Abstract
Background/Aim: Gastric adenocarcinoma (GACA) remains a major global health concern, particularly in Asia, due to its poor prognosis and complex etiology. The interaction between genetic factors and environmental exposures, such as smoking, alcohol consumption, and Helicobacter pylori (HP) infection, plays a crucial role in GACA risk.
Materials and Methods: Interleukin-4 (IL-4) gene promoter polymorphic rs2243248 (T-1099G), rs2243250 (C-589T), and rs2070874 (C-33T) genotypes were analyzed in 161 GACA patients and 483 non-cancer control subjects from a Taiwanese population by PCR-RFLP methodology. The gene-environment interactions were evaluated by stratified analysis.
Results: Genotypic analysis revealed no significant association between IL-4 polymorphisms and GACA risk (all p>0.05). However, interactions between IL-4 C-589T and C-33T genotypes with HP infection were observed (p=0.0114 and 0.0009). In addition, T-1099G and C-33T genotypes interacted with alcohol consumption (p=0.0346 and 0.0295). T-1099G and C-589T variant genotypes were associated with an increased risk of metastasis (p=0.0313 and 0.0118). Moreover, IL-4 polymorphisms did not correlate with smoking behavior in influencing GACA susceptibility.
Conclusion: While IL-4 polymorphisms alone are not predictors of GACA risk, their interactions with environmental factors may contribute to the progression of the disease. Our study emphasizes the need for further research to explore the clinical implications of IL-4 genetic variants in diverse populations and their role in GACA progression.
Introduction
Gastric cancer (GACA) is the fifth most prevalent malignancy and the third leading cause of cancer-related deaths globally (1, 2). Despite significant advances in treatment, GACA remains a major global public health concern due to its complex pathogenesis, poor prognosis, and lack of reliable predictive biomarkers (3, 4). The incidence and mortality rates of GACA are particularly high in Asia, with Eastern Asia alone accounting for over 60% of the global cases (5). Identified risk factors include Helicobacter pylori (HP) infection (6), smoking (7, 8), alcohol consumption (9, 10), obesity (11, 12), and high salt intake (13, 14). Moreover, the interaction between environmental risk factors and genetic predisposition plays a critical, albeit not yet fully understood, role in the multifactorial etiology of GACA (15-18). Despite this, the identification of genetic markers for diagnosing and assessing GACA susceptibility remains largely underexplored.
Interleukine-4 (IL-4) is a four-helix bundle glycoprotein, which is primarily generated by activated T helper 2 (Th2) cells, eosinophils, and macrophages, and has essential roles as a mediator and modulator of immunological responses (19, 20). It is mainly produced along with other interleukins (ILs), such as IL-5, IL-10 and IL-13, which are mainly responsible for the promotion of humoral immunity (21, 22). IL-4, like other ILs, is a cytokine glycoprotein that mediates immune responses by binding to specific cell surface receptors (23). Through its interactions with a variety of receptors, including TLRs, IL-4 contributes to anti-inflammatory responses (24). IL-4 inhibited proliferation of HTB-135 GACA cells by down-regulating G0-G1 cell cycle nuclear-regulating factors, including retinoblastoma gene product, c-myc, and cyclin D1 (25). IL-4 could cause G1 phase arrest in the CRL 1739 GACA cell line (26). IL-4 can also inhibit the growth of GACA cells and this effect is positively corelated with the level of IL-4R expression (27).
The IL-4 gene is located on human chromosome 5q31 and encodes a protein consisting of 153 amino acids. Its structure includes a signal peptide (amino acids 1-24) and a mature peptide (amino acids 25-153) (28). Chronic inflammatory conditions are characterized by persistent cytokine expression and the recruitment of immune cells, often driven by genetic variations in humans. These genetic variations, particularly single-nucleotide polymorphisms (SNPs), are believed to contribute to phenotypic differences among individuals. In recent years, numerous studies have focused on investigating the associations between IL-4 genotypes and GACA susceptibility worldwide; however, the results remain inconsistent (29-39).
This study aimed at achieving two primary objectives. The first was to characterize the genotypic distribution of IL-4 promoter rs2243248 (T-1099G), rs2243250 (C-589T), and rs2070874 (C-33T) (Figure 1) in a well-defined Taiwanese cohort consisting of 161 GACA patients and 483 cancer-free controls. The second objective was to investigate how IL-4 genotypes interact with age, sex, body mass index (BMI), smoking, alcohol consumption, HP infection, and metastasis status in influencing GACA susceptibility.
