Skip to main content
PMC home page
BMC Cancer logoLink to BMC Cancer
. 2009 Oct 26;9:379. doi: 10.1186/1471-2407-9-379

Association between an 8q24 locus and the risk of colorectal cancer in Japanese

Keitaro Matsuo 1,6,✉, Takeshi Suzuki 7, Hidemi Ito 1, Satoyo Hosono 1, Takakazu Kawase 1, Miki Watanabe 1, Kohei Shitara 3, Koji Komori 4, Yukihide Kanemitsu 4, Takashi Hirai 4, Yasushi Yatabe 5, Hideo Tanaka 1,6, Kazuo Tajima 2
PMCID: PMC2783039  PMID: 19857256

Abstract

Background

A genome-wide association study (GWAS), which assessed multiple ethnicities, reported an association between single nucleotide polymorphisms in the 8q24 region and colorectal cancer risk. Although the association with the identified loci was strong, information on its impact in combination with lifestyle factors is limited.

Methods

We conducted a case-control study in 481 patients with colorectal cancer (CRC) and 962 sex-age matched non-cancer controls. Data on lifestyle factors, including diet, were obtained by self-administered questionnaire. Two 8q24 loci, rs6983267 and rs10090154, were assessed by the TaqMan method. Associations were then assessed by multivariate logistic regression models that considered potential confounders.

Results

We found an increased risk of CRC with rs6983267 but not with rs10090154. An allelic OR was 1.22 (1.04-1.44, p for trend = 0.014), which remained significant after adjustment for confounders (OR = 1.25). No statistically significant interaction with potential confounding factors was observed.

Conclusion

The polymorphism rs6983267 showed a significant association with CRC in a Japanese population. Further investigation of the biological mechanism of this association is warranted.

Background

Colorectal cancer (CRC) remains major cancer worldwide [1]. Although numerous epidemiological and biological studies have revealed risk/protective factors for CRC, present knowledge is still insufficient to allow the disease to be overcome, and the struggle to elucidate mechanisms is ongoing.

Recently, several a number of genome-wide association studies (GWAS) have revealed an association between variants on chromosome 8q24 and several sites of cancer, including CRC [2-11]. Each study showed that rs6983267 resides in 128.47-128.54 MB on Chromosome 8, denoted as 'region 3,' [7] and consistently associated with CRC [6,9,12]. This association was confirmed in a subsequent large-scale replication study in Caucasians [13-18]. Most of these CRC GWASs were conducted in Caucasian populations, however, and the data available for Asian populations is limited especially about possible gene-environment interaction [6,19].

The aim of the present case-control study was to clarify the impact of rs6983267 on CRC risk in a Japanese population. In addition, we explored the gene-environmental interaction between potential confounders and rs6983267.

Methods

Subjects

Cases were 481 patients who were histologically diagnosed with CRC (245 with colon cancer, 231 with rectum cancer) between January 2001 and November 2005 at Aichi Cancer Center Hospital (ACCH) and who had no prior history of cancer. Controls were first-visit outpatients at ACCH during the same periods who were confirmed to have no cancer or a prior history of neoplasm. Controls were randomly selected and matched for sex and age (± 4 years) with a 1:2 case-control ratio (n = 962). The subjects were selected from the database of the Hospital-based Epidemiologic Research Program at Aichi Cancer Center (HERPACC). The framework of HERPACC has been described elsewhere [20,21]. Briefly, all outpatients aged 20-79 years were asked at first visit to fill out a questionnaire regarding their lifestyle and provided 7 ml of blood. A trained interviewer checked the completion of each questionnaire. Approximately 95% of eligible subjects completed the questionnaire and 55% provided blood samples. Some 30% of first-visit outpatients were diagnosed at ACCH as having cancer. Under the assumption that the non-cancer population within HERPACC will visit ACCH if they develop cancer in the future, we defined non-cancer first-visit outpatients as those from among whom such cases may arise. Our previous study confirmed that the lifestyle patterns of first-visit outpatients matched the profile of a group randomly selected from the general population of Nagoya City, conferring external validity on the study [22]. Written informed consent was obtained from all subjects and the ethics committee of ACC approved the study.

Determination of the 8q24 loci genotype

DNA of each subject was extracted from the buffy coat fraction with a Blood Mini Kit (Qiagen K.K., Tokyo, Japan) and assessed using the polymerase chain reaction (PCR) TaqMan method [23] with the 7500 Fast Real-time PCR system (Applied Biosystems, Foster City, CA, USA). The probes used were specifically designed for rs6983267 and rs10090154 in 8q24. rs10090154 in the 8q24 'region 1' [7] was chosen because it showed a significant association for a Japanese population in Hawaii [6]. The quality of genotyping was assessed by duplicate analysis of 5% of random samples, with an agreement rate of 100%.

