通过靶向肿瘤相关巨噬细胞的嵌合受体工程化溶瘤病毒重振内源性抗肿瘤免疫
Rejuvenating endogenous antitumor immunity via a chimeric receptor-engineered oncolytic virus targeting tumor-associated macrophages.
我们的研究结果定义了一个精准溶瘤平台,该平台能够解除TAM介导的免疫抑制,同时增强适应性免疫,为癌症免疫治疗提供了一条有前景的转化途径。
英文原题:Shaping the Future of Prostate Cancer Care: The Promise and Pitfalls of Gene- and Cell-Based Therapeutics.
前列腺癌(PCa)在全球范围内大规模影响男性人群。
前列腺癌(PCa)在全球范围内大规模影响男性人群。本文全面概述了PCa不断演变中的治疗格局,并强调了基于基因和细胞的策略的前景与挑战。放疗、化疗和手术等传统治疗模式存在各种局限性;然而,分子精准治疗、免疫疗法以及创新基因编辑工具(如成簇规律间隔短回文重复序列(CRISPR)相关(Cas)系统)日益增长的影响力,正在减少这些传统疗法的局限性。对溶瘤病毒(OV)疗法、病毒和非病毒基因递送系统以及基于细胞的免疫疗法(包括嵌合抗原受体(CAR)T细胞和树突状细胞(DC)疗法)当前进展的比较,展示了它们的治疗潜力以及影响其有效性的关键挑战,包括肿瘤异质性(TH)、免疫逃逸和免疫抑制性肿瘤微环境(TME)。联合策略整合了免疫检查点阻断、放射增敏化疗和生物标志物指导的干预措施,以改善治疗结局。它还提供了一个视角,用于分析人工智能(AI)、多组学整合和协作研究网络在塑造更个性化标准以提升PCa患者照护方面的未来作用。
Prostate Cancer (PCa) affects the population worldwide on a large scale in men. This paper presents a comprehensive overview of the evolving therapeutic landscape for PCa and highlights the promise and challenges of gene- and cell-based strategies. There are various limitations to conventional modalities, such as radiotherapy, chemotherapy, and surgery; however, the growing impact of molecular precision, immunotherapies, and innovative gene-editing tools, such as the clustered regularly interspaced short palindromic repeat (CRISPR)-associated (Cas) system, minimizes the limitations of these conventional therapies. Comparisons of the current progress in Oncolytic Virus (OV) based therapies, viral and non-viral gene delivery systems, and cell-based immunotherapies including Chimeric Antigen Receptor (CAR) T cells and Dendritic Cell (DC) therapies demonstrate both their therapeutic potentials and key challenges to their effectiveness that include Tumor Heterogeneity (TH), immune evasion, and the immunosuppressive Tumor Microenvironment (TME). The combination approach integrates the control point blockade, radiosensitizing chemotherapeutics, and biomarker-guided interventions to improve treatment outcomes. It also provides a perspective for analyzing the future roles of Artificial Intelligence (AI), multi-omics integration, and collaborative research networks in shaping standards that are more personalized to enhance care for PCa patients.
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