NRF1 Predominantly Causes EZH2 Overexpression in Cancer Cells

NRF1 Predominantly Causes EZH2 Overexpression in Cancer Cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article NRF1 Predominantly Causes EZH2 Overexpression in Cancer Cells Dajun Deng, Juanli Qiao, Zhaojun Liu, Liankun Gu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7217912/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract EZH2 is an oncogene and therapeutic target. Only a small proportion of cancer patients benefit from treatment with EZH2 inhibitors (EZH2is). The mechanisms underlying EZH2 overexpression and EZH2i resistance are not clear. Here, we reported that the nuclear respiratory factor 1 gene ( NRF1 ) is the gene whose expression is most strongly correlated with that of the EZH2 gene in various cancer cell lines and that changes in NRF1 expression consistently cause changes in EZH2 expression in cancer cells. Mechanistically, as a transcription factor, NRF1 directly binds to the NRF1-binding sequence within the EZH2 promoter and increases EZH2 promoter activity. Deletion of the DNA-binding motif within the NRF1 or NRF1-binding sequence within the EZH2 promoter abolishes the effects of NRF1 on EZH2 expression. Notably, we further found that the status of NRF1 expression affected the sensitivity of human cancer cells to EZH2is, including GSK343 and tazemetostat. The sensitivity of cancer cells actively expressing both NRF1 and EZH2 to EZH2i is significantly greater than that of cancer cells actively expressing individual EZH2 or NRF1 alone and much greater than that of cancer cells expressing low levels of EZH2 and NRF1 . The effect of NRF1 on the sensitivity of cancer cells to EZH2i is EZH2 dependent. In conclusion, our findings reveal that NRF1 is a dominant cause of EZH2 overexpression in human cancers and that NRF1 overexpression increases the sensitivity of cancer cells to EZH2i. Active NRF1 and EZH2 expression may be useful combined predictors for the treatment of cancers with EZH2i. Health sciences/Diseases/Cancer/Cancer therapy/Targeted therapies Health sciences/Medical research/Translational research Biological sciences/Molecular biology/Transcription/Transcriptional regulatory elements NRF1 EZH2 EZH2 inhibitor cancer prediction of therapeutic sensitivity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Significance We found that NRF1, as a transcription factor, predominantly drives EZH2 overexpression in cancers, and high NRF1 and EZH2 coexpression is a predictor of the sensitivity of cancer cells to EZH2 inhibitors. INTRODUCTION The epigenetic modulator Enhancer of Zeste Homolog 2 (EZH2) is the core catalytic subunit of Polycomb Repressive Complex 2 (PRC2), which typically represses the transcription of target genes by catalyzing the trimethylation of lysine 27 of histone H3 (H3K27me3) in chromatin and activating target gene transcription via a noncanonical pathway [ 1 ]. Whereas EZH2 physiologically regulates a wide range of biological processes, including cell cycle progression, autophagy, apoptosis, DNA damage responses, cellular senescence, and cell fate decisions [ 2 – 5 ], it is also universally overexpressed in human cancers across many organs as a master determinant of cancer phenotypes [ 6 – 12 ]. EZH2 overexpression not only enhances cancer cell proliferation, migration, and invasion but also leads to poor prognosis in cancers [ 11 , 12 ]. However, the mechanisms underlying EZH2 overexpression in cancer cells remain unclear. As a cancer driver, EZH2 overexpression is a therapeutic target in the treatment of cancers. For example, the EZH2 inhibitors (EZH2is) tazemetostat and valemetostat have been approved for the treatment of non-Hodgkin's lymphoma, rare adult sarcoma, and T-cell leukemia/lymphoma [ 13 – 16 ]. A number of other EZH2is, such as GSK343 [ 17 ] and GSK126 [ 18 ], are under development. EZH2is may inhibit the growth of cancer cells not only by blocking H3K27me3 modification but also by improving immunotherapy responses through reactivating antigenic retrovirus elements in the genome [ 17 , 19 , 20 ]. Unfortunately, EZH2i resistance is unavoidable [ 21 , 22 ], and clinical biomarkers to predict the efficiency of EZH2i are in demand. Nuclear respiratory factor 1, encoded by the NRF1 gene (NCBI Gene: 4899), is a transcription factor that directly regulates several nuclear-encoded electron transport chain proteins [ 23 ]. NRF1 plays an essential role in mitochondrial biogenesis by coactivation with peroxisome proliferator-activated receptor gamma coactivator 1α (PGC-1α) [ 24 ]. NRF1 also controls the expression of genes that are associated with DNA replication, cell proliferation, and apoptosis [ 25 ]. Many studies have shown that NRF1 may participate in tumor progression. For example, NRF1 promotes spheroid survival and mesenchymal transition in breast cancer [ 26 , 27 ]. However, the effects of the NRF1 gene on cancer development and its mechanisms are largely unknown. In accordance with the extensive coexpression status of the NRF1 and EZH2 genes in various cancer tissues and our pilot study [ 28 ], in the present study, we systemically studied the contribution of NRF1, a transcription factor, to EZH2 overexpression in cancer cells. Its effect on the sensitivity of cancer cells to EZH2i was also investigated in vitro and in vivo . MATERIALS AND METHODS Cell lines and cultures The human HCT116 and SW480 colon cancer cell lines were kindly provided by Professor Yuanjia Chen at Peking Union Medical College Hospital. The RKO cell line was kindly provided by Professor Guoren Deng at the University of California. The cell lines LoVo, HEK293T, H1299, A549, and HepG2 were kindly provided by Professors Chengchao Shou, Zhiqian Zhang, and Qingyun Zhang at Peking University Cancer Hospital. The H460 cell line was purchased from the Cell Resource Center, Peking Union Medical College. These cells were grown in a 5% CO 2 atmosphere at 37 ° C in RPMI 1640 medium (GIBCO, Carlsbad, USA) supplemented with 10% fetal bovine serum (GIBCO) and 1% penicillin‒streptomycin‒glutamine (GIBCO). These cell lines were tested and authenticated by Beijing Jianlian Genes Technology Co., Ltd. Short tandem repeat (STR) patterns were analyzed via Goldeneye20A STR Identifiler PCR Amplification kit. Gene Mapper v3.2 software (ABI) was used to match the STR pattern with the online databases of ATCC. Human tissue samples Frozen colon cancer and the paired surgical margin tissue samples were collected from 15 patients. The Institutional Review Board of Peking University Cancer Hospital and Institute approved this study. Informed consent was obtained from each patient prior to inclusion in this study. Plasmid construction and transfection The pEZ-M35-NRF1 expression vector and pEZ-M35 empty control vector were purchased from FulenGen Co. (Guangzhou, China). The human DNA binding domain-deleted NRF1 mutant (Δ177–284) plasmid was kindly provided by Professor Jinrong Min at Central China Normal University [ 29 ]. Transient transfection was performed with X-tremeGENE HP DNA Transfection Reagent (Roche, Mannheim, Germany). Transfection efficiency was monitored by Western blotting. Chemicals DMSO and the EZH2i tazemetostat (EPZ-6438; E-7438) were purchased from MCE (New Jersey, USA), and tazemetostat was dissolved in DMSO at a stock concentration of 10 mmol/L. EZH2i GSK343 was purchased from Selleckchem (Houston, TX, USA). GSK343 was dissolved in DMSO at stock concentrations of 100 mg/mL and 10 mmol/L according to the manufacturer’s instructions. RNA extraction and quantitative RT‒PCR (qRT‒PCR) Total RNA was extracted via a Direct-Zol RNA MiniPrep Kit (Tianmo Sci & Tech Develop, Beijing, China) according to the manufacturer’s instructions. cDNA was synthesized via a First-Strand cDNA Synthesis Kit (TransGen Biotech, Beijing, China). SYBR Green PCR master mix reagents (Roche, Mannheim, Germany) were used to perform qRT‒PCR with an Applied Biosystems 7500 Real-Time PCR device (Thermo Fisher, Massachusetts, USA). The samples were analyzed in triplicate, and the expression levels of the target genes were normalized to those of the GAPDH gene. The 2 −ΔCt method was used to calculate the relative expression levels. The specific primer sets used in the qRT‒PCR assay were as follows (5'-3'): gagat ggtga tggga tttc and gaagg tgaag gtcgg agt for GAPDH mRNA; ttgtt ggcgg aagcg tgtaa aatc and tccct agtcc cgcgc aatgagc for EZH2 mRNA; and atgtc cgcac agaag agcaa and ttccc gccca tgctg tttat for NRF1 mRNA. Western blot The cells were collected and lysed at approximately 80% confluence. The proteins were subjected to 10% SDS‒PAGE and then transferred onto PVDF membranes. After being blocked with 5% fat-free milk at 4°C overnight, the membranes were incubated for 1 hr at room temperature with primary antibodies against NRF1, EZH2 (1:2500; Cell Signaling Technology, USA), or GAPDH (1:15000; ProteinTech, China) at room temperature for 1 hr. After being washed with PBST (PBS with 0.1% Tween 20), the membrane was incubated with a specific horseradish peroxidase-conjugated anti-rabbit/mouse IgG antibody (SE131, Solarbio, China) at room temperature for 1 hr. The signals were visualized via an enhanced chemiluminescence kit (New Cell & Molecular Biotech, China) (Supplemental file). Knockdown of gene expression by siRNA For knockdown of gene expression, small interfering double-stranded RNAs (siRNAs) targeting human NRF1 mRNAs, including siNRF#1 (sense [5'-3'], gccac agcca cacau aguatt; antisense, uacua ugugu ggcug uggctt), siNRF1#2 (sense, gcacu acgga ccaua guuatt; antisense, uaacu auggu ccgua gugctt), and scramble control RNA (sense, uucuc cgaac guguc acgutt; antisense, acgug acacg uucgg agaatt), were synthesized by Gene Pharma (Shanghai, China). When the cells reached 70–80% confluence, they were transfected with these siRNAs or scramble controls via PEI MAX (Polysciences, PA, USA) according to the manufacturer's instructions. The knockdown status of target gene expression was determined by Western blotting and qRT‒PCR. Knockout of the NRF1 or EZH2 genes via CRISPR-Cas9 A single guide RNA (sgRNA; 5'-aagac agggt taggt ttgga-3' or 5'-gactt ctgtg agctc attgc-3'; from Thermo Scientific) was used to knock out the genetic sequence in exon 3 of the NRF1 or exon 2 of the EZH2 gene. The sgRNA was inserted into the PX458 vector (Plasmid #48138, Addgene, USA) and used to transfect HCT116 or H460 cells. A flow-sorting assay was performed for green fluorescence with a FACS Calibur flow cytometer (BD Biosciences, Franklin Lakes, USA) 48 hrs posttransfection. The cells were subsequently seeded on 96-well plates to select monoclonal cells. Initial identification of NRF1- or EZH2- knockout (NRF1-KO or EZH2-KO) cell clones was carried out via genomic PCR sequencing and Western blotting. The primers used were as follows (5'-3'): sense, acctc acatt cccct tttcaca; antisense, gcctg gatta ggggg taacag for NRF1 ; sense, gagta tgttt agttc caatcgt; and antisense, ctaca gcagt catta acagtt for EZH2 . Two monoclonal cells were pooled for each experiment. Confocal immunofluorescence assay Cells grown on glass cover slips were fixed with 10% neutral formalin and permeabilized with 0.5% Triton X-100/PBS for 10 min. After being blocked with 5% BSA for 60 min, the sections were incubated with an antibody against FLAG (1:400, Protein Tech, USA) and a rabbit antibody against