Abstract
e13521
Background: Immunohistochemical (IHC) assays are presently used as the gold standard predictive tests for immunotherapy but are compromised due to a number of potential variables. Comparative studies have demonstrated differing levels of PD-L1 staining between assays which appears independent of the antibody binding epitope. Secondly, inter-reader reliability even between expert pathologists is problematic particularly for assessment of PD-L1 positive immune cell populations. Methods: To improve predictive testing for anti PD-L1/PD1 immunotherapies we have developed and validated a Next Generation Sequencing Platform, Immunofocus, able to perform high-throughput quantitative PD-L1 gene expression levels in routine diagnostic PWET biopsies. We applied Immunofocus to a cohort of 130 NSCLCs and compared PD-L1 gene expression levels with PD-L1 IHC scores generated using the VENTANA PD-L1 (SP142) Assay. The PD-L1 IHC assessment was carried out double blinded by an independent laboratory. PD-L1 IHC scores were calculated using an algorithm combining tumour proportion score (TPS) with a PD-L1 positive immune cell (IC) score and immune cell area. Results: An exceptionally high degree of correlation was observed between the NGS PD-L1 levels with the combined PD-L1 IHC scores (P < 0.001). Therapeutic cut points for NGS PD-L1 levels were identified corresponding to PD-L1 IHC defined clinical cut points. Notably, ~20% of patients with negative PD-L1 IHC scores showed high NGS PD-L1 expression levels. We hypothesize that these cases represent false negatives and identify a cohort of patients who have shown significant response rates to anti-PD-L1/PD-directed immunotherapies. Conclusions: The Immunofocus NGS PD-L1 assay has potential to greatly improve patient selection for immunotherapy by removing the IHC assay variables and inter-reader variability which compromise current PD-L1 IHC tests while also providing standardized high throughput in the clinical setting. Immunofocus is able to integrate gene expression with somatic mutation analysis allowing capture of networks regulating the immune-checkpoint including for example adaptive and innate resistance pathways, JAK1/2 pathways, differential MHC expression, TEFF gene signature, neoantigen surrogates such as DDR defects and TMB. The integration of NGS PD-L1 expression with other putative biomarkers of response is presently ongoing to further improve prediction of response.
© 2020 American Society of Clinical Oncology
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