Tumor antigen-specific CD8+ T cells play a critical role in antitumor immunity. Clinical trials reinvigorating the immune system via immune checkpoint blockade (ICB) have shown remarkable clinical promise. Numerous studies have identified an association between NKG7 expression and patient outcome across different malignancies. However, aside from these correlative observations, very little is known about NKG7 and its role in antitumor immunity. Herein, we utilized single-cell RNA sequencing (scRNA-seq) datasets, NKG7-deficient mice, NKG7-reporter mice, and mouse tumor models to investigate the role of NKG7 in neoantigen-mediated tumor rejection and ICB immunotherapy. scRNA-seq of tumors from patients with metastatic melanoma or head and neck squamous cell carcinoma revealed that NKG7 expression is highly associated with cytotoxicity and specifically expressed by CD8+ T cells and natural killer (NK) cells. Furthermore, we identified a key role for NKG7 in controlling intratumor T-cell accumulation and activation. NKG7 was upregulated on intratumor antigen-specific CD8+ T cells and NK cells and required for the accumulation of T cells in the tumor microenvironment. Accordingly, neoantigen-expressing mouse tumors grew faster in Nkg7-deficient mice. Strikingly, efficacy of single or combination ICB was significantly reduced in Nkg7-deficient mice.
See related article by Wen et al., p. 162.
Immune checkpoint blockade (ICB) is able to induce durable responses across multiple malignancies, including melanoma, renal, and non–small cell lung cancer (reviewed in refs. 1–3). In a number of these cancers, patients with durable clinical responses following ICB exhibit an immune signature characterized by increased expression of genes associated with IFNγ-producing Th1 cells and cytotoxic T cells (4–6). However, insights into the underlying functional importance of many of the proteins encoded by these genes have lagged significantly behind. Such understanding is essential for the rational design of next-generation immunotherapies.
A gene that consistently appears in large transcriptomic analysis, and is associated with favorable clinical outcomes or responses to immunotherapy in patients with cancer is natural killer cell granule protein 7 (NKG7; refs. 4, 5, 7–9). Despite these associations, the expression, regulation, and function of NKG7 is poorly characterized. NKG7 is an integral membrane protein expressed in the cytotoxic granules of lymphocytes, including natural killer (NK) and CD8+ T cells (10, 11). We recently confirmed localization of NKG7 with cytotoxic granules in CD8+ T cells (12), and others reported NKG7-dependent accumulation of lytic granules in activated CD8+ T cells (13). We also showed that NKG7 is a regulator of lymphocyte granule exocytosis and downstream of inflammation in a broad range of diseases, and NKG7 expressed by NK cells was critical for controlling cancer initiation and metastasis (12).
Here, we used a previously described Nkg7-deficient mouse line and a Nkg7 transcriptional reporter mouse (12) and employed models of CD8+ T cell–mediated rejection and assessed publicly available single-cell RNA sequencing (scRNA-seq) datasets to understand how NKG7 impacts neoantigen-mediated tumor rejection and ICB immunotherapy.
Materials and Methods
Mice greater than 6 weeks of age were used for all experiments unless specified otherwise. Mice were group housed with a maximum of 6 mice per cage and maintained under pathogen-free conditions at the QIMR Berghofer Medical Research Institute Animal Facility (Herston, Queensland, Australia). B6.Tg(Nkg7-cre)/J (B6.Nkg7-cre) mice (12) were crossed to B6.129(Cg)-Gt(ROSA)26Sortm4(ACTB-tdTomato,-EGFP)Luo/J (B6.mT/mG; RRID: IMSR_JAX:007676; ref. 14) mice once to generate a transcriptional reporter of Nkg7 (Nkg7-cre x mT/mG). C57BL/6J (RRID: IMSR_JAX:000664) mice were sourced from the Walter and Eliza Hall Insitute (WEHI; Kew, Victoria, Australia) and bred in house. C57BL/6J NKG7-deficient (Nkg7−/−) mice and perforin-deficient (Pfp−/−) mice were bred in house as described previously (12, 15). Experimental use was in accordance with the “Australian Code of Practice for the Care and Use of Animals for Scientific Purposes” (Australian National Health and Medical Research Council) and approved by the QIMR Berghofer Medical Research Institute Animal Ethics Committee (Herston, Queensland, Australia; approval numbers: A19619M, A19620M). Mice were sex matched and were randomized into groups pretreatment, but not all experiments were blinded.
