본문 바로가기
KERD
논문KCI 등재

Functional Annotation and Gene Set Analysis of Gastric Cancer Risk Loci in a Korean Population

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

주제분류의학일반

초록

Purpose We aimed to identify the associated single nucleotide polymorphisms (SNPs) with gastric cancer (GC) risk by genome-wide association study (GWAS) and to explore the pathway enrichment of implicated genes and gene-sets with expression patterns.Materials and Methods The study population was comprised of 1,253 GC cases and 4,827 controls from National Cancer Center and an urban community of the Korean Genome Epidemiology Study and their genotyping was performed. SNPs were annotated, and mapped to genes to prioritize by three mapping approaches by functional mapping and annotation (FUMA). The gene-based analysis and gene-set analysis were conducted with full GWAS summary data using MAGMA. Gene-set pathway enrichment test with those prioritized genes were performed.Results In GWAS, rs2303771, a nonsynonymous variant of <i>KLHDC4</i> gene was top SNP associated significantly with GC (odds ratio, 2.59; p=1.32×10<sup>–83</sup>). In post-GWAS, 71 genes were prioritized. In gene-based GWAS, seven genes were under significant p < 3.80×10<sup>–6</sup> (0.05/13,114); <i>DEFB108B</i> had the lowest p=5.94×10<sup>–15</sup>, followed by <i>FAM86C1</i> (p=1.74×10<sup>–14</sup>), <i>PSCA</i> (p=1.81×10<sup>–14</sup>), and <i>KLHDC4</i> (p=5.00×10<sup>–10</sup>). In gene prioritizing, <i>KLDHC4</i> was the only gene mapped with all three gene-mapping approaches. In pathway enrichment test with prioritized genes, <i>FOLR2, PSCA, LY6K, LYPD2</i>, and <i>LY6E</i> showed strong enrichment related to cellular component of membrane; a post-translation modification by synthesis of glycosylphosphatidylinositol (GPI)-anchored proteins pathway.Conclusion While 37 SNPs were significantly associated with the risk of GC, genes involved in signaling pathways related to purine metabolism and GPI-anchored protein in cell membrane are pinpointed to be playing important role in GC.

Abstract

Purpose We aimed to identify the associated single nucleotide polymorphisms (SNPs) with gastric cancer (GC) risk by genome-wide association study (GWAS) and to explore the pathway enrichment of implicated genes and gene-sets with expression patterns. Materials and Methods The study population was comprised of 1,253 GC cases and 4,827 controls from National Cancer Center and an urban community of the Korean Genome Epidemiology Study and their genotyping was performed. SNPs were annotated, and mapped to genes to prioritize by three mapping approaches by functional mapping and annotation (FUMA). The gene-based analysis and gene-set analysis were conducted with full GWAS summary data using MAGMA. Gene-set pathway enrichment test with those prioritized genes were performed. Results In GWAS, rs2303771, a nonsynonymous variant of KLHDC4 gene was top SNP associated significantly with GC (odds ratio, 2.59; p=1.32×10–83). In post-GWAS, 71 genes were prioritized. In gene-based GWAS, seven genes were under significant p < 3.80×10–6 (0.05/13,114); DEFB108B had the lowest p=5.94×10–15, followed by FAM86C1 (p=1.74×10–14), PSCA (p=1.81×10–14), and KLHDC4 (p=5.00×10–10). In gene prioritizing, KLDHC4 was the only gene mapped with all three gene-mapping approaches. In pathway enrichment test with prioritized genes, FOLR2, PSCA, LY6K, LYPD2, and LY6E showed strong enrichment related to cellular component of membrane; a post-translation modification by synthesis of glycosylphosphatidylinositol (GPI)-anchored proteins pathway. Conclusion While 37 SNPs were significantly associated with the risk of GC, genes involved in signaling pathways related to purine metabolism and GPI-anchored protein in cell membrane are pinpointed to be playing important role in GC.

참고문헌 (39)

