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IRISH-1: a retrospective cohort study of PD-L1 by RNA ISH (RISH) as a potentially superior companion biomarker for immune checkpoint inhibitors in NSCLC

Checkpoint inhibitors for cancer immunotherapy have dramatically changed the treatment options for non-small cell lung cancer (NSCLC). anti-PD1 has been to the forefront in this area with FDA approvals granted in 2015 for Nivolumab and Pembrolizumab. Additional drugs are in development, and as of April 2016, 5 drugs may be competing in the same treatment area, raising challenges for pathologists.
Key to these approvals is the use of a companion or complementary diagnostic, in this instance levels of PD-L1 as measured using immunohistochemistry (IHC). However, given that all of the drugs in development have different assays, different cut-offs and different staining platforms, this raises very significant challenges. To test using several different assays, with the same or different platforms on the same tissue sample is simply impractical.
Efforts are in place by the IASLC Pathology committee to compare the current PD-L1 IHC tests – the Blueprint Project. However, we believe that another possibility exists. Given the issues regarding IHC (different antibodies thus different epitopes, and inter-individual variability in the interpretation of results), we believe that rather than looking at protein the selectivity and specificity of a technique called RNA in situ hybridization (RISH) may be superior and it may therefore be more rational to instead look at the mRNA for PD-L1 in order to stratify patients.
We therefore propose to conduct an analysis of PD-L1 in a cohort of patients with NSCLC by RISH to ascertain whether this technique may be a candidate single assay for the measurement of PD-L1, and will attempt to develop a machine-based algorithm for use with scanning systems. Finally, as PD-L1 expression is associated with increased numbers of CD8+ Tumor Infiltrating Lymphocytes (TILs) in NSCLC, we will attempt to assess the feasibility of dual RISH staining in a subset of patients.