Dataset Information

Design of a Novel Recombinant Multi-Epitope Vaccine against Triple-Negative Breast Cancer

ABSTRACT:

Background

Triple-negative breast cancer (TNBC) is determined by the absence of ERBB2, estrogen and progesterone receptors’ expression. Cancer vaccines, as the novel immunotherapy strategies, have emerged as promising tools for treating the advanced stage of TNBC. The aim of this study was to evaluate Carcinoembryonic antigen (CEA), Metadherin (MTDH), and Mucin 1 (MUC-1) proteins as vaccine candidates against TNBC.

Methods

In this research, a novel vaccine was designed against TNBC by using different immunoinformatics and bioinformatics approaches. Effective immunodominant epitopes were chosen from three antigenic proteins, namely CEA, MTDH, and MUC-1. Recombinant TLR4 agonists were utilized as an adjuvant to stimulate immune responses. Following the selection of antigens and adjuvants, appropriate linkers were chosen to generate the final recombinant protein. To achieve an excellent 3D model, the best predicted 3D model was required to be refined and validated. To demonstrate whether the vaccine/TLR4 complex is stable or not, we performed docking analysis and dynamic molecular simulation.

Result

Immunoinformatics and bioinformatics evaluations of the designed construct demonstrated that this vaccine candidate could effectively be used as a therapeutic armament against TNBC.

Conclusion

Bioinformatics studies revealed that the designed vaccine has an acceptable quality. Investigating the effectiveness of this vaccine can be confirmed by supplementary in vitro and in vivo studies.

SUBMITTER: Dariushnejad H

PROVIDER: S-EPMC8987416 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Design of a Novel Recombinant Multi-Epitope Vaccine against Triple-Negative Breast Cancer

Dariushnejad Hassan H Ghorbanzadeh Vajihe V Akbari Soheila S Hashemzadeh Pejman P

Iranian biomedical journal 20220301 2

<h4>Background</h4>Triple-negative breast cancer (TNBC) is determined by the absence of ERBB2, estrogen and progesterone receptors’ expression. Cancer vaccines, as the novel immunotherapy strategies, have emerged as promising tools for treating the advanced stage of TNBC. The aim of this study was to evaluate Carcinoembryonic antigen (CEA), Metadherin (MTDH), and Mucin 1 (MUC-1) proteins as vaccine candidates against TNBC.<h4>Methods</h4>In this research, a novel vaccine was designed against T ...[more]

PMID: 35090304

Similar Datasets

Project description:BackgroundInfluenza A virus is one of the leading causes of annual mortality. The emerging of novel escape variants of the influenza A virus is still a considerable challenge in the annual process of vaccine production. The evolution of vaccines ranks among the most critical successes in medicine and has eradicated numerous infectious diseases. Recently, multi-epitope vaccines, which are based on the selection of epitopes, have been increasingly investigated.ResultsThis study utilized an immunoinformatic approach to design a recombinant multi-epitope vaccine based on a highly conserved epitope of hemagglutinin, neuraminidase, and membrane matrix proteins with fewer changes or mutate over time. The potential B cells, cytotoxic T lymphocytes (CTL), and CD4 T cell epitopes were identified. The recombinant multi-epitope vaccine was designed using specific linkers and a proper adjuvant. Moreover, some bioinformatics online servers and datasets were used to evaluate the immunogenicity and chemical properties of selected epitopes. In addition, Universal Immune System Simulator (UISS) in silico trial computational framework was run after influenza exposure and recombinant multi-epitope vaccine administration, showing a good immune response in terms of immunoglobulins of class G (IgG), T Helper 1 cells (TH1), epithelial cells (EP) and interferon gamma (IFN-g) levels. Furthermore, after a reverse translation (i.e., convertion of amino acid sequence to nucleotide one) and codon optimization phase, the optimized sequence was placed between the two EcoRV/MscI restriction sites in the PET32a+ vector.ConclusionsThe proposed "Recombinant multi-epitope vaccine" was predicted with unique and acceptable immunological properties. This recombinant multi-epitope vaccine can be successfully expressed in the prokaryotic system and accepted for immunogenicity studies against the influenza virus at the in silico level. The multi-epitope vaccine was then tested with the Universal Immune System Simulator (UISS) in silico trial platform. It revealed slight immune protection against the influenza virus, shedding the light that a multistep bioinformatics approach including molecular and cellular level is mandatory to avoid inappropriate vaccine efficacy predictions.

Dataset Information

Design of a Novel Recombinant Multi-Epitope Vaccine against Triple-Negative Breast Cancer

Background

Methods

Result

Conclusion

Publications

Design of a Novel Recombinant Multi-Epitope Vaccine against Triple-Negative Breast Cancer

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets