International journal of molecular sciences · 2026
Therapy-Driven Molecular Evolution of Bladder Cancer: Roles of Cellular Plasticity and Tumor Microenvironment.
СтатьяОбзорНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Baek Seung-Woo, Yoon Seo-Young, Kim Seon-Kyu, Leem Sun-Hee
Аннотация
Drug resistance remains a significant barrier to achieving durable treatment responses. Traditionally, resistance has been attributed to genetic alterations and clonal selection. However, accumulating evidence suggests that early adaptation to therapy is often mediated by non-genetic state transitions. In this review, we propose a conceptual framework in which resistance emerges through therapy-driven molecular evolution in bladder cancer, characterized by three interconnected axes: non-genetic plasticity, metabolic reorganization, and tumor microenvironment remodeling. Using the Gemcitabine-Resistant Cell (GRC) model as a temporal reference system, we describe a stepwise transition from drug-sensitive states dominated by proliferation to survival-optimized resistant states through a growth-survival trade-off. Early adaptive phases are marked by the attenuation of cell-cycle and glycolytic programs, increased epigenetic flexibility, and metabolic rewiring involving mitochondrial and lipid-associated pathways. Later phases involve the reinforcement of resistance through extracellular matrix remodeling, developmental and stress-response signaling, and immunometabolic interactions within the tumor microenvironment, including adenosine- and lipid-associated mediators. Projecting the GRC score onto a clinical bladder cancer cohort further suggests that these evolutionary patterns may also be reflected in patient tumors. Overall, this framework supports a temporally structured view of chemoresistance and highlights opportunities to therapeutically target transitional adaptive states before resistance becomes stabilized.