همایش ملی بیوانفورماتیک ایران

صفحه اصلی / 4th international edition and 13th Iranian Conference on Bioinformatics

In silico vaccine design for breast cancer

نویسندگان :

Zohre Sadeghi¹ Zahra Davoudi²

1- دانشگاه علوم پزشکی زاهدان 2- دانشگاه علوم پزشکی زنجان

کلمات کلیدی :

In silico،cancer،vaccine،multi-epitope

چکیده :

Breast cancer is one of the most common types of cancer among women worldwide and is also the most common cause of cancer-related death in women. Triple-negative breast cancer (TNBC) is a highly aggressive and metastatic subtype of breast cancer that lacks responsiveness to targeted therapies. Consequently, it is crucial to explore and develop new treatment strategies for this malignancy. Recent progress in immunoinformatics has paved the way for innovative approaches, including the design of vaccines that utilize specific epitopes. The aim of this study is to develop a multi-epitope subunit vaccine targeting CEA, WT-1, and Survivin using immunoinformatics techniques. Immunodominant epitopes from cytotoxic T lymphocytes (CTLs), helper T lymphocytes (HTLs), and B cells were selected from epitope prediction servers to develop a peptide vaccine against breast cancer. The selected epitopes were linked using proper linkers. The designed construct demonstrated a significant degree of antigenicity as assessed by VaxiJen, along with non-allergenicity and non-toxicity. The physicochemical properties of the designed vaccine were analyzed using the ProtParam server, which indicated its suitability for immunogenic applications. The 3D model of the construct demonstrated that the refined version was of high quality and exhibited significant structural stability. Molecular docking results revealed that the vaccine exhibits a strong binding affinity for both TLR2 and TLR4, while molecular dynamics simulations confirmed the stability of the docked vaccine-TLR complexes. Our results indicate that the designed multi-epitope vaccine may serve as a promising candidate for protection against breast cancer. However, further experimental studies are required to validate these predictions.