Case-control study on CYP4B1 gene polymorphism and susceptibility to gastric cancer in the chinese Han population
BMC Medical Genomics volume 15, Article number: 223 (2022)
In China, gastric cancer (GC) is one of the most common malignant tumors. This study aimed to explore the relationship of rs2297810, rs4646491 and rs2297809 polymorphisms of CYP4B1 with susceptibility to GC in the Chinese Han population.
A case-control study including 707 GC cases and 707 normal controls was conducted. Three single nucleotide polymorphisms (SNPs) were genotyped by Agena MassARRAY system. Logistic regression analysis was utilized to assess the effects of SNPs on GC risk. Furthermore, multifactor dimensionality reduction (MDR) approach was used to analyze the SNP-SNP interactions.
No significant relationships were found between rs2297810 and rs2297809 and GC risk under all genetic models. For rs4646491, people with TC genotype had a 1.40-fold higher risk of GC than those with CC genotype (OR = 1.40; 95% CI = 1.13–1.74; p = 0.002), and people with TT-TC genotype had a 1.30-fold higher risk of GC than those with CC genotype (OR = 1.30; 95% CI = 1.06–1.61; p = 0.014). Stratification results showed that GC risk in people carrying TC genotype was higher than that in people with CC genotype, males (OR = 1.36; 95% CI = 1.06–1.75; p = 0.015), non-smokers (OR = 1.52; 95% CI = 1.11–2.07; p = 0.009) and non-drinkers (OR = 1.50; 95% CI = 1.10–2.04; p = 0.010). Additionally, the study also revealed that GC risk in people carrying TT-TC genotype was higher than that in people with CC genotype, males (OR = 1.29; 95% CI = 1.01–1.64; p = 0.040), non-smokers (OR = 1.40; 95% CI = 1.04–1.89; p = 0.027) and non-drinkers (OR = 1.39; 95% CI = 1.03–1.87; p = 0.030).
This study firstly found that CYP4B1-rs4646491 was significantly correlated with GC risk, and it might be a risk factor for GC.
Gastric cancer (GC) is the fifth most common cancer and the fourth leading cause of cancer death globally, according to the International Agency for Research on Cancer (IARC) in 2020 [1, 2]. Statistically, due to insignificant early symptoms, over 50% of GC patients are in advanced stage when diagnosed [3,4,5]. Modern research shows that the progression of GC is complex and diverse, and multiple factors contribute to its onset. Genetic factors, such as single nucleotide polymorphisms (SNPs), are considered to be inseparable from GC development. The study of cancer-related gene polymorphisms may attribute to detect new predictive markers in cancer progression .
Cytochrome P450 family 4 (CYP4) enzymes are associated with biological functions such as skin barrier, inflammation, cardiovascular health, and cancer . Variants of the CYP4 gene have been shown to affect individual metabolic variations and disease susceptibility in previous studies . CYP4B1 is mainly expressed in the lungs  and has also been detected in adipose tissue, bladder, esophagus, stomach and so on (https://gtexportal.org/home/gene/CYP4B1). Studies have shown that mutation in the CYP4B1 gene is considered to be a potentially cancer risk and may be involved in cancer by activating carcinogens, developing neovascularization and inducing inflammation [8, 10]. At present, more and more mutations in CYP4B1 have been discovered by high-throughput sequencing technology. However, most of CYP4B1 mutations remain undetected. Further studies of CYP4B1 genetic variants are needed. The contribution of CYP4B1 gene polymorphisms has been studied in other cancers, such as bladder cancer , urothelial cancer , and lung cancer . However, relevant researches on the relationship between polymorphisms of the CYP4B1 gene and GC are lacking.
Therefore, a case-control study was conducted to explore the relationship between the CYP4B1 gene rs2297810, rs4646491 and rs2297809 polymorphisms and GC susceptibility. At the same time, by combining the clinical indicators and demographic characteristics (age, gender, smoking and drinking status), we could comprehensively investigated the association between potential influencing factors and the risk of GC. This study will provide a theoretical basis for the timely screening and diagnosis of GC.
