Background: The majority of patients with lung cancer exhibit drug resistance after anti-PD-1 immunotherapy, leading to shortened patient survival time. Previous studies have suggested an association between epigenetic abnormalities such as methylation and clinical response to anti-PD-1 immunotherapy, while the role of SUMOylation in resistance to anti-PD-1 antibody immunotherapy is still unclear.
Methods: Here, the mRNA expression of 15 SUMO machinery components in PBMC from lung cancer patients receiving anti-PD-1 immunotherapy were analyzed using real-time PCR. Base on the percentage change in mRNA levels, the relationship between the expression of SUMO machinery components and outcomes of anti-PD-1 immunotherapy, and the influencing factors of SUMOylation were evaluated. PBMC was treated with different concentrations of 2-D08 (a specific inhibitor of SUMOylation) in vitro, and analyzed the activation and the death rates of lymphocyte subsets by flow cytometry analysis.
Results: A predictive method, base on the gene expression of three SUMO machinery components (SUMO1, SUMO3 and UBE2I), were developed to distinguish non-responders to PD-1 inhibitors. Furthermore, the number of lymphocytes in peripheral blood significantly reduced in the dysregulated SUMOylation groups (the percentage change >100 or -50 ~ -100 groups). In vitro studies confirmed that lightly low SUMOylation level improved the activation status of T and NK lymphocytes, but extremely low SUMOylation level lead to the increased death rates of lymphocytes.
Conclusion: Our findings implied that dysregulated gene expression of SUMO machinery components could induce the resistance of anti-PD-1 immunotherapy in lung cancer by upregulating the death of peripheral blood lymphocytes. These data might provide effective circulating biomarkers for predicting the efficacy of anti-PD-1 immunotherapy, and uncovered a novel regulatory mechanism of resistance to anti-PD-1 immunotherapy.
Keywords: PD-1; Sumoylation; lymphocyte; peripheral blood; resistance.
Copyright © 2024 Wang, Sun, Liu, Xu, Li, Zhang and Huang.