EZH2 (1:100) at 4°C overnight. Normal rabbit IgG was used as the negative control. Then, the slides were washed with PBST and incubated with Alexa Fluor 647-conjugated goat anti-rabbit IgG (H + L) (1:100, Beyotime Biotech, China) and FITC-labeled goat anti-mouse IgG (1:200, Beijing Zhongshan Golden Bridge Biotech, China) at room temperature for 1 hr. Nuclei were counterstained with DAPI. The cells were visualized, and images were obtained with a Zeiss confocal microscope (Oberkochen, Germany). Luciferase reporter assay The promoter regions of the EZH2 gene, including − 704 to -28, named EZH2-pro1; -520 to -28, named EZH2-pro2; and − 714 to -200, named EZH2-pro3, were inserted into the pGL3-Basic vector (Promega) between the KpnI and Bg1II restriction sites. HCT116 cells and HEK239T cells were transfected with a Renilla luciferase plasmid, and these EZH2 promoter reporter vectors were cotransfected with the NRF1 expression vector or its mutant via PEI MAX (Polysciences, USA) for 24 hrs. Then, the cells were washed, lysed, and evaluated sequentially for firefly luciferase and Renilla luciferase activities according to the Dual-Luciferase Reporter Assay System (Yeasen, Shanghai, China). The results obtained were normalized to Renilla luciferase activity. The average promoter activity for 3 biological replicates was calculated. These experiments were repeated 2 times. Chromatin immunoprecipitation assay (ChIP) The cells were fixed with 1% formaldehyde, lysed at 37°C for 10 min, and sonicated to obtain sheared DNA fragments of approximately 200 ~ 1000 bp. The chromatin was then incubated and precipitated with the NRF1 antibody or control IgG (Millipore, USA). Protein A/G-agarose beads (Roche, Mannheim, Germany) were used to collect the DNA‒protein immunocomplexes. The precipitated DNA was subsequently purified via a DNA, RNA, and protein purification kit (Macherey-Nagel, Germany). The abundance of the NRF1 antibody-precipitated EZH2 promoter was detected via quantitative PCR via the primer set (5'-3') (sense, gccgtg tgttc agcga aaga; antisense, ccgtc caatc acagg gccc). GST-NRF1 purification To construct an NRF1 expression vector, the full-length coding region of the NRF1 gene was amplified via PCR via the primers (5'-3') (sense, tcccc ccggg gggaa tggag gaaca cggag tgac; antisense, ccgct cgagc ggtca ctgtt ccaat gtcac cacctcc) and inserted into the region between the Xma1 and XhoI restriction sites in the pGEX-4T-1 vector. The NRF1 vector was used to transfect BL21 chemically competent cells (TransGen Biotech, Beijing, China). The GST-NRF1 protein was extracted from bacteria and purified with glutathione Sepharose beads (GE Healthcare, Sweden). Electrophoresis mobility shift assay (EMSA) The GST-NRF1 protein was used to detect NRF1-DNA binding activity via EMSA. An EZH2 promoter fragment (5'-3') (EZH2-bio1, ttaca gcgaa ccccg ccgc c gcccg cg cgc gcacg cgct g ccagt; containing the NRF1 binding motif ), its mutant not containing the NRF1 binding motif (EZH2-mut, ttaca gcgaa ccccg ccgc t ggagg tcagt ccgtt ggtct gcgcc ), and two other EZH2 promoter fragments not containing the NRF1 binding motif (EZH2-bio2, atcgc gccat tgcac tccag; and EZH2-bio3, gcgcg cgggg aaacg agcgc) were synthesized and used as EMSA probes. These probes were labeled with biotin at their 3′-end. A 10 × EZH2-bio1 probe or its mutant probe without biotin labeling was used as the competitive EMSA probe to assess the specificity of NRF1-DNA binding. A chemiluminescent EMSA kit (Beyotime, Shanghai, China) was used for EMSA analysis according to the manufacturer’s instructions. Cell treatment HCT116 and LoVo cells were seeded at a density of 3 × 10 4 cells/well in 96-well plates. After being cultured for 24 hrs, the cells were treated with increasing concentrations of GSK343 (0.16, 