Abstract
Objectives
The aim of this study was to investigate the impact of interleukin-27 (IL- 27) gene polymorphism and additional interactions with environmental factors on non-small cell lung cancer (NSCLC) risk based on a Chinese population.
Methods
SNPStats online software (http://bioinfo.iconcologia.net/SNPstats) was used for Hardy-Weinberg equilibrium (HWE) testing. Stratified analysis was performed by logistic regression model to examine the impact of IL- 27 gene SNPs and environmental factors, and additional gene-environment interaction on NSCLC risk.
Results
Logistic regression analysis showed a significant association between rs153109, rs181206 and increased NSCLC risk. However, no significant relationship was found between NSCLC risk and rs17855750 or rs40837 genotype with minor allele. Logistic regression also indicated a significant association between smoking status or alcohol consumption and NSCLC risk in this study. We performed crossover analysis to investigate the interaction between two SNPs (rs153109 and rs181206) and two environmental factors (smoking status and alcohol consumption) using logistic regression. We found that ever or current smokers with rs153109- AG or GG genotype have the highest NSCLC risk, compared with never smokers with the AA genotype after covariate adjustment, OR (95%CI) = 3.02 (1.97–5.12), p = 0.012. However, no significant interaction effect was found between rs153109 and alcohol consumption, rs181206 and smoking, rs181206 and alcohol consumption.
Conclusion
Our results support an important association of the IL- 27 gene rs153109, rs181206, smoking and alcohol consumption with increased NSCLC risk. We also found a significant impact of an interaction between rs153109 minor allele and ever or current smoking on NSCLC risk.
Keywords: Non-small cell lung cancer, Interleukin-27, Polymorphism, Interaction, Smoking, Alcohol
Introduction
Lung cancer accounts for the highest incidence among all cancer types (12.4% of total cases) and serve as the leading cause of cancer mortality (18.7% of total cancer deaths) [1]. Among all pathological types of lung cancer, non-small cell lung cancer (NSCLC) accounts for about 80% of all lung cancer cases [2]. Each subtype has significantly different molecular characteristics and treatment strategies. Recently, the incidence of NSCLC has been increasing dramatically in the Chinese population. The rising incidence of NSCLC was associated with multiple environmental exposures, including tobacco smoke, residential radon, and airborne particulate matter. Emerging evidence also suggested that metabolic comorbidities including abdominal adiposity, sedentary behavior and T2DM were implicated in the pathogenesis of NSCLC [3–5]. Epidemiological investigation has shown that both active tobacco smoking and exposure to secondhand smoke significantly increased the risk of lung cancer [6]. Yet, evidence shows that the development of lung cancer results from a complex interaction between an individual’s genetic factors and diverse environmental risks. Moreover, burgeoning studies are increasingly linking lung cancer prevalence with genetic predispositions [7, 8].
Interleukin-27 (IL-27), a heterodimeric cytokine in the IL-12 family, is structurally composed of EBV-induced gene 3 (EBI3) and p28 subunits. This cytokine activates downstream signaling through a heterodimeric receptor complex (IL27Rα/gp130), mediating the transduction of the signal transducer and activator of transcription 1 (STAT1)/STAT3 pathway [9]. The IL-27 gene is located at the 16p11 region of chromosome 16 and consists of a set of five exons [10]. Previously, several single nucleotide polymorphisms (SNPs) of the IL-27 gene have been reported to be associated with preeclampsia [11], as well as several types of cancer [12, 13], including breast cancer [14], thyroid carcinoma [15] and colorectal cancer [16] and NSCLC [17]. As far as we know, the role of this polymorphism in the susceptibility of NSCLC remains unclear. In addition, several risk factors can influence NSCLC risk, including genetic and environmental factors (Fig. 1). As genome sequencing technology has advanced continuously, it has been clinically found that smoking history is not a decisive factor in lung cancer development. The incidence of lung cancer is affected by genetic differences among smokers. Thus, the aim of this study was to determine the impact of four SNPs in the IL-27 gene, along with their additional interactions with environmental factors, on the risk of NSCLC in a Chinese Han population.
