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Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Research Article

Identification of Novel Key Targets and Candidate Drugs in Oral Squamous Cell Carcinoma

Author(s): Juan Liu, Xinjie Lian, Feng Liu, Xueling Yan, Chunyan Cheng, Lijia Cheng, Xiaolin Sun* and Zheng Shi*

Volume 15, Issue 4, 2020

Page: [328 - 337] Pages: 10

DOI: 10.2174/1574893614666191127101836

open access plus

Abstract

Background: Oral Squamous Cell Carcinoma (OSCC) is the most common malignant epithelial neoplasm. It is located within the top 10 ranking incidence of cancers with a poor prognosis and low survival rates. New breakthroughs of therapeutic strategies are therefore needed to improve the survival rate of OSCC harboring patients.

Objective: Since targeted therapy is considered as the most promising therapeutic strategies in cancer, it is of great significance to identify novel targets and drugs for the treatment of OSCC.

Methods: A series of bioinformatics approaches were launched to identify the hub proteins and their potential agents. Microarray analysis and several online functional activity network analysis were firstly utilized to recognize drug targets in OSCC. Subsequently, molecular docking was used to screen their potential drugs from the specs chemistry database. At the same time, the assessment of ligand-based virtual screening model was also evaluated.

Results: In this study, two microarray data (GSE31056, GSE23558) were firstly selected and analyzed to get consensus candidate genes including 681 candidate genes. Additionally, we selected 33 candidate genes based on whether they belong to the kinases and transcription factors and further clustered candidate hub targets based on functions and signaling pathways with significant enrichment analysis by using DAVID and STRING online databases. Then, core PPI network was then identified and we manually selected GRB2 and IGF1 as the key drug targets according to the network analysis and previous references. Lastly, virtual screening was performed to identify potential small molecules which could target these two targets, and such small molecules can serve as the promising candidate agents for future drug development.

Conclusion: In summary, our study might provide novel insights for understanding of the underlying molecular events of OSCC, and our discovered candidate targets and candidate agents could be used as the promising therapeutic strategies for the treatment of OSCC.

Keywords: Oral squamous cell carcinoma, novel target, GRB2, IGF1, systems biology, drug discovery.

