Profiling of immune features to predict immunotherapy efficacy
Youqiong Ye, Yongchang Zhang, Nong Yang, Qian Gao, Xinyu Ding, Xinwei Kuang, Rujuan Bao, Zhao Zhang, Chaoyang Sun, Bingying Zhou, Li Wang, Qingsong Hu, Chunru Lin, Jianjun Gao, Yanyan Lou, Steven H. Lin, Lixia Diao, Hong Liu, Xiang Chen, Gordon B. Mills, Leng Han
Abstract
) based on dynamic alteration of interleukins in patient plasma as early as two cycles (4-6 weeks) after starting immunotherapy can accurately predict immunotherapy efficacy. Our results reveal a systematic landscape of associations among immune features and provide a noninvasive, cost-effective, and time-efficient approach based on dynamic profiling of pre- and on-treatment plasma to predict immunotherapy efficacy.
Topics & Concepts
ImmunotherapyImmune systemImmune checkpointBiomarkerMedicineImmunologyTumor microenvironmentComputational biologyBiologyBiochemistryCancer Immunotherapy and BiomarkersImmune Cell Function and InteractionImmune cells in cancer