Materials and methods
The study recruited 707 healthy individuals and 707 GC patients from Hainan Cancer Hospital. All participants were genetically unrelated Han Chinese. Questionnaires and medical records were used to obtain clinical characteristics of participants. The average age of patients in this study (539 males and 168 females) was 59.48 ± 10.20 years. All patients with GC were diagnosed clinically and pathologically at their first stomach examination. The exclusion criteria for recruiting cases were: recurrent tumors or other malignant tumors; and patients underwent radiotherapy or chemotherapy. The average age of healthy individuals in this study (538 males and 169 females) was 59.34 ± 9.01 years. Healthy individuals had no history of cancer hereditary diseases. The Ethics Committee of Hainan Cancer Hospital provided its approval for this study. Each individual signed written informed consent.
SNP selection and genotyping
The selection of SNP loci of the CYP4B1 gene in our study was based on the following processes: First, all mutational loci of the CYP4B1 gene were downloaded from the 1000 Genomes Project database. Second, Haploview software was applied to filter SNP loci based on specific parameters (Hardy-Weinberg equilibrium (HWE) > 0.01 and minor allele frequency (MAF) > 0.05). Finally, combined with primer design, three SNP loci (rs2297810, rs4646491 and rs2297809) were selected randomly. Peripheral blood (5 mL) from each subject was collected for DNA extraction by GoldMag genomic DNA purification kit (GoldMag Co. Ltd., Xi’an, China). The DNA concentration was estimated by NanoDrop 2000 (Thermo Scientific, Waltham, Massachusetts, USA).Ultimately, Agena MassARRAY system (Agena Bioscience, San Diego, CA, USA) was carried out to genotype SNPs.
SPSS 20.0 was implemented for statistical analysis. All statistical tests were two-sided, and p < 0.05 was considered statistically significant. The χ2 test was used to evaluate the differences in demographic characteristics and genotype distribution of CYP4B1 between cases and controls. Goodness-of-fit χ2 test was performed to test the HWE of SNPs in the control group. PLINK 1.9 (Harvard, Boston, MA, USA) was used to test the relationship between genotypes and GC risk in different genetic models. Odds ratios (ORs) and 95% confidence intervals (CIs) were obtained by logistic regression analysis after adjusting for age, gender, smoking and drinking status. Multifactor dimensionality reduction software (MDR version 3.0.2) was applied to explore the effects of SNP-SNP interactions. Additionally, one-way ANOVA was used to compare the genotype distribution of all clinical indicators of the case groups.
Characteristics of study participants
Table 1 shows the demographic characteristics of GC patients and controls in this study, showing that there was no significant difference in the distribution of age (age > 60 or age ≤ 60) and gender (male or female) between the case group and control group (p = 0.264; p = 0.950). Smoking and drinking status revealed no significant difference between GC patients and control individuals (p = 0.958; p = 0.595). In the control group, the genotype frequency distribution of three SNPs satisfied HWE (p = 0.373; p = 0.488; p = 0.425; Table 2), implying that samples in this study were representative.
Association between three polymorphisms and the risk of GC
As shown in Table 3, the results proved that the genotype frequencies of CYP4B1 gene rs2297810 and rs2297809 did not statistically different between in case group and control group (p > 0.05). Meanwhile, according to the logistic regression analysis, there was no relationship of CYP4B1 gene rs2297810 and rs2297809 with the risk of GC. For CYP4B1 gene rs4646491, the frequency distribution of the TC genotype was obviously different in two groups (p = 0.002), and the GC risk in the population with TC genotype was 1.40 times higher than those carrying CC genotype. The frequency distribution of the TT-TC genotype showed significant difference in two groups (p = 0.014), and the GC risk in the population carrying TT-TC genotype was 1.30 times higher than those with CC genotype. Taken together, TC genotype and TT-TC genotype could be dangerous elements for GC. However, we did not observe a significant association of the rs4646491 polymorphism with GC risk in allelic, recessive and additive models (p > 0.05; Table 3).
