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Asian Pacific Journal of Cancer Prevention : APJCP logoLink to Asian Pacific Journal of Cancer Prevention : APJCP
. 2025;26(6):1899–1913. doi: 10.31557/APJCP.2025.26.6.1899

Correlation of VEGF +405C/G Polymorphism with Gastrointestinal Tract Cancers Risk: An Updated Meta-Analysis

Sukhpreet Kaur Walia 1, Vasudha Sambyal 1, Kamlesh Guleria 1,*
PMCID: PMC12374524  PMID: 40542752

Abstract

Background:

The functional polymorphisms of VEGF can affect different cellular processes and play a major role in angiogenesis and tumor development. Several case-control studies have explored the association of VEGF +405C/G polymorphism with GIT cancer risk, however, the results were inconsistent. Therefore, the meta-analysis was conducted to clarify the association.

Methods:

Based on the inclusion and exclusion criteria, relevant data were extracted from PubMed, Google Scholar, Web of Science and Science Direct. Twenty three studies comprising 5,656 cases and 6,319 healthy controls were included in the present meta-analysis and the data was analysed by using online MetaGenyo software.

Results:

In the present study, no significant association was found in any of the genetic models in overall analysis as well as when data was stratified according to the ethnicity (p>0.05). After performing sub-group analysis on the basis of cancer type, significant association was found with increased risk of developing esophageal cancer under allele contrast, recessive, GG vs. CC and GG vs. GC models (p<0.05). Under overdominant model, VEGF +405C/G polymorphism was significantly associated with decreased risk of developing esophageal cancer (p=0.017) and GG vs. GC model showed a significant association with the risk of developing colorectal cancer (p=0.047) and pancreatic cancer (p=0.010). However, GC vs. CC model showed that VEGF +405C/G polymorphism was significantly associated with reduced risk of pancreatic cancer (p=0.039).

Conclusion:

The present updated meta-analysis suggested that VEGF +405C/G polymorphism may serve as a biomarker for determining an individual’s risk of esophageal, colorectal and pancreatic cancer.

Key Words: Meta-analysis, VEGF +405C/G polymorphism, gastrointestinal tract cancers, angiogenesis

Introduction

Cancer is a multifactorial disease and one of the leading cause of mortality worldwide [1]. Gastrointestinal tract (GIT) cancers accounts for more than 25% of all cancer cases [2]. Both environmental and genetic factors influence the susceptibility to different GIT cancers. Ninety percent of the variability in the human genome is due to single nucleotide polymorphisms (SNPs), which have been shown to affect cancer susceptibility by either increasing or decreasing an individual’s risk of developing cancer [3]. SNPs in the untranslated region (UTR) may have functional consequences on mRNA stability and expression, as they change the secondary structure and miRNA target sites within the UTRs [4, 5]. The expression of known genes and signaling pathways involved in cancer are altered by these changes.

VEGF, a heparin-binding glycoprotein, plays a crucial role in endothelial cell proliferation and migration, and increases vascular permeability of tumor cells by the process called angiogenesis [6, 7]. Hypoxia-sensitive regulatory elements are found in the 5’ and 3’ UTRs which contribute to high variability in VEGF production among tissues [8, 9]. VEGF +405C/G (VEGF -634C/G) polymorphism present in 5′ UTR is situated in the MZF1 transcription factor’s potential binding site, it affects the translation efficiency of VEGFA and is associated with prognosis of many cancers [10]. It also affects the expression at the post-translation level by changing the activity of the internal ribosomal entry site B, and by promoting the initiation of translation at the AUG codon [11].

