Abstract
Immune checkpoint inhibitor therapy has revolutionized lung adenocarcinoma therapy. Treatment with antibodies against the immune checkpoint molecules programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) can induce a durable response in a subset of patients. Immunohistochemistry characterization of tumor PD-L1 expression using either a histopathology specimen or a cytopathology specimen has been shown to correlate with treatment response. However, the current practice relies on pathologists' visual estimation of tumor PD-L1 staining, which can be variable in certain conditions. Highlighting tumor cells via double immunostaining with PD-L1 and thyroid transcription factor-1 (TTF-1) may improve estimation accuracy. We performed PD-L1 single staining and PD-L1/TTF-1 double staining in 42 pairs of cytopathology and histopathology specimens from lung adenocarcinoma patients. An experienced pathologist visually estimated PD-L1 expression in each case and placed tumor PD-L1 expression into 1 of 3 categories: <1%, 1%-49%, or ≥50%. A medical technologist also performed estimations of the same cases based on a count of 200 tumor cells, and the results were compared. PD-L1/TTF-1 double immunohistochemistry could better identify the PD-L1-positive tumor cells in cytopathology specimens compared with PD-L1 single staining. The concordance of PD-L1 expression categorization between the pathologist's visual estimation and the medical technologist's counting was increased by double staining in cytopathology specimens (Cohen's weighted kappa: single stain, 0.784; double stain, 0.880). Double staining reduced possible error in the pathologist's visual estimation of PD-L1 expression from 9.5% to 4.8%. The benefit was not observed in histopathology specimens. A simple PD-L1/TTF-1 double immunohistochemistry technique can be applied successfully to cytopathology specimens in better identifying patients who can potentially benefit from immune checkpoint blockade treatment.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.