To systematically define molecular features in human tumour cells which determine their degree of sensitivity to human allogeneic natural killer (NK) cells, we quantified the NK cell responsiveness of hundreds of molecularly-annotated "DNA-barcoded" solid tumour cell lines in multiplexed format and applied genome-scale CRISPR-based gene editing screens in several solid tumour cell lines to functionally interrogate which genes in tumour cells regulate the response to NK cells. In these orthogonal studies, NK-sensitive tumour cells tend to exhibit "mesenchymal-like" transcriptional programs; high transcriptional signature for chromatin remodeling complexes; high levels of B7-H6 (NCR3LG1); low levels of HLA-E/antigen presentation genes. Importantly, transcriptional signatures of NK cell-sensitive tumour cells correlate with immune checkpoint inhibitor (ICI) resistance in clinical samples. This study provides a comprehensive map of mechanisms regulating tumour cell responses to NK cells, with implications for future biomarker-driven applications of NK cell immunotherapies.
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. 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), correlating cytotoxicity scores for each cell line with the CCLE transcriptional data (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. 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 an HDAC inhibitor reduced the sensitivity of SW620 colon cancer cells, increased antigen presentation machinery, including HLA-E, and reduced B7-H6. Importantly, we observe that transcriptional signatures of NK cell-sensitive tumor cells correlate with immune checkpoint inhibitor resistance in clinical samples. Strikingly, comprehensive analysis of the CCLE transcriptional signatures revealed that cell lines with mesenchymal-like program tend to be more sensitive to NK cells treatment, compared with cell lines of epithelial-like program. Indeed, mesenchymal tumors tend to have lower expression of antigen presentation machinery in both CCLE and TCGA, suggesting a link between these two machieneries. 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. Citation Format: Michal Sheffer, Emily Lowry, Nicky Beelen, Minasri Borah, Suha Naffar-Abu Amara, Chris C. Mader, Jennifer Roth, Aviad Tsherniak, Olga Dashevsky, Sara Gandolfi, Samantha Bender, Jordan Bryan, Cong Zhu, Li Wang, Ricardo De-Matos Simoes, Channing Yu, Yiguo Hu, Olli Dufva, Marios Giannakis, Todd Golub, Rizwan Romee, Satu Mustjoki, Aedin C. Culhane, Lotte Wieten, Constantine S. Mitsiades. Landscape of molecular events regulating tumor cell responses to natural killer cells [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2020 Oct 19-20. Philadelphia (PA): AACR; Cancer Immunol Res 2021;9(2 Suppl):Abstract nr PO041.
Immunotherapy has remarkably changed the treatment paradigm in hematologic malignancies and natural killer (NK) cell therapy represents an attractive option, as it has been feasible and safe in early clinical trials, without graft-versus-host effects. Nevertheless, the molecular markers determining cancer cell sensitivity or resistance to NK cells, especially in the context of tumor cell interaction with the bone marrow (BM) stromal microenvironment remain incompletely understood, but have major translational relevance since these tumor-stromal interactions have been known to attenuate the response of blood cancer cells to diverse classes of pharmacological agents. To address these questions, we performed NK cell treatment of a series of cell lines from hematologic malignancies by applying a pooled "DNA-barcoded" format of these cell lines (PRISM system). We specifically quantified the dose-dependent responses to primary NK cells for 70 molecularly-annotated blood cancer cell lines, including myeloid and lymphoblastic leukemia, diffuse large B cell lymphoma and 15 multiple myeloma (MM) lines, either in presence or in absence of BM stromal cells (BMSCs) and interferon gamma (IFNg), followed by integrated computational analyses to identify candidate molecular markers correlating with tumor cell sensitivity or resistance to NK cells. NK cell cytotoxicity, quantified by the relative abundance of barcodes in treated cells compared to controls, was correlated with the transcriptional, mutational and other molecular features of each of the 70 cell lines from publicly available databases. Furthermore, data from MM cell lines were compared to our genome-wide loss of function (LOF) and gain of function (GOF) CRISPR screen data in the MM cell line MM.1S. Two distinct clusters of cell lines, sensitive and resistant to NK cell treatment, were identified. Such clusters retained distinct pattern of in vitro resistance in the presence of stroma, while showing an overall markedly decreased NK cell responsiveness, which underscores the protective effect of stromal microenvironment in blood malignancies, regardless of the addition of IFNg. RNA-seq data showed no differences in dependencies between the two clusters and no distinct gene expression patterns at baseline that clearly allows to predict NK cell response, which underscores the heterogeneity of resistance patterns at single gene level, across different hematologic malignancies. However, when comparing baseline RNAseq data to data obtained from previous GOF and LOF CRISPR screens in MM.1S, surface antigens such as PVR, ULBP1, ULBP3 were more frequently downregulated, whereas MUC1 was upregulated in resistant cells clusters. An important observation is that gene lesions such as TP53, PTEN, MMSET, commonly associated with high-risk diseases, do not affect NK cell responses in the cell lines tested. Interestingly, a gene set enrichment analysis (GSEA) showed that the cluster of resistant cells displays upregulation of class I MHC complex, class II MHC complex binding, IL7 pathway and a downregulation of transmembrane receptor protein serine/threonine kinase signaling pathway. GSEA also showed that baseline state of IFN-JAK-STAT signaling correlates with BMSCs-induced NK cell resistance, a result further confirmed by addition of IFNgto tumor-NK cocultures in the absence of BMSCs. No significant differences in NK cell response were observed when comparing cell lines of different hematologic neoplasms, suggesting that candidate markers from these studies may be relevant across different hematologic malignancies. In conclusion, this is the first study of this size correlating the molecular annotation of different concurrently-treated hematologic cell lines with their response to a NK-based treatment in the context of BMSC interaction. This study of a large panel of pooled "DNA-barcoded" cell lines provided complementary and orthogonal information to our LOF and GOF screens, expanding our potential to identify and validate molecular markers for individualized use of NK cell-based therapies in hematologic malignancies. Disclosures Mustjoki: BMS: Honoraria, Research Funding; Novartis: Research Funding; Pfizer: Research Funding. Mitsiades:EMD Serono: Research Funding; Abbvie: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding; Arch Oncology: Research Funding; Fate Therapeutics: Honoraria; Ionis Pharmaceuticals: Honoraria; Takeda: Other: employment of a relative ; Janssen/Johnson & Johnson: Research Funding; TEVA: Research Funding.
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