Graphical Abstract
[1]
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018; 68(6): 394-424.
[http://dx.doi.org/10.3322/caac.21492] [PMID: 30207593]
[2]
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018; 68(1): 7-30.
[http://dx.doi.org/10.3322/caac.21442] [PMID: 29313949]
[3]
Michailidou E, Tzimagiorgis G, Chatzopoulou F, et al. Salivary mRNA markers having the potential to detect oral squamous cell carcinoma segregated from oral leukoplakia with dysplasia. Cancer Epidemiol 2016; 43: 112-8.
[http://dx.doi.org/10.1016/j.canep.2016.04.011] [PMID: 27263493]
[4]
Choi S, Myers JN. Molecular pathogenesis of oral squamous cell carcinoma: implications for therapy. J Dent Res 2008; 87(1): 14-32.
[http://dx.doi.org/10.1177/154405910808700104] [PMID: 18096889]
[5]
Ali J, Sabiha B, Jan HU, Haider SA, Khan AA, Ali SS. Genetic etiology of oral cancer. Oral Oncol 2017; 70: 23-8.
[http://dx.doi.org/10.1016/j.oraloncology.2017.05.004] [PMID: 28622887]
[6]
Zhou W, Wang Y, Lu A, Zhang G. Systems pharmacology in small molecular drug discovery. Int J Mol Sci 2016; 17(2): 246.
[http://dx.doi.org/10.3390/ijms17020246] [PMID: 26901192]
[7]
DeWard A, Critchley-Thorne RJ. Systems biology approaches in cancer pathology. Methods Mol Biol 2018; 1711: 261-73.
[http://dx.doi.org/10.1007/978-1-4939-7493-1_13] [PMID: 29344894]
[8]
Peyvandipour A, Saberian N, Shafi A, Donato M, Draghici S. A novel computational approach for drug repurposing using systems biology. Bioinformatics 2018; 34(16): 2817-25.
[http://dx.doi.org/10.1093/bioinformatics/bty133] [PMID: 29534151]
[9]
Song R, Li Y, Hao W, Wang B, Yang L, Xu F. Identification and analysis of key genes associated with ulcerative colitis based on DNA microarray data. Medicine 2018; 97(21) e10658
[http://dx.doi.org/10.1097/MD.0000000000010658] [PMID: 29794741]
[10]
Koller M, Hartmans E, de Groot DJA, et al. Data-Driven prioritization and review of targets for molecular-based theranostic approaches in pancreatic cancer. J Nucl Med 2017; 58(12): 1899-903.
[http://dx.doi.org/10.2967/jnumed.117.198440] [PMID: 29051346]
[11]
Shi Z, Sun R, Yu T, et al. Identification of novel pathways in plant lectin-induced cancer cell apoptosis. Int J Mol Sci 2016; 17(2): 228.
[http://dx.doi.org/10.3390/ijms17020228] [PMID: 26867193]
[12]
Blancafort P, Segal DJ, Barbas CF III. Designing transcription factor architectures for drug discovery. Mol Pharmacol 2004; 66(6): 1361-71.
[http://dx.doi.org/10.1124/mol.104.002758] [PMID: 15340042]
[13]
Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009; 4(1): 44-57.
[http://dx.doi.org/10.1038/nprot.2008.211] [PMID: 19131956]
[14]
Szklarczyk D, Morris JH, Cook H, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res 2017; 45(D1): D362-8.
[http://dx.doi.org/10.1093/nar/gkw937] [PMID: 27924014]
[15]
Al-Harazi O, El Allali A, Colak D. Biomolecular databases and subnetwork identification approaches of interest to big data community: an expert review. OMICS 2019; 23(3): 138-51.
[http://dx.doi.org/10.1089/omi.2018.0205] [PMID: 30883301]
[16]
Reis PP, Waldron L, Perez-Ordonez B, et al. A gene signature in histologically normal surgical margins is predictive of oral carcinoma recurrence. BMC Cancer 2011; 11: 437.
[http://dx.doi.org/10.1186/1471-2407-11-437] [PMID: 21989116]
[17]
Bhosale PG, Cristea S, Ambatipudi S, et al. Chromosomal alterations and gene expression changes associated with the progression of leukoplakia to advanced gingivobuccal cancer. Transl Oncol 2017; 10(3): 396-409.
[http://dx.doi.org/10.1016/j.tranon.2017.03.008] [PMID: 28433800]
[18]
Berman HM, Westbrook J, Feng Z, et al. The protein data bank. Nucleic Acids Res 2000; 28(1): 235-42.
[http://dx.doi.org/10.1093/nar/28.1.235] [PMID: 10592235]
[19]
Pettersen EF, Goddard TD, Huang CC, et al. UCSF Chimera--a visualization system for exploratory research and analysis. J Comput Chem 2004; 25(13): 1605-12.
[http://dx.doi.org/10.1002/jcc.20084] [PMID: 15264254]
[20]
Lang PT, Brozell SR, Mukherjee S, et al. DOCK 6: combining techniques to model RNA-small molecule complexes. RNA 2009; 15(6): 1219-30.
[http://dx.doi.org/10.1261/rna.1563609] [PMID: 19369428]
[21]
Wang ZJ, Wan ZN, Chen XD, et al. In silico identification of novel kinase inhibitors by targeting B-Raf(v660e) from natural products database. J Mol Model 2015; 21(4): 102.
[http://dx.doi.org/10.1007/s00894-015-2647-8] [PMID: 25832798]
[22]
Shi Z, An N, Zhao S, Li X, Bao JK, Yue BS. In silico analysis of molecular mechanisms of legume lectin-induced apoptosis in cancer cells. Cell Prolif 2013; 46(1): 86-96.
[http://dx.doi.org/10.1111/cpr.12009] [PMID: 23294355]
[23]
Graves AP, Shivakumar DM, Boyce SE, Jacobson MP, Case DA, Shoichet BK. Rescoring docking hit lists for model cavity sites: predictions and experimental testing. J Mol Biol 2008; 377(3): 914-34.
[http://dx.doi.org/10.1016/j.jmb.2008.01.049] [PMID: 18280498]
[24]
Fan J, Upadhye S, Worster A. Understanding receiver operating characteristic (ROC) curves. CJEM 2006; 8(1): 19-20.
[http://dx.doi.org/10.1017/S1481803500013336] [PMID: 17175625]
[25]
Sun R, Li X, Li Y, et al. Screening of novel inhibitors targeting lactate dehydrogenase A via four molecular docking strategies and dynamics simulations. J Mol Model 2015; 21(5): 133.
