Identification of hub genes with prognostic values in gastric cancer by bioinformatics analysis

Ting Li, Xujie Gao, Lei Han, Jinpu Yu, Hui Li, Ting Li, Xujie Gao, Lei Han, Jinpu Yu, Hui Li

Abstract

Background: Gastric cancer (GC) is a prevalent malignant cancer of digestive system. To identify key genes in GC, mRNA microarray GSE27342, GSE29272, and GSE33335 were downloaded from GEO database.

Methods: Differentially expressed genes (DEGs) were obtained using GEO2R. DAVID database was used to analyze function and pathways enrichment of DEGs. Protein-protein interaction (PPI) network was established by STRING and visualized by Cytoscape software. Then, the influence of hub genes on overall survival (OS) was performed by the Kaplan-Meier plotter online tool. Module analysis of the PPI network was performed using MCODE. Additionally, potential stem loop miRNAs of hub genes were predicted by miRecords and screened by TCGA dataset. Transcription factors (TFs) of hub genes were detected by NetworkAnalyst.

Results: In total, 67 DEGs were identified; upregulated DEGs were mainly enriched in biological process (BP) related to angiogenesis and extracellular matrix organization and the downregulated DEGs were mainly enriched in BP related to ion transport and response to bacterium. KEGG pathways analysis showed that the upregulated DEGs were enriched in ECM-receptor interaction and the downregulated DEGs were enriched in gastric acid secretion. A PPI network of DEGs was constructed, consisting of 43 nodes and 87 edges. Twelve genes were considered as hub genes owing to high degrees in the network. Hsa-miR-29c, hsa-miR-30c, hsa-miR-335, hsa-miR-33b, and hsa-miR-101 might play a crucial role in hub genes regulation. In addition, the transcription factors-hub genes pairs were displayed with 182 edges and 102 nodes. The high expression of 7 out of 12 hub genes was associated with worse OS, including COL4A1, VCAN, THBS2, TIMP1, COL1A2, SERPINH1, and COL6A3.

Conclusions: The miRNA and TFs regulation network of hub genes in GC may promote understanding of the molecular mechanisms underlying the development of gastric cancer and provide potential targets for GC diagnosis and treatment.

Keywords: Bioinformatics analysis; Differentially expressed genes; Gastric cancer; Prognosis.

Conflict of interest statement

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Identification of DEGs in mRNA expression profiling datasets GSE27342, GSE29272, and GSE33335
Fig. 2
Fig. 2
PPI network and a significant module. a PPI network of DEGs, red means upregulated genes and green means downregulated genes. b A significant module selected from PPI network, all of them were upregulated genes
Fig. 3
Fig. 3
The network of transcription factors and hub genes
Fig. 4
Fig. 4
Prognostic value of 12 genes in GSE15459. Prognostic value in GSE15459 of THBS2(a), TIMP1(b), VCAN(c), MMP7(d), COL4A1(e), COL1A2(f), SPP1(g), COL6A3(h), COL1A1(i), SERINH1(j), SPARC(k), and COL3A1(l) were obtained in www.kmplot.com. The desired Affymetrix IDs are valid: 203083_at (THBS2), 201666_at (TIMP1), 221731_x_at (VCAN), 204259_at (MMP7), 211980_at (COL4A1), 202403_s_at (COL1A2), 48580_at (SPP1), 201438_at (COL6A3), 202311_s_at (COL1A1), 207714_s_at (SERPINH1), 212667_at (SPARC), and 201852_x_at (COL3A1). HR, hazard ratio; CI, confidence interval; adj. p, adjusted p value
Fig. 5
Fig. 5
The validation of prognostic value of ten genes in GSE62254. Prognostic value in GSE62254 of COL4A1 (a), VCAN (b), THBS2 (c), TIMP1 (d), COL1A2 (e), SERINH1 (f), COL6A3 (g), COL1A1 (h), MMP7 (i), and SPP1 (j) were obtained in www.kmplot.com. The desired Affymetrix IDs are valid: 211980_at (COL4A1), 221731_x_at (VCAN), 203083_at (THBS2), 201666_at (TIMP1), 202403_s_at (COL1A2), 207714_s_at (SERPINH1), 201438_at (COL6A3), 202311_s_at (COL1A1), 204259_at (MMP7), and 48580_at (SPP1). HR, hazard ratio; CI, confidence interval; adj. p, adjusted p value

