Document Type: Original Research


1 Applied Microbiology Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran

2 Department of Microbiology, College of Basic Sciences, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran


Background & Objective: A main contest in chemotherapy is to obtain regulator above the biodistribution of cytotoxic drugs. The utmost promising strategy comprises of drugs coupled with a tumor-targeting bearer that results in wide cytotoxic activity and particular delivery. The B-subunit of Shiga toxin (STxB) is nontoxic and possesses low immunogenicity that exactly binds to the globotriaosylceramide (Gb3/CD77). Gb3/CD77 extremely expresses on a number of human tumors such as pancreatic, colon, and breast cancer and acts as a functional receptor for Shiga toxin (STx). Then, this toxin can be applied to target Gb3-positive human tumors. In this study, we evaluated DT390-STXB chimeric protein as a new anti-tumor candidate via genetically fusing the DT390 fragment of DT538 (Native diphtheria toxin) to STxB.
Methods: This study intended to investigate the DT390- STxB fusion protein structure in silico. Considering the Escherichia coli codon usage, the genomic construct was designed. The properties and the structure of the protein were determined by an in silico technique. The mRNA structure and the physicochemical characteristics, construction, and the stability of the designed chimeric protein were analyzed using computational and bioinformatics tools and servers. Hence, the GOR4 and I-TASSER online web servers were used to predict the secondary and tertiary structures of the designed protein.
Results: The results demonstrated that codon adaptation index (CAI) of dt390-stxB chimeric gene raised from 0.6 in the wild type to 0.9 in the chimeric optimized gene. The mfold data revealed that the dt390-stxB mRNA was completely stable to be translated effectively in the novel host. The normal activity of the fusion protein determined by considering the secondary and tertiary structure of each construct. Energy calculation data indicated that the thermodynamic ensemble for mRNA structure was -427.40 kJ/mol. The stability index (SI) of DT390-STxB was 36.95, which is quite appropriate to preserve the stability of the construct. Ultimately, the DT390-STxB was classified as a steady fusion protein according to the Ramachandran plot.
Conclusion: Our results showed that DT390-STXB was a stable chimeric protein and it can be recruited as a candidate of novel anti-tumor agents for the development of breast cancer treatment.


