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Gastric Cancer

, Volume 22, Issue 1, pp 60–68 | Cite as

Multi-marker analysis of genomic annotation on gastric cancer GWAS data from Chinese populations

  • Fei Yu
  • Tian Tian
  • Bin Deng
  • Tianpei Wang
  • Qi Qi
  • Meng Zhu
  • Caiwang Yan
  • Hui Ding
  • Jinchen Wang
  • Juncheng Dai
  • Hongxia Ma
  • Yanbing DingEmail author
  • Guangfu JinEmail author
Original Article
  • 395 Downloads

Abstract

Background

Gastric cancer (GC) is one of the high-incidence and high-mortality cancers all over the world. Though genome-wide association studies (GWASs) have found some genetic loci related to GC, they could only explain a small fraction of the potential pathogenesis for GC.

Methods

We used multi-marker analysis of genomic annotation (MAGMA) to analyze pathways from four public pathway databases based on Chinese GWAS data including 2631 GC cases and 4373 controls. The differential expressions of selected genes in certain pathways were assessed on the basis of The Cancer Genome Atlas database. Immunohistochemistry was also conducted on 55 GC and paired normal tissues of Chinese patients to localize the expression of genes and further validate the differential expression.

Results

We identified three pathways including chemokine signaling pathway, potassium ion import pathway, and interleukin-7 (IL7) pathway, all of which were associated with GC risk. NMI in IL7 pathway and RAC1 in chemokine signaling pathway might be two new candidate genes involved in GC pathogenesis. Additionally, NMI and RAC1 were overexpressed in GC tissues than normal tissues.

Conclusion

Immune and inflammatory associated processes and potassium transporting might participate in the development of GC. Besides, NMI and RAC1 might represent two new key genes related to GC. Our findings might give new insight into the biological mechanism and immunotherapy for GC.

Keywords

Pathway Gastric cancer GWAS Immune and inflammatory associated processes Potassium transporting 

Notes

Acknowledgements

The authors thank all the participants of the Nanjing/Beijing and the National Cancer Institute gastric cancer studies. This study was supported by grants from the National key research and development program of China (Grant no. 2016YFC1302703); National Natural Science Foundation of China (81521004, 81422042, 81373090, 81703297); Jiangsu Province’s Key Medical Talents Program (QNRC2016352); the key grant of natural science foundation of Jiangsu higher education institutions (15KJA330002); the Priority Academic Program Development of Jiangsu Higher Education Institutions (Public Health and Preventive Medicine) and Top-notch Academic Programs Project of Jiangsu Higher Education Institutions (PPZY2015A067).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Human rights statement

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1964 and later versions.

Informed consent

Informed consent to be included in the study, or the equivalent, was obtained from all patients.

Supplementary material

10120_2018_841_MOESM1_ESM.xlsx (390 kb)
Supplementary material 1 (XLSX 390 KB)
10120_2018_841_MOESM2_ESM.docx (5.8 mb)
Supplementary material 2 (DOCX 5945 KB)

