Personalized cancer vaccine design using AI-powered technologies

Abstract

Immunotherapy has ushered in a new era of cancer treatment, yet cancer remains a leading cause of global mortality. Among various therapeutic strategies, cancer vaccines have shown promise by activating the immune system to specifically target cancer cells. While current cancer vaccines are primarily prophylactic, advancements in targeting tumor-associated antigens (TAAs) and neoantigens have paved the way for therapeutic vaccines. The integration of artificial intelligence (AI) into cancer vaccine development is revolutionizing the field by enhancing various aspect of design and delivery. This review explores how AI facilitates precise epitope design, optimizes mRNA and DNA vaccine instructions, and enables personalized vaccine strategies by predicting patient responses. By utilizing AI technologies, researchers can navigate complex biological datasets and uncover novel therapeutic targets, thereby improving the precision and efficacy of cancer vaccines. Despite the promise of AI-powered cancer vaccines, significant challenges remain, such as tumor heterogeneity and genetic variability, which can limit the effectiveness of neoantigen prediction. Moreover, ethical and regulatory concerns surrounding data privacy and algorithmic bias must be addressed to ensure responsible AI deployment. The future of cancer vaccine development lies in the seamless integration of AI to create personalized immunotherapies that offer targeted and effective cancer treatments. This review underscores the importance of interdisciplinary collaboration and innovation in overcoming these challenges and advancing cancer vaccine development.

Keywords: MHCpeptide binding prediction; artificial intelligence; cancer vaccine; epitope design; neoantigen prediction; nucleic acid cancer vaccines; peptide cancer vaccines; personalized cancer vaccine.

Figure 1

Queries made using specific keywords in databases.

Figure 2

The PRISMA-ScR guidelines-based methodology for selecting studies to be included in the review.

Figure 3

Traditional Vaccine Design Process. The journey of vaccine development commences with the identification and selection of target antigens, which are then combined with suitable adjuvants. Preclinical testing is conducted before progressing to clinical trials. Following the assessment of the vaccine’s efficacy and safety in clinical trials, regulatory approval is sought for large-scale manufacturing and distribution.

Figure 4

Mechanism of action (MOA) of a vaccine. Cancer vaccines introduce tumor-associated antigens or tumor-specific antigens to the immune system. Antigen-presenting cells (APCs), such as dendritic cells, process these antigens and present them in a Human Leukocyte Antigen (HLA)–restricted manner to T cells. Activated T cells recognize and bind to tumor cells expressing the same antigens, leading to the activation of cytotoxic T cells (CD8+ T cells) and helper T cells (CD4+ T cells). CD8+ T cells directly target and kill tumor cells, while CD4+ T cells assist other immune responses. Activated B cells produce antibodies that neutralize tumor cells or their secreted factors, contributing to tumor cell death. Immune surveillance by T cells and B cells monitors for and eliminates any remaining tumor cells that may have escaped initial treatment. The immune system retains the memory of tumor antigens, allowing a rapid response if the tumor recurs. Additionally, cancer vaccines are often combined with other immunotherapies or standard treatments to enhance efficacy.