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

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.

Quantitative 3D structured illumination microscopy of nuclear structures.

3D structured illumination microscopy (3D-SIM) is the super-resolution technique of choice for multicolor volumetric imaging. Here we provide a validated sample preparation protocol for labeling nuclei of cultured mammalian cells, image acquisition and registration practices, and downstream image analysis of nuclear structures and epigenetic marks. Using immunostaining and replication labeling combined with image segmentation, centroid mapping and nearest-neighbor analyses in open-source environments, 3D maps of nuclear structures are analyzed in individual cells and normalized to fluorescence standards on the nanometer scale. This protocol fills an unmet need for the application of 3D-SIM to the technically challenging nuclear environment, and subsequent quantitative analysis of 3D nuclear structures and epigenetic modifications. In addition, it establishes practical guidelines and open-source solutions using ImageJ/Fiji and the TANGO plugin for high-quality and routinely comparable data generation in immunostaining experiments that apply across model systems. From sample preparation through image analysis, the protocol can be executed within one week.