PD-L1 immunostaining scoring for non-small cell lung cancer based on immunosurveillance parameters
Manuel A. Silva, Karen A. Ryall, Claudia Wilm, Jenifer Caldara, Hans Juergen Grote, Janet C. Patterson‐Kane
Abstract
Manuel A. Silva, Karen A. Ryall, Claudia Wilm, Jenifer Caldara, Hans Juergen Grote, Janet C. Patterson‐Kane
Abstract
Non-Small Cell Lung Cancer (NSCLC) is the leading cause of cancer death globally, and new immunotherapies developed and under development targeting PD-1/PD-L1 checkpoint inhibition require accurate patient selection to assure good clinical outcome. PD-L1 immunohistochemistry is the current biomarker assay used for patient selection, but still imprecise in predicting therapy response. Exploring this issue, we performed computational tissue analysis of PD-L1 immunostaining in procured NSCLC tissues (n = 50) using the Merck KGaA anti-PD-L1 clone MKP1A07310. Staining patterns and PD-L1 cut-off points were interrogated using relevant cancer immune-surveillance biomarkers. Groups with high PD-L1 expression levels (above 25/50% staining cut-off points) were enriched for a biomarker profile in the tumor-nest and microenvironment indicating escape from host-immunity, as represented by increased numbers of cells positive for CD8 and Granzyme B (immune-effectors), FOXP3 (immune-suppressive), and CD68 (P < 0.05). Manual analysis of PD-L1 staining patterns identified tumors with an immune-induced reactive pattern relevant for immunotherapy that would ordinarily be excluded by the arbitrary 25% staining threshold (P < 0.05). Conversely, some cases with completely or predominantly immune-independent constitutive PD-L1 staining patterns that indicate insensitivity to immunotherapy may have been incorrectly selected using this staining cut-off point criterion. Therefore, we propose differentiation of reactive vs constitutive PD-L1 staining patterns to improve the accuracy of this biomarker assay in selecting NSCLC patients for PD-1/PD-L1 immunotherapy.
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Non-Small Cell Lung Cancer (NSCLC) is the leading cause of cancer death globally, and new immunotherapies developed and under development targeting PD-1/PD-L1 checkpoint inhibition require accurate patient selection to assure good clinical outcome. PD-L1 immunohistochemistry is the current biomarker assay used for patient selection, but still imprecise in predicting therapy response. Exploring this issue, we performed computational tissue analysis of PD-L1 immunostaining in procured NSCLC tissues (n = 50) using the Merck KGaA anti-PD-L1 clone MKP1A07310. Staining patterns and PD-L1 cut-off points were interrogated using relevant cancer immune-surveillance biomarkers. Groups with high PD-L1 expression levels (above 25/50% staining cut-off points) were enriched for a biomarker profile in the tumor-nest and microenvironment indicating escape from host-immunity, as represented by increased numbers of cells positive for CD8 and Granzyme B (immune-effectors), FOXP3 (immune-suppressive), and CD68 (P < 0.05). Manual analysis of PD-L1 staining patterns identified tumors with an immune-induced reactive pattern relevant for immunotherapy that would ordinarily be excluded by the arbitrary 25% staining threshold (P < 0.05). Conversely, some cases with completely or predominantly immune-independent constitutive PD-L1 staining patterns that indicate insensitivity to immunotherapy may have been incorrectly selected using this staining cut-off point criterion. Therefore, we propose differentiation of reactive vs constitutive PD-L1 staining patterns to improve the accuracy of this biomarker assay in selecting NSCLC patients for PD-1/PD-L1 immunotherapy.
Key concepts: Immunotherapy, Biomarker, Immunosurveillance, Immunostaining, Lung cancer, Immune system, Cancer immunotherapy, FOXP3