Asian Pacific Journal of Cancer Prevention

Asian Pacific Journal of Cancer Prevention (아시아태평양암예방학회)
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Screening for Metastatic Osteosarcoma Biomarkers with a DNA Microarray

  • Diao, Chun-Yu (Traumatic Orthopedic Research, Department of Orthopaedics, The Second Xiangya Hospital of Central South University) ;
  • Guo, Hong-Bing (Traumatic Orthopedic Research, Department of Orthopaedics, The Second Xiangya Hospital of Central South University) ;
  • Ouyang, Yu-Rong (Traumatic Orthopedic Research, Department of Orthopaedics, The Second Xiangya Hospital of Central South University) ;
  • Zhang, Han-Cong (Traumatic Orthopedic Research, Department of Orthopaedics, The Second Xiangya Hospital of Central South University) ;
  • Liu, Li-Hong (Traumatic Orthopedic Research, Department of Orthopaedics, The Second Xiangya Hospital of Central South University) ;
  • Bu, Jie (Traumatic Orthopedic Research, Department of Orthopaedics, The Second Xiangya Hospital of Central South University) ;
  • Wang, Zhi-Hua (Chenzhou No.1 People's Hospital) ;
  • Xiao, Tao (Traumatic Orthopedic Research, Department of Orthopaedics, The Second Xiangya Hospital of Central South University)
  • Published : 2014.02.28
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Abstract

Objective: The aim of this study was to screen for possible biomarkers of metastatic osteosarcoma (OS) using a DNA microarray. Methods: We downloaded the gene expression profile GSE49003 from Gene Expression Omnibus database, which included 6 gene chips from metastatic and 6 from non-metastatic OS patients. The R package was used to screen and identify differentially expressed genes (DEGs) between metastatic and non-metastatic OS patients. Then we compared the expression of DEGs in the two groups and sub-grouped into up-regulated and down-regulated, followed by functional enrichment analysis using the DAVID system. Subsequently, we constructed an miRNA-DEG regulatory network with the help of WebGestalt software. Results: A total of 323 DEGs, including 134 up-regulated and 189 down-regulated, were screened out. The up-regulated DEGs were enriched in 14 subcategories and most significantly in cytoskeleton organization, while the down-regulated DEGs were prevalent in 13 subcategories, especially wound healing. In addition, we identified two important miRNAs (miR-202 and miR-9) pivotal for OS metastasis, and their relevant genes, CALD1 and STX1A. Conclusions: MiR-202 and miR-9 are potential key factors affecting the metastasis of OS and CALD1 and STX1A may be possible targets beneficial for the treatment of metastatic OS. However, further experimental studies are needed to confirm our results.

