Literature DB >> 27022292

Quantitative assessment of caveolin-1 G14713A polymorphism and cancer susceptibility in the Asian population.

Jianjun Tang1, Gang Wang2, Qiang Li1, Rongfeng Song1.   

Abstract

PURPOSE: The relationship between caveolin-1 (CAV1) G14713A polymorphism and cancer susceptibility remains inconclusive. The current meta-analysis was performed on the basis of a systematic search in electronic databases for a more precise estimation of the associations.
METHODS: Odds ratio (OR) with 95% confidence interval (CI) was used to estimate the pooled effect.
RESULTS: A total of 12 studies including 4,994 cases and 5,606 controls were involved in this meta-analysis. In the overall analysis, CAV1 G14713A polymorphism was significantly associated with an increased risk of cancer (A vs G: OR =1.77, 95% CI: 1.49-2.10, P het<0.01; [AA + AG] vs GG: OR =2.03, 95% CI: 1.64-2.53, P het<0.01; AA vs [AG + GG]: OR =1.72, 95% CI: 1.40-2.12, P het<0.01; AA vs GG: OR =2.24, 95% CI: 1.69-2.98, P het<0.01; AG vs GG: OR =1.98, 95% CI: 1.62-2.41, P het<0.01). Subgroup analysis by cancer type showed that CAV1 G14713A polymorphism was associated with an increased risk of digestive system cancer and other cancer types.
CONCLUSION: Our findings suggest that CAV1 G14713A polymorphisms may modify the risk of cancer, especially digestive system cancer. However, further well-designed studies are warranted to validate this association.

Entities:  

Keywords:  cancer; caveolin-1; polymorphism; susceptibility

Year:  2016        PMID: 27022292      PMCID: PMC4792215          DOI: 10.2147/OTT.S92736

Source DB:  PubMed          Journal:  Onco Targets Ther        ISSN: 1178-6930            Impact factor:   4.147


Introduction

Annual cancer incidence and mortality continue to rise worldwide. There were ~12.7 million new cases and 7.6 million new deaths in 2008.1 Although the pathogenetic mechanism of cancer has not been fully understood, extensive evidence has indicated the important roles of polymorphisms in the key genes during the process of carcinogenesis.2–4 Screening and identification of single nucleotide polymorphisms that are related to cancer susceptibility would greatly benefit individuals at high risk of cancer in the early prevention and treatment settings. Caveolin-1 (CAV1) is a member of the caveolin family of proteins and has been proved to modulate multiple cancer-associated processes, including cellular transformation, tumor growth, cell migration and metastasis, cell death and survival, and angiogenesis in a number of signaling pathways.5–7 Thus, CAV1 is thought to play an important role in tumor development and progression. The CAV1 gene is located on the human chromosome 7q31.1 and has some potentially functional polymorphisms identified. Among these polymorphisms, the associations of CAV1 G14713A polymorphism and cancer susceptibility have been widely investigated; however, results are conflicting.8–19 For instance, Liu et al reported significant positive associations between CAV1 G14713A polymorphism and the risk of breast cancer.16 However, Wu et al reported no significant association between CAV1 G14713A polymorphism and risk of prostate cancer.14 Based on these observations, we conducted the present meta-analysis to clarify the role of CAV1 G14713A polymorphism in carcinogenesis.

Methods

Publication search and inclusion criteria

We searched electronic databases containing PubMed, Chinese National Knowledge Infrastructure, and Chinese Biology Medicine up to June 2015, using the following terms: “caveolin-1 or CAV1” AND “genetic polymorphism or polymorphisms or variant” AND “cancer or carcinoma or tumor”. Additional studies were identified by hand-searching references of original or review articles on this topic. If data were published in more than one article, only the publication with the largest sample size was included. Studies were selected according to the following criteria: 1) studies should have evaluated the association between CAV1 G14713A polymorphism and cancer susceptibility; 2) the type of study design should be a case-control study; and 3) studies should have a detailed genotype frequency of cases and controls.

Data extraction

Two investigators independently screened the studies and extracted the following data from the included studies: first author’s name, publication year, ethnicity, cancer type, total number of cases and controls, and genotype distributions in cases and controls. Disagreements were resolved through discussion with another investigator.

