Assessment of programmed cell death ligand 1 (PD-L1) immunohistochemical staining is used for decision on treatment with programmed cell death 1 and PD-L1 checkpoint inhibitors in lung adenocarcinomas and squamous cell carcinomas. This study aimed to compare the staining properties of tumor cells between the antibody clones 28-8, 22C3, SP142, and SP263 and investigate interrater variation between pathologists to see if these stainings can be safely evaluated in the clinical setting. Using consecutive sections from a tissue microarray with tumor tissue from 55 resected lung cancer cases, staining with five PD-L1 assays (28-8 from two different vendors, 22C3, SP142, and SP263) was performed. Seven pathologists individually evaluated the percentage of positive tumor cells, scoring each sample applying cutoff levels used in clinical studies: <1% positive tumor cells (score 0), 1-4% (score 1), 5-9% (score 2), 10-24% (score 3), 25-49% (score 4), and >50% positive tumor cells (score 5). Pairwise analysis of antibody clones showed weighted kappa values in the range of 0.45-0.91 with the highest values for comparisons with 22C3 and 28-8 and the lowest involving SP142. Excluding SP142 resulted in kappa 0.75-0.91. Weighted kappa for interobserver variation between pathologists was 0.71-0.96. Up to 20% of the cases were differently classified as positive or negative by any pathologist compared with consensus score using ≥1% positive tumor cells as cutoff. A significantly better agreement between pathologists was seen using ≥50% as cutoff (0-5% of cases). In conclusion, the concordance between the PD-L1 antibodies 22C3, 28-8 and SP263 is relatively good when evaluating lung cancers and suggests that any one of these assays may be sufficient as basis for decision on treatment with nivolumab, pembrolizumab, and durvalumab. The scoring of the pathologist presents an intrinsic source of error that should be considered especially at low PD-L1 scores.

S U M M A R YThe purpose of the present study was to establish a rapid and reproducible method for quantification of tissue-infiltrating leukocytes using computerized image analysis. To achieve this, the staining procedure, the image acquisition, and the image analysis method were optimized. Because of the adaptive features of the human eye, computerized image analysis is more sensitive to variations in staining compared with manual image analysis. To minimize variations in staining, an automated immunostainer was used. With a digital scanner camera, low-magnification images could be sampled at high resolution, thus making it possible to analyze larger tissue sections. Image analysis was performed by color thresholding of the digital images based on values of hue, saturation, and intensity color mode, which we consider superior to the red, green, and blue color mode for analysis of most histological stains. To evaluate the method, we compared computerized analysis of images with a ϫ 100 or a ϫ 12.5 magnification to assess leukocytes infiltrating rat brain tumors after peripheral immunizations with tumor cells genetically modified to express rat interferon-␥ (IFN-␥ ) or medium controls. The results generated by both methods correlated well and did not show any significant differences. The method allows efficient and reproducible processing of large tissue sections that is less time-consuming than conventional methods and can be performed with standard equipment and software.

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Postprandial glucose, insulin and triglyceride concentrations are influenced by dietary fibre-rich meals, depending on fibre source, dose of soluble and total fibre and possibly gender.