Fig. 1.
Schematic diagram for background and objective of this study
Materials and methods
Subjects
All NSCLC patients who were diagnosed between June 2019 and July 2023 according to World Health Organization Classification of Lung Tumors [18] were consecutively recruited from the Affiliated Jiangyin Hospital of Nantong University and Nantong Tumor Hospital. All controls were selected from those participants who participated in health check-ups at our hospital, and by matching gender, age (± 3 years) and ethnic background. The control group exclusion criteria prioritized minimizing selection bias by removing individuals with documented NSCLC family history. Peripheral blood was uniformly processed within 2 h post-collection using phenol-chloroform extraction protocols. All clinical (types, stage, metastasis, etc.), demographic (age, gender, etc.), physical examination (height, weight, etc.) and lifestyle (smoking status, alcohol consumption etc.) information were collected from medical records. Body mass index (BMI) was determined through standardized anthropometric protocols using the formula: body weight (kg)/height (m²). All enrolled individuals provided signed ethics committee-approved consent forms prior to data collection.
Genomic DNA extraction and genotyping
Peripheral venous blood samples (3 mL) were immediately transferred into EDTA-anticoagulated tubes and centrifuged at 3,000×g for 10 min within 2 h post-collection to isolate plasma fractions. Extract genomic DNA from blood samples using the DNA Blood Mini Kit (Qiagen) kit. We measured the DNA concentration and adjusted it to 50-100ng/µL, then packaged and stored it at −20 ℃ for future use. Genotyping of four SNPs (rs17855750, rs153109, rs181206 and rs40837) of IL- 27 gene was performed by PCR restriction fragment length polymorphism methods. Reaction system (25 µL): Template DNA 100ng, 10 × PCR buffer 2.5 µL, dNTPs (2.5mM) 2 µL, forward primer (10µM) 1 µL, reverse primer (10 µM) 1 µL, Taq DNA polymerase 0.5U, ddH2O supplemented to 25 µL. PCR program: Pre denaturation: 95 ℃ for 5 min, cycle (35 times): 95 ℃ for 30 s → 58 ℃ for 30 s → 72 ℃ for 30 s, final extension: 72 ℃ for 5 min. Add 10 µL of PCR product to 1 µL of restriction endonuclease (10U/µL), add 2 µL of 10 × Buffer, incubate at 37 ℃ for 2–4 h, inactivate at 65 ℃ for 15 min to terminate the reaction. Prepare 2% agarose gel, add 5 µL enzyme digestion product + 1 µL 6× loading buffer into each well, conduct 100 V voltage electrophoresis for 30–40 min, and then observe the results under ultraviolet light after ethidium bromide staining. Genotyping results were verified through replication analysis of a 10% randomly selected subset of participants, demonstrating complete consistency (100% concordance). The descriptions for four SNPs of IL- 27 gene and the primers were shown in Table 1.
Table 1.
