Association between CTLA4 + 49A/G polymorphism and risk of hepatocellular carcinoma: a systematic review and meta-analysis

Abstract The aim of this systematic review and meta-analysis was to compile the data examining the association between the CTLA4 + 49 A/G polymorphism and the risk for HCC. Multiple databases were systematically searched for eligible studies and the pooled odds ratios (ORs) were generated using five genetic models. Pooled data from 11 studies with 3,055 HCC patients and 3,450 controls found no statistically significant association between the polymorphism and HCC risk, both overall and in subgroup analyses. In conclusion, the current meta-analysis shows that the CTLA4 + 49 A/G polymorphism is not significantly associated with the risk of developing HCC.


Introduction
Hepatocellular carcinoma (HCC) is a form of liver cancer that originates in liver cells, also called hepatocytes.HCC is a leading cause of cancer-related deaths worldwide and is particularly common in areas with a high incidence of viral hepatitis and cirrhosis. [1]Risk factors for HCC include chronic infection with hepatitis B or C virus, liver cirrhosis, heavy alcohol use, and exposure to certain toxins. [2]More recently, inherited genetic variants have also been shown to influence disease risk, suggesting that genetic factors play an important role in the development of HCC. [3]iven the important role that chronic hepatitis virus infection plays in HCC, many genetic studies have focused on the association between immune-related genes and the risk of developing the cancer.One of these genes is CTLA4, which encodes the immunosuppressive protein cytotoxic T-lymphocyte associated protein 4 (CTLA4), a critical component of the immunoglobulin classes. [4]It is a costimulatory CD28-like molecule expressed on stimulated T cells and is considered a T lymphocyte inhibitory cytokine.Apart from inhibiting T-cell activation and proliferation, CTLA-4 may also cause apoptosis in activated T cells in a Fasindependent manner. [5]CTLA-4 can also bind to CD80 (B7-1) and possibly CD86 (B7-2), which inhibits excitatory signaling by preventing expression of interleukin-2 (IL-2). [6]It is suggested that overexpression of CTLA4 significantly decreases the antitumor activity of cells during the carcinogenesis process.On the other hand, inhibition of CTLA4 activation increases anti-cancer activity.This explains why previous studies have reported a higher expression of CTLA4 in cancer patients than in healthy controls. [7]enetic polymorphisms can alter protein function and gene expression, affecting cellular activity and influencing cancer risk. [8,9]More than 100 polymorphisms are currently known in the CTLA4 gene region.Among these, notable polymorphisms include the −318 C/T, −1661 A/G, and +6230 G/A variants.However, one of the best studied of these variants is the +49 A/G polymorphism, which results in an amino acid substitution of Thr/Ala in the peptide leader sequence of the CTLA-4 protein.This specific polymorphism stands out due to its potential functional implications and its frequent mention in scientific literature.Compared to other CTLA4 polymorphisms, the +49 A/G has been extensively researched for its association with various diseases, especially cancers. [10]herefore, numerous studies have been conducted to investigate the association between this polymorphism and HCC risk, but the results are conflicting.Given the extensive data available and the conflicting results on the +49 A/G polymorphism, it became a prime candidate for a comprehensive analysis.In this study, we performed a systematic review and meta-analysis to investigate the contribution of the polymorphism to HCC risk.

Literature search
The PubMed, Scopus, Web of Science, China National Knowledge Infrastructure, Wanfang, and VIP databases were searched in December 2022 using the search term "CTLA4 AND polymorphism AND hepatocellular carcinoma" to find relevant articles for meta-analysis.No language restriction was applied.EndNote was used to deduplicate the search results.The abstract and title of unique search entries were independently reviewed by two authors to identify potential studies.Full texts were then retrieved and checked for eligibility.The inclusion criteria for studies required that they examined the association between the CTLA4 + 49 polymorphism and HCC risk.Studies with insufficient data or those that did not meet the inclusion criteria were excluded from the analysis.In addition, a manual search was performed by reviewing the references of potentially relevant articles.

Data extraction
Two independent reviewers performed the data extraction.The following information was extracted from the studies that met the requirements for inclusion: Author name, country where the study was conducted, genotype and allele information, source of control used in the study, Hardy-Weinberg equilibrium (HWE).Subsequently, the reviewers thoroughly examined the extracted data for any discrepancies.In case of discrepancies, a third reviewer was consulted or consensus was reached to resolve discrepancies.

Data synthesis
The modified Newcastle-Ottawa scale (NOS) was used to assess the quality of included studies. [11]Five genetic models, including the homozygous additive, heterozygous additive, dominant, recessive, and allele contrast models, were used in calculating odds ratios (ORs) and 95% confidence intervals (CIs).Meta-analysis was only performed when there was more than one included study.A forest plot was generated for each genetic model.A sensitivity analysis was performed to exclude one study at a time to determine how each study affected the final results.To examine possible sources of heterogeneity, subgroup analysis was performed by ethnicity, HWE conformity, and source of control.In addition, Egger's test and funnel plot were used to assess publication bias.STATA software was used for each analysis.In addition, PS Power and Sample Size Calculation software was used to calculate the power of the current meta-analysis compared to that of the previous meta-analyses.Trial sequential analysis [12] was subsequently performed using the TSA software developed by the Copenhagen Trial Unit.

Study selection
Forty-one (41) records from multiple databases, including PubMed (N = 15), Scopus (N = 10), Web of Science (N = 9), Wanfang (N = 0), CNKI (N = 6), and VIP (N = 1), were retrieved during the initial literature search.After deduplication, 20 records remained.Of these, 11 studies were excluded, of which three were meta-analyses and eight were not relevant to the study.Two additional studies were found during the hand search. [13]ltimately, 11 studies were included in the meta-analysis. [13,14]A PRISMA flow diagram for study selection is provided in Figure 1.

