Table of Contents Author Guidelines Submit a Manuscript
Corrigendum

A corrigendum for this article has been published. To view the corrigendum, please click here.

Computational and Mathematical Methods in Medicine
Volume 2017, Article ID 9803018, 8 pages
https://doi.org/10.1155/2017/9803018
Research Article

Biomarker MicroRNAs for Diagnosis of Oral Squamous Cell Carcinoma Identified Based on Gene Expression Data and MicroRNA-mRNA Network Analysis

1Guanghua School of Stomatology, Affiliated Stomatological Hospital, Guangdong Province Key Laboratory of Stomatology, Guangdong, China
2Oral and Maxillofacial Center, Kiang Wu Hospital, Macau

Correspondence should be addressed to Xiangya Huang; nc.ude.usys.liam@aygnaixh

Received 22 May 2017; Revised 1 August 2017; Accepted 6 August 2017; Published 17 September 2017

Academic Editor: Xiaofeng Song

Copyright © 2017 Hui Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Q. Wang, P. Gao, X. Wang, and Y. Duan, “Investigation and identification of potential biomarkers in human saliva for the early diagnosis of oral squamous cell carcinoma,” Clinica Chimica Acta, vol. 427, pp. 79–85, 2014. View at Publisher · View at Google Scholar · View at Scopus
  2. C.-C. Chang, Y.-J. Yang, Y.-J. Li et al., “MicroRNA-17/20a functions to inhibit cell migration and can be used a prognostic marker in oral squamous cell carcinoma,” Oral Oncology, vol. 49, no. 9, pp. 923–931, 2013. View at Publisher · View at Google Scholar · View at Scopus
  3. Y. Li, B. Li, B. Xu et al., “Expression of p53, p21(CIP1/WAF1) and eIF4E in the adjacent tissues of oral squamous cell carcinoma: establishing the molecular boundary and a cancer progression model,” International Journal of Oral Science, vol. 7, no. 3, pp. 161–168, 2015. View at Publisher · View at Google Scholar · View at Scopus
  4. R. Subapriya, A. Thangavelu, B. Mathavan, C. R. Ramachandran, and S. Nagini, “Assessment of risk factors for oral squamous cell carcinoma in Chidambaram, southern India: a case-control study,” European Journal of Cancer Prevention, vol. 16, no. 3, pp. 251–256, 2007. View at Publisher · View at Google Scholar · View at Scopus
  5. H.-B. Santos, T.-K. dos Santos, A.-R. Paz et al., “Clinical findings and risk factors to oral squamous cell carcinoma in young patients: A 12-year retrospective analysis,” Medicina Oral, Patologia Oral y Cirugia Bucal, vol. 21, no. 2, pp. e151–e156, 2016. View at Publisher · View at Google Scholar · View at Scopus
  6. Y. Tang, W. Yan, J. Chen, C. Luo, A. Kaipia, and B. Shen, “Identification of novel microRNA regulatory pathways associated with heterogeneous prostate cancer,” BMC Systems Biology, vol. 7, supplement 3, article S6, 2013. View at Publisher · View at Google Scholar · View at Scopus
  7. Y. W. Kong, D. Ferland-McCollough, T. J. Jackson, and M. Bushell, “microRNAs in cancer management,” The Lancet Oncology, vol. 13, no. 6, pp. e249–e258, 2012. View at Publisher · View at Google Scholar · View at Scopus
  8. L. Shen, Y. Lin, Z. Sun, X. Yuan, L. Chen, and B. Shen, “Knowledge-guided bioinformatics model for identifying autism spectrum disorder diagnostic microrna biomarkers,” Scientific Reports, vol. 6, article 39663, 2016. View at Publisher · View at Google Scholar
  9. X.-M. Zhao, K.-Q. Liu, G. Zhu et al., “Identifying cancer-related microRNAs based on gene expression data,” Bioinformatics, vol. 31, no. 8, pp. 1226–1234, 2015. View at Publisher · View at Google Scholar · View at Scopus
  10. G.-M. Qin, R.-Y. Li, and X.-M. Zhao, “Identifying Disease Associated miRNAs Based on Protein Domains,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 13, no. 6, pp. 1027–1035, 2016. View at Publisher · View at Google Scholar · View at Scopus
  11. S. Becker, A. Florian, A. Patrascu et al., “Identification of cardiomyopathy associated circulating miRNA biomarkers in patients with muscular dystrophy using a complementary cardiovascular magnetic resonance and plasma profiling approach,” Journal of Cardiovascular Magnetic Resonance, vol. 18, no. 1, article no. 244, 2016. View at Publisher · View at Google Scholar · View at Scopus