Many case-control studies have analyzed the effect of VEGF +405C/G polymorphism on different GIT cancers in different populations but the results were inconsistent and contradictory (Table 1). This may be due to the small sample size, ethnic differences, and heterogeneity between study samples. This brings forth the importance of meta-analysis, which provides the accurate estimate of genetic effect by pooling the individual study data [12]. A meta-analysis has already been done to find the association between VEGF +405C/G polymorphism and GIT cancer risk [13] .This meta-analysis included only 11 studies [14-24], however, it did not include all articles, such as those on esophageal cancer [25], oral cancer [26], gastric cancer [27, 28], hepatocellular carcinoma [29], pancreatic cancer [30, 31] and colorectal cancer [32, 33]. The relationship between VEGF +405C/G polymorphism and overall cancer risk was analyzed by another meta-analysis on 70 studies [34]. In this meta-analysis, authors included only 17 studies on GIT cancers, however there are additional studies that have reported the role of VEGF +405C/G polymorphism in different GIT cancers but were not included in this meta-analysis like on esophageal cancer [25], gastric cancer [28, 35, 36], hepatocellular carcinoma [29], pancreatic cancer [30, 31], colorectal cancer [33]. Furthermore, many case-control studies on different GIT cancers have been published subsequent to these meta-analyses [36-43]. So, an updated meta-analysis that included all the studies that were left out of earlier meta-analysis is needed. Moreover studies where genotypic distribution of controls was deviated from Hardy Weinberg Equilibrium (HWE) were included in both of these meta-analyses [21-24], which may impact the overall analysis.

Table 1.

Characteristics of the Published Case-Control Studies on VEGF +405C/G Polymorphism in Gastrointestinal Tract Cancers

Genotype Distribution
Cancer Ethnicity Country Cases/Controls Source of control Cases Controls HWE in control p-value Reference Study included in the meta analysis
CC GC GG CC GC GG
Oral Caucasian Serbia 114/126 - 11 55 48 16 49 61 0.22 [26] Yes
Caucasian Germany 80/40 - 20 23 37 10 12 18 0.017 [23] No
Esophageal Asian India 231/233 PB 17 98 116 20 110 103 0.21 [43] Yes
Asian India 150/141 HB 9 57 84 17 66 58 0.788 [25] Yes
Caucasian USA 308/546 HB 29 124 155 62 251 233 0.65 [17] Yes
Gastric Asian India 180/360 - 16 64 100 28 160 172 0.26 [39] Yes
Asian Korea 151/367 - 28 70 53 59 178 130 0.88 [38] Yes
Mixed Brazil 177/260 HB 27 82 68 29 117 114 0.901 [36] Yes
Asian China 401/403 PB 66 209 126 65 189 149 0.69 [28] Yes
Asian China 150/150 HB 29 47 74 30 44 76 0.000016 [24] No
Caucasian USA 171/100 HB 30 72 69 21 28 51 0.00012 [22] No
Middle East Oman 130/130 PB 22 59 49 14 54 62 0.66 [20] Yes
Asian China 540/561 PB 92 287 161 97 278 186 0.69 [27] Yes
Caucasian Greece 100/100 PB 19 40 41 9 39 52 0.66 [35] No
Caucasian Greece 100/100 PB 19 40 41 9 39 52 0.66 [15] Yes
Asian Korea 413/413 PB 31 253 129 84 223 106 0.09 [14] Yes
Hepatocellular Asian China 476/526 HB 82 232 162 78 248 200 0.93 [37] Yes
Asian China 92/99 PB 18 40 34 13 52 34 0.31 [29] Yes
Pancreatic Asian India 80/87 HB 10 28 42 9 49 29 0.07 [31] Yes
Caucasian Poland 85/50 - 47 25 13 8 30 12 0.14 [30] Yes
Colorectal Asian Indonesia 40/40 - 5 24 11 12 19 9 0.77 [42] Yes
Middle East Turkey 40/53 PB 8 21 11 14 17 22 0.01 [41] No
Middle East Iran 264/344 HB 35 103 126 45 159 140 0.98 [40] Yes
Caucasian Greece 224/263 PB 34 92 98 49 126 88 0.74 [33] Yes
Caucasian Sweden 302/336 PB 37 130 135 32 137 167 0.61 [32] Yes
Caucasian Greece 312/362 HB 59 125 128 76 141 145 0.00026 [21] No
Caucasian Italy 301/91 PB 48 135 118 15 46 30 0.71 [19] Yes
Asian Korea 465/413 PB 106 193 166 84 223 106 0.09 [18] Yes
Caucasian Austria 432/430 PB 47 192 193 43 195 192 0.52 [16] Yes
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Significant p-values are highlighted in bold

