Unraveling the molecular landscape of Ataxia Telangiectasia: Insights into Neuroinflammation, immune dysfunction, and potential therapeutic target

BACKGROUND

Ataxia Telangiectasia (AT) is a genetic disorder characterized by compromised DNA repair, cerebellar degeneration, and immune dysfunction. Understanding the molecular mechanisms driving AT pathology is crucial for developing targeted therapies.

METHODS

In this study, we conducted a comprehensive analysis to elucidate the molecular mechanisms underlying AT pathology. Using publicly available RNA-seq datasets comparing control and AT samples, we employed in silico transcriptomics to identify potential genes and pathways. We performed differential gene expression analysis with DESeq2 to reveal dysregulated genes associated with AT. Additionally, we constructed a Protein-Protein Interaction (PPI) network to explore the interactions between proteins implicated in AT.

RESULTS

The network analysis identified hub genes, including TYROBP and PCP2, crucial in immune regulation and cerebellar function, respectively. Furthermore, pathway enrichment analysis unveiled dysregulated pathways linked to AT pathology, providing insights into disease progression.

CONCLUSION

Our integrated approach offers a holistic understanding of the complex molecular landscape of AT and identifies potential targets for therapeutic intervention. By combining transcriptomic analysis with network-based methods, we provide valuable insights into the underlying mechanisms of AT pathogenesis.

Rational design of a multivalent vaccine targeting arthropod-borne viruses using reverse vaccinology strategies

Viruses transmitted by arthropods, such as Dengue, Zika, and Chikungunya, represent substantial worldwide health threats, particularly in countries like India. The lack of approved vaccines and effective antiviral therapies calls for developing innovative strategies to tackle these arboviruses. In this study, we employed immunoinformatics methodologies, incorporating reverse vaccinology, to design a multivalent vaccine targeting the predominant arboviruses. Epitopes of B and T cells were recognized within the non-structural proteins of Dengue, Zika, and Chikungunya viruses. The predicted epitopes were enhanced with adjuvants β-defensin and RS-09 to boost the vaccine's immunogenicity. Sixteen distinct vaccine candidates were constructed, each incorporating epitopes from all three viruses. FUVAC-11 emerged as the most promising vaccine candidate through molecular docking and molecular dynamics simulations, demonstrating favorable binding interactions and stability. Its effectiveness was further evaluated using computational immunological studies confirming strong immune responses. The in silico cloning performed using the pET-28a(+) plasmid facilitates the future experimental implementation of this vaccine candidate, paving the way for potential advancements in combating these significant arboviral threats. However, further in vitro and in vivo studies are warranted to confirm the results obtained in this computational study, which highlights the effectiveness of immunoinformatics and reverse vaccinology in creating vaccines against major Arboviruses, offering a promising model for developing vaccines for other vector-borne diseases and enhancing global health security.

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.

Structural immunoinformatics approach for rational design of a multi-epitope vaccine against triple negative breast cancer

TNBC is a highly malignant breast cancer known for its aggressive behavior affecting young female adults. The standard treatment for TNBC includes surgery, chemotherapy, and radiotherapy, which often have significant side effects. Therefore, novel preventive methods are required to combat TNBC effectively. In this study, we utilized immunoinformatics to construct an in-silico vaccine against TNBC using the TRIM25 molecule via the reverse vaccinology method. Four vaccines were designed by generating T and B-cell epitopes linked with four different linkers. The modeled vaccine was docked and the results showed that vaccine-3 exhibited the highest affinity with the immune receptors. The molecular dynamics results revealed that the binding affinity and stability of Vaccine-3 were greater than those of Vaccine 2 complexes. This study has great potential preventive measures for TNBC, and further research is warranted to evaluate its efficacy in preclinical settings. This study presents an innovative preventive strategy for triple-negative breast cancer (TNBC) through immunoinformatics and reverse vaccinology to develop an in-silico vaccine. Leveraging these innovative techniques offers a novel avenue for combating the complex challenges associated with TNBC. This approach demonstrates considerable potential as a significant breakthrough in preventive measures for this particularly aggressive and malignant form of breast cancer.