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Interleukin-10 Is a Promising Marker for Immune-Related Adverse Events in Patients With Non-Small Cell Lung Cancer Receiving Immunotherapy

BACKGROUND: Immune checkpoint inhibitors (ICIs) brought about a major paradigm shift in non-small cell lung cancer (NSCLC) treatment. However, the use of ICIs is related to an unforeseeable pattern of immune-related adverse events (irAEs). Hence, more precise biomarkers are needed to predict the inc...

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Detalles Bibliográficos
Autores principales: Wang, Haowei, Zhou, Fei, Zhao, Chao, Cheng, Lei, Zhou, Caicun, Qiao, Meng, Li, Xuefei, Chen, Xiaoxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863608/
https://www.ncbi.nlm.nih.gov/pubmed/35222434
http://dx.doi.org/10.3389/fimmu.2022.840313
Descripción
Sumario:BACKGROUND: Immune checkpoint inhibitors (ICIs) brought about a major paradigm shift in non-small cell lung cancer (NSCLC) treatment. However, the use of ICIs is related to an unforeseeable pattern of immune-related adverse events (irAEs). Hence, more precise biomarkers are needed to predict the incidence of irAEs to prevent overtreatment of ICIs and decrease occurrences of irAEs. This study was designed to identify capable clinical features and plasma inflammatory factors for predicting irAEs. METHODS: A total of 67 patients who received ICI monotherapy or ICI-based combination therapy were retrospectively identified. Clinical characteristics and plasma inflammatory cytokines were collected and analyzed to screen potential biological markers associated with irAEs. The chi-square test, Fisher’s test, and the Mann–Whitney U test were performed for the primary analysis. The optimal cutoff value was determined by a receiver operating characteristic (ROC) curve. Univariate and multivariate logistic regression models were used to identify risk factors of irAEs. Univariate and multivariate Cox proportional hazards were also performed. RESULTS: Out of 67 patients, 40 (59.7%) experienced irAEs, and 7 (10.4%) experienced severe adverse events (grade ≥ 3). Among these analyzed immune profile biomarkers, only interleukin−10 (IL-10) was related to the risk of irAEs. A high baseline IL−10 plasma level (odds ratio (OR) = 5.318, 95% CI 1.174–24.081, p = 0.030) was found to be a tremendous and independent risk factor for the development of irAEs. Also, for the dynamic analysis, upregulation of IL-10 after one cycle of ICI treatment was positively related to the occurrence of irAEs (OR = 5.712, 95% CI 1.088–29.993, p = 0.039). When pneumonitis, the most common irAEs, was analyzed, only baseline high-expression IL-10 was accompanied with the incidence of pneumonitis (OR = 9.969, 95% CI 1.144–86.843, p = 0.037). CONCLUSION: Baseline and dynamic IL-10 plasma levels are tremendously and independently related to higher risk in the development of irAEs and could be utilized for medical practice to monitor adverse events in patients with ICI treatment.