TRIM58/cg26157385 methylation is associated with eight prognostic genes in lung squamous cell carcinoma

Zhang,Weimin; Cui,Qichen; Qu,Weifeng; Ding,Xiaoyun; Jiang,Donglin; Liu,Hongcheng

doi:10.3892/or.2018.6426

TRIM58/cg26157385 methylation is associated with eight prognostic genes in lung squamous cell carcinoma

Authors:
- Weimin Zhang
- Qichen Cui
- Weifeng Qu
- Xiaoyun Ding
- Donglin Jiang
- Hongcheng Liu
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Affiliations: Department of Thoracic Surgery, The Third Affiliated Hospital of Nantong University, Wuxi, Jiangsu 214000, P.R. China, Department of Central Laboratory, The Third Affiliated Hospital of Nantong University, Wuxi, Jiangsu 214000, P.R. China, Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Shanghai 200000, P.R. China
Published online on: May 8, 2018 https://doi.org/10.3892/or.2018.6426
Pages: 206-216
Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The present study aimed to analyze the differentially expressed genes related to the tripartite motif containing 58 (TRIM58)/cg26157385 methylation sites, and consequently to provide theoretical basis for elucidating the influence of TRIM58/cg26157385 methylation on lung cancer prognosis. Methylation‑sequencing information, mRNA expression profiling data and clinical data were downloaded from cBioPortal database to screen out candidate genes related to the methylation of TRIM58/cg26157385 in squamous cell lung carcinoma. The differentially expressed genes related to TRIM58 methylation were extracted form both training dataset and validation dataset. Cox regression analysis, risk scoring system construction, correlation analysis between the expression value of genes and clinical information were conducted to reveal TRIM58 methylation‑related factors. Additionally, GO function analysis and KEGG pathway enrichment analysis were performed. Based on their expression level and the corresponding survival information for 347 out of 370 samples with squamous cell lung carcinoma, 183 genes significantly associated with prognosis were gained, and the top 8 ones, including alpha‑2‑macroglobulin‑like 1 (A2ML1), cyclin‑E1 (CCNE1), COBL, establishment of sister chromatid cohesion N‑acetyltransferase 2 (ESCO2), G protein‑coupled receptor 115 (GPR115), matrix metalloproteinases 10 (MMP10), OVO homologue‑like 1 (OVOL1) and secretoglobin family 1A member 1 (SCGB1A1), were candidate signature genes significantly correlated with TRIM58 methylation. Furthermore, targeted therapy was significantly correlated with prognosis. Functional enrichment analysis demonstrated that the proliferation and differentiation of epidermal cells in lung squamous cell carcinoma patients were abnormal and the homeostasis was disturbed. Eight genes, including A2ML1, CCNE1, COBL, ESCO2, GPR115, MMP10, OVOL1 and SCGB1A1, were significantly related to TRIM58 methylation and treatment of lung squamous cell carcinoma, and may be used as potential prognostic biomarkers. The present study would help to elucidate the influence of TRIM58/cg26157385 methylation on lung cancer prognosis.

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1	Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ and He J: Cancer statistics in China, 2015. CA Cancer J Clin. 66:115–132. 2016. View Article : Google Scholar : PubMed/NCBI
2	Siegel RL, Miller KD and Jemal A: Cancer statistics, 2016. CA Cancer J Clin. 66:7–30. 2016. View Article : Google Scholar : PubMed/NCBI
3	Wistuba II, Behrens C, Milchgrub S, Bryant D, Hung J, Minna JD and Gazdar AF: Sequential molecular abnormalities are involved in the multistage development of squamous cell lung carcinoma. Oncogene. 18:643–650. 1999. View Article : Google Scholar : PubMed/NCBI
4	Cancer Genome Atlas Research Network: Comprehensive genomic characterization of squamous cell lung cancers. Nature. 489:519–525. 2012. View Article : Google Scholar : PubMed/NCBI
5	Imoto I, Izumi H, Yokoi S, Hosoda H, Shibata T, Hosoda F, Ohki M, Hirohashi S and Inazawa J: Frequent silencing of the candidate tumor suppressor PCDH20 by epigenetic mechanism in non-small-cell lung cancers. Cancer Res. 66:4617–4626. 2006. View Article : Google Scholar : PubMed/NCBI
6	Izumi H, Inoue J, Yokoi S, Hosoda H, Shibata T, Sunamori M, Hirohashi S, Inazawa J and Imoto I: Frequent silencing of DBC1 is by genetic or epigenetic mechanisms in non-small cell lung cancers. Hum Mol Genet. 14:997–1007. 2005. View Article : Google Scholar : PubMed/NCBI
7	Kajiura K, Masuda K, Naruto T, Kohmoto T, Watabnabe M, Tsuboi M, Takizawa H, Kondo K, Tangoku A and Imoto I: Frequent silencing of the candidate tumor suppressor TRIM58 by promoter methylation in early-stage lung adenocarcinoma. Oncotarget. 8:2890–2905. 2017. View Article : Google Scholar : PubMed/NCBI
8	Napolitano LM and Meroni G: TRIM family: Pleiotropy and diversification through homomultimer and heteromultimer formation. IUBMB Life. 64:64–71. 2012. View Article : Google Scholar : PubMed/NCBI
9	Nisole S, Saieb SA and Saïb A: TRIM family proteins: Retroviral restriction and antiviral defence. Nat Rev Microbiol. 3:799–808. 2005. View Article : Google Scholar : PubMed/NCBI
10	Qiu X, Huang Y, Zhou Y and Zheng F: Aberrant methylation of TRIM58 in hepatocellular carcinoma and its potential clinical implication. Oncol Rep. 36:811–818. 2016. View Article : Google Scholar : PubMed/NCBI
11	Thom CS, Traxler EA, Khandros E, Nickas JM, Zhou OY, Lazarus JE, Silva AP, Prabhu D, Yao Y, Aribeana C, et al: Trim58 degrades dynein and regulates terminal erythropoiesis. Dev Cell. 30:688–700. 2014. View Article : Google Scholar : PubMed/NCBI
12	White DE, Rafalskametcalf IU, Ivanov AV, Corsinotti A, Peng H, Lee SC, Trono D, Janicki SM and Rauscher FJ III: The ATM substrate KAP1 controls DNA repair in heterochromatin: Regulation by HP1 proteins and Serine 473/824 phosphorylation. Mol Cancer Res. 10:401–414. 2012. View Article : Google Scholar : PubMed/NCBI
13	Wang X, Zhu H, Snieder H, Su S, Munn D, Harshfield G, Maria BL, Dong Y, Treiber F, Gutin B and Shi H: Obesity related methylation changes in DNA of peripheral blood leukocytes. BMC Med. 8:872010. View Article : Google Scholar : PubMed/NCBI
14	Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W and Smyth GK: limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43:e472015. View Article : Google Scholar : PubMed/NCBI
15	Bao ZS, Li MY, Wang JY, Zhang CB, Wang HJ, Yan W, Liu YW, Zhang W, Chen L and Jiang T: Prognostic value of a nine-gene signature in glioma patients based on mRNA expression profiling. CNS Neurosci Ther. 20:112–118. 2014. View Article : Google Scholar : PubMed/NCBI
16	Cheng W, Ren X, Cai J, Zhang C, Li M, Wang K, Liu Y, Han S and Wu A: A five-miRNA signature with prognostic and predictive value for MGMT promoter-methylated glioblastoma patients. Oncotarget. 6:29285–29295. 2015. View Article : Google Scholar : PubMed/NCBI
17	Zhang CB, Zhu P, Yang P, Cai JQ, Wang ZL, Li QB, Bao ZS, Zhang W and Jiang T: Identification of high risk anaplastic gliomas by a diagnostic and prognostic signature derived from mRNA expression profiling. Oncotarget. 6:36643–36651. 2015.PubMed/NCBI
18	Yu G, Wang LG, Han Y and He QY: clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS. 16:284–287. 2012. View Article : Google Scholar : PubMed/NCBI
19	International Cancer Genome Consortium, . Hudson TJ, Anderson W, Artez A, Barker AD, Bell C, Bernabé RR, Bhan MK, Calvo F, Eerola I, et al: International network of cancer genome projects. Nature. 464:993–998. 2010. View Article : Google Scholar : PubMed/NCBI