Tumor cell lines and culture
MC38 (colon adenocarcinoma), MC38-OVAdim, and MC38-OVAbright (16) cells were grown in DMEM (Gibco) supplemented with 10% FCS (Cell Sera), 1% glutamine (Gibco), 1% sodium pyruvate, 1% non-essential amino acids (Gibco), 100 IU/mL penicillin, and 100 μg/mL streptomycin (Gibco). HCmel12-PmelKO-Tyrp1-Scarlett-hgp100 (HCmel12hgp100; melanoma; ref. 17), MCA1956, and MCA 1969 (fibrosarcomas) were cultured in “complete RPMI medium” consisting of RPMI1640 (Gibco) supplemented with 10% FCS (Cell Sera), 1% glutamine (Gibco), 1% sodium pyruvate, 10 mmol/L HEPES, 1% non-essential amino acids (Gibco), 100 IU/mL penicillin, and 100 μg/mL streptomycin (Gibco). All MC38-derived cell lines were maintained at 37°C in the presence of 10% CO2. All cell lines routinely tested negative for Mycoplasma but cell line authentication was not routinely performed.
For primary tumor models, MC38 (1 × 105), MC38-OVAdim (1 × 106), MC38-OVAbright (1 × 106) colon adenocarcinoma cells, MCA 1956 (1 × 106), and MCA 1969 (5 × 105) fibrosarcoma cells, were injected subcutaneously. Tumor growth was measured every 2 days from days 4–7 using digital callipers, with tumor size calculated as the multiple of the longest tumor diameter with its perpendicular diameter. Cells were confirmed to be free of Mycoplasma contamination by bioluminescent assay (Lonza).
In vivo treatments
For depletion and neutralization experiments, mice were injected intraperitoneally with 100–300 μg control Ig (cIg 1-1, Leinco Technologies), 100 μg anti-CD8β (53.5.8, BioXCell) to deplete CD8+ T cells, 50 μg anti-asialoGM1 (Wako) to deplete NK cells, or 250 μg anti-IFNγ (H22, Leinco Technologies) with the dosing schedule indicated in text/figure legends. For immunotherapy experiments, mice were injected intraperitoneally with 50–250 μg anti-PD-1 (RMP1-14, BioXCell), 250 μg anti-CTLA-4 (UC10-4F10, BioXCell) or the equivalent amount of cIg in sterile PBS, in accordance with the dosing schedule in the text.
Tumor digestion and flow cytometry
Tumors, spleens, and peripheral blood were processed using standard protocols. Briefly, tumors were harvested from mice and dissociated using GentleMACS Homogenizer (Miltenyi Biotec) as per manufacturer's instructions followed by incubation with 1 mg/mL Collagenase D (Sigma) and 1 mg/mL DNaseI (Roche) in RPMI medium at 37°C. After 30–45 minutes, tissues were passed through 70 μm cell strainers (Greiner) and further analyzed. Single-cell suspensions of spleens or peripheral blood were depleted from erythrocytes and stained with mAbs in PBS containing 1% (volume for volume) FBS and 2.5 mmol/L EDTA. Dead cells stained by Zombie-Aqua (BioLegend) were excluded from analysis. Antibodies used for the lymphocyte panel are CD45.2-BUV737, TCRβ-PerCP-Cy5.5, NK1.1-AF780, CD4-BV605, CD8-BV711, CD44-PB, CD62L-PE/CY7, CD69-AF488, CD107a-PE, OVA-tetramer-APC, PD-1-BV785. Antibodies used for the myeloid panel were CD45.2-BUV737, CD64-PerCP-Cy5.5, Ly6G-APC, MHC-II-eF780, CD11c-eF450, CD11b-BV605, Ly6C-BV785. For intracellular staining, cells were stimulated in vitro with PMA/Ionomycin and GolgiStop for 4 hours. After cell surface staining, cells were fixed and permebilized for internal IFNγ-PE or APC, Granzyme B-PB, or Foxp3-PB staining followed by flow cytometry analysis on the BD LSR Fortessa 5.
RNA-seq data analysis
RNA-seq data of previously published melanoma (18) and gastric cancer cases (19) were used in the analysis. Sequence reads underwent adapter trimming using Cutadapt (version 1.9; ref. 20) and were aligned using STAR (version 2.5.2a; ref. 21) to the GRCh37 assembly using the gene, transcript, and exon features model of Ensembl (release 70). RSEM (version 1.2.30; ref. 22) was used to quantify transcript abundances and trimmed mean of M-values (TMM) normalization was performed using the edgeR package. NKG7 expression values shown in Supplementary Fig. S1 are log2-transformed TMM values.
scRNA-seq data analysis
Publically available datasets were downloaded and processed via standard Seurat (version 3.1.5) pipeline (23). Analysis was performed in R (version 4.0.1) on a MacBook Pro running Catalina (version 10.15.5). In brief, genes were removed if they were detected in less than three cells. In addition, in the head and neck squamous cell carcinoma (HNSCC) dataset (24) cells were excluded from further analysis if they had less than 200 or more than 2,500 genes or mitochondrial genes were greater than 10% of gene counts. Whereas, the metastatic melanoma dataset (25) was filtered using a lower threshold of 200 and an upper threshold of 8,000 genes. Clusters were identified within the HNSCC dataset using k.param = 20, pcs = 20, and a resolution of 0.4. Clusters were annotated manually by comparing with canonical immune markers. For heatmap generation, the dataset was first downsampled to 300 cells per cluster and the top genes positively correlated (Pearson) with NKG7 expression were plotted. Graphical output from R were formatted using Adobe Illustrator (version 24.1).
Code used in the analysis of publically available scRNA-seq datasets is available on https://github.com/Eomesodermin.
RNA-seq data from a previously published melanoma study (18) was downloaded from the NCBI database (SRA: SRP094781; BioProject: PRJNA356761) and RNA-seq from gastric cancer cases (19) were downloaded from the European Nucleotide Archive (ENA; accession PRJEB25780). scRNA-seq datasets from Tirosh and colleagues (25) and Cillo and colleagues (24) were downloaded from the Gene Expression Omnibus using accession codes GSE72056 and GSE139324, respectively.
All statistical analyses were performed using GraphPad Prism (version 7.0c; GraphPad Software) or R. A P value ≤ 0.05 was considered statistically significant.
Results and Discussion
NKG7 is differentially expressed in numerous disease settings and expression is often associated with patient outcomes. However, the role NKG7 plays in immunotherapy is unknown. We utilized publically available RNA-seq datasets to query NKG7 expression in pretreatment or on-treatment samples of patients with gastric cancer and melanoma who received immunotherapy, respectively. Indeed, patients who had a complete or partial response showed increased NKG7 expression (Supplementary Fig. S1). We next sought to determine which intratumor cell subsets express NKG7. To this end, we analyzed publically available scRNA-seq datasets. The dataset presented in Tirosh and colleagues (25), represents a collection of tumors from 19 patients with metastatic melanoma (Supplementary Fig. S2A), whereas the dataset originally described in Cillo and colleagues (24), contains data from tumor-infiltrating leukocytes from 26 patients with HNSCC (Supplementary Fig. S2B). Analysis of these datasets revealed that NKG7 expression was restricted to cytotoxic cells, namely, CD8+ T cells and NK cells (Supplementary Fig. S2C and S2D). Notably, NKG7 expression was marginally detected or absent in malignant cells as well as myeloid populations. Interestingly, regulatory T cells and conventional CD4+ T cells showed minimal NKG7 expression. Assessment of NKG7 expression across all cell subsets within both disease settings (melanoma and HNSCC) revealed a strong association with markers of cytotoxicity and CD8+ T-cell markers (Supplementary Fig. S2E and S2F). These data show that NKG7 is associated with cytotoxic immune cells and is predominately expressed by tumor-infiltrating NK and CD8+ T cells.
