. The plates were
washed three times, 100 mL/well of the
sheep PAb 233B3-P diluted 1:5000 in
antibody diluent (Ab dil) was added and they
were incubated for 1 h at 37°C. The plates
were then washed three times, 100 mL/well
of biotinylated donkey antisheep IgG
diluted 1:5000 in Ab dil was added and they
were incubated for 1 h at 37°C. The plates
were washed four times, followed by the
addition of 100 mL/well of peroxidase
substrate (1 mg/mL o-phenylenediamine
dihydrochloride from Sigma) in 0.05 mol/L
phosphate-citrate buffer containing 0.014%
H2O2, pH 5.0 (Sigma). Colour development
was allowed to proceed for 5-15 min and
was terminated by the addition of 100
mL/well of 4N H2SO4. The absorbance was
measured at 490 nm in a microplate reader.
The concentration of hMIC-1 in the
samples was determined by comparison with
an rhMIC-1 standard curve constructed
using standard curve-fitting software
supplied with the microplate reader (Pasteur
Diagnostics). The level of rhMIC-1 in the
standard curve was determined on the basis
of a comparison of this standard to a
master standard of highly purified
recombinant MIC-1. The master standard
protein concentration was determined by
averaging eight estimates of total amino acid
composition. All samples were assayed in
triplicate.
The serum samples were labelled blindly
and shipped from Umeå University, Sweden,
to the Centre for Immunology, St Vincent's
Hospital & University of New South Wales,
Australia, where the serum concentrations
were determined.
Statistical analysis
Tests
for
Hardy-Weinberg
Equilibrium (Studies I, II, III)
Hardy-Weinberg Equilibrium (HWE) tests
for each sequence variant and pair-wise
linkage disequilibrium (LD) tests for all
sequence variants were performed using a
replication method, as described by (Weir,
1996). For each test, 10,000 permutations
were performed and the Fisher probability
test statistic for each replicate was calculated
from the new corresponding multilocus
table. Empirical p-values for each test were
estimated as the proportion of replicate data
Prostate Cancer and Inflammatory Genes
sets found to be as probable as, or less
probable than, the observed data set, as
implemented in the software package
Genetic Data Analysis (GDA).
Association analysis (Studies I, II,
III, IV)
Associations between genotypes/MIC-1
serum and prostate cancer risk were assessed
by the score tests in conditional logistic
regression of a covariate equal to the
number of rare alleles (0, 1, 2) (Studies II
and III) and by dichotomized MIC-1 serum
levels (with a cut-off value of 1000 pg/ml,
based on the median level among unaffected
controls) (study IV). Genotype specific risks
were estimated as Odds Ratios (OR) with
associated 95% confidence intervals by
conditional logistic regression. Both when
testing for association and estimating ORs,
the conditional logistic regression was
stratified by each combination of age (5-year
age groups) and geographical region (the
northern part of Sweden vs. the south
eastern part of Sweden and the Stockholm
area) to adjust for the matching conducted
in collecting control subjects. Besides age
and geographical region, no other factors
were included in the regression analysis. In
Study I unconditional logistic regression was
used to test for association between
genotypes and affection status. We adjusted
for age and geographical region using
indicator variables representing each
combination of age of onset (5-year age
groups) and geographical region.
39
Haplotype analysis (Studies II, III)
Tests of association between haplotypes and
prostate cancer risk were performed using a
score test developed by Schaid et al. (Schaid
et al., 2002), as implemented in the software
HAPLO.STAT for the R programming
language. This method, based on the
generalized linear model framework, allows
adjustment for possible confounding
variables and provides both global and
haplotype-specific tests. In these analyses,
age and geographic region were adjusted for
using indicator variables representing each
combination of age category (5-year age
groups) and geographical region was
adjusted as described earlier. Haplotypes
with estimated frequencies less than 0.005
were pooled into a single group. Empirical
P-values, based on 10,000 simulations, were
computed for the global score test and each
of the haplotype-specific score tests.
Assessment of serum levels (Study
IV)
Serum MIC-1 levels of prostate cancer cases
and controls were presented as means +/standard deviation (SD). Formal comparison
of MIC-1 levels between different subject
groups were conducted using analysis of
variance (ANOVA) methods. To evaluate
the diagnostic value of MIC-1 serum levels,
nonparametric
receiver
operating
characteristic (ROC) analysis was performed.
40
Prostate Cancer and Inflammatory Genes
Results and comments
Genetic analysis of MSR1 (Study I)
In order to evaluate the role of MSR1 gene
mutations in prostate cancer in the Swedish
population we carried out a genetic analysis
in a large number of subjects from two
different study populations in Sweden. We
initially screened a set of DNA samples
representing one affected individual from
each of 83 Swedish families affected by
HPC. Among these individuals we identified
18 sequence variants in total, including two
exonic variants, four intronic and nine
variants located in the 5’- or 3’-uncoding
regions. A nonsense mutation at codon 293
(R293X) and five common sequence
variants (PRO3, INDEL1, IVS5-57, P275,
INDEL7) identified in this study, were also
reported by Xu et al (Xu et al., 2002).
The truncating mutation R293X results
in a deletion of most of the collagen-like
domain, including the ligand-binding region
and the cysteine-rich domain. Experimental
studies have demonstrated that an MSR1
mutant harbouring a similar truncating
mutation to R293X has a dominant-negative
phenotype when expressed in vitro (Dejager
et al., 1993). R293X was found in two
probands from two different families among
the 83 HPC families (2.4%). One family had
one affected (the proband) and three
unaffected R293X carriers, while the other
family had one affected (the proband) and
two unaffected R293X carriers. However,
due to the low numbers of affected men in
these two families, it was not possible to
determine whether the mutation segregated
with the disease.
In agreement with our findings, R293X
mutation was observed in the same
frequency (3.2%) among Caucasian HPC
families in the study from the United States,
(Xu et al., 2002). In addition, Seppälä et al.
reported the same frequency (2.5%) among
120 families affected with HPC (Seppälä et
al., 2003), as well as Wang et al. among 163
families affected with familial prostate
cancer (3.1%) (Wang et al., 2003) (Table 2).
We further evaluated the association
between this mutation and prostate cancer
by screening a group of 215 unrelated men
with prostate cancer and 425 age-matched
controls. The R293X mutation was found
more frequently in men with prostate cancer
(10 individuals, 4.9%) than their matched
controls (10 individuals, 2.7%), however this
difference was not statistically significant
(P=0.16) (Table 2). In contrast, Xu et al.
reported a significant difference in
frequencies of the R293X mutation between
men with non-HPC and unaffected men
(2.5% versus 0.39%, P=0.047) (Xu et al.,
2002). The choice of control population
might explain some of the differences
between our results and the previous report.
The men in the control population in the
present study were on average 66 years old
at recruitment, an age at which only 15% of
all prostate cancers have been diagnosed.
Thus, some of the unaffected R293X
carriers are likely to develop prostate cancer
eventually. Another difference is that Xu et
al. only included men with PSA values <4
and a normal prostate examination.
Prostate Cancer and Inflammatory Genes
41
Table 2. Reported studies of the association between the MSR1 nonsense
mutation R293X and prostate cancer risk
No. of carriers/total (frequency )
Study
Families
with HPC
C ontrols
P-value
Xu et al. 2002
6/190
(3.2%)
C ases with
unselected
prostate
cancer
8/317
(2.52%)
Seppälä et al. 2003
3/120
(2.5%)
6/537
(1.1%)
5/480
(1.0%)
0.91
Wang et al. 2003
5/163
(3.1%)
14/496
(2.8%)
16/492
(3.3%)
0.69
Lindmark et al. 2004
1/256
(0.39%)
0.047*
2/83 (2.4%) 10/215
10/425
(4.9%)
(2.7%)
* Fisher exact test (two-sided) between cases and controls.
Two other studies that investigated the
possible association between the R293X
mutation and prostate cancer did not find
any statistically significant difference
between unselected prostate cancer cases
and controls (Seppälä et al., 2003; Wang et
al., 2003) (Table 2). If the R293X mutation
increases the risk for prostate cancer by a
factor of two and the frequency is ~3% in
the general population, as our results
suggest, a much larger case-control study
would be needed to significantly verify this.
In addition, we detected two novel
potential pathogenic mutations, IVS3-4
A>G and IVS4+3 A>G, respectively
located in the splice donor region and splice
site acceptor region of exon 4. Both of these
mutations were observed in single families,
and neither of them was detected when
screening the group of unselected men with
prostate cancer or age-matched healthy
controls. Point mutations which alter a
conserved sequence in the splice donor
region, the splice acceptor region or a region
nearby may cause aberrant splicing of a
gene. Several studies have shown that
0.16*
mutations located in similar positions to
IVS3-4 and IVS4+3 can lead to exon
skipping, intron retention or insertions and
deletions due to utilization of cryptic splice
sites (Margaglione et al., 2000; Attanasio et
al., 2001, 2003). Further functional studies
are needed to assess the functional
significance, if any, of these mutations.
Besides the three rare mutations
described above, we decided to elucidate the
importance of five common sequence
variants found in the mutation screening of
MSR1: an SNP in the promoter region
(PRO3), a 15-bp insertion/deletion of
“GAATGCTTTATTGTA” in intron 1
(INDEL1), an SNP in intron 5 (IVS5-57), a
SNP in Exon 6 (P275A), and a 3-bp
insertion/deletion of “TTA” in intron 7
(INDEL7). The initial study evaluating the
role of the five sequence variants in the
MSR1 gene, reported a significant difference
in the allele frequencies of each of the five
variants between patients with non-HPC
and unaffected control subjects, which led
to the suggestion that these common MSR1
variants are associated with prostate cancer
42
Prostate Cancer and Inflammatory Genes
risk in the general population (Xu et al.,
2003). To investigate whether these variants
are associated with prostate cancer risk we
decided to genotype them in 215 unrelated
patients with prostate cancer and 425 age–
matched controls. None of the variants were
found to be associated with prostate cancer
(Table 3).
Table 3. Allele frequencies of common MSR1 sequence variants in unselected
prostate cancer cases and unaffected control subjects
Allele frequencies (%)
215 cases / 425 controls;
Lindmark et al. 2004
Sequence
Allele
Controls
Cases
Pvariant
values*
PRO3
G
6.1
6.0
1.00
INDEL1
+
5.9
5.9
0.94
IVS5-57
A
3.2
2.9
0.80
P275A
C
96.9
96.3
0.55
INDEL7
97.2
96.7
0.62
* χ2-test for the allele
Two other studies have evaluated the
common sequence variant in exon 6 (P275)
for its role in prostate cancer risk in the
general population. Carrier frequencies of
the P275A variant were compared between
unselected prostate cancer cases and
controls. Their data are consistent with our
results because they found no statistically
significant difference in the carrier
frequencies between the different sample
groups (Seppälä et al., 2003; Wang et al.,
2003).
It is not known how MSR1 could
contribute to the development of prostate
cancer. However, MSR1 is induced in
Allele frequencies (%)
301 cases / 250 controls;
Xu et al. 2003
Controls
Cases
Pvalues*
7.6
12.3
0.01
7.9
11.8
0.04
3.6
7.0
0.02
91.2
95.0
0.01
91.3
94.4
0.04
macrophages by oxidative stress and may
modify the amounts of reactive oxygen
intermediates. The inflammation and
proliferative regeneration of prostate
epithelium in the presence of increased
oxidative stress that are associated with
MSR1 expression may have a role in the
development of prostate cancer (Xu et al.,
2002).
In conclusion, we found no evidence to
support the hypothesis that the sequence
variants in the MSR1 gene play a role in the
development of hereditary or sporadic
prostate cancer.
Prostate Cancer and Inflammatory Genes
43
Genetic analysis of IL-1RN (Study II)
Several studies have shown that IL1-RN acts
as an important regulator of the
inflammatory response by inhibiting the
action of IL-1α and IL-1β. Since chronic
inflammation in the prostate appears to be a
co-factor in the pathogenesis of prostate
cancer, we hypothesized that functional
polymorphisms in inflammation-related
genes, such as IL-1RN may be associated
with prostate cancer risk. To test this
hypothesis, we performed genotype analyses
for four IL1-RN gene polymorphisms in a
large population-based case-control study of
1383 prostate cancer case patients and 779
control subjects.
