Clinical response to checkpoint inhibitors-based (CPIs) therapies can vary among tumor types and between patients. This led to a significant amount of pre-clinical and clinical research into biomarker identification. Biomarkers have been found to cover both the tumor itself and the tumor microenvironment. Entering host-related parameters into the equation should provide a valuable strategy for identifying not only factors predictive of treatment efficacy but also of treatment-related toxicity. It is clear that germline variants can offer efficient and easily-assessable indicators (blood DNA) to enlarge the spectrum of predictive markers for CPI-based treatment. A major issue concerns the real functional significance of the reported single-nucleotide polymorphisms (SNPs) linked to CPI-treatment outcome. Powered calculations should lead to an optimal trade-off between sample size and allele frequency. New molecular technologies and new analytical methods should provide opportunities to bridge the knowledge gap between SNP-CPI treatment associations and the functional impact of these SNPs.
Keywords: Check-point inhibitors; Germinal immunogenetics; Immunotherapy; Predictive factors.
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