NKG7 regulates tumor growth in multiple mouse models
We have previously demonstrated the role that NKG7 plays in NK cell–mediated control of metastasis (12); however, many primary human tumors contain a significant T-cell infiltrate and successful ICB therapy is largely CD8+ T-cell dependent (26). A number of variably antigenic mouse models of cancer are spontaneously controlled by CD8+ T cells and/or are sensitive to ICB (16). We first evaluated the growth of several of these tumors, including MC38-OVAdim, MC38-OVAbright, and MCA1969, in wild type (WT) versus Nkg7-deficient mice (Fig. 1A–C). In each case, all tumors grew progressively in Nkg7-deficient mice, whereas tumors either grew slower (MC38-OVAdim) or were rejected (MC38-OVAbright and MCA1969) in WT mice. The MCA1969 fibrosarcoma was derived as a spontaneously regressing tumor derived from immune-deficient mice and here T-cell depletion but not NK-cell depletion, from the point of tumor inoculation, allowed equivalent outgrowth in both Nkg7-deficient and WT mice (Fig. 1C). Further analysis in this model revealed a very similar tumor growth profile between Nkg7-deficient and perforin-deficient mice (Supplementary Fig. S3A). Interestingly, the outgrowth of tumors in Nkg7-deficient mice was similar to that in previously well-characterized immune-deficient DNAM-1 (Cd226)−/− mice that lack significant tumor control (Supplementary Fig. S3B; refs. 16, 27).
NKG7 is critical for the efficacy of ICB
We next assessed the functional importance of NKG7 in three different mouse models of cancer, characterized as responsive to ICB. In the MC38 colon adenocarcinoma model, despite the approximately equivalent growth in cIg-treated WT and Nkg7-deficient mice, the therapeutic efficacy of anti-PD1/anti-CTLA4 combination therapy was significantly compromised in Nkg7-deficient mice (Fig. 2A). A similar impact of Nkg7 loss was also observed for anti-PD1/anti-CTLA4 combination therapy in a second experiment (Fig. 2B). Control of the MC38 tumors by the anti-PD1/anti-CTLA4 combination was T-cell dependent in WT (Fig. 2C) and Nkg7-deficient mice (Fig. 2D). Similar loss of activity for ICB monotherapy or combination therapy also occurred in Nkg7-deficient mice in the MCA1956 fibrosarcoma model (Fig. 2E).