Main Subjects

  1. Hutchinson AD, Hosking JR, Kichenadasse G, Mattiske JK, Wilson C. Objective and subjective cognitive impairment following chemotherapy for cancer: a systematic review. Cancer treatment reviews. 2012;38(7):926-34. [DOI:10.1016/j.ctrv.2012.05.002] [PMID]
  2. Sui X, Chen R, Wang Z, Huang Z, Kong N, Zhang M, et al. Autophagy and chemotherapy resistance: a promising therapeutic target for cancer treatment. Cell death & disease. 2013;4(10):e838. [DOI:10.1038/cddis.2013.350] [PMID] [PMCID]
  3. Sharkey RM, Goldenberg DM. Targeted therapy of cancer: new prospects for antibodies and immunoconjugates. CA: A Cancer Journal for Clinicians. 2006;56(4):226-43. [DOI:10.3322/canjclin.56.4.226] [PMID]
  4. Jain KK. Use of bacteria as anticancer agents. Expert Opinion on Biological Therapy. 2001;1(2):291-300. [DOI:10.1517/14712598.1.2.291] [PMID]
  5. Frankel AE. Methods for treating acute myeloid leukemia with diphtheria toxin-interleukin-3 conjugates. Google Patents; 2013.
  6. Frankel AE. Methods and compositions based on diphtheria toxin-interleukin-3 conjugates. Google Patents; 2015.
  7. Prince HM, Newland KM. Denileukin diftitox for the treatment of cutaneous T-cell lymphoma. Expert Opinion on Orphan Drugs. 2014;2(6):625-34. [DOI:10.1517/21678707.2014.912580]
  8. Zhan C, Li C, Wei X, Lu W, Lu W. Toxins and derivatives in molecular pharmaceutics: drug delivery and targeted therapy. Advanced drug delivery reviews. 2015;90:101-18. [DOI:10.1016/j.addr.2015.04.025] [PMID]
  9. Schubert I. Diphtheria Toxin Based Molecules as Therapeutic Approaches. Corynebacterium diphtheriae and Related Toxigenic Species: Springer; 2014. p. 277-90. [DOI:10.1007/978-94-007-7624-1_15]
  10. Williams D, Parker K, Bacha P, Bishai W, Borowski M, Genbauffe F, et al. Diphtheria toxin receptor binding domain substitution with interleukin-2: genetic construction and properties of a diphtheria toxin-related interleukin-2 fusion protein. Protein engineering. 1987;1(6):493-8. [DOI:10.1093/protein/1.6.493] [PMID]
  11. Chan YS, Ng TB. Shiga toxins: from structure and mechanism to applications. Applied microbiology and biotechnology. 2016;100(4):1597-610. [DOI:10.1007/s00253-015-7236-3] [PMID]
  12. LaCasse E, Bray M, Patterson B, Lim W-M, Perampalam S, Radvanyi L, et al. Shiga-like toxin-1 receptor on human breast cancer, lymphoma, and myeloma and absence from CD34+ hematopoietic stem cells: implications for ex vivo tumor purging and autologous stem cell transplantation. Blood. 1999;94(8):2901-10.
  13. Gaston MA, Pellino CA, Weiss AA. Failure of manganese to protect from Shiga toxin. PloS one. 2013;8(7):e69823. [DOI:10.1371/journal.pone.0069823] [PMID] [PMCID]
  14. Haicheur N, Bismuth E, Bosset S, Adotevi O, Warnier G, Lacabanne V, et al. The B subunit of Shiga toxin fused to a tumor antigen elicits CTL and targets dendritic cells to allow MHC class I-restricted presentation of peptides derived from exogenous antigens. The Journal of Immunology. 2000;165(6):3301-8. [DOI:10.4049/jimmunol.165.6.3301] [PMID]
  15. Geyer PE, Maak M, Nitsche U, Perl M, Novotny A, Slotta-Huspenina J, et al. Gastric adenocarcinomas express the glycosphingolipid Gb3/CD77: Targeting of gastric cancer cells with Shiga toxin B-subunit. Molecular cancer therapeutics. 2016;15(5):1008-17. [DOI:10.1158/1535-7163.MCT-15-0633] [PMID]
  16. Ishitoya S, Kurazono H, Nishiyama H, Nakamura E, Kamoto T, Habuchi T, et al. Verotoxin induces rapid elimination of human renal tumor xenografts in SCID mice. The Journal of urology. 2004;171(3):1309-13. [DOI:10.1097/01.ju.0000100110.11129.85] [PMID]
  17. Batisse C, Dransart E, Sarkouh RA, Brulle L, Bai S-K, Godefroy S, et al. A new delivery system for auristatin in StxB-drug conjugate therapy. European journal of medicinal chemistry. 2015;95:483-91. [DOI:10.1016/j.ejmech .2015.03.047] [PMID]
  18. Doolittle ED. Methods in Enzymology, RF. 1996. p. 540-53.
  19. Puigbo P, Guzman E, Romeu A, Garcia-Vallve S. OPTIMIZER: a web server for optimizing the codon usage of DNA sequences. Nucleic Acids Res 2007;35:W126-131 [DOI:10.1093/nar/gkm219] [PMID] [PMCID]
  20. Puigbo P, Romeu A, Garcia-Vallve S. HEG-DB: a database of predicted highly expressed genes in prokaryotic complete genomes under translational selection. Nucleic Acids Res 2008;36:D524-527. [DOI:10.1093/nar/gkm831] [PMID] [PMCID]
  21. Irini A. D, and Darren R. F. Bioinformatic Approach for Identifying Parasite and Fungal Candidate Subunit Vaccines. The Open Vaccine Journal. 2008; 1: 22-26. [DOI:10.2174/1875035400801010022]
  22. Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 2003;31:3406-3415. [DOI:10.1093/nar/gkg595] [PMID] [PMCID]