20	Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, Sun Y, Jacobsen A, Sinha R, Larsson E, et al: Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 6:pl12013. View Article : Google Scholar : PubMed/NCBI
21	Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, Jacobsen A, Byrne CJ, Heuer ML, Larsson E, et al: The cBio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2:401–404. 2012. View Article : Google Scholar : PubMed/NCBI
22	Okada A, Tomasetto C, Lutz Y, Bellocq JP, Rio MC and Basset P: Expression of matrix metalloproteinases during rat skin wound healing: Evidence that membrane type-1 matrix metalloproteinase is a stromal activator of pro-gelatinase A. J Cell Biol. 137:67–77. 1997. View Article : Google Scholar : PubMed/NCBI
23	Vaalamo M, Karjalainen-Lindsberg ML, Puolakkainen P, Kere J and Saarialhokere U: Distinct expression profiles of stromelysin-2 (MMP-10), collagenase-3 (MMP-13), macrophage metalloelastase (MMP-12), and tissue inhibitor of metalloproteinases-3 (TIMP-3) in intestinal ulcerations. Am J Pathol. 152:1005–1014. 1998.PubMed/NCBI
24	Yen CY, Chen CH, Chang CH, Tseng HF, Liu SY, Chuang LY, Wen CH and Chang HW: Matrix metalloproteinases (MMP) 1 and MMP10 but not MMP12 are potential oral cancer markers. Biomarkers. 14:244–249. 2009. View Article : Google Scholar : PubMed/NCBI
25	Haitina T, Olsson F, Stephansson O, Alsiö J, Roman E, Ebendal T, Schiöth HB and Fredriksson R: Expression profile of the entire family of Adhesion G protein-coupled receptors in mouse and rat. BMC Neurosci. 9:1–14. 2008. View Article : Google Scholar : PubMed/NCBI
26	Galliano MF, Toulza E, Gallinaro H, Jonca N, Ishida-Yamamoto A, Serre G and Guerrin M: A novel protease inhibitor of the alpha2-macroglobulin family expressed in the human epidermis. J Biol Chemist. 281:5780–5789. 2006. View Article : Google Scholar
27	Vissers LE, Bonetti M, Overman Paardekooper J, Nillesen WM, Frints SG, de Ligt J, Zampino G, Justino A, Machado JC, Schepens M, et al: Heterozygous germline mutations in A2ML1 are associated with a disorder clinically related to Noonan syndrome. Eur J Hum Genet. 23:317–324. 2015. View Article : Google Scholar : PubMed/NCBI
28	Nakayama K, Nakayama N, Jinawath N, Salani R, Kurman RJ, Shih IeM and Wang TL: Amplicon profiles in ovarian serous carcinomas. Int J Cancer. 120:2613–2617. 2007. View Article : Google Scholar : PubMed/NCBI
29	Nakayama N, Nakayama K, Shamima Y, Ishikawa M, Katagiri A, Iida K and Miyazaki K: Gene amplification CCNE1 is related to poor survival and potential therapeutic target in ovarian cancer. Cancer. 116:2621–2634. 2010.PubMed/NCBI
30	Kim BJ, Kang KM, Jung SY, Choi HK, Seo JH, Chae JH, Cho EJ, Youn HD, Qin J and Kim ST: Esco2 is a novel corepressor that associates with various chromatin modifying enzymes. Biochem Biophys Res Commun. 372:298–304. 2008. View Article : Google Scholar : PubMed/NCBI
31	Ahuja R, Pinyol R, Reichenbach N, Custer L, Klingensmith J, Kessels MM and Qualmann B: Cordon-bleu is an actin nucleation factor and controls neuronal morphology. Cell. 131:337–350. 2007. View Article : Google Scholar : PubMed/NCBI
32	Nair M, Teng A, Bilanchone V, Agrawal A, Li B and Dai X: Ovol1 regulates the growth arrest of embryonic epidermal progenitor cells and represses c-myc transcription. J Cell Biol. 173:253–264. 2006. View Article : Google Scholar : PubMed/NCBI
33	Roca H, Hernandez J, Weidner S, McEachin RC, Fuller D, Sud S, Schumann T, Wilkinson JE, Zaslavsky A, Li H, et al: Transcription factors OVOL1 and OVOL2 induce the mesenchymal to epithelial transition in human cancer. PloS One. 8:e767732013. View Article : Google Scholar : PubMed/NCBI
34	Schwintzer L, Koch N, Ahuja R, Grimm J, Kessels MM and Qualmann B: The functions of the actin nucleator Cobl in cellular morphogenesis critically depend on syndapin I. Embo J. 30:3147–3159. 2011. View Article : Google Scholar : PubMed/NCBI
35	Nie W, Xue C, Chen J and Xiu Q: Secretoglobin 1A member 1 (SCGB1A1)+38A/G polymorphism is associated with asthma risk: A meta-analysis. Gene. 528:304–308. 2013. View Article : Google Scholar : PubMed/NCBI
36	Peri A, Cordella-Miele E, Miele L and Mukherjee AB: Tissue-specific expression of the gene coding for human Clara cell 10-kD protein, a phospholipase A2-inhibitory protein. J Clin Invest. 92:2099–2109. 1993. View Article : Google Scholar : PubMed/NCBI