Login Register Cart 0
Generic placeholder image

Combinatorial Chemistry & High Throughput Screening

Editor-in-Chief

ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Screening and Interaction Analysis of Key Genes in miR-542-3p Over- Expressed Osteosarcoma Cells by Bioinformatics

Author(s): Zhongqiu Li, Peng Zhang, Feifei Feng and Qiao Zhang*

Volume 23, Issue 5, 2020

Page: [411 - 418] Pages: 8

DOI: 10.2174/1386207323666200401103353

Price: $65

TIMBC 2025
Abstract

Background: Osteosarcoma is one of the most serious primary malignant bone tumors that threaten the lives of children and adolescents. However, the mechanism underlying and how to prevent or treat the disease have not been well understood.

Aims and Objective: This aim of the present study was to identify the key genes and explore novel insights into the molecular mechanism of miR-542-3p over-expressed Osteosarcoma.

Materials and Methods: Gene expression profile data GDS5367 was downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were screened using GEO2R, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the DAVID database. And protein-protein interaction (PPI) network was constructed by the STRING database. In addition, the most highly connected module was screened by plugin MCODE and hub genes by plugin CytoHubba. Furthermore, UALCAN and The Cancer Genome Atlas were performed for survival analysis.

Result: In total, 1421 DEGs were identified, including 598 genes were up-regulated and 823 genes were down-regulated. GO analysis showed that DEGs were classified into three groups and DEGs mainly enriched in Steroid biosynthesis, Ubiquitin mediated proteolysis and p53 signaling pathway. Six hub genes (UBA52, RNF114, UBE2H, TRIP12, HNRNPC, and PTBP1) may be key genes with the progression of osteosarcoma.

Conclusion: The results could better understand the mechanism of osteosarcoma, which may facilitate a novel insight into treatment targets.

Keywords: Osteosarcoma, miR-542-3p, module analysis, survival analysis, bioinformatics analysis, gene expression.