Description and primer sequences designed for sequencing four SNPs of IL-27 gene
| SNPs | Chromosome | Major/minor alleles | Primer (5’→3’) |
|---|---|---|---|
| rs17855750 |
16:28503907 (GRCh38) 16:28515228 (GRCh37) |
T/G |
Forward: 5′- ATCTCGCCAGGAAGCTGCGC-3′ Reverse: 5′- CTGTTAGTGGGGGCCAGAAGGGA-3′ |
| rs153109 |
16:28507775 (GRCh38) 16:28519096 (GRCh37 |
A/G |
Forward: 5′- CTGATCCTGACCTCACTCAACGC-3′ Reverse: 5′- CTGACTGGGACTGGGACTCAGC-3′ |
| rs181206 |
16:28502082 (GRCh38) 16:28513403 (GRCh37) |
T/C |
Forward: 5′- ACCACGCTTCAGCCCTTCCATGCCC-3′ Reverse: 5′- GCTGGGAGGGCTGGGGACCCAGGGC-3′ |
| rs40837 |
16:28499524 (GRCh38) 16:28510845 (GRCh37) |
G/A |
Forward: 5′- GCGCACGCGTCCCCCACCCTTTAGAACTTT-3′ Reverse: 5′- GCGCAAGCTTTGGATGAGAGTGCTTTATTGG-3′ |
Statistical analysis
SPSS version 22.0 software (Chicago) was used to perform statistical analyses of data. The direct counting method was used for calculating genotypes and alleles frequencies of the selected four SNPs. SNPStats online software (http://bioinfo.iconcologia.net/SNPstats) was used for Hardy-Weinberg equilibrium (HWE) testing and linkage disequilibrium (LD) analysis. Logistic regression model was used to investigate the association between IL- 27 gene four SNPs and NSCLC risk. The crossover analysis was performed to examine the additive gene-environment interaction between IL- 27 gene SNPs and environmental factors on the risk of NSCLC by SNPStats online software. The odds ratio (OR), 95% confident interval (95%CI) and interaction p-values were calculated after adjusting for covariates, which were verified by variable selection and collinearity check. Statistical significance was considered when p-values were less than 0.0125 according to Bonferroni correction.
Results
A total of 1526 participants, including 760 NSCLC patients and 766 healthy controls were enrolled in this case- control study. The age distribution of the cases and controls conforms to a normal distribution by using the Kolmogorov-Smirnov test. The mean age was 69.3 ± 13.4 for NSCLC patients and 68.6 ± 12.7 for healthy controls. The general and clinical characteristics of participants stratified to cases and controls were shown in Table 2. The distribution of smoking status and alcohol consumption were significantly different between the cases and controls, the rates of ever or current smoking and alcohol consumption were higher in NSCLC patients than in controls. The mean of age and distribution of gender and overweight or obesity were not significant different between NSCLC patients and controls. In all patients, 19.7% of which was squamous cell carcinoma (SCC), 65% of which was in III or IV stage, 49.5% of which have lymph node metastasis (LNM).
Table 2.
General characteristic of study participants for cases and controls
| Variables | NSCLC patients (n = 760) |
Controls (n = 766) |
p-values |
|---|---|---|---|
| Age (years) | 69.3 ± 13.4 | 68.6 ± 12.7 | 0.295 |
| Males, N (%) | 518 (68.2) | 520 (67.9) | 0.909 |
| Alcohol consumption, N (%) | 0.014 | ||
| Never | 392 (51.6) | 443 (57.8) | |
| Ever or currently | 368 (48.4) | 323 (42.2) | |
| Smoking status, N (%) | < 0.001 | ||
| Never | 453 (59.6) | 547 (71.4) | |
| Ever or currently | 307 (40.4) | 219 (28.6) | |
| Overweight or obesity, N (%) | 229 (30.1) | 273 (35.6) | 0.079 |
| Type of NSCLC, N (%) | |||
| SCC | 150 (19.7) | ||
| Non-SCC | 610 (80.3) | ||
| Stage, N (%) | |||
| I or II | 266 (35.0) | ||
| III or IV | 494 (65.0) | ||
| LNM, N (%) | |||
| Yes | 376 (49.5) | ||
| No | 384 (50.5) | ||
Means ± standard deviation for age, SCC squamous cell carcinoma, LNM Lymph node metastasis
The genotypes of four SNPs of IL- 27 gene were distributed according to a Hardy– Weinberg equilibrium (all p values > 0.05). The frequencies for the genotype and allele of IL- 27 gene- rs153109 were significantly higher in the NSCLC patients than in healthy controls. In addition, the frequencies for the genotype and allele of IL- 27 gene- rs181206 were also significantly higher in the NSCLC patients than in healthy controls (Table 3). No significant difference was obtained between case and control groups in terms of rs17855750 or rs40837 minor alleles. Logistic regression analysis showed a significant association between rs153109 and increased NSCLC risk after adjusting for gender, age, smoking status, alcohol consumption and BMI (Table 4). Compared to subjects with rs153109-AA genotype, adjusted OR (95%CI) = 1.75 (1.34–2.18), 1.58 (0.74–2.48) and 1.80 (1.38–2.21) for participants with rs153109- AG, GG and AG + GG genotype, respectively. We also found a significant association between rs181206 and increased NSCLC risk. Compared to subjects with rs181206-TT genotype, NSCLC risk was significantly higher in carriers with rs181206- AG, GG and AG + GG genotype, adjusted OR (95%CI) was 1.68 (1.21–2.17), 1.96 (1.42–2.53) and 1.73 (1.27–2.21), respectively. However, no significant relationship was found between NSCLC risk and rs17855750 or rs40837 genotype with minor allele (Table 4).
