This comprehensive thesis delves into the intricacies of the T cell immune response against human papillomavirus (HPV) 16 antigens (E6, E7, and L1) within both CD8 and CD4 T cell subsets. A particular emphasis is placed on exploring potential cross- reactivity, extending the investigation to include HPV18. The evaluation of traditional vaccines, Cervarix and Gardasil, is crucial to understanding their efficacy. Utilizing advanced techniques such as AIM and LPA assays, the study meticulously analyzes T cell activation and proliferation. The research scope encompasses diverse participant groups, including HPV-vaccinated and non-vaccinated individuals, as well as those at different stages of HPV-induced cervical cancer. A focal point of the investigation is on CD4 T cells expressing CXCR5, known for their pivotal role in B cell antibody production. The study aims to deepen this understanding through experimental analyses and immunoinformatics, culminating in the design of a sophisticated multi-epitope vaccine. System immunology takes center stage, exploring gene expression changes in PBMCs before and after vaccination. Network analysis aims to identify key genes critical for an effective immune response. Additionally, drug design strategies, employing QSAR and pharmacophore modeling, seek to modulate the target gene, potentially enhancing vaccine efficacy. The study's multifaceted objectives encompass T cell responses, follicular T cell dynamics, HPV clade differences, immunoinformatics-based vaccine design, gene expression alterations, target gene drugability, and computational drug design. Key findings underscore the importance of vaccination regimen optimization, provide rationale for L1 antigen selection, elucidate the representative roles of HPV 16 and 18, refine antigenic focus, showcase multi-epitope vaccine development, and offer insights from immune system simulations and gene expression dynamics.
This comprehensive thesis delves into the intricacies of the T cell immune response against human papillomavirus (HPV) 16 antigens (E6, E7, and L1) within both CD8 and CD4 T cell subsets. A particular emphasis is placed on exploring potential cross- reactivity, extending the investigation to include HPV18. The evaluation of traditional vaccines, Cervarix and Gardasil, is crucial to understanding their efficacy. Utilizing advanced techniques such as AIM and LPA assays, the study meticulously analyzes T cell activation and proliferation. The research scope encompasses diverse participant groups, including HPV-vaccinated and non-vaccinated individuals, as well as those at different stages of HPV-induced cervical cancer. A focal point of the investigation is on CD4 T cells expressing CXCR5, known for their pivotal role in B cell antibody production. The study aims to deepen this understanding through experimental analyses and immunoinformatics, culminating in the design of a sophisticated multi-epitope vaccine. System immunology takes center stage, exploring gene expression changes in PBMCs before and after vaccination. Network analysis aims to identify key genes critical for an effective immune response. Additionally, drug design strategies, employing QSAR and pharmacophore modeling, seek to modulate the target gene, potentially enhancing vaccine efficacy. The study's multifaceted objectives encompass T cell responses, follicular T cell dynamics, HPV clade differences, immunoinformatics-based vaccine design, gene expression alterations, target gene drugability, and computational drug design. Key findings underscore the importance of vaccination regimen optimization, provide rationale for L1 antigen selection, elucidate the representative roles of HPV 16 and 18, refine antigenic focus, showcase multi-epitope vaccine development, and offer insights from immune system simulations and gene expression dynamics.
Comprehensive Insights into HPV 16 Immunity: From T Cell Activation and Proliferation to Vaccine Design and Drug Discovery
SOLEYMANINEJADIAN, EHSAN
2024-12-16
Abstract
This comprehensive thesis delves into the intricacies of the T cell immune response against human papillomavirus (HPV) 16 antigens (E6, E7, and L1) within both CD8 and CD4 T cell subsets. A particular emphasis is placed on exploring potential cross- reactivity, extending the investigation to include HPV18. The evaluation of traditional vaccines, Cervarix and Gardasil, is crucial to understanding their efficacy. Utilizing advanced techniques such as AIM and LPA assays, the study meticulously analyzes T cell activation and proliferation. The research scope encompasses diverse participant groups, including HPV-vaccinated and non-vaccinated individuals, as well as those at different stages of HPV-induced cervical cancer. A focal point of the investigation is on CD4 T cells expressing CXCR5, known for their pivotal role in B cell antibody production. The study aims to deepen this understanding through experimental analyses and immunoinformatics, culminating in the design of a sophisticated multi-epitope vaccine. System immunology takes center stage, exploring gene expression changes in PBMCs before and after vaccination. Network analysis aims to identify key genes critical for an effective immune response. Additionally, drug design strategies, employing QSAR and pharmacophore modeling, seek to modulate the target gene, potentially enhancing vaccine efficacy. The study's multifaceted objectives encompass T cell responses, follicular T cell dynamics, HPV clade differences, immunoinformatics-based vaccine design, gene expression alterations, target gene drugability, and computational drug design. Key findings underscore the importance of vaccination regimen optimization, provide rationale for L1 antigen selection, elucidate the representative roles of HPV 16 and 18, refine antigenic focus, showcase multi-epitope vaccine development, and offer insights from immune system simulations and gene expression dynamics.File | Dimensione | Formato | |
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Descrizione: Comprehensive Insights into HPV 16 Immunity: From T Cell Activation and Proliferation to Vaccine Design and Drug Discovery
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