« Previous Next »
[1]
Ding, L.; Wang, C.; Cui, Y.; Han, X.; Zhou, Y.; Bai, J.; Li, R. S-phase kinase-associated protein 2 is involved in epithelial-mesenchymal transition in methotrexate-resistant osteosarcoma cells. Int. J. Oncol., 2018, 52(6), 1841-1852.
[http://dx.doi.org/10.3892/ijo.2018.4345] [PMID: 29620168]
[2]
Zhang, J.; Yan, Y.G.; Wang, C.; Zhang, S.J.; Yu, X.H.; Wang, W.J. MicroRNAs in osteosarcoma. Clin. Chim. Acta, 2015, 444, 9-17.
[http://dx.doi.org/10.1016/j.cca.2015.01.025] [PMID: 25661090]
[3]
Ottaviani, G.; Jaffe, N. The epidemiology of osteosarcoma. Cancer Treat. Res., 2009, 152, 3-13.
[http://dx.doi.org/10.1007/978-1-4419-0284-9_1] [PMID: 20213383]
[4]
Ali, I.; Haque, A.; Saleem, K.; Hsieh, M.F. Curcumin-I Knoevenagel’s condensates and their Schiff’s bases as anticancer agents: synthesis, pharmacological and simulation studies. Bioorg. Med. Chem., 2013, 21(13), 3808-3820.
[http://dx.doi.org/10.1016/j.bmc.2013.04.018]
[5]
Imran, A.; Waseem, A.W.; Kishwar, S. Design and synthesis of thalidomide based dithiocarbamate Cu(II), Ni(II) and Ru(III) complexes as anticancer agents. Polyhedron, 2013, 56, 134-143.
[6]
Imran, A. Nano anti-cancer drugs: pros and cons and future perspectives. Curr. Cancer Drug Targets, 2011, 11(2), 131-134.
[http://dx.doi.org/10.2174/156800911794328457]
[7]
Luetke, A.; Meyers, P.A.; Lewis, I.; Juergens, H. Osteosarcoma treatment - where do we stand? A state of the art review. Cancer Treat. Rev., 2014, 40(4), 523-532.
[http://dx.doi.org/10.1016/j.ctrv.2013.11.006] [PMID: 24345772]
[8]
Zhang, Y.; Wang, Z.; Gemeinhart, R.A. Progress in microRNA delivery. J. Control. Release, 2013, 172(3), 962-974.
[http://dx.doi.org/10.1016/j.jconrel.2013.09.015] [PMID: 24075926]
[9]
Zhou, Y.; Han, Y.; Zhang, Z.; Shi, Z.; Zhou, L.; Liu, X.; Jia, X. MicroRNA-124 upregulation inhibits proliferation and invasion of osteosarcoma cells by targeting sphingosine kinase 1. Hum. Cell, 2017, 30(1), 30-40.
[http://dx.doi.org/10.1007/s13577-016-0148-4] [PMID: 27743351]
[10]
Li, Y.; Zhang, J.; Zhang, L.; Si, M.; Yin, H.; Li, J. Diallyl trisulfide inhibits proliferation, invasion and angiogenesis of osteosarcoma cells by switching on suppressor microRNAs and inactivating of Notch-1 signaling. Carcinogenesis, 2013, 34(7), 1601-1610.
[http://dx.doi.org/10.1093/carcin/bgt065] [PMID: 23430952]
[11]
Yuan, L.; Yuan, P.; Yuan, H.; Wang, Z.; Run, Z.; Chen, G.; Zhao, P.; Xu, B. miR-542-3p inhibits colorectal cancer cell proliferation, migration and invasion by targeting OTUB1. Am. J. Cancer Res., 2017, 7(1), 159-172.
[PMID: 28123857]
[12]
Ma, T.; Yang, L.; Zhang, J. MiRNA 542 3p downregulation promotes trastuzumab resistance in breast cancer cells via AKT activation. Oncol. Rep., 2015, 33(3), 1215-1220.
[http://dx.doi.org/10.3892/or.2015.3713] [PMID: 25586125]
[13]
Kim, V.N.; Han, J.; Siomi, M.C. Biogenesis of small RNAs in animals. Nat. Rev. Mol. Cell Biol., 2009, 10(2), 126-139.
[http://dx.doi.org/10.1038/nrm2632] [PMID: 19165215]
[14]
Bartel, D.P. MicroRNAs: target recognition and regulatory functions. Cell, 2009, 136(2), 215-233.
[http://dx.doi.org/10.1016/j.cell.2009.01.002] [PMID: 19167326]
[15]
Woetzel, D.; Huber, R.; Kupfer, P.; Pohlers, D.; Pfaff, M.; Driesch, D.; Häupl, T.; Koczan, D.; Stiehl, P.; Guthke, R.; Kinne, R.W. Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation. Arthritis Res. Ther., 2014, 16(2), R84.
[http://dx.doi.org/10.1186/ar4526] [PMID: 24690414]
[16]
Barrett, T.; Wilhite, S.E.; Ledoux, P.; Evangelista, C.; Kim, I.F.; Tomashevsky, M.; Marshall, K.A.; Phillippy, K.H.; Sherman, P.M.; Holko, M.; Yefanov, A.; Lee, H.; Zhang, N.; Robertson, C.L.; Serova, N.; Davis, S.; Soboleva, A. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res., 2013, 41(Database issue), D991-D995.