Statistical analysis

Odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated to assess the strength of associations of CAV1 G14713A polymorphism with cancer susceptibility. ORs were calculated using five genetic models: homozygous (AA vs GG), heterozygous (AG vs GG), dominant ([AA + AG] vs GG), recessive (AA vs [AG + GG]), and allele contrast (A vs G). Subgroup analysis was also conducted according to the type of cancer. Heterogeneity among studies was assessed using the Q-test and I2 statistics. When heterogeneity was considered significant (Phet<0.05 or I2>50%), a random-effect model was used; otherwise, a fixed-effect model was used. Sensitivity analysis was performed by removing the single studies, one at a time and recalculating the summarized ORs. Potential publication bias of the included studies was assessed by Begg’s funnel plots and Egger’s test. All P-values were two sided, and all analyses were carried out with STATA 12.0 software package (Stata Corporation, College Station, TX, USA).

Results

Characteristics of studies and main results

As shown in Figure 1, we initially extracted 56 articles in relation to the search words. Among them, 12 articles that met the inclusion criteria were included in this study. The principle characteristics of the 12 eligible studies are summarized in Tables 1 and 2. Six studies were conducted on digestive system cancer and six studies on cancer of other systems. The main meta-analysis results and the heterogeneities are shown in Table 3 and Figure 2. In the overall analysis, CAV1 G14713A polymorphism showed a significant association with increased risk of cancer (A vs G: OR =1.77, 95% CI: 1.49–2.10, Phet<0.01; [AA + AG] vs GG: OR =2.03, 95% CI: 1.64–2.53, Phet<0.01; AA vs [AG + GG]: OR =1.72, 95% CI: 1.40–2.12, Phet<0.01; AA vs GG: OR =2.24, 95% CI: 1.69–2.98, Phet<0.01; AG vs GG: OR =1.98, 95% CI: 1.62–2.41, Phet<0.01). In addition, the results of stratified analysis by tumor type suggested that CAV1 G14713A polymorphism was associated with an increased risk of digestive system cancer (A vs G: OR =2.02, 95% CI: 1.75–2.33, Phet=0.03; [AA + AG] vs GG: OR =2.40, 95% CI: 1.94–2.98, Phet<0.01; AA vs [AG + GG]: OR =2.01, 95% CI: 1.68–2.40, Phet=0.83; AA vs GG: OR =2.84, 95% CI: 2.36–3.42, Phet=0.32; AG vs GG: OR =2.30, 95% CI: 1.84–2.88, Phet=0.01) and cancer of other systems (A vs G: OR =1.55, 95% CI: 1.18–2.03, Phet<0.01; [AA + AG] vs GG: OR =1.72, 95% CI: 1.25–2.36, Phet<0.01; AA vs [AG + GG]: OR =1.49, 95% CI: 1.06–2.10, Phet=0.01; AA vs GG: OR =1.81, 95% CI: 1.16–2.84, Phet<0.01; AG vs GG: OR =1.69, 95% CI: 1.28–2.24, Phet<0.01).
Figure 1

Flow-chart of included studies for this meta-analysis.

Table 1

Main characteristics of included studies

First authorEthnicityCancer typeCaseControl
Wang et al8AsianEsophageal squamous cell carcinoma (digestive system cancer)427427
Zhang et al9AsianGastric cancer (digestive system cancer)412412
Lin et al10AsianGastric cancer (digestive system cancer)358358
Wang et al11AsianLeukemia (other system cancer)266266
Hsu et al12AsianHepatocellular carcinoma (digestive system cancer)298298
Chang et al13AsianUpper urothelial tract cancer (other system cancer)218580
Wu et al14AsianProstate cancer (other system cancer)250500
Tsou et al15AsianNasopharyngeal carcinoma (other system cancer)176176
Liu et al16AsianBreast cancer (other system cancer)1,2321,232
Bau et al17AsianOral cancer (digestive system cancer)620620
Bau et al18AsianBladder cancer (other system cancer)375375
Yang et al19AsianColorectal cancer (digestive system cancer)362362
Table 2

Allele frequency and genotype distributions of cases and controls in included studies

First authorCase (G14713A)
Control (G14713A)
GGGAAAGA + AAGG + GAGAGGGAAAGA + AAGG + GAGA
Wang et al82121684721538059226228112323146404685169
Zhang et al91481758926432347135326510443147369634190
Lin et al10172136501863084802362359033123325560156
Wang et al1111010650156216326206176672390243419113
Hsu et al1216296401362584201761967725102273469127
Chang et al13118722810019030812837714657203523900260
Wu et al1415172279922337412633012941170459789211
Tsou et al151134716631602737911645156016127775
Liu et al167044091195281,1131,8176478013111204311,1121,913551
Bau et al1723827910338251775548539716756223564961279
Bau et al18144160712313044483022459634130341586164
Yang et al19135165622273004352892349632128330564160
Table 3