Quality control of the genotype results
(based on included CEPH controls, repeated
study samples and water blanks) provided an
estimated error rate of 0%. Except for the
SNP rs315951, which significantly deviated
from HWE in cases (P=0.04), but not
controls (P=0.34), the genotype data for the
remaining three SNPs were consistent with
HWE (all P>0.05). The significant deviation
of the genotype frequencies of SNP
rs315951 from expected proportions among
the prostate cancer subjects may be a result
of
genotyping
errors,
population
stratification, selection, or statistical
fluctuations. However, given the high quality
of the genotyping results and the ethnic
homogeneity of the Swedish population, it
seems most plausible that chance alone was
responsible for the observed departure from
HWE. Since the departure from HWE was
in the direction of excessive homozygosity,
the error in haplotype estimations (based on
the EM algorithm) was not increased (Fallin
et al., 2000). Moreover, all statistical
inferences regarding haplotypes were based
on simulated P-values, which are expected
to be less sensitive to departure from HWE
than the asymptotically distributed score
statistic.
The SNP analysis showed that there were
no significant differences in proportions of
any of the four htSNPs between the controls
and prostate cancer cases. Assuming that the
SNPs had a dominant or recessive allelic
effect on prostate cancer risk did not alter
these findings. Furthermore, stratified
analyses based on age (<65 or ³65), tumour
stage (localized or locally advanced) and
family
history
(sporadic
or
familial/hereditary) detected no significant
differences in genotype frequencies between
cases and controls.
We also performed a haplotype analysis
of the four htSNPs, which identified the
presence of eight major haplotypes. Global
tests for association between haplotypes and
prostate cancer risk all yielded nonsignificant results. However, individual
haplotype analyses revealed that one
haplotype was statistically significantly
associated with prostate cancer risk (Table
4). The frequency of the ATGC haplotype
of SNPs rs878972, rs315934, rs3087263, and
rs315951 was significantly higher among
cases (38.7%) compared to controls (33.5%)
(haplotype-specific P=0.009). Furthermore,
in the stratified analysis the frequency of the
“ATGC” haplotype was higher in sporadic
(39.3%) than in familial (34.8%) prostate
cancer cases. Likewise, cases with advanced
disease had a higher prevalence (40.0%) than
patients with localised disease (37.5%). The
fact that the association was strengthened in
cases with advanced disease is particularly
noteworthy. While it is important to identify
disease susceptibility genes, it is equally or
44
Prostate Cancer and Inflammatory Genes
probably even more important to identify
genes that play roles in disease progression,
especially for prostate cancer since the
disease has a late average age of onset and is
life threatening in a relatively small
proportion of cases (aggressive cases).
Polymorphisms
in
genes
mediating
progression of prostate cancer could
function as genetic markers predicting an
increased risk of progressive disease.
The observation that the most common
haplotype was associated with prostate
cancer risk but none of the individual
htSNPs, highlights the advantages of
studying all variations in a gene with the use
of a haplotype-tagging approach instead of
testing a limited number of single variants.
Two different scenarios may explain this
observation. First, the association may be a
result of two or more sequence variants in
the region that do not individually confer a
detectably increased risk for prostate cancer,
but do confer a statistically significant risk in
combination, which can be detected using
the haplotype-association strategy. For
example, there may be two SNPs in the gene
that only alter protein function significantly
when they occur together. Second, the
ATGC-haplotype may be in strong linkage
disequilibrium (LD) with a risk-conferring
sequence variant in IL1-RN, or in close
vicinity to the gene, while the degree of LD
between this risk-conferring sequence
variant and each of the four htSNPs is much
weaker.
In this study the overall haplotype test
gave a non-significant result, while the
haplotype-specific score was significant for
the most common haplotype. However, the
estimated odds ratios show significantly
increased risk only for homozygous carriers
(OR = 1.6; 95% CI, 1.2-2.2) of the “ATGC”
haplotype and not for heterozygous carriers
(OR = 1.0: 95% CI, 0.8-1.2). Since the
proportion of individuals that are
homozygous for this haplotype is
considerably lower than the overall
frequency of the haplotype, the power of the
global test will be considerably lower than if
heterozygous carriers were also at increased
risk.
45
Prostate Cancer and Inflammatory Genes
%
38.7
15.5
15.3
13.6
7.7
5.4
2.7
0.7
%
2.60
-1.01
-1.16
-0.58
-0.80
-0.38
0.97
0.33
Score*
0.009
0.301
0.234
0.560
0.428
0.713
0.337
0.737
0.116
P†
39.3
15.0
15.2
14.0
7.9
4.9
2.9
0
%
2.85
-1.24
-1.22
-0.41
-0.64
-0.89
1.06
Score*
SPC
33.5
17.6
17.5
14.3
8.4
5.8
1.8
0.6
Cases
C
G
C
G
C
C
G
G
rs315951
Controls
G
G
G
G
A
G
G
A
rs3087263
Haplotype
P†
%
2.67
-1.15
-1.78
0.45
-0.20
-0.86
0.17
Score*
0.009
0.246
0.080
0.655
0.839
0.401
0.872
P†
0.024
0.006
0.215
0.208
0.667
0.513
0.367
0.274
0.052
40.0
15.0
14.1
14.9
8.4
4.8
2.4
0
Advanced PC
Table 4. Estimated haplotype frequencies in the IL1-RN gene in controls, patients with sporadic prostate cancer (SPC) and
patients with advanced prostate cancer.
T
T
T
C
T
C
T
T
rs315934
Score test statistics for association between haplotype and prostate cancer risk.
Empirical P values based on 10,000 replications.
†
*
A
A
C
A
C
A
C
C
Overall
rs878972
46
Prostate Cancer and Inflammatory Genes
Several studies have evaluated the role of
IL-1RN in a number of malignancies by
investigating the frequency of the 86-bp
VNTR in various study populations.
However, since the VNTR only covers a
minor part of the variance in the gene, it is
not enough to solely analyze the repeat to
evaluate the role of IL-1RN. Therefore, we
used another approach, in which we studied
a set of tagging SNPs that captured almost
all the genetic information in the entire gene.
We genotyped four htSNPs in the study
population, which explained >98% of
diversity in the gene. The VNTR was not
included in the genotyping, but it was almost
equivalent to the htSNP rs878972 (Pearson
correlation coefficient = 0.99). The htSNP
rs878072 was not associated with prostate
cancer risk, thus it is unlikely that the VNTR
in intron 2 by itself contributes significantly
to prostate cancer risk.
The IL-1RN gene belongs to the IL-1
gene cluster, which spans a 360-kb region of
chromosome 2 (Steinkasserer et al., 1992).
This cluster of genes contains several proand anti-inflammatory cytokine genes that
are expressed in both physiological and
pathological conditions and play a key role
in the inflammatory immune response. The
high density of IL-1 genes in this region,
which
share
similar
functional
characteristics, raises the possibility that an
association between a haplotype in IL-1RN
and prostate cancer may in fact be due to an
association between another gene or genes
in the cluster and prostate cancer.
Knowledge of the degree of LD across this
region is vital to our understanding of the
combinations of genotypes that are
important in disease. Several analyses have
been performed to determine the degree of
LD across this region, all of which have
found moderate LD in this gene cluster that
is not strictly correlated with distances
between markers (Cox et al., 1998; Bensen et
al., 2003). Thus, additional SNPs in this
region need to be identified and analysed to
determine whether apparent associations
between IL-1RN and prostate cancer reflect
a causative relationship, or are due to the
effects of another gene in the cluster.
Our results suggest that (a) prostate
cancer risk variant(s) may be located
somewhere in the region of IL1-RN. The
exact location and biological function of
this/these sequence variant/variants remain
to be identified. Further studies are needed
to replicate our findings in other populations
and to elucidate the biological function of
the IL-1RN haplotype in relation to prostate
cancer risk.
Genetic analysis of MIC-1 (Study III)
Due to the potential importance of MIC-1
in tumour development and regulation of
inflammation responses, we decided to
further elucidate the role of MIC-1 by
investigating possible associations between
sequence variants in the gene and prostate
cancer risk.
As a first step, we genotyped four
common SNPs (Exon1+25, Exon1+142,
IVS1+1809, and Exon2+2423 [H6D]) in a
large population-based case-control study of
1383 prostate cancer patients and 780
control subjects. With these four SNPs it
was possible to capture >98% of the
Prostate Cancer and Inflammatory Genes
haplotype variation in the gene, and each of
them were in HWE among both cases and
controls (all P>0.05). These SNPs were in
strong LD, as most of the pair-wise D’
estimates were 1.0, with the lowest at 0.94.
Testing
for
genotype
frequency
differences between cases and controls
revealed one SNP (H6D) for which there
was a significant difference between cases
and controls (P=0.006); proportions of
homozygotes for the common CC genotype
encoding the wild-type protein being higher
among prostate cancer cases than among
controls (53.0% versus 48.5%). In an
assessment of genotype-specific risk we
found that the OR for carriers of the GC or
GG genotype, which encodes the H6D
mutant, was lower than the OR for the CC
genotype carriers (OR=0.83; 95% CI, 0.690.99). The decreased risk for carriers of the
GC or GG genotype compared with that of
the CC genotype carriers was further
accentuated both in patients with advanced
disease (OR=0.79; 95% CI, 0.63-0.99) and in
patients with a positive family history of
prostate cancer (OR=0.68; 95% CI, 0.480.96) (Table 5). The observation that the
association was further strengthened in
patients with a positive family history is
consistent with the hypothesis that risk
genotypes may co-segregate with unknown
gene alterations with low penetrance within
families. In summary, the findings that an
association between the H6D variant and
prostate cancer is present in sporadic cases
and further accentuated in familial cases are
consistent with current knowledge.
Although this study provided strong
evidence for an association between the
H6D sequence variant in the MIC-1 gene
and prostate cancer, the underlying
47
mechanisms involved remain unclear. The
substituted amino acid at position six is
located adjacent to the cysteine at position
seven, which has been indicated to be
important for the stability of MIC-1 (Fairlie
et al., 2001). Because of the different
biochemical properties of aspartic acid and
histidine, the H6D polymorphism may alter
MIC-1’s stability and function. If it abolishes
or reduces MIC-1 activity, inflammation in
the prostate may go unchecked in carriers
with the risk genotype, leading to an
increased risk for tumour development. On
the other hand, expression of a MIC-1
protein with increased activity or stability
may lead to a reduced pro-inflammatory
response, which in turn could reduce the
capacity to eradicate certain pathogens
effectively. This is in line with the infectious
aetiology of prostate cancer that has been
proposed
(Dennis
et
al.,
2002a).
Furthermore, altered functionality of MIC-1
due to the H6D polymorphism may also
lead to decreased tumour cell growth
inhibition mediated through the TGF-β
signalling pathway. Other types of
investigations, such as in vitro and in vivo
functional studies of the H6D variant, are
needed to address these possibilities.
In conclusion, this is the first published
study evaluating the possible association
between sequence variants in the MIC-1
gene and prostate cancer risk. Our study
provided evidence for such an association,
but more studies are needed to confirm or
refute this finding in independent
populations and to elucidate the mechanism
whereby the H6D sequence variant affects
the expression and function of MIC-1 in the
signalling pathways that seem to control
macrophage regulation and tumour growth.
48
Prostate Cancer and Inflammatory Genes
Table 5. Association between prostate cancer and the H6D sequence variant of the MIC-1
gene in a large population-based study (CAPS).
OR* (95% CI)
Study subset
All PC
No. of
subjects
1340
Advanced PC
GG vs. CC
GC or GG vs. CC
0.77
(0.64, 0.93)
1.22
(0.84, 1.75)
0.83
(0.69, 0.99)
0.75
(0.59, 0.95)
1.11
(0.70, 1.74)
0.79
(0.63, 0.99)
159
0.61
(0.42, 0.89)
1.18
(0.61, 2.29)
0.68
(0.48, 0.96)
57
0.44
(0.24, 0.81)
0.62
(0.18, 2.05)
0.47
(0.26, 0.82)
Advanced PC
FPC and
HPC†
GC vs. CC
*Conditional logistic regression stratified by age and geographical region.