Physical map of IL-4 T-1099G (rs2243248), C-589T (rs2243250), and C-33T (rs2070874) polymorphic sites.
Materials and Methods
Recruitment of GACA cases and non-cancer controls. A hospital-based cohort comprising 161 GACA patients was recruited from the general surgery outpatient clinics at China Medical University Hospital (CMUH), as previously documented (40, 41). Each participant voluntarily provided a 5 ml peripheral blood sample for genetic analysis. For comparison, a control group of 483 age- and sex-matched healthy, cancer-free individuals was selected from the CMUH Health Examination Cohort database. The study design and protocols were reviewed and approved by the Institutional Review Board (IRB) of CMUH (IRB number: DMR100-IRB-107). Written informed consent was obtained from all participants with the assistance from the colleagues of Tissue Bank of China Medical University Hospital. Table I summarizes the demographic characteristics of the study population, including age, sex, body mass index (BMI), smoking and alcohol consumption habits, HP infection status, and histological classifications.
Selected characteristics of the control and gastric cancer groups.
Methodology of IL-4 genotype identification. Genomic DNA was extracted from peripheral blood leukocytes and processed according to previously established protocols (42, 43). Polymerase chain reaction (PCR) amplification was carried out under standard cycling conditions: an initial denaturation at 94°C for 5 min, followed by 35 cycles of 94°C for 30 s, 55°C for 30 s, and 72°C for 30 s, with a final extension at 72°C for 10 min. The primer sequences used for IL-4 genotyping were as follows: forward 5′-GGTCCTTACGTTCACTGCTG-3′ and reverse 5′-GGC TCAAGTGCTCCTCCTAC-3′ for IL-4 T-1099G. Forward 5′-TAAACTTGGGAGAACATGGT-3′ and reverse 5′-TGG GGAAAGATAGAGTAATA-3′ for IL-4 C-589T. Forward 5′-CTGGAAGAGAGGTGCTGATT-3′ and reverse 5′-ACTC ACCTTCTGCTCTGTGA-3′ for IL-4 C-33T. Genotyping was performed using PCR-restriction fragment length polymorphism (PCR-RFLP) analysis. The PCR products for IL-4 rs2243248, rs2243250, and rs2070874 were digested with SfcI, AvaII, and BsmAI, respectively. Digested products were resolved via 3% agarose gel electrophoresis at 100V for 30 min and subsequently visualized for genotype determination. The PCR-RFLP procedure achieved a 100% success rate. All genotypic analyses were conducted independently and in a blinded manner by two researchers.
Statistical analyses. To ensure that the control subjects were representative of the Taiwanese population and to minimize potential genotyping errors, the genotypic frequencies of IL-4 polymorphisms in the healthy control group were assessed for compliance with Hardy-Weinberg equilibrium (HWE) using a goodness-of-fit test. Additionally, Pearson’s chi-square test was employed to analyze the distribution of IL-4 polymorphic genotypes across different subgroups. The associations between IL-4 genotypes and GACA risk were evaluated by calculating odds ratios (ORs) with corresponding 95% confidence intervals (CIs). A p-value of <0.05 was considered statistically significant.
Results
Table I summarizes the demographic characteristics of 161 GACA patients and 483 non-cancer control subjects. Since the case and control groups were matched for age and sex, no significant differences were observed in age (p=0.3519) or sex distribution (p=1.0000). However, significant disparities were noted in smoking habits, alcohol consumption, and HP infection status between GACA patients and controls (all p<0.0001), suggesting these factors as potential risk indicators for GACA in the Taiwanese population. Regarding tumor localization, GACA cases exhibited tumors in the upper (14.2%), middle (42.9%), and lower (42.9%) regions of the stomach. Additionally, distant metastasis was identified in 91 (56.5%) of the GACA patients (Table I).
