Cerebrospinal fluid immunological cytokines predict intracranial tumor response to immunotherapy in non-small cell lung cancer patients with brain metastases

脑脊液免疫细胞因子可预测非小细胞肺癌脑转移患者颅内肿瘤对免疫疗法的反应

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Abstract

BACKGROUND: Immunotherapy has shown intracranial efficacy in non-small cell lung cancer (NSCLC) patients with brain metastases. However, predictive biomarkers for intracranial response to immunotherapy are lacking. This post-hoc analysis aimed to explore the potential of immunological cytokines in cerebrospinal fluid (CSF) to predict intracranial tumor response to immunotherapy in patients with brain metastases. METHODS: Treatment-naive NSCLC patients with brain metastases who received camrelizumab plus chemotherapy were enrolled. Paired plasma and CSF samples were prospectively collected at baseline and the first treatment assessment. All samples were analyzed for 92 immuno-oncology cytokines using Olink's panels. RESULTS: A total of 28 patients were included in this analysis. At baseline, most immunological cytokines were significantly lower in CSF than in plasma, whereas a subset comprising CD83, PTN, TNFRSF21, TWEAK, ICOSLG, DCN, IL-8, and MCP-1, was increased in CSF. Baseline CSF levels of LAMP3 were significantly higher in patients with intracranial tumor response, while the levels of CXCL10, IL-12, CXCL11, IL-18, TIE2, HGF, and PDCD1 were significantly lower. Furthermore, the CXCL10, CXCL11, TIE2, PDCD1, IL-18, HGF, and LAMP3 in CSF were also significantly associated with intracranial progression-free survival for immunotherapy. The identified cytokines in CSF were decreased at the first treatment evaluation in patients with intracranial tumor response. The logistic CSF immuno-cytokine model yielded an AUC of 0.91, as compared to PD-L1 expression (AUC of 0.72). CONCLUSIONS: Immunological cytokines in CSF could predict intracranial tumor response to immunotherapy in NSCLC patients with brain metastases, and the findings warrant validation in a larger prospective cohort study. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04211090.

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