Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
Identification of Therapy-Induced Clonal Evolution and Resistance Pathways in Minimal Residual Clones in Multiple Myeloma through Single-Cell Sequencing.
СтатьяНазвание 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.
Cui Jian, Li Xiaoyun, Deng Shuhui, Du Chenxing, Fan Huishou, Yan Wenqiang, Xu Jingyu, Li Xiaoqing, Yu Tengteng, Zhang Shuaishuai, Lv Rui, Sui Weiwei, Hao Mu, Du Xin, Xu Yan, Yi Shuhua, Zou Dehui, Cheng Tao, Qiu Lugui, Gao Xin, An Gang
Аннотация
PURPOSE: In multiple myeloma (MM), therapy-induced clonal evolution is associated with treatment resistance and is one of the most important hindrances toward a cure for MM. To further understand the molecular mechanisms controlling the clonal evolution of MM, we applied single-cell RNA sequencing (scRNA-seq) to paired diagnostic and posttreatment bone marrow (BM) samples.
EXPERIMENTAL DESIGN: scRNA-seq was performed on 38 BM samples from patients with monoclonal gammopathy of undetermined significance (n = 1), MM patients at diagnosis (n = 19), MM posttreatment (n = 17), and one healthy donor (HD). The single-cell transcriptome data of malignant plasma cells (PC) and the surrounding immune microenvironment were analyzed.
RESULTS: Profiling by scRNA-seq data revealed three primary trajectories of transcriptional evolution after treatment: clonal elimination in patients with undetectable minimal residual disease (MRD-) and clonal stabilization and clonal selection in detectable MRD (MRD+) patients. We noted a metabolic shift toward fatty acid oxidation in cycling-resistant PCs, whereas selective PCs favored the NF-κB pathway. Intriguingly, when comparing the genetic and transcriptional dynamics, we found a significant correlation between genetic and nongenetic factors in driving the clonal evolution. Furthermore, we identified variations in cellular interactions between malignant PCs and the tumor microenvironment. Selective PCs showed the most robust cellular interactions with the tumor microenvironment.
CONCLUSIONS: These data suggest that MM cells could rapidly adapt to induction treatment through transcriptional adaptation, metabolic adaptation, and specialized immune evasion. Targeting therapy-induced resistance mechanisms may help to avert refractory disease in MM.
EXPERIMENTAL DESIGN: scRNA-seq was performed on 38 BM samples from patients with monoclonal gammopathy of undetermined significance (n = 1), MM patients at diagnosis (n = 19), MM posttreatment (n = 17), and one healthy donor (HD). The single-cell transcriptome data of malignant plasma cells (PC) and the surrounding immune microenvironment were analyzed.
RESULTS: Profiling by scRNA-seq data revealed three primary trajectories of transcriptional evolution after treatment: clonal elimination in patients with undetectable minimal residual disease (MRD-) and clonal stabilization and clonal selection in detectable MRD (MRD+) patients. We noted a metabolic shift toward fatty acid oxidation in cycling-resistant PCs, whereas selective PCs favored the NF-κB pathway. Intriguingly, when comparing the genetic and transcriptional dynamics, we found a significant correlation between genetic and nongenetic factors in driving the clonal evolution. Furthermore, we identified variations in cellular interactions between malignant PCs and the tumor microenvironment. Selective PCs showed the most robust cellular interactions with the tumor microenvironment.
CONCLUSIONS: These data suggest that MM cells could rapidly adapt to induction treatment through transcriptional adaptation, metabolic adaptation, and specialized immune evasion. Targeting therapy-induced resistance mechanisms may help to avert refractory disease in MM.