An IFNγ/STAT1/JMJD3 Axis Induces ZEB1 Expression and Promotes Aggressiveness in Lung Adenocarcinoma

The inhibition of PD1/PD-L1 has led to a paradigm shift in the treatment of lung adenocarcinoma. Important consequences of PD1/PD-L1 blockade are increased T-cell function and IFNγ production (1). IFNγ is one of the essential cytokines in antitumor immunity and immunotherapies. IFNγ has direct tumor cell-specific antitumor effects, such as cell-cycle arrest and the subsequent inhibition of lung cancer cell proliferation (2). Garris and colleagues have demonstrated that effective anti-PD-1 cancer immunotherapy requires T-cell–dendritic cell crosstalk and involves the cytokines IFNγ and IL12 (3). Genomic defects in the IFNγ pathway in tumor cells, including mutations in both IFNγ receptors, JAK2, and the IFNγ signaling downstream protein IRF1, contribute to resistance to immunotherapy (4–6). IFNγ promotes CXCL9, CXCL10, and CXCL11 expression, thereby increasing the recruitment of CXCR3⁺ T cells into the tumor microenvironment, which plays a crucial role in determining the effectiveness of immunotherapy (7, 8).

Despite the pivotal role of IFNγ in antitumor host immunity, under certain circumstances, IFNγ induces tumor progression (9). IFNγ, like most cytokines, induces inhibitory feedback mechanisms to restrain the magnitude of the immune response (1). For instance, the high concentration of IFNγ produced by functional cytolytic T cells induces PD-L1 expression, which enables tumor cells to acquire the capability to counterattack immune cells (10, 11). Sustained IFN signaling in tumor cells triggers STAT1-dependent epigenetic and transcriptional changes, which consequently lead to the expression of multiple ligands for T-cell inhibitory receptors besides PD-1/PD-L1, which in turn confers tumor resistance to PD-1/PD-L1-based immunotherapy (12). Moreover, very recently, IFNγ has been reported to induce epithelial-to-mesenchymal transition (EMT) in prostate cancer and renal cancer and stimulate metastasis. In these cases, IFNγ regulates the turnover of specific tumor-suppressive microRNAs, such as miR-363 in particular, through the upregulation of the IFN-stimulated gene IFN-induced tetratricopeptide repeat 5 (IFIT5), consequently leads to EMT in cancer cells (13).

EMT has long been associated with the acquisition of malignant cell traits, such as motility and invasiveness (14). EMT is executed by EMT activating transcription factors (EMT-TF), mainly of the SNAIL, TWIST, and ZEB families (15). These transcription factors are also involved in cancer initiation, cancer cell plasticity, and cancer progression (16, 17). It remains unclear whether IFNγ induces EMT-TF expression and promotes EMT in lung adenocarcinoma cells. In this study, we showed that IFNγ upregulated ZEB1 expression and promoted EMT in lung cancer cells. We found that IFNγ stimulation resulted in induction of JMJD3, decreased H3K27 trimethylation in the promoter region of the ZEB1 gene, and consequently increased ZEB1 expression. Knockdown of ZEB1 in lung adenocarcinoma cells eliminated IFNγ-mediated protumor effects while retaining its antitumor functions.

Human lung adenocarcinoma A549 (ATCC Catalog No. CRL-7909, RRID: CVCL_0023), HCC827 (KCLB Catalog No. 70827, RRID: CVCL_2063), H1975 (ATCC Catalog No. CRL-5908, RRID: CVCL_1511), H2228 (ATCC Catalog No. CRL-5935, RRID: CVCL_1543), H1573 (ATCC Catalog No. CRL-5877, RRID: CVCL_1478), H2444 (ATCC Catalog No. CRL-5945, RRID: CVCL_1552), and UMC-11(ATCC Catalog No. CRL-5975, RRID: CVCL_1784) cell lines were obtained from Cobioer Biosciences. Short tandem repeat (STR) analysis was performed for A549, HCC827, and H1975 cell lines in 2017 and other cell lines in 2019 (Cobioer Biosciences). All of the cell lines were confirmed to be mycoplasma negative (Biothrive Sci. & Tech. Ltd.). Lung adenocarcinoma cells were maintained as a monolayer culture in RPMI1640 (GIBCO) supplemented with 10% FBS (GIBCO) and 1% penicillin/streptomycin (Hyclone).

Lung adenocarcinoma specimens were obtained from 42 patients, who underwent pulmonary resection prior to radiation or chemotherapy in the Department of Thoracic Surgery, Tong Ji Hospital. Histologic diagnosis of tumors was based on the WHO criteria. The TNM stage was determined according to the 7th Edition AJCC staging guidelines. This research was performed in accordance with the Helsinki Declaration. The use of human tissue samples was approved by the Institutional Ethics Committee of the Huazhong University of Science and Technology. Each patient signed written informed consent on the day of admission.

All of the antibodies and reagents are listed in Supplementary Table S1.

The TRizol method was used to isolate total RNA. TRizol was obtained from TAKARA. RNA was reverse transcribed into cDNA using the RT Reagent Kit according to the manufacturer's protocol (Vazyme Biotech Co.). qRT-PCR was carried out using Fast SYBR Green Master Mix (Life Technologies). The primers were obtained from TsingKe Biological Technology. The primer sequences are presented in Supplementary Table S2. Negative controls without template were included, and all of the reactions were conducted in triplicate. β-Actin was used as internal control. Relative expression of target genes was determined by the 2^−ΔΔCt method.

siRNA sequences specifically targeting JAK1, JAK2, STAT1, ZEB1, and JMJD3 were synthesized by RiboBio. siRNA (50 nmol/L) and Lipofectamine 3000 (Life Technologies) were gently premixed in medium without FBS as per the guidelines. Knockdown efficacy was evaluated using RT-PCR and immunoblotting.

The shRNA sequence targeting ZEB1 (shRNA-ZEB1) was 5′-GAACCAGTTGTAAATGTAA-3′. shRNA-ZEB1 was inserted in the GV493 vector (hU6-MCS-CBh-gcGFP-IRES-puromycin; GeneChem). Empty GV493 vector was used as a negative control. Knockdown of ZEB1 was confirmed by RT-PCR and immunoblotting.

Total RNA was isolated from cells using the RNeasy Mini Kit (Qiagen). Paired-end libraries were synthesized using the VAHTS stranded mRNA-seq Library Prep Kit for Illumina (Vazyme) following the manufacturer's guidelines. Briefly, the poly-A containing mRNA molecules were purified using poly-T oligo-attached magnetic beads. Purified libraries were quantified with a Qubit 2.0 Fluorometer (Life Technologies) and validated with an Agilent 2100 bioanalyzer (Agilent Technologies) to confirm the insert size and calculate the mole concentration. Clusters were generated by cBot with the library diluted to 10 pmol/L and sequenced on Illumina HiSeq X-ten (Illumina). Library construction and sequencing were performed at Shanghai Biotechnology Corporation. The RNA-seq data have been deposited in the Gene Expression Omnibus database [Gene Expression Omnibus (GEO), RRID: SCR_005012] under accession code GSE150255.

Cells were lysed and proteins were separated by SDS-PAGE and transferred to Immobilon-P membranes (Millipore). The blots were developed using the ECL detection system (Advansta). To ensure that equal amounts of sample protein were applied per lane, β-actin was used as loading control.

Cells were harvested and washed twice with ice-cold PBS. Subsequently, cells were resuspended in Triton Extraction Buffer (TEB: PBS containing 0.5% Triton X-100 and 2 mmol/L PMSF) at a cell density of 10⁷ cells/mL. Then the cells were lysed on ice for 10 minutes with gentle stirring, and centrifuged at 400 × g for 10 minutes at 4°C. The cell pellet was resuspended in 0.2N HCl at a cell density of 4 × 10⁷ cells/mL at 4°C overnight. The samples were centrifuged at 400 × g for 10 minutes at 4°C, and the supernatant was used for immunoblot analysis.

Cells cultured on cover slides were pretreated with indicated reagents for 72 hours. The cells were fixed with 4% paraformaldehyde for 20 minutes, permeabilized with 0.1% Triton X-100 for 10 minutes, blocked with 5% BSA for 0.5 hours, and labeled with primary antibody at 4°C overnight. The cells were staining with secondary antibody for 0.5 hours at room temperature, and cells were counterstained with DAPI for 10 minutes at room temperature. Cells were visualized with a fluorescence microscope (Olympus).

Cell proliferation was assessed using the CCK-8 Kit (Dojindo Molecular Laboratories). Cells were seeded (3,000–5,000 in 100 μL/well) and cultured overnight before exposure to the indicated stimuli. Absorbance was measured at 450 nm using a microplate spectrophotometer (TECAN).

Cells were seeded in 6-well plates at a density of 800 cells/well and maintained for 14 days with or without IFNγ (100 IU/mL). The cells were fixed with 4% (w/v) paraformaldehyde for 20 minutes, stained with crystal violet for 15 minutes, and washed with PBS three times.

The cell migration assay was carried out using 8 μm pore size Transwell chambers (Corning). In brief, cells were suspended in serum-free medium and plated into the upper chambers (7 × 10⁴ cells in 100 μL/well). In the lower chambers, medium supplemented with 10% FBS was used as a chemo-attractant. IFNγ and other indicated reagents were added to both chambers at equal concentrations. After 24 hours of incubation, the cells that migrated through the membrane to the bottom surface were fixed with 4% (w/v) paraformaldehyde, and stained with 0.1% (w/v) crystal violet. The migratory cells were examined under an optical microscope at 200× magnification. The average numbers of migratory cells were obtained from three randomly chosen fields.

ELISA was performed using a CXCL-10 ELISA kit (Ruixin Biotech) according to the manufacturer's instructions.

The ChIP assay was performed using ChIP Kit, following the manufacturer's instructions (Cell Signaling Technology). Immunoprecipitation was performed overnight at 4°C with anti-H3K27me3 (Active Motif Catalog No. 39155, RRID: AB_2561020) and anti-H3K4me3 (Active Motif Catalog No. 39915, RRID: AB_2687512) antibodies, and a normal rabbit IgG (Cell Signaling Technology; Catalog No. 2729, RRID: AB_1031062) control. The fragments of the human ZEB1 promoter in immunoprecipitates were identified by qPCR. Detailed information on primers is provided in Supplementary Table S2.

All of the animal experiments were approved by the Animal Care Committee of Tongji Hospital (approval number: TJH-201902001). NCG mice were purchased from the Experimental Animal Center (Hubei, China) and maintained in an environment with a standardized barrier system (System Barrier Environment No. 00021082). A549 cells, A549-shRNA-control cells, and A549-shRNA-ZEB1 cells pretreated with IFNγ (400 IU/mL) for 4 days or without IFNγ treatment were resuspended in 100 μL PBS and then injected into the tail vein of NCG mice (2 × 10⁶ cells/mouse), followed by intraperitoneal injection of IFNγ (2,000 IU in 100 μL per mouse) every other day for total three times. Histologically detectable lung metastatic foci were observed microscopically 7 days postinjection (18). The lungs were excised, fixed in 10% formalin, paraffin-embedded, and stained with hematoxylin and eosin (H&E) for pathologic identification of tumor nodules in the lung parenchyma. The photomicrographs of the lungs were taken using a light microscope (Axio Observer 3; Zeiss). The metastasis area and lung area were quantified using ImageJ (ImageJ, RRID: SCR_003070) software.

Fresh lung cancer tissues were obtained from patients undergoing pulmonary resection prior to radiation or chemotherapy in the Department of Thoracic Surgery, Tongji Hospital. The ex vivo culture was performed as described previously (19). Briefly, fresh human lung cancer tissue was dissected into 1 mm³ cubes, placed on a Gelatin sponge (HuSHiDa), and bathed in RPMI1640 medium supplemented with 10% heat-inactivated FBS and 100 IU/mL penicillin–streptomycin. In addition, indicated amounts of IFNγ were added to the media. Tissues were cultured at 37°C for 24 to 36 hours and collected for RNA extraction.

Data in bar graphs are displayed as mean ± SD. Data between two groups were compared with the two-tailed Student t test (*P < 0.05, **P < 0.01, ***P < 0.001), and one-way ANOVA was used to compare data between three or more groups. The association between ZEB1 and IFNG mRNA levels was assessed by Pearson correlation test. Statistical analysis was performed with GraphPad Prism software v. 8.0 (GraphPad Prism, RRID: SCR_002798). For RNA-seq data, the P value significance threshold in multiple tests was set by the FDR. Fold-changes were also estimated according to the FPKM value in each sample. The differentially expressed genes were selected using the following criteria: FDR ≤0.05 and log₂ (fold-change) ≥0.5.

Previously, we performed a global transcriptome study (microarray analysis) and compared tumor tissues with high versus low IFNG expression levels. ZEB1 mRNA levels were significantly higher in tumors with high IFNG expression (GSE99995). We examined the correlation between IFNG and ZEB1 in a uniform cohort of a total of 42 patients with locally advanced lung adenocarcinoma (stage IIIA) from our patient archive (Supplementary Table S3). IFNG expression in tumors was significantly correlated with ZEB1 expression (Fig. 1A; n = 42, r = 0.3653; P = 0.0174). Among these patients, 18 paraffin-embedded tumors were available for ZEB1 IHC analysis. The median IFNG expression was used to split patients into two groups (IFNG^hi, n = 8 vs. IFNG^low, n = 10). ZEB1 immunoreactivity was observed in both tumor stroma and tumor nests. Positive ZEB1 immunoreactivity in tumor nests was found in four samples. Three of them were from the IFNG ^hi group (three of total eight tumors, 37.5%) and only one was from the IFNG^low group (1 of 10 tumors, 10%; Supplementary Fig. S1A). Next, to determine whether IFNγ could directly induce ZEB1 expression in lung cancer cells, A549 cells were treated with IFNγ. As shown in Supplementary Fig. S1B, ZEB1 protein expression was increased in A549 cells in response to IFNγ stimulation. IFNγ also upregulated ZEB1 gene transcription in lung adenocarcinoma cells (Fig. 1B). IFNγ did not induce ZEB1 expression in UMC-11 cells, a lung carcinoid cell line. Immunoblotting analysis revealed that ZEB1 protein levels increased within 12 hours upon IFNγ stimulation and sustained for at least 72 hours after a single treatment (Fig. 1C). Strikingly, prolonged exposure of A549 and H1975 to IFNγ led to sustained ZEB1 expression even after removal of IFNγ (Fig. 1D).

Finally, we cultured human-derived lung adenocarcinoma ex vivo to confirm the effect of IFNγ on ZEB1 expression. IFNγ induced the transcription of the ZEB1 gene in tumors but not in distant nontumor lung tissues (Fig. 1E). Our data demonstrate that IFNγ upregulates ZEB1 expression at both mRNA and protein levels in lung adenocarcinoma cells.

E-cadherin and Vimentin are the most commonly used EMT markers, as their expression patterns undergo dramatic changes during EMT. IFNγ stimulation downregulated E-cadherin expression and upregulated Vimentin expression, as determined by immunoblot analysis (Fig. 2A). The altered expression patterns of E-cadherin and Vimentin in lung cancer cells upon IFNγ treatment were further validated by immunofluorescence analysis (Fig. 2B). RT-PCR analysis revealed that CDH1 transcription was decreased at 24 hours and maintained at a low level in A549 and H2228 cells, whereas VIM transcription was significantly increased to various degrees in the three cell lines in response to IFNγ stimulation (Fig. 2C).

Treatment with low amounts of IFNγ (10 IU/ml) for 3 days did not significantly affect E-cadherin levels in A549 and HCC827 (Supplementary Fig. S1C). Although treatment with IFNγ at 25 IU/ml significantly downregulated E-cadherin levels in A549 and HCC827 cells (Supplementary Fig. S1D). Prolonged exposure to IFNγ induced morphologic changes in A549 and HCC827 cells, which acquired a fibroblast-like appearance (Fig. 2D), indicating that IFNγ-treated cells enter a stable mesenchymal-associated state. Substantial evidence has shown that EMT is associated with increased cell migration in vitro. As shown in Fig. 2E, the migratory capability of A549 and HCC827 cells was indeed significantly increased after IFNγ treatment. Collectively, these data demonstrate that IFNγ induces EMT in lung adenocarcinoma cells and promotes cell migration in vitro.

EMT involves a robust reprogramming of gene expression. We analyzed the transcriptome alterations by RNA-seq analysis during EMT following IFNγ treatment. It has been reported that A549 cells have mesenchymal characteristics, whereas HCC827 cells have epithelial features (20). For these reasons, we selected A549 and HCC827 cells to investigate the reprogramming of gene transcription by IFNγ. An EMT signature consisting of 130 genes was analyzed, including 67 upregulated mesenchymal-associated genes and 63 downregulated epithelial-associated genes (Supplementary Table S4; ref. 21). Of the 63 epithelial-associated genes, 35 genes including CDH1, were highly expressed in HCC827 cells compared with A549 cells; of the 67 mesenchymal-associated genes, 35 genes, including VIM, were expressed at lower levels in HCC827 cells than in A549 cells (Fig. 3A). These results indicate that relative to A549 cells, HCC827 cells have more epithelial-associated features, which was consistent with the reports by others (20). EMT is a dynamic process with intermediary states that are not easily identified in cultured cells. We performed transcriptome analysis after the cells were treated with IFNγ for 8 or 24 hours. The number of differentially expressed genes was dramatically increased after 24 hours of stimulation with IFNγ compared with 8 hours of stimulation (Supplementary Fig. S2).

