Comparison of continuous measures across diagnostic PD-L1 assays in non-small cell lung cancer using automated image analysis

• Published in: Modern pathology 2020-03, Vol.33 (3), p.380-390
• Main Authors: Widmaier, Moritz, Wiestler, Tobias, Walker, Jill, Barker, Craig, Scott, Marietta L., Sekhavati, Farzad, Budco, Alexei, Schneider, Katrin, Segerer, Felix J., Steele, Keith, Rebelatto, Marlon C.
• Format: Article
• Language: English
• Subjects: 13/51; 631/67/1612/1350; 692/53/2421; Algorithms; Apoptosis; Automation; B7-H1 Antigen - analysis; Biomarkers, Tumor - analysis; Carcinoma, Non-Small-Cell Lung - immunology; Carcinoma, Non-Small-Cell Lung - pathology; Cell death; Humans; Image Interpretation, Computer-Assisted; Image processing; Immunohistochemistry; Laboratory Medicine; Lung cancer; Lung Neoplasms - immunology; Lung Neoplasms - pathology; Medical diagnosis; Medicine; Medicine & Public Health; Non-small cell lung carcinoma; Observer Variation; Pathologists; Pathology; PD-1 protein; PD-L1 protein; Predictive Value of Tests; Reproducibility of Results; Small cell lung carcinoma; Tumor cells
• ISSN: 0893-3952; 1530-0285
• DOI: 10.1038/s41379-019-0349-y

Tumor programmed cell death ligand-1 (PD-L1) expression is a key biomarker to identify patients with non-small cell lung cancer who may have an enhanced response to anti-programmed cell death-1 (PD-1)/PD-L1 treatment. Such treatments are used in conjunction with PD-L1 diagnostic immunohistochemistry assays. We developed a computer-aided automated image analysis with customized PD-L1 scoring algorithm that was evaluated via correlation with manual pathologist scores and used to determine comparability across PD-L1 immunohistochemistry assays. The image analysis scoring algorithm was developed to quantify the percentage of PD-L1 positive tumor cells on scans of whole-slide images of archival tumor samples from commercially available non-small cell lung cancer cases, stained with four immunohistochemistry PD-L1 assays (Ventana SP263 and SP142 and Dako 22C3 and 28-8). The scans were co-registered and tumor and exclusion annotations aligned to ensure that analysis of each case was restricted to comparable tissue areas. Reference pathologist scores were available from previous studies. F1, a statistical measure of precision and recall, and overall percentage agreement scores were used to assess concordance between pathologist and image analysis scores and between immunohistochemistry assays. In total, 471 PD-L1-evalulable samples were amenable to image analysis scoring. Image analysis and pathologist scores were highly concordant, with F1 scores ranging from 0.8 to 0.9 across varying matched PD-L1 cutoffs. Based on F1 and overall percentage agreement scores (both manual and image analysis scoring), the Ventana SP263 and Dako 28-8 and 22C3 assays were concordant across a broad range of cutoffs; however, the Ventana SP142 assay showed very different characteristics. In summary, a novel automated image analysis scoring algorithm was developed that was highly correlated with pathologist scores. The algorithm permitted quantitative comparison of existing PD-L1 diagnostic assays, confirming previous findings that indicate a high concordance between the Ventana SP263 and Dako 22C3 and 28-8 PD-L1 immunohistochemistry assays.