0.8, 4, 20 and 100 [µM]) dissolved in culture medium containing 0.001% DMSO for 72 hrs or with tazemetostat at increasing concentrations of 1.85, 5.56, 16.67, 50 and 150 [µM]. H460 cells were treated with increasing concentrations of GSK343 (1.67, 3.33, 10, 20 and 40 [µM]) dissolved in culture medium. In vivo xenograft experiment Five-week-old female nude BALB/c mice (18–20 g) were purchased from Beijing Huafukang Bioscience (Beijing, China) and housed under specific pathogen-free conditions. For subcutaneous tumor xenografts, 1×10 7 HCT116 NRF1-WT and NRF1-KO cells were suspended in 100 µL of phosphate-buffered saline (PBS) and then inoculated subcutaneously into the left/right posterior dorsal region of each mouse (n = 9). The mice were euthanized when the tumors reached approximately 1 cm in diameter. For drug treatment, HCT116 NRF1-wild-type (WT) and NRF1-KO cells (2.5 × 10 7 ) were suspended in 100 µL of PBS and then inoculated subcutaneously into the posterior dorsal region of each mouse. When the tumors reached a volume of approximately 50 mm 3 (approximately 5 mm in diameter), the mice were randomly divided into groups (NRF1-WT: n = 4/group; NRF1-KO: n = 7/group) to receive DMSO (as a solvent control) or GSK343 treatment (dissolved in a solution of 2% DMSO, 40% PEG300 and 5% Tween 80). GSK343 was administered at a dose of 10 mg/kg via intraperitoneal (ip) injection five times a week for 42 days. The mice were weighed, and the tumor diameter was measured with a caliper every 2 days. The tumor volume was calculated via an empirical formula (tumor volume = 0.5 × length × width 2 ). The subcutaneous tumors were surgically excised, photographed, sectioned, and fixed in 10% formalin. This study was approved by the institute animal ethics committee. Immunohistochemical (IHC) staining Xenograft-derived tumor IHC staining was performed on formaldehyde-fixed paraffin-embedded (FFPE) tissue blocks. Immunohistochemistry was carried out with an anti-Ki67 (Beijing Zhongshan Golden Bridge Biotech, China) antibody. Briefly, tissue slides were dewaxed in xylene, rehydrated, subjected to antigen retrieval in 10 mM citrate buffer (pH 6.0) at 98°C for 3 min and treated with 3% H 2 O 2 for 10 min to block endogenous peroxidase. The slides were then blocked with 5% BSA in PBS for 30 min and incubated with primary antibody overnight at 4°C. The PBS-washed sections were further treated with Histostain™-Plus and DAB Kits and counterstained with hematoxylin. The sections were dehydrated and stabilized with mounting medium, and images were taken with an optical microscope. Under 20× magnification, the percentage of Ki67-positive cells relative to the total number of cells (Ki67-positive index) in six fields of view for each group was calculated. Download of publicly available RNA-seq datasets The mRNA levels of genes associated with EZH2 transcription were extracted from cDNA array datasets for 921 cell lines from the Cancer Cell Line Encyclopedia (CCLE, Broad, 2019) [ 30 ] and for 991 samples from the pancancer analysis of whole genomes [ 31 ]. These datasets were downloaded from the cBioPortal database [ 32 – 34 ]. The coexpression analysis results were downloaded from the GEPIA2 website (gepia2.cancer-pku.cn) [ 35 ]. The drug sensitivity data for the cancer cell lines were obtained from the Genomics of Drug Sensitivity in Cancer (GDSC2) [ 36 ] and the Cancer Therapeutics Response Portal (CTRP) v2 [ 37 ]. Statistical analysis Statistical analysis was carried out using SPSS 22.0 software (SPSS Inc., Chicago, IL, USA). Data are presented as the mean ± SD or as the median or the median (25–75 percentiles). Statistical analysis methods included Student's t test, one-way analysis of variance (ANOVA), and two-way ANOVA. All tests are two-sides. A p value < 