Dynamic immune signatures of patients with advanced non–small-cell lung cancer for infection prediction after immunotherapy

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Abstract

Background: Pulmonary infections are a crucial health concern for patients with advanced non–small-cell lung cancer (NSCLC). Whether the clinical outcome of pulmonary infection is influenced by immunotherapy(IO) remains unclear. By evaluating immune signatures, this study investigated the post-immunotherapy risk of pulmonary infection in patients with lung cancer and identified circulating biomarkers that predict post-immunotherapy infection. Methods: Blood specimens were prospectively collected from patients with NSCLC before and after chemotherapy(C/T) and/or IO to explore dynamic changes in immune signatures. Real-world clinical data were extracted from medical records for outcome evaluation. Mass cytometry and ELISA were employed to analyze immune signatures and cytokine profiles to reveal potential correlations between immune profiles and the risk of infection. Results: The retrospective cohort included 283 patients with advanced NSCLC. IO was associated with a lower risk of pneumonia (odds ratio=0.46, p=0.012). Patients receiving IO and remained pneumonia-free exhibited the most favorable survival outcomes compared with those who received C/T or developed pneumonia (p<0.001). The prospective cohort enrolled 30 patients. The proportion of circulating NK cells significantly increased after treatment in IO alone (p<0.001) and C/T+IO group (p<0.01). An increase in cell densities of circulating PD-1+CD8+(cytotoxic) T cells (p<0.01) and PD-1+CD4+ T cells (p<0.01) were observed in C/T alone group after treatment. In IO alone group, a decrease in cell densities of TIM-3+ and PD-1+ cytotoxic T cells (p<0.05), and PD-1+CD4+ T cells (p<0.01) were observed after treatment. In C/T alone and C/T+IO groups, cell densities of circulating PD-1+ cytotoxic T cells significantly increased in patients with pneumonia after treatment(p<0.05). However, in IO alone group, cell density of PD-1+ cytotoxic T cells significantly decreased in patients without pneumonia after treatment (p<0.05). TNF-α significantly increased after treatment with IO alone (p<0.05) but decreased after C/T alone (p<0.01). Conclusions: Our results indicate that the incorporation of immunotherapy into treatment regimens may potentially offer protective effects against pulmonary infection. Protective effects are associated with reduction of exhausted T-cells and augmentation of TNF-α and NK cells. Exhausted T cells, NK cells, and TNF-α may play crucial roles in immune responses against infections. These observations highlight the potential utility of certain circulating biomarkers, particularly exhausted T cells, for predicting post-treatment infections.

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Luo, Y. H., Shen, C. I., Chiang, C. L., Huang, H. C., & Chen, Y. M. (2024). Dynamic immune signatures of patients with advanced non–small-cell lung cancer for infection prediction after immunotherapy. Frontiers in Immunology, 15. https://doi.org/10.3389/fimmu.2024.1269253

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