Table 3.
Frequencies for genotypes and alleles of four SNPs of IL-27 gene in cases and controls
| SNPs | Genotypes or alleles | Frequencies N (%) | p- values for HWE test in controls | |
|---|---|---|---|---|
| NSCLC patients (N = 760) | Controls (N = 766) | |||
| rs17855750 | 0.449 | |||
| TT genotype | 422 (55.5) | 468 (61.1) | ||
| TG genotype | 285 (37.5) | 266 (34.7) | ||
| GG genotype | 53 (7.0) | 32 (4.2) | ||
| TG + GG genotype | 338 (44.5) | 298 (38.9) | ||
| T allele | 1129 (74.3) | 1202 (78.5) | ||
| G allele | 391 (25.7) | 330 (21.5) | ||
| rs153109 | 0.181 | |||
| AA genotype | 378 (49.7) | 502 (65.5) | ||
| AG genotype | 304 (40.0) | 229 (29.9) | ||
| GG genotype | 78 (10.3) | 35 (4.6) | ||
| AG + GG genotype | 382 (50.3) | 264 (34.5) | ||
| A allele | 1060 (69.7) | 1233 (80.5) | ||
| G allele | 460 (30.3) | 299 (19.5) | ||
| rs181206 | 0.722 | |||
| TT genotype | 422 (55.5) | 521 (68.0) | ||
| TC genotype | 290 (38.2) | 220 (28.7) | ||
| CC genotype | 48 (6.3) | 25 (3.3) | ||
| TC + CC genotype | 338 (44.5) | 245 (32.0) | ||
| T allele | 1134 (74.6) | 1262 (82.4) | ||
| C allele | 386 (25.4) | 270 (17.6) | ||
| rs40837 | 0.266 | |||
| GG genotype | 450 (59.2) | 500 (65.3) | ||
| GA genotype | 268 (35.3) | 236 (30.8) | ||
| AA genotype | 40 (5.5) | 30 (3.9) | ||
| GA + AA genotype | 310 (40.8) | 266 (34.7) | ||
| G allele | 1168 (76.8) | 1236 (80.7) | ||
| A allele | 352 (23.2) | 296 (19.3) | ||
Table 4.