Therefore, we carried out an up-to-date meta-analysis of all eligible case-control studies to investigate the relationship between VEGF +405C/G polymorphism and GIT cancer risk. Finding the functional biomarkers associated with cancer risk may help in the development of drugs as well as valuable insight into the pathophysiology for particular malignancy. We hypothesized that the VEGF +405C/G polymorphism might be associated with altered risk of GIT cancers, and a comprehensive meta-analysis will provide a better understanding of its role in different populations.

The present meta-analysis aims

- To determine the overall association between VEGF +405C/G polymorphism and GIT cancer risk,

- To analyze the association of VEGF +405C/G polymorphism in different ethnic groups and cancer subtypes,

- To assess the heterogeneity, publication bias among the included studies,

- To examine the impact of individual study on the overall analyses by using sensitivity analysis.

In this meta-analysis, we statistically combine data from previously published case-control studies across different populations that investigated the association between the VEGF +405C/G polymorphism and GIT cancer risk.

Search Strategy

A comprehensive literature search was conducted by the three authors: SKW (Research Scholar), KG (Associate Professor and Head of Human Genetics Department) and VS (Professor) to identify relevant case-control studies for the present meta-analysis. For this, all the available literature published till March, 2024 on the association of VEGF +405C/G polymorphism with gastrointestinal tract (GIT) cancer risk was retrieved from different online databases such as PubMed, Google Scholar, Web of Science and Science Direct. The keywords and terms used to search the relevant articles were: vascular endothelial growth factor, VEGF +405C/G polymorphism, VEGF +634C/G polymorphism, rs2010963, GIT cancers risk, case-control studies, genetic association studies. We also identified articles by manually searching the references of different articles, reviews and previous meta-analyses. We included articles that were published in English language only. The selection process used was illustrated as a flow diagram (Figure 1).

Figure 1.

Figure 1

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Flow Diagram Showing the Selection Process for Meta-Analysis by Using PRISMA Guidelines

Inclusion and Exclusion Criteria

Case-control studies that have evaluated the association of VEGF +405C/G polymorphism with different GIT cancers with sufficient genotype data to calculate the odds ratio (OR) and 95% CI were included. However, short/brief reports, animal model studies, case-only studies, and the case-controls studies in which genotypic frequencies were deviated from HWE in controls were not included in the present meta-analysis. The characteristics of the studies includes and excluded have been detailed in Table 1.

Materials and Methods

The present meta-analysis was performed following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines [44]. The PICO (Participants, Intervention, Comparison, Outcome) criteria was used to design the study questions [45].

Data Extraction and Quality Assessment

Based on the inclusion and exclusion criteria, relevant data were extracted from the individual publication such as: ethnicity of population, number of cases and controls, genotype distribution among cases and controls, HWE p-value, last name of the first author and year of publication. The New-Castle Ottawa Scale (NOS) was used to evaluate the quality of eligible studies [46]. NOS is based on star scoring system and comprised three parameters:

a. Selection (Is the case defined adequately?, Representativeness of cases, Selection of controls and Definition of controls)

b. Comparability (Comparability of cases and controls on the basis of age, gender, ethnicity etc.)

c. Exposure (Ascertainment of exposure, Same method of ascertainment for cases and controls and Non-Response Rate).

Each publication can receive up to 9 stars and publications that received 5 or more stars are regarded as of high quality. Publications included in the present meta-analysis were of high quality, as indicated by the overall score, which ranged from 6 to 8 (Table 2).

Table 2.