[PMID: 23193258]
[17]
Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Davis, A.P.; Dolinski, K.; Dwight, S.S.; Eppig, J.T.; Harris, M.A.; Hill, D.P.; Issel-Tarver, L.; Kasarskis, A.; Lewis, S.; Matese, J.C.; Richardson, J.E.; Ringwald, M.; Rubin, G.M.; Sherlock, G. Gene ontology: tool for the unification of biology. Nat. Genet., 2000, 25(1), 25-29.
[http://dx.doi.org/10.1038/75556] [PMID: 10802651]
[18]
Altermann, E.; Klaenhammer, T.R. PathwayVoyager: pathway mapping using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database; Bmc Genomics, 2005, p. 6.
[19]
Huang, D.W.; Sherman, B.T.; Tan, Q.; Kir, J.; Liu, D.; Bryant, D.; Guo, Y.; Stephens, R.; Baseler, M.W.; Lane, H.C.; Lempicki, R.A. DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res., 2007, 35, W169-75.
[http://dx.doi.org/10.1093/nar/gkm415]
[20]
Szklarczyk, D.; Franceschini, A.; Wyder, S.; Forslund, K.; Heller, D.; Huerta-Cepas, J.; Simonovic, M.; Roth, A.; Santos, A.; Tsafou, K.P.; Kuhn, M.; Bork, P.; Jensen, L.J.; von Mering, C. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res., 2015, 43(Database issue), D447-D452.
[http://dx.doi.org/10.1093/nar/gku1003] [PMID: 25352553]
[21]
Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res., 2003, 13(11), 2498-2504.
[http://dx.doi.org/10.1101/gr.1239303] [PMID: 14597658]
[22]
Bader, G.D.; Hogue, C.W. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics, 2003, 4, 2.
[http://dx.doi.org/10.1186/1471-2105-4-2] [PMID: 12525261]
[23]
Chandrashekar, D.S.; Bashel, B.; Balasubramanya, S.A.H.; Creighton, C.J.; Ponce-Rodriguez, I.; Chakravarthi, B.V.S.K.; Varambally, S. UALCAN: A portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia, 2017, 19(8), 649-658.
[http://dx.doi.org/10.1016/j.neo.2017.05.002] [PMID: 28732212]
[24]
Ali, I.; Rahis-Uddin, ; Salim, K.; Rather, M.A.; Wani, W.A.; Haque, A. Advances in nano drugs for cancer chemotherapy. Curr. Cancer Drug Targets, 2011, 11(2), 135-146.
[http://dx.doi.org/10.2174/156800911794328493] [PMID: 21158724]
[25]
Ali, I.; Lone, M.N.; Suhail, M.; Mukhtar, S.D.; Asnin, L. Advances in Nanocarriers for anticancer drugs delivery. Curr. Med. Chem., 2016, 23(20), 2159-2187.
[http://dx.doi.org/10.2174/0929867323666160405111152] [PMID: 27048343]
[26]
Ali, I.; Wani, W.A.; Haque, A.; Saleem, K. Glutamic acid and its derivatives: candidates for rational design of anticancer drugs. Future Med. Chem., 2013, 5(8), 961-978.
[http://dx.doi.org/10.4155/fmc.13.62] [PMID: 23682571]
[27]
Ali, I.; Wani, W.A.; Saleem, K.; Wesselinova, D. Syntheses, DNA binding and anticancer profiles of L-glutamic acid ligand and its copper(II) and ruthenium(III) complexes. Med. Chem., 2013, 9(1), 11-21.
[http://dx.doi.org/10.2174/157340613804488297] [PMID: 22741786]
[28]
Li, Z.; Yao, J.N.; Huang, W.T.; He, R.Q.; Ma, J.; Chen, G.; Wei, Q.J. Expression of miR 542 3p in osteosarcoma with miRNA microarray data, and its potential signaling pathways. Mol. Med. Rep., 2019, 19(2), 974-983.
[PMID: 30569116]
[29]
Li, H.; Liu, H.; Pei, J.; Wang, H.; Lv, H. miR 542 3p overexpression is associated with enhanced osteosarcoma cell proliferation and migration ability by targeting Van Gogh like 2. Mol. Med. Rep., 2015, 11(2), 851-856.
[http://dx.doi.org/10.3892/mmr.2014.2777] [PMID: 25352048]
[30]
Cai, W.; Xu, Y.; Zuo, W.; Su, Z. MicroR-542-3p can mediate ILK and further inhibit cell proliferation, migration and invasion in osteosarcoma cells. Aging (Albany NY), 2019, 11(1), 18-32.
[http://dx.doi.org/10.18632/aging.101698] [PMID: 30636169]
[31]
Kobayashi, M.; Oshima, S.; Maeyashiki, C.; Nibe, Y.; Otsubo, K.; Matsuzawa, Y.; Nemoto, Y.; Nagaishi, T.; Okamoto, R.; Tsuchiya, K.; Nakamura, T.; Watanabe, M. The ubiquitin hybrid gene UBA52 regulates ubiquitination of ribosome and sustains embryonic development. Sci. Rep., 2016, 6, 36780.
