Istituto Nazionale Tumori Fondazione "G. Pascale", Via Mariano Semmola, 80131, Naples, Italy.
University of Manchester/The Christie NHS Foundation Trust, Manchester, UK.
Drugs. 2016 Jun;76(9):925-45. doi: 10.1007/s40265-016-0588-x.
Strategies to help improve the efficacy of the immune system against cancer represent an important innovation, with recent attention having focused on anti-programmed death (PD)-1/PD-ligand 1 (L1) monoclonal antibodies. Clinical trials have shown objective clinical activity of these agents (e.g., nivolumab, pembrolizumab) in several malignancies, including melanoma, non-small-cell lung cancer, bladder cancer, squamous head and neck cancer, renal cell cancer, ovarian cancer, microsatellite-unstable colorectal cancer, and Hodgkin's lymphoma. Expression of PD-L1 in the tumor microenvironment appears to be crucial for therapeutic activity, and initial trials suggested positive PD-L1 tumor expression was associated with higher response rates. However, subsequent observations have questioned the prospect of using PD-L1 expression as a biomarker for selecting patients for therapy, especially since many patients considered PD-L1-negative experience a benefit from treatment. Importantly, there is not yet a definitive test for determination of PD-L1 and a cut-off reference for PD-L1-positive status has not been established. Immunohistochemistry with different antibodies and different thresholds has been used to define PD-L1 positivity (1-50 %), with no clear superiority of one threshold over another for identifying which patients respond. Moreover, the type of cells on which PD-L1 expression is most relevant is not yet clear, with immune infiltrate cells and tumor cells both being used. In conclusion, while PD-L1 expression is often a predictive factor for treatment response, it must be complemented by other biomarkers or histopathologic features, such as the composition and amount of inflammatory cells in the tumor microenvironment and their functional status. Multi-parameter quantitative or semi-quantitative algorithms may become useful and reliable tools to guide patient selection.
旨在提高免疫系统对癌症疗效的策略代表了一项重要的创新,最近的研究重点集中在抗程序性死亡(PD)-1/PD-配体 1(L1)单克隆抗体上。临床试验表明,这些药物(如 nivolumab、pembrolizumab)在多种恶性肿瘤中具有客观的临床活性,包括黑色素瘤、非小细胞肺癌、膀胱癌、头颈部鳞状细胞癌、肾细胞癌、卵巢癌、微卫星不稳定结直肠癌和霍奇金淋巴瘤。肿瘤微环境中 PD-L1 的表达似乎对治疗活性至关重要,最初的试验表明,肿瘤 PD-L1 表达阳性与更高的反应率相关。然而,随后的观察结果对使用 PD-L1 表达作为选择患者进行治疗的生物标志物的前景提出了质疑,尤其是因为许多被认为是 PD-L1 阴性的患者从治疗中获益。重要的是,目前还没有确定 PD-L1 的明确检测方法,也没有建立 PD-L1 阳性状态的截止参考值。不同的抗体和不同的阈值的免疫组织化学已被用于定义 PD-L1 阳性(1-50%),但没有一种阈值比另一种阈值更能明确识别哪些患者有反应。此外,PD-L1 表达最相关的细胞类型尚不清楚,免疫浸润细胞和肿瘤细胞都被用于研究。总之,虽然 PD-L1 表达通常是治疗反应的预测因素,但它必须与其他生物标志物或组织病理学特征(如肿瘤微环境中炎症细胞的组成和数量及其功能状态)相结合。多参数定量或半定量算法可能成为指导患者选择的有用和可靠工具。