Cyclin D1 G870A polymorphism contributes to colorectal cancer susceptibility: evidence from a systematic review of 22 case-control studies.

Abstract

Cyclin D1 (CCND1) plays a vital role in cancer cell cycle progression. Numerous epidemiological studies have evaluated the association between the CCND1 G870A polymorphism and the risk of colorectal cancer. However, these studies have yielded conflicting results. To derive a more precise estimation of this association, we conducted a meta-analysis and systematic review.
A comprehensive search was conducted to identify eligible studies of the CCND1 G870A polymorphism and colorectal cancer risk. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were derived from a fixed effect or random effect model. We applied a grading system (Venice criteria) that assessed the epidemiological strength of the association. A total of 22 publications that included 6157 cases and 8198 controls were identified. We found that the CCND1 G870A polymorphism was significantly associated with overall colorectal cancer risk (homozygote genetic model: OR = 1.130, 95% CI = 1.023-1.248, P = 0.016; heterozygote genetic model: OR = 1.124, 95% CI = 1.030-1.226, P = 0.009; dominant genetic model: OR = 1.127, 95% CI = 1.037-1.224, P = 0.005). After further stratified analyses, the increased risk was observed only in the subgroups of hospital-based studies, PCR-RFLP genotyping methods, sporadic colorectal cancer, and Caucasian ethnicity.
The available evidence demonstrates that the CCND1 870A allele might be a low-penetrant risk factor for colorectal cancer.

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Cyclin D1 G870A Polymorphism Contributes to
Colorectal Cancer Susceptibility: Evidence from a
Systematic Review of 22 Case-Control Studies
Yongzhi Yang1,2, Feng Wang1, Chenzhang Shi2, Yang Zou2, Huanlong Qin1*, Yanlei Ma1*
1Department of Surgery, Shanghai Tenth People’s Hospital affiliated with Tongji University, Shanghai, People’s Republic of China, 2Department of Surgery, The Sixth
People’s Hospital affiliated with Shanghai Jiao Tong University, Shanghai, People’s Republic of China
Abstract
Background: Cyclin D1 (CCND1) plays a vital role in cancer cell cycle progression. Numerous epidemiological studies have
evaluated the association between the CCND1 G870A polymorphism and the risk of colorectal cancer. However, these
studies have yielded conflicting results. To derive a more precise estimation of this association, we conducted a meta-
analysis and systematic review.
Methodology/Principal Findings: A comprehensive search was conducted to identify eligible studies of the CCND1 G870A
polymorphism and colorectal cancer risk. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were derived from a
fixed effect or random effect model. We applied a grading system (Venice criteria) that assessed the epidemiological
strength of the association. A total of 22 publications that included 6157 cases and 8198 controls were identified. We found
that the CCND1 G870A polymorphism was significantly associated with overall colorectal cancer risk (homozygote genetic
model: OR=1.130, 95% CI=1.023–1.248, P=0.016; heterozygote genetic model: OR=1.124, 95% CI=1.030–1.226, P=0.009;
dominant genetic model: OR=1.127, 95% CI=1.037–1.224, P=0.005). After further stratified analyses, the increased risk was
observed only in the subgroups of hospital-based studies, PCR-RFLP genotyping methods, sporadic colorectal cancer, and
Caucasian ethnicity.
Conclusions: The available evidence demonstrates that the CCND1 870A allele might be a low-penetrant risk factor for
colorectal cancer.
Citation: Yang Y, Wang F, Shi C, Zou Y, Qin H, et al. (2012) Cyclin D1 G870A Polymorphism Contributes to Colorectal Cancer Susceptibility: Evidence from a
Systematic Review of 22 Case-Control Studies. PLoS ONE 7(5): e36813. doi:10.1371/journal.pone.0036813
Editor: Amanda Ewart Toland, Ohio State University Medical Center, United States of America
Received January 27, 2012; Accepted April 6, 2012; Published May 11, 2012
Copyright: ? 2012 Yang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was financially sponsored by Shanghai Rising-Star Program (No.11QA1404800), grants from the National Natural Science Foundation of China
(No.81001069) and the National 863 High Technology Foundation (No.2009AA02Z118). The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: yanleima@live.cn (YLM); hl-qin@hotmail.com (HLQ)
Introduction
Colorectal cancer (CRC) is the second most common type of
cancer in women and the third most common type in men in the
United States and Europe [1,2]. The multistep carcinogenesis of
the adenoma-carcinoma sequence is determined by caretaker
molecular pathways, and this conventional theory is also thought
to describe colorectal oncogenesis [3,4]. However, it is now
commonly accepted that the pathogenesis of CRC involves the
multi-factorial interactions of environmental triggers and genetic
susceptibility [5]. A recent study have revealed that approximately
35% of CRC cases can be attributed to inherited genetic
susceptibility [5].
The adenine-to-guanine (A/G) substitution at nucleotide 870
(CCND1 G870A polymorphism, rs603965) and excessive cyclin D1
activity are common in numerous human tumors, including breast
cancer, lung cancer, head and neck cancers, gastric cancer,
gynecological cancers, blood-related cancers, and CRC [6,7].
Although various studies have linked the CCND1 G870A
polymorphism to increased CRC risk, the results remain
controversial. To further investigate the combined effect of the
CCND1 G870A polymorphism on CRC susceptibility, we
performed a meta-analysis and systematic review.
Methods
Identification and Eligibility of Relevant Studies
All published literature investigating an association between the
CCND1 G870A polymorphism and colorectal cancer risk were
eligible. We searched for studies using the PubMed database up to
October 2011. The relevant search terms ‘‘G870A’’, ‘‘A870G’’,
‘‘CCND1’’, ‘‘cyclin D1’’, ‘‘polymorphism’’, ’’cancer’’, ‘‘colorectal’’,
‘‘colonic’’, ‘‘colon’’, ‘‘rectal’’, ‘‘rectum’’, and ‘‘humans’’ were used.
Both free text and a MeSH search for keywords were employed.
We also manually searched the reference lists in selected articles
and the abstracts published at major international conferences.
Abstracts that were not written in English were excluded. All the
studies met the following criteria: (1) the CCND1 G870A
polymorphism was determined; (2) the outcome had to be
colorectal cancer in humans. The major exclusion criteria were
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(1) reviews, tutorials, letters, and editorials; (2) duplicate data; (3)
not a case-control design; (4) insufficient data were reported as
cyclin D1 expression levels were provided without genotype data;
(5) overlapping data and data superseded by the latest reports.
Data Extraction
Data were extracted independently and crosschecked against
the research consensus. The following variables were recorded: the
first author’s last name; publication year; region/country where
the study was performed; participant gender; ethnicity (included
Caucasian, Asian and Mixed) of the study population; epidemi-
ological type of colorectal cancer (included hereditary nonpolyp-
osis colorectal cancer (HNPCC), sporadic colorectal cancer
(sCRC), and sporadic colonic cancer (sCC)); histopathological
subgroup information if known (included Dukes’ stage (A/B and
C/D) and degree of differentiation (well/moderate, moderate and
poor)); control source (family-based study (FB), population-based
study (PB), and hospital-based study (HB)); genotyping method
(polymerase chain reaction (PCR) single-stranded conformation
polymorphism (PCR-SSCP), PCR restriction fragment length
polymorphism (PCR-RFLP), high-performance liquid chromatog-
raphy (HPLC), TaqMan PCR, and DNA sequencing); sample size
(total cases and controls as well as the numbers of cases and
controls with G/G, G/A, and A/A genotypes); and the P value of
the Hardy-Weinberg equilibrium in the control group. Only the
latest studies were included when the data sets overlapped or were
duplicated. The primary authors were contacted to provide
additional information when necessary. Study identification and
data extraction were conducted independently by three investiga-
tors and checked for accuracy by one author.
Statistical Analysis
Dichotomous variables were pooled using an odds ratio (OR).
The summary OR was replaced by the risk difference (RD) if one
of the studies reported no events in either the case group or the
control group.
The wild type G/G genotype was considered as a reference.
Pooled effects were calculated for a homozygote comparison
model (A/A vs. G/G), a heterozygote comparison model (G/A vs.
G/G), a dominant model (G/A+A/A vs. G/G), and a recessive
model (A/A vs. G/G+G/A).
The statistical heterogeneity between included studies was
determined using the chi-square-based Q-test [8,9]. According to
the Higgins’ I2statistic, heterogeneity was defined as low or
moderate if less than 50% and high if greater than 50% [8]. A
fixed effect model was applied using the Mantel-Haenszel method
for low or moderate statistical heterogeneous studies [10]. A
random effect model, which assumed that the studies involved
came from a random sample of a hypothetical population of
studies that took into account heterogeneity, was used when
heterogeneity was high [11]. A Galbraith plot was created to
graphically assess the extent of heterogeneity between studies from
the current meta-analysis [12,13]. A L’Abbe ´ plot was used for the
additionally assessment of colorectal cancer risk [14,15]. The
Hardy-Weinberg equilibrium (HWE) was determined using
the chi-square test in the control groups [16].
Sensitivity analyses were conducted either by replacing a value
of effect with another or removing individual studies from the data
set. Sensitivity analyses were also performed by excluding studies
in which the genotype frequencies in the controls significantly
deviated from the HWE. We conducted subgroup analyses of the
study design, cancer type, cancer location, ethnicity, Dukes’ stage,
degree of differentiation, gender and genotyping method to
investigate potential sources of heterogeneity.
Publication bias among the included studies was assessed
graphically using a Begg’s funnel plot [17]. Additionally,
publication bias was also evaluated statistically with an Egger’s
test [18].
The study confidence interval (CI) was established at 95%.
Two-tailed P values of less than 0.05 were considered statistically
significant. All statistical analyses were performed using the
STATA version 11.0 software (Stata Corporation, College Station,
TX).
Assessment of Cumulative Evidence
The Venice criteria [19] were developed by the Human
Genome Epidemiology Network (HuGENet) Working Group to
assess the cumulative epidemiological strength of genetic associ-
ation studies; these same criteria were applied in this study.
Following the Venice criteria, our meta-analysis was graded based
on three categories: (1) the amount of evidence (sample sizes of
cases and controls that were greater than 1000, 100–1000, or less
than 100 were assigned a grade of A, B, or C, respectively); (2) the
extent of replication (a Higgins’ I2statistic [8] that was less than
25%, 25% – 50% or greater than 50% was assigned a grade of A,
B, or C, respectively); (3) protection from bias (a grade of A was
assigned if there was no observable bias, a grade of B was assigned
if bias could be present or could explain the presence of the
association; a grade of C was assigned if bias was considerable and
had an effect even the presence or absence of the association).
Results
Characteristics of the Studies
Through literature search and selection, a total of 22 publications
[20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,-
41] including 6157 cases and 8198 controls comparing the CCND1
G870A polymorphism and colorectal cancer susceptibility were
identified based on MOOSE (Meta-analysis Of Observational
Studies in Epidemiology) guidelines [42]. Two studies [24,35]
investigated both HNPCC and sCRC, and the genotype frequen-
cies were therefore separated into three types: Mixed, HNPCC, and
sCRC. One article [26] mentioned two independent populations
(Asians and Caucasians), and the study was thus treated as three
separate estimates: Mixed, Asians, and Caucasians. A flow chart of
the inclusion and exclusion criteria is presented in Figure 1.
Five articles [20,26,34,37,39] showed mixed or missing ethnicity
data.Ninestudies[24,30,32,33,34,35,37,40,41]showedmixedtypesof
cancer data. Of the 22 included studies, 2 were family-based [20,22],
11 were population-based [21,23,24,26,28,31,32,33,37,38,40], and 9
were hospital-based [25,27,29,30,34,35,36,39,41]. Multiple genotyp-
ing methods were employed in the studies and included PCR-RFLP,
PCR-SSCP, HLC, TaqMan PCR, and DNA sequencing. The
distribution of genotypes in the controls of all studies was consistent
with Hardy-Weinberg equilibrium except in one study [29].
Characteristics of the studies included are summarized in Table 1.
Heterogeneity Analysis
The genotype data in the 22 studies were homogenous for the
heterozygote genetic model (G/A vs. G/G: Q-test=23.65,
P=0.310, I2=11.20) and the dominant genetic model (G/A+A/
A vs. G/G: Q-test=27.93, P=0.142, I2=24.80), but heteroge-
neity was significant for the homozygote genetic model (A/A vs.
G/G: Q-test=39.53, P=0.008, I2=46.90) and the recessive
genetic model (A/A vs. G/G+G/A: Q-test=27.93, P=0.142,
I2=52.70).
Galbraith plot analyses of all included studies were used to
assess the potential sources of heterogeneity. Two studies [20,41]
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were found to be contributors of heterogeneity in the homozygote
comparison model (Figure 2).
Association of the CCND1 G870A Polymorphism with CRC
Susceptibility
The multivariable-adjusted ORs for each study and the OR for
the combination of all the studies are shown in Table 2; these
ORs were used to determine the association of the G870A
polymorphism with CRC susceptibility. A significant association of
the G870A polymorphism with CRC susceptibility was observed
in the homozygote comparison model, the heterozygote compar-
ison model, and the dominant model when all the studies were
considered (A/A vs. G/G: OR=1.130, 95% CI=1.023–1.248,
P=0.016; G/A vs. G/G: OR=1.124, 95% CI=1.030–1.226,
P=0.009; G/A+A/A vs. G/G: OR=1.127, 95% CI=1.037–
1.224, P=0.005), However, the association was not observed in
the recessive genetic model (A/A vs. G/G+G/A: OR=1.067,
95% CI=0.941–1.210, P=0.311).
Stratifying Analyses
We conducted subgroup analyses, and the results are listed in
Table 2. Additionally, the L’Abbe ´ plot was also used to assess the
CRC risk in each group in all included studies (Figure 3).
Significant association of the CCND1 G870A polymorphism
with CRC risk was observed in many subgroup categories,
including subsets of hospital-based studies (A/A vs. G/G:
OR=1.260, 95% CI=1.072–1.482, P=0.005; G/A vs. G/G:
OR=1.249, 95% CI=1.082–1.442, P=0.002; G/A+A/A vs. G/
G: OR=1.252, 95% CI=1.093–1.433, P=0.001), subsets of
sCRC cases (G/A vs. G/G: OR=1.204, 95% CI=1.053–1.376,
P=0.007; G/A+A/A vs. G/G: OR=1.188, 95% CI=1.046–
1.348, P=0.008), subsets of Caucasian ethnicity (G/A vs. G/G:
OR=1.145, 95% CI=1.004–1.306, P=0.043; G/A+A/A vs. G/
G: OR=1.162, 95% CI=1.026–1.316, P=0.018), subsets of
Duke’s stage C/D (A/A vs. G/G: OR=1.275, 95% CI=1.007–
1.613, P=0.043; G/A vs. G/G: OR=1.365, 95% CI=1.097–
1.698, P=0.005), subsets of the well/moderate degree of
differentiation (G/A+A/A vs.
CI=1.063–1.682, P=0.013), male subjects (G/A vs. G/G:
OR=1.393, 95% CI=1.073–1.809, P=0.013; G/A+A/A vs.
G/G: OR=1.359, 95% CI=1.080–1.710, P=0.009), and subsets
ofthe PCR-RFLPgenotyping
OR=1.262, 95% CI=1.126–1.415, P,0.001; G/A vs. G/G:
OR=1.190, 95% CI=1.076–1.315, P=0.001; G/A+A/A vs. G/
G: OR=1.216, 95% CI=1.106–1.337, P,0.001). Specifically,
the subgroup of Caucasian ethnicity was associated with 1.3- to
G/G:OR=1.337, 95%
method (A/Avs. G/G:
Figure 1. Flow chart of study selection according to MOOSE guidelines [42].
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Table 1. Characteristics of the studies included in the meta-analysis.