Exposure data

Cumulative smoking dose was evaluated as pack-years, the product of the number of packs consumed per day and years of smoking. Smoking habit was classified into the three categories of never, pack-years < 20 (low-moderate) and ≥ 20 pack years (heavy). Consumption of types of alcoholic beverages (Japanese sake, beer, shochu, whiskey and wine) per occasion was determined with reference to the average number of drinks per day, which was then converted into a Japanese sake (rice wine) equivalent (one unit sake = 23 g ethanol) [24]. Daily ethanol consumption was estimated as the product of the frequency of alcohol beverage and average ethanol consumption occasion, and drinking habit was classified into the four categories of non-drinker, low (< 5 g/day), moderate (< 23 g/day) and heavy (≥ 23 g/day). Consumption of folate was determined using a semi-quantitative food frequency questionnaire (SQFFQ) as described in detail elsewhere [25]. Briefly, the SQFFQ consisted of 47 single food items with frequencies in the eight categories of never or seldom, 1-3 times/month, 1-2 times/week, 3-4 times/week, 5-6 times/week, once/day, twice/day, and 3+ times/day. Average daily intake of nutrients was estimated by multiplying the food intake (in grams) or serving size by the nutrient content per 100 grams of food as listed in the Standard Tables of Food Composition in Japan, 5th edition. Consumption of supplemental folate was not considered in total consumption because the questionnaire for multi-vitamins was not quantitative. Energy-adjusted intake of nutrients was calculated by the residual method [26]. The SQFFQ was validated by reference to a 3-day weighted dietary record as a standard, which showed the reproducibility and validity to be acceptable [27,28]. The de-attenuated correlation coefficients for energy-adjusted intakes of folate were 0.36 in men and 0.38 in women. Body mass index (BMI) was calculated as the self-reported weight (kilograms) divided by the square of self-reported height (meters). A family history of CRC in first-degree relatives was based on self-reporting, as described elsewhere [29]. The questionnaire also covered the regularity of physical exercise: subjects were asked to report the frequency and intensity of recreational exercise, with average daily exercise hours in any intensity calculated and categorized into the three levels of none, and < 0.5 and ≥ 0.5 hours/day.

Statistical analysis

Odds ratios (ORs) and 95% confidence intervals (CIs) for assessment of the impact of each 8q24 locus, included in the model as an ordinal score (1 to 3), were calculated using multivariable conditional logistic regression models. We explored two models: model 1 was a crude model; model 2 included age and sex plus potential confounders as indicator variables. Confounders considered in model 2 were smoking status (never, former, current moderate, and heavy), drinking habit (non, low, moderate, and heavy), folate consumption by tertile (T1-3), BMI (< 22.5, 22.5 - 24.9, 25.0-27.4 and ≥ 27.5 kg/m2), family history of colorectal cancer (yes or no), and regular exercise (none, < 0.5 hour/day, and ≥ 0.5 hour/day). Interactions between rs6983267 assuming linear effect of allele and potential confounders similarly assuming linear effect were assessed in multivariable unconditional logistic regression models to avoid the dropping of subjects in conditional logistic regression models. To assess possible discrepancies between expected and observed haplotypes, accordance with the Hardy-Weinberg equilibrium (HWE) was checked for controls with the χ2 test. Statistical analyses were performed using STATA version 10 (Stata, College Station, TX), with P-values < 0.05 considered statistically significant.

Results

Table 1 shows baseline characteristics of the 481 CRC cases, with an average age of 60 years, and the 962 controls matched for sex and age. Males accounted for 62.4% of subjects. Apart from a family history of CRC in a first-degree relative, potential confounders showed no clear difference between cases and controls. A family history of CRC was significantly more frequent among CRC cases.

Table 1.

Characteristics of cases and controls

Variables Cases Controls p-values
Total 481 962
Sex 1.00
Male 300 62.4% 600 62.4%
Female 181 37.6% 362 37.6%
Age (years) 0.803
< 40 20 4.2% 39 4.1%
40-49 50 10.4% 105 10.9%
50-59 169 35.1% 328 34.1%
60-69 164 34.1% 353 36.7%
70- 78 16.2% 137 14.2%
Mean age (SD) 60 (10.2) 60 (9.86)
Site of Cancer
Colon 245 50.9%
Rectum 236 49.1%
Smoking 0.102
None 215 44.7% 493 51.3%
Low-moderate (< 20 pack-years) 59 12.3% 116 12.1%
Heavy (≥ 20 pack-years) 203 42.2% 345 35.9%
Unknown 4 0.8% 8 0.8%
Drinking 0.695
None 190 39.5% 383 39.8%
Low (< 5 g ethanl/day) 64 13.3% 125 13.0%
Moderate (5≤ and < 23 g ethanol/day) 85 17.7% 196 20.4%
High (≥ 23 g ethanol/day) 135 28.1% 243 25.3%
Unknown 7 1.5% 15 1.6%
Daily folate consumption 0.857
T1 (≤ 262.0 μg/day) 153 31.8% 286 29.7%
T2 (≤ 346.6 μg/day) 158 32.9% 318 33.1%
T3 (> 346.6 μg/day) 162 33.7% 341 35.5%
Unknown 8 1.7% 17 1.8%
Body-Mass Index (BMI) kg/m2 0.923
< 22.5 206 42.8% 397 41.3%
22.5 ≤ and < 25 157 32.6% 314 32.6%
25 ≤ and < 27.5 73 15.2% 162 16.8%
≥ 27.5 41 8.5% 79 8.2%
Unknown 4 0.8% 10 1.0%
Family history of colorectal cancer in the first degree relatives 0.014
No 453 94.2% 932 96.9%
Yes 28 5.8% 30 3.1%
Average recreational exercise 0.329
None 192 39.9% 349 36.3%
< 0.5 hour/day 194 40.3% 398 41.4%
0.5 ≤ hour/day 95 19.8% 215 22.4%
Open in a new tab

Genotype distributions for 8q24 rs6983267 and rs10090154 are shown in Table 2. Among controls, both genotypes were accordant with the HWE. The minor allele frequency for rs6983267 was 0.338 (G-allele). The age- and sex-adjusted in the allelic model showed an OR of 1.22 (1.04-1.44, p = 0.0144) and the confounder-adjusted model an OR of 1.25 (1.06-1.48, p = 0.0071). Genotypic model showed a significant association only with rs6983267 GG genotype (OR = 1.64, 1.15-2.35, p = 0.0063). In contrast, rs10090154 showed no association with CRC risk. Table 3 shows stratified analyses conducted to explore possible interactions between potential confounders although point estimates for ORs were not static; no significant interactions were seen between the factors examined and rs6983267. The lack of association in those with a positive family history was of interest vis a vis the significant association in those without it, albeit that the number of subjects with a family history was limited.