Table 4 presents the stratification results of the relationship between rs2297810, rs4646491 and rs2297809 polymorphisms of CYP4B1 gene and the risk of GC. More precisely, stratification by age revealed that the frequency distributions of TC heterozygous genotype and TT-TC genotype of rs4646491 were statistically different between the case and control groups (p = 0.015; p = 0.040). GC risk in TC genotype carriers was 1.36 times higher than that in CC genotype carriers, and the risk in TT-TC genotype carriers was 1.29 times than that in CC genotype carriers. Stratification of participants according to their smoking habits indicated that the frequency distribution of TC heterozygous genotype and TT-TC genotype of rs4646491 were statistically different between the cases and controls (p = 0.009; p = 0.027). The risk of GC in people with TC genotype was 1.52 times higher than those with CC genotype, and the risk in people with TT-TC genotype was 1.40 times than those with CC genotype. Furthermore, in the non-drinking subgroup, the frequency distribution of TC heterozygous genotype and TT-TC genotype of rs4646491 were statistically different between cases and controls (p = 0.010; p = 0.030). The risk of GC in people with TC genotype was 1.50 times higher than those with CC genotype, and the risk in people with TT-TC genotype was 1.39 times than those with CC genotype. The rs4646491 polymorphism TC and TT-TC genotype might be risk factors for GC. In the allele, recessive and additive models, the frequency distributions of rs4646491 genotypes were not statistically different (p > 0.05). For rs2297810 and rs2297809, no significant differences were observed in each group under all genetic models. Age-, stage-, and lymphatic metastasis-stratified analyses were also performed to investigate the association between SNPs and GC risk under different genotypic models, and no significant differences were found (Supplementary Table 1).
MDR analysis on the correlation between SNP-SNP interactions and the risk of GC
The impact of SNP-SNP high-order interactions on the risk of GC was assessed by MDR analysis. The dendrogram (Fig. 1) indicates that the interaction between rs2297810 and rs4646491 had a strong antagonistic effect on the CYP4B1 gene. The best locus model of CYP4B1 SNPs for predicting GC susceptibility is shown in Table 5. Among all models, the two-locus model (rs2297810-rs4646491) was the best predictive model with a perfect cross-validation consistency (CVC) of 10/10 and a test accuracy of 0.547 (OR = 1.49, 95% CI = 1.21–1.84, p < 0.001).
Different clinical indicators based on the genotypes of selected SNPs
We also analyzed the association between three SNPs and clinical indicators of GC patients. Clinical indicators included carcinoma embryonic antigen (CEA), alpha fetoprotein (AFP), carbohydrate antigen 199 (CA199), carbohydrate antigen 125 (CA125) and carbohydrate antigen 50 (CA50). The results showed no significant association between clinical indicators of three SNPs and the risk of GC under different genotypes (Supplementary Table 2).
At present, the incidence of GC shows a gradual upward trend. It has been reported that various factors may lead to the occurrence of GC, including inflammation, infection, diet, environmental factors, immune factors and genetic factors. Cytochrome P450 (CYP) is a superfamily of enzymes and a typical phase I drug metabolism enzyme, which is located in the inner membrane of mitochondria and the endoplasmic reticulum membrane of eukaryotic cells. [8, 14]. CYP4B1 is a member of the CYP4B subfamily, and the current researches on CYP4B1 gene mainly focus on its function analysis. Studies have shown that CYP4B1 plays an important role in the metabolic process of endogenous compounds and exogenous substances (drugs, environmental toxicants, pro-carcinogens), thereby affecting the occurrence and development of diseases . It is well known that the drug metabolizing enzymes in the human body are also the metabolic enzymes of important carcinogens, which control and affect the metabolism of carcinogens, so they play a decisive role in tumor susceptibility. The stomach is the major site of exposure to poisons and carcinogens, and its metabolic balance is crucial for maintaining normal physiological functions. Therefore, we have reason to speculate that CYP4B1 is closely related to the pathogenic mechanism of GC. Based on this, our study investigated the association of SNPs (rs2297810, rs4646491 and rs2297809) in the CYP4B1 gene with GC risk. As a result, we found for the first time that the TC genotype of CYP4B1-rs4646491 was statistically associated with an increased risk of GC. Our findings can provide a new perspective for future research on GC.
In recent years, the study of SNP has become an effective tool and method for molecular genetics research, and has attracted much attention . In our study, three SNPs (rs2297810, rs4646491 and rs2297809) of the CYP4B1 gene were taken as the research objects to explore the relationship between them and GC risk. As a result, we found that only rs4646491 was associated with increased GC risk. Notably, no studies describing the role of rs4646491 in disease susceptibility have been published previously. As for rs2297809 and rs2297810 polymorphisms, only a few studies have reported them. For example, rs2297809 and rs2297810 polymorphisms were reported in a study exploring genes controlling the age at onset of Parkinson’s disease, but no positive results were observed . Likewise, our findings also showed that rs2297809 and rs2297810 polymorphisms were not significantly associated with GC risk under all genetic models. Current evidence may suggest that rs2297810 and rs2297809 are not associated with GC risk, but lager sample size and further validation in other populations are need.