†FPC= Familial Prostate Cancer, HPC= Hereditary Prostate Cancer.
Analysis of MIC-1 serum levels (Study IV)
The development of sensitive immunoassays
for MIC-1 has made it possible to study
MIC-1 protein levels in human serum and
other body fluids. Brown et al. found the
MIC-1 serum concentration to be higher in
patients with colorectal cancer than in
controls, and production of the protein was
also up-regulated in tumour tissues
compared to its normal counterparts (Brown
et al., 2003). The same pattern was also
observed in a small study in patients with
breast and prostate cancer (Buckhaults et al.,
2001). Based on these findings, together
with the results from study III, we decided
to
determine
the
serum
MIC-1
concentration in the CAPS population to
elucidate whether the circulating MIC-1
levels are related to prostate cancer and
MIC-1 genotype and whether MIC-1 levels
are associated with prostate cancer risk. At
the time of the study sera from 620 controls
and 1116 cases from the CAPS study were
available for analyses. 19 prostate cancer
cases were excluded from further statistical
analyses since clinical data were missing for
these subjects.
Examination of serum MIC-1 levels
among control subjects revealed that MIC-1
concentrations increased with increasing age
(P<0.001) (Figure 4). This is an interesting
and important finding since it influences the
interpretation of the serum analyses. A
number of investigations of potential serum
markers for cancer (including MIC-1), have
used a small number of control subjects,
drawn from volunteers or blood donors,
limiting the scope to identify possible
correlations between serum levels and age.
Further, using a control group that differs
significantly in mean age from the case
subjects could result in significant difference
in serum concentration between cases and
controls that are solely due to the
differences in mean age between the two
Prostate Cancer and Inflammatory Genes
groups. The reason for the relationship
between age and serum MIC-1 levels found
among the controls in this study is unclear,
49
but may be related to an increased general
inflammation burden.
3000
MIC-1 (pg/ml)
2500
2000
1500
1000
500
0
<60
60-64
65-69
70-74
75-79
Age at inclusion (years)
Figure 4. MIC-1 concentration in 620 controls without prostate cancer with respect to age
(P<0.001).
The mean serum MIC-1 level among all
prostate cancer patients analysed was 1357
pg/ml, SD=1534, which was significantly
higher (P= 0.004) than the MIC-1 level
among the control subjects (1190 pg/ml,
SD=942) (Table 6) In addition, MIC-1 levels
were significantly higher (P<0.001) among
patients with advanced disease than among
patients with localised prostate cancer,
(mean 1666 pg/ml, SD=2138 and 1121
pg/ml, SD=733, respectively (Table 6). The
prostate cancer group was further divided
into subgroups depending on the treatment
(watchful waiting, hormonal treatment,
radical prostatectomy and radiotherapy) they
received. For 43 patients, treatment was not
specified so these patients could not be
classified. Significant differences in serum
MIC-1 level between the different treatment
options were observed (P<0.001). However,
multiple ANOVA analyses of MIC-1 levels
with age, disease stage and treatment as
independent factors revealed significant
effects of age and disease stage, while no
significant effect was observed for
treatment.
50
Prostate Cancer and Inflammatory Genes
Table 6. Serum MIC-1 level of all prostate cancer patients and controls according to
stage and treatment
MIC-1 (pg/ml)
Status
n
Mean ± S.D
P-value*
Controls
Prostate cancer cases (all)
620
1097
1190±942
1357±1534
0.004
Stage
Localized
Advanced
622
475
1121±733
1666±2138
<0.001
Treatment
Watchful waiting
Radical prostatectomy
Hormonal treatment
Radiotherapy
245
219
506
84
1278±773
1059±929
1575±2057
1153±573
<0.001
* Analysis of variance (ANOVA)
To further refine the correlation between
serum MIC-1 levels and disease stage, the
prostate cancer group was stratified based
on the TNM classification. The stratified
analysis revealed a significant increase in
serum MIC-1 levels with increasing TNMstage (P<0.001, age adjusted)(Figure 5). The
same trend was observed when only
untreated cases (n=245) were included in the
analysis (P=0.029) (data not shown), clearly
indicating that this phenomenon is not
related to treatment effects. All together
these results clearly demonstrate a
relationship between MIC-1 serum level and
tumour burden. These data are consistent
with previous reports that patients with
metastatic cancer had significantly elevated
serum MIC-1 levels compared with other
cancer patients (Brown et al., 2003).
However, if the elevation is a secondary
effect of the tumour growth or wether MIC1 palys an active role in the disease
progression, where an increase in serum
concentration enhances tumous growth, is
still
needed
to
be
investigated.
Prostate Cancer and Inflammatory Genes
51
4000
3500
MIC-1 (pg/ml)
3000
2500
2000
1500
1000
500
0
I
II
III
IV
TNM tumour stage
Figure 5. Correlation between MIC-1 serum concentrations and disease stage (P<0.001)
among 1097 men with prostate cancer.
A possible association between serum
levels and prostate cancer risk were also
assessed. Using logistic regression analysis, a
serum MIC-1 level above the median of the
controls is indicated to be a significant
predictor for development of prostate
cancer. Thus, considering a cut-off serum
level of > 1000 pg/ml, the relative risk for
development of prostate cancer was 1.5
(95% CI, 1.1-2.0). To test the ability of the
serum assay to differentiate prostate cancer
cases from control subjects, ROC analyses
were performed. The ROC curve clearly
showed that there is no diagnostic
usefulness MIC-1 (area under ROC curve:
0.56) (Figure 6). On the other hand, the
clear relation between clinical stage and
serum MIC-1 levels indicates that MIC-1
may be useful as a prognostic factor, where
high serum concentrations at diagnosis of
prostate cancer are associated with a poor
prognosis. For this purpose, serial
measurements of MIC-1 among diagnosed
cancer patients would probably be of greater
value
than
a
single
observation.
Prostate Cancer and Inflammatory Genes
0.6
0.4
0.0
0.2
Sensitivity
0.8
1.0
52
0.0
0.2
0.4
0.6
0.8
1.0
1 - Specificity
Figure 6. Receiver operator characteristic (ROC) curve of MIC-1 for differentiation of
patients with untreated prostate cancer (n=245) from control subjects (n=620). Area
under ROC curve: 0.56.
Finally, to test for possible association
between MIC-1 genotype and serum levels,
we compared serum levels between control
subjects with different genotypes according
to the H6D polymorphism. No significant
differences in MIC-1 serum levels between
the genotypes was observed (P=0.41)
(Figure 7). We therefore suggest that the
H6D polymorphism may alter the function
or stability may of the protein, for example
the D allele may be more biologically active
or function in a different way compared to
the H allele and thereby alter the risk for
prostate cancer development.
Another important question needed to
be answered, but that is beyond the result
from this study, involves the role that MIC-1
may play in the development of prostate
cancer. The increase in serum MIC-1 level
associated with the presence of prostate
cancer implies that an inflammatory process
in the prostate may be involved in the
development or progression of prostate
cancer, since in vitro studies have shown that
MIC-1 may function as a suppressor of
Prostate Cancer and Inflammatory Genes
macrophage-mediated
proinflammatory
activity. However, studies of several tumour
cell lines have also shown that MIC-1 has
proapoptotic and antitumorigenic activities
(Bauskin et al., 2005). Brown et al. proposed
the following explanation for this dual role
of MIC-1 in cancer progression. As the
prostate cancer tumour progresses, MIC-1
secretion may rise, leading to an inhibitory
effect on tumour growth. However, this
inhibitory effect may be negated by the
decrease in local tumour immunity,
mediated by the immune suppressor effect
of MIC-1, and thus providing a mechanism
for tumour escape (Brown et al., 2003).
Another explanation for the incongruous
indications of both proapoptotic and
antitumorigenic functions for MIC-1 –
53
together with the striking correlation
between elevated MIC-1 levels and
metastatic progression of prostate, breast
and colorectal cancer – is related to MIC-1’s
similarity to the TBF-β protein. It has been
reported that MIC-1, like TGF-β, requires
an intact signaling pathway mediated by type
I and type II TGF-β receptors, as well as
receptor-activated Smad4 to exert its effects
(Tan et al., 2000). TGF-β is considered to act
as a tumor supressor during the early stages
of cancer (by inhibiting cell proliferation),
and as a promoter of growth and metastasis
in later stages, thereby enhancing
angiogenesis,
immunosupression
and
synthesis of extracellular matrix (Dumont et
al., 2003).
3000
MIC-1 (pg/ml)
2500
2000
1500
1000
500
0
CC
CG
GG
H6D genotype
Figure 7. Correlation between MIC-1 genotypes and serum level in 620 controls without
prostate cancer. No significant difference in MIC-1 serum levels among control subjects
with different genotypes was observed (P=0.41).
54
Prostate Cancer and Inflammatory Genes
In conclusion, a clear association
between disease stages and serum MIC-1
levels was found, indicating that MIC-1 may
be
involved
in
prostate
cancer
tumorigenesis. Moreover, our results
indicate that serum MIC-1 levels are
associated with an increased risk for prostate
cancer. We also assessed the clinical value of
the MIC-1 protein as a serum marker. Our
data revealed that the differences in serum
MIC-1 levels between cases and controls are
not large enough to provide a discriminatory
test for the presence of prostate cancer.
However, the clear relation between clinical
stage and serum MIC-1 levels indicates that
MIC-1 may be useful as a prognostic factor,
high serum concentrations being associated
with a poor prognosis.
Prostate Cancer and Inflammatory Genes
55
Discussion
Association studies
Association studies offer a potentially
powerful approach to identify genetic
variants that influence susceptibility to
complex diseases, but are afflicted by the
impression that they are not consistently
reproducible. Nevertheless, a number of
complex diseases have been consistently
shown to be associated with specific genetic
variants,
including
thrombophilia,
Alzheimer’s disease, and diabetes types 1
and type 2 (Hattersley et al., 2005). The
susceptibility variants identified to date
either common, and carry a modest risk, or
uncommon and carry a substantial relative
risk. However, few of the many possible
associations investigated in published
cancer-genetic association studies have been
subsequently established beyond reasonable
doubt (Pharoah et al., 2004). In other cases,
the results of further investigations have
generally been conflicting, for several
possible reasons, including population
stratification, small sample sizes, and
misclassification of study subjects.
One of the major factors hindering
association studies of prostate cancer are
that prostate cancer is often detected by
PSA measurements in cases where there are
no clinically distinguishing features. A
further complication is that the presence of
prostate cancer is also frequently undetected
among controls, partly due to the fact that
prostate cancer is commonly a late age of
onset disease, and there are often long
periods in which it is present but there are
no obvious symptoms. Evidence from
autopsies indicate that over 50% of men
harbour tumours in the prostate by the time
they are 60 years old, which means that a
larger proportion of men die with prostate
cancer rather than from it (Sakr et al., 1994).
This makes it difficult to find case-control
populations where cases and controls differ
significantly in the phenotype of interest,
thus reducing the probability of detecting
cancer-associated factors.
Another problem that arises when
performing association studies of prostate
cancer, as well as other complex diseases, is
the heterogeneous nature of these diseases.
Prostate cancer patients may be predisposed
to the condition, due to the inheritance of
different sequence variants of the same or
different genes from different founders.
This causes two major problems. First,
inherited
susceptibility
could
vary
significantly among ethnic groups. Second,
different distributions of ethnicity among
cases and controls could lead to population
stratification, so observed differences in
genotype frequencies of a variant may
partially reflect differences in the genetic
background of cases and controls. However,
if cases and controls are well matched,
differences in the frequency of genotypes
should only be seen at predisposition loci.
A further substantial problem is that a
large number of genes and genetic variants
may affect the risk for prostate cancer
through different mechanisms, and the
effect of each given gene, or variant of a
gene, is likely to be minor in the general
population. Such polygenic effects could
apply even in a homogenous population.
56
Prostate Cancer and Inflammatory Genes
This phenomenon is observed in other
complex diseases, as reported in a recent
meta-analysis of genetic association studies
in complex diseases (Lohmueller et al., 2003).
