[Rinsho ketsueki] The Japanese journal of clinical hematology · 2026
[Biomarkers for enhancing efficacy of CAR-T cell therapy].
СтатьяОбзорАннотация на английскомНазвание и аннотация: Перевод пока не подготовлен
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.
Terakura Seitaro
Аннотация
Chimeric antigen receptor T-cell (CAR-T) therapy has revolutionized the treatment of relapsed/refractory hematologic malignancies, achieving remarkable response rates in B-cell acute lymphoblastic leukemia and lymphomas. However, treatment responses and toxicities vary substantially among patients, necessitating the establishment of robust predictive biomarkers for optimal patient stratification and treatment personalization. This review systematically categorizes key factors affecting CAR-T therapy efficacy into tumor-intrinsic and T cell-intrinsic components. Tumor-intrinsic factors include tumor burden, antigen expression heterogeneity, and immunosuppressive components within the tumor microenvironment, such as regulatory T cells, myeloid-derived suppressor cells, tumor-associated macrophages, and inhibitory cytokines (e.g., TGF-β and IL-10). T cell-intrinsic factors encompass memory T cell subset composition, particularly central memory and stem cell memory populations, CAR expression density and transduction efficiency, polyfunctional cytokine production profiles, mitochondrial function and metabolic fitness, and expression of immune checkpoint molecules. Recent technological advances in single-cell RNA sequencing, comprehensive proteomics, and high-dimensional immunophenotyping combined with machine learning algorithms enable increasingly precise biomarker identification and predictive modeling. Integration of these multidimensional biomarkers into unified prediction models holds substantial promise for personalizing therapy, enhancing efficacy while minimizing adverse events, and ultimately achieving durable remission in patients receiving CAR-T therapy.