The Newcastle-Ottawa Scale (NOS) for the Assessment of Case-Control Studies Included in the Meta-Analysis

Selection Comparability Exposure Total Score Reference
Case defined adequately Representativeness of the cases Selection of controls Definition of controls Comparability of cases/ controls Ascertainment of exposure Same selection method of ascertainment of cases-controls Same Non response rate in cases/ controls
* * * * ** * * - 8 [43]
* * - * ** * * * 8 [25]
* * - * ** * * - 7 [17]
* * - * ** * * - 7 [26]
* * - * ** * * - 7 [39]
* * - * ** * * - 7 [38]
* * - * ** * * - 7 [36]
* * * * ** * * - 8 [28]
* * * * ** * * - 8 [20]
* * * * ** * * * 8 [27]
* * * * ** * * * 8 [15]
* * * * ** * * - 8 [14]
* * - * ** * * - 7 [37]
* * * * ** * * - 8 [29]
* * - * ** * * - 7 [31]
* * - * ** * * - 7 [30]
* * - * ** * * - 7 [42]
* * - * ** * * - 7 [40]
* * * * ** * * - 8 [33]
* * * * ** * * - 8 [32]
* * * * - * * - 6 [19]
* * * * - * * - 6 [18]
* * * * ** * * - 8 [16]
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Statistical Analysis

Data analyses in the present meta-analysis were performed by using online statistical software, MetaGenyo [47]. Pooled odds ratio (OR) and 95% confidence intervals (CI) were used to evaluate the association between VEGF +405C/G polymorphism and GIT cancer risk. The association was assessed under different genetic models. p<0.05 was considered as statistically significant. Cochran’s Q-test was used to assess the heterogeneity (I2) among studies. p<0.05 or I2 > 50% indicates the presence of heterogeneity and in this case random effect model was selected (Dersimonian-Laird method). If p≥0.05 and I2 <50%, fixed effect model was used (Mantel-Haenszel method). Publication bias was assessed by Begg’s funnel plot [48] and by Egger’s linear regression test [49], p<0.05 was considered as significant publication bias. In order to find probable outliers, a sensitivity analysis was also carried out by excluding each study at a time and then re-evaluating the results.

Results

Twenty three studies comprising 5656 cases and 6319 healthy controls were included in the present meta-analysis. The characteristics of the included studies have been detailed in Table 1. Out of 23 studies, 7 studies were on colorectal cancer, 3 studies were on esophageal cancer, 8 studies were on gastric cancer, 2 studies were on hepatocellular cancer, 2 studies were on pancreatic cancer and one study was on oral cancer. From 23 studies, 12 studies have evaluated the association of VEGF +405C/G polymorphism with the risk of developing GIT cancers in Asian population, 8 studies in Caucasian population, 2 studies with Middle East population and one study with mixed ethnicity.

Pooled Analysis

Analysis was done by using all genetic models in order to find the association between VEGF +405C/G polymorphism and GIT cancer risk. Overall no significant association was found in any of the genetic models (p>0.05). Stratification analysis on the basis of ethnicity, also revealed no significant association between VEGF +405C/G polymorphism and GIT cancer risk in any of the genetic model (p>0.05) (Table 3). After performing sub-group analysis on the basis of cancer type, we found a significant association of VEGF +405C/G polymorphism with increased risk of developing esophageal cancer under allele contrast (OR=1.29; 95%CI, 1.11-1.51; p=0.001), recessive (OR=1.41; 95%CI, 1.15-1.72; p=0.0008), GG vs. CC (OR=1.56; 95%CI, 1.09-2.24; p=0.016), and GG vs. GC (OR=1.37; 95%CI, 1.11-1.69; p=0.0029) models. Under over dominant model, VEGF +405C/G polymorphism was significantly associated with decreased risk of developing esophageal cancer (OR=0.78; 95%CI, 0.64-0.96; p=0.017). GG vs. GC model showed a significant association of VEGF +405C/G polymorphism with the risk of developing colorectal cancer (OR=1.26; 95%CI, 1.00-1.58; p=0.047) and pancreatic cancer (OR=2.03; 95%CI, 1.18-3.50; p=0.010). However, GC vs. CC model showed that VEGF +405C/G polymorphism was significantly associated with reduced risk of pancreatic cancer (OR=0.26; 95%CI, 0.07-0.94; p=0.039) (Table 4) (Figure 2).