In A549 cells, 58 genes were differentially expressed after 24 hours of IFNγ treatment, including 20 upregulated and 38 downregulated genes [Log₂(FC) ≥ 0.5, P < 0.05; Fig. 3B; Supplementary Table S5]. Among these differentially expressed genes, of 67 genes that are upregulated in EMT, 13 genes were upregulated after IFNγ treatment, and of 63 genes that are downregulated in EMT, 23 genes were downregulated after IFNγ treatment. In HCC827 cells, 58 genes were differentially expressed after 24 hours of IFNγ treatment, including 32 upregulated and 26 downregulated genes [Log₂(FC) ≥ 0.5, P < 0.05; Fig. 3C; Supplementary Table S6]; among these differentially expressed genes, of 67 genes that upregulated in EMT, 21 genes were upregulated after IFNγ treatment, and of 63 genes that are downregulated in EMT, 12 genes were downregulated after IFNγ treatment. Detailed analysis revealed that IFNγ stimulation of the mesenchymal-like A549 cells led to downregulation of more epithelial-associated genes (genes downregulated during EMT), whereas IFNγ stimulation of the epithelial-like HCC827 cells led to upregulation of more mesenchymal-associated genes (genes upregulated during EMT). Although IFNγ altered the expression patterns of E-cadherin and Vimentin in both A549 and HCC827 cells, transcriptome analysis of EMT-associated genes in IFNγ-treated cells revealed that IFNγ induced EMT in lung cancer cells is not a unified state. The characteristics of IFNγ-induced EMT could be associated with the intrinsic state of untreated lung cancer cells.

Although IFNγ differentially alters the expression of EMT-associated genes in A549 and HCC827 cells, RNA-seq analysis showed that the expression of 15 genes was equally affected in both cell lines upon IFNγ treatment, including 7 upregulated and 8 downregulated genes. Among the upregulated genes, CTGF, which encodes connective tissue growth factor (CTGF), can induce EMT and its expression levels are highly correlated with EMT markers (22). FGF2, which encodes basic fibroblast growth factor, and MAP1B, which encodes a protein belonging to the microtubule-associated protein family, are both upregulated during EMT (21). FGF2 promotes EMT and metastasis through the FGFR1–ERK1/2–SOX2 axis in FGFR1-amplified lung cancer (23). Actin binding LIM protein 1, encoded by the ABL1M1 gene, plays multiple roles in establishing and maintaining cellular structure through mediating interactions between actin filaments and cytoplasmic LIM binding partners (24). ABLIM1 is downregulated during EMT (21). These differentially expressed genes in response to IFNγ stimulation in both A549 and HCC827 cells were confirmed by qRT-PCR (Fig. 3D).

To determine whether ZEB1 is involved in IFNγ induced EMT, we knocked down ZEB1 using siRNA and we found that knockdown of ZEB1 abrogated the IFNγ-induced upregulation of VIM transcription (Supplementary Figs. S3A and S3E). IFNγ-mediated alterations in the expression pattern of E-cadherin and Vimentin in A549 and HCC827 cells were reversed upon ZEB1 knockdown (Fig. 3F).

The migratory capability of A549 cells promoted by IFNγ was significantly compromised by the downregulation of ZEB1 expression (Fig. 4A). To examine the in vivo effects of IFNγ on lung cancer cell metastasis, we established an in vivo metastasis model by intravenous injection of A549 cells that had been treated with IFNγ in vitro for 4 days into NCG mice (2 × 10⁶ cells/mouse) (Fig. 4B). The mice were given recombinant human IFNγ (2,000 IU/mouse) intraperitoneally every other day for a total of three times. Seven days after injection of A549 cells, lung tissues were collected and the presence of metastatic foci and the size of metastases were analyzed microscopically. Control mice were given untreated A549 cells and the mice were not given IFNγ. As shown in Fig. 4C, IFNγ treatment significantly increased the number and the size of metastatic nodules in lung tissues.

