This article presents a bioinformatics approachto designing a vaccine against Triple Negative Breast Cancer(TNBC), a hard-to-treat and aggressive form of breast cancer.The study identifies the targets for the vaccine and outlines theprocess for designing the vaccine using computational tools.Materials and Methods: The study identifies nine proteins astargets for the vaccine, selected based on their ability to bind tothe MHC system. Linear Epitope and Conformational Epitopealgorithms were used to identify epitopes within these proteins.A vaccine candidate was designed using a suitable linker andadjuvant, and computational tests were carried out to ensurethat the vaccine met the necessary physicochemical propertiesand structural analysis.Results: The resulting vaccine candidate passed all computationaltests and showed high population coverage in variouscountries, including Iran, France, England, Spain, China, Japan,India, Saudi Arabia, Israel, the United States, Brazil, Guinea-Bissau, and Australia. The proposed vaccine targets surfaceantigens of TNBC cells, providing a new way to stimulate theimmune system to attack the cancer cells.Conclusion: This study demonstrates the potential of bioinformaticsapproaches in designing effective cancer vaccines.The vaccine candidate designed using the identified targets forTNBC offers a promising approach to treating this hard-to-treatform of breast cancer. The study opens new avenues for furtherresearch and development of vaccines against other types ofcancer.
