Designing a novel SOX9 based multi-epitope vaccine to combat metastatic triple-negative breast cancer using immunoinformatics approach

Immunoinformatics-driven approach for development of potential multi-epitope vaccine against the secreted protein FlaC of Campylobacter jejuni

Campylobacter jejuni causes a leading human gastrointestinal infection which is associated with foodborne diarrhea, stomach cramping, and fever. In the recent years, numerous multidrug-resistant strains of C. jejuni has evolved and is considered in the priority pathogens category. Therefore, an increasing demand exists to develop an effective vaccine against Campylobacteriosis. The T cell and B cell epitopes from the FlaC protein were predicted using comprehensive immunoinformatics tools. The predicted epitopes were chosen based on their antigenicity, allergenicity, and toxicity profiles. Using the bioinformatics approach various physicochemical properties of the constructed vaccine were determined. The molecular docking analysis of the vaccine with the TLRs demonstrated that TLR5 has a higher binding affinity of -1159.0 kcal/mol. Molecular dynamics simulation has confirmed the stable association of the vaccine with TLR5. The immune response of the constructed vaccine was validated using immunostimulation. Based on this study, we recommend the formulation of a multi-epitope vaccine as a promising agent to effectively combat the dreadful campylobacteriosis infection.Communicated by Ramaswamy H. Sarma.

Advancements and hurdles in the development of a vaccine for triple-negative breast cancer: A comprehensive review of multi-omics and immunomics strategies

Triple-Negative Breast Cancer (TNBC) presents a significant challenge in oncology due to its aggressive behavior and limited therapeutic options. This review explores the potential of immunotherapy, particularly vaccine-based approaches, in addressing TNBC. It delves into the role of immunoinformatics in creating effective vaccines against TNBC. The review first underscores the distinct attributes of TNBC and the importance of tumor antigens in vaccine development. It then elaborates on antigen detection techniques such as exome sequencing, HLA typing, and RNA sequencing, which are instrumental in identifying TNBC-specific antigens and selecting vaccine candidates. The discussion then shifts to the in-silico vaccine development process, encompassing antigen selection, epitope prediction, and rational vaccine design. This process merges computational simulations with immunological insights. The role of Artificial Intelligence (AI) in expediting the prediction of antigens and epitopes is also emphasized. The review concludes by encapsulating how Immunoinformatics can augment the design of TNBC vaccines, integrating tumor antigens, advanced detection methods, in-silico strategies, and AI-driven insights to advance TNBC immunotherapy. This could potentially pave the way for more targeted and efficacious treatments.

Design of a novel multi-epitope vaccine candidate against endometrial cancer using immunoinformatics and bioinformatics approaches

Endometrial cancer (EC) is one of the most common cancers of the female reproductive system. Multi-epitope vaccine may be a promising and effective strategy against EC. In this study, we designed a novel multi-epitope vaccine based on the antigenic proteins PRAME and TMPRSS4 using immunoinformatics and bioinformatics approaches. After a rigorous selection process, 14 cytotoxic T lymphocyte (CTL) epitopes, 6 helper T lymphocyte (HTL) epitopes, and 8 B cell epitopes (BCEs) were finally selected for vaccine construction. To enhance the immunogenicity of the vaccine candidate, the pan HLA DR-binding epitope was included in the vaccine design as an adjuvant. The final vaccine construct had 455 amino acids and a molecular weight of 49.8 kDa, and was predicted to cover 95.03% of the total world population. Docking analysis showed that there were 10 hydrogen bonds and 19 hydrogen bonds in the vaccine-HLA-A*02:01 and vaccine-HLA-DRB1*01:01 complexes, respectively, indicating that the vaccine has a good affinity to MHC molecules. This was further supported by molecular dynamics (MD) simulation. Immune simulation showed that the designed vaccine was able to induce higher levels of immune cell activity, with the secretion of numerous cytokines. The codon adaptation index (CAI) value and GC content of the optimised codon sequences of the vaccine were 0.986 and 54.43%, respectively, indicating that the vaccine has the potential to be highly expressed. The in silico analysis suggested that the designed vaccine may provide a novel therapeutic option for the individualised treatment of EC patients in the future.Communicated by Ramaswamy H. Sarma.

Design and In Silico Validation of a Novel MZF-1-Based Multi-Epitope Vaccine to Combat Metastatic Triple Negative Breast Cancer

Immunotherapy is emerging as a potential therapeutic strategy for triple negative breast cancer (TNBC) owing to the immunogenic landscape of its tumor microenvironment. Interestingly, peptide-based cancer vaccines have garnered a lot of attention as one of the most promising cancer immunotherapy regimens. Thus, the present study intended to design a novel, efficacious peptide-based vaccine against TNBC targeting myeloid zinc finger 1 (MZF1), a transcription factor that has been described as an oncogenic inducer of TNBC metastasis. Initially, the antigenic peptides from MZF1 were identified and evaluated based on their likelihood to induce immunological responses. The promiscuous epitopes were then combined using a suitable adjuvant (50S ribosomal L7/L12 protein) and linkers (AAY, GPGPG, KK, and EAAAK) to reduce junctional immunogenicity. Furthermore, docking and dynamics analyses against TLR-4 and TLR-9 were carried out to understand more about their structural stability and integrity. Finally, the constructed vaccine was subjected to in silico cloning and immune simulation studies. Overall, the findings imply that the designed chimeric vaccine could induce strong humoral and cellular immune responses in the desired organism. In light of these findings, the final multi-epitope vaccine could be used as an effective prophylactic treatment for TNBC and may pave the way for future research.

Design of a potential Sema4A-based multi-epitope vaccine to combat triple-negative breast cancer: an immunoinformatic approach

Immunotherapy is revamping the therapeutic strategies for TNBC owing to its higher mutational burden and tumour-associated antigens. One of the most intriguing developments in cancer immunotherapy is the focus on peptide-based cancer vaccines. Thus, the current work aims to develop an efficient peptide-based vaccine against TNBC that targets Sema4A, which has recently been identified as a major regulator of TNBC progression. Initially, the antigenic peptides derived from Sema4A were determined and evaluated based on their capability to provoke immunological responses. The assessed epitopes were then linked with a suitable adjuvant (RpfB and RpfE) and appropriate linkers (AAY, GPGPG, KK and EAAAK) to preclude junctional immunogenicity. Eventually, docking and dynamics simulations are performed against TLR-2, TLR-4, TLR-7 and TLR-9 to assess the interaction between the vaccine construct and TLR receptors, as the TLR signalling pathway is critical in the host immune response. The developed vaccine was then exposed to in silico cloning and immune simulation analysis. The findings suggest that the designed vaccine could potentially evoke significant humoral and cellular immune responses in the intended organism. Considering these outcomes, the final multi-epitope vaccine could be employed to serve as an effective choice for TNBC management and may open new avenues for further studies.