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在肺癌中进行精准免疫肿瘤学反应的体外建模。

Ex vivo modeling of precision immuno-oncology responses in lung cancer.

机构信息

Translational Immunology Research Program (TRIMM), Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki, Helsinki, Finland.

出版信息

Sci Adv. 2024 Nov;10(44):eadq6830. doi: 10.1126/sciadv.adq6830. Epub 2024 Oct 30.

Abstract

Despite immunotherapy's promise in cancer treatment, patient responses vary substantially because of the individual nature of the immune system and the lack of reliable biomarkers. To address this issue, we developed a precision ex vivo platform that integrates patient-specific tumor and immune cells to study the mechanisms of antitumor immune response, predict immunotherapy outcomes, and identify effective treatments. This platform revealed unique single-cell immune response mechanisms and sensitivities to standard-of-care immunotherapies. Furthermore, we were able to identify a synergistic combination of anti-programmed cell death protein 1 (anti-PD-1) together with a Casitas B lineage lymphoma-b inhibitor that overcame anti-PD-1 resistance in selected patient samples. Activation of the interferon-γ-stimulated cytokines predicted combination efficacy, while immunosuppressive cytokines were associated with poor response. Our findings underscore the platform's potential in tailoring immunotherapies and advancing drug development, offering avenues for personalized cancer treatment.

摘要

尽管免疫疗法在癌症治疗方面具有广阔的前景,但由于免疫系统的个体差异以及缺乏可靠的生物标志物,患者的反应差异很大。为了解决这个问题,我们开发了一种精密的体外平台,该平台整合了患者特异性的肿瘤和免疫细胞,以研究抗肿瘤免疫反应的机制、预测免疫治疗的结果,并确定有效的治疗方法。该平台揭示了独特的单细胞免疫反应机制和对标准免疫疗法的敏感性。此外,我们还能够确定抗程序性细胞死亡蛋白 1(anti-PD-1)与 Casitas B 细胞淋巴瘤-b 抑制剂的协同组合,该组合克服了选定患者样本中对 anti-PD-1 的耐药性。干扰素-γ 刺激细胞因子的激活预测了联合治疗的疗效,而免疫抑制性细胞因子与不良反应相关。我们的研究结果强调了该平台在定制免疫疗法和推进药物开发方面的潜力,为个性化癌症治疗提供了途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c83/11524168/8c70f8232bae/sciadv.adq6830-f1.jpg

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