PhD Science Writer, New York, New York.
Computational Oncology, Program for Computational Immuno-Oncology, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer, New York, New York.
Ann N Y Acad Sci. 2021 Apr;1489(1):30-47. doi: 10.1111/nyas.14526. Epub 2020 Nov 13.
Cancer immunotherapy has dramatically changed the approach to cancer treatment. The aim of targeting the immune system to recognize and destroy cancer cells has afforded many patients the prospect of achieving deep, long-term remission and potential cures. However, many challenges remain for achieving the goal of effective immunotherapy for all cancer patients. Checkpoint inhibitors have been able to achieve long-term responses in a minority of patients, yet improving response rates with combination therapies increases the possibility of toxicity. Chimeric antigen receptor T cells have demonstrated high response rates in hematological cancers, although most patients experience relapse. In addition, some cancers are notoriously immunologically "cold" and typically are not effective targets for immunotherapy. Overcoming these obstacles will require new strategies to improve upon the efficacy of current agents, identify biomarkers to select appropriate therapies, and discover new modalities to expand the accessibility of immunotherapy to additional tumor types and patient populations.
癌症免疫疗法极大地改变了癌症治疗方法。靶向免疫系统以识别和摧毁癌细胞的目标为许多患者提供了实现深度、长期缓解和潜在治愈的前景。然而,要实现所有癌症患者有效免疫治疗的目标,仍存在许多挑战。检查点抑制剂已能够使少数患者获得长期缓解,但联合治疗提高缓解率会增加毒性的可能性。嵌合抗原受体 T 细胞在血液癌症中显示出高缓解率,但大多数患者会复发。此外,一些癌症在免疫上是众所周知的“冷”,通常不是免疫治疗的有效靶点。克服这些障碍将需要新的策略来提高现有药物的疗效,确定生物标志物以选择合适的治疗方法,并发现新的模式来扩大免疫疗法对更多肿瘤类型和患者群体的可及性。