Predicting immunotherapy response through genomics

•Biomarkers are key to maximize clinical benefit of treatment with anti-CTLA4, anti-PD1 and anti-PDL1 drugs.•Genomic correlates of neoantigen load, such as defective mismatch repair and tumour mutation burden, are clinically applicable, but fail to completely explain differences in response patterns to immune checkpoint inhibitors.•HLA genotype, interferon expression and copy number variation are other promising biomarkers related to immune response pathways.•Somatic mutations in genes such as TP53, PTEN, PBRM1 and ARID1A may also help identify responders to immunotherapy. Immune checkpoint inhibitors (ICI) aim to restore the immune system anti-tumor function by blocking two inhibitory axes: CTLA-4/CD28 and PD1/PDL1. ICI is established as a treatment option for multiple cancers, but their remarkable clinical impact is observed only in a fraction of patients. Together with their adverse effects and high cost, it’s imperative to identify patients who are likely to benefit from this type of treatment. Genomic features represent promising candidates as predictive biomarkers of response to ICI, with agnostic FDA-approvals of an anti-PD1 drug for tumors with microsatellite instability and tumors with a high mutational burden. Other genomic markers are also emerging to help refine patient selection. In this review, we discuss recent progress in genomic biomarkers development and its challenges, with a focus on alterations in the neoantigen burden, immune, and oncogenic pathways.