Cyclin D1 G870A polymorphism and risk of upper digestive tract cancer: a systematic review

Review Article

Cyclin D1 G870A polymorphism and risk of upper digestive tract cancer: a systematic review

Corresponding author: Yun-Hao Tang, PhD, Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, No 74 Linjiang Road, Chongqing 400010, People’s Republic of China. Email:   


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Keywords: Anti-aging reagent; Klotho; Glucosamine; hyaluronic acid; Anti-aging food NOx; Protection of global warming.

To evaluate the association between the CCND1 G870A polymorphism and the risk of upper digestive tract cancer.

Methods: All case-control studies evaluated association between CCND1 G870A polymorphism and risk of UDTC were identified by using a predefined search strategy. Summary odds ratios (ORs) and 95% confidence intervals (95% CIs) for CCND1 G870A polymorphism and risk of UDTC were calculated.

Results: Twenty-five case-control studies which including 5955 UDTC cases and 7048 controls were considered eligible for inclusion. Meta-analysis showed that the CCND1 G870A polymorphism was significantly associated with increased UDTC risk [AA vs. GG: OR, 1.26; 95% CI, 1.01-1.58; (AA + GA) vs. GG: OR, 1.18, 95% CI, 1.00-1.40; A vs. G: OR, 1.13; 95% CI, 1.01-1.26]. In the subgroup analysis, a significant association was found among Asian groups [AA vs. GG: OR, 1.35; 95% CI, 1.03-1.77; AA vs. (GA + GG): OR, 1.22, 95% CI, 1.03-1.44; A vs. G: OR, 1.13; 95% CI, 1.02-1.26]. Similar results were also observed in studies with PCR-RFLP method and in studies without HWE in controls.

Conclusion: Our study indicates that the CCND1 G870A polymorphism may be a risk factor for UDTC, especially for the Asians.


Upper digestive tract cancer (UDTC) is a group of the most common malignancies with more than 1.5 million new cases each year worldwide [1, 2]. Among them, gastric cancer, esophageal cancer and oral cancer are the second, sixth and eighth leading cause of cancer-related death, respectively [3-5]. The mechanism of UDTC development remains unclear, it involves interactions between environmental factors and host inherited susceptibility. Several environmental factors, such as poor nutritional status, diets low in vegetables and fiber, consumption of high temperature beverages, and infection of H. Pylori, have been proven to probably increase UDTC risk [6-10]. In recent years, genetic factors, such as single nucleotide polymorphisms (SNPs), are increasingly studied and recognized as major contributors to UDTC formation.

The cyclin D1 (CCND1) gene, which located on human chromosome 1q31-32, expresses a key protein to regulate the transition from G1 to S phase [11, 12]. Several studies have suggested that protein overexpression of CCND1 is associated with a number of cancers [13-18]. Overexpression of CCND1 accelerates the G1-S transition, and thus increases cell proliferation, which is closely-related to carcinogenesis [19]. Besides gene amplification, gene polymorphism is another major reason for affecting the activity of CCND1 [20]. Among them, G870A (rs603965) is one of the most common functional SNPs in CCND1, and has been studied frequently in recent years. It has been demonstrated by several studies that this polymorphism is associated with susceptibility of numerous cancers, which including colorectal cancer, bladder cancer, breast cancer, prostate cancer, liver cancer, and lung cancer [21-25]. Moreover, a number of studies have also been conducted to investigate the association between CCND1 G870A polymorphism and UDTC [26-31]. But unfortunately, inconsistent results were presented from these studies, which might result from ethnic heterogeneity and weak statistical power of individually study with small sample size. Up to now, there is no available systematic review regarding the association between CCND1 and risk of UDTC. In order to clarify this issue, we reviewed and assessed the existed literature to evaluate whether CCND1 G870A polymorphism is associated with risk of UDTC by meta-analysis.

Materials and methods

Search strategy
We searched MEDLINE, PUBMED, EMBASE and CNKI (China National Knowledge Infrastructure Whole Article Database) by using the following search term: (upper gastrointestinal tract OR stomach OR gastric OR esophageal OR esophagus OR oral) and (Cyclin D1 OR CCND1) and (carcinoma OR cancer OR tumor OR neoplasm) and (variant OR polymorphism) and (risk OR susceptibility). All case-control studies evaluated association between CCND1 G870A polymorphism and risk of UDTC published in English or Chinese prior to June 2015 were identified. If samples of two studies overlap, only the largest one was included. Potentially related publications were obtained from references within the articles identified by the electronic search. Furthermore, we contacted some experts in the field for identifying unpublished or ongoing studies.