After evaluating 301 published studies that
attempted to replicate reported disease
associations for 25 different genes, the study
confirmed the associations for only eight of
the 25 genes. Strikingly, seven of these eight
genes were associated with modest estimated
genetic effects (ORs between 1.07 and 1.76
in the pooled analyses). This highlights the
need to use studies with large and well
characterised populations to identify such
effects convincingly. For example, in order
to detect a sequence variant with a frequency
of 20% in the population conferring a
relative risk of 1.5 (50% increased risk) a
study of approximately 1000 cases and 1000
controls will be needed (Pharoah et al.,
2004). Historically, the majority of genetic
association studies have analyzed a relatively
small number of study subjects, leading to
both false positive and false negative
reports.
The genotyping quality is an important
factor for a successful and reliable
association study (Hattersley et al., 2005).
Robust quality control needs to be
implemented in the genotyping procedure,
including both positive and negative
controls and at least 5% repeated study
samples. To assure reliable results both cases
and control samples should be included on
the same plate and, furthermore, the casecontrol status of each sample should be
blinded during genotyping. Most reported
deviations
from
Hardy-Weinberg
equilibrium originate from problems with
genotyping methods.
Another issue highlighting a problem in
interpreting the findings of an association
study is the risk of type I error due to
multiple testing. As a result of a large
number of possible candidate genes and
multiple sequence variants with in a gene,
there is the substantial problem of multiple
tests. To overcome this problem, correction
methods have been suggested that
compensate for multiple testing. However,
in analysis of variance, the multiple testing is
further complicated by the fact that the
comparisons are not independent. Due to
linkage disequilibrium among closely spaced
sequence variants the different tests of the
variants within a gene or other defined
region will not be independent. At present
there is a lack of appropriate methods to
adjust for multiple, dependent tests (Cordell
et al., 2005).
In addition, a candidate variant that
segregates with a specific condition may not
be causally linked to it, but could be in
linkage disequilibrium (LD) with the causal
variant or variants. A number of variants
that are in LD with a specific variant of
interest are likely to be associated with a
disease even if there is only one underlying
variant that causes the risk. Systematically
studying a set of htSNPs that may or may
not be functionally relevant to a disease, but
capture all the sequence variation in the
entire genes, makes it possible to assess
whether sequence variants in the genes are
associated with a particular disease (Johnson
et al., 2001). If the association is confirmed
in an independent population, the region
that is represented by the associated htSNP
or htSNPs needs to be sequenced. After
identifying all genetic variants within the
region, in vivo and in vitro functional studies
of the identified sequence variants will be
needed to finally establish the identity of the
causal variant.
Finally, performing an association study
with one candidate SNP also has another
major drawback when no association is
found, since the lack of association does not
Prostate Cancer and Inflammatory Genes
exclude the possibility that there may be
another important variant in the same gene.
By using the tagging SNP approach, in
which the variance in the entire gene is
evaluated, it is easier to obtain evidence that
could exclude the possibility that a candidate
gene plays a role in prostate cancer
pathogenesis (Pharoah et al., 2004).
We have performed association studies to
evaluate the role of sequence variants in
three different genes in prostate cancer
susceptibility, and have therefore taken into
account the issues described above. The
criteria needed to perform a well-designed
association study have been fulfilled with
varying degrees in the three studies.
In study I, we used a homogenous
population with minimal risks for
population stratification drawn from the
NSHDC. Each case had two controls
matched in terms of sex, age, date at
recruitment and geographical residency.
However, the NSHDC case-control study
sample is too small to detect modest genetic
risks (OR 1.5-2.0) such as those expected for
the five common sequence variants
evaluated (PRO3, INDEL1, IVS5-57,
P275A, INDEL7). For instance, to evaluate
convincingly the effects of the rare mutation
R293X, which is present at a frequency of
3% in the general population, according to
our observations, and increases prostate
cancer risk by a factor of two (OR ~2.0), a
much larger case-control study would be
needed.
In Studies II and III we used 780
controls and 1383 cases drawn from the
CAPS study, a population-based case-
57
control study that recruited subjects from
70% of the Swedish population. The genetic
background of the Swedish population is
homogenous, which significantly reduces the
risk for population stratification. In addition,
the population-based study was carefully
designed, and almost all patients who met
the inclusion criteria enrolled in the study.
Control subjects were frequently matched to
case subjects on the basis of residence area,
sex and age. Further, the full clinical
spectrum of prostate cancer was well
represented, with over 45% of cases having
advanced disease. The large number of study
subjects increases the statistical power to
detect a modestly altered risk for prostate
cancer. However, it should be noted that the
statistical power to detect a risk genotype for
an allele present at low frequencies is still
limited unless the study is very large. For
example, to have 80% power to detect a risk
genotype that confers an OR of 1.4 (at a 5%
significance level according to two-sided
tests), the risk genotype need to be present
in 5% of the population. If the risk genotype
only confers an OR of 1.2, it needs to be
present in 20% of the population to have
80% power to detect the genotype (Figure
8). Finally, a careful quality control was
implemented in the genotyping procedure
by including both cases and controls
(including CEPH samples, blinded repeats
and water blanks on the same DNA plates).
No indication of genotyping error was
observed in Studies II and III, the genotype
consistency was 100% for the CEPH
control DNA samples, and results from
duplicated samples were 100% concordant,
giving an estimated error rate of 0%.
Prostate Cancer and Inflammatory Genes
58
1.0
MAF = 5%
MAF = 10%
MAF = 20%
0.9
0.8
0.7
Power
0.6
0.5
0.4
0.3
0.2
0.1
0.0
1.0
1.1
1.2
1.3
1.4
1.5
Relative Risk
Figure 8. Graph illustrating the dependence of the power to detect a risk genotype on
minor allele frequency (MAF), at a significance level of 5% according to two-sided tests.
Cytokine polymorphisms in prostate cancer
In 1863, Virchow first suggested that cancer
originates at sites of chronic inflammation
(Balkwill et al., 2001). Chronic inflammation
has also been proposed recently to be an
important factor in prostate cancer
pathogenesis
(Platz
et
al.,
2004).
Inflammatory processes involve the action
of a number of mediators, including
metabolites of arachidonic acid, cytokines,
chemokines, and free radicals. The balance
between the effects of pro-inflammatory and
anti-inflammatory
cytokines
strongly
influences the outcome of inflammatory
events. Cytokine genes are highly
polymorphic and the stability and function
of the cytokines that specific variants
encode, which in turn can affect the
inflammation response, depend on the
location and nature of the polymorphisms.
Prostate Cancer and Inflammatory Genes
The role of sequence variants in two
genes encoding cytokines (MIC-1, IL-1RN)
was evaluated in the studies underlying this
thesis. Both of these cytokines are important
regulators of the inflammatory response,
although MIC-1 has also been documented
to act as an inhibitor of tumour growth. The
haplotype-tagging approaches used enabled
us to elucidate most of the genetic variation
with a limited number of SNP genotypes.
The anti-inflammatory cytokine IL-1RN
is well known for its role as a competitive
inhibitor of the pro-inflammatory cytokines
IL-1α/β, and thus as a “neutralizer” of the
physiological
and
pathophysiological
inflammatory responses. Our results
revealed that the most common haplotype
of IL-1RN was associated with an increased
risk of prostate cancer. The genetic analysis
of the MIC-1 gene showed that a nonsynonymous polymorphism in exon two was
associated with prostate cancer. The
polymorphism alters an amino acid in the
mature protein, but although this variant has
been previously reported, no functional
studies have evaluated its biological role.
Further studies of other types are needed to
elucidate the biological rationale for the
association between sequence variants in
these two genes and prostate cancer, but it is
tempting to speculate that these variations
could be linked to an imbalance in the
inflammatory process.
Polymorphisms affecting susceptibility to
complex disorders, like prostate cancer, are
likely to be fairly common in the population,
and therefore should not be deleterious for
the carrier. They are unlikely therefore to
disrupt gene activity or protein function
completely, but instead affect gene
expression levels, mRNA stability, protein
folding or the affinity of the encoded
proteins to their receptors or substrates.
These polymorphisms might be beneficial in
59
some situations and harmful in others. For
example, decreased stability of the mRNA
or protein encoded by the MIC-1 gene could
lead to a prolonged inflammatory response,
which could be advantageous for combating
infectious agents. However, chronic
exposure of inflammatory mediators leads to
increased cell proliferation, mutagenesis,
oncogene activation, and angiogenesis - the
ultimate results of which will be
proliferation of cells that have lost normal
growth control (Shacter et al., 2002).
Another
interesting
observation
regarding the association between these two
genes and prostate cancer risk is the fact that
both genes are expressed in macrophages.
Macrophages, together with lymphocytes,
are the predominant cell types in areas of
chronic inflammation, a condition that is
extremely common in the prostate, but are
rarely found in tumour tissues. Furthermore,
increased
macrophage
activity
and
infiltration of lymphocytes in the tumour
has been found to be related to poor
prognosis in prostate cancer (Irani et al.,
1999; Lissbrant et al., 2000; McArdle et al.,
2004). Both MIC-1 and IL1-RN are antiinflammatory cytokines; MIC-1 has been
shown to down-regulate the overall activity
of macrophages, whereas IL1-RN is known
to inhibit the function of IL1-α/β, and
thereby decrease the pro-inflammatory
activity of the macrophage. Since
macrophages produce a number of
mediators that strongly influence cell
proliferation and differentiation under both
physiological
and
pathological
circumstances, as well as being the key cells
regulating reactions leading to and driving
chronic inflammation, increases in their
activity could enhance tumour initiation and
progression. Sequence variants in these two
genes could be the causes of such increases
in activity.
60
Prostate Cancer and Inflammatory Genes
In collaboration with a US research
group at Wake Forest University we
systematically evaluted associations between
sequence variants of 20 inflammatory genes
and prostate cancer. The genes were selected
based on their roles in inflammation and the
results of gene expression profiling studies
in prostate cancer tissue. Sequence variants
of eight of these genes – MIC-1 IL1-RN,
TLR-1, TLR-4, TLR-6, TLR-10, IL-10, and
COX-2 (Lindmark et al., 2004, 2005; Zheng
et al., 2004; Sun et al., 2005) – were found to
be associated with prostate cancer risk. The
high frequency of positive results obtained
for this group of genes clearly indicate that
genes related to inflammation processes may
play an important role in the development
of prostate cancer.
So far, most studies evaluating possible
associations between sequence variants and
prostate cancer risk have tended to focus on
one gene at a time, even though the
aetiology of prostate cancer cannot be
explained by genetic variability in a single
gene. One reason for the focus on single
genes is probably that most studies lack the
statistical power to evaluate the combined
effect of several genetic polymorphisms.
However, there is a need to assess the
effects of multiple genes simultaneously, as
clearly demonstrated by considering how
cytokines function. Cytokines act in a highly
complex coordinated network in which they
induce or repress their own synthesis as well
as that of other cytokines and cytokine
receptors (Howell et al., 2002). Furthermore,
there is often considerable overlap and
redundancy between the functions of
individual cytokines. Due to their highly
interrelated functions, it is very important to
simultaneously evaluate polymorphisms in
the genes encoding cytokines, their receptors
and downstream effectors. In an attempt to
do so, Xu et al. explored the joint effects of
20 genes (mentioned above) involved in the
inflammation pathway on prostate cancer
risk. Using a data-mining method (MDR),
they found that the interactions of four
SNPs in these inflammatory genes (one SNP
each from IL-10, IL-1RN, TIRAP, and
TLR5) are significant indicators of prostate
cancer risk (Xu et al., 2005).
Prostate Cancer and Inflammatory Genes
61
Future perspectives
Many questions arise from the studies
appended to this thesis, but the overall
findings are in concordance with the
growing body of evidence that chronic
inflammation plays an important role in the
development of prostate cancer. In the two
association studies reported in Papers II and
III we detected sequence variations in two
inflammatory genes that alter the risk for
developing prostate cancer. Since these
findings are novel, there is a need for largescale, independent confirmatory studies.
However, if the results are corroborated, the
next steps would be to identify the causal
varints in these regions and to elucidate the
underlying mechanism(s) responsible for
these associations. Since the cytokine
pathways are highly interrelated it is possible
that polymorphisms in several related
cytokines are needed to cause disease.
