Screening differential genes and prognostic analysis of gastric cancer based on TCGA database

doi:10.3760/cma.j.cn371439-20190923-00004

Abstract

Abstract:

Objective To extract the genes associated with prognosis from the differential expressed genes in gastric cancer tissues by using a large number of gastric cancer genome data in the cancer genome atlas (TCGA) database. Methods Gene expression data of gastric adenocarcinoma were downloaded from TCGA database. After R language data preprocessing, edgeR was used to analyze the gene differential expression, and R language was used to identify the significant gene ontology (GO) terms and KEGG pathways in gene differential expression. Multivariate Cox stepwise regression analysis was used to predict the genes that affected survival. Genes obtained above were used for survival analysis online in Kaplan-Meier Plotter website (http://Kaplan-Meier Plotter.com). Results A total of 305 gastric cancer and 30 normal gastric tissues were retrieved in TCGA database, and 3 231 differential genes were screened out, including 2 005 up-regulated genes and 1 226 down-regulated genes. These genes were enriched in GO terms including antigen binding, serine hydrolase activity, receptor ligands activity, serine peptidase activity, serine type endopeptidase activity, glycosaminoglycans binding, cytokine activity, hormone activity, peptidase inhibitor activity, metallopeptidase activity and so on. The genes in KEGG pathway analysis were enriched in chemical carcinogen, neuractive receptor-ligand interaction, cytokine-cytokine receptor interaction, metabolism of xenobiotics by cytochrome P450, protein digestion and absorption, staphylococcus aureus infection, retinol metabolism, drug metabolism P450, steroid hormone metabolism, pancreatic secretion and so on. Cox analysis showed that GPX3 and SERPINE1 had significant effect on the survival of gastric cancer patients. Receiver operating characteristic curve analysis showed that the expressions of GPX3 and SERPINE1 had a certain predictive value for the survival time of gastric cancer patients, when the critical values of GPX3 and SERPINE1 were 0.46 and 0.68 respectively, the sensitivity was 60.35%, the specificity was 82.06%, and the area under the curve was 0.763 (95%CI: 0.828-0.936). Kaplan-Meier analysis showed that the high expressions of GPX3 (P<0.001) and SERPINE1 (P=0.001) were significantly related to the poor prognosis of gastric adenocarcinoma. Conclusion The higher expression of SERPINE1 and GPX3 genes, the shorter survival time of gastric cancer patients. They may be the targets for predicting the prognosis of gastric cancer.

Key words: Stomach neoplasms, Proto-oncogenes, Prognosis, Gene ontology

Zou Wenjing, He Shuixiang, Liu Dan, Li Xu. Screening differential genes and prognostic analysis of gastric cancer based on TCGA database[J]. Journal of International Oncology, 2020, 47(4): 211-216.