  12. I. Fukumoto, K. Koshizuka, T. Hana Zawa et al., “The tumor-suppressive microRNA-23b/27b cluster regulates the MET oncogene in oral squamous cell carcinoma,” International Journal of Oncology, vol. 49, no. 3, pp. 1119–1129, 2016. View at Publisher · View at Google Scholar · View at Scopus
  13. G. Zeng, W. Xun, K. Wei, Y. Yang, and H. Shen, “MicroRNA-27a-3p regulates epithelial to mesenchymal transition via targeting YAP1 in oral squamous cell carcinoma cells,” Oncology Reports, vol. 36, no. 3, pp. 1475–1482, 2016. View at Publisher · View at Google Scholar · View at Scopus
  14. S.-Y. Wu, A. T. H. Wu, and S.-H. Liu, “Microrna-17-5p regulated apoptosis-related protein expression and radiosensitivity in oral squamous cell carcinoma caused by betel nut chewing,” Oncotarget, vol. 7, no. 32, pp. 51482–51493, 2016. View at Publisher · View at Google Scholar · View at Scopus
  15. P. Xu, Y. Li, H. Zhang, M. Li, and H. Zhu, “MicroRNA-340 Mediates Metabolic Shift in Oral Squamous Cell Carcinoma by Targeting Glucose Transporter-1,” Journal of Oral and Maxillofacial Surgery, vol. 74, no. 4, pp. 844–850, 2016. View at Publisher · View at Google Scholar · View at Scopus
  16. Z. Liu, C. Diep, T. Mao et al., “MicroRNA-92b promotes tumor growth and activation of NF-κB signaling via regulation of NLK in oral squamous cell carcinoma,” Oncology Reports, vol. 34, no. 6, pp. 2961–2968, 2015. View at Publisher · View at Google Scholar · View at Scopus
  17. W. Ren, C. Qiang, L. Gao et al., “Circulating microRNA-21 (MIR-21) and phosphatase and tensin homolog (PTEN) are promising novel biomarkers for detection of oral squamous cell carcinoma,” Biomarkers, vol. 19, no. 7, pp. 590–596, 2014. View at Publisher · View at Google Scholar · View at Scopus
  18. W. Yan, L. Xu, Z. Sun et al., “MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model,” Oncotarget, vol. 6, no. 28, pp. 26424–26436, 2015. View at Publisher · View at Google Scholar · View at Scopus
  19. W. Zhang, J. Zang, X. Jing et al., “Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer,” Journal of Translational Medicine, vol. 12, article 66, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. J. Zhu, S. Wang, W. Zhang et al., “Screening key microRNAs for castration-resistant prostate cancer based on miRNA/mRNA functional synergistic network,” Oncotarget, vol. 6, no. 41, pp. 43819–43830, 2015. View at Publisher · View at Google Scholar · View at Scopus
  21. J. Chen, D. Zhang, W. Zhang et al., “Clear cell renal cell carcinoma associated microRNA expression signatures identified by an integrated bioinformatics analysis,” Journal of Translational Medicine, vol. 11, no. 1, article 169, 2013. View at Publisher · View at Google Scholar · View at Scopus
  22. T. Barrett, T. O. Suzek, D. B. Troup et al., “NCBI GEO: mining millions of expression profiles—database and tools,” Nucleic Acids Research, vol. 33, pp. D562–D566, 2005. View at Publisher · View at Google Scholar · View at Scopus
  23. C. Chen, E. Méndez, J. Houck et al., “Gene expression profiling identifies genes predictive of oral squamous cell carcinoma,” Cancer Epidemiology Biomarkers and Prevention, vol. 17, no. 8, pp. 2152–2162, 2008. View at Publisher · View at Google Scholar · View at Scopus
  24. H. M. Jung, B. L. Phillips, R. S. Patel et al., “Keratinization-associated miR-7 and miR-21 regulate tumor suppressor reversion-inducing cysteine-rich protein with kazal motifs (RECK) in oral cancer,” The Journal of Biological Chemistry, vol. 287, no. 35, pp. 29261–29272, 2012. View at Publisher · View at Google Scholar · View at Scopus
  25. G. K. Smyth, “Linear models and empirical Bayes methods for assessing differential expression in microarray experiments,” Statistical Applications in Genetics and Molecular Biology, vol. 3, Art. 3, 29 pages, 2004. View at Publisher · View at Google Scholar · View at MathSciNet
