Designing a Novel Multi-epitope T Vaccine for “Targeting Protein for Xklp-2” (TPX2) in Hepatocellular Carcinoma Based on Immunoinformatics Approach

  • Parisa Ghahremanifard
  • Farzaneh Afzali
  • Amin Rostami
  • Zahra Nayeri
  • Bijan Bambai
  • Zarrin MinuchehrEmail author


Hepatocellular carcinoma (HCC) is one of the leading cancer-related deaths worldwide. Recently, studies for HCC treatment are focused on cancer immunotherapy, particularly cancer vaccines, to complete and assist other therapies. TPX2 is a microtubule-associated protein necessary for cell division; therefore, alteration in its expression, especially up regulation, is associated with several human carcinomas such as HCC. In this study, immunoinformatics tools were used to design a rational multi-epitope T vaccine against TPX2 in HCC. Cytotoxic T lymphocytes (CTL) and Helper T lymphocytes (HTL) epitopes were predicted and Maltose-binding protein (MBP) was added to the construct as an adjuvant. Evaluation of vaccine properties was indicated that our construct is stable and immunogenic enough to induce relevant responses besides not being allergic. After predicting the tertiary structure and energy minimization, protein–protein docking and molecular dynamics were performed to calculate the free energy and stability of possible interactions between the vaccine and toll-like receptor 4 (TLR4) to assure that simultaneous complementary responses would be activated by our construct. Finally, Codon optimization and in silico cloning were performed to ensure the vaccine expression efficiency in the desired host.


Construct Hepatocellular cancer Immunogenicity Immunotherapeutic In-silico 



Hepatocellular carcinoma


Maltose-binding protein


Hepatitis B virus


Hepatitis C virus


Transarterial chemoembolization


Radiofrequency ablation


Cytotoxic T lymphocytes


Targeting protein for Xklp-2


Helper T lymphocytes


Tumor-specific antigens


Tumor-associated antigens


Major histocompatibility complex


Grand average of hydropathicity

E. coli

Escherichia coli


Java Codon Adaptation Tool


Codon Adaptation Index


Root mean square deviation


Root mean square fluctuation



The financial support of this research project by the National Institute of Genetic Engineering and Biotechnology (NIGEB) of Iran is acknowledged. Also, we would like to thank Dr. Javad Zamani for his contribution in this article.

Author Contributions

ZM, BB and PGH conceptualized the project. FA and P.GH did the analyses and interpreted the data except the data related to docking part which was done by ZN and FA. PGH and AR wrote the manuscript. ZM supported the project (corresponding author). All authors read and approved the final manuscript.

Compliance with Ethical Standards

Conflict of interest

There is no conflict of interest.

Supplementary material

10989_2019_9915_MOESM1_ESM.docx (22 kb)
Supplementary material 1 (DOCX 21 kb)


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Systems Biotechnology DepartmentNational Institute of Genetic Engineering and Biotechnology (NIGEB)TehranIran
  2. 2.Medical Biotechnology DepartmentNational Institute of Genetic Engineering and Biotechnology (NIGEB)TehranIran
  3. 3.Pars Silico Bioinformatics LaboratoryTehranIran
  4. 4.Paramedical Sciences DepartmentShahid Beheshti University of Medical SciencesTehranIran

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