To determine the role of ZEB1 in this event, we transfected A549 cells with shRNA against ZEB1 (shRNA-ZEB1) and obtained a stable ZEB1-depleted cell line (Supplementary Fig. S3B). The IFNγ-promoted increase of A549 cell migration in vitro was diminished in shRNA-ZEB1 A549 cells (Fig. 4D). Our in vivo metastasis model showed that the number and the size of metastatic nodules were reduced in mice injected with IFNγ-treated shRNA-ZEB1 A549 cells compared with mice injected with IFNγ-treated control A549 cells, indicating that loss of ZEB1 dramatically reduces IFNγ-promoted metastasis of A549 cells (Fig. 4E). Our data demonstrate that ZEB1 is responsible for IFNγ-induced cell migration in vitro and metastasis in vivo.

We next evaluated whether IFNγ-induced activation of the JAK1/2–STAT1 pathway is involved in the regulation of ZEB1 expression. We knocked down JAK1, JAK2, and STAT1 using siRNA in A549 and HCC827 cells, and these cells were subsequently stimulated with IFNγ. Upregulation of ZEB1 by IFNγ was no longer observed in the knockdown of JAK1, JAK2, and STAT1 cells (Fig. 5A–C).

ZEB1 transcription is regulated by the modulation of the chromatin environment at gene regulatory elements (25, 26). H3K27me3 is often associated with transcriptional repression. The relative absence of H3K27me3 in the chromatin at the ZEB1 promoter signals active transcription (25). Interestingly, the expression of H3K27 trimethylation and the ratio of H3K27me3 to H3 was rapidly reduced in A549 cells after exposure to IFNγ (Fig. 5D). JMJD3, a direct transcriptional target of STAT1, catalyzes the demethylation of H3K27me3 (27). For these reasons, we examined whether IFNγ induces JMJD3 expression. JMJD3 transcription was rapidly upregulated in A549 and HCC827 cells upon exposure to IFNγ (Fig. 5E). Immunoblot analysis revealed increased JMJD3 expression after 3 hours of IFNγ treatment (Fig. 5F). To determine whether JMJD3 is associated with IFNγ-induced ZEB1 expression, the JMJD3-specific inhibitor GSK-J4 was used (28). To determine the proper amount of GSK-J4 to be used in our experimental setting, we evaluated the effect of GSK-J4 alone on H3K27me3 levels and ZEB1 expression. As shown in Fig. 5G, GSK-J4 at concentrations of 1 and 5 μmol/L significantly enhanced H3K27me3 levels but did not alter ZEB1 expression. However, GSK-J4 at 10 μmol/L did not increase H3K27me3 levels while enhancing ZEB1 expression significantly, suggesting that GSK-J4 at lower concentration serves as JMJD3 inhibitor and has no direct effect on ZEB1 expression. For these reasons, we used GSK-J4 at a concentration of 1 to 5 μmol/L to determine whether inhibition of JMJD3 activity prevents IFNγ-induced upregulation of ZEB1. As shown in Fig. 5H, additional GSK-J4 prevented IFNγ-induced upregulation of ZEB1 expression. Knockdown experiments with siRNA-JMJD3 further confirmed that IFNγ-induced ZEB1 expression requires JMJD3 (Fig. 5I). Downregulation of STAT1 expression led to abrogation of IFNγ-induced JMJD3 expression (Fig. 5J), confirming that IFNγ-induced JMJD3 expression is STAT1 dependent.

The ZEB1 promoter exhibits a bivalent chromatin configuration (28). H3K4me3 is associated with transcriptional initiation (29), whereas H3K27me3 is associated with transcriptional repression. We performed a ChIP assay at the ZEB1 promoter to compare the levels of histone modifications in control versus IFNγ-treated cells. IFNγ treatment led to a significant reduction in H3K27me3 levels at the ZEB1 promoter in A549 cells, whereas IFNγ did not significantly affect H3K4me3 levels at the ZEB1 promoter (Fig. 5K). These data demonstrate that IFNγ enables the ZEB1 promoter to transition from the bivalent to the active chromatin state, at least in part through the demethylation of H3K27me3.