0.05 was considered statistically significant. RESULTS NRF1 upregulates EZH2 transcription The basal levels of the NRF1 protein and mRNA in colon RKO and SW480 cancer cells were lower than those in HCT116 and LoVo cells (Fig. 1 A). Thus, these cell lines were used in NRF1 gain- and loss-of-function experiments. The level of EZH2 mRNA was significantly elevated in RKO and SW480 cells with transient NRF1 overexpression (NRF1-OE) for 48 hrs (Fig. 1 B). Conversely, the level of EZH2 mRNA was significantly reduced by transient siRNA-mediated knockdown of NRF1 (siNRF1) in HCT116 and LoVo cells for 48 hrs (Fig. 1 C). In addition, siNRF1 decreased both the protein and mRNA levels of the EZH2 gene in lung A549 and H1299 cancer cells but not in liver HepG2 cancer cells (Figure S1 ). When the NRF1 exon sequence encoding the DNA binding domain was knocked out via CRISPR-Cas9 (NRF1-KO), both the mRNA and protein levels of the EZH2 gene were markedly reduced in NRF1-KO HCT116 cells (Fig. 1 D). In the rescue experiment, NRF1-OE mostly mitigated the effect of NRF1-KO on EZH2 expression. To confirm the effect of NRF1 on EZH2 expression, we further performed confocal immunofluorescence microscopy analyses. We initially mixed wild-type (WT) and NRF1-KO cells, seeded them on the same slide as the NRF1 positive and negative controls, and observed an obvious decrease in EZH2 abundance in NRF1-KO cells (GFP-labeled) relative to that in NRF1-WT cells (Fig. 1 E). Then, we performed the rescue experiment and found that the EZH2 level in NRF1-KO cells with FLAG-NRF1 expression was significantly greater than that in cells without FLAG-NRF1 expression (Fig. 1 F). These results strongly reveal that NRF1 upregulates EZH2 transcription in cancer cells. NRF1 binds the EZH2 promoter as a transcription factor To determine whether NRF1 directly upregulates EZH2 expression as a transcription factor, we searched the online promoter analysis tool Jaspar [ 38 , 39 ] and identified a putative NRF1-binding site (-118 to -129 nt) in the proximal promoter flanking the transcription start site (TSS) of the EZH2 gene (Fig. 2 A and 2 B). Chromatin immunoprecipitation (ChIP)-PCR analysis revealed that EZH2 promoter DNA was enriched by NRF1 in HCT116 cells (Fig. 2 A). To evaluate the importance of the NRF1 binding site in regulating EZH2 transcription by NRF1, we constructed three EZH2 promoter reporter vectors, including the full-length EZH2 promoter (EZH2-pro1: -28 to -704 nt) and its truncated mutants with the 184 nt deletion of the distal fragment (EZH2-pro2: -28 to -520 nt) or the 172 nt deletion of the proximal fragment (EZH2-pro3: -200 to -714 nt) not containing the NRF1 binding site (Fig. 2 B). Luciferase reporter experiments revealed that the promoter activity of EZH2-pro3 was significantly lower than that of EZH2-pro1 and EZH2-pro2 in both NRF1-OE HCT116 and HEK293T cells (Fig. 2 C). The baseline promoter activity of EZH2-pro3 was also lower than that of EZH2-pro1 and EZH2-pro2 in HCT116 cells. These findings reveal that the NRF1 binding site may play an important role in increasing EZH2 transcription via NRF1. Then, we constructed an NRF1 mutant (Δ177–284) that does not contain the DNA-binding domain. Whereas wild-type NRF1 overexpression greatly increased EZH2 promoter activity, NRF1 mutation did not affect EZH2 promoter activity (Fig. 2 D), suggesting that the DNA-binding domain is essential for NRF1 to upregulate EZH2 . We further used EMSA to validate the direct binding between the NRF1 protein and the EZH2 promoter. EMSAs revealed that the biotin-labeled EZH2 -bio1 probe (containing the NRF1-binding site) bound the purified GST-NRF1 protein and that the interaction of the NRF1 protein with the EZH2 promoter DNA was blocked by the addition of the "cold" EZH2 -bio1 probe