Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2018, Article ID 5238760, 12 pages
https://doi.org/10.1155/2018/5238760
Research Article

Identification of Key Candidate Proteins and Pathways Associated with Temozolomide Resistance in Glioblastoma Based on Subcellular Proteomics and Bioinformatical Analysis

1Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
2The Laboratory for Precision Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
3Department of Neurosurgery, The First Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan 646000, China
4Department of General Intensive Care Unit, The Third Affiliated Hospital of Sun Yat-sen University of Medical Sciences, Guangzhou 510630, China
5Guangdong Provincial Key Laboratory of Molecular Oncologic Pathology, Guangzhou, Guangdong 510515, China
6School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
7Center for Clinical Medical Education, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China
8Nanfang Glioma Center, Guangzhou, Guangdong 510515, China

Correspondence should be addressed to Song-tao Qi; moc.621@yyfnoatgnosiq and Ya-wei Liu; moc.361@kcudpmil

Received 10 October 2017; Revised 11 December 2017; Accepted 28 December 2017; Published 1 March 2018

Academic Editor: Steven De Vleeschouwer

Copyright © 2018 Guo-zhong Yi 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. R. Stupp, W. P. Mason, and M. J. van den Bent, “Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma,” Oncology Times, vol. 27, no. 9, pp. 15-16, 2005. View at Publisher · View at Google Scholar
  2. P. Y. Wen and S. Kesari, “Malignant gliomas in adults,” The New England Journal of Medicine, vol. 359, no. 5, pp. 492–507, 2008. View at Publisher · View at Google Scholar · View at Scopus
  3. D. N. Louis, A. Perry, G. Reifenberger et al., “The world health organization classification of tumors of the central nervous system: a summary,” Acta Neuropathologica, vol. 131, no. 6, pp. 803–820, 2016. View at Publisher · View at Google Scholar
  4. H. S. Friedman, T. Kerby, and H. Calvert, “Temozolomide and treatment of malignant glioma,” Clinical Cancer Research, vol. 6, no. 7, pp. 2585–2597, 2000. View at Google Scholar · View at Scopus
  5. J. N. Sarkaria, G. J. Kitange, C. D. James et al., “Mechanisms of chemoresistance to alkylating agents in malignant glioma,” Clinical Cancer Research, vol. 14, no. 10, pp. 2900–2908, 2008. View at Publisher · View at Google Scholar · View at Scopus
  6. R. Drissi, M.-L. Dubois, and F.-M. Boisvert, “Proteomics methods for subcellular proteome analysis,” FEBS Journal, vol. 280, no. 22, pp. 5626–5634, 2013. View at Publisher · View at Google Scholar · View at Scopus
  7. H. Wang, W. Feng, Y. Lu et al., “Expression of dynein, cytoplasmic 2, heavy chain 1 (DHC2) associated with glioblastoma cell resistance to temozolomide,” Scientific Reports, vol. 6, Article ID 28948, 2016. View at Publisher · View at Google Scholar · View at Scopus
  8. Y. Lu, L. Xiao, Y. Liu et al., “MIR517C inhibits autophagy and the epithelialto- mesenchymal (-like) transition phenotype in human glioblastoma through KPNA2-dependent disruption of TP53 nuclear translocation,” Autophagy, vol. 11, no. 12, pp. 2213–2232, 2015. View at Publisher · View at Google Scholar · View at Scopus
  9. G.-Z. Yi, Y.-W. Liu, W. Xiang et al., “Akt and β-catenin contribute to TMZ resistance and EMT of MGMT negative malignant glioma cell line,” Journal of the Neurological Sciences, vol. 367, pp. 101–106, 2016. View at Publisher · View at Google Scholar · View at Scopus
  10. J. R. Wisniewski, “Quantitative evaluation of filter aided sample preparation (fasp) and multienzyme digestion FASP protocols,” Analytical Chemistry, vol. 88, no. 10, pp. 5438–5443, 2016. View at Publisher · View at Google Scholar · View at Scopus
  11. J. Rappsilber, Y. Ishihama, and M. Mann, “Stop and Go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics,” Analytical Chemistry, vol. 75, no. 3, pp. 663–670, 2003. View at Publisher · View at Google Scholar · View at Scopus
  12. J. Cox, N. Neuhauser, A. Michalski, R. A. Scheltema, J. V. Olsen, and M. Mann, “Andromeda: a peptide search engine integrated into the MaxQuant environment,” Journal of Proteome Research, vol. 10, no. 4, pp. 1794–1805, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Cox, M. Y. Hein, C. A. Luber, I. Paron, N. Nagaraj, and M. Mann, “Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ,” Molecular & Cellular Proteomics, vol. 13, no. 9, pp. 2513–2526, 2014. View at Publisher · View at Google Scholar · View at Scopus
  14. A. Franceschini, D. Szklarczyk, S. Frankild et al., “String v9.1: protein-protein interaction networks, with increased coverage and integration,” Nucleic Acids Research, vol. 41, no. 1, pp. D808–D815, 2013. View at Publisher · View at Google Scholar · View at Scopus