Table 2.

Genotypes distribution of 8q24 polymorphisms and odds ratios for the minor alleles and genotypes.

Allelic model Genotype model
Model 1 *1 Model 2 *2 Heterozygote Minor homozygote
8q24 locus Genotype OR 95% CI p-value ORa 95% CI p-value ORa 95% CI p-value ORa 95% CI p-value
rs6983267 (Minor allele: G, MAF*1 in controls = 0.338)
TT TG GG UK*4
case/control 181/418 222/436 73/107 3/1 1.22 1.04-1.44 0.0144 1.25 1.06-1.48 0.0071 1.19 0.93-1.52 0.1665 1.64 1.15-2.35 0.0063
rs10090154 (Minor allele: T, MAF in controls = 0.153)
CC CT TT UK
case/control 355/689 112/247 11/23 3/3 0.90 0.72-1.12 0.3443 0.87 0.69-1.09 0.2140 0.83 0.63-1.08 0.1690 0.90 0.43-1.89 0.7854
Open in a new tab

*1 Crude conditional logistic regression model.

*2 Adjusted for age as continuous variable, drinking (non, low, moderate, heavy, and unknown), smoking (non, moderate, heavy, unknwon), BMI (< 22.5, < 25, < 27.5, 27.5-, unknown), folate in tertile (T1, T2, T3, and unknown), total energy intake, family history of colorectal cancer, average recreational exercise (none, < 0.5 hour/day, 0.5-hour/day) in conditional logisitic regression.

*3 MAF indicates minor allele frequency.

*4 UK indicates the subjects whose genotyping was unsuccessful.

Table 3.

Stratified analysis according to potential confounding factors for 8q24 rs6983267 genotype

rs6983267 allelic model
Model 1*1 Model*2
Exposure Number of controls with each genotype (TT/TG/GG) Number of cases with each genotype (TT/TG/GG) OR*1 95% CI p-value OR 95% CI p-value Interaction P
Sex 0.181
Male 122/133/43 259/270/70 1.11 0.91-1.37 0.295 1.14 0.93-1.41 0.212
Female 61/89/30 159/166/37 1.44 1.10-1.88 0.007 1.34 1.01-1.78 0.040
Smoking 0.401
None 73/106/35 206/232/55 1.34 1.05-1.70 0.018 1.29 1.01-1.65 0.042
Low-moderate (< 20 pack-years) 19/31/9 52/52/12 1.51 0.93-2.43 0.094 1.49 0.89-2.49 0.130
Heavy (≥ 20 pack-years) 88/84/29 158/147/39 1.11 0.86-1.43 0.423 1.12 0.86-1.44 0.407
Drinking 0.437
None 69/92/30 166/179/38 1.36 1.04-1.76 0.023 1.35 1.03-1.77 0.028
Low (< 5 g ethanl/day) 23/29/12 51/58/16 1.25 0.81-1.93 0.308 1.44 0.91-2.28 0.124
Moderate (5≤ and < 23 g ethanol/day) 34/41/9 85/83/27 0.98 0.67-1.43 0.918 0.99 0.67-1.46 0.941
High (≥ 23 g ethanol/day) 55/59/19 112/108/23 1.22 0.89-1.67 0.217 1.22 0.88-1.69 0.231
Daily folate consumption 0.694
T1 (≤ 262.0 μg/day) 54/73/25 112/137/37 1.14 0.85-1.53 0.375 1.22 0.90-1.66 0.197
T2 (≤ 346.6 μg/day) 59/75/22 104/141/36 1.21 0.91-1.61 0.191 1.25 0.93-1.67 0.141
T3 (> 346.6 μg/day) 66/72/24 157/152/32 1.24 0.94-1.64 0.135 1.30 0.97-1.73 0.080
Body-Mass Index (BMI) kg/m2 0.678
< 22.5 73/100/32 177/176/44 1.34 1.05-1.72 0.020 1.43 1.10-1.85 0.007
22.5 ≤ and < 25 69/69/19 128/148/37 0.93 0.70-1.25 0.663 0.93 0.69-1.25 0.637
25 ≤ and < 27.5 23/34/16 74/69/19 1.58 1.06-2.36 0.024 1.67 1.09-2.55 0.018
≥ 27.5 18/17/5 31/41/7 0.98 0.54-1.79 0.944 1.06 0.54-2.10 0.863
Family history of colorectal cancer in the first degree relatives 0.765
No 169/212/69 404/422/105 1.24 1.05-1.46 0.011 1.26 1.06-1.48 0.008
Yes 14/10/4 14/14/2 1.09 0.50-2.38 0.833 0.84 0.29-2.43 0.741
Average recreational exercise 0.109
None 77/90/24 161/140/48 1.10 0.85-1.42 0.462 1.13 0.87-1.47 0.356
< 0.5 hour/day 73/89/31 158/199/40 1.20 0.93-1.56 0.163 1.20 0.92-1.57 0.174
0.5 ≤ hour/day 33/43/18 99/97/19 1.59 1.11-2.28 0.012 1.70 1.15-2.50 0.008
Open in a new tab

*1 Odds ratios were adjusted for age and sex in unconditional logistic regression models. Conditional logistic models were not applied because keeping matching in stratficiation gave unstabel estimation.

*2 Odds ratio adjusted for age, sex and all variables in this examination except variable used for stratification.

*3 Interaction term between rs6983267 genotype in score and stratifiying factor in socre was added in model 2.

