About this Research Topic
Cancer is one of the most prevalent diseases and the main cause of death and an important barrier to raising life expectancy in the world. Under the discussion of cancer treatment, immunotherapy has the potential to strengthen the immune system's ability to recognize and combat cancerous cells. Therapeutic vaccines against cancer, AIDS, hepatitis B, and bacterial infections are the subject of intense research and development. These vaccines aim to stimulate T-cell responses in order to eradicate tumor cells. This title alludes to a thorough investigation of viral immunotherapy and cancer that bridges the gap between experimental science and computer models. With a multidisciplinary viewpoint, this work explores the dynamic intersection of viral immunotherapeutic strategies and cancer. It emphasizes a comprehensive approach to comprehending and treating these complex diseases by making a unique traversal between the domains of computational modeling and experimental science. The authors draw attention to the ways that state-of-the-art computer-based approaches aid in the development and improvement of cutting-edge cancer and viral immunotherapy strategies. Additionally, the shift from virtual simulations to experimental science is examined, demonstrating how computational discoveries are applied in practical ways.
The ratio of cancer prevalence to therapeutic strategies is not justifiable. Still today, we are facing challenges regarding the safe and effective treatment of cancer. The goal of this title is to develop therapeutic options for cancer including the approaches of designing therapeutic vaccines, immunotherapeutic innovations, and the potential role of computational and machine learning tools for the development of these strategies.
The aim of this Research Topic is to summarize current developments in the field of cancer immunotherapy. We welcome the submission of Original Research articles presenting basic and/or translational studies as well as Review, Mini-Review, and Systematic Review articles focused on, but not limited to, the following topics:
1. Cancer genetic models and virtual framework.
2. Role of computers in vaccine development
3. Concepts of cancer immunotherapy and therapeutic vaccines
4. Experimental trials for the development of viral and cancer vaccines
5. Role of synthetic peptides and epitopes for viral and cancer treatment
The ratio of cancer prevalence to therapeutic strategies is not justifiable. Still today, we are facing challenges regarding the safe and effective treatment of cancer. The goal of this title is to develop therapeutic options for cancer including the approaches of designing therapeutic vaccines, immunotherapeutic innovations, and the potential role of computational and machine learning tools for the development of these strategies.
The aim of this Research Topic is to summarize current developments in the field of cancer immunotherapy. We welcome the submission of Original Research articles presenting basic and/or translational studies as well as Review, Mini-Review, and Systematic Review articles focused on, but not limited to, the following topics:
1. Cancer genetic models and virtual framework.
2. Role of computers in vaccine development
3. Concepts of cancer immunotherapy and therapeutic vaccines
4. Experimental trials for the development of viral and cancer vaccines
5. Role of synthetic peptides and epitopes for viral and cancer treatment
Keywords: Cancer immunotherapy, therapeutic vaccine, virus and cancer, computers and machine learning models, Experimental design
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