The genotypic distributions of the IL-4 promoter polymorphisms T-1099G (rs2243248), C-589T (rs2243250), and C-33T (rs2070874) among the GACA cases and controls are shown in Table II. First, the genotypic distributions of 1099G, C-589T and C-33T among non-cancer control subjects fitted well with HWE (all pHWE>0.05, Table II). Second, there was no association between the genotypes of T-1099G, C-589T or C-33T and GACA susceptibility in the Taiwanese cohort (all p for trend and p-values were larger than 0.05) (Table II). The combined heterozygous and homozygous variant genotypes of T-1099G, C-589T or C-33T were not associated with any altered GACA risk (all p-values were larger than 0.05, Table II).
Associations between interleukin-4 genotypes and gastric cancer risk.
To further confirm these findings based on the genotypic frequency distribution in Table II, the allelic frequency distribution analysis for IL-4 T-1099G, C-589T and C-33T was also conducted and the results are presented in Table III. In support, none of the variant alleles at IL-4 T-1099G, C-589T or C-33T was significantly associated with GACA risk (all p-values were larger than 0.05).
Distributions of interleukin-4 allelic frequencies among the investigated gastric cancer patients and non-cancer control subjects.
Overall, the findings presented in Table II and Table III support the preliminary conclusion that none of the IL-4 T-1099G, C-589T or C-33T genotypes can serve as reliable predictors of GACA diagnostic risk.
We have further examined the interactions between IL-4 T-1099G, C-589T and C-33T genotypes and various demographic, lifestyle, and clinical factors to assess their combined impact on GACA risk (Table IV, Table V, Table VI). The results showed that IL-4 T-1099G genotypes interact with BMI (p=0.0091) and alcohol consumption (p=0.0346) to influence the risk of GACA (Table IV). Particularly, the genotypic frequencies of IL-4 T-1099G GT and GG genotypes were significantly higher among ever drinkers than never drinkers (18.2% and 3.6% versus 9.4% and 0%, Table IV). In addition, IL-4 T-1099G GT and GG genotypes were significantly more frequent among GACA patients with metastasis compared to those without (17.6% and 2.2% versus 5.6% and 0%, p=0.0313, Table IV).
Combinative effects of interleukin-4 rs2243248 (T-1099G) genotype with demographic and clinical features on gastric cancer risk.
Combinative effects of interleukin-4 rs2243250 (C-589T) genotype with demographic and clinical features on gastric cancer risk.
Combinative effects of interleukin-4 rs2070874 (C-33T) genotype with demographic and clinical features on gastric cancer risk.
Regarding IL-4 C-589T, the results showed that its genotypes interact with HP infection (p=0.0114) to increase the risk of GACA (Table V). Particularly, the genotypic frequencies of IL-4 C-589T CT and CC genotypes were significantly higher among individuals with a history of HP infection compared to those without (38.4% and 4.5% versus 16.3% and 2.1%, Table V). Similar to those of IL-4 T-1099G, IL-4 C-589T CT and CC genotypes were significantly higher among those GACA patients with metastasis than those without (39.6% and 5.5% versus 21.4% and 1.4%, p=0.0118, Table V).
As for IL-4 C-33T, the results showed that its genotypes interact with alcohol consumption (p=0.0295) and HP infection (p=0.0009) to increase the risk of GACA (Table VI). For the former factor, the genotypic frequencies of IL-4 C-33T CT and TT genotypes were notably higher among ever drinkers than never drinkers (40.0% and 9.1% versus 30.2% and 1.9%, Table VI). For the later factor, the genotypic frequencies of IL-4 C-33T CT and TT genotypes were higher among HP ever infectors than never infectors (42.0% and 5.3% versus 14.3% and 2.0%, Table VI).
Discussion
Clinically, IL-4 expression is up-regulated in GACA patients. Gabitass and his colleagues reported significantly higher plasma IL-4 levels in 25 GACA patients compared to 54 healthy controls (44). Similarly, Cárdenas and his colleagues observed elevated serum IL-4 levels in 17 GACA patients relative to 30 healthy individuals (45). Furthermore, Diaz Orea et al. analyzed 30 GACA biopsy samples via immunohistochemistry and found significantly higher IL-4 expression in early-stage (I and II) compared to late-stage (III and IV) tumors, suggesting a potential growth-inhibitory role of IL-4 in GACA progression (46).
