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.

There is an important need in immuno-oncology to develop reliable immunohistochemistry (IHC) to assess the expression of CTLA-4+ tumor-infiltrating lymphocytes in human cancers and quantify them with image analysis (IA). We used commercial polyclonal and monoclonal antibodies and characterized three chromogenic cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) assays with suitable specificity and sensitivity for use in formalin-fixed, paraffin-embedded (FFPE) tissues. We found variable numbers of CTLA-4+ lymphocytes in multiple types of cancer and secondary lymphoid organs (SLOs) and other normal human tissues. Combining CTLA-4 with CD3, CD4, or CD8 by immunofluorescence showed that CTLA-4+ lymphocytes in SLOs and tumors were typically CD3+ and CD4+, but not CD8+. Individual lymphocytes expressed CTLA-4 either as primarily granular cytoplasmic staining or as excentric globular deposits. The CTLA-4/FoxP3 (forkhead box P3 protein) duplex IHC demonstrated that CTLA-4+/FoxP3− lymphocytes predominated in the germinal centers of SLOs and tumor tertiary lymphoid structures (TLSs), whereas CTLA-4+/FoxP3+ lymphocytes populated the T-cell zone of SLOs and TLSs, plus tumor stroma. IA scoring was highly comparable with pathologist scoring for CTLA-4 and CTLA-4/FoxP3 assays and a FoxP3 single IHC. Our findings show that CTLA-4 IHC can be used to reliably label lymphocytes in FFPE human tissues, making it possible to investigate the role of CTLA-4 in the tumor microenvironment.

The kinetics of stem and progenitor cell differentiation at the single-cell level provides essential clues to the complexity of the underlying decision-making circuits. In many hematopoietic progenitor cells, differentiation is accompanied by the expression of lineage-specific markers and by a transition from a non-adherent to an adherent state. Here, using the granulocyte-macrophage progenitor (GMP) as a model, we introduce a label-free approach that allows one to follow the course of this transition in hundreds of single cells in parallel. We trap single cells in patterned arrays of micro-wells and use phase-contrast time-lapse movies to distinguish non-adherent from adherent cells by an analysis of Brownian motion. This approach allowed us to observe the kinetics of induced differentiation of primary bone-marrow-derived GMPs into macrophages. The time lapse started 2 hours after addition of the cytokine M-CSF, and nearly 80% of the population had accomplished the transition within the first 20 h. The analysis of Brownian motion proved to be a sensitive and robust tool for monitoring the transition, and thus provides a high-throughput method for the study of cell differentiation at the single-cell level.

Cancer therapy via redirected lysis mediated by antibodies and antibody-derived agents relies on the availability of substantial numbers of sufficiently active immune effector cells. To monitor antitumor responses before and during therapy, sensitive methods are needed, capable of quantitating specific lysis of target cells. Here we present a chip-based single-cell cytometric assay, which uses adherent human target cells arrayed in structured micro-fields. Using a fluorescent indicator of cell death and time-lapse microscopy in an automated high-throughput mode, we measured specific target cell lysis by activated human NK cells, mediated by the therapeutic single chain triplebody SPM-2 (33-16-123). This antibody-derived tri-specific fusion protein carries binding sites for the myeloid antigens CD33 and CD123 and recruits NK cells via a binding site for the Fc-receptor CD16. Specific lysis increased with increasing triplebody concentration, and the single-cell assay was validated by direct comparison with a standard calcein-release assay. The chip-based approach allowed measurement of lysis events over 16 hours (compared to 4 hours for the calcein assay) and required far smaller numbers of primary cells. In addition, dynamic properties inaccessible to conventional methods provide new details about the activation of cytolytic effector cells by antibody-derived agents. Thus, the killing rate exhibited a dose-dependent maximum during the reaction interval. In clinical applications ex vivo monitoring of NK activity of patient's endogenous cells will likely help to choose appropriate therapy, to detect impaired or recovered NK function, and possibly to identify rare subsets of cancer cells with particular sensitivity to effector-cell mediated lysis.