  1. Sung H, "Global cancer statistics 2020 : GLOBOCAN esti mates of incidence and mortality worldwide for 36 cancers in 185 countries", CA Cancer J Clin, 71, pp.209~249 (2021)
  2. Hong S, "Cancer statistics in Korea : incidence, mortality, survival, and preva lence in 2018", Cancer Res Treat, 53, pp.301~315 (2021)
  3. Akbari A, "Overview of epidemiological characteristics, clinical features, and risk factors of gastric cancer in Asia-Pacific region", Asia Pac J Clin Oncol, 18, pp.493~505 (2022)
  4. Thrastardottir TO, "The asso ciation between the gut microbiome, nutritional habits, anti biotics, and gastric cancer : a scoping review", Curr Nutr Rep, 11, pp.19~38 (2022)
  5. McLean MH, "Genetics of gastric cancer", Nat Rev Gastroenterol Hepatol, 11, pp.664~674 (2014)
  6. Study Group of Millennium Genome Project for Cancer, "Genetic variation in PSCA is associated with susceptibility to diffuse-type gastric cancer", Nat Genet, 40, pp.730~740 (2008)
  7. Abnet CC, "A shared susceptibility locus in PLCE1 at 10q23 for gastric adenocarcinoma and esophageal squamous cell carcinoma", Nat Genet, 42, pp.764~767 (2010)
  8. Shi Y, "A genome wide association study identifies new susceptibility loci for non-cardia gastric cancer at 3q13. 31 and 5p13. 1", Nat Genet, 43, pp.1215~1218 (2011)
  9. Jin G, "Genetic vari ants at 6p21. 1 and 7p15. 3 are associated with risk of multiple cancers in Han Chinese", Am J Hum Genet, 91, pp.928~934 (2012)
  10. Zhao Y, "A large-scale integrative analysis of GWAS and common meQTLs across whole life course identifies genes, pathways and tissue", cell types for three major psychiatric disorders, 2018, pp.95, 347~352
  11. Zhu Z, "Integration of summary data from GWAS and eQTL stud ies predicts complex trait gene targets", Nat Genet, 48, pp.4817~ (2016)
  12. Welter D, "The NHGRI GWAS Catalog, a curated resource of SNP trait associations", Nucleic Acids Res, 42, pp.D1001~D1006 (2014)
  13. Gallagher MD, "The post-GWAS era : from association to function", Am J Hum Genet, 102, pp.717~730 (2018)
  14. Freedman ML, "Principles for the post-GWAS functional characterization of cancer risk loci", Nat Genet, 43, pp.513~518 (2011)
  15. Reimand J, "Pathway enrichment analysis and visu alization of omics data using g : Profiler, GSEA, Cytoscape and EnrichmentMap", Nat Protoc, 14, pp.482~517 (2019)
  16. Watanabe K, "Func tional mapping and annotation of genetic associations with FUMA", Nat Commun, 8, pp.1826~ (2017)
  17. 1000 Genomes Project Consortium, "A global reference for human genetic variation", Nature, 526, pp.68~74 (2015)
  18. Kircher M, "A general framework for estimating the relative patho genicity of human genetic variants", Nat Genet, 46, pp.310~315 (2014)
  19. Boyle AP, "Annotation of functional variation in per sonal genomes using RegulomeDB", Genome Res, 22, pp.17907~ (2012)
  20. GTEx Consortium, "The GTEx Consortium atlas of genetic reg ulatory effects across human tissues", Science, 369, pp.131830~ (2020)
  21. Ernst J, "ChromHMM : automating chromatin-state discovery and characterization", Nat Methods, 9, pp.215~216 (2012)
  22. The ENCODE Project Consortium, "An integrated encyclope dia of DNA elements in the human genome", Nature, 489, pp.57~74 (2012)
  23. Roadmap Epigenomics Consortium, "Integrative analysis of 111reference human epigenomes", Nature, 518, pp.317~330 (2015)
  24. Schmiedel BJ, "Impact of genetic pol ymorphisms on human immune cell gene expression", Cell, 175, pp.1701~1715 (2018)
  25. "Unraveling the polygenic architecture of com plex traits using blood eQTL metaanalysis" (2018)[URL]
  26. de Leeuw CA, "MAGMA : generalized gene-set analysis of GWAS data", PLoS Comput Biol, 11, pp.e1004219~ (2015)
  27. Park B, "Genome-wide association of genetic variation in the PSCA gene with gastric cancer susceptibility in a Korean popula tion", Cancer Res Treat, 51, pp.748~757 (2019)
  28. Kim YD, "Risk of gastric cancer is associated with PRKAA1 gene poly morphisms in Koreans", World J Gastroenterol, 20, pp.8592~8598 (2014)
  29. Song HR, "Common genetic variants at 1q22 and 10q23 and gastric cancer susceptibility in a Korean population", Tumour Biol, 35, pp.3133~3137 (2014)
  30. Hwang JY, "Reca pitulation of previous genome-wide association studies with two distinct pathophysiological entities of gastric cancer in the Korean population", J Hum Genet, 58, pp.233~235 (2013)
  31. Cai M, "Environmental factors, seven GWAS-identified susceptibility loci, and risk of gastric cancer and its precursors in a Chinese population", Cancer Med, 6, pp.708~720 (2017)
  32. Qiu L, "Predictive model for risk of gastric cancer using genetic variants from genome-wide association studies and high-evidence meta analysis", Cancer Med, 9, pp.7310~7316 (2020)
  33. Mayor S, "Sorting GPI-anchored proteins", Nat Rev Mol Cell Biol, 5, pp.110~120 (2004)
  34. Lv Y, "Overexpres sion of lymphocyte antigen 6 complex, locus E in gastric can cer promotes cancer cell growth and metastasis", Cell Physiol Biochem, 45, pp.1219~1229 (2018)
  35. Yeom CJ, "LY6E : a conductor of malignant tumor growth through modulation of the PTEN", PI3K, HIF-1 axis, pp.Oncotarget, 2016[DOI]
  36. Li E, "PSCA promotes prostate cancer proliferation and cell-cycle progression by up-regulating c-Myc", Prostate, 77, pp.1563~1572 (2017)
  37. Craig SE, "Cancer cells cut homophilic cell adhesion molecules and run", Cancer Res, 71, pp.303~309 (2011)
  38. Niu XM, "Acetylcholine receptor pathway in lung cancer : New twists to an old story", World J Clin Oncol, 5, pp.667~676 (2014)
  39. Cheng K, "Acetylcholine release by human colon cancer cells medi ates autocrine stimulation of cell proliferation", Am J Physiol Gastrointest Liver Physiol, 295, pp.G591~G597 (2008)

관련 논문AI추천

이 간행물의 다른 논문 (30건)