*4 Subjects were exlucded from analysis because of lack of information, smoking (4 cases and 8 controls), drinking (7 cases and 15 controls), folate (8 cases and 17 controls), and BMI (3 cases and 10 controls)

Discussion

In this study, we found that the G allele in rs6983267 was associated with a significantly increased risk of CRC in a Japanese population. This finding is consistent with those from previous GWASs [6,9,11] and a pooled analysis [12], as reviewed in Table 4, which reported the consistency of this association with CRC and colorectal adenoma in populations with European ancestry. The only previous study of rs6983267 in a population with Asian ethnicity (Japanese-American) was that by Haiman et al [6], and to our knowledge the present study is the first indication in Japanese living in Japan. Tenesa et al. reported significant association with rs7014346 in 8q24, which is in high linkage disequilibrium with rs6983267, in Japanese population [19], supporting significant association between the rs6983267 in CRC in Japanese. Recent advances in genetic analysis have enabled a comprehensive approach to identifying disease susceptibility loci. The consistency of findings in this and the previous studies warrants the usefulness of the GWAS approach across ethnicities. We also evaluated potential interactions between common background factors and rs6983267, but found no significant interaction between them. Berndt et al. also reported a lack of interaction between rs6983267 and age, sex, smoking, family history of CRC and cancer site [12]. The consistency of this finding indicates that rs6983267 is associated with CRC risk independently of common risk factors.

Table 4.

Review of results of 8q24 rs6983267 for colorectal cancer in allelic model.

Author Year Case/Control Country Study subjects Per allele OR (95%CI) Adjustment
Haiman et al. 2007 1,807/5,511 USA Pooled 1.25 (1.12-1.38) Sex
217/1,049 African American 1.37 (0.98-1.91) Sex
381/1,197 Japanese American 1.13 (0.96-1.34) Sex
61/347 Native Hawaiian 1.59 (1.02-2.47) Sex
251/1,007 Latinos 1.26 (1.02-1.55) Sex
214/973 European Americans 1.28 (1.03-1.58) Sex
Tomlinson et al. 2007 7,954/6,206 UK CRC pooled 1.21 (1.15-1.27) Crude
620/960 Panel A CRC White UK residents 1.38 (1.19-1.59) Crude
4,361/3,752 Panel B White UK residents 1.19 (1.12-1.26) Crude
1,901/1,079 Panel C 1.21 (1.09-1.35) Crude
1,072/415 Panel D European Ancestry 1.13 (0.96-1.33) Crude
1,425/2,255 Adenoma pooled 1.22 (1.10-1.34) Crude
407/1,027 Panel A Adenoma White UK residents 1.53 (1.29-1.81) Crude
607/765 Panel E 1.05 (0.90-1.23) Crude
411/463 Panel F 1.13 (0.93-1.37) Crude
Poynter et al. 2007 1,339/2,191 USA Population -- based 1.11 (0.96-1.29) Age and sex
Tuupanen et al. 2008 996/1,012 Finland Population-based 1.22 (1.08-1.38) Crude
Berndt et al. 2008 3,134/4,454 USA Colorectal neoplasms pooled 1.16 (1.07-1.25) Age, sex, and study
547/1,656 PLCO 1.17 (1.01-1.35) Age and sex
1,174/1,293 PLCO adenoma 1.24 (1.11-1.39) Age and sex
364/363 PLCO II 0.93 (0.75-1.16) Age and sex
544/542 NHS 1.10 (0.93-1.30) Age and sex
505/600 Minnesota 1.21 (1.01-1.44) Age and sex
Ghousaini et al. 2008 2,299/2,284 UK Cases from prospective study at East Anglia 1.27 (1.16-1.37) Crude
Lie et al. 2008 561/721 USA Colon cancer cases from SEER Kentucky 1.69 (1.19-2.40) Age, sex, BMI, and NSAID use.
Cuacasian 1.61 (1.36-2.30) Age, sex, BMI, and NSAID use.
Schafmayer 2009 2,713/2,718 Germany Colorectal cancer cases with German ancestry 1.22 (1.13-1.31) Crude
Curtin et al. 2009 1,069/1,040 USA/UK Colorectal cancer cases from USA/UK 1.17 (1.03-1.32) Crude
Our study 481/962 Japan HERPACC II participatns (Japanese) 1.22 (1.04-1.44) Age and sex
1.26 (1.06-1.48) Age, sex, drinking, smoking, BMI, folate consumption, energy, physical exercise, and family history of CRC
Open in a new tab

Rs6983267 was originally identified using a non-hypothesis-based approach, and evidence has suggested a possible biological mechanism behind this observed association. The rs6983267 polymorphism resides 15 kb upstream of a processed pseudogene (POU5F1P1) of the POU-domain factor gene, POU5F1, which encodes transcription factor OCT4, with 97.5% shared identity [30]. OCT4, a transcript of POU5F1, plays a role in maintaining stem cell pluripotency, self-renewal and chromatin structure in stem cells [31], and promotes tumor growth in a dose-dependent manner [32]. A conserved POU5F1-binding site I at the 5' promoter region of the WNT-signaling gene, FZD5, has been reported [33]. Tomlinson et al. reported the expression of either POU5F1 or POU5F1P1 in cell lines and primary CRCs [9], while Suo et al. similarly reported the expression of these genes in cancer cell lines and cancer tissues [30]. Given that OCT4 pseudogenes in mice are reported to mediate stem cell regulatory function [34], it is possible to hypothesize that OCT4 pseudogenes, including POU5F1P1, might play a role in stem cell proliferation. However, no difference in expression according to rs6983267 status was observed [9]. Berndt discussed the potential contribution of MYC, which is located > 300 KB distant to rs6983267[12]. Recently, Pomerantz et al. reported rs6983267 displays a difference in binding of transcription factor 7-like 2 (TCF7L2) leading to a different physical interaction with MYC [35]; however, Tuupanen et al. failed to find clear association between rs6983267 genotype and MYC expression. There still remains controversy between MYC and rs6983267 requiring further studies. Moreover, Tuupanen et al. reported rs6983267 affects a binding site for the Wnt-regulated transcription factor (TCF4), with the risk allele G showing stronger binding in vivo and in vitro. Overall, these findings indicate that the possible biological mechanism behind the effect of rs6983267 polymorphism on CRC carcinogenesis requires further study.