Inclusion and exclusion criteria

We reviewed abstracts of all citations and retrieved studies. The following criteria were used to select the eligible studies: (1) case-control design; (2) clear description of cancer diagnoses and sources of participants; (3) evaluation of the association between CCND1 G870A polymorphism and risk of UDTC; (4) sufficient sample data were presented to calculate the odd ratio (OR) and confidence interval (CI). Patients could be of any age, gender, and race. Studies were excluded if one of the following major criteria existed: (1) cohort design; (2) duplicate data; (3) no sufficient data were reported.

Data collection and analysis

Selection of trials and data extraction: The titles and abstracts of publications identified according to the above search strategy were assessed independently for inclusion by two investigators (Tang Yun-Hao and Chen Hong). The full text was obtained for further assessment if the abstract suggests relevance. Disagreement was resolved by discussion. Data was extracted by two independent investigators (Tang Yun-Hao and Chen Hong). The following recorded data were extracted from each available study: author, publication data, region of participants, total numbers of cases and controls, ethnicity, cancer type, genotypes, source of control, genotypes methods, and P for Hardy–Weinberg equilibrium (HWE). Different ethnic groups were categorized as Mixed, Caucasian, and Asian.

Data synthesis: We assessed statistical heterogeneity by using a Chi-squared test where P < 0.1 indicates significant heterogeneity. If heterogeneity was found, we synthesized data by adopting the random-effects model; otherwise, fixed-effects model was employed. The actual strength of association between CCND1 G870A polymorphism and risk of UDTC was evaluated by calculating using the crude odds ratios (ORs) and 95% confidence intervals (95% CIs). A Z-test was also used and P-value less than 0.05 was considered to be statistically significant. Pooled ORs and 95% CIs of five different genetic model comparisons were separately calculated from the combination of single studies: the homozygote comparison (GG vs. AA), heterozygote comparison (GG vs. GA), dominant model (GG vs. GA+AA), recessive model (AA vs. GA+GG), and allele comparison (G vs. A). Stratified analyses were also investigated by cancer type, ethnicity, source of controls, genotyping methods, and HWE in controls. The chi-square test for goodness of fit (χ2 or Fisher’s exact test) was used to evaluate whether HWE exist in the controls, and P < 0.05 was considered as significant disequilibrium. Potential publication bias and other possible biases were examined by using Begg’s funnel plot and Egger’s linear regression methods, and P < 0.05 was considered statistically significant. Sensitivity analysis was performed to detect the reliability of the results. The results of the studies were analyzed using the statistical software STATA 12.0 (STATA Corp., College Station, TX, USA).


Description of included trials

There were 146 papers relevant to the search words. After screening the title and reading the abstract, 26 studies were identified [26-51]. Samples of two studies were partially overlapped [46, 51], so we excluded the smaller one [51]. As a result, a total of 25 case-control studies [26-50] which including 5955 UDTC cases and 7048 controls were considered eligible for inclusion based on MOOSE (Meta-analysis Of Observational Studies in Epidemiology) guidelines [52]. The flow chart of selection of studies and reasons for exclusion is presented in Figure 1. Studies had been carried out in China, Korea, Japan, USA, India, Germany, Kazakhstan, Canada, Iran, and Brazil. Of these, ten studies focused on oropharyngeal cancer, eight on esophageal cancer, five on gastric cancer, and two on both esophageal and gastric cancers. The genotyping methods of these 25 studies consisted of the polymerase chain reaction-ligase detection reaction (PCR-LDR), polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), and TaqMan methods. The detail characteristics of studies included in the meta-analysis are presented in Tables 1.

Figure 1: Flow chart of study selection and specific reasons for exclusion from the meta-analysis


Figure 2: Overall meta-analysis for CCND1 G870A polymorphism (AA vs. GG) and risk of UDTC.

Figure 3: Overall meta-analysis for CCND1 G870A polymorphism [(AA + GA) vs. GG] and risk of UDTC.

Figure 4: Overall meta-analysis for CCND1 G870A polymorphism (A vs. G) and risk of UDTC.