Meta-analysis of caveolin-1 G14713A polymorphism and cancer susceptibility in Asian population

VariablesAllele contrast (A vs G)
Dominant contrast ([AA + AG] vs GG)
Recessive contrast (AA vs [AG + GG])
I2PhetPzOR (95% CI)I2PhetPzOR (95% CI)I2PhetPzOR (95% CI)
All86%<0.01<0.011.77 (1.49–2.10)86%<0.01<0.012.03 (1.64–2.53)61%<0.01<0.011.72 (1.40–2.12)
Digestive system cancer61%0.03<0.012.02 (1.75–2.33)71%<0.01<0.012.40 (1.94–2.98)0%0.83<0.012.01 (1.68–2.40)
Other cancer types88%<0.01<0.011.55 (1.18–2.03)86%<0.01<0.011.72 (1.25–2.36)70%0.010.021.49 (1.06–2.10)
Homozygous contrast (AA vs GG)Heterozygous contrast (AG vs GG)
All78%<0.01<0.012.24 (1.69–2.98)79%<0.01<0.011.98 (1.62–2.41)
Digestive system cancer14%0.32<0.012.84 (2.36–3.42)68%0.01<0.012.30 (1.84–2.88)
Other cancer types81%<0.010.011.81 (1.16–2.84)78%<0.01<0.011.69 (1.28–2.24)

Abbreviations: Phet, P-value of heterogeneity test; PZ, P-value of Z-test; OR, odds ratio; CI, confidence interval.

Figure 2

Forest plots representing the pooled results of ORs for the association between CAV1 G14713A polymorphism and overall cancer risk.

Note: Weights are from random effects analysis.

Abbreviations: OR, odds ratio; CI, confidence interval; CAV1, caveolin-1.

Sensitivity analysis and publication bias

A sensitivity analysis was performed by omitting every study in turn to check the influence of the removed data. Pooled estimates for all genetic models were insensitive to the removal of individual study, and the corresponding pooled ORs were not substantially altered, suggesting that our results were stable and reliable (Figure 3). Both Begg’s funnel plots and Egger’s test were performed to examine the underlying publication bias (Figure 4). The symmetrical funnel plots and P-value >0.05 for Egger’s test indicated no publication bias in this meta-analysis.
Figure 3

Sensitivity analysis results of the association between CAV1 G14713A polymorphism and overall cancer risk.

Abbreviations: CI, confidence interval; OR, odds ratio; CAV1, caveolin-1.

Figure 4

Begg’s funnel plots of the association between CAV1 G14713A polymorphism and overall cancer risk.

Abbreviations: SE, standard error of the logOR; logOR, natural logarithm of the OR; OR, odds ratio; CAV1, caveolin-1.

Discussion

CAV1 is the major structural protein in caveolae and consists of 178 amino acids; it has been identified as a tumor suppressor in 1989.20 CAV1 plays an important role in many signaling pathways, molecular transport, and cellular proliferation and differentiation, which are potentially involved in the development of human cancer.21 The association of CAV1 G14713A polymorphism with cancer risk has been widely reported, but results are conflicting. For example, some studies indicated that CAV1 G14713A polymorphism was associated with cancer risk, such as esophageal squamous cell carcinoma, gastric cancer, hepatocellular carcinoma, and breast cancer.9,10,12,16 Other studies demonstrated that CAV1 G14713A polymorphism was not associated with the risk of cancer, including prostate cancer and nasopharyngeal carcinoma.14,15 To provide a more detailed overview of the association, five genetic models were used in the current meta-analysis. To our knowledge, this is the first meta-analysis of the association between CAV1 G14713A polymorphism and cancer risk, and the results suggested that CAV1 G14713A polymorphism increased the risk of cancer. In the subgroup analysis by tumor type, CAV1 G14713A polymorphism was significantly associated with an increased risk of digestive system cancer and cancer of other systems. Our meta-analysis had some advantages. For instance, we strictly obeyed the inclusion and exclusion criteria to reduce selection bias. Furthermore, there was no evidence of publication bias in this meta-analysis, and the sensitivity analysis confirmed the reliability and stability of the results. Despite these advantages, limitations should be considered when interpreting our results. First, our results were based on unadjusted estimates. More analyses that are precise can be conducted if individual data, including age and sex, were available. Second, all published studies were based on Asian populations. Therefore, the results of this meta-analysis may be applicable to the specified ethnicity alone.