First author (Year)
Country
Ethnicity
Type of
cancer
Source of
controls
Genotyping
method
Total, N
GG genotype, N
GA genotype, N
AA genotype, N
HWE
Reference
Cases
Controls
Cases
Controls
Cases
Controls
Cases
Controls
Kong (2000)
US
Mixed
HNPCC
FB
PCR-SSCP
49
37
9
10
36
21
4
6
0.51
[20]
McKay (2000)
UK
Caucasian
sCRC
PB
PCR-RFLP
100
101
25
34
58
50
17
17
0.849
[21]
Bala (2001)
Finland
Caucasian
HNPCC
FB
PCR-SSCP
146
186
50
47
70
97
26
42
0.551
[22]
Kong (2001)
US
Caucasian
sCRC
PB
PCR-SSCP
156
152
36
45
71
84
49
23
0.112
[20]
Porter (2002)
UK
Caucasian
Mixed
PB
PCR-RFLP
334
171
85
60
175
81
74
30
0.768
[24]
Porter (2002)
UK
Caucasian
HNPCC
PB
PCR-RFLP
99
171
30
60
47
81
22
30
0.768
[24]
Porter (2002)
UK
Caucasian
sCRC
PB
PCR-RFLP
128
171
34
60
65
81
29
30
0.768
[24]
Grieu (2003)
Australia
Caucasian
sCRC
HB
PCR-SSCP
569
327
142
90
313
158
114
79
0.556
[25]
Le Marchand (2003)
US
Mixed
Mixed
PB
PCR-RFLP
504
624
109
164
253
315
142
145
0.792
[26]
Le Marchand (2003)
US
Caucasian
sCRC
PB
PCR-RFLP
138
161
29
50
75
85
34
26
0.311
[26]
Le Marchand (2003)
US
Asian
sCRC
PB
PCR-RFLP
296
380
75
96
143
195
78
89
0.603
[26]
Lewis (2003)
US
Caucasian
sCRC
HB
PCR-RFLP
161
213
51
84
84
98
26
31
0.781
[27]
Hong (2005)
Singapore
Asian
sCRC
PB
PCR-RFLP
254
101
55
12
128
50
71
39
0.505
[28]
Huang (2006)
Taiwan
Asian
sCRC
HB
PCR-RFLP
831
1052
126
199
411
464
294
389
0.004
[29]
Jiang (2006)
India
Asian
Mixed
HB
PCR-RFLP
301
291
46
56
130
145
125
90
0.86
[30]
Kruger (2006)
Germany
Caucasian
HNPCC
PB
Multiplex PCR
315
245
110
73
144
121
61
51
0.947
[31]
Probst-Hensch (2006)
Singapore
Asian
Mixed
PB
TaqMan PCR
300
1169
56
207
132
548
112
414
0.272
[32]
Schernhammer (2006)
US
Caucasian
Mixed
PB
TaqMan PCR
610
1237
125
264
311
593
174
380
0.25
[33]
Forones (2008)
Brazil
Mixed
Mixed
HB
PCR-RFLP
123
120
36
34
66
67
21
19
0.141
[34]
Grunhage (2008)
Germany
Caucasian
Mixed
HB
PCR-RFLP
194
218
37
48
93
109
64
61
0.958
[35]
Grunhage (2008)
Germany
Caucasian
HNPCC
HB
PCR-RFLP
98
218
13
48
50
109
35
61
0.958
[35]
Grunhage (2008)
Germany
Caucasian
sCRC
HB
PCR-RFLP
96
218
24
48
43
109
29
61
0.958
[35]
Talseth (2008)
Australia/Poland Caucasian
HNPCC
HB
TaqMan PCR
157
153
34
42
78
80
45
31
0.527
[36]
Tan (2008)
Germany
Mixed
Mixed
PB
PCR-RFLP
498
600
120
147
263
310
115
143
0.414
[37]
Jelonek (2010)
Poland
Caucasian
sCC
PB
PCR-RFLP
50
153
12
44
33
71
5
38
0.383
[38]
Kanaan (2010)
US
NS
sCRC
HB
PCR-HLC
75
93
19
24
39
48
17
21
0.748
[39]
Liu (2010)
China
Asian
Mixed
PB
PCR-RFLP
373
838
66
160
187
429
120
249
0.303
[40]
Yaylim-Eraltan (2010)
Turkey
Caucasian
Mixed
HB
PCR-RFLP
57
117
9
29
28
60
20
28
0.781
[41]
HWE: Hardy–Weinberg equilibrium; US: United States; UK: United Kingdom; HNPCC: hereditary nonpolyposis colorectal cancer; sCRC: sporadic colorectal cancer; sCC: sporadic colonic cancer; FB: family-based study; PB: population-
based study; HB: hospital-based study; PCR: polymerase chain reaction; SSCP: single-stranded conformation polymorphism; RFLP: restriction fragment length polymorphism; HPLC: high-performance liquid chromatography.
