Article Text
Abstract
Background Natural killer (NK) cells exhibit potent activity in pre-clinical models of diverse hematologic malignancies and solid tumors and infusion of high numbers of NK cells, either autologous or allogeneic, after their ex vivo expansion and activation, has been feasible and safe in clinical studies.
Methods To systematically define molecular features in human tumor cells which determine their degree of sensitivity to human allogeneic NK cells, we quantified the NK cell responsiveness of hundreds of molecularly-annotated ‘DNA-barcoded’ solid tumor cell lines in multiplexed format (PRISM; Profiling Relative Inhibition Simultaneously in Mixtures approach),1 correlating cytotoxicity scores for each cell line with the CCLE transcriptional data2 (RNA-seq), to reveal genes that are associated with resistance or sensitivity to NK cells. In addition, we applied genome-scale CRISPR-based gene editing screens in several solid tumor cell lines to interrogate, at a functional level, which genes regulate tumor cell response to NK cells.3 4Figure 1 schematically depicts the two screens.
Results Based on these orthogonal studies, NK sensitive tumor cells tend to exhibit high levels of the NK cell-activating ligand B7-H6 (NCR3LG1); low levels of the inhibitory ligand HLA-E; microsatellite instability (MSI) status; high transcriptional signature for chromatin remodeling complexes and low antigen presentation machinery genes. Treatment with HDAC inhibitor reduced the sensitivity of SW620 colon cancer cells, increased antigen presentation machinery, including HLA-E, and reduced B7-H6. Importantly, transcriptional signatures of NK cell-sensitive tumor cells correlate with immune checkpoint inhibitor resistance in clinical samples. Widespread analysis of CCLE transcriptional signatures revealed that cell lines with mesenchymal-like program tend to be more sensitive to NK cells, compared with epithelial-like cell lines. Indeed, mesenchymal tumors tend to have lower expression of antigen presentation machinery in both CCLE and TCGA.
Overview of PRISM and CRISPR studies a, Schematic depiction of PRISM study. b, Schematic depiction of CRISPR screens. c, Histogram of gene fold changes (z-scores). Listed are selected genes with most prominent p-values across more than one screen.
Conclusions This study provides a comprehensive map of mechanisms regulating tumor cell responses to NK cells, with implications for future biomarker-driven applications of NK cell immunotherapies. The integration of PRISM and CRISPR identified potential regulators of tumor cell response to NK cell, which upon further validation, may serve as biomarkers in future NK cell-based studies. Moreover, NK cells may complement T-cells, killing tumor cells that do not respond to immune checkpoint inhibitors.
Acknowledgements This work was supported by Stand Up To Cancer (SU2C) Convergence 2.0 Grant; SU2C Phillip A. Sharp Award for Innovation in Collaboration; Claudia Adams Barr Program in Innovative Basic Cancer Research; Human Frontier Science Program Fellowship; and Leukemia and Lymphoma Society Scholar Award.
References
Yu C, et al., High-throughput identification of genotype-specific cancer vulnerabilities in mixtures of barcoded tumor cell lines. Nat Biotechnol 2016. 34(4): p. 419–23.
Ghandi M, et al. Next-generation characterization of the cancer cell line encyclopedia. Nature 2019. 569(7757): p. 503–508.
Doench JG, et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat Biotechnol 2016. 34(2): p. 184–191.
Shalem O, et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 2014;343(6166): p. 84–87.
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