Table 3.

Association of VEGF +405C/G Polymorphism with Gastrointestinal Cancer Risk According to Ethnicity

Model Ethnicity Number of studies Test of association Test of heterogeneity Publication bias
OR 95% CI p-value Model p-value I2 Egger's test
p-value
Allele contrast Overall 23 1.02 (0.92- 1.13) 0.67 Random 0 0.7 0.62
(G vs. C)
Asian 12 1.11 (0.98- 1.26) 0.09 Random 0.0007 0.66 0.17
Caucasian 8 0.92 (0.74- 1.14) 0.44 Random 0 0.78 0.09
Middle East 2 0.92 (0.56- 1.51) 0.74 Random 0.02 0.81 NA
Mixed 1 0.81 (0.61- 1.08) 0.15 Fixed NA NA NA
Recessive model (GG vs. GC+CC) Overall 23 1.08 (0.95- 1.23) 0.22 Random 0 0.62 0.87
Asian 12 1.18 (0.98- 1.42) 0.08 Random 0.0006 0.66 0.12
Caucasian 8 1.01 (0.81- 1.27) 0.89 Random 0.017 0.59 0.29
Middle East 2 0.96 (0.49- 1.90) 0.92 Random 0.021 0.81 NA
Mixed 1 0.79 (0.54- 1.18) 0.26 Fixed NA NA NA
Dominant model (GG+GC vs. CC) Overall 23 0.96 (0.78- 1.16) 0.65 Random 0 0.67 0.58
Asian 12 1.11 (0.85- 1.46) 0.43 Random 0.0001 0.7 0.48
Caucasian 8 0.8 (0.54- 1.19) 0.28 Random 0.0009 0.71 0.12
Middle East 2 0.84 (0.57- 1.25) 0.4 Fixed 0.248 0.25 NA
Mixed 1 0.69 (0.39- 1.22) 0.21 Fixed NA NA NA
Overdominant (GC vs. CC +GG) Overall 23 0.89 (0.79- 1.02) 0.09 Random 0 0.63 0.17
Asian 12 0.89 (0.74- 1.08) 0.25 Random 0.0001 0.72 0.24
Caucasian 8 0.87 (0.70- 1.09) 0.23 Random 0.016 0.59 0.46
Middle East 2 0.85 (0.65- 1.12) 0.26 Fixed 0.132 0.56 NA
Mixed 1 1.05 (0.72- 1.55) 0.78 Fixed NA NA NA
GG vs. CC Overall 23 1.01 (0.83- 1.25) 0.86 Random 0 0.65 0.75
Asian 12 1.2 (0.89- 1.60) 0.21 Random 0.0003 0.68 0.28
Caucasian 8 0.87 (0.59- 1.29) 0.5 Random 0.0032 0.67 0.1
Middle East 2 0.8 (0.36- 1.81) 0.59 Random 0.075 0.68 NA
Mixed 1 0.64 (0.35- 1.17) 0.15 Fixed NA NA NA
GG vs. GC Overall 23 1.11 (0.98- 1.27) 0.1 Random 0.0004 0.57 0.46
Asian 12 1.18 (0.97- 1.44) 0.1 Random 0.0004 0.68 0.15
Caucasian 8 1.09 (0.95- 1.25) 0.23 Fixed 0.11 0.4 0.75
GG vs. GC Middle East 2 1.03 (0.55- 1.95) 0.92 Random 0.042 0.76 NA
Mixed 1 0.85 (0.56- 1.28) 0.44 Fixed NA NA NA
GC vs. CC Overall 23 0.91 (0.75- 1.12) 0.37 Random 0 0.65 0.41
Asian 12 1.04 (0.77- 1.39) 0.79 Random 0.0001 0.72 0.86
Caucasian 8 0.79 (0.54- 1.15) 0.21 Random 0.006 0.65 0.19
Middle East 2 0.79 (0.52- 1.20) 0.27 Fixed 0.699 0 NA
Mixed 1 0.75 (0.41- 1.36) 0.35 Fixed NA NA NA
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Figure 2.

Figure 2

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Forest Plots to Identify the Relationship between VEGF +405C/G Polymorphism and GIT Cancer Risk Using Different Genetic Models

Heterogeneity Analysis

In overall analysis, substantial heterogeneity was observed in all genetic association models (I2 >50%), so random effect model was used. However, after stratification on basis of ethnicity and cancer type, some did (I2 >50%), and some did not (I2 <50%), exhibit heterogeneity (Tables 3, 4).

Table 4.

Association of VEGF +405C/G Polymorphism with Gastrointestinal Cancer Risk According to Cancer Type

Model Cancer type Number of studies Test of association Test of heterogeneity Publication bias
OR 95% CI p-value Model p-value I2 Egger's test
p-value
Allele contrast Overall 23 1.02 (0.92- 1.13) 0.67 Random 0 0.7 0.62
(G vs. C)
Colorectal 7 1.09 (0.99- 1.19) 0.07 Fixed 0.107 0.42 0.39
Esophageal 3 1.29 (1.11- 1.51) 0.001 Fixed 0.326 0.11 0.47
Gastric 8 0.94 (0.78- 1.12) 0.49 Random 0.0002 0.75 0.22
Hepatocellular 2 0.88 (0.75- 1.04) 0.14 Fixed 0.813 0 NA
Oral 1 0.93 (0.63- 1.36) 0.7 Fixed NA NA NA
Pancreatic 2 0.73 (0.19- 2.86) 0.65 Random 0.0001 0.94 NA
Recessive model (GG vs. GC+CC) Overall 23 1.08 (0.95- 1.23) 0.22 Random 0 0.62 0.87
Colorectal 7 1.22 (0.99- 1.51) 0.059 Random 0.032 0.56 0.7
Esophageal 3 1.41 (1.15- 1.72) 0.0008 Fixed 0.46 0 0.5
Gastric 8 0.92 (0.76- 1.11) 0.39 Random 0.032 0.54 0.49
Hepatocellular 2 0.88 (0.69- 1.12) 0.29 Fixed 0.384 0 NA
Oral 1 0.77 (0.46- 1.29) 0.32 Fixed NA NA NA
Pancreatic 2 1.17 (0.31- 4.38) 0.82 Random 0.014 0.83 NA
Dominant model (GG+GC vs. CC) Overall 23 0.96 (0.78- 1.16) 0.65 Random 0 0.67 0.58
Colorectal 7 0.96 (0.81- 1.15) 0.7 Fixed 0.36 0.08 0.06
Esophageal 3 1.34 (0.94- 1.89) 0.09 Fixed 0.48 0 0.47
Gastric 8 0.94 (0.63- 1.39) 0.75 Random 0 0.79 0.3
