RNF43 p.G659fs 通过 PI3K/AKT/mTOR 信号通路和 HLA-E 上调导致 MSI-high 结直肠癌中 NK 细胞功能障碍
RNF43 p.G659fs leads to natural killer cell dysfunction in MSI-high colorectal cancer through PI3K/AKT/mTOR signaling and HLA-E up-regulation.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:A novel LGALS1-depended and immune-associated fatty acid metabolism risk model in acute myeloid leukemia stem cells.
A novel LGALS1-depended and immune-associated fatty acid metabolism risk model in acute myeloid leukemia stem cells.
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白血病干细胞被认为是白血病起始、复发和耐药的根源。脂质是人体细胞的重要组成部分,在肿瘤微环境中常发生变化;白血病干细胞会重塑脂质代谢以维持干性,但目前尚无脂质相关标志物获批用于急性髓系白血病预测或治疗。本研究基于TCGA及生物信息学分析构建并验证脂肪酸代谢风险评分模型(LFMRS),发现该模型可作为独立风险因素,并结合年龄预测患者生存。模型关键基因半乳糖凝集素1(LGALS1)在白血病干细胞中高表达并与不良预后相关。体外抑制LGALS1可减少急性髓系白血病细胞及干细胞增殖、增强凋亡并降低脂质积累;体内抑制则限制疾病进展和脂质积累,并影响CD8阳性T细胞及NK细胞数量。研究揭示LFMRS尤其LGALS1在急性髓系白血病中的作用,或可帮助改善预后并制定个体化治疗。
Leukemia stem cells (LSCs) are recognized as the root cause of leukemia initiation, relapse, and drug resistance. Lipid species are highly abundant and essential component of human cells, which often changed in tumor microenvironment. LSCs remodel lipid metabolism to sustain the stemness.
However, there is no useful lipid related biomarker has been approved for clinical practice in AML prediction and treatment.
Here, we constructed and verified fatty acid metabolism-related risk score (LFMRS) model based on TCGA database via a series of bioinformatics analysis, univariate COX regression analysis, and multivariate COX regression analysis, and found that the LFMRS model could be an independent risk factor and predict the survival time of AML patients combined with age.
Moreover, we revealed that Galectin-1 (LGALS1, the key gene of LFMRS) was highly expressed in LSCs and associated with poor prognosis of AML patients, and LGALS1 repression inhibited AML cell and LSC proliferation, enhanced cell apoptosis, and decreased lipid accumulation in vitro. LGALS1 repression curbed AML progression, lipid accumulation, and CD8 + T and NK cell counts in vivo.
Our study sheds light on the roles of LFMRS (especially LGALS1) model in AML, and provides information that may help clinicians improve patient prognosis and develop personalized treatment regimens for AML.
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