Abbreviations: LC, lung cancer; HC, hepatocellular carcinoma; EOC, epithelial ovarian carcinoma; NSCLC, non-small cell lung cancer, ESCC, esophageal squamous cell carcinoma; GCA, gastric cardiac carcinoma; BrC, breast cancer; CRC, colorectal cancer, bladder cancer; EAC, esophageal adenocarcinoma; LSCC, laryngeal squamous cell carcinoma. SNPs: single nucleotide polymorphisms; HCC, hospital-based case-control; PCC, population-based case-control; PCR-RFLP, polymerase chain polymorphism reaction-restriction fragment length; PCR-SSCP, PCR-single strand conformational polymorphism. MAF, minor allele frequency; HWE, Hardy–Weinberg equilibrium.

Quantitative synthesis

Overall, the pooled analysis of all the 25 included studies showed that there was a significant association between the CCND1 G870A polymorphism and risk of UDTC in codominant (AA vs. GG: OR, 1.26; 95% CI, 1.01-1.58; P = 0.040, Pheterogeneity = 0.000), dominant [(AA + GA) vs. GG: OR, 1.18, 95% CI, 1.00-1.40; P = 0.046, Pheterogeneity = 0.000], and allele contrast models (A vs. G: OR, 1.13; 95% CI, 1.01-1.26; P = 0.026, Pheterogeneity = 0.000) (Table 2, Figure 2-4). The stratified analysis according to ethnicity revealed an increased UDTC risk among Asian groups [AA vs. GG: OR, 1.35; 95% CI, 1.03-1.77; AA vs. (GA + GG): OR, 1.22, 95% CI, 1.03-1.44; A vs. G: OR, 1.13; 95% CI, 1.02-1.26]. When studies were stratified by genotyping methods, a significant association was found in studies with PCR-RFLP method [AA vs. GG: OR, 1.38; 95% CI, 1.05-1.81; (AA + GA) vs. GG: OR, 1.28, 95% CI, 1.03-1.59; AA vs. (GA + GG): OR, 1.22, 95% CI, 1.01-1.48; A vs. G: OR, 1.19; 95% CI, 1.04-1.36]. Similarly, a significantly increased UDTC risk was observed in studies without HWE in controls [AA vs. GG: OR, 1.26; 95% CI, 1.01-1.58; (AA + GA) vs. GG: OR, 1.47, 95% CI, 1.05-2.07; AA vs. (GA + GG): OR, 1.61, 95% CI, 1.35-1.93; A vs. G: OR, 1.13; 95% CI, 1.02-1.26] (Table 2).

aP value of Q-test for heterogeneity test. Random-effects model was used when P value <0.1, otherwise, fixed-effects model was adopted

bHCC, hospital-based case control; PCC, population-based case control.

cHWE: P for Hardy–Weinberg

Heterogeneity analysis

There was significant heterogeneity among these included studies in all of the five genetic model comparisons. By using Galbraith plot analyses, twelve studies [27, 28, 29, 31, 33, 39, 40, 41, 45, 47, 48, 49], nine studies [27, 28, 29, 31, 39, 41, 45, 48, 49], eight studies [27, 29, 30, 37, 39, 40, 47, 48], four studies [28, 39, 41, 48], and ten studies [27, 28, 29, 31, 39, 40, 41, 47, 48, 49] were found to be main contributors of heterogeneity in AA vs. GG, (AA + GA) vs. GG, AA vs. (GA + GG), GA vs. GG, and A vs. G model comparisons, respectively. After excluding these outlier studies, we re-analyzed the association with reduced heterogeneity [AA vs. GG: OR, 1.17; 95% CI, 1.02-1.35; Pheterogeneity = 0.442; (AA + GA) vs. GG: OR, 1.17, 95% CI, 1.05-1.31; Pheterogeneity = 0.628; AA vs. (GA + GG): OR, 1.04, 95% CI, 0.94-1.16; Pheterogeneity = 0.318; GA vs. GG: OR, 1.03; 95% CI, 0.93-1.14; Pheterogeneity = 0.171; A vs. G: OR, 1.08; 95% CI, 1.02-1.15; Pheterogeneity = 0.164].

