Transformative protein scaffold designs for dual-modality cancer applications: Advances in therapeutic delivery and molecular imaging of tumor microenvironments
Publication type: Journal Article
Publication date: 2025-07-01
scimago Q1
wos Q1
SJR: 1.285
CiteScore: 10.3
Impact factor: 8.5
ISSN: 01418130, 18790003
Abstract
Despite significant advances in cancer immunotherapy, current approaches face critical limitations, including systemic toxicity, inadequate tumor penetration, and insufficient therapeutic efficacy against immunosuppressive tumor microenvironments. A significant research gap exists in developing platforms that can simultaneously address these challenges while providing real-time monitoring capabilities. We critically analyze recent innovations in scaffold-based delivery systems that enable the controlled release of immunomodulatory agents directly within tumor microenvironments, thereby minimizing systemic exposure and associated toxicities. This comprehensive review examines engineered protein scaffolds as multifunctional platforms for cancer immunotherapy, emphasizing their design principles, synthetic methodologies, and therapeutic applications. Successful protein scaffolds demonstrate crucial performance characteristics including thermal stability (Tm >70 °C), high target specificity with sub-nanomolar binding affinities, and minimal immunogenicity (>95 % human-like sequence identity). We evaluate scaffold effectiveness through quantitative metrics including tumor-to-background ratios exceeding 3:1 for imaging applications, circulation half-lives >12 h for therapeutic delivery, and production yields above 100 mg/L in recombinant expression systems. Clinical benchmarks for these platforms include comparison with conventional antibody performance, demonstrating improved tissue penetration due to their compact size (<50 kDa), enhanced proteolytic resistance through rational engineering, and reduced off-target effects confirmed through multi-organoid models. Advanced technologies including AI-driven generative models and reinforcement learning algorithms are revolutionizing scaffold design, while cell-free protein synthesis systems and orthogonal translation machinery enable on-demand production of complex architectures. By integrating insights from structural biology, computational modeling, and synthetic biology, this review highlights remarkable progress in protein scaffold engineering for dual-modality cancer applications while addressing ongoing challenges in translating these promising platforms to clinical practice.
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Alissa M. et al. Transformative protein scaffold designs for dual-modality cancer applications: Advances in therapeutic delivery and molecular imaging of tumor microenvironments // International Journal of Biological Macromolecules. 2025. Vol. 318. p. 144881.
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Alissa M., Alghamdi A., Alghamdi S. A., Alshehri M. A., Aloraini G. S., Albelasi A., Alshammari M. S. Transformative protein scaffold designs for dual-modality cancer applications: Advances in therapeutic delivery and molecular imaging of tumor microenvironments // International Journal of Biological Macromolecules. 2025. Vol. 318. p. 144881.
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TY - JOUR
DO - 10.1016/j.ijbiomac.2025.144881
UR - https://linkinghub.elsevier.com/retrieve/pii/S0141813025054339
TI - Transformative protein scaffold designs for dual-modality cancer applications: Advances in therapeutic delivery and molecular imaging of tumor microenvironments
T2 - International Journal of Biological Macromolecules
AU - Alissa, Mohammed
AU - Alghamdi, Abdullah
AU - Alghamdi, Suad A.
AU - Alshehri, Mohammed A
AU - Aloraini, Ghfren S
AU - Albelasi, Abdullah
AU - Alshammari, Mohammed S
PY - 2025
DA - 2025/07/01
PB - Elsevier
SP - 144881
VL - 318
SN - 0141-8130
SN - 1879-0003
ER -
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@article{2025_Alissa,
author = {Mohammed Alissa and Abdullah Alghamdi and Suad A. Alghamdi and Mohammed A Alshehri and Ghfren S Aloraini and Abdullah Albelasi and Mohammed S Alshammari},
title = {Transformative protein scaffold designs for dual-modality cancer applications: Advances in therapeutic delivery and molecular imaging of tumor microenvironments},
journal = {International Journal of Biological Macromolecules},
year = {2025},
volume = {318},
publisher = {Elsevier},
month = {jul},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0141813025054339},
pages = {144881},
doi = {10.1016/j.ijbiomac.2025.144881}
}