In our December editorial we discuss the quest for better biomarkers in cancer immunotherapy -
Immune-checkpoint inhibitors that block the immunoinhibitory receptor PD-1 and its ligand PD-L1 or the immunomodulatory receptor CTLA-4 have had a transformational impact on the care of patients with cancer, offering curative potential for patients who until recently had no suitable therapeutic options.
Although high tumor mutational burden , presence of tumor microsatellite instability and mismatch-repair-deficient status, as well as high PD-L1 expression, in tumor cells are well established biomarkers, they are not perfect. For example, some patients with PD-L1-negative tumors do respond to ICI treatment.
As ICIs are tested for more indications, more trial datasets also exist with the potential to both identify and validate potential determinants of response. However, integrating these data has proven challenging due to heterogeneity in trial inclusion criteria, the types of samples collected, workflows for sampling and data processing, as well as assay selection.
In addition to trial-intrinsic differences, restricted access to datasets further complicates biomarker-validation efforts. Although many clinical research journals, including, require inclusion of data availability or sharing statements in published papers, data access is still often limited and results that are shared may not be fully clinically annotated, which greatly reduces their utility for analysis and validation.
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