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Chen B, Wang Y, Tang W, Chen Y, Liu C, Kang M, Xie J. Association between PPARγ, PPARGC1A, and PPARGC1B genetic variants and susceptibility of gastric cancer in an Eastern Chinese population. BMC Med Genomics 2022; 15:274. [PMID: 36587194 PMCID: PMC9805199 DOI: 10.1186/s12920-022-01428-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 12/26/2022] [Indexed: 01/01/2023] Open
Abstract
PURPOSE Previous studies showed that peroxisome proliferator-activated receptor gamma (PPARγ) and PPARγ coactivator1 family (PPARGC1A and PPARGC1B) gene single nucleotide variants (SNVs)were strongly associated with cancer susceptibility. The purpose of this study was to investigate the association of PPARγ, PPARGC1A, and PPARGC1B variants with the risk of gastric cancer (GC). PATIENTS AND METHODS We performed a case-control study of 490 GC cases and 1,476 healthy controls from eastern China. PPARγ rs1801282 C > G, rs3856806 C > T, PPARGC1A rs2970847 C > T, rs8192678 C > T and PPARGC1B rs7732671 G > C, rs17572019 G > A SNVs were selected to investigate the association between these SNVs and GC susceptibility. Genotypes of the SNVs were assessed by multiplex fluorescent PCR using a custom-by-design 48-Plex SNPscantm Kit. RESULTS The PPARγ rs1801282 SNV was associated with a decreased risk for GC (GC vs. CC: odds ratio (OR) = 0.62, 95% confidence interval (95%CI) = 0.42-0.93, adjusted P = 0.019; GC + GG vs. GG: OR = 0.63 95%CI = 0.42-0.93, adjusted P = 0.019; respectively). In addition, stratified analysis revealed that the PPARγ rs1801282 SNV was correlated with the risk of GC in subgroups of age ≥ 61, no smoking, and no alcohol consuming. We also confirmed that the PPARγ rs3856806 C > T SNV promoted the risk of GC in women. The PPARGC1A rs8192678 TT genotype decreased the susceptibility of GC in men. The PPARGC1A rs2970847 C > T SNV decreased the susceptibility of GC in the subgroup of BMI ≥ 24 kg/m2. The PPARGC1B rs7732671 G > C and rs17572019 G > A SNVs promoted the risk of GC in the subgroup of BMI ≥ 24 kg/m2. CONCLUSION This study indicates that the PPARγ, PPARGC1A, and PPARGC1B SNVs may be associated with the susceptibility of GC in eastern Chinese population. Future studies with larger populations, detailed H. pylori infection status for subgroup analysis, and functional study are needed to further clarify the relationship between these SNVs and GC risk.
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Affiliation(s)
- Boyang Chen
- grid.440618.f0000 0004 1757 7156Department of Cardiothoracic Surgery, The Affiliated Hospital of Putian University, Putian, 351100 Fujian Province China
| | - Yafeng Wang
- Department of Cardiology, The People’s Hospital of Xishuangbanna Dai Autonomous Prefecture, Jinghong, Yunnan Province China
| | - Weifeng Tang
- grid.428392.60000 0004 1800 1685Department of Cardiothoracic Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu Province China
| | - Yu Chen
- grid.415110.00000 0004 0605 1140Department of Medical Oncology, Fujian Cancer Hospital, Fujian Medical University Cancer Hospital, Fuzhou, Fujian Province China
| | - Chao Liu
- grid.452247.2Department of Cardiothoracic Surgery, Affiliated People’s Hospital of Jiangsu University, Zhenjiang, Jiangsu Province China
| | - Mingqiang Kang
- grid.440618.f0000 0004 1757 7156Department of Cardiothoracic Surgery, The Affiliated Hospital of Putian University, Putian, 351100 Fujian Province China ,grid.411176.40000 0004 1758 0478Department of Thoracic Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001 Fujian Province China
| | - Jinbiao Xie
- grid.440618.f0000 0004 1757 7156Department of Cardiothoracic Surgery, The Affiliated Hospital of Putian University, Putian, 351100 Fujian Province China
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Goudarzi H, Seyedjavadi SS, Fazeli M, Azad M, Goudarzi M. Genotyping of Peroxisome Proliferator-Activated Receptor gamma in Iranian Patients with Helicobacter pylori Infection. Asian Pac J Cancer Prev 2016. [PMID: 26225656 DOI: 10.7314/apjcp.2015.16.13.5219] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Helicobacter pylori (H. pylori) infection as a serious problem in both adults and children can induce chronic gastritis, peptic ulcer disease (PUD), and possibly gastric cancer. The aim of the current study was to survey antibiotic resistance and also to determine influence of PPARγ polymorphism in patients with H. pylori infection. During an 11-month-period, 98 H. pylori isolates were collected from 104 biopsy specimens. In vitro susceptibility of H. pylori isolates to 4 antimicrobial agents metronidazole, clarithromycin, amoxicillin and tetracycline were assessed by quantitative method according to European Committee on Antimicrobial Susceptibility Testing (EUCAST) guideline. PPARγ polymorphism was determined using polymerase chain reaction-restriction fragment length polymorphism assay. The frequency of H. pylori infection in our study was 94.2%. In vitro susceptibility data showed that highest level of resistance was related to metronidazole (66.3%), and the majority of H. pylori isolates were highly susceptible to amoxicillin and tetracycline (94.9% and 96.9%, respectively). Genotypic frequencies were 25.5% for CC (Pro12Pro), 40.8% for GC (Pro12Ala) and 33.7% for GG (Ala12Ala). In our study, CG genotype had highest distributions among infected patients with H. pylori. The study suggests that the PPAR-γ Pro12Ala polymorphism could be evaluated as a potential genetic marker for susceptibility to gastric cancer in the presence of H. pylori infection.