Hepatocellular 2 0.79 (0.58- 1.09) 0.15 Fixed 0.49 0 NA
Oral 1 1.36 (0.60- 3.07) 0.46 Fixed NA NA NA
Pancreatic 2 0.35 (0.07- 1.77) 0.2 Random 0.012 0.84 NA
Overdominant (GC vs. GG +CC) Overall 23 0.89 (0.79- 1.02) 0.09 Random 0 0.63 0.17
Colorectal 7 0.84 (0.69- 1.02) 0.075 Random 0.048 0.52 0.38
Esophageal 3 0.78 (0.64- 0.96) 0.017 Fixed 0.851 0 0.54
Gastric 8 1.1 (0.98- 1.24) 0.106 Fixed 0.19 0.3 0.29
Hepatocellular 2 0.99 (0.79- 1.25) 0.971 Fixed 0.18 0.45 NA
Oral 1 1.46 (0.88- 2.45) 0.144 Fixed NA NA NA
Pancreatic 2 0.35 (0.22- 0.57) 1.67 Fixed 0.407 0 NA
GG vs. CC Overall 23 1.02 (0.83- 1.25) 0.86 Random 0 0.65 0.75
Colorectal 7 1.13 (0.93- 1.38) 0.22 Fixed 0.25 0.24 0.4
Esophageal 3 1.56 (1.09- 2.24) 0.016 Fixed 0.38 0 0.49
Gastric 8 0.89 (0.58- 1.36) 0.58 Random 0 0.79 0.39
Hepatocellular 2 0.76 (0.54- 1.07) 0.12 Fixed 0.89 0 NA
Oral 1 1.14 (0.49- 2.69) 0.76 Fixed NA NA NA
Pancreatic 2 0.49 (0.07- 3.36) 0.47 Random 0.01 0.85 NA
GG vs. GC Overall 23 1.11 (0.98- 1.27) 0.1 Random 0.0004 0.57 0.46
Colorectal 7 1.26 (1.00- 1.58) 0.047 Random 0.027 0.58 0.97
Esophageal 3 1.37 (1.11- 1.69) 0.0029 Fixed 0.65 0 0.52
Gastric 8 0.92 (0.81- 1.05) 0.23 Fixed 0.19 0.29 0.94
Hepatocellular 2 0.92 (0.72- 1.19) 0.53 Fixed 0.24 0.26 NA
Oral 1 0.7 (0.41- 1.20) 0.19 Fixed NA NA NA
Pancreatic 2 2.03 (1.18- 3.50) 0.01 Fixed 0.26 0.22 NA
GC vs. CC Overall 23 0.91 (0.75- 1.12) 0.37 Random 0 0.65 0.41
Colorectal 7 0.85 (0.70- 1.03) 0.1 Fixed 0.36 0.08 0.005
Esophageal 3 1.13 (0.79- 1.64) 0.49 Fixed 0.68 0 0.42
Gastric 8 0.98 (0.67- 1.44) 0.93 Random 0.0001 0.76 0.22
Hepatocellular 2 0.82 (0.59- 1.15) 0.25 Fixed 0.304 0.05 NA
Oral 1 1.63 (0.69- 3.85) 0.26 Fixed NA NA NA
Pancreatic 2 0.26 (0.07- 0.94) 0.039 Random 0.06 0.71 NA
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Significant p-values are highlighted in bold

