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.
CAR-T(CAR-T)细胞在血液系统恶性肿瘤中的应用推动了这种免疫治疗形式的显著进展。
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Baseline immune state and T-cell clonal kinetics are associated with durable response to CAR-T therapy in large B-cell lymphoma.
Baseline immune state and T-cell clonal kinetics are associated with durable response to CAR-T therapy in large B-cell lymphoma.
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采用靶向CD19的CAR-T 细胞(CAR-Ts)的工程化细胞治疗已彻底改变复发/难治性大B细胞淋巴瘤(LBCL)患者的结局,但与应答相关的细胞和分子特征在很大程度上仍未明确。
我们通过整合单细胞RNA和T细胞受体测序、流式细胞术和质谱流式细胞术,分析了50例接受axicabtagene ciloleucel治疗的LBCL患者从单采日(第-28天/基线)至CAR-T 输注后28天的系列外周血样本,以描述与CAR-T 应答相关的特征。与应答相关的治疗前患者特征包括B细胞存在以及绝对淋巴细胞计数与绝对单核细胞计数比值(ALC/AMC)升高。应答者的输注产物中富集克隆扩增、高度活化的CD8+ T细胞。
我们将这些观察扩展至ZUMA-1队列中的99例患者,并识别出一部分基线B细胞升高的患者,其中80%为完全缓解者。我们将B细胞比例0.5%和ALC/AMC 1.2整合到一个双因素预测模型中,并将该模型应用于ZUMA-1队列。符合1项或两项标准的患者估计1年无进展生存率为65%,而两项标准均不符合的患者为31%。
我们的结果表明,患者基线时的免疫状态通过调节T细胞单采产物组成以及在治疗前促进更有利的循环免疫区室,影响对CAR-T 产生应答的可能性。这些基线免疫特征可在CAR-T 前于临床环境中便捷检测,可用于预测治疗应答。
Engineered cellular therapy with CD19-targeting chimeric antigen receptor T cells (CAR-Ts) has revolutionized outcomes for patients with relapsed/refractory large B-cell lymphoma (LBCL), but the cellular and molecular features associated with response remain largely unresolved.
We analyzed serial peripheral blood samples ranging from the day of apheresis (day -28/baseline) to 28 days after CAR-T infusion from 50 patients with LBCL treated with axicabtagene ciloleucel by integrating single-cell RNA and T-cell receptor sequencing, flow cytometry, and mass cytometry to characterize features associated with response to CAR-T.
Pretreatment patient characteristics associated with response included the presence of B cells and increased absolute lymphocyte count to absolute monocyte count ratio (ALC/AMC). Infusion products from responders were enriched for clonally expanded, highly activated CD8+ T cells.
We expanded these observations to 99 patients from the ZUMA-1 cohort and identified a subset of patients with elevated baseline B cells, 80% of whom were complete responders.
We integrated B-cell proportion 0. 5% and ALC/AMC 1. 2 into a 2-factor predictive model and applied this model to the ZUMA-1 cohort. Estimated progression-free survival at 1 year in patients meeting 1 or both criteria was 65% vs 31% for patients meeting neither criterion.
Our results suggest that patients' immunologic state at baseline affects the likelihood of response to CAR-T through both modulation of the T-cell apheresis product composition and promoting a more favorable circulating immune compartment before therapy. These baseline immunologic features, measured readily in the clinical setting before CAR-T, can be applied to predict response to therapy.
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