دوره 13، شماره 3 - ( 5-1404 )
جلد 13 شماره 3 صفحات 202-189 |
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Ghanei Z, Sefid F. A Novel Chimeric Vaccine Targeting Leukemia Inhibitory Factor and Leukemia Inhibitory Factor Receptor: A Computational Approach to Cancer Immunotherapy. Res Mol Med (RMM) 2025; 13 (3) :189-202
URL: http://rmm.mazums.ac.ir/article-1-621-fa.html
URL: http://rmm.mazums.ac.ir/article-1-621-fa.html
A Novel Chimeric Vaccine Targeting Leukemia Inhibitory Factor and Leukemia Inhibitory Factor Receptor: A Computational Approach to Cancer Immunotherapy. Research in Molecular Medicine. 1404; 13 (3) :189-202
چکیده: (240 مشاهده)
Background: Leukemia inhibitory factor (LIF) and LIF receptor (LIFR) are critical mediators of cellular processes, including immune regulation, stem cell maintenance, and tumor progression. In Oncology, aberrant LIF/LIFR signaling promotes tumor survival and immune evasion. This study presents the computational design of a novel chimeric vaccine targeting immunogenic epitopes derived from human LIF and LIFR.
Materials and Methods: We employed comprehensive in silico methods to investigate the biochemical characteristics, immunogenic epitopes, and potential functional domains of LIF and LIFR. After identifying suitable regions and designing a chimeric vaccine, physicochemical properties and 3D structure were predicted using various bioinformatics tools, both individually and in combination.
Results: The results showed highly antigenic B-cell and T-cell epitopes within LIF (amino acids 70-100) and LIFR (amino acids 700-780), as indicated by a VaxiJen score of 0.9737. A multi-epitope construct was engineered by fusing selected epitopes with flexible GGGGS linkers to enhance immunogenicity and structural stability.
Conclusion: A computationally designed chimeric vaccine targeting LIF and LIFR is a promising cancer immunotherapy strategy. Also, success requires rigorous in vivo validation and optimization, highlighting computational biology’s role in cancer treatment innovation and targeting key pathways.
Materials and Methods: We employed comprehensive in silico methods to investigate the biochemical characteristics, immunogenic epitopes, and potential functional domains of LIF and LIFR. After identifying suitable regions and designing a chimeric vaccine, physicochemical properties and 3D structure were predicted using various bioinformatics tools, both individually and in combination.
Results: The results showed highly antigenic B-cell and T-cell epitopes within LIF (amino acids 70-100) and LIFR (amino acids 700-780), as indicated by a VaxiJen score of 0.9737. A multi-epitope construct was engineered by fusing selected epitopes with flexible GGGGS linkers to enhance immunogenicity and structural stability.
Conclusion: A computationally designed chimeric vaccine targeting LIF and LIFR is a promising cancer immunotherapy strategy. Also, success requires rigorous in vivo validation and optimization, highlighting computational biology’s role in cancer treatment innovation and targeting key pathways.
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