Inge L J, Dennis E
Roche Tissue Diagnostics, Tucson, USA.
Immunooncol Technol. 2020 May 11;6:2-8. doi: 10.1016/j.iotech.2020.04.001. eCollection 2020 Jun.
Immune checkpoint inhibitors targeting programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) have rapidly become integral to standard-of-care therapy for non-small cell lung cancer and other cancers. Immunohistochemical (IHC) staining of PD-L1 is currently the accepted and approved diagnostic assay for selecting patients for PD-L1/PD-1 axis therapies in certain indications. However, the inherent biological complexity of PD-L1 and the availability of several PD-L1 assays - each with different detection systems, platforms, scoring algorithms and cut-offs - have created challenges to ensure reliable and reproducible results based on subjective visual assessment by pathologists. The increasing adoption of computer technologies into the daily workflow of pathology provides an opportunity to leverage these tools towards improving the clinical value of PD-L1 IHC assays. This review describes several image analysis software programs of computer-aided PD-L1 scoring in the hope of driving further discussion and technological advancement in digital pathology and artificial intelligence approaches, particularly as precision medicine evolves to encompass accurate simultaneous assessment of multiple features of cancer cells and their interactions with the tumor microenvironment.
靶向程序性细胞死亡蛋白1（PD-1）和程序性细胞死亡配体1（PD-L1）的免疫检查点抑制剂已迅速成为非小细胞肺癌和其他癌症标准治疗方案中不可或缺的一部分。目前，PD-L1的免疫组织化学（IHC）染色是在某些适应症中选择适合接受PD-L1/PD-1轴疗法患者的公认且获批的诊断检测方法。然而，PD-L1固有的生物学复杂性以及多种PD-L1检测方法的存在——每种检测方法都有不同的检测系统、平台、评分算法和临界值——给基于病理学家主观视觉评估确保获得可靠且可重复的结果带来了挑战。计算机技术在病理学日常工作流程中的日益应用为利用这些工具提高PD-L1 IHC检测的临床价值提供了契机。本综述描述了几种用于计算机辅助PD-L1评分的图像分析软件程序，以期推动数字病理学和人工智能方法方面的进一步讨论和技术进步，尤其是随着精准医学的发展，要同时准确评估癌细胞的多个特征及其与肿瘤微环境的相互作用。
