The field of immune-oncology is exploding dramatically. Immunotherapy agents overcome tumor evasion through targeted immune checkpoint inhibitors and scientifically driven combination therapies including multiple immune-stimulating and chemotherapeutic agents. However, not all patients are benefited from immunotherapy and precision medicine requires tremendous understanding of the tumor microenvironment. Complex tissue architecture, heterogeneous biomarker expression as well as visual and cognitive traps affects visual interpretation by pathologists. Moreover, increased requirement of precise diagnostic cut-points of the biomarker measurements poses a problem for pathologists, who are asked to scan thousands of cells in a tissue section and to arrive at a score accurately in order to give a result that can predict a response to the targeted therapy. The promise of digital pathology and image analysis tools help overcome these challenges by performing intelligent interpretations that cannot be gleaned by the pathologist's eye.
Flagship Biosciences developed a platform for understanding the abundance and spatial relationships of different immune cell types and for immune cell clustering using duplex immunohistochemistry. Researchers also adopted HALO platform by Indica labs for digital quantification of PD-L1 tumor cells in melanoma. Another area of concern is the availability of multiple PD-L1 diagnostic immunohistochemistry (IHC) assay and lack of clarity on immunolabelling parameters determined by pathologists and the comparability across assays. A customized Image Analysis scoring PD-L1 scoring solution to permit a quantitative comparison of the 4 PDL1 IHC assays was developed by Definiens that enables to quantify the percentage of positive tumor cells on a whole slide image for 4 PD-L1 assays by co-registration of images and comparing identical areas per case. Aperio Image Toolbox and GENIE image analysis tool (Leica Microsystems) quantifies membrane PD-L1 expression in malignant epithelial cells and macrophages based on Region of Interest analysis.
Biomarker expression in lymphoid or other immune effector cells is a special challenge for pathologists to measure immune phenotypes, which may predict patient responses to immunomodulating therapies, was observed in the Blueprint 2 study. To overcome the aforementioned challenges, Optra PD-L1 automated image analysis approach generates separate scores for interpretation of PD-L1 IHC expression on both tumor and immune cells without the need of multiple biomarkers for immune cells in the same tissue section in a single read. While all the features/functions are available for integrating, analyzing and collaborating on a single platform; OptraSCAN and image analysis suite can support whole slide scanning, integrated image analysis, image registration and quantification of tumor and/or immune cells based on biomarker content to aid immune-oncology development.
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