Logistic regression analysis on association between four SNPs of IL- 27 gene and NSCLC risk under two genetic models
| SNPs | Genotypes or Alleles | OR (95%CI) a | p- values |
|---|---|---|---|
| rs17855750 | |||
| Co-dominant | TT genotype | 1.00 | |
| TG genotype | 1.36 (0.88–1.89) | 0.365 | |
| GG genotype | 1.58 (0.74–2.48) | 0.481 | |
| Dominant | TG + GG genotype | 1.40 (0.84–1.97) | 0.513 |
| T allele | |||
| G allele | |||
| rs153109 | |||
| Co-dominant | AA genotype | 1.00 | |
| AG genotype | 1.75 (1.34–2.18) | < 0.001 | |
| GG genotype | 2.02 (1.41–2.65) | < 0.001 | |
| Dominant | AG + GG genotype | 1.80 (1.38–2.21) | < 0.001 |
| A allele | |||
| G allele | |||
| rs181206 | |||
| Co-dominant | TT genotype | 1.00 | |
| TC genotype | 1.68 (1.21–2.17) | < 0.001 | |
| CC genotype | 1.96 (1.42–2.53) | < 0.001 | |
| Dominant | TC + CC genotype | 1.73 (1.27–2.21) | < 0.001 |
| T allele | |||
| C allele | |||
| rs40837 | |||
| Co-dominant | GG genotype | 1.00 | |
| GA genotype | 1.28 (0.85–1.77) | 0.405 | |
| AA genotype | 1.54 (0.73–2.39) | 0.632 | |
| Dominant | GA + AA genotype | 1.31 (0.81–1.85) | 0.562 |
| G allele | |||
| A allele | |||
a Adjusted for gender, age, smoking status, alcohol consumption and BMI
We also conducted a logistic regression to investigate the relationship between three environmental factor (smoking status, alcohol consumption and overweight or obesity) and NSCLC risk. the rates of ever or current smoking and alcohol consumption were higher in NSCLC patients than in controls. Logistic regression indicated a significant association between smoking status or alcohol consumption and NSCLC risk in this study. Compared to never smokers and never alcohol consumption, current or ever smokers or alcohol consumption have higher NSCLC risk, adjusted OR (95%CI) was 1.46 (1.12–1.85) and 1.37 (1.08–1.74), respectively. But no significant relationship was found between overweight or obesity and NSCLC risk, compared to participants with normal BMI, adjusted OR (95%CI) was 0.92 (0.63–1.40) in overweight or obesity participants (Table 5).
Table 5.
The association between environmental factors and NSCLC risk
| Environmental factors | N (%) | OR (95%CI) | p-values | |
|---|---|---|---|---|
| Cases (n = 760) | Controls (n = 766) | |||
| Smoking status | ||||
| Never | 392 (51.6) | 443 (57.8) | 1.00 | |
| Current or ever | 368 (48.4) | 323 (42.2) | 1.46 (1.12–1.85) | 0.002 a |
| Alcohol consumption | ||||
| Never | 453 (59.6) | 547 (71.4) | 1.00 | |
| Current or ever | 307 (40.4) | 219 (28.6) | 1.37 (1.08–1.74) | 0.014 b |
| Overweight or obesity | ||||
| No | 531 (69.9) | 503 (65.7) | 1.00 | |
| Yes | 229 (30.1) | 263 (34.3) | 0.92 (0.63–1.40) | 0.241 c |
a Adjusted for gender, age, alcohol consumption and BMI
b Adjusted for gender, age, smoking status and BMI
c Adjusted for gender, age, smoking status and alcohol consumption
To obtain the potential gene- environment interaction combinations between IL- 27 gene SNPs and environmental factors, we performed crossover analysis to investigate the interaction between two SNPs (rs153109 and rs181206) and two environmental factors (smoking status and alcohol consumption) using logistic regression, odds ratios and 95% CI and interaction p values were calculated (Table 6). We found that ever or current smokers with rs153109- AG or GG genotype have the highest NSCLC risk, compared with never smokers with the AA genotype after covariate adjustment, OR (95%CI) = 3.02 (1.97–5.12), p = 0.012. However, no significant interaction effect was found between rs153109 and alcohol consumption, rs181206 and smoking, rs181206 and alcohol consumption (all interaction p values more than 0.05). LD analysis was also performed among four SNPs of the IL- 27 genes. However, no strong LD was found between any two of these SNPs.
Table 6.