  15. P. Shannon, A. Markiel, O. Ozier et al., “Cytoscape: a software environment for integrated models of biomolecular interaction networks,” Genome Research, vol. 13, no. 11, pp. 2498–2504, 2003. View at Publisher · View at Google Scholar · View at Scopus
  16. S. Reuveni, M. Ehrenberg, and J. Paulsson, “Ribosomes are optimized for autocatalytic production,” Nature, vol. 547, no. 7663, pp. 293–297, 2017. View at Publisher · View at Google Scholar · View at Scopus
  17. D. Simsek, G. C. Tiu, R. A. Flynn et al., “The mammalian ribo-interactome reveals ribosome functional diversity and heterogeneity,” Cell, vol. 169, no. 6, pp. 1051–1065.e18, 2017. View at Publisher · View at Google Scholar · View at Scopus
  18. N. Nag, K. Y. Lin, K. A. Edmonds et al., “EIF1A/eIF5B interaction network and its functions in translation initiation complex assembly and remodeling,” Nucleic Acids Research, vol. 44, no. 15, pp. 7441–7456, 2016. View at Publisher · View at Google Scholar · View at Scopus
  19. X. M. Zheng, D. Black, P. Chambon, and J. M. Egly, “Sequencing and expression of complementary DNA for the general transcription factor BTF3,” Nature, vol. 344, no. 6266, pp. 556–559, 1990. View at Publisher · View at Google Scholar · View at Scopus
  20. R. Jain, P. Kulkarni, S. Dhali, S. Rapole, and S. Srivastava, “Quantitative proteomic analysis of global effect of LLL12 on U87 cell's proteome: an insight into the molecular mechanism of LLL12,” Journal of Proteomics, vol. 113, pp. 127–142, 2015. View at Publisher · View at Google Scholar · View at Scopus
  21. R. K. Swoboda, R. Somasundaram, L. Caputo et al., “Shared MHC class II-dependent melanoma ribosomal protein L8 identified by phage display,” Cancer Research, vol. 67, no. 8, pp. 3555–3559, 2007. View at Publisher · View at Google Scholar · View at Scopus
  22. A. Russo, A. Saide, S. Smaldone, R. Faraonio, and G. Russo, “Role of uL3 in multidrug resistance in p53-mutated lung cancer cells,” International Journal of Molecular Sciences, vol. 18, no. 3, article no. 547, 2017. View at Publisher · View at Google Scholar · View at Scopus
  23. A. Russo and G. Russo, “Ribosomal proteins control or bypass p53 during nucleolar stress,” International Journal of Molecular Sciences, vol. 18, no. 1, p. 140, 2017. View at Publisher · View at Google Scholar
  24. L. Fancello, K. R. Kampen, I. J. F. Hofman, J. Verbeeck, and K. De Keersmaecker, “The ribosomal protein gene RPL5 is a haploinsufficient tumor suppressor in multiple cancer types,” Oncotarget , vol. 8, no. 9, pp. 14462–14478, 2017. View at Publisher · View at Google Scholar · View at Scopus
  25. A. R. Kornblihtt, I. E. Schor, M. Alló, G. Dujardin, E. Petrillo, and M. J. Muñoz, “Alternative splicing: a pivotal step between eukaryotic transcription and translation,” Nature Reviews Molecular Cell Biology, vol. 14, no. 3, pp. 153–165, 2013. View at Publisher · View at Google Scholar · View at Scopus
  26. J. Zhang and J. L. Manley, “Misregulation of pre-mRNA alternative splicing in cancer,” Cancer Discovery, vol. 3, no. 11, pp. 1228–1237, 2013. View at Publisher · View at Google Scholar · View at Scopus
  27. C. Heintz, T. K. Doktor, A. Lanjuin et al., “Splicing factor 1 modulates dietary restriction and TORC1 pathway longevity in C. elegans,” Nature, vol. 541, no. 7635, pp. 102–106, 2017. View at Publisher · View at Google Scholar · View at Scopus
  28. C. M. Nefzger and J. M. Polo, “DEAD-Box RNA binding protein DDX5: not a black-box during reprogramming,” Cell Stem Cell, vol. 20, no. 4, pp. 419-420, 2017. View at Publisher · View at Google Scholar · View at Scopus
  29. A. Fukuda, T. Nakadai, M. Shimada, and K. Hisatake, “Heterogeneous nuclear ribonucleoprotein R enhances transcription from the naturally configured c-fos promoter in Vitro,” The Journal of Biological Chemistry, vol. 284, no. 35, pp. 23472–23480, 2009. View at Publisher · View at Google Scholar · View at Scopus
  30. X. Fang, J.-G. Yoon, L. Li et al., “Landscape of the SOX2 protein-protein interactome,” Proteomics, vol. 11, no. 5, pp. 921–934, 2011. View at Publisher · View at Google Scholar · View at Scopus
  31. T. Lee and J. Pelletier, “The biology of its potential as a therapeutic target,” Oncotarget, vol. 7, no. 27, pp. 42716–42739, 2016. View at Google Scholar
  32. M. Fidaleo, F. Svetoni, E. Volpe, B. Miñana, D. Caporossi, and M. P. Paronetto, “Genotoxic stress inhibits ewing sarcoma cell growth by modulating alternative pre-mRNA processing of the RNA helicase DHX9,” Oncotarget , vol. 6, no. 31, pp. 31740–31757, 2015. View at Publisher · View at Google Scholar · View at Scopus