Reduced accumulation of tumor-infiltrating CD8+ T cells in NKG7-deficient mice
To learn more about the impact of host NKG7 deficiency on the tumor microenvironment, we next assessed WT or Nkg7−/− mice injected subcutaneously with MC38-OVAbright colon adenocarcinoma (as in Fig. 1B). Tumors were collected on days 8 and 12. Tumor weight shown in Fig. 3A demonstrated the greater tumor size in Nkg7−/− mice compared with WT mice. These tumors were also assessed for immune cell content using the gating strategy outlined in Supplementary Fig. S4A, with a focus on the properties of tumor-infiltrating CD8+ T cells. The NK-cell and T-cell percentages in tumor-infiltrating CD45.2+ cells were significantly lower in Nkg7−/− mice than in WT mice (Fig. 3B and C), with a corresponding increase in myeloid cell frequencies (Supplementary Fig. S4B). CD45.2+ cells per mg of tumor were unchanged (Supplementary Fig. S4C). Because no notable difference in the frequency of CD4+ T cells was found (Fig. 3D), the major difference at the level of T cells was a result of the lower CD8+ T-cell frequency in Nkg7−/− mice at days 8 and 12 (Fig. 3E). Consistent with tumor weight data (Fig. 3A), Nkg7−/− mice also displayed reduced frequencies of tumor-specific OVA-tetramer+ cells among CD8+ T cells (Fig. 3F). The priming of OVA-tetramer+ cells early after tumor inoculation appeared equivalent in WT and Nkg7−/− mice, as indicated by frequencies of tumor-specific OVA-tetramer+ CD8+ T cells in peripheral blood (Fig. 3G). The mean fluorescence intensity (MFI) and expression frequency levels of CD107a were lower in Nkg7−/− mice than in WT mice, consistent with the previously observed reduction in granule exocytosis reported in NK cells in metastasis burdened lungs (Supplementary Fig. S5A and S5B; ref. 12). However, other markers of activation such as granzyme B, IFNγ, CD69 and appeared unaltered in intratumor CD8+ T cells in Nkg7−/− mice compared with WT mice (Supplementary Fig. S5C–S5H).
Consistent with bulk CD8+ T cells (Supplementary Fig. S5), the CD107a MFI and frequency was lower in OVA-specific CD8+ T cells from Nkg7-deficient mice compared with WT mice (Supplementary Fig. S6A). The CD69 MFI and frequency was unchanged in OVA-specific CD8+ T cells from Nkg7-deficient mice compared with WT mice (Supplementary Fig. S6B). Furthermore, in MC38-OVAbright tumors, we observed a lower CD107a MFI and frequency in Nkg7-deficient CD4+ T cells (Supplementary Fig. S6C), but not Nkg7-deficient NK cells (Supplementary Fig. S6E), suggesting that Nkg7 might be important for degranulation of T cells in the tumor. We did not see differences in CD69 (MFI and frequency) between WT and Nkg7-deficient CD4+ T cells and NK cells in the tumor (Supplementary Fig. S6D and S6F).
No increase in CD8+ T-cell frequency in tumor-infiltrating lymphocytes of Nkg7−/− mice responding to ICB
We next assessed tumor-infiltrating lymphocytes (TIL) in MC38 tumors after two doses of combination immunotherapy (Supplementary Fig. S7A). Two doses of combination immunotherapy inhibited MC38 tumor growth in WT mice, but not in Nkg7−/− mice (Supplementary Fig. S7B). Accordingly, we also saw a significant increase in the frequency of tumor-infiltrating CD8+ T cells in WT mice following combination immunotherapy, but not in Nkg7−/− mice (Supplementary Fig. S7C). Interestingly, and consistent with previous reports of anti-PD1 therapy (28), the combination immunotherapy reduced the frequency of PD1+ CD8+ TILs and the expression of PD1 as defined by MFI in WT mice compared with Nkg7−/− mice (Supplementary Fig. S7D). There was a trend toward an increase in CD4+ FoxP3− TILs and decrease in CD4+ FoxP3+ TILs, in combination immunotherapy treated WT mice but these changes were not statistically significant (Supplementary Fig. S7E and S7F).