Given the significant differences observed in IL-4 protein expression between GACA patients and healthy individuals, considerable scientific interest has been directed toward investigating IL-4 SNPs as potential genetic biomarkers for GACA. Among the three IL-4 polymorphic loci examined in this study (T-1099G, C-589T, and C-33T), the C-589T polymorphism has garnered the most research attention, as it has been reported to influence IL-4 secretion capacity (47). Specifically, the TT genotype has been associated with reduced IL-4 expression (48). The earliest investigation of IL-4 C-589T in relation to GACA risk was conducted by El-Omary’s team in 2003, analyzing 314 GACA cases and 210 cancer-free controls in the United States (29). Their findings indicated no significant association between IL-4 C-589T genotypes and GACA risk. In the same year, Wu and his colleagues conducted a study in China with 220 GACA patients and 210 healthy controls, yielding similar negative results (30). However, both studies lacked rigorous adherence to HWE in their control cohorts, potentially affecting the reliability of their findings. Subsequently, in 2005, Lai and his colleagues performed a study in Taiwan with a smaller cohort (123 GACA cases and 162 controls), ensuring compliance with HWE. Despite this methodological improvement, their results also failed to reveal a significant association (31). In 2007, Garcia-Gonzalez et al. expanded the investigation to a Spanish cohort, analyzing 404 GACA cases and 404 controls, and similarly reported no significant correlation (32). In 2008, Crusius and his colleagues conducted a study on a mixed European cohort comprising 242 GACA cases and 1,154 controls from 10 countries, reinforcing the absence of association (33). Both Garcia-Gonzalez and Crusius’ studies were notable for their large sample sizes and well-balanced control groups that adhered to HWE. In 2009, Ando’s team examined a Japanese cohort (330 GACA cases and 190 controls), yet again finding no significant association (34). That same year, Ko et al. in South Korea undertook a rare attempt to include IL-4 C-589T in a GACA genotyping study; however, their sample set was relatively small (84 GACA cases vs. 336 controls), and the control group did not meet HWE standards (35). Their findings remained consistent with prior studies, showing no significant association. A contrasting result emerged in 2017 when Yun and his colleagues reported a significant association between the IL-4 C-589T polymorphism and GACA risk in a Chinese cohort (340 GACA cases and 364 controls). Their study indicated that individuals carrying the CC and CT genotypes had an increased risk of developing GACA compared to those with the TT genotype (36). However, another study reported by Wang and his colleagues in China that same year (362 GACA cases and 384 controls) failed to replicate these findings (37). In 2018, Pavithra’s team conducted a study in India, again reporting no significant association (38). Interestingly, in 2020, a study in Chile involving 310 GACA cases and 311 controls reported a significant association, with the T allele being identified as a risk factor (39). However, this study lacked detailed genotype-specific data. According to the NCBI database (49), the T allele of IL-4 C-589T exhibits a high frequency in East Asian (0.7795) and African (0.7300) populations, an intermediate frequency in Admixed Americans (0.3660), and a low frequency among Caucasians (0.1635). Despite early attention to IL-4 C-589T as a candidate locus, most studies—both in East Asian and non-East Asian populations—have found no significant association between this polymorphism and GACA risk. This aligns with our current findings (Table II and Table III) and is further supported by the most recent meta-analysis on this topic (50). A notable discrepancy remains regarding Yun’s findings in Inner Mongolia. Given China’s vast geographic expanse and ethnically diverse populations, a plausible explanation for their unique results could be the genetic homogeneity and conservation of Inner Mongolia due to its relative geographic and cultural isolation. In summary, regardless of whether the study population is from Inner Mongolia, Chile, or any other region, larger, multi-center genotypic studies are essential to elucidate the potential ethnic- or region-specific impact of the IL-4 C-589T polymorphism on GACA susceptibility.
To date, no study has examined the correlation between IL-4 T-1099G and the risk of GACA. Our investigation is the first to demonstrate a lack of significant association (Table II and Table III). Concerning IL-4 C-33T, four relevant studies have been documented. The first, conducted by Crusius and his colleagues in 2008, analyzed a multiethnic European cohort consisting of 242 GACA patients and 1,154 controls across 10 countries (33). The second study, led by Ko, involved a South Korean population comprising 81 GACA cases and 324 controls (35). Notably, both research teams had also investigated IL-4 C-589T but reported no significant findings. The third study, conducted by Wu and his colleagues in 2009, focused on a South Chinese cohort with 1,045 GACA cases and 1,100 controls. Unlike the previous studies, this research examined only the IL-4 C-33T variant and similarly found no substantial association with GACA (51). The last one and most recent study was conducted by He and his colleagues in 2019. They analyzed 479 GACA cases and 483 controls in Nanjing, China, and found no significant differences (52). All these findings align with our present results (Table II and Table III).
