The Ratio of IP10 to IL-8 in Plasma Reflects and Predicts the Response of Patients With Lung Cancer to Anti-PD-1 Immunotherapy Combined With Chemotherapy
Open Access
- 12 April 2021
- journal article
- research article
- Published by Frontiers Media SA in Frontiers in Immunology
Abstract
Antibodies against checkpoint inhibitors such as anti-programmed cell death protein 1 (PD-1) and its ligand anti-programmed death ligand 1 (PD-L1) have shown clinical efficacy in the treatment of multiple cancers. However, there are only a few studies on biomarkers for these targeted immunotherapies, especially in peripheral blood. We first studied the role of interferon-induced protein-10 (IP10) combined with interleukin-8 (IL-8) in peripheral blood as a biomarker of immune-combined chemotherapy for lung cancer and multiple cancers. We used the high-throughput cytokine detection platform and performed bioinformatics analysis of blood samples from 67 patients with lung cancer and 24 with multiple cancers. We selected the ratio of IP-10 to IL-8 (S2/S0, ratio of changes at 10–12 weeks after treatment to baseline) to predict the response to immunotherapy combined with chemotherapy and evaluate the survival of lung cancer patients and mixed cancer patients. In patients treated with the combination therapy, the specificity and sensitivity of IL-8 and IP10 together as predictors were improved compared with those of IL-8 and IP10 alone. Our conclusion was verified in not only lung cancer but also multiple cancer research cohorts. We then further validated the predictive effect of biomarkers in different histologic types of NSCLC and chemotherapy combined with different PD-1 drug groups. Subsequent validation should be conducted with a larger number of patients. The proposed marker IP10 (S2/S0)/IL-8 (S2/S0), as a predictive immunotherapy biomarker, has broad prospects for future clinical applications in treating patients with multiple intractable neoplasms.Funding Information
- National Natural Science Foundation of China (81672274)
- National Science and Technology Major Project (2018ZX09201-013)
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