Sensitivity analysis and publication bias

The sensitivity analyses, which were conducted by excluding one study dataset and repeating the meta-analysis for the remaining studies, indicated that no individual study had a significant influence on the pooled results. Begg’s funnel plot and Egger’s test were used to estimate the potential publication bias in this meta-analysis. The shape of the funnel plots was symmetrical in the AA vs. (GA + GG) model, but not in the AA vs. GG, (AA + GA) vs. GG, GA vs. GG, and A vs. G model. Similar results were also shown in Egger’s test [(P = 0.010 for AA vs. GG; P = 0.017 for (AA + GA) vs. GG; P = 0.048 for GA vs. GG; and P = 0.031 for A vs. G], which indicated that there was a certain amount of publication bias in the included studies.


The normal growth of human cell depends on the balance of various regulatory proteins in the cell cycle. Any disorder of regulatory proteins may cause abnormal cell proliferation, thereby providing potential chance for carcinogenesis [53]. Cyclin D1, a member of D-type cyclins family, is one of the most important protein which regulate the G1/S-phase transition [54]. Among more than 250 identified SNPs which spanning CCND1 gene, the well-known adenine-to-guanine (A/G) substitution at nucleotide 870, which results in an alternately spliced RNA transcripts (isoform b) encodes CCND1 protein with a longer half-life, has been paid the most attention [21]. This mutation may facilitate transition of variant cell passing through the G1/S-phase and result in abnormal proliferation, bringing about cancer onset [55]. Previous studies have demonstrated that the CCND1 A allele may be linked to higher incidence of several types of tumor including breast cancer, lung cancer, colorectal cancer, and others [23, 24, 56-59].

In 1998, Matthias et al. firstly investigated the etiological relationship between CCND1 G870A polymorphism and the susceptibility of oral cancer [33]. After that, many case-control studies focused on the relationship between CCND1 G870A polymorphism and the UDTC susceptibility have been conducted, and revealed conflicting findings. In order to obtain more reliable conclusions, we collect 25 case-control studies with 5955 UDTC cases and 7048 controls included, and combine the individual results to increase the statistical power. In this systematic review, the CCND1 G870A polymorphism was found to be possibly associated with increased risk of UDTC under three genetic models including the codominant model (OR = 1.26), dominant model (OR = 1.18), and allele contrast model (OR = 1.13). However, in the stratified analysis by ethnicity, similar results were found only among Asian groups. Genotypes of the CCND1 G870A polymorphism were not found to be associated with an increased risk of developing UDTC in the Caucasian population. A reasonable explanation to interpret this finding may be due to the fact that the environment exposures, which also play an important role in the development of UDTC, are discrepant between different ethnic populations. When studies were stratified by cancer types, no association was found between the CCND1 G870A polymorphism and any specific type of UDTC which including oropharyngeal cancer, esophageal cancer, and gastric cancer. These findings were consistent with the results from another previous meta-analysis investigating the relationship between the CCND1 G870A polymorphism and digestive tract cancer [60], but seemed to contradict the overall pooled results of this meta-analysis. This contradiction may cause by the fact that there were two included studies investigated both esophageal and gastric cancers, leading to the discrepancy in statistical weight between overall and stratified analyses.

We recognize some limitations of this study. First, many environmental factors, such as infection of H. Pylori, smoking and eating habits, have also been considered to be associated with UDTC. Due to lack of detail data from the original studies, stratified analysis according to these factors, which may be needed to eliminate the influence of these factors, did not be performed. Therefore, all of our findings may be resulted by the context of the gene within other extrinsic factors. Second, the controls were not uniformly defined. Control groups of some included studies were hospital-based, and thus may have been exposed to unknown bias factors. This could affect the reliability of this meta-analysis. Third, several previous studies have demonstrated that CCND1 G870A polymorphism is in linkage disequilibrium with another SNP [33, 61]. Therefore, it is extremely possible that CCND1 G870A polymorphism is not the only intrinsic factor affects carcinogenesis of UDTC. Nevertheless, it was hardly to be proved in this systematic review because of a lack of data. Fourth, like other retrospective secondary studies, the methodological limitations of the included studies determine the quality of a systematic review. Although a detailed protocol was well-designed and performed strictly in this study, a publication bias was still revealed by the statistical testing. Thus, our results should be interpreted with caution.

In conclusion, this systematic review demonstrated that the CCND1 G870A polymorphism may be associated with UDTC susceptibility, especially among patients of Asian ethnicity. In view of some limitations and potential bias existed in the current study, further prospective population-based clinical trials with a larger sample size are required to certify this association.

Acknowledgements: None.


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