References

    1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65:87–108. doi: 10.3322/caac.21262.
    1. Chen W, Zheng R, Zhang S, Zhao P, Zeng H, Zou X. Report of cancer incidence and mortality in China, 2010. Ann Transl Med. 2014;2:61.
    1. Shah MA, Kelsen DP. Gastric cancer: a primer on the epidemiology and biology of the disease and an overview of the medical management of advanced disease. J Natl Compr Cancer Netw. 2010;8:437–447. doi: 10.6004/jnccn.2010.0033.
    1. Deng N, Goh LK, Wang H, Das K, Tao J, Tan IB, Zhang S, Lee M, Wu J, Lim KH, et al. A comprehensive survey of genomic alterations in gastric cancer reveals systematic patterns of molecular exclusivity and co-occurrence among distinct therapeutic targets. Gut. 2012;61:673–684. doi: 10.1136/gutjnl-2011-301839.
    1. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90. doi: 10.3322/caac.20107.
    1. Zhang Z, Dou M, Yao X, Tang H, Li Z, Zhao X. Potential biomarkers in diagnosis of human gastric cancer. Cancer Investig. 2016;34:115–122. doi: 10.3109/07357907.2015.1114122.
    1. Chen CZ, Li L, Lodish HF, Bartel DP. MicroRNAs modulate hematopoietic lineage differentiation. Science. 2004;303:83–86. doi: 10.1126/science.1091903.
    1. Raver-Shapira N, Marciano E, Meiri E, Spector Y, Rosenfeld N, Moskovits N, Bentwich Z, Oren M. Transcriptional activation of miR-34a contributes to p53-mediated apoptosis. Mol Cell. 2007;26:731–743. doi: 10.1016/j.molcel.2007.05.017.
    1. Marsit CJ, Eddy K, Kelsey KT. MicroRNA responses to cellular stress. Cancer Res. 2006;66:10843–10848. doi: 10.1158/0008-5472.CAN-06-1894.
    1. Schmittgen TD. Regulation of microRNA processing in development, differentiation and cancer. J Cell Mol Med. 2008;12:1811–1819. doi: 10.1111/j.1582-4934.2008.00483.x.
    1. Bustin SA, Dorudi S. Gene expression profiling for molecular staging and prognosis prediction in colorectal cancer. Expert Rev Mol Diagn. 2004;4:599–607. doi: 10.1586/14737159.4.5.599.
    1. Nannini M, Pantaleo MA, Maleddu A, Astolfi A, Formica S, Biasco G. Gene expression profiling in colorectal cancer using microarray technologies: results and perspectives. Cancer Treat Rev. 2009;35:201–209. doi: 10.1016/j.ctrv.2008.10.006.
    1. Kulasingam V, Diamandis EP. Strategies for discovering novel cancer biomarkers through utilization of emerging technologies. Nat Clin Pract Oncol. 2008;5:588–599. doi: 10.1038/ncponc1187.
    1. Cui J, Chen Y, Chou WC, Sun L, Chen L, Suo J, Ni Z, Zhang M, Kong X, Hoffman LL, et al. An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer. Nucleic Acids Res. 2011;39:1197–1207. doi: 10.1093/nar/gkq960.
    1. Cheng L, Wang P, Yang S, Yang Y, Zhang Q, Zhang W, Xiao H, Gao H, Zhang Q. Identification of genes with a correlation between copy number and expression in gastric cancer. BMC Med Genet. 2012;5:14.
    1. Wang G, Hu N, Yang HH, Wang L, Su H, Wang C, Clifford R, Dawsey EM, Li JM, Ding T, et al. Comparison of global gene expression of gastric cardia and noncardia cancers from a high-risk population in China. PLoS One. 2013;8:e63826. doi: 10.1371/journal.pone.0063826.
    1. Dennis GJ, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 2003;4:P3. doi: 10.1186/gb-2003-4-5-p3.