Keywords

References

  1. Amsellem V, Kryszke MH, Hervy M, et al (2005). The actin cytoskeleton-associated protein zyxin acts as a tumor suppressor in Ewing tumor cells. Exp Cell Res, 304, 443-56. https://doi.org/10.1016/j.yexcr.2004.10.035
  2. Bao Y-P, Yi Y, Peng L-L, et al (2013). Roles of microRNA-206 in osteosarcoma pathogenesis and progression. Asian Pac J Cancer Prev, 14, 3751-5. https://doi.org/10.7314/APJCP.2013.14.6.3751
  3. Benjamini Y (2010). Discovering the false discovery rate. J R Stat Soc Series B Stat Methodol, 72, 405-16. https://doi.org/10.1111/j.1467-9868.2010.00746.x
  4. Benjamini Y, Hochberg Y (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol, 289-300.
  5. Breitkreutz BJ, Stark C, Tyers M (2003a). The GRID: The general repository for interaction datasets. Genome Biol, 4, R23. https://doi.org/10.1186/gb-2003-4-3-r23
  6. Breitkreutz BJ, Stark C, Tyers M (2003b). Osprey: a network visualization system. Genome Biol, 4, R22. https://doi.org/10.1186/gb-2003-4-3-r22
  7. Cuomo M E, Knebel A, Platt G, et al (2005). Regulation of microfilament organization by Kaposi sarcoma-associated herpes virus-cyclin.CDK6 phosphorylation of caldesmon. J Biol Chem, 280, 35844-58. https://doi.org/10.1074/jbc.M503877200
  8. Densmore C L, Kleinerman ES, Gautam A, et al (2001). Growth suppression of established human osteosarcoma lung metastases in mice by aerosol gene therapy with PEI-p53 complexes. Cancer Gene Therapy, 8, 619-27. https://doi.org/10.1038/sj.cgt.7700343
  9. Di Cristofano C, Leopizzi M, Miraglia A, et al (2010). Phosphorylated ezrin is located in the nucleus of the osteosarcoma cell. Mod Pathol, 23, 1012-20. https://doi.org/10.1038/modpathol.2010.77
  10. Duncan D, Prodduturi N, Zhang B (2010). WebGestalt2: an updated and expanded version of the Web-based Gene Set Analysis Toolkit. Bmc Bioinformatics, 11, P10. https://doi.org/10.1186/1471-2105-11-S4-P10
  11. Emmrich S, Katsman-Kuipers J, Henke K, et al (2013). miR- 9 is a tumor suppressor in pediatric AML with t (8; 21). Leukemia, ????????
  12. Fan WD, Zhang XQ, Guo HL, et al (2012). Bioinformatics analysis reveals connection of squamous cell carcinoma and adenocarcinoma of the lung. Asian Pac J Cancer Prev, 13, 1477-82. https://doi.org/10.7314/APJCP.2012.13.4.1477
  13. Ferrari S, Smeland S, Mercuri M, et al (2005). Neoadjuvant chemotherapy with high-dose Ifosfamide, high-dose methotrexate, cisplatin, and doxorubicin for patients with localized osteosarcoma of the extremity: a joint study by the Italian and Scandinavian Sarcoma Groups. J Clin Oncol, 23, 8845-52. https://doi.org/10.1200/JCO.2004.00.5785
  14. Hoffman A E, Liu R, Fu A, et al (2013). Targetome profiling, pathway analysis and genetic association study implicate miR-202 in lymphomagenesis. Cancer Epidemiol Biomarkers Prev, 22, 327-36. https://doi.org/10.1158/1055-9965.EPI-12-1131-T
  15. Hu S, Xu C, Guan W, et al (2013). Texture feature extraction based on wavelet transform and gray-level co-occurrence matrices applied to osteosarcoma diagnosis. Biomed Mater Eng, 23, S129-S43.
  16. Huang da W, Sherman BT, Lempicki RA (2009). Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 4, 44-57. https://doi.org/10.1038/nprot.2008.211
  17. Huang G, Nishimoto K, Zhou Z, et al (2012). miR-20a encoded by the miR-17-92 cluster increases the metastatic potential of osteosarcoma cells by regulating Fas expression. Cancer Res, 72, 908-16. https://doi.org/10.1158/0008-5472.CAN-11-1460
  18. Hwang W, Cho YR, Zhang A, Ramanathan M (2006). A novel functional module detection algorithm for protein-protein interaction networks. Algorithms Mol Biol, 1, 24. https://doi.org/10.1186/1748-7188-1-24
  19. Jones K B, Salah Z, Del Mare S, et al (2012). miRNA signatures associate with pathogenesis and progression of osteosarcoma. Cancer Res, 72, 1865-77. https://doi.org/10.1158/0008-5472.CAN-11-2663
  20. Khew-Goodall Y, Goodall GJ (2010). Myc-modulated miR-9 makes more metastases. Nat Cell Biol, 12, 209-11.
  21. Lau SK, Boutros PC, Pintilie M, et al (2007). Three-gene prognostic classifier for early-stage non-small-cell lung cancer. J Clin Oncol, 25, 5562-9. https://doi.org/10.1200/JCO.2007.12.0352
  22. Lu J, Luo H, Liu X, et al (2013). miR-9 targets CXCR4 and functions as a potential tumor suppressor in nasopharyngeal carcinoma. Carcinogenesis, ????????.
  23. Ma L, Young J, Prabhala H, et al (2010). miR-9, a MYC/MYCNactivated microRNA, regulates E-cadherin and cancer metastasis. Nat Cell Biol, 12, 247-56.
  24. Ragland BD, Bell WC, Lopez RR, Siegal GP (2002). Cytogenetics and molecular biology of osteosarcoma. Lab Invest, 82, 365-73. https://doi.org/10.1038/labinvest.3780431
  25. Rao-Bindal K, Rao CK, Yu L, Kleinerman ES (2012). Expression of c-FLIP in pulmonary metastases in osteosarcoma patients and human xenografts. Pediatr Blood Cancer, 60, 575-9.
  26. Ren L, Hong S, Cassavaugh J, et al (2008). The actincytoskeleton linker protein ezrin is regulated during osteosarcoma metastasis by PKC. Oncogene, 28, 792-802.
  27. Salinas-Souza C, De Oliveira R, Alves MT, et al (2013). The metastatic behavior of osteosarcoma by gene expression and cytogenetic analyses. Hum Pathol, 44, 2188-98. https://doi.org/10.1016/j.humpath.2013.04.013
  28. Smyth GK (2005). Limma: linear models for microarray data. Bioinformatics and computational biology solutions using R and Bioconductor. Springer.
  29. Smyth GK, Speed T (2003). Normalization of cDNA microarray data. Methods, 31, 265-73. https://doi.org/10.1016/S1046-2023(03)00155-5
  30. Sun C, Li N, Yang Z, et al (2013). mir-9 regulation of BrcA1 and Ovarian cancer Sensitivity to cisplatin and PArP inhibition. J Natl Cancer Inst, 105, 1750-8. https://doi.org/10.1093/jnci/djt302
  31. Tanay A, Sharan R, Kupiec M, Shamir R (2004). Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data. Proc Natl Acad Sci USA, 101, 2981-6. https://doi.org/10.1073/pnas.0308661100
  32. Thorsen K, Sorensen KD, Brems-Eskildsen AS, et al (2008). Alternative splicing in colon, bladder, and prostate cancer identified by exon array analysis. Mol Cell Proteomics, 7, 1214-24. https://doi.org/10.1074/mcp.M700590-MCP200
  33. Tsao MS, Lau S, Boutros P, et al (2011). Materials and methods for prognosing lung cancer survival. Google Patents.
  34. Willis RC, Hogue CW (2006). Searching, viewing, and visualizing data in the Biomolecular Interaction Network Database (BIND). Curr Protoc Bioinformatics, Chapter 8: Unit 8.9.
  35. Zhang B, Kirov S, Snoddy J (2005). WebGestalt: an integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res, 33, W741-8. https://doi.org/10.1093/nar/gki475
  36. Zhang B, Pan X, Cobb GP, Anderson TA (2007). microRNAs as oncogenes and tumor suppressors. Dev Biol, 302, 1-12. https://doi.org/10.1016/j.ydbio.2006.08.028
  37. Zhang H, Cai X, Wang Y, et al (2010). microRNA-143, down-regulated in osteosarcoma, promotes apoptosis and suppresses tumorigenicity by targeting Bcl-2. Oncol Rep, 24, 1363-9.
  38. Zhao Y, Li C, Wang M, et al (2013). Decrease of miR-202-3p expression, a novel tumor suppressor, in gastric cancer. PloS One, 8, e69756. https://doi.org/10.1371/journal.pone.0069756
  39. Zhou G, Shi X, Zhang J, et al (2013). MicroRNAs in osteosarcoma: From biological players to clinical contributors, a review. J Int Med Res, 41, 1-12. https://doi.org/10.1177/0300060513475959

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