Publication Bias

No overall publication bias was observed as assessed by symmetrical Begg’s funnel plots (Figure 3) and by Egger’s test (p>0.05). Subgroup analysis on the basis of cancer type revealed publication bias in colorectal cancer under GC vs. CC model (Tables 3, 4).

Figure 3.

Figure 3

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Funnel Plots for Detection of Publication Bias Using Different Genetic Models

Sensitivity Analysis

Sensitivity analysis was carried out by removing one study at a time from the pooled analysis in order to examine the impact of individual study on the results. Results demonstrated that removal of any study had no observable impact on the overall analysis (Figure 4).

Figure 4.

Figure 4

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Sensitivity Analysis by Using Different Genetic Model

Discussion

Gastrointestinal tract cancers are among the most common type of cancers which are caused by the combined effect of various factors like environment, genetic and epigenetic modifications. Genetic factors are the most significant contributing factor in the development of cancer. SNPs are the genetic markers that are widely used in the cancer research and identification of SNPs that are significantly associated with cancer risk will be useful for developing therapeutic approaches [50]. The functional polymorphisms of VEGF can affect different cellular processes and play a major role in angiogenesis and tumor development [51]. Genetic polymorphisms in VEGF may alter VEGF production and activity, resulting in variations in tumor development among individuals. VEGF +405C/G polymorphism was found to be associated with decreased VEGF protein expression and plays a role in the development of tumors [10, 52]. Many case-control studies have detected the effect of VEGF +405C/G polymorphism on different GIT cancers however, the results were inconclusive or controversial. So, a comprehensive meta-analysis was conducted to evaluate the association of VEGF +405C/G polymorphism with GIT cancer susceptibility. No significant association was found between VEGF +405C/G polymorphism and GIT cancers risk in the present meta-analysis. However, stratification analysis on the basis of cancer type showed that VEGF +405C/G polymorphism was associated with increased risk of developing colorectal cancer under GG vs. GC model. A meta-analysis conducted on GIT cancers involving 2862 cases and 3028 controls reported a significant association of VEGF +405C/G polymorphism with colorectal cancer risk under recessive model [13]. No significant association of VEGF +405C/G polymorphism with cancer risk was reported in other meta-analysis [53]. In meta-analysis of 70 case-control studies, including 25,245 cases 28,219 controls reported a significant association with increased cancer risk under the CG vs. GG, dominant, and allele contrast models in African population. An increased risk of urogenital cancers was reported under CG vs. GG, CC vs. GG, CC vs. CG, dominant, recessive and allele contrast models. Reduced risk of osteosarcoma was observed under the CC vs. CG model, while an increased risk of osteosarcoma was identified under the overdominant model. A significant association with reduced thyroid cancer risk was reported under the CC vs. GG, recessive, and allele contrast models [34].

Previous studies on the correlation between VEGF +405C/G polymorphism and different GIT cancers reported varied results. The GG genotype of VEGF +405C/G polymorphism was significantly associated with increased risk of esophageal cancer in patients from Kashmir, North-West India [25]. Similarly, in the present study significant association was found with increased risk of esophageal cancer under allele contrast, recessive, GG vs. CC and GG vs. GC models when data was stratified on the basis of cancer type. No association of VEGF +405C/G polymorphism with esophageal cancer risk was reported in Caucasian population [17]. A significant association of VEGF +405C/G polymorphism with increased risk of colorectal cancer under GG vs. GC model was observed in the present study. Our findings were different from some previously published studies. CG genotype, combined CG+CC genotypes and C allele of VEGF +405C/G polymorphism were associated with decreased risk of colorectal cancer in Italian [19], Korean [18] and Caucasian [33] patients respectively. There was no association of VEGF +405C/G polymorphism with colorectal cancer risk in Caucasian [16], Swedish population [32].

Present meta-analysis has many strengths: In the present meta-analysis substantially larger number of studies was included than the previous meta-analysis on VEGF +405C/G polymorphism with GIT cancers susceptibility, thus will enhance the statistical power of the study and provide the more precise results. Present meta-analysis included studies in which genotype distribution in controls were in HWE. Moreover, high quality studies as assessed by New-Castle Ottawa scale were included in the present meta-analysis. Additionally, we conducted a sensitivity analysis, which demonstrated that individual study had no impact on the overall outcome.

There are some limitations of the present meta-analysis: Significant heterogeneity was observed, which may influence the interpretation of results. Subgroup analysis on the basis of cancer type showed publication bias in colorectal cancer under GC vs. CC model.

In conclusion, the present updated meta-analysis observed a significant association between VEGF +405C/G polymorphism and GIT cancers (esophageal cancer, colorectal cancer, pancreatic cancer). While the present study indicate that VEGF +405C/G polymorphism may play a role in susceptibility to GIT cancer, the observed heterogeneity highlights the need for further research to identify the underlying mechanisms and also the interactions with environmental factors.

Author Contribution Statement

KG and VS designed the study. SKW and KG prepared the manuscript. All authors read and approved the manuscript.

Acknowledgements

Availability of data

All data has been included in the manuscript.

Conflict of interest

All authors declare that they have no conflict of interest.

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Data Availability Statement

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