As mentioned in the introduction part, many risk factors are identified to be associated with GACA across the world. The most well-established risk factor is HP infection (6), and long-term HP infection has been reported to account for up to approximately 75% of GACA cases (53). In 2017, Yun and his colleagues reported that the IL-4 C-589T genotype has combinative impacts with HP infection on determining personal GACA risk (36). However, a negative interaction was presorted by He’s team in 2019 (52).
GACA has been established as a smoking-related malignancy (54, 55). Our study further confirmed that cigarette smoking is a significant risk factor for GACA in the Taiwanese population (Table I). However, we were unable to demonstrate any significant interaction between IL-4 genotypes and smoking behavior in influencing individual susceptibility to GACA (Table IV, Table V, Table VI). In 2017, Yun and his colleagues reported that the IL-4 C-589T genotype has a combined effect with smoking behavior in determining individual GACA risk (36).
An elevated risk was observed among subgroups of GACA patients who consumed alcohol and carried variant IL-4 genotypes at T-1099G (Table IV) and C-33T (Table VI), but not at C-589T (Table V). The detailed mechanisms remain unclear. On the contrary, literature suggests that alcohol consumption can significantly elevate the effects of IL-4 C-589T on the risk of GACA (36). Further studies are greatly warranted to confirm our results.
Notably, GACA patients harboring the IL-4 T-1099G and C-589T variant genotypes exhibited a higher risk of distant metastasis compared to those with the corresponding wild-type genotypes (Table IV and Table V). Although the precise mechanisms by which IL-4 influences the metastatic behavior of GACA remain unclear, our findings have significant clinical implications. Specifically, IL-4-based early, precise, and personalized genotypic screening could be beneficial for individuals with a history of alcohol consumption and/or long-term HP infection, encouraging proactive modifications to mitigate their risk. Moreover, GACA patients carrying IL-4 T-1099G and/or C-589T variant genotypes may benefit from more intensive whole-body follow-up examinations to reduce the likelihood of distant metastasis.
In conclusion, our study provides compelling evidence that IL-4 T-1099G, C-589T, and C-33T genotypes are not significantly associated with GACA susceptibility. Notably, IL-4 T-1099G exhibited interactions with BMI and alcohol consumption, while IL-4 C-589T and C-33T interacted with HP infection and alcohol consumption. Furthermore, the variant genotypes of IL-4 T-1099G and C-589T were associated with an increased risk of distant metastasis.
These findings underscore the potential influence of gene-environment interactions in GACA pathogenesis, despite the absence of direct genotypic associations. Further validation across diverse ethnic populations is warranted to confirm the clinical relevance of IL-4 genetic variants.
Acknowledgements
The Authors are grateful to China Medical University Hospital the Tissue-bank and Dr. Yang’s leadership for their excellent sample collection. The technical assistance from Ai-Chia Tung and Yi-Wen Hung highly appreciated. This study was supported by Taichung Armed Forces General Hospital (TCAFGH-D-113009), Taichung Veterans General Hospital (TCVGH-1134904B) and China Medical University plus Asia University (CMU113-ASIA-04). None of the funders had taken part in the study design, data collection and analysis, decision to publish or preparation of the manuscript.
Footnotes
Authors’ Contributions
Conceptualization: CKF, DTB, and HTL; Data curation: CKF, YCY, JCC, and MDY; Formal analysis: JCC, YCY, and HTL; Funding acquisition: CKF, DTB, and HTL; Investigation: HYS, CWT, CKF, and WSC; Methodology: CWT, WSC, and DTB; Project administration: CKF, HTL, WSC, and DTB; Resources: CKF and HTL; Supervision: WSC and DTB; Validation: CWT and WSC, and DTB; Writing-original draft: CKF, HTL, and DTB; Writing-review & editing: WSC and DTB.
Conflicts of Interest
All the Authors declare no conflicts of interest regarding this study.
- Received March 21, 2025.
- Revision received April 6, 2025.
- Accepted April 7, 2025.
- Copyright © 2025 The Author(s). Published by the International Institute of Anticancer Research.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