    1. Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. Bmc Bioinformatics. 2003;4:2. doi: 10.1186/1471-2105-4-2.
    1. Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T. miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res. 2009;37:D105–D110. doi: 10.1093/nar/gkn851.
    1. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–140. doi: 10.1093/bioinformatics/btp616.
    1. Lachmann A, Xu H, Krishnan J, Berger SI, Mazloom AR, Ma’Ayan A. ChEA: transcription factor regulation inferred from integrating genome-wide ChIP-X experiments. Bioinformatics. 2010;26:2438–2444. doi: 10.1093/bioinformatics/btq466.
    1. Xia J, Gill EE, Hancock RE. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nat Protoc. 2015;10:823–844. doi: 10.1038/nprot.2015.052.
    1. Gyorffy B, Lanczky A, Szallasi Z. Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian-cancer using microarray data from 1287 patients. Endocr Relat Cancer. 2012;19:197–208. doi: 10.1530/ERC-11-0329.
    1. Zhang X, Yang JJ, Kim YS, Kim KY, Ahn WS, Yang S. An 8-gene signature, including methylated and down-regulated glutathione peroxidase 3, of gastric cancer. Int J Oncol. 2010;36:405–414.
    1. Ooi CH, Ivanova T, Wu J, Lee M, Tan IB, Tao J, Ward L, Koo JH, Gopalakrishnan V, Zhu Y, et al. Oncogenic pathway combinations predict clinical prognosis in gastric cancer. PLoS Genet. 2009;5:e1000676. doi: 10.1371/journal.pgen.1000676.
    1. Cristescu R, Lee J, Nebozhyn M, Kim KM, Ting JC, Wong SS, Liu J, Yue YG, Wang J, Yu K, et al. Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes. Nat Med. 2015;21:449–456. doi: 10.1038/nm.3850.
    1. Van Cutsem E, Sagaert X, Topal B, Haustermans K, Prenen H. Gastric cancer. Lancet. 2016;388:2654–64. doi: 10.1016/S0140-6736(16)30354-3.
    1. Ito S, Nagata K. Biology of Hsp47 (Serpin H1), a collagen-specific molecular chaperone. Semin Cell Dev Biol. 2016;62:142–51. doi: 10.1016/j.semcdb.2016.11.005.
    1. Wu ZB, Cai L, Lin SJ, Leng ZG, Guo YH, Yang WL, Chu YW, Yang SH, Zhao WG. Heat shock protein 47 promotes glioma angiogenesis. Brain Pathol. 2016;26:31–42. doi: 10.1111/bpa.12256.
    1. Kamikawaji K, Seki N, Watanabe M, Mataki H, Kumamoto T, Takagi K, Mizuno K, Inoue H. Regulation of LOXL2 and SERPINH1 by antitumor microRNA-29a in lung cancer with idiopathic pulmonary fibrosis. J Hum Genet. 2016;61:985. doi: 10.1038/jhg.2016.99.
    1. Yamamoto N, Kinoshita T, Nohata N, Yoshino H, Itesako T, Fujimura L, Mitsuhashi A, Usui H, Enokida H, Nakagawa M, et al. Tumor-suppressive microRNA-29a inhibits cancer cell migration and invasion via targeting HSP47 in cervical squamous cell carcinoma. Int J Oncol. 2013;43:1855–1863. doi: 10.3892/ijo.2013.2145.
    1. Sauk JJ, Nikitakis N, Siavash H. Hsp47 a novel collagen binding serpin chaperone, autoantigen and therapeutic target. Front Biosci. 2005;10:107–118. doi: 10.2741/1513.
    1. Morino M, Tsuzuki T, Ishikawa Y, Shirakami T, Yoshimura M, Kiyosuke Y, Matsunaga K, Yoshikumi C, Saijo N. Specific expression of HSP47 in human tumor cell lines in vitro. In Vivo. 1997;11:17–21.
    1. Aitken KJ, Bagli DJ. The bladder extracellular matrix. Part I: architecture, development and disease. Nat Rev Urol. 2009;6:596–611. doi: 10.1038/nrurol.2009.201.
