In Silico Designing a Novel Multi-epitope DNA Vaccine against Anti-apoptotic Proteins in Tumor Cells

Author(s): Shirin Mahmoodi*, Navid Nezafat.

Journal Name: Current Proteomics

Volume 16 , Issue 3 , 2019

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Graphical Abstract:


Background: Cancer therapy has been known as one of the most important challenges in the world. Various therapeutic methods such as cancer immunotherapy are used to eradicate tumor cells. Vaccines have an important role among different cancer immunotherapeutic approaches. In the field of vaccine production, bioinformatics approach is considered as a useful tool to design multi-epitope cancer vaccines, mainly for selecting immunodominant Cytotoxic T Lymphocytes (CTL) and Helper T Lymphocytes (HTL) epitopes.

Objective: Generally, to design efficient multi-epitope cancer vaccines, Tumor-Specific Antigens (TSA) are targeted. In the context of DNA-based cancer vaccines, they contain genes that code tumor antigens and are delivered to host by different methods.

Methods: In this study, the anti-apoptotic proteins (BCL2, BCL-X, survivin) that are over-expressed in different tumor cells were selected for CTL and HTL epitopes prediction through different servers such as RANKPEP, CTLpred, and BCPREDS.

Results: Three regions from BCL2 and one region from BCL-X were selected as CTL epitopes and two segments from survivin were defined as HTL epitopes. In addition, β-defensin was used as a proper adjuvant to enhance vaccine efficacy. The aforesaid segments were joined together by appropriate linkers, and some important properties of designed vaccine such as antigenicity, allergenicity and physicochemical characteristics were determined by various bioinformatics servers.

Conclusion: Based on the bioinformatics results, the physicochemical and immunological features showed that the designed vaccine construct can be used as an efficient cancer vaccine after its efficacy was confirmed by in vitro and in vivo immunological assays.

Keywords: Cancer immunotherapy, epitope, DNA vaccine, anti-apoptotic proteins, bioinformatics, tumor.

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Year: 2019
Page: [222 - 230]
Pages: 9
DOI: 10.2174/1570164616666181127142214
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