  23. Amala S. In silico Analysis and 3D Modeling of ASAH1 Protein in Farber Lipogranulomatosis. Advanced Biotech 2010;10(6):6-8.
  24. Garnier J, Gibrat JF, Robson B. Methods in Enzymology. Ed RFD, editor1996.
  25. Zhang Y. I-TASSER server for protein 3D structure prediction [Research Support, Non-U.S. Gov't]. 2008 [cited 9]. 2008/01/25:[40]. Available from: http://www.ncbi. [DOI:10.1186/1471-2105-9-40] [PMID] [PMCID]
  26. Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein sztructure and function prediction. Nat Protoc 2010;5:725-738. [DOI:10.1038/nprot.2010.5] [PMID] [PMCID]
  27. Roy A, Yang J, Zhang Y. COFACTOR: an accurate comparative algorithm for structure-based protein function annotation. Nucleic Acids Res 2012;40:W471-477. [DOI:10.1093/nar/gks372] [PMID] [PMCID]
  28. Kelley LA, Sternberg MJ. Protein structure prediction on the Web: a case study using the Phyre server. Nat Protoc 2009;4:363-371. [DOI:10.1038/nprot.2009.2] [PMID]
  29. Guex N, Peitsch MC. SWISS‐MODEL and the Swiss‐Pdb Viewer: an environment for comparative protein modeling. electrophoresis. 1997;18(15):2714-23. [DOI:10.1002/elps.1150181505] [PMID]
  30. Ahmad S, Gromiha M, Fawareh H, Sarai A. ASAView: database and tool for solvent accessibility representation in proteins. BMC bioinformatics. 2004;5(1):51. [DOI:10.1186/1471-2105-5-51] [PMID] [PMCID]
  31. Lovell SC, Davis IW, Arendall WB 3rd, de Bakker PI, Word JM, Prisant MG, Richardson JS, and et al. Structure validation by Calpha geometry: phi,psi and Cbeta deviation. Proteins 2003;50:437-450. [DOI:10.1002/prot.10286] [PMID]
  32. Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35: 407-10. [DOI:10.1093/nar/gkm290] [PMID] [PMCID]
  33. Shaw J, Akiyoshi DE, Arrigo DA, Rhoad AE, Sullivan B, Thomas J, et al. Cytotoxic properties of DAB486EGF and DAB389EGF, epidermal growth factor (EGF) receptor-targeted fusion toxins. Journal of Biological Chemistry. 1991;266(31):21118-24.
  34. Cawley DB, Herschman HR, Gilliland DG, Collier RJ. Epidermal growth factor-toxin A chain conjugates: EGF-ricin A is a potent toxin while EGF-diphtheria fragment A is nontoxic. Cell. 1980;22(2):563-70. [DOI:10.1016/0092-8674(80)90366-9]
  35. Takahashi T, Umata T, Mekada E. Extension of juxtamembrane domain of diphtheria toxin receptor arrests translocation of diphtheria toxin fragment A into cytosol. Biochemical and biophysical research communications. 2001;281(3):690-6. [DOI:10.1006/bbrc.2001.4427] [PMID]
  36. Akin S, Babacan T, Sarici F, Altundag K. A novel targeted therapy in breast cancer: cyclin dependent kinase inhibitors. J BUON. 2014;19(1):42-6.
  37. Alewine C, Hassan R, Pastan I. Advances in anticancer immunotoxin therapy. The oncologist. 2015;20(2):176-85. [DOI:10.1634/theoncologist.2014-0358] [PMID] [PMCID]
  38. Allahyari H, Heidari S, Ghamgosha M, Saffarian P, Amani J. Immunotoxin: A new tool for cancer therapy. Tumor Biology. 2017;39(2):1010428317692226. [DOI:10.1177/1010428317692226] [PMID]
  39. Chandramohan V, Sampson JH, Pastan I, Bigner DD. Toxin-based targeted therapy for malignant brain tumors. Clinical and Developmental Immunology. 2012;2012. [DOI:10.1155/2012/480429] [PMID] [PMCID]
  40. Tinoco G, Warsch S, Glück S, Avancha K, Montero AJ. Treating breast cancer in the 21st century: emerging biological therapies. Journal of Cancer. 2013;4(2):117. [DOI:10.7150/jca.4925] [PMID] [PMCID]
  41. Maak M, Nitsche U, Keller L, Wolf P, Sarr M, Thiebaud M, et al. Tumor-specific targeting of pancreatic cancer with Shiga toxin B-subunit. Molecular cancer therapeutics.2011;10(10): 1918-28. [DOI:10.1158/1535-7163.MCT-11-0006] [PMID]
  42. Johansson D, Kosovac E, Moharer J, Ljuslinder I, Brännström T, Johansson A, et al. Expression of verotoxin-1 receptor Gb3 in breast cancer tissue and verotoxin-1 signal transduction to apoptosis. BMC cancer. 2009;9(1):67. [DOI:10.1186/1471-2407-9-67] [PMID] [PMCID]
  43. Geyer PE, Maak M, Nitsche U, Perl M, Novotny A, Slotta-Huspenina J, et al. Gastric adenocarcinomas express the glycosphingolipid Gb3/CD77: Targeting of gastric cancer cells with Shiga toxin B-subunit. Molecular cancer therapeutics. 2016;15(5):1008-17. [DOI:10.1158/1535-7163.MCT-15-0633] [PMID]
  44. Imani-Fooladi AA, Yousefi F, Mousavi SF, Amani J. In silico design and analysis of TGFαl3-seb fusion protein as "a new antitumor agent" candidate by ligand-targeted superantigens technique. Iranian journal of cancer prevention. 2014;7(3):152.
  45. Keshtvarz M, Salimian J, Yaseri M, Bathaie SZ, Rezaie E, Aliramezani A, et al. Bioinformatic prediction and experimental validation of a PE38-based recombinant immunotoxin targeting the Fn14 receptor in cancer cells. Immunotherapy. 2017;9(5):387-400. [DOI:10.2217/imt-2017-0008] [PMID]