    1. Zou X, Feng B, Dong T, Yan G, Tan B, Shen H, Huang A, Zhang X, Zhang M, Yang P, et al. Up-regulation of type I collagen during tumorigenesis of colorectal cancer revealed by quantitative proteomic analysis. J Proteome. 2013;94:473–485. doi: 10.1016/j.jprot.2013.10.020.
    1. Li J, Li X, Lan T, Qi C, He X, Yang H, Li Y, Wang L, Guan X. Type I collagen secreted by lung cancer cells promotes cancer cell growth in a three- dimensional culture system. Nan Fang Yi Ke Da Xue Xue Bao. 2014;34:1129–1134.
    1. Santala M, Simojoki M, Risteli J, Risteli L, Kauppila A. Type I and III collagen metabolites as predictors of clinical outcome in epithelial ovarian cancer. Clin Cancer Res. 1999;5:4091–4096.
    1. Desert R, Mebarki S, Desille M, Sicard M, Lavergne E, Renaud S, Bergeat D, Sulpice L, Perret C, Turlin B, et al. “Fibrous nests” in human hepatocellular carcinoma express a Wnt-induced gene signature associated with poor clinical outcome. Int J Biochem Cell Biol. 2016;81:195. doi: 10.1016/j.biocel.2016.08.017.
    1. Salem O, Erdem N, Jung J, Munstermann E, Worner A, Wilhelm H, Wiemann S, Korner C. The highly expressed 5′isomiR of hsa-miR-140-3p contributes to the tumor-suppressive effects of miR-140 by reducing breast cancer proliferation and migration. BMC Genomics. 2016;17:566. doi: 10.1186/s12864-016-2869-x.
    1. Xie X, Liu X, Zhang Q, Yu J. Overexpression of collagen VI alpha3 in gastric cancer. Oncol Lett. 2014;7:1537–1543. doi: 10.3892/ol.2014.1910.
    1. Feng J, Tang L. SPARC in tumor pathophysiology and as a potential therapeutic target. Curr Pharm Des. 2014;20:6182–6190. doi: 10.2174/1381612820666140619123255.
    1. Zhang J, Wang P, Zhu J, Wang W, Yin J, Zhang C, Chen Z, Sun L, Wan Y, Wang X, et al. SPARC expression is negatively correlated with clinicopathological factors of gastric cancer and inhibits malignancy of gastric cancer cells. Oncol Rep. 2014;31:2312–2320. doi: 10.3892/or.2014.3118.
    1. Furger KA, Menon RK, Tuck AB, Bramwell VH, Chambers AF. The functional and clinical roles of osteopontin in cancer and metastasis. Curr Mol Med. 2001;1:621–632. doi: 10.2174/1566524013363339.
    1. Raja UM, Gopal G, Shirley S, Ramakrishnan AS, Rajkumar T. Immunohistochemical expression and localization of cytokines/chemokines/growth factors in gastric cancer. Cytokine. 2016;89:82–90. doi: 10.1016/j.cyto.2016.08.032.
    1. Zhang DT, Yuan J, Yang L, Guo XN, Hao ZM, Han ZY, Wu KC, Fan DM. Osteopontin expression and its relation to invasion and metastases in gastric cancer. Zhonghua Zhong Liu Za Zhi. 2005;27:167–169.
    1. Ricciardelli C, Sakko AJ, Ween MP, Russell DL, Horsfall DJ. The biological role and regulation of versican levels in cancer. Cancer Metastasis Rev. 2009;28:233–245. doi: 10.1007/s10555-009-9182-y.
    1. Zhang Z, Zhang J, Miao L, Liu K, Yang S, Pan C, Jiao B. Interleukin-11 promotes the progress of gastric carcinoma via abnormally expressed versican. Int J Biol Sci. 2012;8:383–393. doi: 10.7150/ijbs.3579.
    1. Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136:215–233. doi: 10.1016/j.cell.2009.01.002.