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1.5-fold increased risk of sCRC without heterogeneity (A/A vs. G/
G: OR=1.511, 95% CI=1.158–1.972, P=0.002; G/A vs. G/G:
OR=1.307, 95% CI=1.057–1.617, P=0.014; G/A+A/A vs. G/
G: OR=1.369, 95% CI=1.118–1.676, P=0.002) (Table 2).
Sensitivity Analyses
Sensitivity analyses was performed by omitting one study at a
time. This procedure did not influence the pooled value, which
supports the robustness of this current meta-analysis.
Publication Bias Analysis
The Begg’s funnel plot and the Egger’s test (A/A vs. G/G:
P=0.465; G/A vs. G/G: P=0.731; G/A+A/A vs. G/G:
P=0.516; A/A vs. G/G+G/A: P=0.399) showed no evidence
of publication bias (Figure 4).
Assessment of Cumulative Evidence
We applied the Venice criteria [19] to evaluate the overall
evidence of an association between the CCND1 G870A polymor-
phism and colorectal cancer susceptibility. The total sample size
(6157 cases and 8198 controls) in our meta-analysis exceeded
1000. Therefore, we assigned the amount of evidence category an
A grade. Next, we assessed the extent of replication. Our meta-
analysis showed a significantly increased risk of colorectal cancer
in the homozygote genetic model, the heterozygote genetic model
and the dominant genetic model but not in the recessive model in
any category. We observed minimal heterogeneity in the
heterozygote genetic model and the dominant genetic model
and moderate heterogeneity in the heterozygote genetic model.
Therefore, we assigned a B grade for the extent of replication.
Finally, there was no evidence of publication bias in our pooled
data, and most of the included studies were well matched for race,
ethnicity, gender and age. The summary ORs of each genetic
model were greater than 1.15; therefore, bias could not have easily
rendered the observed association. Nevertheless, most studies did
not publish sufficient information about whether the G870A
polymorphism was relevant to other polymorphisms or other
candidate genes. Therefore, the Venice criterion of protection
from bias was given a B grade. The overall grade of the Venice
criteria for our data was ‘‘ABB’’, which is consistent with moderate
evidence demonstrating the linkage between the G870A polymor-
phism and colorectal cancer risk.
Discussion
Cell cycle regulation plays an important role in the evolution of
cancer by influencing cell proliferation, differentiation and
apoptosis [43]. It has been demonstrated in all eukaryotic
organisms that the transition from the G1 phase to the S phase
of the cell cycle is controlled by sequential activation of cyclin/
cyclin-dependent kinase (Cdk) complexes [44]. The cyclin D1
locus (also called CCND1 or PRAD1, located on 11q13) consists of
five exons and four introns and encodes cyclin D, a key regulatory
protein promoting the transition through the restriction point in
the G1 phase [45]. Over 250 single nucleotide polymorphisms
(SNP) spanning CCND1 have been identified and cataloged in
public SNP databases (dbSNP: www.ncbi.nlm.nih.gov/SNP/;
HapMap: www.hapmap.org). Of the polymorphisms identified,
the common adenine-to-guanine (A/G) substitution at nucleotide
870 in the conserved splice donor region of exon 4 has received
the most investigation [6]. Normally, the G870 allele creates an
optimal splice donor site and results in a well-described transcript
for cyclin D1, termed cyclin D1a; however, the CCND1 G870A
Figure 2. Galbraith plot [12] analysis of the amount of heterogeneity from all the included studies (AA vs. GG). The y-axis shows the
ratio of the log OR to its standard error (SE), and the x-axis shows the reciprocal of the SE. Each study is represented by the name of the first author. A
regression line runs centrally through the name. At a 2 standard deviation distance parallel to the regression line, the 2 lines create an interval.
Studies lacking in heterogeneity would lie within the 95% confidence interval (positioned 2 units above and below the central regression line).
doi:10.1371/journal.pone.0036813.g002
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