[http://dx.doi.org/10.1038/srep36780] [PMID: 27829658]
[32]
Kobayashi, M.; Oshima, S.; Otsubo, K.; Nibe, Y.; Maeyashiki, C.; Watanabe, M. The ubiquitin-hybrid gene UBA52 regulates TNFa signaling in colon cancer. J. Gastroenterol. Hepatol., 2016, 31, 145-146.
[33]
Lin, B.; Ke, Q.; Li, H.; Pheifer, N.S.; Velliquette, D.C.; Leaman, D.W. Negative regulation of the RLH signaling by the E3 ubiquitin ligase RNF114. Cytokine, 2017, 99, 186-193.
[http://dx.doi.org/10.1016/j.cyto.2017.05.002] [PMID: 28625874]
[34]
Lin, B.; Ke, Q.; Leaman, D.W.; Goel, V.; Agarwal, A. Regulation of RANKL-induced osteoclastogenesis by RING finger protein RNF114. J. Orthop. Res., 2018, 36(1), 159-166.
[PMID: 28708287]
[35]
Yang, P.; Lu, Y.; Li, M.; Zhang, K.; Li, C.; Chen, H.; Tao, D.; Zhang, S.; Ma, Y. Identification of RNF114 as a novel positive regulatory protein for T cell activation. Immunobiology, 2014, 219(6), 432-439.
[http://dx.doi.org/10.1016/j.imbio.2014.02.002] [PMID: 24631332]
[36]
Martin, I.; Vourc’h, P.; Mahé, M.; Thépault, R.A.; Antar, C.; Védrine, S.; Praline, J.; Camu, W.; Andres, C.R.; Corcia, P.; French, A.L.S.S.G. Association study of the ubiquitin conjugating enzyme gene UBE2H in sporadic ALS. Amyotroph. Lateral Scler., 2009, 10(5-6), 432-435.
[http://dx.doi.org/10.3109/17482960802444972] [PMID: 19922136]
[37]
Liu, X.; Yang, X.; Li, Y.; Zhao, S.; Li, C.; Ma, P.; Mao, B. Trip12 is an E3 ubiquitin ligase for USP7/HAUSP involved in the DNA damage response. FEBS Lett., 2016, 590(23), 4213-4222.
[http://dx.doi.org/10.1002/1873-3468.12471] [PMID: 27800609]
[38]
Bramswig, N.C.; Lüdecke, H.J.; Pettersson, M.; Albrecht, B.; Bernier, R.A.; Cremer, K.; Eichler, E.E.; Falkenstein, D.; Gerdts, J.; Jansen, S.; Kuechler, A.; Kvarnung, M.; Lindstrand, A.; Nilsson, D.; Nordgren, A.; Pfundt, R.; Spruijt, L.; Surowy, H.M.; de Vries, B.B.A.; Wieland, T.; Engels, H.; Strom, T.M.; Kleefstra, T.; Wieczorek, D. Identification of new TRIP12 variants and detailed clinical evaluation of individuals with non-syndromic intellectual disability with or without autism. Hum. Genet., 2017, 136(2), 179-192.
[http://dx.doi.org/10.1007/s00439-016-1743-x] [PMID: 27848077]
[39]
Wang, L.; Zhang, P.J.; Molkentine, D.; Molkentine, J.; Raju, U.; Valdecanas, D.; Tailor, R.; Thames, H.; Buchholz, T.; Chen, J.J.; Ma, L.; Mason, K.; Meyn, R.; Skinner, H.D. TRIP12 as a mediator of human papillomavirus/p16-related radiation enhancement effects. Cancer Res., 2016, 76.
[PMID: 27425591]
[40]
Huang, H.; Han, Y.; Zhang, C.; Wu, J.; Feng, J.; Qu, L.; Shou, C. HNRNPC as a candidate biomarker for chemoresistance in gastric cancer. Tumour Biol., 2016, 37(3), 3527-3534.
[http://dx.doi.org/10.1007/s13277-015-4144-1] [PMID: 26453116]
[41]
Wu, Y.; Zhao, W.; Liu, Y.; Tan, X.; Li, X.; Zou, Q.; Xiao, Z.; Xu, H.; Wang, Y.; Yang, X. Function of HNRNPC in breast cancer cells by controlling the dsRNA-induced interferon response. EMBO J., 2018, 37(23) e99017
[http://dx.doi.org/10.15252/embj.201899017] [PMID: 30158112]
[42]
Shen, Y.; Liu, S.; Fan, J.; Jin, Y.; Tian, B.; Zheng, X.; Fu, H. Nuclear retention of the lncRNA SNHG1 by doxorubicin attenuates hnRNPC-p53 protein interactions. EMBO Rep., 2017, 18(4), 536-548.
[http://dx.doi.org/10.15252/embr.201643139] [PMID: 28264987]
[43]
Wang, X.; Li, Y.; Fan, Y.; Yu, X.; Mao, X.; Jin, F. PTBP1 promotes the growth of breast cancer cells through the PTEN/Akt pathway and autophagy. J. Cell. Physiol., 2018, 233(11), 8930-8939.
[http://dx.doi.org/10.1002/jcp.26823] [PMID: 29856478]

Rights & Permissions Print Cite
Article Metrics
30
2
Wayfinder Image
TIMBC 2025
© 2025 Bentham Science Publishers | Privacy Policy