Furthermore, the effect of variations in the
ability to influence an inflammatory
response may not be manifest unless
exposure to certain infectious agents or
oxidants occurs. These issues may have to
be addressed in order to identify the casual
variant or variants in the cytokine genes.
The results of Study IV clearly showed a
positive correlation between serum MIC-1
levels and disease stages. Among the group
of patients with TNM-stage IV there were
large variations in MIC-1 values. A recent
study found that mice transfected with
prostate cancer cell line DU145 expressing
human MIC-1 dramatically lost weight, and
the degree of weight loss was proportional
to serum levels of tumour-derived human
MIC-1. This effect could be reversed in a
dose-dependent manner by injecting the
mice with a monoclonal antibody specific
for human MIC-1 (personal communication,
Samuel
Breit).
Collectively,
these
observations raise the possibility that the
large variations in MIC-1 values seen among
stage IV patients could influence the
outcome for these patients. Performing a
follow-up study in which clinical parameters
and disease-progression-data are collected
regarding the cases included in the CAPS
study, could help assess this possibility.
MIC-1 has been reported to be expressed
in both epithelial cells and macrophages, two
types of cells that are abundant in tissues in,
and adjacent to, prostate tumours. To
further elucidate the role of MIC-1 in cancer
pathogenesis, it would be valuable to
determine how much MIC-1 (if any) these
cell types produce in normal prostate tissue
and the various prostate cancer stages. This
could be done by analyzing
protein
expression in prostate tissue sections from a
selected number of cases and controls drawn
from the CAPS study. Another approach
would be to use sections of prostate tissue
with various disease stages from TRAMP
mice to examine the localisation and
expression pattern of the MIC-1 protein.
In summary, although multiple pieces of
evidence clearly indicate that prostatic
inflammation plays an important role in the
development of prostate cancer, much work
remains to be done to elucidate the
underlying mechanims.
Prostate Cancer and Inflammatory Genes
62
Conclusions
Based on the findings in Paper I-IV, the following conclusions can be made:
ü Genetic analysis in a large number of subjects from two different study populations
in Sweden failed to support a role of sequence variants in the MSR1 gene in the
development of hereditary or sporadic prostate cancer.
ü A comprehensive evaluation of a possible association between sequence variants of
IL1-RN gene and prostate cancer susceptibility revealed that the most common
haplotype in the I L1-RN gene confers an increase risk for prostate cancer. These
findings highlight the advantages of studying all variation in a gene with the use of a
haplotype-tagging approach instead of testing a limited number of single sequence
variants.
ü A large population-based association study provided strong genetic data supporting
an association between the nonsynonymous polymorphism H6D in the MIC-1 gene
and prostate cancer risk. More studies are needed to understand the mechanism by
which sequence variation in this gene affect the function of the MIC-1 protein
which in turn confers an altered prostate cancer risk.
ü MIC-1 serum levels are elevated in prostate cancer patients compared to control
subjects. In addition, MIC-1 serum levels were significantly associated with age and
disease stage. The differences in serum concentration between prostate cancer
patients and healthy individuals are not large enough to provide a discriminatory
diagnostic test for the presence of this disease. However, serial measurements of
MIC-1 may be useful in the management of prostate cancer.
ü The findings of the studies underlying this thesis are in overall concordance with the
growing evidence from epidemiological, molecular, and histopathological studies
that chronic inflammation plays an important role in the development of prostate
cancer. The results indicate that further research is required on the possible roles of
genetic variation in genes involved in the inflammatory process and on how this
variation may affect susceptibility to, and development of, prostate cancer.
Prostate Cancer and Inflammatory Genes
63
Acknowledgements
The work for this thesis was performed at
the department of Radiation Sciences,
Oncology, Umeå University. I hereby wish
to sincerely thank all of those involved in
helping me to complete it.
In particular I would like to thank:
Henrik Grönberg, my supervisor, for
excellent scientific guidance and for helpful
discussions throughout my research studies.
Also thanks for your great understanding in
how I have organized the research studies
together with my medical studies.
Jianfeng Xu and Lilly Zheng, for your
excellent collaboration and assistance in
experiments and for stimulating the
scientific discussions.
All co-authors, for contributing to my
work.
All the people in the research group BjörnAnders J for friendship and for all
interesting discussions in many different
areas, and for always being there with a
helping hand, Fredrik W for your invaluable
and comprehensive statistical help and for given
me self-confidence at the squash court,
Ingela G for truly skilful laboratory
assistance and Lena L for keeping track on
everything and helping me when I have run
out of time, Monica E, Elisabeth S and
Karin A for all your work with the study
populations, Kristina C, for god company
during the writing procedure, and Camilla
T, Beatrice M, Sara L, Stina for valuable
comments and enthusiasm in my research.
Mark Hunter, for introducing me into the
tricky business of MIC-1 ELISA.
Anders Bergh, for all interesting
discussions and for valuable comments on
the final draft of this thesis.
All the colleagues at the Department of
Medical Biosciences, for providing a nice
working-atmosphere.
Carina Ahlgren and Anna Wernblom for
excellent help no matter what kind of
problems I have brought to you.
To all I have forgotten to mention
Gun-Brith and Royne, my parents in law,
for all your support both of my family and
me.
My parents, Monica and Jörgen for
devoted support and for always believing in
me.
Margareta and Freddie for being part of
the family and for your support.
Benjamin and Tuva, our wonderful kids,
for always helping me keep things in
perspective and for bringing so much joy
into our lives.
Anna, my love, for sharing your life with
me, and for your endless support.
64
Prostate Cancer and Inflammatory Genes
References
Adlercreutz H, Markkanen H, Watanabe S (1993) Plasma concentrations of phytooestrogens in Japanese men. Lancet 342:1209-1210
Afrin LB, Ergul SM (2000) Medical therapy of prostate cancer: 1999. J S C Med Assoc
96:77-84
Alexander RB, Ponniah S, Hasday J, Hebel JR (1998) Elevated levels of
proinflammatory cytokines in the semen of patients with chronic
prostatitis/chronic pelvic pain syndrome. Urology 52:744-749
Arend WP, Malyak M, Guthridge CJ, Gabay C (1998) Interleukin-1 receptor antagonist:
role in biology. Annu Rev Immunol 16:27-55
Attanasio C, David A, Neerman-Arbez M (2003) Outcome of donor splice site mutations
accounting for congenital afibrinogenemia reflects order of intron removal in
the fibrinogen alpha gene (FGA). Blood 101:1851-1856
Attanasio C, de Moerloose P, Antonarakis SE, Morris MA, Neerman-Arbez M (2001)
Activation of multiple cryptic donor splice sites by the common congenital
afibrinogenemia mutation, FGA IVS4 + 1 G-->T. Blood 97:1879-1881
Baek SJ, Kim KS, Nixon JB, Wilson LC, Eling TE (2001) Cyclooxygenase inhibitors
regulate the expression of a TGF-beta superfamily member that has
proapoptotic and antitumorigenic activities. Mol Pharmacol 59:901-908
Balkwill F, Mantovani A (2001) Inflammation and cancer: back to Virchow? Lancet
357:539-545
Baron JA, Sandler RS (2000) Nonsteroidal anti-inflammatory drugs and cancer prevention.
Annu Rev Med 51:511-523
Basler JW, Piazza GA (2004) Nonsteroidal anti-inflammatory drugs and cyclooxygenase-2
selective inhibitors for prostate cancer chemoprevention. J Urol 171:S59-62
discussion S6
Bauskin AR, Brown DA, Junankar S, Rasiah KK, Eggleton S, Hunter M, Liu T,
Smith D, Kuffner T, Pankhurst GJ, Johnen H, Russell PJ, Barret W,
Stricker PD, Grygiel JJ, Kench JG, Henshall SM, Sutherland RL, Breit
SN (2005) The propeptide mediates formation of stromal stores of
PROMIC-1: role in determining prostate cancer outcome. Cancer Res
65:2330-2336
Bensen JT, Langefeld CD, Hawkins GA, Green LE, Mychaleckyj JC, Brewer CS,
Kiger DS, Binford SM, Colicigno CJ, Allred DC, Freedman BI, Bowden
DW (2003) Nucleotide variation, haplotype structure, and association with
end-stage renal disease of the human interleukin-1 gene cluster. Genomics
82:194-217
Prostate Cancer and Inflammatory Genes
65
Bootcov MR, Bauskin AR, Valenzuela SM, Moore AG, Bansal M, He XY, Zhang HP,
Donnellan M, Mahler S, Pryor K, Walsh BJ, Nicholson RC, Fairlie WD,
Por SB, Robbins JM, Breit SN (1997) MIC-1, a novel macrophage
inhibitory cytokine, is a divergent member of the TGF-beta superfamily. Proc
Natl Acad Sci U S A 94:11514-11519
Bosland MC (2000) The role of steroid hormones in prostate carcinogenesis. Journal of the
National Cancer Institute Monographs 27:39-66
Böttner M, Suter-Crazzolara C, Schober A, Unsicker K (1999) Expression of a novel
member of the TGF-beta superfamily, growth/differentiation factor15/macrophage-inhibiting cytokine-1 (GDF-15/MIC-1) in adult rat tissues.
Cell Tissue Res 297:103-110
The Breast Cancer Linkage Consortium (1999) Cancer risks in BRCA2 mutation carriers.
J Natl Cancer Inst 91:1310-1316
Brown DA, Ward RL, Buckhaults P, Liu T, Romans KE, Hawkins NJ, Bauskin AR,
Kinzler KW, Vogelstein B, Breit SN (2003) MIC-1 serum level and
genotype: associations with progress and prognosis of colorectal carcinoma.
Clinical Cancer Research 9:2642-2650
Bruner DW, Moore D, Parlanti A, Dorgan J, Engstrom P (2003) Relative risk of prostate
cancer for men with affected relatives: systematic review and meta-analysis.
Int J Cancer 107:797-803
Buckhaults P, Rago C, St Croix B, Romans KE, Saha S, Zhang L, Vogelstein B,
Kinzler KW (2001) Secreted and cell surface genes expressed in benign and
malignant colorectal tumors. Cancer Res 61:6996-7001
Bylund A, Lundin E, Zhang JX, Nordin A, Kaaks R, Stenman UH, Aman P,
Adlercreutz H, Nilsson TK, Hallmans G, Bergh A, Stattin P (2003)
Randomised controlled short-term intervention pilot study on rye bran bread
in prostate cancer. Eur J Cancer Prev 12:407-415
Bylund A, Zhang JX, Bergh A, Damber JE, Widmark A, Johansson A, Adlercreutz H,
Aman P, Shepherd MJ, Hallmans G (2000) Rye bran and soy protein delay
growth and increase apoptosis of human LNCaP prostate adenocarcinoma in
nude mice. Prostate 42:304-314
Carpten J, Nupponen N, Isaacs S, Sood R, Robbins C, Xu J, Faruque M, Moses T,
Ewing C, Gillanders E, Hu P, Bujnovszky P, Makalowska I, BaffoeBonnie A, Faith D, Smith J, Stephan D, Wiley K, Brownstein M, Gildea
D, Kelly B, Jenkins R, Hostetter G, Matikainen M, Schleutker J,
Klinger K, Connors T, Xiang Y, Wang Z, De Marzo A, Papadopoulos
N, Kallioniemi OP, Burk R, Meyers D, Grönberg H, Meltzer P,
Silverman R, Bailey-Wilson J, Walsh P, Isaacs W, Trent J (2002)
Germline mutations in the ribonuclease L gene in families showing linkage
with HPC1. Nat Genet 30:181-184
Chan JM, Giovannucci EL (2001) Vegetables, fruits, associated micronutrients, and risk of
prostate cancer. Epidemiol Rev 23:82-86
66
Prostate Cancer and Inflammatory Genes
Chang YW, Jang JY, Kim NH, Lee JW, Lee HJ, Jung WW, Dong SH, Kim HJ, Kim
BH, Lee JI, Chang R (2005) Interleukin-1B (IL-1B) polymorphisms and
gastric mucosal levels of IL-1beta cytokine in Korean patients with gastric
cancer. Int J Cancer 114:465-471
Cohen RJ, Shannon BA, McNeal JE, Shannon T, Garrett KL (2005) Propionibacterium
acnes associated with inflammation in radical prostatectomy specimens: a
possible link to cancer evolution? J Urol 173:1969-1974
Combs GF (2004) Status of selenium in prostate cancer prevention. Br J Cancer 91:195-199
Cordell HJ, Clayton DG (2005) Genetic association studies. Lancet 366:1121-1131
Coughlin SS, Hall IJ (2002) A review of genetic polymorphisms and prostate cancer risk.