Conclusion

The present study demonstrated that CAV1 G14713A polymorphism might contribute to individual susceptibility to cancer. However, further well-designed studies are required to evaluate this association.
  21 in total

1.  Progestin-induced caveolin-1 expression mediates breast cancer cell proliferation.

Authors:  M Salatino; W Beguelin; M G Peters; R Carnevale; C J Proietti; M D Galigniana; C G Vedoy; R Schillaci; E H Charreau; M C Sogayar; P V Elizalde
Journal:  Oncogene       Date:  2006-06-26       Impact factor: 9.867

2.  Lysyl oxidase rs1800449 polymorphism and cancer risk among Asians: evidence from a meta-analysis and a case-control study of colorectal cancer.

Authors:  Xueren Gao; Shulong Zhang; Zhansheng Zhu
Journal:  Mol Genet Genomics       Date:  2014-08-12       Impact factor: 3.291

3.  Significant association of caveolin-1 (CAV1) genotypes with prostate cancer susceptibility in Taiwan.

Authors:  Hsi-Chin Wu; Chao-Hsiang Chang; Yung-An Tsou; Chia-Wen Tsai; Cheng-Chieh Lin; Da-Tian Bau
Journal:  Anticancer Res       Date:  2011-02       Impact factor: 2.480

4.  Significant association of caveolin-1 genotypes with bladder cancer susceptibility in Taiwan.

Authors:  Da-Tian Bau; Chao-Hsiang Chang; Ru-Yin Tsai; Hwei-Chung Wang; Rou-Fen Wang; Chia-Wen Tsai; Chun-Hsu Yao; Yueh-Sheng Chen; Song-Kun Shyue; Chih-Yang Huang
Journal:  Chin J Physiol       Date:  2011-06-30       Impact factor: 1.764

5.  The association of Caveolin-1 genotypes with oral cancer susceptibility in Taiwan.

Authors:  Da-Tian Bau; Ming Hsui Tsai; Yung-An Tsou; Chung-Hsing Wang; Chia-Wen Tsai; Shung-Shung Sun; Chun-Hung Hua; Song-Kun Shyue; Ru-Yin Tsai
Journal:  Ann Surg Oncol       Date:  2011-01-19       Impact factor: 5.344

6.  Differential expression and function of caveolin-1 in human gastric cancer progression.

Authors:  Elke Burgermeister; Xiangbin Xing; Christoph Röcken; Mark Juhasz; Jie Chen; Michaela Hiber; Katrin Mair; Maria Shatz; Moti Liscovitch; Roland M Schmid; Matthias P A Ebert
Journal:  Cancer Res       Date:  2007-09-15       Impact factor: 12.701

7.  The contribution of caveolin-1 genotype and phenotype to hepatocellular carcinoma.

Authors:  Chin-Mu Hsu; Mei-Due Yang; Chia-Wen Tsai; Chien-Yi Ho; Wen-Shin Chang; Sheng-Chi Chang; Long-Bin Jeng; Yuhsin Tsai; Fuu-Jen Tsai; Da-Tian Bau
Journal:  Anticancer Res       Date:  2013-02       Impact factor: 2.480

Review 8.  Caveolin-1 in tumor progression: the good, the bad and the ugly.

Authors:  Jacky G Goetz; Patrick Lajoie; Sam M Wiseman; Ivan R Nabi
Journal:  Cancer Metastasis Rev       Date:  2008-12       Impact factor: 9.264

9.  Significant association of caveolin-1 (CAV1) genotypes with upper urothelial tract cancer.

Authors:  Wen-Shin Chang; Song-Shei Lin; Fang-Jing Li; Chia-Wen Tsai; Long-Yuan Li; Chi-Shun Lien; Wen-Ling Liao; Hsi-Chin Wu; Chang-Hai Tsai; Tzu-Ching Shih; Da-Tian Bau
Journal:  Anticancer Res       Date:  2013-11       Impact factor: 2.480

10.  eNOS Genetic Polymorphisms and Cancer Risk: A Meta-Analysis and a Case-Control Study of Breast Cancer.

Authors:  Xueren Gao; Jie Wang; Wenjun Wang; Mingxi Wang; Jianqiong Zhang
Journal:  Medicine (Baltimore)       Date:  2015-07       Impact factor: 1.889

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