References

  1. 1.
    Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87–108.Google Scholar
  2. 2.
    Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, et al. Cancer statistics in China, 2015. CA Cancer J Clin. 2016;66(2):115–32.Google Scholar
  3. 3.
    Bornschein J, Selgrad M, Warnecke M, Kuester D, Wex T, Malfertheiner P. H. pylori infection is a key risk factor for proximal gastric cancer. Digestive Dis Sci. 2010;55(11):3124–31.Google Scholar
  4. 4.
    Blankfield RP. Helicobacter pylori infection and the development of gastric cancer. N EnglJ Med. 2002;346(1):65–7.Google Scholar
  5. 5.
    Cheng XJ, Lin JC, Tu SP. Etiology and prevention of gastric cancer. Gastrointest Tumors. 2016;3(1):25–36.Google Scholar
  6. 6.
    Van Cutsem E, Sagaert X, Topal B, Haustermans K, Prenen H. Gastric cancer. Lancet. 2016;388(10060):2654–64.Google Scholar
  7. 7.
    Mocellin S, Verdi D, Pooley KA, Nitti D. Genetic variation and gastric cancer risk: a field synopsis and meta-analysis. Gut. 2015;64(8):1209–19.Google Scholar
  8. 8.
    Abnet CC, Freedman ND, Hu N, Wang Z, Yu K, Shu XO, et al. A shared susceptibility locus in PLCE1 at 10q23 for gastric adenocarcinoma and esophageal squamous cell carcinoma. Nat Genet. 2010;42(9):764–7.Google Scholar
  9. 9.
    Wang Z, Dai J, Hu N, Miao X, Abnet CC, Yang M, et al. Identification of new susceptibility loci for gastric non-cardia adenocarcinoma: pooled results from two Chinese genome-wide association studies. Gut. 2017;66(4):581–7.Google Scholar
  10. 10.
    Shi Y, Hu Z, Wu C, Dai J, Li H, Dong J, et al. A genome-wide association study identifies new susceptibility loci for non-cardia gastric cancer at 3q13.31 and 5p13.1. Nat Genet. 2011;43(12):1215–8.Google Scholar
  11. 11.
    Hu N, Wang Z, Song X, Wei L, Kim BS, Freedman ND, et al. Genome-wide association study of gastric adenocarcinoma in Asia: a comparison of associations between cardia and non-cardia tumours. Gut. 2016;65(10):1611–8.Google Scholar
  12. 12.
    Zhu M, Yan C, Ren C, Huang X, Zhu X, Gu H, et al. Exome array analysis identifies variants in SPOCD1 and BTN3A2 that affect risk for gastric cancer. Gastroenterology. 2017;152(8):2011–21.Google Scholar
  13. 13.
    Sakamoto H, Yoshimura K, Saeki N, Katai H, Shimoda T, Matsuno Y, et al. Genetic variation in PSCA is associated with susceptibility to diffuse-type gastric cancer. Nat Genet. 2008;40(6):730–40.Google Scholar
  14. 14.
    Mucci LA, Hjelmborg JB, Harris JR, Czene K, Havelick DJ, Scheike T, et al. Familial risk and heritability of cancer among twins in Nordic countries. Jama. 2016;315(1):68–76.Google Scholar
  15. 15.
    Hyland PL, Zhang H, Yang Q, Yang HH, Hu N, Lin SW, et al. Pathway, in silico and tissue-specific expression quantitative analyses of oesophageal squamous cell carcinoma genome-wide association studies data. Int J Epidemiol. 2016;45(1):206–20.Google Scholar
  16. 16.
    Li D, Duell EJ, Yu K, Risch HA, Olson SH, Kooperberg C, et al. Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer. Carcinogenesis. 2012;33(7):1384–90.Google Scholar
  17. 17.
    Menashe I, Maeder D, Garcia-Closas M, Figueroa JD, Bhattacharjee S, Rotunno M, et al. Pathway analysis of breast cancer genome-wide association study highlights three pathways and one canonical signaling cascade. Cancer Res. 2010;70(11):4453–9.Google Scholar
  18. 18.
    de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015;11(4):e1004219.Google Scholar
  19. 19.
    Sniekers S, Stringer S, Watanabe K, Jansen PR, Coleman JRI, Krapohl E, et al. Genome-wide association meta-analysis of 78,308 individuals identifies new loci and genes influencing human intelligence. Nat Genet. 2017;49(7):1107–12.Google Scholar
  20. 20.
    Jansen A, Dieleman GC, Smit AB, Verhage M, Verhulst FC, Polderman TJC, et al. Gene-set analysis shows association between FMRP targets and autism spectrum disorder. Eur J Hum Genet EJHG. 2017;25(7):863–8.Google Scholar
  21. 21.
    Delaneau O, Marchini J, Zagury JF. A linear complexity phasing method for thousands of genomes. Nat Methods. 2011;9(2):179–81.Google Scholar
  22. 22.
    Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 2009;5(6):e1000529.Google Scholar
  23. 23.
    Marchini J, Howie B, Myers S, McVean G, Donnelly P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet. 2007;39(7):906–13.Google Scholar
  24. 24.
    Magi R, Morris AP. GWAMA: software for genome-wide association meta-analysis. BMC Bioinform. 2010;11:288.Google Scholar
  25. 25.
    Timbers TA, Garland SJ, Mohan S, Flibotte S, Edgley M, Muncaster Q, et al. Accelerating gene discovery by phenotyping whole-genome sequenced multi-mutation strains and using the sequence kernel association test (SKAT). PLoS Genet. 2016;12(8):e1006235.Google Scholar
  26. 26.
    Chen Y, Tian T, Mao MJ, Deng WY, Li H. CRBP-1 over-expression is associated with poor prognosis in tongue squamous cell carcinoma. BMC Cancer. 2018;18(1):514.Google Scholar
  27. 27.
    Lee JH, Kim Y, Choi JW, Kim YS. Genetic variants and risk of gastric cancer: a pathway analysis of a genome-wide association study. SpringerPlus. 2015;4:215.Google Scholar
  28. 28.
    Zhu H, Yang M, Zhang H, Chen X, Yang X, Zhang C, et al. Genome-wide association pathway analysis to identify candidate single nucleotide polymorphisms and molecular pathways for gastric adenocarcinoma. Tumour Biol J Int Soc Oncodev Biol Med. 2015;36(7):5635–9.Google Scholar
  29. 29.
    Zhang K, Chang S, Cui S, Guo L, Zhang L, Wang J. ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework. Nucleic acids research. 2011;39(Web Server issue):W437–43.Google Scholar
  30. 30.
    Palomino DC, Marti LC. Chemokines and immunity. Einstein (Sao Paulo). 2015;13(3):469–73.Google Scholar
  31. 31.
    Lewellis SW, Knaut H. Attractive guidance: how the chemokine SDF1/CXCL12 guides different cells to different locations. Semin Cell Dev Biol. 2012;23(3):333–40.Google Scholar
  32. 32.
    Roy I, McAllister DM, Gorse E, Dixon K, Piper CT, Zimmerman NP, et al. Pancreatic cancer cell migration and metastasis is regulated by chemokine-biased agonism and bioenergetic signaling. Cancer Res. 2015;75(17):3529–42.Google Scholar
  33. 33.
    Singh R, Lillard JW Jr, Singh S. Chemokines: key players in cancer progression and metastasis. Front Biosci (Schol Ed). 2011;3:1569–82.Google Scholar
  34. 34.
    Wani N, Nasser MW, Ahirwar DK, Zhao H, Miao Z, Shilo K, et al. C-X-C motif chemokine 12/C-X-C chemokine receptor type 7 signaling regulates breast cancer growth and metastasis by modulating the tumor microenvironment. Breast Cancer Res BCR. 2014;16(3):R54.Google Scholar
  35. 35.
    Bolitho C, Hahn MA, Baxter RC, Marsh DJ. The chemokine CXCL1 induces proliferation in epithelial ovarian cancer cells by transactivation of the epidermal growth factor receptor. Endocrine-Related Cancer. 2010;17(4):929–40.Google Scholar
  36. 36.
    Kiefer F, Siekmann AF. The role of chemokines and their receptors in angiogenesis. Cell Mol Life Sci CMLS. 2011;68(17):2811–30.Google Scholar
  37. 37.
    Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420(6917):860–7.Google Scholar
  38. 38.
    Surh CD, Sprent J. Homeostasis of naive and memory T cells. Immunity. 2008;29(6):848–62.Google Scholar
  39. 39.
    Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646–74.Google Scholar
  40. 40.
    Rosenberg SA, Restifo NP. Adoptive cell transfer as personalized immunotherapy for human cancer. Science. 2015;348(6230):62–8.Google Scholar
  41. 41.
    Amedei A, Prisco D, MM DE. The use of cytokines and chemokines in the cancer immunotherapy. Recent Patents Anti-Cancer Drug Discov. 2013;8(2):126–42.Google Scholar
  42. 42.
    Ruella M, Kalos M. Adoptive immunotherapy for cancer. Immunol Rev. 2014;257(1):14–38.Google Scholar
  43. 43.
    Ye Z, Li Z, Jin H, Qian Q. Therapeutic cancer vaccines. Adv Exp Med Biol. 2016;909:139–67.Google Scholar
  44. 44.
    Subhash VV, Yeo MS, Tan WL, Yong WP. Strategies and advancements in harnessing the immune system for gastric cancer immunotherapy. J Immunol Res. 2015;2015:308574.Google Scholar
  45. 45.
    Valentine FT, Golomb FM, Harris M, Roses DF. A novel immunization strategy using cytokine/chemokines induces new effective systemic immune responses, and frequent complete regressions of human metastatic melanoma. Oncoimmunology. 2018;7(2):e1386827.Google Scholar
  46. 46.
    Alfaro C, Sanmamed MF, Rodriguez-Ruiz ME, Teijeira A, Onate C, Gonzalez A, et al. Interleukin-8 in cancer pathogenesis, treatment and follow-up. Cancer Treat Rev. 2017;60:24–31.Google Scholar
  47. 47.
    Fridlender ZG, Buchlis G, Kapoor V, Cheng G, Sun J, Singhal S, et al. CCL2 blockade augments cancer immunotherapy. Cancer Res. 2010;70(1):109–18.Google Scholar
  48. 48.
    Gao J, Zhao L, Wan YY, Zhu B. Mechanism of action of IL-7 and its potential applications and limitations in cancer immunotherapy. Int J Mol Sci. 2015;16(5):10267–80.Google Scholar