    1. Volinia S, Calin GA, Liu CG, Ambs S, Cimmino A, Petrocca F, Visone R, Iorio M, Roldo C, Ferracin M, et al. A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A. 2006;103:2257–2261. doi: 10.1073/pnas.0510565103.
    1. Han TS, Hur K, Xu G, Choi B, Okugawa Y, Toiyama Y, Oshima H, Oshima M, Lee HJ, Kim VN, et al. MicroRNA-29c mediates initiation of gastric carcinogenesis by directly targeting ITGB1. Gut. 2015;64:203–214. doi: 10.1136/gutjnl-2013-306640.
    1. Cristobal I, Madoz-Gurpide J, Manso R, Rojo F, Garcia-Foncillas J. MiR-29c downregulation contributes to metastatic progression in colorectal cancer. Ann Oncol. 2015;26:2199–2200. doi: 10.1093/annonc/mdv302.
    1. Cao JM, Li GZ, Han M, Xu HL, Huang KM. MiR-30c-5p suppresses migration, invasion and epithelial to mesenchymal transition of gastric cancer via targeting MTA1. Biomed Pharmacother. 2017;93:554–560. doi: 10.1016/j.biopha.2017.06.084.
    1. Xia Y, Chen Q, Zhong Z, Xu C, Wu C, Liu B, Chen Y. Down-regulation of miR-30c promotes the invasion of non-small cell lung cancer by targeting MTA1. Cell Physiol Biochem. 2013;32:476–485. doi: 10.1159/000354452.
    1. Zhang Q, Yu L, Qin D, Huang R, Jiang X, Zou C, Tang Q, Chen Y, Wang G, Wang X, Gao X. Role of microRNA-30c targeting ADAM19 in colorectal cancer. PLoS One. 2015;10:e120698.
    1. Ling XH, Han ZD, Xia D, He HC, Jiang FN, Lin ZY, Fu X, Deng YH, Dai QS, Cai C, et al. MicroRNA-30c serves as an independent biochemical recurrence predictor and potential tumor suppressor for prostate cancer. Mol Biol Rep. 2014;41:2779–2788. doi: 10.1007/s11033-014-3132-7.
    1. Wang YX, Zhang XY, Zhang BF, Yang CQ, Chen XM, Gao HJ. Initial study of microRNA expression profiles of colonic cancer without lymph node metastasis. J Dig Dis. 2010;11:50–54. doi: 10.1111/j.1751-2980.2009.00413.x.
    1. Sorrentino A, Liu CG, Addario A, Peschle C, Scambia G, Ferlini C. Role of microRNAs in drug-resistant ovarian cancer cells. Gynecol Oncol. 2008;111:478–486. doi: 10.1016/j.ygyno.2008.08.017.
    1. Xu Y, Zhao F, Wang Z, Song Y, Luo Y, Zhang X, Jiang L, Sun Z, Miao Z, Xu H. MicroRNA-335 acts as a metastasis suppressor in gastric cancer by targeting Bcl-w and specificity protein 1. Oncogene. 2012;31:1398–1407. doi: 10.1038/onc.2011.340.
    1. Liao W, Gu C, Huang A, Yao J, Sun R. MicroRNA-33b inhibits tumor cell growth and is associated with prognosis in colorectal cancer patients. Clin Transl Oncol. 2016;18:449–456. doi: 10.1007/s12094-015-1388-6.
    1. Qu J, Li M, An J, Zhao B, Zhong W, Gu Q, Cao L, Yang H, Hu C. MicroRNA-33b inhibits lung adenocarcinoma cell growth, invasion, and epithelial-mesenchymal transition by suppressing Wnt/beta-catenin/ZEB1 signaling. Int J Oncol. 2015;47:2141–2152. doi: 10.3892/ijo.2015.3187.
    1. Tian Q, Xiao Y, Wu Y, Liu Y, Song Z, Gao W, Zhang J, Yang J, Zhang Y, Guo T, et al. MicroRNA-33b suppresses the proliferation and metastasis of hepatocellular carcinoma cells through the inhibition of Sal-like protein 4 expression. Int J Mol Med. 2016;38:1587–1595. doi: 10.3892/ijmm.2016.2754.
    1. Yin H, Song P, Su R, Yang G, Dong L, Luo M, Wang B, Gong B, Liu C, Song W, et al. DNA Methylation mediated down-regulating of MicroRNA-33b and its role in gastric cancer. Sci Rep. 2016;6:18824. doi: 10.1038/srep18824.
