Cytology cell blocks from malignant pleural effusion are good candidates for PD-L1 detection in advanced NSCLC compared with matched histology samples
BMC Cancer(2020)
Abstract
Background Detection of programmed cell death ligand-1 (PD-L1) by immunohistochemistry (IHC) has been commonly used to predict the efficacy of treatment with PD-1/PD-L1 inhibitors. However, there is limited literature regarding the reliability of PD-L1 testing using malignant pleural effusion (MPE) cell blocks. Here, we assess PD-L1 expression in sections from MPE cell blocks and evaluate the value of IHC double staining in the interpretation of PD-L1 expression. Methods In all, 124 paired formalin-fixed tissues from advanced NSCLC patients, including MPE cell blocks and matched histology samples, were included. PD-L1 expression was assessed using the SP263 assay, and the tumor proportion score (TPS) and the staining intensity were evaluated. PD-L1 staining results were also compared between IHC double and single staining techniques. Results PD-L1 expression was concordant in most paired cases (86/101, 85.1%) among three TPS cut-offs (<1%, 1–49% and ≥ 50%), with a kappa value of 0.774. Moreover, a significant difference in PD-L1 expression between MPE cell blocks and biopsy samples was observed ( p = 0.005). For the 15 discordant pairs, 13 MPE cell block samples showed increased expression of PD-L1. Compared with the standard IHC single PD-L1 assay, double staining with anti-TTF-1 and anti-PD-L1 revealed a negative effect on PD-L1 expression testing and resulted in weaker staining intensity and a lower TPS ( p = 0.000). Conclusions MPE cell block samples are good candidates for PD-L1 expression detection in advanced NSCLC patients. The mechanism and clinical significance of the higher PD-L1 expression rate in MPE cell blocks compared with small biopsy samples remain to be evaluated prospectively.
MoreTranslated text
Key words
Cytology,Immunohistochemistry,Malignant pleural effusion,Non-small-cell lung carcinomas,PD-L1
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined