Tetraspanin family identified as the central genes detected in gastric cancer using bioinformatics analysis

Qi,Weiwei; Sun,Libin; Liu,Ning; Zhao,Shufen; Lv,Jing; Qiu,Wensheng

doi:10.3892/mmr.2018.9360

Tetraspanin family identified as the central genes detected in gastric cancer using bioinformatics analysis

Authors:
- Weiwei Qi
- Libin Sun
- Ning Liu
- Shufen Zhao
- Jing Lv
- Wensheng Qiu
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Affiliations: Department of Oncology and Chemotherapy, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266031, P.R. China, Department of Tumor Combined Therapy, The Affiliated Hospital of Qingdao University, Qingdao, Shandong 266031, P.R. China
Published online on: August 8, 2018 https://doi.org/10.3892/mmr.2018.9360
Pages: 3599-3610
Copyright: © Qi et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Gastric cancer has become a serious disease in the past decade. It has the second highest mortality rate among the four most common cancer types, leading to ~700,000 mortalities annually. Previous studies have attempted to elucidate the underlying biological mechanisms of gastric cancer. The present study aimed to obtain useful biomarkers and to improve the understanding of gastric cancer mechanisms at the genetic level. The present study used bioinformatics analysis to identify 1,829 differentially expressed genes (DEGs) which were obtained from the GSE54129 dataset. Using protein‑protein interaction information from the Search Tool for the Retrieval of Interacting Genes database, disease modules were constructed for gastric cancer using Cytoscape software. In the Gene Ontology analysis of biology processes, upregulated genes were significantly enriched in ‘extracellular matrix organization’, ‘cell adhesion’ and ‘inflammatory response’, whereas downregulated DEGs were significantly enriched in ‘xenobiotic metabolic process’, ‘oxidation‑reduction process’ and ‘steroid metabolic process’. During Kyoto Encyclopedia of Genes and Genomes analysis, upregulated DEGs were significantly enriched in ‘extracellular matrix‑receptor interaction’, ‘focal adhesion’ and ‘PI3K‑Akt signaling pathway’, whereas the downregulated DEGs were significantly enriched in ‘chemical carcinogenesis’, ‘metabolism of xenobiotics by cytochrome P450’ and ‘peroxisome’. The present study additionally identified 10 hub genes from the DEGs: Tumor protein p53 (TP53), C‑X‑C motif chemokine ligand 8 (CXCL8), tetraspanin 4 (TSPAN4), lysophosphatidic acid receptor 2 (LPAR2), adenylate cyclase 3 (ADCY3), phosphoinositide‑3‑kinase regulatory subunit 1 (PIK3R1), neuromedin U (NMU), C‑X‑C motif chemokine ligand (CXCL12), fos proto‑oncogene, AP‑1 transcription factor subunit (FOS) and sphingosine‑1‑phosphate receptor 1 (S1PR1), which have high degrees with other DEGs. The survival analysis revealed that the high expression of ADCY3, LPAR2, S1PR1, TP53 and TSPAN4 was associated with a lower survival rate, whereas high expression of CXCL8, FOS, NMU and PIK3R1 was associated with a higher survival rate. No significant association was identified between CXCL12 and survival rate. Additionally, TSPAN1 and TSPAN8 appeared in the top 100 DEGs. Finally, it was observed that 4 hub genes were highly expressed in gastric cancer tissue compared with para‑carcinoma tissue in the 12 patients; the increased TSPAN4 was significant (>5‑fold). Tetraspanin family genes may be novel biomarkers of gastric cancer. The findings of the present study may improve the understanding of the molecular mechanisms underlying the development of gastric cancer.

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1	Crew KD and Neugut AI: Epidemiology of gastric cancer. World J Gastroenterol. 12:354–362. 2006. View Article : Google Scholar : PubMed/NCBI
2	Parkin DM, Bray F, Ferlay J and Pisani P: Global cancer statistics, 2002. CA Cancer J Clin. 55:74–108. 2005. View Article : Google Scholar : PubMed/NCBI
3	World Health Organization (WHO), . GLOBOCAN 2012: Estimated Cancer Incidence, Mortality and Prevalence Worldwide in 2012. WHO; Geneva: 2012, http://globocan.iarc.fr/Pages/fact_sheets_cancer.aspx
4	Liu P, Wang X, Hu CH and Hu TH: Bioinformatics analysis with graph-based clustering to detect gastric cancer-related pathways. Genet Mol Res. 11:3497–3504. 2012. View Article : Google Scholar : PubMed/NCBI
5	Tian J, Wang XD and Chen ZC: Survival of patients with stomach cancer in Changle city of China. World J Gastroenterol. 10:1543–1546. 2004. View Article : Google Scholar : PubMed/NCBI
6	Wagner AD, Grothe W, Haerting J, Kleber G, Grothey A and Fleig WE: Chemotherapy in advanced gastric cancer: A systematic review and meta-analysis based on aggregate data. J Clin Oncol. 24:2903–2909. 2006. View Article : Google Scholar : PubMed/NCBI
7	Bejjani BA and Shaffer LG: Clinical utility of contemporary molecular cytogenetics. Annu Rev Genomics Hum Genet. 9:71–86. 2008. View Article : Google Scholar : PubMed/NCBI
8	Arocho A, Chen B, Ladanyi M and Pan Q: Validation of the 2-DeltaDeltaCt calculation as an alternate method of data analysis for quantitative PCR of BCR-ABL P210 transcripts. Diagn Mol Pathol. 15:56–61. 2006. View Article : Google Scholar : PubMed/NCBI
9	Gautier L, Cope L, Bolstad BM and Irizarry RA: affy-analysis of Affymetrix GeneChip data at the probe level. Bioinformatics. 20:307–315. 2004. View Article : Google Scholar : PubMed/NCBI
10	Phipson B, Lee S, Majewski IJ, Alexander WS and Smyth GK: Robust hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression. Ann Appl Stat:. 10:946–963. 2016. View Article : Google Scholar : PubMed/NCBI
11	Warnes GR, Bolker B, Bonebakker L, Gentleman R, Andy Liaw WH, Lumley T, Maechler M, Magnusson A, Moeller S, Schwartz M and Venables B: gplots: Various R Programming Tools for Plotting Data. https://cran.r-project.org/web/packages/gplots/index.htmlMarch 30–2016
12	Kanehisa M: The KEGG database. Novartis Found Symp. 247:91–101; discussion 101–103, 119–128. 244–252. 2002. View Article : Google Scholar : PubMed/NCBI
13	Martucci D, Masseroli M and Pinciroli F: Gene ontology application to genomic functional annotation, statistical analysis and knowledge mining. Stud Health Technol Inform. 102:108–131. 2004.PubMed/NCBI
14	Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC and Lempicki RA: DAVID: Database for annotation, visualization, and integrated discovery. Genome Biol. 4:P32003. View Article : Google Scholar : PubMed/NCBI
15	Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, et al: STRING v10: Protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 43(Database Issue): D447–D452. 2015. View Article : Google Scholar : PubMed/NCBI
16	Szász AM, Lánczky A, Nagy Á, Förster S, Hark K, Green JE, Boussioutas A, Busuttil R, Szabó A and Győrffy B: Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients. Oncotarget. 7:49322–49333. 2016. View Article : Google Scholar : PubMed/NCBI
17	Ferro A, Peleteiro B, Malvezzi M, Bosetti C, Bertuccio P, Levi F, Negri E, La Vecchia C and Lunet N: Worldwide trends in gastric cancer mortality (1980–2011), with predictions to 2015, and incidence by subtype. Eur J Cancer. 50:1330–1344. 2014. View Article : Google Scholar : PubMed/NCBI
18	Yang S, Shin J, Park KH, Jeung HC, Rha SY, Noh SH, Yang WI and Chung HC: Molecular basis of the differences between normal and tumor tissues of gastric cancer. Biochim Biophys Acta. 1772:1033–1040. 2007. View Article : Google Scholar : PubMed/NCBI
