Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, No.201, Sec. 2, Shipai Rd., Taipei, 11217, Taiwan.
Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
J Transl Med. 2022 Mar 16;20(1):131. doi: 10.1186/s12967-022-03335-5.
Immune checkpoint blockade therapy has revolutionized non-small cell lung cancer treatment. However, not all patients respond to this therapy. Assessing the tumor expression of immune checkpoint molecules, including programmed death-ligand 1 (PD-L1), is the current standard in predicting treatment response. However, the correlation between PD-L1 expression and anti-PD-1/PD-L1 treatment response is not perfect. This is partly caused by tumor heterogeneity and the common practice of assessing PD-L1 expression based on limited biopsy material. To overcome this problem, we developed a novel method that can make formalin-fixed, paraffin-embedded tissue translucent, allowing three-dimensional (3D) imaging. Our protocol can process tissues up to 150 μm in thickness, allowing anti-PD-L1 staining of the entire tissue and producing high resolution 3D images. Compared to a traditional 4 μm section, our 3D image provides 30 times more coverage of the specimen, assessing PD-L1 expression of approximately 10 times more cells. We further developed a computer-assisted PD-L1 quantitation method to analyze these images, and we found marked variation of PD-L1 expression in 3D. In 5 of 33 needle-biopsy-sized specimens (15.2%), the PD-L1 tumor proportion score (TPS) varied by greater than 10% at different depth levels. In 14 cases (42.4%), the TPS at different depth levels fell into different categories (< 1%, 1-49%, or ≥ 50%), which can potentially influence treatment decisions. Importantly, our technology permits recovery of the processed tissue for subsequent analysis, including histology examination, immunohistochemistry, and mutation analysis. In conclusion, our novel method has the potential to increase the accuracy of tumor PD-L1 expression assessment and enable precise deployment of cancer immunotherapy.
免疫检查点阻断疗法彻底改变了非小细胞肺癌的治疗方式。然而，并非所有患者对该疗法都有反应。评估肿瘤免疫检查点分子的表达，包括程序性死亡配体 1（PD-L1），是预测治疗反应的当前标准。然而，PD-L1 表达与抗 PD-1/PD-L1 治疗反应之间的相关性并不完美。这部分是由于肿瘤异质性和基于有限的活检材料评估 PD-L1 表达的常见做法所致。为了克服这个问题，我们开发了一种新方法，可以使福尔马林固定、石蜡包埋的组织半透明，从而实现三维（3D）成像。我们的方案可以处理厚度达 150 μm 的组织，实现整个组织的抗 PD-L1 染色，并产生高分辨率的 3D 图像。与传统的 4 μm 切片相比，我们的 3D 图像提供了 30 倍的标本覆盖范围，评估了大约 10 倍的细胞 PD-L1 表达。我们进一步开发了一种计算机辅助 PD-L1 定量分析方法来分析这些图像，结果发现 3D 中的 PD-L1 表达存在明显的变化。在 33 个针芯活检大小的标本中（15.2%），有 5 个标本在不同深度的 PD-L1 肿瘤比例评分（TPS）变化超过 10%。在 14 个病例（42.4%）中，不同深度的 TPS 属于不同的类别（<1%、1-49%或≥50%），这可能会影响治疗决策。重要的是，我们的技术允许回收处理后的组织进行后续分析，包括组织学检查、免疫组化和突变分析。总之，我们的新方法有可能提高肿瘤 PD-L1 表达评估的准确性，并实现癌症免疫治疗的精确部署。
