PD-L1 and nectin-4 expression and genomic characterization of bladder cancer with divergent differentiation

PD-L1和nectin-4表达及分化程度不同的膀胱癌的基因组特征

阅读:1

Abstract

BACKGROUND: Bladder cancer with divergent differentiation (BCDD) comprises a heterogenous group of tumors with a poor prognosis, and differential expression of nectin-4 and programmed death ligand-1 (PD-L1) has been reported in BCDD. Importantly, nectin-4 expression in bladder cancer is associated with response to enfortumab vedotin, and PD-L1 expression is associated with responses to immune checkpoint inhibitors (ICIs). METHODS: The authors conducted a retrospective review identifying 117 patients with advanced or metastatic BCDD who were treated at Winship Cancer Institute from 2011 to 2021. They performed immunohistochemistry staining for nectin-4 and PD-L1 expression by histologic subtype as well as genomic analysis of these patients, including RNA sequencing, whole-exome sequencing, and fusion detection analysis as well as a subgroup genomic analysis of patients with BCDD who received ICIs. RESULTS: The results indicated that nectin-4 expression was highest in the groups who had the squamous and plasmacytoid subtypes, whereas the group that had the sarcomatoid subtype (70.8%) had the highest proportion of PD-L1-positive patients. Genomic analysis yielded several key findings, including a 50% RB1 mutation rate in patients who had small cell BCDD, targetable PIK3CA mutations across multiple subtypes of BCDD, and significantly higher expression of TEC in responders to ICIs. CONCLUSIONS: In this study, the authors identified clinically relevant data on nectin-4 and PD-L1 expression in patients with rare bladder tumors. They also identified several novel findings in the genomic analysis that highlight the role of precision medicine in this population of patients. Larger, prospective studies are needed to validate these hypothesis-generating data.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。