CAR-T(CAR-T)细胞疗法在非肿瘤性疾病中的应用
Chimeric antigen receptor T (CAR-T) cell therapy in non-oncological diseases.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Multi-omics analysis reveals dynamic proteomic remodeling and metabonomic dysregulation underlying cytokine release syndrome in CAR-T-treated B-ALL.
Multi-omics analysis reveals dynamic proteomic remodeling and metabonomic dysregulation underlying cytokine release syndrome in CAR-T-treated B-ALL.
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CAR-T 疗法改变了B细胞急性淋巴细胞白血病(B-ALL)的治疗,但疗效和毒性的预测性生物标志物仍然有限。本研究通过液相色谱-串联质谱(LC-MS/MS)分析19例B-ALL患者在四个治疗阶段的样本。蛋白质组学分析揭示了治疗期间免疫应答、炎症调节、补体激活及细胞代谢的动态变化。与细胞因子释放综合征(CRS)相关的差异表达蛋白主要涉及补体和凝血级联、细胞黏附分子及吞噬体通路。代谢组学分析显示,CAR-T 治疗期间牛磺酸和亚牛磺酸代谢、初级胆汁酸生物合成及类固醇激素生物合成通路富集。CRS不同阶段的代谢物显示精氨酸和脯氨酸代谢紊乱逐渐加重,并伴随烟酸-烟酰胺代谢激活,这与炎症升级及多器官损伤相关。研究者采用Cox回归筛选出6种蛋白标志物(SCRN2、OAF、SBSN、ERP44、TWF2和ENSA)和7种代谢标志物(假尿苷、3-甲基戊二酰肉碱、3-(2-羟苯基)丙酸、N-乙酰苏氨酸、PC(18:1(9Z)/16:0)、PE(P-18:0/20:4(5Z,8Z,11Z,14Z))及Cer(d18:1/24:1(15Z)))。这些标志物具有良好的预测能力,可用于CRS监测和生存预测。
CAR-T therapy has transformed B-cell acute lymphoblastic leukemia (B-ALL) treatment, but predictive biomarkers for efficacy and toxicity remain limited. Through liquid chromatography-tandem mass spectrometry (LC-MS/MS) profiling of 19 B-ALL patients across four treatment phases. Proteomic analysis revealed dynamic alterations in immune response, inflammatory regulation, complement activation, and cellular metabolism during treatment. Cytokine release syndrome (CRS)-associated differentially expressed proteins predominantly involved complement and coagulation cascades, cell adhesion molecules, and phagosome pathways. Metabonomic profiling demonstrated enrichment in taurine and hypotaurine metabolism, primary bile acid biosynthesis, and steroid hormone biosynthesis pathways during CAR-T therapy.
Stage-specific metabolites of CRS revealed escalating arginine and proline metabolism dysregulation and nicotinate-nicotinamide metabolism activation, correlating with inflammatory escalation and multi-organ injury.
Cox regression analysis was used to screen 6 protein [(SCRN2, OAF, SBSN, ERP44, TWF2 and ENSA) and 7 metabolic (pseudouridine, 3-methylglutarylcarnitine, 3-(2-hydroxyphenyl) propanoic acid, N-acetylthreonine, PC(18:1(9Z)/16:0), PE(P-18:0/20:4(5Z,8Z,11Z,14Z)), and Cer(d18:1/24:1(15Z)] markers, which showed good predictive ability and provided potential biomarkers for CRS monitoring and survival prediction.
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