Genomic correlates of response to immune checkpoint blockade

Abstract

Despite impressive durable responses, immune checkpoint inhibitors do not provide a long-term benefit to the majority of patients with cancer. Understanding genomic correlates of response and resistance to checkpoint blockade may enhance benefits for patients with cancer by elucidating biomarkers for patient stratification and resistance mechanisms for therapeutic targeting. Here we review emerging genomic markers of checkpoint blockade response, including those related to neoantigens, antigen presentation, DNA repair, and oncogenic pathways. Compelling evidence also points to a role for T cell functionality, checkpoint regulators, chromatin modifiers, and copy-number alterations in mediating selective response to immune checkpoint blockade. Ultimately, efforts to contextualize genomic correlates of response into the larger understanding of tumor immune biology will build a foundation for the development of novel biomarkers and therapies to overcome resistance to checkpoint blockade.

Fig. 1 |. Framework for genomic correlates of response to immune checkpoint blockade within the tumor immune microenvironment.

The left side outlines correlates of response, focusing on antigen presentation and recognition; the right side delineates resistance pathways that promote tumor immune evasion and induce immunosuppressive cells, which in turn inhibit the T cell-mediated anti-tumor response. Credit: Debbie Maizels/Springer Nature

Fig. 2 |. Antigen presentation and genomic correlates of response to immune checkpoint blockade.

HLA genes HLA-A, HLA-B, and HLA-C encode the MHC class I proteins that present intracellular peptides on the cell surface to T cell receptors (TCRs) and require B2M for stabilization on the cell surface. IFN-γ, which can be released by activated T cells, binds IFNGR1/2 on tumors, which triggers JAK-STAT signaling that activates IFN response genes, including IRF1, which induces the transcription of other genes to increase the surface expression of PD-L1 and MHC molecules. Genomic mechanisms of checkpoint blockade response include upregulation of IFN-γ response gene expression^,, loss of protein tyrosine phosphatase non-receptor type 2 (PTPN2), and germline HLA heterozygosity. Conversely, genomic pathways of resistance include B2M loss^,–, somatic HLA loss of heterozygosity, reduced HLA gene expression, increased expression of MEX3B, IFNGR1/2 or IRF1copy-number loss, JAK1/2 inactivation^,,, APLNR (apelin receptor) loss, and amplification of negative regulators of the IFN-γ pathway, including SOCS1 (suppressor of cytokine signaling 1) and PIAS4 (protein inhibitor of activated STAT4). Credit: Debbie Maizels/Springer Nature

Fig. 3 |. Trial designs to overcome checkpoint blockade resistance.

a, A basket trial matches therapeutic agents based on genomic alterations irrespective of tumor site of origin. In the illustrated example, breast, colorectal, and prostate tumors are tested for TGF-β and IFN-γ transcriptomic signatures. Those patients whose tumors possess high TGF-β or low IFN-γ signatures are treated with TGF-β inhibitors or STING agonists, respectively, in addition to anti-PD-1 therapy, while tumors without genomic targets are treated with chemotherapy and anti-PD-1 therapy. b, An adaptive trial design employs interim analyses to make modifications, such as expansion of patient cohorts with more promising responses, illustrated in the figure as an expansion of the breast cancer cohort. Credit: Debbie Maizels/Springer Nature.