It has been reported that there is a gender difference in the incidence of GC worldwide, and the incidence of GC in men is about twice as high as that in women, especially in countries with a high incidence of GC . We got a similar result by stratification analysis that CYP4B1 gene rs4646491 was associated with the risk of GC in the male group. On the one hand, we believed that men’s unhealthy lifestyle habits (smoking or drinking) contribute to this fact. On the other hand, this may be related to the role of androgens in regulating CYP4B1 expression. Imaoka S et al.  have found that the expression of CYP4B1 in the bladder of mature male rats is higher than that in the bladder of mature female rats, and its expression increases with the growth of rat, suggesting that the CYP4B1 gene may be specifically expressed in males. Combined with our findings that the rs4646491 polymorphism was associated with an increased risk of GC in men, further indicating that androgens may affect the expression of CYP4B1 by affecting the mutation of rs4646491, thereby affecting the occurrence and development of GC.
Smoking and alcohol consumption are major risk factors for GC. Previous studies have shown that risk of GC is higher in smokers and drinkers when compared to no-smokers and no-drinkers [19,20,21,22,23]. However, studies have also found that non-drinkers  and non-smokers are still at the risk of developing GC . Our results manifested that there was a correlation between the lifestyle of non-smokers and non-drinkers and the risk of GC. This was partially consistent with our findings. As is known to all, tumor-related clinical indicators is of great significance for the early detection, diagnosis and prognosis monitoring of tumors. Many studies have shown that CEA [25,26,27], AFP , CA199 , CA125  and CA50  are common biomarkers in GC. However, no significant association between clinical indicators (CEA, AFP, CA19-9, CA125 and CA50) of targeted SNPs and the risk of GC under different genotypes was found in our study. The reason for this result may be related to the small random sample in our study. In follow-up studies, the sample size should be expanded for more in-depth research.
This research firstly showed a significant association between rs4646491 on CYP4B1 gene and GC risk, suggesting that rs4646491 polymorphism on CYP4B1 was an important factor for predicting the risk of GC, and it was beneficial for the early discovery and diagnosis of GC. At the same time, there are several limitations in the study. Firstly, GC patients and healthy subjects from the same hospital may not be representative of the population as a whole. Secondly, this study includes only three SNPs, which may not provide a comprehensive understanding of genetic variations in the CYP4B1 gene. Therefore, further studies are needed to explore the association of multiple SNPs in the CYP4B1 gene with GC risk in populations from different regions and ethnicities.
In conclusion, our study firstly indicates that the rs4646491 polymorphism on CYP4B1 may be associated with the risk of GC. This study will provide a theoretical basis for the early detection and treatment of GC in the future.
The datasets supporting the conclusions of this article are included within the article and its additional files.
Single nucleotide polymorphisms.
Multifactor dimensionality reduction.
Cytochrome P450 family 4.
Minor allele frequency.
Carcinoma embryonic antigen.
Carbohydrate antigen 199.
Carbohydrate antigen 125.
Carbohydrate antigen 50.
Smyth EC, Nilsson M, Grabsch HI, van Grieken NC, Lordick F. Gastric cancer. Lancet (London England). 2020;396(10251):635–48. doi:https://doi.org/10.1016/s0140-6736(20)31288-5.
Sung H, Ferlay J, Siegel RL. Global Cancer S. 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 2021;71(3):209–249. doi: https://doi.org/10.3322/caac.21660.
Wang FH, Shen L, Li J, Zhou ZW, Liang H, Zhang XT, Tang L, Xin Y, Jin J, Zhang YJ, et al. The Chinese Society of Clinical Oncology (CSCO): clinical guidelines for the diagnosis and treatment of gastric cancer. Cancer Commun (London England). 2019;39(1):10. doi:https://doi.org/10.1186/s40880-019-0349-9.
Fan Y, Gu X. Association of Genetic Polymorphisms in TNFRSF11 with the Progression of Genetic Susceptibility to Gastric Cancer. 2020;2020:4103264. doi: https://doi.org/10.1155/2020/4103264.