We did not observe any association with rs10090154 (OR = 0.90) on the contrary to the results from Multi-ethnic cohort study [6]. The point estimate for minor allele in the previous study was 1.41 (95%CI: 1.14-1.75). Following case-control study for Japanese American in Hawaii showed lack of association (OR = 1.07, 95%CI: 0.78-1.48)[6]. Inconsistency across studies might come from the finding in the original GWAS was by chance although threshold in statistical significance was high enough. Or, statistical power in following studies including ours was not good enough. By all means, more evidence is needed to clarify significance of the locus.

Several potential limitations of the present study require consideration. First, use of hospital-based control in this study for potential cause of selection bias. We used non-cancer patients at our hospital as controls, given the likelihood that our cases arose within this population base. Moreover, we previously showed that individuals selected randomly from our control population were similar to the general population in terms of baseline characteristics [22]. Given the similarity in minor allele frequency between our controls and that in the HapMap database for Japanese, it is reasonable to assume the external validity of our study results to the general population. Second, as with other case-control studies, this study may have suffered from information bias: although the questionnaires were completed before the diagnosis in our hospital, some patients referred from other institutions might have known their diagnosis. Lack of interaction needs careful interpretation because confounders assessed in this study showed no association with CRC risk by themselves.

Conclusion

Our present investigation showed that rs6983267 in 8q24 is an independent risk factor of CRC in a Japanese population. Further studies to clarify the biological mechanisms of this association are warranted.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

MW carried out the molecular genetic studies. JY carried out the immunoassays. MT participated in the sequence alignment. TS, TK, HT, and KT participated in the design of the study and helped to draft the manuscript. KS, KK, YK, TH and YY participated in the enrollment and conduct of the study. KM conceived of the study, participated in its design and statistical analyses. All authors read and approved the final manuscript.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2407/9/379/prepub

Contributor Information

Keitaro Matsuo, Email: kmatsuo@aichi-cc.jp.

Takeshi Suzuki, Email: takesuzu@med.nagoya-cu.ac.jp.

Hidemi Ito, Email: hidemi@aichi-cc.jp.

Satoyo Hosono, Email: shosono@aichi-cc.jp.

Takakazu Kawase, Email: t_kawase@aichi-cc.jp.

Miki Watanabe, Email: mwatanabe@aichi-cc.jp.

Kohei Shitara, Email: kshitara@aichi-cc.jp.

Koji Komori, Email: komori@aichi-cc.jp.

Yukihide Kanemitsu, Email: kanemitsu@aichi-cc.jp.

Takashi Hirai, Email: thirai@aichi-cc.jp.

Yasushi Yatabe, Email: yyatabe@aichi-cc.jp.

Hideo Tanaka, Email: hitanaka@aichi-cc.jp.

Kazuo Tajima, Email: ktajima@aichi-cc.jp.

Acknowledgements

The authors are grateful to the many doctors, nurses, and technical and administration staff of Aichi Cancer Center Hospital for the daily administration of the HERPACC study.

This study was supported by a Grants-in-Aid for Scientific Research from the Ministry of Education, Science, Sports, Culture and Technology of Japan, for Cancer Research from the Ministry of Health, Labour and Welfare of Japan, and for the Third Term Comprehensive 10-year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare of Japan.

Financial disclosure: The authors declare that they have nothing to disclose regarding financial issues.