[http://dx.doi.org/10.1007/s00894-015-2675-4] [PMID: 25934158]
[26]
Pronk S, Páll S, Schulz R, et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 2013; 29(7): 845-54.
[http://dx.doi.org/10.1093/bioinformatics/btt055] [PMID: 23407358]
[27]
Tanzawa H, Uzawa K, Kasamatsu A, et al. Targeting gene therapies enhance sensitivity to chemo- and radiotherapy of human oral squamous cell carcinoma. 2015; 12(2): 43-52.
[28]
Neville BW, Day TA. Oral cancer and precancerous lesions. CA Cancer J Clin 2002; 52(4): 195-215.
[http://dx.doi.org/10.3322/canjclin.52.4.195] [PMID: 12139232]
[29]
Vincent-Chong VK, Salahshourifar I, Woo KM, et al. Genome wide profiling in oral squamous cell carcinoma identifies a four genetic marker signature of prognostic significance. PLoS One 2017; 12(4) e0174865
[http://dx.doi.org/10.1371/journal.pone.0174865] [PMID: 28384287]
[30]
Shi Z, Li CY, Zhao S, et al. A systems biology analysis of autophagy in cancer therapy. Cancer Lett 2013; 337(2): 149-60.
[http://dx.doi.org/10.1016/j.canlet.2013.06.004] [PMID: 23791881]
[31]
Chu LH, Chen BS. Construction of a cancer-perturbed protein-protein interaction network for discovery of apoptosis drug targets. BMC Syst Biol 2008; 2: 56.
[http://dx.doi.org/10.1186/1752-0509-2-56] [PMID: 18590547]
[32]
Di Pietro C, Ragusa M, Barbagallo D, et al. The apoptotic machinery as a biological complex system: analysis of its omics and evolution, identification of candidate genes for fourteen major types of cancer, and experimental validation in CML and neuroblastoma. BMC Med Genomics 2009; 2: 20.
[http://dx.doi.org/10.1186/1755-8794-2-20] [PMID: 19402918]
[33]
Ganesan A, Coote ML, Barakat K. Molecular dynamics-driven drug discovery: leaping forward with confidence. Drug Discov Today 2017; 22(2): 249-69.
[http://dx.doi.org/10.1016/j.drudis.2016.11.001] [PMID: 27890821]
[34]
Ekyalongo RC, Yee D. Revisiting the IGF-1R as a breast cancer target. NPJ Precis Oncol 2017; 1 pii: 14
[35]
Costa-Silva DR, da Conceição Barros-Oliveira M, Borges RS, et al. Insulin-like growth factor 1 gene polymorphism in women with breast cancer. Med Oncol 2017; 34(4): 59.
[http://dx.doi.org/10.1007/s12032-017-0915-4] [PMID: 28315227]
[36]
Philippou A, Armakolas A, Koutsilieris M. Evidence for the Possible Biological Significance of the igf-1 Gene Alternative Splicing in Prostate Cancer. Front Endocrinol 2013; 4: 31.
[http://dx.doi.org/10.3389/fendo.2013.00031] [PMID: 23519101]
[37]
Jiang LH, Yuan XL, Yang NY, et al. Daucosterol protects neurons against oxygen-glucose deprivation/reperfusion-mediated injury by activating IGF1 signaling pathway. J Steroid Biochem Mol Biol 2015; 152: 45-52.
[http://dx.doi.org/10.1016/j.jsbmb.2015.04.007] [PMID: 25864625]
[38]
Chao XL, Wang LL, Liu R, Li Y, Zhou XJ. Association between CA repeat polymorphism in IGF1 gene promoter and colorectal cancer risk in a native Chinese population. Neoplasma 2019; 66(6): 1002-8.
[http://dx.doi.org/10.4149/neo_2019_190117N51] [PMID: 31305125]
[39]
Lara OD. Grabbing the Grb2/GAB2 complex in ovarian cancer. Gynecol Oncol 2018; 2(149): 60.
[40]
Giubellino A, Burke TR Jr, Bottaro DP. Grb2 signaling in cell motility and cancer. Expert Opin Ther Targets 2008; 12(8): 1021-33.
[http://dx.doi.org/10.1517/14728222.12.8.1021] [PMID: 18620523]
[41]
Wagner K, Hemminki K, Grzybowska E, et al. The insulin-like growth factor-1 pathway mediator genes: SHC1 Met300Val shows a protective effect in breast cancer. Carcinogenesis 2004; 25(12): 2473-8.
[http://dx.doi.org/10.1093/carcin/bgh263] [PMID: 15308584]
[42]
Yang B, Dong K, Guo P, et al. Identification of key biomarkers and potential molecular mechanisms in oral squamous cell carcinoma by bioinformatics analysis. J Comput Biol 2020; 27(1): 40-54.
[http://dx.doi.org/10.1089/cmb.2019.0211] [PMID: 31424263]
[43]
Dharmawardana PG, Peruzzi B, Giubellino A, Burke TR Jr, Bottaro DP. Molecular targeting of growth factor receptor-bound 2 (Grb2) as an anti-cancer strategy. Anticancer Drugs 2006; 17(1): 13-20.
[http://dx.doi.org/10.1097/01.cad.0000185180.72604.ac] [PMID: 16317285]
[44]
Sun R, Bao MY, Long X, et al. Metabolic gene NR4A1 as a potential therapeutic target for non-smoking female non-small cell lung cancer patients. Thorac Cancer 2019; 10(4): 715-27.
[http://dx.doi.org/10.1111/1759-7714.12989] [PMID: 30806032]
[45]
Fu L, Zhang S, Zhang L, et al. Systems biology network-based discovery of a small molecule activator BL-AD008 targeting AMPK/ZIPK and inducing apoptosis in cervical cancer. Oncotarget 2015; 6(10): 8071-88.
[http://dx.doi.org/10.18632/oncotarget.3513] [PMID: 25797270]
[46]
Shi Z, An N, Lu BM, et al. Identification of novel kinase inhibitors by targeting a kinase-related apoptotic protein-protein interaction network in HeLa cells. Cell Prolif 2014; 47(3): 219-30.
[http://dx.doi.org/10.1111/cpr.12098] [PMID: 24645986]
[47]
Shi Z, Yu T, Sun R, et al. discovery of novel human epidermal growth factor receptor-2 inhibitors by structure-based virtual screening. Pharmacogn Mag 2016; 12(46): 139-44.
[http://dx.doi.org/10.4103/0973-1296.177912] [PMID: 27076751]

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