  26. M. E. Ritchie, B. Phipson, D. Wu et al., “limma powers differential expression analyses for RNA-sequencing and microarray studies,” Nucleic Acids Research, 2015. View at Publisher · View at Google Scholar
  27. F. Xiao, Z. Zuo, G. Cai, S. Kang, X. Gao, and T. Li, “miRecords: an integrated resource for microRNA-target interactions,” Nucleic Acids Research, vol. 37, no. 1, pp. D105–D110, 2009. View at Publisher · View at Google Scholar · View at Scopus
  28. P. Sethupathy, B. Corda, and A. G. Hatzigeorgiou, “TarBase: a comprehensive database of experimentally supported animal microRNA targets,” RNA, vol. 12, no. 2, pp. 192–197, 2006. View at Publisher · View at Google Scholar · View at Scopus
  29. Q. Jiang, Y. Wang, Y. Hao et al., “miR2Disease: a manually curated database for microRNA deregulation in human disease,” Nucleic Acids Research, vol. 37, no. 1, pp. D98–D104, 2009. View at Publisher · View at Google Scholar · View at Scopus
  30. S.-D. Hsu, F.-M. Lin, W.-Y. Wu et al., “MiRTarBase: a database curates experimentally validated microRNA-target interactions,” Nucleic Acids Research, vol. 39, supplement 1, pp. D163–D169, 2011. View at Publisher · View at Google Scholar · View at Scopus
  31. V. A. Gennarino, M. Sardiello, R. Avellino et al., “MicroRNA target prediction by expression analysis of host genes,” Genome Research, vol. 19, no. 3, pp. 481–490, 2009. View at Publisher · View at Google Scholar · View at Scopus
  32. E. R. Gamazon, H.-K. Im, S. Duan et al., “ExprTarget: an integrative approach to predicting human microRNA targets,” PLoS ONE, vol. 5, no. 10, Article ID e13534, 2010. View at Publisher · View at Google Scholar · View at Scopus
  33. J.-H. Yang, J.-H. Li, P. Shao, H. Zhou, Y.-Q. Chen, and L.-H. Qu, “StarBase: a database for exploring microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data,” Nucleic Acids Research, vol. 39, no. 1, pp. D202–D209, 2011. View at Publisher · View at Google Scholar · View at Scopus
  34. G. Dennis Jr. et al., “DAVID: database for annotation, visualization, and integrated discovery,” Genome Biology, vol. 4, no. 5, 2003. View at Google Scholar
  35. M. I. Rather, M. N. Nagashri, S. S. Swamy, K. S. Gopinath, and A. Kumar, “Oncogenic microRNA-155 down-regulates tumor suppressor CDC73 and promotes oral squamous cell carcinoma cell proliferation: implications for cancer therapeutics,” Journal of Biological Chemistry, vol. 288, no. 1, pp. 608–618, 2013. View at Publisher · View at Google Scholar · View at Scopus
  36. O. Baba, S. Hasegawa, H. Nagai et al., “MicroRNA-155-5p is associated with oral squamous cell carcinoma metastasis and poor prognosis,” Journal of Oral Pathology and Medicine, vol. 45, no. 4, pp. 248–255, 2016. View at Publisher · View at Google Scholar · View at Scopus
  37. E. Sasabe, Z. Yang, S. Ohno, and T. Yamamoto, “Reactive oxygen species produced by the knockdown of manganese-superoxide dismutase up-regulate hypoxia-inducible factor-1α expression in oral squamous cell carcinoma cells,” Free Radical Biology and Medicine, vol. 48, no. 10, pp. 1321–1329, 2010. View at Publisher · View at Google Scholar · View at Scopus
  38. K.-F. Hua, P.-C. Liao, Z. Fang et al., “Generation of Reactive Oxygen Species by Polyenylpyrroles Derivatives Causes DNA Damage Leading to G2/M Arrest and Apoptosis in Human Oral Squamous Cell Carcinoma Cells,” PLoS ONE, vol. 8, no. 6, Article ID e67603, 2013. View at Publisher · View at Google Scholar · View at Scopus
  39. M. Czesnikiewicz-Guzik, B. Lorkowska, J. Zapala et al., “NADPH oxidase and uncoupled nitric oxide synthase are major sources of reactive oxygen species in oral squamous cell carcinoma. Potential implications for immune regulation in high oxidative stress conditions,” Journal of Physiology and Pharmacology, vol. 59, no. 1, pp. 139–152, 2008. View at Google Scholar · View at Scopus
