@article{Lu2026, 
author = {Shijia Lu and Yanmin Wang and Han Zhang and Mengjia Yan and Mengdan Sang and Jinle Wang and Huaying Du and Jinwen Sima and Yiran Zhen and Xue Yang and Yutong Zhang and Hongwei Zhou},
title = {Targeting PCNA in Cancer: A Paradigm Shift from Static Inhibition to Dynamic Network Modulation},
year = {2026},
journal = {Oncology Research},
volume = {34},
number = {8},
pages = {8},
keywords = {Proliferating cell nuclear antigen, targeted protein degradation, artificial intelligence, precision therapy, tumor microenvironment, synthetic lethality, clinical translation},
url = {https://www.sciopen.com/article/10.32604/or.2026.079988},
doi = {10.32604/or.2026.079988},
abstract = {Proliferating Cell Nuclear Antigen (PCNA) is a core protein in DNA replication and repair. Its functional dysregulation drives tumorigenesis and therapeutic resistance, making it a critical anticancer target. However, the fundamental conflict between PCNA’s indispensable “guardian” function in normal cells and its hijacked “accomplice” role in cancer cells constitutes the central challenge for targeted intervention: how to eradicate tumors while avoiding severe toxicity to normal tissues. This review aims to systematically review the latest advances and translational dilemmas in the field of PCNA-targeted therapy. It outlines various intervention strategies, including small-molecule inhibitors, proteolysis-targeting chimeras, post-translational modification interference, and synthetic lethality approaches, analyzing their potential and limitations in preclinical research. The review focuses on dissecting key bottlenecks hindering clinical translation, such as the selectivity dilemma, delivery barriers, and resistance evolution. Concurrently, it critically examines how cross-disciplinary technologies—including artificial intelligence, spatiotemporal regulation, and synthetic biology—offer novel ideas to address these bottlenecks, while clarifying that most remain in early exploratory stages. By synthesizing progress, challenges, and future directions, this article provides a framework to inform the development of highly selective and translatable PCNA-based anticancer strategies.}
}