References

  1. Parkin DM, Whelan SL, Ferlay J, Teppo L, Thomas DB. Cancer Incidence in Five Continents. IARC Sci Publ. Lyon; 2003. [Google Scholar]
  2. Amundadottir LT, Sulem P, Gudmundsson J, Helgason A, Baker A, Agnarsson BA, Sigurdsson A, Benediktsdottir KR, Cazier JB, Sainz J, Jakobsdottir M, Kostic J, Magnusdottir DN, Ghosh S, Agnarsson K, Birgisdottir B, Le Roux L, Olafsdottir A, Blondal T, Andresdottir M, Gretarsdottir OS, Bergthorsson JT, Gudbjartsson D, Gylfason A, Thorleifsson G, Manolescu A, Kristjansson K, Geirsson G, Isaksson H, Douglas J, Johansson JE, Balter K, Wiklund F, Montie JE, Yu X, Suarez BK, Ober C, Cooney KA, Gronberg H, Catalona WJ, Einarsson GV, Barkardottir RB, Gulcher JR, Kong A, Thorsteinsdottir U, Stefansson K. A common variant associated with prostate cancer in European and African populations. Nat Genet. 2006;38:652–8. doi: 10.1038/ng1808. [DOI] [PubMed] [Google Scholar]
  3. Freedman ML, Haiman CA, Patterson N, McDonald GJ, Tandon A, Waliszewska A, Penney K, Steen RG, Ardlie K, John EM, Oakley-Girvan I, Whittemore AS, Cooney KA, Ingles SA, Altshuler D, Henderson BE, Reich D. Admixture mapping identifies 8q24 as a prostate cancer risk locus in African-American men. Proc Natl Acad Sci USA. 2006;103:14068–73. doi: 10.1073/pnas.0605832103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Easton DF, Pooley KA, Dunning AM, Pharoah PD, Thompson D, Ballinger DG, Struewing JP, Morrison J, Field H, Luben R, Wareham N, Ahmed S, Healey CS, Bowman R, Meyer KB, Haiman CA, Kolonel LK, Henderson BE, Le Marchand L, Brennan P, Sangrajrang S, Gaborieau V, Odefrey F, Shen CY, Wu PE, Wang HC, Eccles D, Evans DG, Peto J, Fletcher O, Johnson N, Seal S, Stratton MR, Rahman N, Chenevix-Trench G, Bojesen SE, Nordestgaard BG, Axelsson CK, Garcia-Closas M, Brinton L, Chanock S, Lissowska J, Peplonska B, Nevanlinna H, Fagerholm R, Eerola H, Kang D, Yoo KY, Noh DY, Ahn SH, Hunter DJ, Hankinson SE, Cox DG, Hall P, Wedren S, Liu J, Low YL, Bogdanova N, Schurmann P, Dork T, Tollenaar RA, Jacobi CE, Devilee P, Klijn JG, Sigurdson AJ, Doody MM, Alexander BH, Zhang J, Cox A, Brock IW, MacPherson G, Reed MW, Couch FJ, Goode EL, Olson JE, Meijers-Heijboer H, Ouweland A van den, Uitterlinden A, Rivadeneira F, Milne RL, Ribas G, Gonzalez-Neira A, Benitez J, Hopper JL, McCredie M, Southey M, Giles GG, Schroen C, Justenhoven C, Brauch H, Hamann U, Ko YD, Spurdle AB, Beesley J, Chen X, Mannermaa A, Kosma VM, Kataja V, Hartikainen J, Day NE. Genome-wide association study identifies novel breast cancer susceptibility loci. Nature. 2007;447:1087–93. doi: 10.1038/nature05887. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Gudmundsson J, Sulem P, Manolescu A, Amundadottir LT, Gudbjartsson D, Helgason A, Rafnar T, Bergthorsson JT, Agnarsson BA, Baker A, Sigurdsson A, Benediktsdottir KR, Jakobsdottir M, Xu J, Blondal T, Kostic J, Sun J, Ghosh S, Stacey SN, Mouy M, Saemundsdottir J, Backman VM, Kristjansson K, Tres A, Partin AW, Albers-Akkers MT, Godino-Ivan Marcos J, Walsh PC, Swinkels DW, Navarrete S, Isaacs SD, Aben KK, Graif T, Cashy J, Ruiz-Echarri M, Wiley KE, Suarez BK, Witjes JA, Frigge M, Ober C, Jonsson E, Einarsson GV, Mayordomo JI, Kiemeney LA, Isaacs WB, Catalona WJ, Barkardottir RB, Gulcher JR, Thorsteinsdottir U, Kong A, Stefansson K. Genome-wide association study identifies a second prostate cancer susceptibility variant at 8q24. Nat Genet. 2007;39:631–7. doi: 10.1038/ng1999. [DOI] [PubMed] [Google Scholar]
  6. Haiman CA, Le Marchand L, Yamamato J, Stram DO, Sheng X, Kolonel LN, Wu AH, Reich D, Henderson BE. A common genetic risk factor for colorectal and prostate cancer. Nat Genet. 2007;39:954–6. doi: 10.1038/ng2098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Haiman CA, Patterson N, Freedman ML, Myers SR, Pike MC, Waliszewska A, Neubauer J, Tandon A, Schirmer C, McDonald GJ, Greenway SC, Stram DO, Le Marchand L, Kolonel LN, Frasco M, Wong D, Pooler LC, Ardlie K, Oakley-Girvan I, Whittemore AS, Cooney KA, John EM, Ingles SA, Altshuler D, Henderson BE, Reich D. Multiple regions within 8q24 independently affect risk for prostate cancer. Nat Genet. 2007;39:638–44. doi: 10.1038/ng2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Schumacher FR, Feigelson HS, Cox DG, Haiman CA, Albanes D, Buring J, Calle EE, Chanock SJ, Colditz GA, Diver WR, Dunning AM, Freedman ML, Gaziano JM, Giovannucci E, Hankinson SE, Hayes RB, Henderson BE, Hoover RN, Kaaks R, Key T, Kolonel LN, Kraft P, Le Marchand L, Ma J, Pike MC, Riboli E, Stampfer MJ, Stram DO, Thomas G, Thun MJ, Travis R, Virtamo J, Andriole G, Gelmann E, Willett WC, Hunter DJ. A common 8q24 variant in prostate and breast cancer from a large nested case-control study. Cancer Res. 2007;67:2951–6. doi: 10.1158/0008-5472.CAN-06-3591. [DOI] [PubMed] [Google Scholar]
