Weyerer Veronika, Strissel Pamela L, Strick Reiner, Sikic Danijel, Geppert Carol I, Bertz Simone, Lange Fabienne, Taubert Helge, Wach Sven, Breyer Johannes, Bolenz Christian, Erben Philipp, Schmitz-Draeger Bernd J, Wullich Bernd, Hartmann Arndt, Eckstein Markus
Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Krankenhausstr. 8-10, 91054 Erlangen, Germany.
Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), 91054 Erlangen, Germany.
Cancers (Basel). 2021 May 12;13(10):2327. doi: 10.3390/cancers13102327.
Immune therapy has gained significant importance in managing urothelial cancer. The value of PD-L1 remains a matter of controversy, thus requiring an in-depth analysis of its biological and clinical relevance.
A total of 193 tumors of muscle-invasive bladder cancer patients (MIBC) were assessed with four PD-L1 assays. PD-L1 scoring results were correlated with data from a comprehensive digital-spatial immune-profiling panel using descriptive statistics, hierarchical clustering and uni-/multivariable survival analyses.
PD-L1 scoring algorithms are heterogeneous (agreements from 63.1% to 87.7%), and stems from different constellations of immune and tumor cells (IC/TC). While Ventana IC5% algorithm identifies tumors with high inflammation and favorable baseline prognosis, CPS10 and the TCarea25%/ICarea25% algorithm identify tumors with TC and IC expression. Spatially organized immune phenotypes, which correlate either with high PD-L1 IC expression and favorable prognosis or constitutive PD-L1 TC expression and poor baseline prognosis, cannot be resolved properly by PD-L1 algorithms. PD-L1 negative tumors with relevant immune infiltration can be detected by sTILs scoring on HE slides and digital CD8 scoring.
Contemporary PD-L1 scoring algorithms are not sufficient to resolve spatially distributed MIBC immune phenotypes and their clinical implications. A more comprehensive view of immune phenotypes along with the integration of spatial PD-L1 expression on IC and TC is necessary in order to stratify patients for ICI.
免疫疗法在尿路上皮癌的治疗中已变得极为重要。PD-L1的价值仍存在争议，因此需要对其生物学和临床相关性进行深入分析。
使用四种PD-L1检测方法对193例肌肉浸润性膀胱癌患者（MIBC）的肿瘤进行评估。通过描述性统计、层次聚类以及单变量/多变量生存分析，将PD-L1评分结果与来自全面数字空间免疫图谱面板的数据相关联。
PD-L1评分算法具有异质性（一致性从63.1%到87.7%），且源于免疫细胞和肿瘤细胞（IC/TC）的不同组合。虽然Ventana IC5%算法可识别出具有高炎症反应和良好基线预后的肿瘤，但CPS10以及TCarea25%/ICarea25%算法可识别出具有TC和IC表达的肿瘤。与高PD-L1 IC表达和良好预后相关的空间组织化免疫表型，或与组成性PD-L1 TC表达和不良基线预后相关的免疫表型，无法通过PD-L1算法得到妥善解析。通过HE玻片上的sTILs评分和数字CD8评分可检测到具有相关免疫浸润的PD-L1阴性肿瘤。
当代PD-L1评分算法不足以解析空间分布的MIBC免疫表型及其临床意义。为了对ICI治疗的患者进行分层，有必要对免疫表型有更全面的认识，并整合IC和TC上的空间PD-L1表达情况。