Interaction between two SNPs of IL- 27 gene and smoking status or alcohol consumption on NSCLC risk
| IL- 27 gene genotypes | Environmental factors | OR (95% CI) | P-values |
|---|---|---|---|
| IL- 27 gene rs153109- smoking interaction a | |||
| AA | Never | 1.00 | - |
| AA | Ever or currently | 1.58 (0.96–1.94) | 0.156 |
| AG + GG | Never | 1.85 (1.27–2.48) | 0.001 |
| AG + GG | Ever or currently | 3.02 (1.97–5.12) | < 0.001 |
| Interaction p-value: 0.012 | |||
| IL- 27 gene rs153109- alcohol consumption interaction b | |||
| AA | Never | 1.00 | |
| AA | Ever or currently | 1.42 (0.91–1.96) | 0.116 |
| AG + GG | Never | 1.75 (1.13–2.35) | 0.002 |
| AG + GG | Ever or currently | 2.36 (1.40–4.36) | < 0.001 |
| Interaction p-value: 0.235 | |||
| IL- 27 gene rs181206- smoking interaction a | |||
| TT | Never | 1.00 | |
| TT | Ever or currently | 1.58 (1.08–2.19) | 0.012 |
| TC + CC | Never | 1.47 (0.91–2.05) | 0.210 |
| TC + CC | Ever or currently | 2.51 (1.53–4.50) | < 0.001 |
| Interaction p-value: 0.342 | |||
| IL- 27 gene rs181206- alcohol consumption interaction b | |||
| TT | Never | 1.00 | |
| TT | Ever or currently | 1.41 (0.87–1.97) | 0.326 |
| TC + CC | Never | 1.82 (1.17–2.53) | 0.0012 |
| TC + CC | Ever or currently | 2.16 (1.48–3.25) | < 0.001 |
| Interaction p-value: 0.410 | |||
a Adjusted for gender, age, alcohol consumption and BMI
b Adjusted for gender, age, smoking status and BMI
Discussion
In current study, we found that both rs153109 and rs181206 polymorphism of IL- 27 gene were significantly associated with increased NSCLC risk based on this Chinese Han population. The heterodimeric cytokine IL-27, which is composed of EBI3 and p28 subunits, demonstrates potent immunoregulatory functions in tumor immunity. It promotes cytotoxic lymphocyte-mediated tumor regression through mechanisms that are dependent on STAT1/STAT3 phosphorylation [9]. Specifically, IL-27 promotes the cloning of native CD8 + T cells. It enhances their cytotoxic potential through synergistic activation with IL-12. This activation triggers IFN-γ production and amplifies CTL-mediated tumor cell clearance [11, 19]. Previously, IL-27 gene SNPs have been reported associated with several types of cancer [12–16]. Ge et al. [17] suggested that the IL-27 gene SNPs correlated with the susceptibility of NSCLC in the Chinese population. But another study in Chinese population by Huang et al. [20] suggested that the rs153109 of the IL-27 gene might be associated with the genetic susceptibility to NSCLC, indicating that IL-27 may play a certain role in the occurrence and development of NSCLC. The study by Ge et al. [17] concluded inconsistent results with our study. The reasons were as follows: First, the sample size of our study was larger than that of previous studies. The study by Ge et al. [17] enrolled 388 patients and 390 controls, which was less than that in our study; Second, the afore-mentioned study enrolled more women than men (63.4% women and 36.6% men), and different gender percentages could influence the stability of the results.
IL-27 is primarily produced by antigen presenting cells (APCs) and exhibits diverse biological functions, including anti-inflammatory response [21] and anti- tumour immunity. Existing research results have indicated that the expression of IL-27 is elevated in certain autoimmune diseases [22] and tumor tissues [23, 24]. Moreover, the IL-27 expression is closely associated with the severity of the disease. Experiments on IL-27 gene transduction in mice have demonstrated that IL-27 can inhibit tumors and their metastasis. This is achieved by regulating NK cells, CD8 + T cells, and angiogenesis [25]. In addition, the immune inflammatory response of IL-27 is crucial in tumor occurrence and development [26]. Research has indicated that IL-27 functions differently in tumor cells with varying levels of immunogenicity [27]. Additionally, study has confirmed that IL-27 can not only directly inhibit the proliferation and metastasis of NSCLC cells but also inhibit the occurrence of endothelial to mesenchymal transition (EndMT) in NSCLC cells [28]. Consequently, it inhibits the occurrence and development of NSCLC cells. Another study [21] indicated that Cytotoxic CD8 + T lymphocytes (CTLs) are crucial for anti-tumor immunity, but they often exhibit dysfunction in tumors. Therefore, IL-27 can control tumors by triggering cytotoxic CD8 + T cell programs.