without biotin labeling. No interaction was detected between the GST-NRF1 protein and the EZH2-bio2 or EZH2-bio3 control probes (Fig. 3 A and 3 B). In addition, the "cold" EZH2-mut probe (not containing the NRF1-binding site) did not block the interaction between NRF1 and the EZH2- bio1 probe (Fig. 3 C). These results suggest that NRF1 directly activates EZH2 transcription as a transcription factor. NRF1 is a dominant cause of cancer-specific EZH2 overexpression There are two histone H3-lysine 27 methyltransferase genes ( EZH2 and EZH1 ) in the human genome with distinct functions. For example, EZH1 is more abundant in nonproliferative adult organs, whereas EZH2 expression is tightly associated with proliferation [ 40 ]. EZH2 is frequently upregulated in many cancers (Figure S2A), whereas EZH1 is always downregulated in these cancers (Figure S2B). Unexpectedly, no inverse correlation between the levels of EZH2 and EZH1 transcripts was observed in either cancer or normal tissues from more than ten thousand patients in the TCGA or GTEx (Figure S2C), excluding the possibility that EZH1 downregulation leads to EZH2 upregulation in cancers. To evaluate the importance of NRF1 to EZH2 overexpression in cancer cells, we compared the levels of NRF1 and EZH2 expression in colon carcinoma and paired surgical margin tissue samples from 15 patients. The results of qRT‒PCR revealed that both these two genes were significantly upregulated in colon carcinoma tissues relative to the surgical margin tissues and that the NRF1 mRNA levels were significantly correlated with the EZH2 mRNA levels (the correlation coefficient (R, Pearson) = 0.90, p < 0.0001; Fig. 4 A, left). We further performed bioinformatics analyses. We found that the correlation coefficient (R, Spearman) between the levels of EZH2 and NRF1 transcripts was much greater in cancer cell lines (R = 0.70) than in cancer tissues (containing noncancer stroma cells; R = 0.48) than in normal tissues (R = 0.29 or 0.28), whereas the correlation coefficient between EZH1 and NRF1 transcript levels was much lower in cancer cell lines (R = 0.29) than in cancer tissues (R = 0.59) than in normal tissues (R = 0.73 or 0.74) (Fig. 4 B). In addition, EZH2 transcript levels in cancer cell lines or tissues were consistently and positively associated with the number of copies of the NRF1 gene (Figure S3A and S3B). EZH2 protein levels in cancer cell lines were also significantly associated with NRF1 protein levels (Figure S3D; R = 0.47). These data suggest that NRF1 may upregulate EZH2 in a cancer-specific fashion. Although somatic copy number amplification caused upregulation of the EZH2 gene (Figure S3C), the frequency of copy number amplification of EZH2 across cancers was very low (0.79%; 78 of 9889 samples). A positive correlation between the levels of NRF1 and EZH2 transcripts was consistently observed in various pancancer subgroups with and without copy number alterations in the EZH2 gene (Fig. 4 C), suggesting that NRF1 has a dominant effect on EZH2 overexpression in cancer cells. Furthermore, NRF1 is among the top genes whose expression is correlated mostly with EZH2 expression and vice versa according to transcriptome datasets in the CCLE project (Figure S4A and S4B). In fact, NRF1 is the only transcription factor among these top 20 EZH2 -cotranscribing genes. These phenomena suggest that NRF1 may be a master transcription factor for the EZH2 gene. To investigate the role of NRF1 in colon cancer, we detected the effect of NRF1-KO on the proliferation of HCT116 cells in vitro and in vivo . The results of long-term dynamic monitoring of live cells revealed that compared with NRF1-WT, NRF1-KO significantly inhibited cell proliferation (Figure S5A). Furthermore, we established a tumor xenograft mouse model