Abstract

IntroductionProgrammed cell death ligand-1 (PD-L1) expression is a promising biomarker for identifying treatment related to non-small cell lung cancer (NSCLC). Automated image analysis served as an aided PD-L1 scoring tool for pathologists to reduce inter- and intrareader variability. We developed a novel automated tumor proportion scoring (TPS) algorithm, and evaluated the concordance of this image analysis algorithm with pathologist scores.MethodsWe included 230 NSCLC samples prepared and stained using the PD-L1(SP263) and PD-L1(22C3) antibodies separately. The scoring algorithm was based on regional segmentation and cellular detection. We used 30 PD-L1(SP263) slides for algorithm training and validation.ResultsOverall, 192 SP263 samples and 117 22C3 samples were amenable to image analysis scoring. Automated image analysis and pathologist scores were highly concordant [intraclass correlation coefficient (ICC) = 0.873 and 0.737]. Concordances at moderate and high cutoff values were better than at low cutoff values significantly. For SP263 and 22C3, the concordances in squamous cell carcinomas were better than adenocarcinomas (SP263 ICC = 0.884 vs 0.783; 22C3 ICC = 0.782 vs 0.500). In addition, our automated immune cell proportion scoring (IPS) scores achieved high positive correlation with the pathologists TPS scores.ConclusionsThe novel automated image analysis scoring algorithm permitted quantitative comparison with existing PD-L1 diagnostic assays and demonstrated effectiveness by combining cellular and regional information for image algorithm training. Meanwhile, the fact that concordances vary in different subtypes of NSCLC samples, which should be considered in algorithm development.

Highlights

  • Programmed cell death ligand-1 (PD-L1) expression is a promising biomarker for identifying treatment related to non-small cell lung cancer (NSCLC)

  • PD-L1 is expressed in many tumors cells (TCs), which can interact with Programmed cell death-1 (PD-1) expressed on cytotoxic T cells and thereby evade the recognition by the host’s immune system [2, 3]

  • Tumor samples demographics Tumor resection samples for PD-L1 assessment were obtained from 230 patients with stage I to IV NSCLC

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Summary

Introduction

Programmed cell death ligand-1 (PD-L1) expression is a promising biomarker for identifying treatment related to non-small cell lung cancer (NSCLC). We developed a novel automated tumor proportion scoring (TPS) algorithm, and evaluated the concordance of this image analysis algorithm with pathologist scores. PD-1/PD-L1 inhibitors are used to block the immuno-escape interaction between TCs and immune cells in a variety of cancers. The Food and Drug Administration (FDA) and European Medicines Agency (EMA) have approved several diagnostic IHC antibodies with respective platforms, such as 22C3, 28-8, 73-10 from Dako (Agilent), SP142, SP263 from Ventana Medical Systems, to assess PD-L1 expression levels in patients with non-small cell lung cancer (NSCLC) [9, 13, 14]

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