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:Glycoconjugate Nanoparticle-Based Systems in Cancer Immunotherapy: Novel Designs and Recent Updates.
Glycoconjugate Nanoparticle-Based Systems in Cancer Immunotherapy: Novel Designs and Recent Updates.
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多年来,细胞表面聚糖(特别是肿瘤相关碳水化合物抗原,TACAs)一直是被动和主动抗癌免疫治疗设计的目标。免疫疗法作为多种恶性肿瘤治疗方法的最新进展已经彻底改变了抗肿瘤治疗方案。检查点抑制剂、CAR-T 细胞、溶瘤病毒疗法、单克隆抗体和疫苗已被开发出来,许多获批疗法已在一部分患者中带来了显著疗效。然而,其中许多疗法对特定患者群体具有高度选择性,因此,寻找改进的治疗方法和完善递送技术仍是持续而热烈的研究领域。这些药物大多针对蛋白质/肽表位,但基于聚糖的靶点正日益受到关注,少数已获批的免疫疗法其活性归功于寡糖靶点。此外,纳米技术和纳米颗粒衍生系统可以基于肿瘤选择性策略,帮助改善这些药物向特定器官和细胞类型的递送。本综述将首先概述该研究领域的一些历史起源,随后重点介绍过去5年的工作。基于治疗设计方面的进展,可以预测优化系统在提高患者阳性结局百分比方面的未来前景。
For many years, cell-surface glycans (in particular, Tumor-Associated Carbohydrate Antigens, TACAs) have been the target of both passive and active anticancer immunotherapeutic design. Recent advances in immunotherapy as a treatment for a variety of malignancies has revolutionized anti-tumor treatment regimens. Checkpoint inhibitors, Chimeric Antigen Receptor T-cells, Oncolytic virus therapy, monoclonal antibodies and vaccines have been developed and many approvals have led to remarkable outcomes in a subset of patients.
However, many of these therapies are very selective for specific patient populations and hence the search for improved therapeutics and refinement of techniques for delivery are ongoing and fervent research areas. Most of these agents are directed at protein/peptide epitopes, but glycans-based targets are gaining in popularity, and a handful of approved immunotherapies owe their activity to oligosaccharide targets.
In addition, nanotechnology and nanoparticle-derived systems can help improve the delivery of these agents to specific organs and cell types based on tumor-selective approaches. This review will first outline some of the historical beginnings of this research area and subsequently concentrate on the last 5 years of work. Based on the progress in therapeutic design, predictions can be made as to what the future holds for increasing the percentage of positive patient outcomes for optimized systems.
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