ZEB1 transcription is tightly regulated by miRNA. Recent studies have revealed that IFNγ promotes ZEB1 expression through IFIT5-mediated suppression of miR-363 in prostate cancer and renal cancer (13). We did not observe the downregulation of miR-363 expression by IFNγ in lung cancer cells (Supplementary Fig. S4). The miR-200 family inhibits ZEB1 expression and in turn, ZEB1 directly represses the transcription of miR-200 loci (30). As shown in Fig. 6A, miR-200c expression was significantly reduced in A549 and HCC827 cells after 12 hours of IFNγ treatment, and the reduction of miR-200c expression was even more dramatic after 24 and 48 hours of IFNγ treatment. We wondered whether IFNγ-promoted ZEB1 expression in lung cancer cells is related to the downregulation of miR-200 expression. IFNγ-induced upregulation of ZEB1 transcription was observed after 4 hours in both A549 and HCC827 cells, whereas miR-200c expression was not affected even after 6 hours of IFNγ stimulation (Fig. 6B and C). Moreover, increased ZEB1 protein expression was observed at 12 hours of IFNγ stimulation (Fig. 1C). Thus, our data suggest that IFNγ first promotes ZEB1 transcription, and subsequently suppresses miR-200c expression.

Further analysis revealed that downregulation of ZEB1 enhanced miR-200 expression in IFNγ-treated cells compared with untreated cells (Fig. 6E). Knockdown of ZEB1 also led to a significant reduction of IFNγ-induced PD-L1 expression in A549 and HCC827 cells (Fig. 6D). PD-L1 expression has been reported to be directly regulated by miR-200 family members (31). Collectively, IFNγ stimulation rapidly induces ZEB1 expression and consequently downregulates miR-200c, which at least partially contributes to the upregulation of PD-L1 expression.

Previous studies by us and others have shown that IFNγ suppresses the proliferation of lung cancer cells (2, 32). We wondered whether ZEB1 is involved in the IFNγ-mediated suppression of cell proliferation. Knockdown of ZEB1 by siRNA did not alter the antiproliferative effects of IFNγ in both A549 and HCC827 cells (Fig. 7A). ZEB1 knockdown did not affect IFNγ-mediated suppression of colony formation (Fig. 7B). Cyclin E1, which is encoded by the CCNE1 gene, plays a critical role in the control of cell cycle progression by allowing G₁- to S-phase transition (33). IFNγ-treated A549 cells exhibited significantly lower CCNE1 mRNA levels than untreated A549 cells. Knockdown of ZEB1 did not affect IFNγ-mediated reduction of CCNE1 expression (Fig. 7C). IFNγ-mediated suppression of cell proliferation requires STAT1 and IRF1 (2). Downregulation of ZEB1 had no effect on IFNγ-induced STAT1 and IRF1 expression at mRNA and protein levels (Fig. 7D and E). ZEB1 knockdown did not affect IFNγ-induced phosphorylation of STAT1 (Fig. 7F). We also examined whether knockdown of ZEB1 affects STAT1-IRF1 target genes CXCL9 and CXCL10 expression. As shown in Fig. 7G, downregulation of ZEB1 expression did not alter the IFNγ-induced expression pattern of CXCL9 and CXCL10. The results were confirmed by ELISA analysis of CXCL10 expression at the protein level (Fig. 7H).

The main findings of this study are summarized as follows: (i) IFNγ induces EMT in lung adenocarcinoma cells. RNA-seq analysis revealed that IFNγ stimulation altered the expression pattern of EMT-associated genes. Morphologic changes in lung adenocarcinoma cells were observed after prolonged exposure to IFNγ. Functionally, IFNγ promoted cell migration and metastasis in vivo. (ii) IFNγ stimulation resulted in upregulation of JMJD3 and hence decreased H3K27 trimethylation in the promoter region of ZEB1, increasing ZEB1 expression. (iii) Increased ZEB1 expression mediated IFNγ-induced EMT. (iv) Knockdown of ZEB1 abrogated IFNγ-induced EMT and PD-L1 expression. (v) Inhibition or downregulation of ZEB1 did not affect IFNγ-mediated antitumor effects, including its suppression of cell proliferation and the increase in CXCL9 and CXCL10 expression, which promotes the recruitment of T cells to the tumor microenvironment. On the based on our findings, we propose that the IFNγ-induced upregulation of ZEB1 might increase the aggressiveness of lung cancer cells. Targeting ZEB1 eliminates the protumor effects of IFNγ while retaining its antitumor functions.