Annals of Epidemiology 12:182-196
Coussens LM, Werb Z (2002) Inflammation and cancer. Nature 420:860-867
Cox A, Camp NJ, Nicklin MJ, di Giovine FS, Duff GW (1998) An analysis of linkage
disequilibrium in the interleukin-1 gene cluster, using a novel grouping
method for multiallelic markers. Am J Hum Genet 62:1180-1188
Crawford ED (2003) Epidemiology of prostate cancer. Urology 62:3-12
De Marzo AM, DeWeese TL, Platz EA, Meeker AK, Nakayama M, Epstein JI, Isaacs
WB, Nelson WG (2004) Pathological and molecular mechanisms of prostate
carcinogenesis: implications for diagnosis, detection, prevention, and
treatment. J Cell Biochem 91:459-477
De Marzo AM, Marchi VL, Epstein JI, Nelson WG (1999) Proliferative inflammatory
atrophy of the prostate: implications for prostatic carcinogenesis. Am J
Pathol 155:1985-1992
De Marzo AM, Meeker AK, Zha S, Luo J, Nakayama M, Platz EA, Isaacs WB,
Nelson WG (2003) Human prostate cancer precursors and pathobiology.
Urology 62:55-62
Dejager S, Mietus-Snyder M, Friera A, Pitas RE (1993) Dominant negative mutations of
the scavenger receptor. Native receptor inactivation by expression of
truncated variants. J Clin Invest 92:894-902
Dennis LK, Dawson DV (2002a) Meta-analysis of measures of sexual activity and prostate
cancer. Epidemiology 13:72-79
Dennis LK, Lynch CF, Torner JC (2002b) Epidemiologic association between prostatitis
and prostate cancer. Urology 60:78-83
Derynck R, Feng XH (1997) TGF-beta receptor signaling. Biochim Biophys Acta
1333:F105-F150
Dillner J, Knekt P, Boman J, Lehtinen M, Af Geijersstam V, Sapp M, Schiller J,
Maatela J, Aromaa A (1998) Sero-epidemiological association between
human-papillomavirus infection and risk of prostate cancer. Int J Cancer
75:564-567
Dinarello CA (1988) Biology of interleukin 1. FASEB J 2:108-115
Dinarello CA (1994) The interleukin-1 family: 10 years of discovery. FASEB J 8:1314-1325
Drachenberg DE (2000) Treatment of prostate cancer: watchful waiting, radical
prostatectomy, and cryoablation. Semin Surg Oncol 18:37-44
Prostate Cancer and Inflammatory Genes
67
Dumont N, Arteaga CL (2003) Targeting the TGF beta signaling network in human
neoplasia. Cancer Cell 3:531-536
El-Omar EM, Carrington M, Chow WH, McColl KE, Bream JH, Young HA, Herrera
J, Lissowska J, Yuan CC, Rothman N, Lanyon G, Martin M, Fraumeni
JF, Rabkin CS (2000) Interleukin-1 polymorphisms associated with
increased risk of gastric cancer. Nature 404:398-402
Fairlie WD, Moore AG, Bauskin AR, Russell PK, Zhang HP, Breit SN (1999) MIC-1 is
a novel TGF-beta superfamily cytokine associated with macrophage
activation. J Leukoc Biol 65:2-5
Fairlie WD, Russell PK, Wu WM, Moore AG, Zhang HP, Brown PK, Bauskin AR,
Breit SN (2001) Epitope mapping of the transforming growth factor-beta
superfamily protein, macrophage inhibitory cytokine-1 (MIC-1): identification
of at least five distinct epitope specificities. Biochemistry 40:65-73
Fallin D, Schork NJ (2000) Accuracy of haplotype frequency estimation for biallelic loci,
via the expectation-maximization algorithm for unphased diploid genotype
data. Am J Hum Genet 67:947-959
Feldman BJ, Feldman D (2001) The development of androgen-independent prostate
cancer. Nat Rev Cancer 1:34-45
Feneley MR, Young MP, Chinyama C, Kirby RS, Parkinson MC (1996) Ki-67
expression in early prostate cancer and associated pathological lesions. J Clin
Pathol 49:741-748
Fernández L, Galán Y, Jiménez R, Gutiérrez A, Guerra M, Pereda C, Alonso C, Riboli
E, Agudo A, González C (2005) Sexual behaviour, history of sexually
transmitted diseases, and the risk of prostate cancer: a case-control study in
Cuba. Int J Epidemiol 34:193-197
FRANKSLM (1954) Atrophy and hyperplasia in the prostate proper. J Pathol Bacteriol
68:617-621
Giles GG, Severi G, English DR, McCredie MR, Borland R, Boyle P, Hopper JL
(2003) Sexual factors and prostate cancer. BJU International 92:211-216
Glas J, Török HP, Schneider A, Brünnler G, Kopp R, Albert ED, Stolte M, Folwaczny
C (2004) Allele 2 of the interleukin-1 receptor antagonist gene is associated
with early gastric cancer. J Clin Oncol 22:4746-4752
Gough PJ, Greaves DR, Gordon S (1998) A naturally occurring isoform of the human
macrophage scavenger receptor (SR-A) gene generated by alternative splicing
blocks modified LDL uptake. J Lipid Res 39:531-543
Graichen R, Liu D, Sun Y, Lee KO, Lobie PE (2002) Autocrine human growth hormone
inhibits placental transforming growth factor-beta gene transcription to
prevent apoptosis and allow cell cycle progression of human mammary
carcinoma cells. J Biol Chem 277:26662-26672
Granowitz EV, Santos AA, Poutsiaka DD, Cannon JG, Wilmore DW, Wolff SM,
Dinarello CA (1991) Production of interleukin-1-receptor antagonist during
experimental endotoxaemia. Lancet 338:1423-1424
Grönberg H (2003) Prostate cancer epidemiology. Lancet 361:859-864
68
Prostate Cancer and Inflammatory Genes
Gsur A, Feik E, Madersbacher S (2004) Genetic polymorphisms and prostate cancer risk.
World J Urol 21:414-423
Haas GP, Sakr WA (1997) Epidemiology of prostate cancer. CA Cancer J Clin 47:273-287
Habermacher GM, Chason JT, Schaeffer AJ (2005) Prostatitis/Chronic Pelvic Pain
Syndrome. Annu Rev Med.
Hassel BA, Zhou A, Sotomayor C, Maran A, Silverman RH (1993) A dominant negative
mutant of 2-5A-dependent RNase suppresses antiproliferative and antiviral
effects of interferon. EMBO J 12:3297-3304
Hattersley AT, McCarthy MI (2005) What makes a good genetic association study? Lancet
366:1315-1323
Hayes RB, Pottern LM, Strickler H, Rabkin C, Pope V, Swanson GM, Greenberg RS,
Schoenberg JB, Liff J, Schwartz AG, Hoover RN, Fraumeni JF (2000)
Sexual behaviour, STDs and risks for prostate cancer. Br J Cancer 82:718-725
Hollstein M, Rice K, Greenblatt MS, Soussi T, Fuchs R, Sørlie T, Hovig E, SmithSørensen B, Montesano R, Harris CC (1994) Database of p53 gene
somatic mutations in human tumors and cell lines. Nucleic Acids Res
22:3551-3555
Holzbeierlein JM, McIntosh J, Thrasher JB (2005) The role of soy phytoestrogens in
prostate cancer. Current Opinion in Urology 15:17-22
Hood BL, Darfler MM, Guiel TG, Furusato B, Lucas DA, Ringeisen BR, Sesterhenn
IA, Conrads TP, Veenstra TD, Krizman DB (2005) Proteomic analysis of
formalin fixed prostate cancer tissue. Mol Cell Proteomics.
Howell WM, Calder PC, Grimble RF (2002) Gene polymorphisms, inflammatory diseases
and cancer. Proc Nutr Soc 61:447-456
Hromas R, Hufford M, Sutton J, Xu D, Li Y, Lu L (1997) PLAB, a novel placental bone
morphogenetic protein. Biochim Biophys Acta 1354:40-44
Hsing AW (2001) Hormones and prostate cancer: what's next? Epidemiol Rev 23:42-58
Hu Z, Shao M, Chen Y, Zhou J, Qian J, Xu L, Ma H, Wang X, Xu Y, Lu D, Shen H
(2005) Allele 2 of the interleukin-1 receptor antagonist gene (IL1RN*2) is
associated with a decreased risk of primary lung cancer. Cancer Lett
</Pagination><Ab-1 receptor antag
Hughes C, Murphy A, Martin C, Sheils O, O'Leary J (2005) Molecular pathology of
prostate cancer. J Clin Pathol 58:673-684
Irani J, Goujon JM, Ragni E, Peyrat L, Hubert J, Saint F, Mottet N (1999) High-grade
inflammation in prostate cancer as a prognostic factor for biochemical
recurrence after radical prostatectomy. Pathologist Multi Center Study
Group. Urology 54:467-472
Ishiguro T, Naito M, Yamamoto T, Hasegawa G, Gejyo F, Mitsuyama M, Suzuki H,
Kodama T (2001) Role of macrophage scavenger receptors in response to
Listeria monocytogenes infection in mice. Am J Pathol 158:179-188
Jaffee EM, Hruban RH, Canto M, Kern SE (2002) Focus on pancreas cancer. Cancer Cell
2:25-28
Jerónimo C, Usadel H, Henrique R, Oliveira J, Lopes C, Nelson WG, Sidransky D
(2001) Quantitation of GSTP1 methylation in non-neoplastic prostatic tissue
Prostate Cancer and Inflammatory Genes
69
and organ-confined prostate adenocarcinoma. J Natl Cancer Inst 93:17471752
Johnson GC, Esposito L, Barratt BJ, Smith AN, Heward J, Di Genova G, Ueda H,
Cordell HJ, Eaves IA, Dudbridge F, Twells RC, Payne F, Hughes W,
Nutland S, Stevens H, Carr P, Tuomilehto-Wolf E, Tuomilehto J,
Gough SC, Clayton DG, Todd JA (2001) Haplotype tagging for the
identification of common disease genes. Nat Genet 29:233-237
Jones PA, Baylin SB (2002) The fundamental role of epigenetic events in cancer. Nat Rev
Genet 3:415-428
Kannan K, Amariglio N, Rechavi G, Givol D (2000) Profile of gene expression regulated
by induced p53: connection to the TGF-beta family. FEBS Lett 470:77-82
Key TJ, Allen N, Appleby P, Overvad K, Tjønneland A, Miller A, Boeing H, Karalis
D, Psaltopoulou T, Berrino F, Palli D, Panico S, Tumino R, Vineis P,
Bueno-De-Mesquita HB, Kiemeney L, Peeters PH, Martinez C,
Dorronsoro M, González CA, Chirlaque MD, Quiros JR, Ardanaz E,
Berglund G, Egevad L, Hallmans G, Stattin P, Bingham S, Day N,
Gann P, Kaaks R, Ferrari P, Riboli E (2004) Fruits and vegetables and
prostate cancer: no association among 1104 cases in a prospective study of
130544 men in the European Prospective Investigation into Cancer and
Nutrition (EPIC). Int J Cancer 109:119-124
Klump B, Nehls O, Okech T, Hsieh CJ, Gaco V, Gittinger FS, Sarbia M, Borchard F,
Greschniok A, Gruenagel HH, Porschen R, Gregor M (2004) Molecular
lesions in colorectal cancer: impact on prognosis? Original data and review of
the literature. Int J Colorectal Dis 19:23-42
Ko LJ, Prives C (1996) p53: puzzle and paradigm. Genes Dev 10:1054-1072
Kodama T, Freeman M, Rohrer L, Zabrecky J, Matsudaira P, Krieger M (1990) Type I
macrophage scavenger receptor contains alpha-helical and collagen-like coiled
coils. Nature 343:531-535
Kolonel LN (2001) Fat, meat, and prostate cancer. Epidemiol Rev 23:72-81
Koopmann J, Buckhaults P, Brown DA, Zahurak ML, Sato N, Fukushima N, Sokoll
LJ, Chan DW, Yeo CJ, Hruban RH, Breit SN, Kinzler KW, Vogelstein
B, Goggins M (2004) Serum macrophage inhibitory cytokine 1 as a marker
of pancreatic and other periampullary cancers. Clinical Cancer Research
10:2386-2392
Kotar K, Hamel N, Thiffault I, Foulkes WD (2003) The RNASEL 471delAAAG allele
and prostate cancer in Ashkenazi Jewish men. J Med Genet 40:e22.
