Immunological profiling for short-term predictive analysis in PD-1/PD-L1 therapy for lung cancer

Abstract

BackgroundImmune checkpoint inhibitors, such as anti-programmed cell death-1 (PD-1) and PD-1 ligand-1 (PD-L1) antibodies, have achieved breakthrough results in improving long-term survival rates in lung cancer. Although high levels of PD-L1 expression and tumor mutational burden have emerged as pivotal biomarkers, not all patients derive lasting benefits, and resistance to immune checkpoint blockade remains a prevalent issue. Comprehending the immunological intricacies of lung cancer is crucial for uncovering the mechanisms that govern responses and resistance to immunomodulatory treatments. This study aimed to explore the potential of peripheral immune markers in predicting treatment efficiency among lung cancer patients undergoing PD-1/PD-L1 checkpoint inhibitors.MethodsThis study enrolled 71 lung cancer patients undergoing PD-1/PD-L1 inhibitor therapy and 20 healthy controls. Immune cell subsets (CD4 + T cells, CD8 + T cells, B cells, NK cells, and NKT cells), phenotypic analysis of T cells and B cells, and PMA/Ionomycin-stimulated lymphocyte function assay were conducted.ResultsLung cancer patients exhibited significant alterations in immune cell subsets, notably an increased percentage of Treg cells. Post-treatment, there were substantial increases in absolute numbers of CD3 + T cells, CD8 + T cells, and NKT cells, along with heightened HLA-DR expression on CD3 + T and CD8 + T cells. Comparison between complete remission and non-complete remission (NCR) groups showed higher Treg cell percentages and HLA-DR + CD4 + T cells in the NCR group.ConclusionThe study findings suggest potential predictive roles for immune cell subsets and phenotypes, particularly Treg cells, HLA-DR + CD4 + T cells, and naïve CD4 + T cells, in evaluating short-term PD-1/PD-L1 therapy efficacy for lung cancer patients. These insights offer valuable prospects for personalized treatment strategies and underscore the importance of immune profiling in lung cancer immunotherapy.