Tumor antigen-driven expression of NKG7 in CD8+ T cells
Next, we wanted to compare NKG7 expression patterns of human cancer data in Supplementary Fig. S1 with expression of Nkg7 in tumor-bearing mice. There are no antibodies currently available for the detection of human or mouse NKG7. We have previously described the generation of a Nkg7-cre strain (12), that when crossed to the B6.mT/mG strain generates a transcriptional reporter of Nkg7 (Nkg7-cre x mT/mG), via the detection of Nkg7 by GFP acquisition. The Nkg7-reporter (Nkg7-cre x mT/mG) mice were injected subcutaneously with MC38-OVAbright colon adenocarcinoma. Nkg7 expression was then analysed in peripheral blood, spleen, and tumor-infiltrating immune cells over time (Fig. 4, representative plots in Supplementary Fig. S8). The tumor grew and regressed in these mice as shown in WT mice (Supplementary Fig. S8A; Fig. 1B). About 20% of CD8+ T cells expressed Nkg7 in peripheral blood and spleen from days 4–10 after tumor inoculation, but there was a marked increase in Nkg7 expression in up to 85% of intratumor CD8+ T cells at days 8 and 10 after inoculation (Fig. 4A). Compared with CD8+ T cells, only a small fraction of tumor-infiltrating CD4+ T cells showed induction of Nkg7 expression (peripheral blood only ∼1%–2%; and tumor ∼5%–15%; Fig. 4B). A much higher frequency of NK cells (∼80%–90%) expressed Nkg7 and this was not significantly regulated in the tumor (Fig. 4C). The percentages of Nkg7-expressing OVA-tetramer+ cells among CD8+ T mirrored the increase in all CD8+ T cells (Fig. 4D), although notably, Nkg7 was mostly increased in OVA-tetramer+ cells in the spleen (Fig. 4E), but in all CD8+ T cells in the tumor (Fig. 4F). These data imply that Nkg7 is regulated in T cells largely by tumor antigen recognition and the expression pattern mirrors what has been observed in human datasets.
We have utilized scRNA-seq datasets, NKG7-deficient mice, NKG7-reporter mice, and mouse tumor models to demonstrate an important role of NKG7 in CD8+ T cell–mediated tumor rejection and immunotherapy. NKG7 expression is highly associated with cytotoxicity and most highly expressed by CD8+ T cells and NK cells. NKG7 was upregulated on intratumor antigen-specific CD8+ T cells and NK cells, and was required for the accumulation of intratumor T cells. Future design of therapeutics that agonize or upregulate NKG7 on effector lymphocytes in tumors may provide a new approach for cancer treatment.
S.S. Ng reports a patent for PCT/AU2019/050049, modulating immune responses, pending. M. Braun reports grants from Dr. Mildred Scheel Stiftung für Krebsforschung from the Deutsche Krebshilfe (German Cancer Aid) during the conduct of the study. M.J. Smyth reports grants from Bristol Myers Squibb and personal fees from Tizona Therapeutics outside the submitted work. C.R. Engwerda reports a patent for PCT/AU2019/050049 pending. No disclosures were reported by the other authors.
X.-Y. Li: Formal analysis, investigation, writing–original draft, writing–review and editing. D. Corvino: Data curation, formal analysis, investigation, methodology, writing–review and editing. B. Nowlan: Investigation, visualization, methodology, writing–review and editing. A.R. Aguilera: Investigation. S.S. Ng: Investigation, writing–review and editing. M. Braun: Data curation, formal analysis. A.R. Cillo: Resources, data curation, formal analysis. T. Bald: Supervision, writing–review and editing. M.J. Smyth: Conceptualization, formal analysis, supervision, funding acquisition, validation, writing–original draft, project administration, writing–review and editing. C.R. Engwerda: Conceptualization, resources, supervision, funding acquisition, project administration, writing–review and editing.
We thank the staff of QIMR Berghofer for animal husbandry. We thank Michael Hoelzel for supplying code used in correlation analysis. We thank Dario Vignali and colleagues for data sharing. This research was funded by National Health and Medical Research Council (NH&MRC) to M.J. Smyth (1030247 and 1105312). X.-Y. Li is funded by the National Natural Science Foundation of China (81902936). T. Bald is funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation) under Germany's Excellence Strategy – EXC2151 (390873048). M.J. Smyth was funded by an NH&MRC Program Grant (1132519) and an Investigator Grant (1173958). C.R. Engwerda was funded by an NH&MRC Program Grant (1132975) and a Senior Research Fellowship (1154265).