19	Zhao Z, Song Y, Piao D, Liu T and Zhao L: Identification of genes and long non-coding RNAs associated with the pathogenesis of gastric cancer. Oncol Rep. 34:1301–1310. 2015. View Article : Google Scholar : PubMed/NCBI
20	Guo LL, He ZC, Yang CQ, Qiao PT and Yin GL: Epigenetic silencing of olfactomedin-4 enhances gastric cancer cell invasion via activation of focal adhesion kinase signaling. BMB Rep. 48:630–635. 2015. View Article : Google Scholar : PubMed/NCBI
21	Nam KH, Lee BL, Park JH, Kim J, Han N, Lee HE, Kim MA, Lee HS and Kim WH: Caveolin 1 expression correlates with poor prognosis and focal adhesion kinase expression in gastric cancer. Pathobiology. 80:87–94. 2013. View Article : Google Scholar : PubMed/NCBI
22	Hao NB, Tang B, Wang GZ, Xie R, Hu CJ, Wang SM, Wu YY, Liu E, Xie X and Yang SM: Hepatocyte growth factor (HGF) upregulates heparanase expression via the PI3K/Akt/NF-κB signaling pathway for gastric cancer metastasis. Cancer Lett. 361:57–66. 2015. View Article : Google Scholar : PubMed/NCBI
23	Cho SJ, Kook MC, Lee JH, Shin JY, Park J, Bae YK, Choi IJ, Ryu KW and Kim YW: Peroxisome proliferator-activated receptor γ upregulates galectin-9 and predicts prognosis in intestinal-type gastric cancer. Int J Cancer. 136:810–820. 2015. View Article : Google Scholar : PubMed/NCBI
24	Choi JM, Park WS, Song KY, Lee HJ and Jung BH: Development of simultaneous analysis of tryptophan metabolites in serum and gastric juice-an investigation towards establishing a biomarker test for gastric cancer diagnosis. Biomed Chromatogr. 30:1963–1974. 2016. View Article : Google Scholar : PubMed/NCBI
25	Leung WK, Wu KC, Wong CY, Cheng AS, Ching AK, Chan AW, Chong WW, Go MY, Yu J, To KF, et al: Transgenic cyclooxygenase-2 expression and high salt enhanced susceptibility to chemical-induced gastric cancer development in mice. Carcinogenesis. 29:1648–1654. 2008. View Article : Google Scholar : PubMed/NCBI
26	Kim HS, Kwack SJ and Lee BM: Alteration of cytochrome P-450 and glutathione S-transferase activity in normal and malignant human stomach. J Toxicol Environ Health A. 68:1611–1620. 2005. View Article : Google Scholar : PubMed/NCBI
27	Song H, Peng JS, Yao DS, Liu DL, Yang ZL, Du YP and Xiang J: Metabolic disorders of fatty acids and fatty acid amides associated with human gastric cancer morbidity. Chin Med J (Engl). 125:757–763. 2012.PubMed/NCBI
28	Li C, Qiu W, Yang Z, Luo J, Yang F, Liu M, Xie J and Tang J: Stereoselective synthesis of some methyl-substituted steroid hormones and their in vitro cytotoxic activity against human gastric cancer cell line MGC-803. Steroids. 75:859–869. 2010. View Article : Google Scholar : PubMed/NCBI
29	Nicolai S, Rossi A, Di Daniele N, Melino G, Annicchiarico-Petruzzelli M and Raschellà G: DNA repair and aging: The impact of the p53 family. Aging (Albany NY). 7:1050–1065. 2015. View Article : Google Scholar : PubMed/NCBI
30	Rufini A, Tucci P, Celardo I and Melino G: Senescence and aging: The critical roles of p53. Oncogene. 32:5129–5143. 2013. View Article : Google Scholar : PubMed/NCBI
31	Wawryk-Gawda E, Chylińska-Wrzos P, Lis-Sochocka M, Chłapek K, Bulak K, Jędrych M and Jodłowska-Jędrych B: P53 protein in proliferation, repair and apoptosis of cells. Protoplasma. 251:525–533. 2014. View Article : Google Scholar : PubMed/NCBI
32	Yuan L, Zhang Y, Xia J, Liu B, Zhang Q, Liu J, Luo L, Peng Z, Song Z and Zhu R: Resveratrol induces cell cycle arrest via a p53-independent pathway in A549 cells. Mol Med Rep. 11:2459–2464. 2015. View Article : Google Scholar : PubMed/NCBI
33	Ando K, Oki E, Zhao Y, Ikawa-Yoshida A, Kitao H, Saeki H, Kimura Y, Ida S, Morita M, Kusumoto T and Maehara Y: Mortalin is a prognostic factor of gastric cancer with normal p53 function. Gastric Cancer. 17:255–262. 2014. View Article : Google Scholar : PubMed/NCBI
34	Uchi R, Kogo R, Kawahara K, Sudo T, Yokobori T, Eguchi H, Sugimachi K, Maehama T, Mori M, Suzuki A, et al: PICT1 regulates TP53 via RPL11 and is involved in gastric cancer progression. Br J Cancer. 109:2199–2206. 2013. View Article : Google Scholar : PubMed/NCBI