Smoking tobacco has been extensively identified as a key environmental risk factor in the development of NSCLC [29, 30]. Previously, several studies [31–33] focused on the impact of gene- smoking interaction on NSCLC risk in different populations. A study [34] indicated that higher levels of IL-27 may contribute to an enhanced IFN-γ + CD8 + Tc1 response in mice with emphysema due to smoking. This process appears to occur without the participation of the STAT1 and STAT3 pathways. However, the interaction between IL-27 genetic variants and smoking in relation to the risk of NSCLC has not been comprehensively examined yet. Therefore, we firstly investigate the gene- environment interaction between IL-27 gene and smoking status. Our analysis found a significant interaction between rs153109 and smoking habits. Current or ever smokers with the AG or GG variants of rs153109 have the highest risk for NSCLC when compared with non-smokers with the AA genotype. It means that both smoking and rs153109 minor allele were risk factors for NSCLC, and the effect of smoking on NSCLC risk could be influenced by different rs153109 genotypes. The biological mechanism of this interaction is not yet clear. We believe that genetic variations (rs153109) can regulate the activity of key enzymes (such as metabolic enzymes or DNA repair enzymes), thus affecting the sensitivity to smoking carcinogens (such as NNK or BaP). Genetic polymorphism (rs153109) may enhance the metabolic activation of tobacco toxins or weaken the DNA damage repair ability, synergistically increasing the risk of lung cancer [35].
Several limitations existed in this study. Firstly, IL-27 level was not tested for all participants, so we could not investigate the IL-27 level in different IL-27 gene genotypes. Secondly, few women smoked or drank alcohol. So, we could not analysis the gene- environment interaction grouped by gender. We suggest stratified analysis by gender to explore gender difference on IL-27 gene- environment interaction. Thirdly, just smoking status and alcohol consumption were included in the gene- environment interaction analysis, more environmental factors should be enrolled in the future, and the results obtained in this study should be verified in different populations with larger sample size, and also should be interpreted by future biological studies.
In conclusion, we found a significant association of the IL- 27 gene rs153109, rs181206, smoking and alcohol consumption with increased NSCLC risk. We also found a significant impact of an interaction between rs153109 minor allele and ever or current smoking on NSCLC risk.
Acknowledgements
We thank all the partners, staff and reviewers who help us in the process of this study.
Clinical trial number
Not applicable.
Abbreviations
- NSCLC
non-small cell lung cancer
- IL- 27
Interleukin-27
- BMI
Body mass index
- SNPs
single nucleotide polymorphisms
- GMDR
Generalized multifactor dimensionality reduction
- PCR
polymerase Chain Reaction
- HWE
Hardy- Weinberg equilibrium
Authors’ contributions
The manuscript writing, editing, and review were conducted by Zhu J and Zhai X, Yang B and Tan C participated in the genomic DNA extraction and genotyping. Ni F and Guan Y participated in information collection and questionnaire investigation. Cai J participated in methodology section revision.
Funding
This study was supported by the Youth Project of Wuxi Municipal Health Commission (Q202310) and the Health Committee of Nantong (MS2023059, MS2023053).
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
Each participant understood the study process and signed a written informed consent before the study. The protocol was approved by committee of the Affiliated Jiangyin Hospital of Nantong University (2024-L044) in accordance with the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
JiaminZhu and XiaogangZhai contributed equally to this article.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.