Study characteristics
The characteristics of the study are shown in Table 1.The meta-analysis included a total of 11 studies involving 3,055 HCC patients and 3,450 control subjects.The majority of the studies -nine of the 11 -were conducted in China, another in Pakistan, and one in Egypt.All studies were conducted in Asia, with the exception of El-Said et al. 2014 that   was conducted in Egypt, a transcontinental country.Four studies used population-based controls, and seven used hospital-based controls.In one study, HWE was not followed.According to the NOS, all studies included in the meta-analysis were considered to be of good quality (Table 2).

Power calculation
Calculation with the PS Power and Sample Size Calculation software indicates that the current meta-analysis had a power of 0.542.In comparison, meta-analyses by Xiaolei et al., [15] Wang et al., [16] and El Awady et al. [17] had a power of 0.303, 0.519 and 0.236, respectively.

Trial sequential analysis
Trial sequential analysis was performed to determine whether there is enough evidence for the observed lack of genetic association (Figure 4 and Supplementary Figure S3).In the plots, it appears that the z-score did not cross the O'Brien Fleming trial sequential monitoring boundary    in all genetic models, indicating that a significant effect has not been observed.Thus, additional studies may be needed to reach a conclusion about the association between CTLA4 + 49 polymorphism and HCC.

Discussion
The non-synonymous amino acid shift from threonine to alanine caused by the CTLA4 + 49 polymorphism alters the polarity of the amino acid and may affect protein functionality. [18]For this reason, it has been hypothesized that the +49 polymorphism affects T cell self-reactivity and is associated with autoimmune diseases such as autoimmune liver disease as well as the resolution of HCV infection leading to HCC. [19][20][21][22] Numerous studies have investigated the association between the polymorphism and HCC risk; however, the results are conflicting.The aim of the current study was to address the conflicting findings of the association between CTLA4 + 49 polymorphism and the risk of HCC through a meta-analysis.The results of the meta-analysis showed that there was no statistically significant association between the CTLA4 + 49 polymorphism and HCC risk in any of the five genetic models studied (homozygous additive, heterozygous additive, dominant, recessive, and allele contrast).Sensitivity analysis showed that no single study had a significant effect on the overall results, indicating that the results were reliable.In addition, subgroup analyses by source of control, HWE, or ethnicity did not reveal any significant associations.It is worth noting that only one study was conducted in non-Asians and only one study deviated from the HWE; therefore, no pooled analysis was conducted for non-Asians and the non-HWE subgroup.In addition, there was no evidence of publication bias, underscoring the validity of the results of the meta-analysis.This is not the first meta-analysis to examine the association between CTLA4 + 49 polymorphism and risk for HCC.The first meta-analysis was conducted in 2015 by Xiaolei et al., [15] which included only two individual studies and found a significant association between the G allele of the polymorphism and increased risk of HCC.A few years later, Wang et al. [16] performed another meta-analysis that included four studies and made a similar observation that carriers of the G allele were associated with an increased risk of HCC.More recently, El Awady et al. [17] found a significant association between the CTLA4 + 49 polymorphism and an increased risk of HCC in the recessive model in their meta-analysis involving eight studies.In contrast, the current meta-analysis involving 11 studies showed no significant association between CTLA4 + 49 polymorphism and HCC risk.The inclusion of more studies suggests that our study power is higher and that our results better estimate the true situation.In addition, knowing the importance of careful data extraction in a meta-analysis, [23] we performed a thorough review of the data included in our study with those of previous meta-analyses.During the thorough review, we found that all individual studies included in the previous meta-analyses were also included in our analysis and that all raw data and analysis methods of the previous meta-analyses were correct.This means that the difference between our results and those of the previous meta-analyses was solely due to the improved study power in our study.
There are several limitations to this meta-analysis.First, the majority of the studies included in the meta-analysis were conducted in China, which may have contributed to some homogeneity in the study population.Since the results of genetic association studies are usually influenced by ethnicity, it would be interesting to conduct additional studies in populations of other ethnicities. [24]In addition, the case-control studies on which the current meta-analysis is based may suffer from inherent biases. [25]These findings could be validated by subsequent research using different study designs, such as prospective cohort studies.Furthermore, the variability in genotyping methods across different studies can potentially introduce heterogeneity, affecting the overall conclusion.The lack of adjustment for confounding factors in some studies might also have distorted the true relationship between the polymorphism and HCC risk.In addition, we did not consider the potential interaction with other genes, which might modulate the effect of the CTLA4 + 49 polymorphism.Finally, even though the strength of this study is that it is the largest and most recent meta-analysis that has examined the CTLA4 + 49 polymorphism and risk for HCC, results of the trial sequential analysis suggest that further studies are needed to draw a more reliable conclusion from our work.Nevertheless, compared to previous studies, our study is more highly powered and may provide direction for future research in this area.
In conclusion, the current meta-analysis found no evidence of an association between the CTLA4 + 49 polymorphism and the risk for HCC.These results need to be confirmed by further studies, especially in different ethnic populations and with different study approaches.

Figure 1 .
Figure 1.PRisMA flow diagram for study selection.

*
Bonferroni correction was not applied, because the HWe P value for each study is independent of each other, so it was not a multiple comparison.

Figure 2 .
Figure 2. (A) Forest plot and (B) publication bias for the association between CTLA4 + 49 A/G polymorphism and Hcc risk (dominant model).

Figure 3 .
Figure 3. sensitivity analysis forest plot for dominant model.

Figure 4 .
Figure 4. trial sequential analysis plot for dominant model.

Table 1 .
characteristics of the included studies.

Table 2 .
Quality appraisal of the included studies.

Table 3 .
Results of meta-analysis.