López-Basave HN, Morales-Vásquez F, Ruiz-Molina JM, Namendys-Silva SA, Vela-Sarmiento I, Ruan JM, Rosciano AE, Calderillo-Ruiz G, Díaz-Romero C, Herrera-Gómez A, et al. Gastric cancer in young people under 30 years of age: worse prognosis, or delay in diagnosis? Cancer Manage Res. 2013;5:31–6. doi:https://doi.org/10.2147/cmar.s40377.
Pan H, Gu X, Wang X, Gao Z, Ding G, Zou C, Fan Y. Case-control study on TP73 rs1801173 C > T gene polymorphism and susceptibility to gastric cancer in a Chinese Han population. 2022;15(1):14. doi: https://doi.org/10.1186/s12920-021-01151-2.
Gu X, Mao Z, Pan H, Zou C, Ding G, Fan Y. Case-Control Study on TNFRSF6B Gene Polymorphism and Susceptibility to Gastric Cancer in a Chinese Han Population. Pharmacogenomics and personalized medicine. 2020;13:749–56. doi:https://doi.org/10.2147/pgpm.s283308.
Jarrar YB, Lee SJ. Molecular Functionality of Cytochrome P450 4 (CYP4) Genetic Polymorphisms and Their Clinical Implications. Int J Mol Sci. 2019;20(17):4274. doi:https://doi.org/10.3390/ijms20174274.
Poch MT, Cutler NS, Yost GS, Hines RN. Molecular mechanisms regulating human CYP4B1 lung-selective expression. Drug Metab Dispos. 2005;33(8):1174–84. doi:https://doi.org/10.1124/dmd.105.004523.
Lim S, Alshagga M, Ong CE, Chieng JY, Pan Y. Cytochrome P450 4B1 (CYP4B1) as a target in cancer treatment. 2020;39(6):785–796. doi: https://doi.org/10.1177/0960327120905959.
Sasaki T, Horikawa M, Orikasa K, Sato M, Arai Y, Mitachi Y, Mizugaki M, Ishikawa M, Hiratsuka M. Possible relationship between the risk of Japanese bladder cancer cases and the CYP4B1 genotype. Jpn J Clin Oncol. 2008;38(9):634–40. doi:https://doi.org/10.1093/jjco/hyn081.
Lin JT, Chan TC, Li CF, Huan SKH, Tian YF, Liang PI, Pan CT, Shiue YL. Downregulation of the cytochrome P450 4B1 protein confers a poor prognostic factor in patients with urothelial carcinomas of upper urinary tracts and urinary bladder. APMIS: acta pathologica, microbiologica, et immunologica Scandinavica. 2019;127(4):170–180. doi: https://doi.org/10.1111/apm.12939.
Tamaki Y, Arai T, Sugimura H, Sasaki T, Honda M, Muroi Y, Matsubara Y, Kanno S, Ishikawa M, Hirasawa N, et al. Association between cancer risk and drug-metabolizing enzyme gene (CYP2A6, CYP2A13, CYP4B1, SULT1A1, GSTM1, and GSTT1) polymorphisms in cases of lung cancer in Japan. Drug Metab Pharmacokinet. 2011;26(5):516–22. doi:https://doi.org/10.2133/dmpk.dmpk-11-rg-046.
Adhikari A, De M. Association of Cytochrome P450 with Cancer Induced by Betel Quid (BQ): A Review. iMedPub. 2015;1.
Liu X, Jia Y, Shi C, Kong D, Wu Y, Zhang T, Wei A, Wang D. CYP4B1 is a prognostic biomarker and potential therapeutic target in lung adenocarcinoma. 2021;16(2):e0247020. doi: https://doi.org/10.1371/journal.pone.0247020.
Fan Y, Gu X, Pan H, Dai Z, Zou C, Gao Z, Zhang H. Association of Genetic Polymorphisms in TNFRSF11 with the Progression of Genetic Susceptibility to Gastric Cancer. J Oncol. 2020;2020:4103264. doi:https://doi.org/10.1155/2020/4103264.
Oliveira SA, Li YJ, Noureddine MA, Zuchner S, Qin X, Pericak-Vance MA, Vance JM. Identification of risk and age-at-onset genes on chromosome 1p in Parkinson disease. Am J Hum Genet. 2005;77(2):252–64. doi:https://doi.org/10.1086/432588.
Xia C, Dong X, Li H, Cao M, Sun D, He S, Yang F, Yan X, Zhang S, Li N, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chin Med J (Engl). 2022;135(5):584–90. doi:https://doi.org/10.1097/cm9.0000000000002108.