Figures/Tables 6

References 20

[1]	Zhang Y, Chen W, Wang H , et al. Upregulation of miR-519 enhances radiosensitivity of esophageal squamous cell carcinoma trough targeting PI3K/AKT/mTOR signaling pathway[J]. Cancer Chemother Pharmacol, 2019,84(6):1209-1218. DOI: 10.1007/s00280-019-03922-2. doi: 10.1007/s00280-019-03922-2
[2]	Orditura M, Galizia G, Sforza V , et al. Treatment of gastric cancer[J]. World J Gastroenterol, 2014,20(7):1635-1649. DOI: 10.3748/wjg.v20.i7.1635. doi: 10.3748/wjg.v20.i7.1635
[3]	万晶晶 . 胃癌病因学的研究进展[J]. 医学综述, 2014,20(14):2542-2544. DOI: 10.3969/j.issn.1006-2084.2014.14.018.
[4]	Karimi P, Islami F, Anandasabapathy S , et al. Gastric cancer: descriptive epidemiology, risk factors, screening, and prevention[J]. Cancer Epidemiol Biomarkers Prev, 2014,23(5):700-713. DOI: 10.1158/1055-9965.EPI-13-1057. doi: 10.1158/1055-9965.EPI-13-1057
[5]	Cho YE, Yu LR, Abdelmegeed MA , et al. Apoptosis of enterocytes and nitration of junctional complex proteins promote alcohol-induced gut leakiness and liver injury[J]. J Hepatol, 2018,69(1):142-153. DOI: 10.1016/j.jhep.2018.02.005. doi: 10.1016/j.jhep.2018.02.005
[6]	Zhou C, Pan R, Li B , et al. GPX3 hypermethylation in gastric cancer and its prognostic value in patients aged over 60[J]. Future Oncol, 2019,15(11):1279-1289. DOI: 10.2217/fon-2018-0674. doi: 10.2217/fon-2018-0674
[7]	Vignon C, Georget MT, Levern Y , et al. Bone marrow mesenchymal stromal cells regulate the metabolism of H(2)O(2) in human leukemic cells[J]. Blood, 2010,116(21). DOI: 10.1182/blood.V116.21.1058.1058.
[8]	Zhu X, Wang J, Li L , et al. GPX3 suppresses tumor migration and invasion via the FAK/AKT pathway in esophageal squamous cell carcinoma[J]. Am J Transl Res, 2018,10(6):1908-1920.
[9]	Lin Y, Zhang Y, Chen Y , et al. Promoter methylation and clinical significance of GPX3 in esophageal squamous cell carcinoma[J]. Pathol Res Pract, 2019,215(11):152676. DOI: 10.1016/j.prp.2019.152676. doi: 10.1016/j.prp.2019.152676
[10]	Shaaban Y, Taalab MM, Aref S , et al. The clinical significance of decreased GPX3 expression level in Egyptian AML patients[J]. Clin Lymphoma Myeloma Leuk, 2019,19:S205. DOI: 10.1016/j.clml.2019.07.064.
[11]	Liu Q, Bai W, Huang F , et al. Downregulation of microRNA-196a inhibits stem cell self-renewal ability and stemness in non-small-cell lung cancer through upregulating GPX3 expression[J]. Int J Biochem Cell Biol, 2019,115:105571. DOI: 10.1016/j.biocel.2019.105571. doi: 10.1016/j.biocel.2019.105571
[12]	Worley BL, Kim YS, Mardini J , et al. GPx3 supports ovarian cancer progression by manipulating the extracellular redox environment[J]. Redox Biol, 2019,25:101051. DOI: 10.1016/j.redox.2018.11.009. doi: 10.1016/j.redox.2018.11.009
[13]	Xu B, Bai Z, Yin J , et al. Global transcriptomic analysis identifies SERPINE1 as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer[J]. Peer J, 2019,7:e7091. DOI: 10.7717/peerj.7091. doi: 10.7717/peerj.7091
[14]	Couto PP, Bastos-Rodrigues L, Schayek H , et al. Spectrum of germline mutations in smokers and nonsmokers in Brazilian nonsmall-cell lung cancer (NSCLC) patients[J]. Carcinogenesis, 2017,38(11):1112-1118. DOI: 10.1093/carcin/bgx089. doi: 10.1093/carcin/bgx089
[15]	Zeng C, Chen Y . HTR1D, TIMP1, SERPINE1, MMP3 and CNR2 affect the survival of patients with colon adenocarcinoma[J]. Oncol Lett, 2019,18(3):2448-2454. DOI: 10.3892/ol.2019.10545.
[16]	Vachher M, Arora K, Burman A , et al. NAMPT, GRN, and SERPINE1 signature as predictor of disease progression and survival in gliomas[J]. J Cell Biochem, 2020,121(4):3010-3023. DOI: 10.1002/jcb.29560. doi: 10.1002/jcb.v121.4
[17]	Li M, Zhao H, Zhao SG , et al. The HMGA2-IMP2 pathway promotes granulosa cell proliferation in polycystic ovary syndrome[J]. 2019,104(4):1049-1059. DOI: 10.1210/jc.2018-00544.
[18]	沈苗, 钟兴伟 . SERPINE1基因在胃癌中的表达及临床意义[J]. 世界华人消化杂志, 2018,26(31):1818-1824. DOI: 10.11569/wcjd.v26.i31.1818.
[19]	Wu DM, Wang S, Wen X, et al. MircoRNA-1275 promotes proliferation, invasion and migration of glioma cells via SERPINE1[J]. J Cell Mol Med, 2018,22(10):4963-4974. DOI: 10.1111/jcmm.13760. doi: 10.1111/jcmm.13760
[20]	Sang Y, Chen MY, Luo D , et al. TEL2 suppresses metastasis by down-regulating SERPINE1 in nasopharyngeal carcinoma[J]. Oncotarget, 2015,6(30):29240-29253. DOI: 10.18632/oncotarget.5074. doi: 10.18632/oncotarget.v6i30