  40. P. Li, L. Y. Xiao, and H. Tan, “Muc-1 promotes migration and invasion of oral squamous cell carcinoma cells via PI3K-Akt signaling,” International Journal of Clinical and Experimental Pathology, vol. 8, no. 9, pp. 10365–10374, 2015. View at Google Scholar
  41. Y.-M. Ding, J.-H. Dong, L.-L. Chen, and H.-D. Zhang, “Increased expression of galectin-1 is associated with human oral squamous cell carcinoma development,” Oncology Reports, vol. 21, no. 4, pp. 983–987, 2009. View at Publisher · View at Google Scholar · View at Scopus
  42. S. Aggarwal, S. C. Sharma, and S. N. Das, “Galectin-1 and galectin-3: Plausible tumour markers for oral squamous cell carcinoma and suitable targets for screening high-risk population,” Clinica Chimica Acta, vol. 442, pp. 13–21, 2015. View at Publisher · View at Google Scholar · View at Scopus
  43. K. Ueda, “Heparin induces apoptosis through suppression of AKt in oral squamous cell carcinoma cells,” Anticancer Research, vol. 29, no. 4, pp. 1079–1088, 2009. View at Google Scholar
  44. S. Mori, M. Nose, H. Morikawa et al., “A novel evaluation system of metastatic potential of oral squamous cell carcinoma according to the histopathological and histochemical grading,” Oral Oncology, vol. 34, no. 6, pp. 549–557, 1998. View at Publisher · View at Google Scholar · View at Scopus
  45. Y. Kimura, A. Kasamatsu, D. Nakashima et al., “ARNT2 regulates tumoral growth in oral squamous cell carcinoma,” Journal of Cancer, vol. 7, no. 6, pp. 702–710, 2016. View at Publisher · View at Google Scholar · View at Scopus
  46. E. A. Stanford, A. Ramirez-Cardenas, Z. Wang et al., “Role for the aryl hydrocarbon receptor and diverse ligands in oral squamous cell carcinoma migration and tumorigenesis,” Molecular Cancer Research, vol. 14, no. 8, pp. 696–706, 2016. View at Publisher · View at Google Scholar · View at Scopus
  47. X. Xie, Y. Jiang, Y. Yuan et al., “MALDI imaging reveals NCOA7 as a potential biomarker in oral squamous cell carcinoma arising from oral submucous fibrosis,” Oncotarget, vol. 7, no. 37, pp. 59987–60004, 2016. View at Publisher · View at Google Scholar · View at Scopus
  48. S. Klosek, K. Nakashiro, S. Hara, C. Li, S. Shintani, and H. Hamakawa, “Constitutive activation of Stat3 correlates with increased expression of the c-Met/HGF receptor in oral squamous cell carcinoma,” Oncology Reports, 2004. View at Publisher · View at Google Scholar
  49. H. Borgiel-Marek, B. Marek, I. Niedzielska, and D. Kajdaniuk, “Serum concentration of fibroblastic growth factor in oral squamous cell carcinoma before and after surgery,” International Journal of Oral and Maxillofacial Surgery, vol. 38, no. 5, p. 537, 2009. View at Publisher · View at Google Scholar
  50. Z. Liu, Y. Niu, C. Li, Y. Yang, and C. Gao, “Integrating multiple microarray datasets on oral squamous cell carcinoma to reveal dysregulated networks,” Head and Neck, vol. 34, no. 12, pp. 1789–1797, 2012. View at Publisher · View at Google Scholar · View at Scopus
  51. Y. He, F. Shao, W. Pi et al., “Largescale transcriptomics analysis suggests over-expression of BGH3, MMP9 and PDIA3 in oral squamous cell carcinoma,” PLoS ONE, vol. 11, no. 1, Article ID e0146530, 2016. View at Publisher · View at Google Scholar · View at Scopus
  52. M. M. Bakri, H. M. Hussaini, A. Holmes, R. D. Cannon, and A. M. Rich, “Revisiting the association between candidal infection and carcinoma, particularly oral squamous cell carcinoma,” Journal of Oral Microbiology, vol. 2, no. 2010, article no. 5780, 2010. View at Publisher · View at Google Scholar · View at Scopus
  53. F.-M. Fang, C.-F. Li, H.-Y. Huang et al., “Overexpression of a chromatin remodeling factor, RSF-1/HBXAP, correlates with aggressive oral squamous cell carcinoma,” American Journal of Pathology, vol. 178, no. 5, pp. 2407–2415, 2011. View at Publisher · View at Google Scholar · View at Scopus
  54. B. Li et al., “[Assessment of mental health status in oral squamous cell carcinoma patients and its correlation with catecholamines level],” Shanghai Kou Qiang Yi Xue, vol. 22, no. 6, pp. 671–675, 2013. View at Google Scholar