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Affiliation(s)
- Hossein Goudarzi
- Infectious Diseases and Tropical Medicine Research Center, Shahid Beheshti University of Medical Science, Tehran, Iran E-mail :
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Carbo A, Bassaganya-Riera J, Pedragosa M, Viladomiu M, Marathe M, Eubank S, Wendelsdorf K, Bisset K, Hoops S, Deng X, Alam M, Kronsteiner B, Mei Y, Hontecillas R. Predictive computational modeling of the mucosal immune responses during Helicobacter pylori infection. PLoS One 2013; 8:e73365. [PMID: 24039925 PMCID: PMC3764126 DOI: 10.1371/journal.pone.0073365] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2013] [Accepted: 07/18/2013] [Indexed: 02/06/2023] Open
Abstract
T helper (Th) cells play a major role in the immune response and pathology at the gastric mucosa during Helicobacter pylori infection. There is a limited mechanistic understanding regarding the contributions of CD4+ T cell subsets to gastritis development during H. pylori colonization. We used two computational approaches: ordinary differential equation (ODE)-based and agent-based modeling (ABM) to study the mechanisms underlying cellular immune responses to H. pylori and how CD4+ T cell subsets influenced initiation, progression and outcome of disease. To calibrate the model, in vivo experimentation was performed by infecting C57BL/6 mice intragastrically with H. pylori and assaying immune cell subsets in the stomach and gastric lymph nodes (GLN) on days 0, 7, 14, 30 and 60 post-infection. Our computational model reproduced the dynamics of effector and regulatory pathways in the gastric lamina propria (LP) in silico. Simulation results show the induction of a Th17 response and a dominant Th1 response, together with a regulatory response characterized by high levels of mucosal Treg) cells. We also investigated the potential role of peroxisome proliferator-activated receptor γ (PPARγ) activation on the modulation of host responses to H. pylori by using loss-of-function approaches. Specifically, in silico results showed a predominance of Th1 and Th17 cells in the stomach of the cell-specific PPARγ knockout system when compared to the wild-type simulation. Spatio-temporal, object-oriented ABM approaches suggested similar dynamics in induction of host responses showing analogous T cell distributions to ODE modeling and facilitated tracking lesion formation. In addition, sensitivity analysis predicted a crucial contribution of Th1 and Th17 effector responses as mediators of histopathological changes in the gastric mucosa during chronic stages of infection, which were experimentally validated in mice. These integrated immunoinformatics approaches characterized the induction of mucosal effector and regulatory pathways controlled by PPARγ during H. pylori infection affecting disease outcomes.
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Affiliation(s)
- Adria Carbo
- Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Josep Bassaganya-Riera
- Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Department of Biomedical Sciences and Pathobiology, Virginia-Maryland Regional College of Veterinary Medicine, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Mireia Pedragosa
- Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Monica Viladomiu
- Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Madhav Marathe
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Stephen Eubank
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Katherine Wendelsdorf
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Keith Bisset
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Stefan Hoops
- Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Xinwei Deng
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Department of Statistics, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Maksudul Alam
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Barbara Kronsteiner
- Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Yongguo Mei
- Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Raquel Hontecillas
- Nutritional Immunology and Molecular Medicine Laboratory, Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- Center for Modeling Immunity to Enteric Pathogens Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, Virginia, United States of America
- * E-mail:
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Canbay E, Kurnaz O, Canbay B, Bugra D, Cakmakoglu B, Bulut T, Yamaner S, Sokucu N, Buyukuncu Y, Yilmaz-Aydogan H. PPAR-gamma Pro12Ala polymorphism and gastric cancer risk in a Turkish population. Asian Pac J Cancer Prev 2013; 13:5875-8. [PMID: 23317272 DOI: 10.7314/apjcp.2012.13.11.5875] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Peroxisome proliferator-activated receptor gamma (PPARγ) is a ligand dependent transcription factor involved in various processes, including carcinogenesis. We aimed to investigate any possible association of the PPARγPro12Ala (rs1801282) polymorphism with risk of developing gastric cancer (GC). PATIENTS AND METHODS A hospital based case control study was designed covering 50 patients with GC and 120 healthy controls. The frequencies of PPARγPro12Ala (rs1801282) were determined using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. RESULTS The Ala12 allele of the PPARγPro12Ala G gene was associated with a 1.95 fold increased risk of GC development (p: 0.022; 95% CI: 1.58-2.40). Subgroup analyses showed that the same allele was also associated with metastasis (p: 0.000; OR:4.09; 95%CI:2.273-7.368) and differentiation (p: 0.004; OR:1.95; 95%CI:1.335-2.875) in patients with GC. CONCLUSION This study suggests that the PPARγPro12Ala G (Ala12) allele might be associated with development, differentiation and metastatic process of GC in the Turkish population. Further studies conducted in larger study groups and in different ethnic populations will be needed to clarify the exact role of the PPARγPro12Ala polymorphism in GC.
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Affiliation(s)
- Emel Canbay
- National Peritoneal Organization to support Peritoneal Dissemination Treatment, Department of General Surgery, Kishiwada Tokushukai Hospital, Osaka, Japan.
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