  9. Tomlinson I, Webb E, Carvajal-Carmona L, Broderick P, Kemp Z, Spain S, Penegar S, Chandler I, Gorman M, Wood W, Barclay E, Lubbe S, Martin L, Sellick G, Jaeger E, Hubner R, Wild R, Rowan A, Fielding S, Howarth K, Silver A, Atkin W, Muir K, Logan R, Kerr D, Johnstone E, Sieber O, Gray R, Thomas H, Peto J, Cazier JB, Houlston R. A genome-wide association scan of tag SNPs identifies a susceptibility variant for colorectal cancer at 8q24.21. Nat Genet. 2007;39:984–8. doi: 10.1038/ng2085. [DOI] [PubMed] [Google Scholar]
  10. Yeager M, Orr N, Hayes RB, Jacobs KB, Kraft P, Wacholder S, Minichiello MJ, Fearnhead P, Yu K, Chatterjee N, Wang Z, Welch R, Staats BJ, Calle EE, Feigelson HS, Thun MJ, Rodriguez C, Albanes D, Virtamo J, Weinstein S, Schumacher FR, Giovannucci E, Willett WC, Cancel-Tassin G, Cussenot O, Valeri A, Andriole GL, Gelmann EP, Tucker M, Gerhard DS, Fraumeni JF Jr, Hoover R, Hunter DJ, Chanock SJ, Thomas G. Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nat Genet. 2007;39:645–9. doi: 10.1038/ng2022. [DOI] [PubMed] [Google Scholar]
  11. Zanke BW, Greenwood CM, Rangrej J, Kustra R, Tenesa A, Farrington SM, Prendergast J, Olschwang S, Chiang T, Crowdy E, Ferretti V, Laflamme P, Sundararajan S, Roumy S, Olivier JF, Robidoux F, Sladek R, Montpetit A, Campbell P, Bezieau S, O'Shea AM, Zogopoulos G, Cotterchio M, Newcomb P, McLaughlin J, Younghusband B, Green R, Green J, Porteous ME, Campbell H, Blanche H, Sahbatou M, Tubacher E, Bonaiti-Pellie C, Buecher B, Riboli E, Kury S, Chanock SJ, Potter J, Thomas G, Gallinger S, Hudson TJ, Dunlop MG. Genome-wide association scan identifies a colorectal cancer susceptibility locus on chromosome 8q24. Nat Genet. 2007;39:989–94. doi: 10.1038/ng2089. [DOI] [PubMed] [Google Scholar]
  12. Berndt SI, Potter JD, Hazra A, Yeager M, Thomas G, Makar KW, Welch R, Cross AJ, Huang WY, Schoen RE, Giovannucci E, Chan AT, Chanock SJ, Peters U, Hunter DJ, Hayes RB. Pooled analysis of genetic variation at chromosome 8q24 and colorectal neoplasia risk. Hum Mol Genet. 2008;17:2665–72. doi: 10.1093/hmg/ddn166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Ghoussaini M, Song H, Koessler T, Al Olama AA, Kote-Jarai Z, Driver KE, Pooley KA, Ramus SJ, Kjaer SK, Hogdall E, DiCioccio RA, Whittemore AS, Gayther SA, Giles GG, Guy M, Edwards SM, Morrison J, Donovan JL, Hamdy FC, Dearnaley DP, Ardern-Jones AT, Hall AL, O'Brien LT, Gehr-Swain BN, Wilkinson RA, Brown PM, Hopper JL, Neal DE, Pharoah PD, Ponder BA, Eeles RA, Easton DF, Dunning AM. Multiple loci with different cancer specificities within the 8q24 gene desert. J Natl Cancer Inst. 2008;100:962–6. doi: 10.1093/jnci/djn190. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Schafmayer C, Buch S, Volzke H, von Schonfels W, Egberts JH, Schniewind B, Brosch M, Ruether A, Franke A, Mathiak M, Sipos B, Henopp T, Catalcali J, Hellmig S, ElSharawy A, Katalinic A, Lerch MM, John U, Folsch UR, Fandrich F, Kalthoff H, Schreiber S, Krawczak M, Tepel J, Hampe J. Investigation of the colorectal cancer susceptibility region on chromosome 8q24.21 in a large German case-control sample. Int J Cancer. 2009;124:75–80. doi: 10.1002/ijc.23872. [DOI] [PubMed] [Google Scholar]
  15. Curtin K, Lin WY, George R, Katory M, Shorto J, Cannon-Albright LA, Bishop DT, Cox A, Camp NJ. Meta association of colorectal cancer confirms risk alleles at 8q24 and 18q21. Cancer Epidemiol Biomarkers Prev. 2009;18:616–21. doi: 10.1158/1055-9965.EPI-08-0690. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Li L, Plummer SJ, Thompson CL, Merkulova A, Acheson LS, Tucker TC, Casey G. A common 8q24 variant and the risk of colon cancer: a population-based case-control study. Cancer Epidemiol Biomarkers Prev. 2008;17:339–42. doi: 10.1158/1055-9965.EPI-07-0713. [DOI] [PubMed] [Google Scholar]
  17. Poynter JN, Figueiredo JC, Conti DV, Kennedy K, Gallinger S, Siegmund KD, Casey G, Thibodeau SN, Jenkins MA, Hopper JL, Byrnes GB, Baron JA, Goode EL, Tiirikainen M, Lindor N, Grove J, Newcomb P, Jass J, Young J, Potter JD, Haile RW, Duggan DJ, Le Marchand L. Variants on 9p24 and 8q24 are associated with risk of colorectal cancer: results from the Colon Cancer Family Registry. Cancer Res. 2007;67:11128–32. doi: 10.1158/0008-5472.CAN-07-3239. [DOI] [PubMed] [Google Scholar]
  18. Tuupanen S, Niittymaki I, Nousiainen K, Vanharanta S, Mecklin JP, Nuorva K, Jarvinen H, Hautaniemi S, Karhu A, Aaltonen LA. Allelic imbalance at rs6983267 suggests selection of the risk allele in somatic colorectal tumor evolution. Cancer Res. 2008;68:14–7. doi: 10.1158/0008-5472.CAN-07-5766. [DOI] [PubMed] [Google Scholar]
