医学
免疫系统
免疫疗法
淋巴细胞
T细胞
免疫检查点
流式细胞术
人口
免疫学
肿瘤科
内科学
环境卫生
作者
Ling Chen,Hongyu Tan,Ruixuan Geng,Yifan Li,Yingyi Wang,Taisheng Li
标识
DOI:10.1111/1759-7714.15493
摘要
ABSTRACT Purpose Our study aimed to comprehensively describe the features of peripheral blood multiple immune cell phenotypes in solid tumor patients during pretreatment and after immunotherapy, providing a more convenient approach for studying the prognosis of immunotherapy in different solid tumor patients. Methods We prospectively recruited patients with advanced solid tumors from Peking Union Medical College Hospital (PUMCH) between February 2023 and April 2024. Using multicolor flow cytometry, our study comprehensively observed and described the signatures of peripheral blood lymphocyte subsets including activation, proliferation, function, naïve memory, and T cell exhaustion immune cell subsets in this population of pretreatment and after immunotherapy. Results Our study enrolled 59 advanced solid tumor patients with immunotherapy and 59 healthy controls were matched by age and gender. The results demonstrated a marked upregulation in the expression of lymphocyte activation markers CD38 and HLA‐DR, as well as exhaustion and proliferation markers PD‐1 and Ki67, in solid tumor patients compared to healthy controls. After immune checkpoint blockade (ICB) treatment, mainly the expression of Ki67CD4+T and HLA‐DRCD38CD4+T, was significantly upregulated compared to pretreatment levels ( p = 0.017, p = 0.019, respectively). We further found that gynecological tumors with better prognoses had higher baseline activation levels of CD4+ T cells compared to other solid tumors with poorer prognoses. Conclusion Our study elucidated the characteristics of different lymphocyte subsets in the peripheral blood of solid tumor patients. Further research revealed changes in the phenotypes of different lymphocyte subsets after ICIs treatment, with the activated phenotype of CD4+ T cells playing a crucial role in the antitumor effect. This lays the groundwork for further exploration of prognostic biomarkers and predictive models for cancer patients with immunotherapy.
科研通智能强力驱动
Strongly Powered by AbleSci AI