    1. Varambally S, Cao Q, Mani RS, Shankar S, Wang X, Ateeq B, Laxman B, Cao X, Jing X, Ramnarayanan K, et al. Genomic loss of microRNA-101 leads to overexpression of histone methyltransferase EZH2 in cancer. Science. 2008;322:1695–1699. doi: 10.1126/science.1165395.
    1. Carvalho J, van Grieken NC, Pereira PM, Sousa S, Tijssen M, Buffart TE, Diosdado B, Grabsch H, Santos MA, Meijer G, et al. Lack of microRNA-101 causes E-cadherin functional deregulation through EZH2 up-regulation in intestinal gastric cancer. J Pathol. 2012;228:31–44.
    1. Tam WL, Ng HH. Sox2: masterminding the root of cancer. Cancer Cell. 2014;26:3–5. doi: 10.1016/j.ccr.2014.06.024.
    1. Tian Y, Jia X, Wang S, Li Y, Zhao P, Cai D, Zhou Z, Wang J, Luo Y, Dong M. SOX2 oncogenes amplified and operate to activate AKT signaling in gastric cancer and predict immunotherapy responsiveness. J Cancer Res Clin Oncol. 2014;140:1117–1124. doi: 10.1007/s00432-014-1660-0.
    1. Wang S, Tie J, Wang R, Hu F, Gao L, Wang W, Wang L, Li Z, Hu S, Tang S, et al. SOX2, a predictor of survival in gastric cancer, inhibits cell proliferation and metastasis by regulating PTEN. Cancer Lett. 2015;358:210–219. doi: 10.1016/j.canlet.2014.12.045.
    1. Zhou Y, Du WD, Wu Q, Liu Y, Chen G, Ruan J, Xu S, Yang F, Zhou FS, Tang XF, et al. EZH2 genetic variants affect risk of gastric cancer in the Chinese Han population. Mol Carcinog. 2014;53:589–597.
    1. Choi JH, Song YS, Yoon JS, Song KW, Lee YY. Enhancer of zeste homolog 2 expression is associated with tumor cell proliferation and metastasis in gastric cancer. Apmis. 2010;118:196–202. doi: 10.1111/j.1600-0463.2009.02579.x.
    1. Chiang YT, Wang K, Fazli L, Qi RZ, Gleave ME, Collins CC, Gout PW, Wang Y. GATA2 as a potential metastasis-driving gene in prostate cancer. Oncotarget. 2014;5:451–461.
    1. Takayama K, Suzuki T, Tsutsumi S, Fujimura T, Urano T, Takahashi S, Homma Y, Aburatani H, Inoue S. RUNX1, an androgen- and EZH2-regulated gene, has differential roles in AR-dependent and -independent prostate cancer. Oncotarget. 2015;6:2263–2276. doi: 10.18632/oncotarget.2949.
    1. Li N, Zhang QY, Zou JL, Li ZW, Tian TT, Dong B, Liu XJ, Ge S, Zhu Y, Gao J, Shen L. miR-215 promotes malignant progression of gastric cancer by targeting RUNX1. Oncotarget. 2016;7:4817–4828.
    1. Park JW, Park DM, Choi BK, Kwon BS, Seong JK, Green JE, Kim DY, Kim HK. Establishment and characterization of metastatic gastric cancer cell lines from murine gastric adenocarcinoma lacking Smad4, p53, and E-cadherin. Mol Carcinog. 2015;54:1521–1527. doi: 10.1002/mc.22226.
    1. Pasini D, Bracken AP, Jensen MR, Lazzerini DE, Helin K. Suz12 is essential for mouse development and for EZH2 histone methyltransferase activity. EMBO J. 2004;23:4061–4071. doi: 10.1038/sj.emboj.7600402.
    1. Xia R, Jin FY, Lu K, Wan L, Xie M, Xu TP, De W, Wang ZX. SUZ12 promotes gastric cancer cell proliferation and metastasis by regulating KLF2 and E-cadherin. Tumour Biol. 2015;36:5341–5351. doi: 10.1007/s13277-015-3195-7.

Source: PubMed

Sponsorzy i współpracownicy

Warunki medyczne

Interwencje lekowe

3
Subskrybuj