Kuper H, Adami HO, Trichopoulos D (2000) Infections as a major preventable cause of
human cancer. J Intern Med 248:171-183
Landström M, Zhang JX, Hallmans G, Aman P, Bergh A, Damber JE, Mazur W,
Wähäla K, Adlercreutz H (1998) Inhibitory effects of soy and rye diets on
the development of Dunning R3327 prostate adenocarcinoma in rats.
Prostate 36:151-161
Li PX, Wong J, Ayed A, Ngo D, Brade AM, Arrowsmith C, Austin RC, Klamut HJ
(2000) Placental transforming growth factor-beta is a downstream mediator
70
Prostate Cancer and Inflammatory Genes
of the growth arrest and apoptotic response of tumor cells to DNA damage
and p53 overexpression. J Biol Chem 275:20127-20135
Lichtenstein P, Holm NV, Verkasalo PK, Iliadou A, Kaprio J, Koskenvuo M, Pukkala
E, Skytthe A, Hemminki K (2000) Environmental and heritable factors in
the causation of cancer--analyses of cohorts of twins from Sweden, Denmark,
and Finland. N Engl J Med 343:78-85
Lin X, Tascilar M, Lee WH, Vles WJ, Lee BH, Veeraswamy R, Asgari K, Freije D,
van Rees B, Gage WR, Bova GS, Isaacs WB, Brooks JD, DeWeese TL,
De Marzo AM, Nelson WG (2001) GSTP1 CpG island hypermethylation is
responsible for the absence of GSTP1 expression in human prostate cancer
cells. Am J Pathol 159:1815-1826
Lindmark F, Zheng SL, Wiklund F, Bälter KA, Sun J, Chang B, Hedelin M, Clark J,
Johansson JE, Meyers DA, Adami HO, Isaacs W, Grönberg H, Xu J
(2005) Interleukin-1 receptor antagonist haplotype associated with prostate
cancer risk. Br J Cancer 93:493-497
Lindmark F, Zheng SL, Wiklund F, Bensen J, Bälter KA, Chang B, Hedelin M, Clark
J, Stattin P, Meyers DA, Adami HO, Isaacs W, Grönberg H, Xu J (2004)
H6D polymorphism in macrophage-inhibitory cytokine-1 gene associated
with prostate cancer. J Natl Cancer Inst 96:1248-1254
Lissbrant IF, Stattin P, Wikstrom P, Damber JE, Egevad L, Bergh A (2000) Tumor
associated macrophages in human prostate cancer: relation to
clinicopathological variables and survival. International Journal of Oncology
17:445-451
Liu T, Bauskin AR, Zaunders J, Brown DA, Pankhurst S, Russell PJ, Breit SN,
Panhurst S (2003) Macrophage inhibitory cytokine 1 reduces cell adhesion
and induces apoptosis in prostate cancer cells. Cancer Res 63:5034-5040
Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN (2003) Meta-analysis
of genetic association studies supports a contribution of common variants to
susceptibility to common disease. Nat Genet 33:177-182
Lucia MS, Torkko KC (2004) Inflammation as a target for prostate cancer
chemoprevention: pathological and laboratory rationale. J Urol 171:S30-4
discussion S35
Machado JC, Pharoah P, Sousa S, Carvalho R, Oliveira C, Figueiredo C, Amorim A,
Seruca R, Caldas C, Carneiro F, Sobrinho-Simões M (2001) Interleukin
1B and interleukin 1RN polymorphisms are associated with increased risk of
gastric carcinoma. Gastroenterology 121:823-829
Margaglione M, Santacroce R, Colaizzo D, Seripa D, Vecchione G, Lupone MR, De
Lucia D, Fortina P, Grandone E, Perricone C, Di Minno G (2000) A Gto-A mutation in IVS-3 of the human gamma fibrinogen gene causing
afibrinogenemia due to abnormal RNA splicing. Blood 96:2501-2505
Matsumoto A, Naito M, Itakura H, Ikemoto S, Asaoka H, Hayakawa I, Kanamori H,
Aburatani H, Takaku F, Suzuki H (1990) Human macrophage scavenger
Prostate Cancer and Inflammatory Genes
71
receptors: primary structure, expression, and localization in atherosclerotic
lesions. Proc Natl Acad Sci U S A 87:9133-9137
McArdle PA, Canna K, McMillan DC, McNicol AM, Campbell R, Underwood MA
(2004) The relationship between T-lymphocyte subset infiltration and survival
in patients with prostate cancer. Br J Cancer 91:541-543
McCarron SL, Edwards S, Evans PR, Gibbs R, Dearnaley DP, Dowe A, Southgate C,
Easton DF, Eeles RA, Howell WM (2002) Influence of cytokine gene
polymorphisms on the development of prostate cancer. Cancer Res 62:33693372
McIntyre KW, Stepan GJ, Kolinsky KD, Benjamin WR, Plocinski JM, Kaffka KL,
Campen CA, Chizzonite RA, Kilian PL (1991) Inhibition of interleukin 1
(IL-1) binding and bioactivity in vitro and modulation of acute inflammation
in vivo by IL-1 receptor antagonist and anti-IL-1 receptor monoclonal
antibody. J Exp Med 173:931-939
McNeal JE (1968) Regional morphology and pathology of the prostate. Am J Clin Pathol
49:347-357
McNeal JE (1988) Normal histology of the prostate. Am J Surg Pathol 12:619-633
Miller DC, Zheng SL, Dunn RL, Sarma AV, Montie JE, Lange EM, Meyers DA, Xu J,
Cooney KA (2003) Germ-line mutations of the macrophage scavenger
receptor 1 gene: association with prostate cancer risk in African-American
men. Cancer Res 63:3486-3489
Minami Y, Staples MP, Giles GG (1993) The incidence of colon, breast and prostate
cancer in Italian migrants to Victoria, Australia. Eur J Cancer 29A:1735-1740
MORGANTIG, GIANFERRARIL, CRESSERIA, ARRIGONIG, LOVATIG (1956)
[Clinico-statistical and genetic research on neoplasms of the prostate.]. Acta
Genetica et Statistica Medica 6:304-305
Nadler RB, Koch AE, Calhoun EA, Campbell PL, Pruden DL, Bennett CL, Yarnold
PR, Schaeffer AJ (2000) IL-1beta and TNF-alpha in prostatic secretions are
indicators in the evaluation of men with chronic prostatitis. J Urol 164:214218
Nakamura T, Scorilas A, Stephan C, Yousef GM, Kristiansen G, Jung K, Diamandis
EP (2003) Quantitative analysis of macrophage inhibitory cytokine-1 (MIC-1)
gene expression in human prostatic tissues. Br J Cancer 88:1101-1104
Nakayama M, Bennett CJ, Hicks JL, Epstein JI, Platz EA, Nelson WG, De Marzo
AM (2003) Hypermethylation of the human glutathione S-transferase-pi gene
(GSTP1) CpG island is present in a subset of proliferative inflammatory
atrophy lesions but not in normal or hyperplastic epithelium of the prostate: a
detailed study using laser-capture microdissection. Am J Pathol 163:923-933
Nelson CP, Kidd LC, Sauvageot J, Isaacs WB, De Marzo AM, Groopman JD, Nelson
WG, Kensler TW (2001) Protection against 2-hydroxyamino-1-methyl-6phenylimidazo[4,5-b]pyridine cytotoxicity and DNA adduct formation in
human prostate by glutathione S-transferase P1. Cancer Res 61:103-109
Nelson WG, De Marzo AM, Isaacs WB (2003) Prostate cancer. N Engl J Med 349:366381
72
Prostate Cancer and Inflammatory Genes
Nelson WG, DeWeese TL, DeMarzo AM (2002) The diet, prostate inflammation, and the
development of prostate cancer. Cancer Metastasis Rev 21:3-16
Ntais C, Polycarpou A, Ioannidis JP (2003) SRD5A2 gene polymorphisms and the risk of
prostate cancer: a meta-analysis. Cancer Epidemiol Biomarkers Prev 12:618624
Page WF, Braun MM, Partin AW, Caporaso N, Walsh P (1997) Heredity and prostate
cancer: a study of World War II veteran twins. Prostate 33:240-245
Palapattu GS, Sutcliffe S, Bastian PJ, Platz EA, De Marzo AM, Isaacs WB, Nelson
WG (2004) Prostate carcinogenesis and inflammation: emerging insights.
Carcinogenesis </Pagination><Ab-disciplinary bod
Paralkar VM, Vail AL, Grasser WA, Brown TA, Xu H, Vukicevic S, Ke HZ, Qi H,
Owen TA, Thompson DD (1998) Cloning and characterization of a novel
member of the transforming growth factor-beta/bone morphogenetic
protein family. J Biol Chem 273:13760-13767
Parkin DM, Bray F, Ferlay J, Pisani P (2005) Global cancer statistics, 2002. CA Cancer J
Clin 55:74-108
Parsons JK, Nelson CP, Gage WR, Nelson WG, Kensler TW, De Marzo AM (2001)
GSTA1 expression in normal, preneoplastic, and neoplastic human prostate
tissue. Prostate 49:30-37
Patel DA, Bock CH, Schwartz K, Wenzlaff AS, Demers RY, Severson RK (2005)
Sexually transmitted diseases and other urogenital conditions as risk factors
for prostate cancer: a case-control study in Wayne County, Michigan. Cancer
Causes Control 16:263-273
Pharoah PD, Dunning AM, Ponder BA, Easton DF (2004) Association studies for
finding cancer-susceptibility genetic variants. Nat Rev Cancer 4:850-860
Platt N, Gordon S (2001) Is the class A macrophage scavenger receptor (SR-A)
multifunctional? - The mouse's tale. J Clin Invest 108:649-654
Platz EA, De Marzo AM (2004) Epidemiology of inflammation and prostate cancer. J Urol
171:S36-S40
Pontari MA, Ruggieri MR (2004) Mechanisms in prostatitis/chronic pelvic pain syndrome.
J Urol 172:839-845
Putzi MJ, De Marzo AM (2000) Morphologic transitions between proliferative
inflammatory atrophy and high-grade prostatic intraepithelial neoplasia.
Urology 56:828-832
Rennert H, Bercovich D, Hubert A, Abeliovich D, Rozovsky U, Bar-Shira A, Soloviov
S, Schreiber L, Matzkin H, Rennert G, Kadouri L, Peretz T, Yaron Y,
Orr-Urtreger A (2002) A novel founder mutation in the RNASEL gene,
471delAAAG, is associated with prostate cancer in Ashkenazi Jews. Am J
Hum Genet 71:981-984
Rich AR (1979) Classics in oncology. On the frequency of occurrence of occult carcinoma
of the prostate: Arnold Rice Rich, M.D., Journal of Urology 33:3, 1935. CA
Cancer J Clin 29:115-119
Prostate Cancer and Inflammatory Genes
73
Roberts RO, Jacobson DJ, Girman CJ, Rhodes T, Lieber MM, Jacobsen SJ (2002) A
population-based study of daily nonsteroidal anti-inflammatory drug use and
prostate cancer. Mayo Clin Proc 77:219-225
Roberts RO, Lieber MM, Rhodes T, Girman CJ, Bostwick DG, Jacobsen SJ (1998)
Prevalence of a physician-assigned diagnosis of prostatitis: the Olmsted
County Study of Urinary Symptoms and Health Status Among Men. Urology
51:578-584
Rubin MA, De Marzo AM (2004) Molecular genetics of human prostate cancer. Mod
Pathol 17:380-388
Ruska KM, Sauvageot J, Epstein JI (1998) Histology and cellular kinetics of prostatic
atrophy. Am J Surg Pathol 22:1073-1077
Sakr WA, Grignon DJ, Crissman JD, Heilbrun LK, Cassin BJ, Pontes JJ, Haas GP
(1994) High grade prostatic intraepithelial neoplasia (HGPIN) and prostatic
adenocarcinoma between the ages of 20-69: an autopsy study of 249 cases. In
Vivo 8:439-443
Schaid DJ (2004) The complex genetic epidemiology of prostate cancer. Hum Mol Genet
13 Spec No 1:R103-R121
Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA (2002) Score tests for
association between traits and haplotypes when linkage phase is ambiguous.