Ladeiras-Lopes R, Pereira AK, Nogueira A, Pinheiro-Torres T, Pinto I, Santos-Pereira R, Lunet N. Smoking and gastric cancer: systematic review and meta-analysis of cohort studies. Cancer causes & control: CCC. 2008;19(7):689–701. doi:https://doi.org/10.1007/s10552-008-9132-y.
La Torre G, Chiaradia G, Gianfagna F, De Lauretis A, Boccia S, Mannocci A, Ricciardi W. Smoking status and gastric cancer risk: an updated meta-analysis of case-control studies published in the past ten years. Tumori. 2009;95(1):13–22.
Tramacere I, Negri E, Pelucchi C, Bagnardi V, Rota M, Scotti L, Islami F, Corrao G, La Vecchia C, Boffetta P. A meta-analysis on alcohol drinking and gastric cancer risk. Annals of oncology: official journal of the European Society for Medical Oncology. 2012;23(1):28–36. doi:https://doi.org/10.1093/annonc/mdr135.
Deng W, Jin L, Zhuo H, Vasiliou V, Zhang Y. Alcohol consumption and risk of stomach cancer: A meta-analysis. Chemico-Biol Interact. 2021;336:109365. doi:https://doi.org/10.1016/j.cbi.2021.109365.
Li WY, Han Y, Xu HM, Wang ZN, Xu YY, Song YX, Xu H, Yin SC, Liu XY, Miao ZF. Smoking status and subsequent gastric cancer risk in men compared with women: a meta-analysis of prospective observational studies. BMC Cancer. 2019;19(1):377. doi:https://doi.org/10.1186/s12885-019-5601-9.
Larsson SC, Carter P, Kar S. Smoking, alcohol consumption, and cancer: A mendelian randomisation study in UK Biobank and international genetic consortia participants. 2020;17(7):e1003178. doi: https://doi.org/10.1371/journal.pmed.1003178.
Shen M, Wang H, Wei K, Zhang J, You C. Five common tumor biomarkers and CEA for diagnosing early gastric cancer: A protocol for a network meta-analysis of diagnostic test accuracy. Medicine. 2018;97(19):e0577. doi:https://doi.org/10.1097/md.0000000000010577.
Feng F, Tian Y, Xu G, Liu Z, Liu S, Zheng G, Guo M, Lian X, Fan D, Zhang H. Diagnostic and prognostic value of CEA, CA19-9, AFP and CA125 for early gastric cancer. BMC Cancer. 2017;17(1):737. doi:https://doi.org/10.1186/s12885-017-3738-y.
Abd Temur A, Aqeel Rashid F. Irisin and Carcinoembryonic Antigen (CEA) as Potential Diagnostic Biomarkers in Gastric and Colorectal Cancers. Rep Biochem Mol biology. 2021;10(3):488–94. doi:https://doi.org/10.52547/rbmb.10.3.488.
Mao X, Wang J, Luo F. Alpha-fetoprotein can promote gastric cancer progression via upregulation of metastasis-associated colon cancer 1. Oncol Lett. 2022;23(3):84. doi:https://doi.org/10.3892/ol.2022.13204.
Pan Q, Law COK, Yung MMH, Han KC, Pon YL, Lau TCK. Novel RNA aptamers targeting gastrointestinal cancer biomarkers CEA, CA50 and CA72-4 with superior affinity and specificity. 2018;13(10):e0198980. doi: https://doi.org/10.1371/journal.pone.0198980.
We thank all authors for their contributions and supports. We are also grateful to all subjects for providing blood samples.
This study was supported by the Hainan Provincial Major science and technology project in 2020 (number: ZDKJ202005) and the specific research fund of the Innovation Platform for Academicians of Hainan Province.
Ethics approval and consent to participate
This study was approved by the Ethics Committee of Hainan Cancer Hospital and conformed to the ethical principles of the Declaration of Helsinki. All participants signed informed consent forms before participating in the study.
Consent for publication
The authors have declared that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
About this article
Cite this article
Yu, S., Chen, Z., Cheng, J. et al. Case-control study on CYP4B1 gene polymorphism and susceptibility to gastric cancer in the chinese Han population. BMC Med Genomics 15, 223 (2022). https://doi.org/10.1186/s12920-022-01367-w