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:Recent advancement in targeted therapy and role of emerging technologies to treat cancer.
Recent advancement in targeted therapy and role of emerging technologies to treat cancer.
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癌症是一类复杂疾病,表现为细胞异常生长和扩散。DNA突变、化学或环境暴露、病毒感染、慢性炎症及激素异常等均可能导致癌症。耐药和毒性使癌症治疗更加复杂,而癌症类型多样,也难以制定通用治疗指南。二代测序降低了基因检测成本,可发现能够使用专门药物治疗的基因突变。人工智能、机器学习、活检、二代测序和数字病理可推动个体化癌症治疗,帮助识别患者特异性生物靶点并制定治疗方案。单克隆抗体、CAR-T 和癌症疫苗是有前景的癌症治疗方式;近期纳入这些疗法的试验显示,其临床结局和药物耐受性优于传统化疗。将这些疗法与新技术结合,可能改变癌症治疗并使更多患者获益。本文综述单克隆抗体、双特异性抗体、双特异性T细胞衔接器、双可变结构域抗体、CAR-T 疗法、癌症疫苗、溶瘤病毒、基于脂质纳米颗粒的mRNA癌症疫苗等靶向治疗的开发、挑战及其在不同癌症中的临床结局,并探讨人工智能和机器学习如何帮助发现新的癌症治疗靶点。
Cancer is a complex disease that causes abnormal cell growth and spread. DNA mutations, chemical or environmental exposure, viral infections, chronic inflammation, hormone abnormalities, etc. , are underlying factors that can cause cancer. Drug resistance and toxicity complicate cancer treatment.
Additionally, the variability of cancer makes it difficult to establish universal treatment guidelines. Next-generation sequencing has made genetic testing inexpensive. This uncovers genetic mutations that can be treated with specialty drugs. AI (artificial intelligence), machine learning, biopsy, next-generation sequencing, and digital pathology provide personalized cancer treatment. This allows for patient-specific biological targets and cancer treatment. Monoclonal antibodies, CAR-T, and cancer vaccines are promising cancer treatments.
Recent trial data incorporating these therapies have shown superiority in clinical outcomes and drug tolerability over conventional chemotherapies. Combinations of these therapies with new technology can change cancer treatment and help many.
This review discusses the development and challenges of targeted therapies like monoclonal antibodies (mAbs), bispecific antibodies (BsAbs), bispecific T cell engagers (BiTEs), dual variable domain (DVD) antibodies, CAR-T therapy, cancer vaccines, oncolytic viruses, lipid nanoparticle-based mRNA cancer vaccines, and their clinical outcomes in various cancers.
We will also study how artificial intelligence and machine learning help find new cancer treatment targets.
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