  19. Tenesa A, Farrington SM, Prendergast JG, Porteous ME, Walker M, Haq N, Barnetson RA, Theodoratou E, Cetnarskyj R, Cartwright N, Semple C, Clark AJ, Reid FJ, Smith LA, Kavoussanakis K, Koessler T, Pharoah PD, Buch S, Schafmayer C, Tepel J, Schreiber S, Volzke H, Schmidt CO, Hampe J, Chang-Claude J, Hoffmeister M, Brenner H, Wilkening S, Canzian F, Capella G, Moreno V, Deary IJ, Starr JM, Tomlinson IP, Kemp Z, Howarth K, Carvajal-Carmona L, Webb E, Broderick P, Vijayakrishnan J, Houlston RS, Rennert G, Ballinger D, Rozek L, Gruber SB, Matsuda K, Kidokoro T, Nakamura Y, Zanke BW, Greenwood CM, Rangrej J, Kustra R, Montpetit A, Hudson TJ, Gallinger S, Campbell H, Dunlop MG. Genome-wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nat Genet. 2008;40:631–7. doi: 10.1038/ng.133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Tajima K, Hirose K, Inoue M, Takezaki T, Hamajima N, Kuroishi T. A Model of Practical Cancer Prevention for Out-patients Visiting a Hospital: the Hospital-based Epidemiologic Research Program at Aichi Cancer Center (HERPACC) Asian Pac J Cancer Prev. 2000;1:35–47. [PubMed] [Google Scholar]
  21. Hamajima N, Matsuo K, Saito T, Hirose K, Inoue M, Takezaki T, Kuroishi T, Tajima K. Gene-environment Interactions and Polymorphism Studies of Cancer Risk in the Hospital-based Epidemiologic Research Program at Aichi Cancer Center II (HERPACC-II) Asian Pac J Cancer Prev. 2001;2:99–107. [PubMed] [Google Scholar]
  22. Inoue M, Tajima K, Hirose K, Hamajima N, Takezaki T, Kuroishi T, Tominaga S. Epidemiological features of first-visit outpatients in Japan: comparison with general population and variation by sex, age, and season. J Clin Epidemiol. 1997;50:69–77. doi: 10.1016/S0895-4356(96)00297-1. [DOI] [PubMed] [Google Scholar]
  23. Livak KJ. Allelic discrimination using fluorogenic probes and the 5' nuclease assay. Genet Anal. 1999;14:143–9. doi: 10.1016/s1050-3862(98)00019-9. [DOI] [PubMed] [Google Scholar]
  24. Matsuo K, Wakai K, Hirose K, Ito H, Saito T, Tajima K. Alcohol dehydrogenase 2 His47Arg polymorphism influences drinking habit independently of aldehyde dehydrogenase 2 Glu487Lys polymorphism: analysis of 2,299 Japanese subjects. Cancer Epidemiol Biomarkers Prev. 2006;15:1009–13. doi: 10.1158/1055-9965.EPI-05-0911. [DOI] [PubMed] [Google Scholar]
  25. Matsuo K, Ito H, Wakai K, Hirose K, Saito T, Suzuki T, Kato T, Hirai T, Kanemitsu Y, Hamajima H, Tajima K. One-carbon metabolism related gene polymorphisms interact with alcohol drinking to influence the risk of colorectal cancer in Japan. Carcinogenesis. 2005;26:2164–71. doi: 10.1093/carcin/bgi196. [DOI] [PubMed] [Google Scholar]
  26. Willett W, Stampfer MJ. Total energy intake: implications for epidemiologic analyses. Am J Epidemiol. 1986;124:17–27. doi: 10.1093/oxfordjournals.aje.a114366. [DOI] [PubMed] [Google Scholar]
  27. Imaeda N, Goto C, Tokudome Y, Hirose K, Tajima K, Tokudome S. Reproducibility of a short food frequency questionnaire for Japanese general population. J Epidemiol. 2007;17:100–7. doi: 10.2188/jea.17.100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Tokudome Y, Goto C, Imaeda N, Hasegawa T, Kato R, Hirose K, Tajima K, Tokudome S. Relative validity of a short food frequency questionnaire for assessing nutrient intake versus three-day weighed diet records in middle-aged Japanese. J Epidemiol. 2005;15:135–45. doi: 10.2188/jea.15.135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Suzuki T, Matsuo K, Wakai K, Hiraki A, Hirose K, Sato S, Ueda R, Tajima K. Effect of familial history and smoking on common cancer risks in Japan. Cancer. 2007;109:2116–23. doi: 10.1002/cncr.22685. [DOI] [PubMed] [Google Scholar]
  30. Suo G, Han J, Wang X, Zhang J, Zhao Y, Dai J. Oct4 pseudogenes are transcribed in cancers. Biochem Biophys Res Commun. 2005;337:1047–51. doi: 10.1016/j.bbrc.2005.09.157. [DOI] [PubMed] [Google Scholar]
  31. Campbell PA, Perez-Iratxeta C, Andrade-Navarro MA, Rudnicki MA. Oct4 targets regulatory nodes to modulate stem cell function. PLoS ONE. 2007;2:e553. doi: 10.1371/journal.pone.0000553. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Gidekel S, Pizov G, Bergman Y, Pikarsky E. Oct-3/4 is a dose-dependent oncogenic fate determinant. Cancer Cell. 2003;4:361–70. doi: 10.1016/S1535-6108(03)00270-8. [DOI] [PubMed] [Google Scholar]
  33. Katoh Y, Katoh M. Conserved POU-binding site linked to SP1-binding site within FZD5 promoter: Transcriptional mechanisms of FZD5 in undifferentiated human ES cells, fetal liver/spleen, adult colon, pancreatic islet, and diffuse-type gastric cancer. Int J Oncol. 2007;30:751–5. [PubMed] [Google Scholar]
  34. Lin H, Shabbir A, Molnar M, Lee T. Stem cell regulatory function mediated by expression of a novel mouse Oct4 pseudogene. Biochem Biophys Res Commun. 2007;355:111–6. doi: 10.1016/j.bbrc.2007.01.106. [DOI] [PubMed] [Google Scholar]
  35. Pomerantz MM, Ahmadiyeh N, Jia L, Herman P, Verzi MP, Doddapaneni H, Beckwith CA, Chan JA, Hills A, Davis M, Yao K, Kehoe SM, Lenz HJ, Haiman CA, Yan C, Henderson BE, Frenkel B, Barretina J, Bass A, Tabernero J, Baselga J, Regan MM, Manak JR, Shivdasani R, Coetzee GA, Freedman ML. The 8q24 cancer risk variant rs6983267 shows long-range interaction with MYC in colorectal cancer. Nat Genet. 2009;41:882–4. doi: 10.1038/ng.403. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from BMC Cancer are provided here courtesy of BMC

RESOURCES