Our results showed that IFNγ stimulation induced a dramatic change in the expression pattern of E-cadherin and Vimentin in lung cancer cells. It is widely recognized that experimental models using only a small selection of epithelial and mesenchymal biomarkers, including E-cadherin, N-cadherin, and Vimentin, to define or confirm EMT sketch an oversimplified view of this complex process. EMT is not one clearly defined tumor state but a set of multiple dynamic transitional states between epithelial and mesenchymal phenotypes (16, 34). Because of the complexity of the EMT process, reliable biomarkers are still lacking and a comprehensive method to identify and/or measure EMT, particularly in vivo, does not exist. Nevertheless, numerous gene expression studies have been conducted to obtain transcriptome signatures and marker genes associated with EMT (20, 35). In our study, we not only analyzed CDH1 and VIM expression levels, but we also performed a transcriptome analysis to determine whether IFNγ alters the expression of other EMT-associated genes. We obtained the EMT core gene signatures, which consists of 130 genes, through a meta-analysis of 18 independent and published gene expression studies of EMT (21). Comparing the expression levels of these 130 genes, we found that IFNγ stimulation altered the transcription of almost 50% of EMT-associated genes in both A549 and HCC827 cells. Among these differentially expressed genes, the EMT-associated transcription factor ZEB1 was rapidly upregulated in response to IFNγ stimulation. In addition to these genetic biomarkers, several in vitro criteria have been used to determine EMT, including a spindle-shape morphology and increased migratory capability (36, 37). We found that exposure of lung cancer cells to IFNγ induced morphologic changes, and also promoted cell migration in vitro and metastasis in vivo. Our findings demonstrate that IFNγ is capable of inducing EMT in lung adenocarcinoma cells.

In prostate cancer and renal cancer, IFNγ induces EMT through the IFIT5–XRN1 complex, which regulates the turnover of specific tumor-suppressive miRNAs, such as miR-101, miR-128, and miR-363 (13). In our study, IFNγ treatment even upregulated miR-363 levels in lung cancer cells. Our findings suggest that the mechanism by which IFNγ induced EMT is cancer type-dependent and context-specific. In lung cancer cells, IFNγ stimulation led to a rapid increase in mRNA and protein levels of the STAT1-target gene JMJD3. In mammary epithelial cells, JMJD3 mediates TGFβ induced EMT through upregulation of SNAIL expression, leading to breast cancer invasion (38). JMJD3 upregulates Slug and promotes cell migration, invasion, and transition towards a stem-like phenotype in hepatocellular carcinoma (39). JMJD3 could be a key regulator of cancer aggressiveness. We found that targeting JMJD3 with the inhibitor GSK-J4 or JMJD3 knockdown using siRNA abrogated IFNγ-induced ZEB1 expression.

Recently obtained evidence has indicated that EMT-associated transcription factors regulate a large set of cancer cell features, extending beyond tumor migration, invasion, and metastasis. Recent studies have demonstrated a robust correlation between EMT score, ZEB1/miR-200 levels, and PD-L1 expression in multiple cancer datasets (31). In this study, we showed that IFNγ-induced ZEB1 expression is involved in the upregulation of PD-L1 expression through its suppressive effects on miR-200 expression. Moreover, Lou and colleagues have reported that an EMT-related mRNA signature is associated with increased expression of diverse immune inhibitory ligands and receptors in lung adenocarcinoma, including PD-L1, TIM-3, LAG3, and CTLA-4 (40). As illustrated in our working model, IFNγ can simultaneously induce EMT-like features and PD-L1 expression in lung cancer cells via the upregulation of ZEB1 expression. However, whether these two events are independent remains to be elucidated. Our findings suggest that strong antitumor immune properties might be accompanied by increased tumor progression through multiple means.

In this study, downregulation of ZEB1 did not affect IFNγ-mediated suppression of cell proliferation and increased expression of CXCL9 and CXCL10. JMJD3 inhibitor GSK-J4 suppressed IFNγ-induced ZEB1 expression. GSK-J4 has been applied in the treatment of several cancers, such as acute myeloid leukemia and prostate cancer (41, 42). Our study sheds light on the functional mechanism by which targeting ZEB1 might limit the protumor effects of IFNγ.

No disclosures were reported.

J. Yang: Data curation, formal analysis, investigation, methodology, writing–original draft, writing–review and editing. X. Wang: Data curation, formal analysis, methodology. B. Huang: Data curation, formal analysis, methodology, writing–review and editing. R. Liu: Methodology. H. Xiong: Methodology, writing–review and editing. F. Ye: Methodology. C. Zeng: Methodology. X. Fu: Conceptualization, investigation, writing–review and editing. L. Li: Conceptualization, resources, formal analysis, supervision, funding acquisition, validation, methodology, writing–original draft, writing–review and editing.

This work was supported by the National Natural Science Foundation of China (Grant Nos. 81874168, 81672808, and 81472652 to L. Li).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.