35	Busuttil RA, Zapparoli GV, Haupt S, Fennell C, Wong SQ, Pang JM, Takeno EA, Mitchell C, Di Costanzo N, Fox S, et al: Role of p53 in the progression of gastric cancer. Oncotarget. 5:12016–12026. 2014. View Article : Google Scholar : PubMed/NCBI
36	Yang D, Yang W, Zhang Q, Hu Y, Bao L and Damirin A: Migration of gastric cancer cells in response to lysophosphatidic acid is mediated by LPA receptor 2. Oncol Lett. 5:1048–1052. 2013. View Article : Google Scholar : PubMed/NCBI
37	Hong SH, Goh SH, Lee SJ, Hwang JA, Lee J, Choi IJ, Seo H, Park JH, Suzuki H, Yamamoto E, et al: Upregulation of adenylate cyclase 3 (ADCY3) increases the tumorigenic potential of cells by activating the CREB pathway. Oncotarget. 4:1791–1803. 2013. View Article : Google Scholar : PubMed/NCBI
38	Luo Y, Zhang C, Tang F, Zhao J, Shen C, Wang C, Yu P, Wang M, Li Y, Di JI, et al: Bioinformatics identification of potentially involved microRNAs in Tibetan with gastric cancer based on microRNA profiling. Cancer Cell Int. 15:1152015. View Article : Google Scholar : PubMed/NCBI
39	Wang C, Mao J, Redfield S, Mo Y, Lage JM and Zhou X: Systemic distribution, subcellular localization and differential expression of sphingosine-1-phosphate receptors in benign and malignant human tissues. Exp Mol Pathol. 97:259–265. 2014. View Article : Google Scholar : PubMed/NCBI
40	Chen L, Li X, Wang GL, Wang Y, Zhu YY and Zhu J: Clinicopathological significance of overexpression of TSPAN1, K167 and CD34 in gastric carcinoma. Tumori. 94:531–538. 2008. View Article : Google Scholar : PubMed/NCBI
41	Lu Z, Luo T, Nie M, Pang T, Zhang X, Shen X, Ma L, Bi J, Wei G, Fang G and Xue X: TSPAN1 functions as an oncogene in gastric cancer and is downregulated by miR-573. FEBS Lett. 589:1988–1994. 2015. View Article : Google Scholar : PubMed/NCBI
42	Anami K, Oue N, Noguchi T, Sakamoto N, Sentani K, Hayashi T, Naito Y, Oo HZ and Yasui W: TSPAN8, identified by Escherichia coli ampicillin secretion trap, is associated with cell growth and invasion in gastric cancer. Gastric Cancer. 19:370–380. 2016. View Article : Google Scholar : PubMed/NCBI
43	Wei L, Li Y and Suo Z: TSPAN8 promotes gastric cancer growth and metastasis via ERK MAPK pathway. Int J Clin Exp Med. 8:8599–8607. 2015.PubMed/NCBI
44	Fu Y, Zhang Q, Kang C, Zhang J, Zhang K, Pu P, Wang G and Wang T: Inhibitory effects of adenovirus mediated Akt1 and PIK3R1 shRNA on the growth of malignant tumor cells in vitro and in vivo. Cancer Biol Ther. 8:1002–1009. 2009. View Article : Google Scholar : PubMed/NCBI
45	Yamashita K, Upadhyay S, Osada M, Hoque MO, Xiao Y, Mori M, Sato F, Meltzer SJ and Sidransky D: Pharmacologic unmasking of epigenetically silenced tumor suppressor genes in esophageal squamous cell carcinoma. Cancer Cell. 2:485–495. 2002. View Article : Google Scholar : PubMed/NCBI
46	Przygodzka P, Papiewska-Pajak I, Bogusz H, Kryczka J, Sobierajska K, Kowalska MA and Boncela J: Neuromedin U is upregulated by Snail at early stages of EMT in HT29 colon cancer cells. Biochim Biophys Acta. 1860:2445–2453. 2016. View Article : Google Scholar : PubMed/NCBI
47	Huang Q, Lan F, Wang X, Yu Y, Ouyang X, Zheng F, Han J, Lin Y, Xie Y, Xie F, et al: IL-1β-induced activation of p38 promotes metastasis in gastric adenocarcinoma via upregulation of AP-1/c-fos, MMP2 and MMP9. Mol Cancer. 13:182014. View Article : Google Scholar : PubMed/NCBI
48	Verbeke H, Geboes K, Van Damme J and Struyf S: The role of CXC chemokines in the transition of chronic inflammation to esophageal and gastric cancer. Biochim Biophys Acta. 1825:117–129. 2012.PubMed/NCBI
49	Izumi D, Ishimoto T, Miyake K, Sugihara H, Eto K, Sawayama H, Yasuda T, Kiyozumi Y, Kaida T, Kurashige J, et al: CXCL12/CXCR4 activation by cancer-associated fibroblasts promotes integrin β1 clustering and invasiveness in gastric cancer. Int J Cancer. 138:1207–1219. 2016. View Article : Google Scholar : PubMed/NCBI