  49. 49.
    Bortner CD, Cidlowski JA. Cell shrinkage and monovalent cation fluxes: role in apoptosis. Arch Biochem Biophys. 2007;462(2):176–88.Google Scholar
  50. 50.
    Cain K, Langlais C, Sun XM, Brown DG, Cohen GM. Physiological concentrations of K + inhibit cytochrome c-dependent formation of the apoptosome. J Biol Chem. 2001;276(45):41985–90.Google Scholar
  51. 51.
    Hughes FM Jr, Bortner CD, Purdy GD, Cidlowski JA. Intracellular K + suppresses the activation of apoptosis in lymphocytes. J Biol Chem. 1997;272(48):30567–76.Google Scholar
  52. 52.
    Cotter TG. Apoptosis and cancer: the genesis of a research field. Nat Rev Cancer. 2009;9(7):501–7.Google Scholar
  53. 53.
    Eil R, Vodnala SK, Clever D, Klebanoff CA, Sukumar M, Pan JH, et al. Ionic immune suppression within the tumour microenvironment limits T cell effector function. Nature. 2016;537(7621):539–43.Google Scholar
  54. 54.
    Chandy KG, Norton RS. Immunology channelling potassium to fight cancer. Nature. 2016;537(7621):497–9.Google Scholar
  55. 55.
    Han Y, Shi Y, Han Z, Sun L, Fan D. Detection of potassium currents and regulation of multidrug resistance by potassium channels in human gastric cancer cells. Cell Biol Int. 2007;31(7):741–7.Google Scholar
  56. 56.
    Bao J, Zervos AS. Isolation and characterization of Nmi, a novel partner of Myc proteins. Oncogene. 1996;12(10):2171–6.Google Scholar
  57. 57.
    Fillmore RA, Mitra A, Xi Y, Ju J, Scammell J, Shevde LA, et al. Nmi (N-Myc interactor) inhibits Wnt/beta-catenin signaling and retards tumor growth. Int J Cancer. 2009;125(3):556–64.Google Scholar
  58. 58.
    Hou J, Wang T, Xie Q, Deng W, Yang JY, Zhang SQ, et al. N-Myc-interacting protein (NMI) negatively regulates epithelial-mesenchymal transition by inhibiting the acetylation of NF-kappaB/p65. Cancer Lett. 2016;376(1):22–33.Google Scholar
  59. 59.
    Zhu M, John S, Berg M, Leonard WJ. Functional association of Nmi with Stat5 and Stat1 in IL-2- and IFNgamma-mediated signaling. Cell. 1999;96(1):121–30.Google Scholar
  60. 60.
    Rani A, Murphy JJ. STAT5 in cancer and immunity. J Interferon Cytokine Res. 2016;36(4):226–37.Google Scholar
  61. 61.
    Eller-Borges R, Batista WL, da Costa PE, Tokikawa R, Curcio MF, Strumillo ST, et al. Ras, Rac1, and phosphatidylinositol-3-kinase (PI3K) signaling in nitric oxide induced endothelial cell migration. Nitric Oxide Biol Chem. 2015;47:40–51.Google Scholar
  62. 62.
    Dammann K, Khare V, Gasche C. Tracing PAKs from GI inflammation to cancer. Gut. 2014;63(7):1173–84.Google Scholar
  63. 63.
    Shi Y, Bollam SR, White SM, Laughlin SZ, Graham GT, Wadhwa M, et al. Rac1-mediated DNA damage and inflammation promote Nf2 tumorigenesis but also limit cell-cycle progression. Dev Cell. 2016;39(4):452–65.Google Scholar
  64. 64.
    Leng R, Liao G, Wang H, Kuang J, Tang L. Rac1 expression in epithelial ovarian cancer: effect on cell EMT and clinical outcome. Med Oncol. 2015;32(2):329.Google Scholar
  65. 65.
    Zhou Y, Liao Q, Han Y, Chen J, Liu Z, Ling H, et al. Rac1 overexpression is correlated with epithelial mesenchymal transition and predicts poor prognosis in non-small cell lung cancer. J Cancer. 2016;7(14):2100–9.Google Scholar
  66. 66.
    Ji J, Feng X, Shi M, Cai Q, Yu Y, Zhu Z, et al. Rac1 is correlated with aggressiveness and a potential therapeutic target for gastric cancer. Int J Oncol. 2015;46(3):1343–53.Google Scholar
  67. 67.
    Bid HK, Roberts RD, Manchanda PK, Houghton PJ. RAC1: an emerging therapeutic option for targeting cancer angiogenesis and metastasis. Mol Cancer Ther. 2013;12(10):1925–34.Google Scholar
  68. 68.
    Kim J, Kim Y, Lee KA. Ethnic differences in gastric cancer genetic susceptibility: allele flips of interleukin gene. World J Gastroenterol. 2014;20(16):4558–65.Google Scholar

Copyright information

© The International Gastric Cancer Association and The Japanese Gastric Cancer Association 2018

Authors and Affiliations

  1. 1.Department of Epidemiology and Biostatistics, School of Public HealthNanjing Medical UniversityNanjingChina
  2. 2.Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre For Cancer MedicineNanjing Medical UniversityNanjingChina
  3. 3.Department of Epidemiology and Biostatistics, School of Public HealthNantong UniversityNantongChina
  4. 4.Department of Gastroenterologythe Affiliated Hospital of Yangzhou UniversityYangzhouChina

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