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肺癌免疫治疗的不完美预测指标——一个有待进一步研究的领域。

Imperfect Predictors for Lung Cancer Immunotherapy-A Field for Further Research.

作者信息

Wojas-Krawczyk Kamila, Kubiatowski Tomasz

机构信息

Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, Lublin, Poland.

Department of Clinical Oncology, Saint John of Dukla Oncology Centre of the Lublin Region, Lublin, Poland.

出版信息

Front Oncol. 2020 Nov 30;10:568174. doi: 10.3389/fonc.2020.568174. eCollection 2020.

Abstract

The armamentarium for lung cancer immunotherapy has been strengthened using two groups of monoclonal antibodies: 1) anti-PD-1 antibodies, including pembrolizumab and nivolumab, which block the programmed death 1 receptor on the lymphocyte surface, resulting in increasing activity of these cells, and 2) anti-PD-L1 antibodies, including atezolizumab, durvalumab, and avelumab, which block the ligand for the PD-1 molecule on tumor cells and on tumor-infiltrating immune cells. The effectiveness of both groups of antibodies has been proven in many clinical trials, which translates into positive immunotherapeutic registrations for cancer patients. Regarding the predictive factor, PD-L1 expression on cancer cells is the only biomarker validated in prospective clinical trials used for qualification to immunotherapy in advanced non-small cell lung cancer (NSCLC) patients. However, it is not an ideal one. Unfortunately, no clinical benefits could be noted in patients with high PD-L1 expression on tumor cells against the effectiveness of immunotherapy that may be observed in patients without PD-L1 expression. Furthermore, the mechanism of antitumor immune response is extremely complex, multistage, and depends on many factors. Cancer cells could be recognized by the immune system, provided tumor-specific antigen presentation, and these arise as a result of somatic mutations in tumor cells. Based on novel immunotherapy registration, high tumor mutation burden (TMB) has become an important predictive factor. The intensity of lymphocyte infiltration in tumor tissue may be another predictive factor. The effectiveness of anti-PD-L1 immunotherapy is observed in patients with high expression of genes associated with the effector function of T lymphocytes (i.e., their ability to produce IFN-gamma). This does not end the list of potential factors that become useful in qualification of cancer patients for immunotherapy. There remains a need to search for new and perfect predictive factors for immunotherapy.

摘要

肺癌免疫治疗的手段通过两组单克隆抗体得到了加强

1)抗程序性死亡蛋白1(PD-1)抗体,包括帕博利珠单抗和纳武利尤单抗,它们可阻断淋巴细胞表面的程序性死亡蛋白1受体,从而增强这些细胞的活性;2)抗程序性死亡配体1(PD-L1)抗体,包括阿替利珠单抗、度伐利尤单抗和阿维鲁单抗,它们可阻断肿瘤细胞和肿瘤浸润免疫细胞上PD-1分子的配体。两组抗体的有效性已在多项临床试验中得到证实,这为癌症患者带来了积极的免疫治疗注册结果。关于预测因素,癌细胞上的PD-L1表达是前瞻性临床试验中唯一被验证可用于晚期非小细胞肺癌(NSCLC)患者免疫治疗资格认定的生物标志物。然而,它并非理想的生物标志物。遗憾的是,肿瘤细胞上PD-L1高表达的患者并未显示出相对于无PD-L1表达患者免疫治疗有效性的临床获益。此外,抗肿瘤免疫反应机制极其复杂、具有多阶段性且取决于多种因素。肿瘤细胞发生体细胞突变后可呈现肿瘤特异性抗原,从而使癌细胞能够被免疫系统识别。基于新的免疫治疗注册结果,高肿瘤突变负荷(TMB)已成为一个重要的预测因素。肿瘤组织中淋巴细胞浸润的强度可能是另一个预测因素。在与T淋巴细胞效应功能相关基因(即产生γ干扰素的能力)高表达的患者中可观察到抗PD-L1免疫治疗的有效性。这并非潜在因素的全部,仍有必要寻找新的、完善的免疫治疗预测因素。

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