Am J Hum Genet 70:425-434
Sehouli J, Mustea A, Koensgen D, Lichtenegger W (2003) Interleukin-1 receptor
antagonist gene polymorphism in epithelial ovarian cancer. Cancer Epidemiol
Biomarkers Prev 12:1205-1208
Seppälä EH, Ikonen T, Autio V, Rökman A, Mononen N, Matikainen MP, Tammela
TL, Schleutker J (2003) Germ-line alterations in MSR1 gene and prostate
cancer risk. Clinical Cancer Research 9:5252-5256
Shacter E, Weitzman SA (2002) Chronic inflammation and cancer. Oncology (Huntingt)
16:217-26 229 discussio
Shah R, Mucci NR, Amin A, Macoska JA, Rubin MA (2001) Postatrophic hyperplasia of
the prostate gland: neoplastic precursor or innocent bystander? Am J Pathol
158:1767-1773
Shimizu H, Ross RK, Bernstein L, Yatani R, Henderson BE, Mack TM (1991)
Cancers of the prostate and breast among Japanese and white immigrants in
Los Angeles County. Br J Cancer 63:963-966
Shirai H, Murakami T, Yamada Y, Doi T, Hamakubo T, Kodama T (1999) Structure
and function of type I and II macrophage scavenger receptors. Mech Ageing
Dev 111:107-121
Silverman RH (2003) Implications for RNase L in prostate cancer biology. Biochemistry
42:1805-1812
Simard J, Dumont M, Labuda D, Sinnett D, Meloche C, El-Alfy M, Berger L, Lees E,
Labrie F, Tavtigian SV (2003) Prostate cancer susceptibility genes: lessons
learned and challenges posed. Endocrine-Related Cancer 10:225-259
74
Prostate Cancer and Inflammatory Genes
Smith JR, Freije D, Carpten JD, Grönberg H, Xu J, Isaacs SD, Brownstein MJ, Bova
GS, Guo H, Bujnovszky P, Nusskern DR, Damber JE, Bergh A,
Emanuelsson M, Kallioniemi OP, Walker-Daniels J, Bailey-Wilson JE,
Beaty TH, Meyers DA, Walsh PC, Collins FS, Trent JM, Isaacs WB
(1996) Major susceptibility locus for prostate cancer on chromosome 1
suggested by a genome-wide search. Science 274:1371-1374
Stattin P, Bylund A, Rinaldi S, Biessy C, Déchaud H, Stenman UH, Egevad L, Riboli
E, Hallmans G, Kaaks R (2000) Plasma insulin-like growth factor-I, insulinlike growth factor-binding proteins, and prostate cancer risk: a prospective
study. J Natl Cancer Inst 92:1910-1917
Stattin P, Lumme S, Tenkanen L, Alfthan H, Jellum E, Hallmans G, Thoresen S,
Hakulinen T, Luostarinen T, Lehtinen M, Dillner J, Stenman UH,
Hakama M (2004) High levels of circulating testosterone are not associated
with increased prostate cancer risk: a pooled prospective study. Int J Cancer
108:418-424
Steinkasserer A, Spurr NK, Cox S, Jeggo P, Sim RB (1992) The human IL-1 receptor
antagonist gene (IL1RN) maps to chromosome 2q14-q21, in the region of
the IL-1 alpha and IL-1 beta loci. Genomics 13:654-657
Sun J, Wiklund F, Zheng SL, Chang B, Bälter K, Li L, Johansson JE, Li G, Adami
HO, Liu W, Tolin A, Turner AR, Meyers DA, Isaacs WB, Xu J,
Grönberg H (2005) Sequence variants in Toll-like receptor gene cluster
(TLR6-TLR1-TLR10) and prostate cancer risk. J Natl Cancer Inst 97:525-532
Tan JK, Png DJ, Liew LC, Li MK, Wong ML (2002) Prevalence of prostatitis-like
symptoms in Singapore: a population-based study. Singapore Med J 43:189193
Tan M, Wang Y, Guan K, Sun Y (2000) PTGF-beta, a type beta transforming growth
factor (TGF-beta) superfamily member, is a p53 target gene that inhibits
tumor cell growth via TGF-beta signaling pathway. Proc Natl Acad Sci U S A
97:109-114
Tarlow JK, Blakemore AI, Lennard A, Solari R, Hughes HN, Steinkasserer A, Duff
GW (1993) Polymorphism in human IL-1 receptor antagonist gene intron 2 is
caused by variable numbers of an 86-bp tandem repeat. Hum Genet 91:403404
Taylor ML, Mainous AG, Wells BJ (2005) Prostate cancer and sexually transmitted
diseases: a meta-analysis. Fam Med 37:506-512
Thomas CA, Li Y, Kodama T, Suzuki H, Silverstein SC, El Khoury J (2000) Protection
from lethal gram-positive infection by macrophage scavenger receptordependent phagocytosis. J Exp Med 191:147-156
Thomas R, True LD, Lange PH, Vessella RL (2001) Placental bone morphogenetic
protein (PLAB) gene expression in normal, pre-malignant and malignant
human prostate: relation to tumor development and progression. Int J Cancer
93:47-52
Prostate Cancer and Inflammatory Genes
75
Tsujimoto Y, Takayama H, Nonomura N, Okuyama A, Aozasa K (2002) Postatrophic
hyperplasia of the prostate in Japan: histologic and immunohistochemical
features and p53 gene mutation analysis. Prostate 52:279-287
van Leenders GJ, Gage WR, Hicks JL, van Balken B, Aalders TW, Schalken JA, De
Marzo AM (2003) Intermediate cells in human prostate epithelium are
enriched in proliferative inflammatory atrophy. Am J Pathol 162:1529-1537
Wall JD, Pritchard JK (2003) Haplotype blocks and linkage disequilibrium in the human
genome. Nat Rev Genet 4:587-597
Wang L, McDonnell SK, Cunningham JM, Hebbring S, Jacobsen SJ, Cerhan JR,
Slager SL, Blute ML, Schaid DJ, Thibodeau SN (2003) No association of
germline alteration of MSR1 with prostate cancer risk. Nat Genet 35:128-129
Wang L, McDonnell SK, Elkins DA, Slager SL, Christensen E, Marks AF,
Cunningham JM, Peterson BJ, Jacobsen SJ, Cerhan JR, Blute ML,
Schaid DJ, Thibodeau SN (2002) Analysis of the RNASEL gene in familial
and sporadic prostate cancer. Am J Hum Genet 71:116-123
Weir BS (1996) Anonymous Genetic data analysis II. Sinauer, Sunderland (MA)
Welsh JB, Sapinoso LM, Kern SG, Brown DA, Liu T, Bauskin AR, Ward RL,
Hawkins NJ, Quinn DI, Russell PJ, Sutherland RL, Breit SN,
Moskaluk CA, Frierson HF, Hampton GM (2003) Large-scale delineation
of secreted protein biomarkers overexpressed in cancer tissue and serum.
Proc Natl Acad Sci U S A 100:3410-3415
Welsh JB, Sapinoso LM, Su AI, Kern SG, Wang-Rodriguez J, Moskaluk CA, Frierson
HF, Hampton GM (2001) Analysis of gene expression identifies candidate
markers and pharmacological targets in prostate cancer. Cancer Res 61:59745978
Wiklund F, Jonsson BA, Brookes AJ, Strömqvist L, Adolfsson J, Emanuelsson M,
Adami HO, Augustsson-Bälter K, Grönberg H (2004) Genetic analysis of
the RNASEL gene in hereditary, familial, and sporadic prostate cancer.
Clinical Cancer Research 10:7150-7156
Wiseman H, Halliwell B (1996) Damage to DNA by reactive oxygen and nitrogen species:
role in inflammatory disease and progression to cancer. Biochem J 313:17-29
Witkin SS, Gerber S, Ledger WJ (2002) Influence of interleukin-1 receptor antagonist gene
polymorphism on disease. Clin Infect Dis 34:204-209
Wollmann W, Goodman ML, Bhat-Nakshatri P, Kishimoto H, Goulet RJ, Mehrotra
S, Morimiya A, Badve S, Nakshatri H (2005) The macrophage inhibitory
cytokine integrates AKT/PKB and MAP kinase signaling pathways in breast
cancer cells. Carcinogenesis 26:900-907
Wu MS, Wu CY, Chen CJ, Lin MT, Shun CT, Lin JT (2003) Interleukin-10 genotypes
associate with the risk of gastric carcinoma in Taiwanese Chinese. Int J
Cancer 104:617-623
Xiao W, Oefner PJ (2001) Denaturing high-performance liquid chromatography: A review.
Hum Mutat 17:439-474
76
Prostate Cancer and Inflammatory Genes
Xu J, Lowey J, Wiklund F, Sun J, Lindmark F, Hsu FC, Dimitrov L, Chang B, Turner
AR, Liu W, Adami HO, Suh E, Moore JH, Zheng SL, Isaacs WB, Trent
JM, Grönberg H (2005) The interaction of four genes in the inflammation
pathway significantly predicts prostate cancer risk. Cancer Epidemiol
Biomarkers Prev 14:2563-2568
Xu J, Zheng SL, Hawkins GA, Faith DA, Kelly B, Isaacs SD, Wiley KE, Chang B,
Ewing CM, Bujnovszky P, Carpten JD, Bleecker ER, Walsh PC, Trent
JM, Meyers DA, Isaacs WB (2001) Linkage and association studies of
prostate cancer susceptibility: evidence for linkage at 8p22-23. Am J Hum
Genet 69:341-350
Xu J, Zheng SL, Komiya A, Mychaleckyj JC, Isaacs SD, Chang B, Turner AR, Ewing
CM, Wiley KE, Hawkins GA, Bleecker ER, Walsh PC, Meyers DA,
Isaacs WB (2003) Common sequence variants of the macrophage scavenger
receptor 1 gene are associated with prostate cancer risk. Am J Hum Genet
72:208-212
Xu J, Zheng SL, Komiya A, Mychaleckyj JC, Isaacs SD, Hu JJ, Sterling D, Lange
EM, Hawkins GA, Turner A, Ewing CM, Faith DA, Johnson JR,
Suzuki H, Bujnovszky P, Wiley KE, DeMarzo AM, Bova GS, Chang B,
Hall MC, McCullough DL, Partin AW, Kassabian VS, Carpten JD,
Bailey-Wilson JE, Trent JM, Ohar J, Bleecker ER, Walsh PC, Isaacs
WB, Meyers DA (2002) Germline mutations and sequence variants of the
macrophage scavenger receptor 1 gene are associated with prostate cancer
risk. Nat Genet 32:321-325
Zeng ZR, Hu PJ, Hu S, Pang RP, Chen MH, Ng M, Sung JJ (2003) Association of
interleukin 1B gene polymorphism and gastric cancers in high and low
prevalence regions in China. Gut 52:1684-1689
Zha S, Yegnasubramanian V, Nelson WG, Isaacs WB, De Marzo AM (2004)
Cyclooxygenases in cancer: progress and perspective. Cancer Lett 215:1-20
Zheng SL, Augustsson-Bälter K, Chang B, Hedelin M, Li L, Adami HO, Bensen J, Li
G, Johnasson JE, Turner AR, Adams TS, Meyers DA, Isaacs WB, Xu J,
Grönberg H (2004) Sequence variants of toll-like receptor 4 are associated
with prostate cancer risk: results from the CAncer Prostate in Sweden Study.
Cancer Res 64:2918-2922
`