by subcutaneously implanting NRF1-WT and NRF1-KO HCT116 cells into nude mice. The results revealed that NRF1-KO cell-derived xenografts were observed in only one of these mice (1/9), whereas NRF1-WT cell-derived xenografts were observed in all nine mice (9/9) (Figure S5B, p < 0.0001). These results suggest that NRF1 promotes tumor growth. NRF1 increases the sensitivity of cancer cells to EZH2 inhibitors GSK343 is an EZH2i. By analyzing the GDSC2 datasets [ 36 ] and Cancer Cell Line Encyclopedia (CCLE) datasets [ 30 ], we found that among the transcription factor ChIP-seq clusters from ENCODE with factorbook motifs (Figure S4C) [ 39 ], information on both the area under curve (AUC) of GSK343 and the mRNA levels was available for 71 transcription factors that can bind the EZH2 promoter in human cancer cell lines (n = 845) and that the correlation coefficient between the levels of the NRF1 transcript and the AUC of GSK343 was among the top three (Figure S6A). A similar relationship was also observed between the sensitivity of cancer cell lines (n = 750) to BRD-K62801835, another EZH2i, by analyzing the CTRPv2 datasets (Figure S6B) [ 37 ]. In addition, the levels of both EZH2 and NRF1 transcripts were inversely correlated with the half maximal inhibitory concentration (IC50) of GSK343 (R=-0.267 and − 0.320, respectively) (Figure S7A). When these cell lines were subclassified as NRF1 or EZH2 expression-high or -low according to the median mRNA level, the GSK343-IC50 of the NRF1 or EZH2 expression-high cancer cell lines was significantly lower than that of the NRF1 or EZH2 expression-low cancer cell lines (Figure S7B). Notably, the GSK343-IC50 of cell lines with high NRF1 expression was significantly lower than that of cells with low NRF1 expression among the cell lines with high EZH2 expression, whereas no significant difference in the GSK343-IC50 was detected between NRF1 -high cell lines and NRF1 -low cell lines among the cell lines with low EZH2 expression (Figure S7C). These results suggest that NRF1 may affect the sensitivity of cancer cells to GSK343 through the upregulation of EZH2 . We further found that the GSK343-IC50 was increased by siNRF1 in both HCT116 cells (9.8 to 11.6 or 12.2 [µM]) and LoVo cells (5.1 to 7.0 or 6.8) (Fig. 5 A and 5 B). We also found that the GSK343-IC50 was increased by NRF1-KO in HCT116 cells (8.9 to 14.5). NRF1-OE clearly mitigated the effect of NRF1-KO (14.5 to 10.8) on the GSK343-IC50 in the rescue experiment (Fig. 5 C). Similar effects of changes in NRF1 expression on the sensitivity of another EZH2i, tazemetostat, were also detected (Figure S8). To evaluate whether NRF1 affects the sensitivity of cancer cells to EZH2is through the upregulation of EZH2 , we knocked out the EZH2 gene (EZH2-KO) in H460 cells (Fig. 6 A) and used these cells to determine whether EZH2-KO cancels the effects of NRF1 on the sensitivity of cancer cells to EZH2is. EZH2-KO alone weakly increased the GSK343-IC50 (5.2 to 5.9 or 9.2 to 10.0). While NRF1-OE or siNRF1 decreased or increased the GSK343-IC50 only in EZH2-WT cells, such effects were not detected in EZH2-KO cells (Fig. 6 B and 6 C), demonstrating that the effects of NRF1 expression changes on the GSK343-IC50 were dependent on the effect of NRF1 on EZH2 transcription. To confirm the impact of NRF1 on the sensitivity of cancer cells to EZH2i in vivo , we established xenograft mouse models by subcutaneously implanting NRF1-WT and NRF1-KO HCT116 cells into nude mice. When the tumors became palpable (approximately 50 mm 3 ), the mice were treated with DMSO (as a solvent control) or GSK343 at a dose of 10 mg/kg. After 42 days of GSK343 treatment, the tumors in the control group reached the predetermined endpoint. Strikingly, GSK343 treatment was much more effective than DMSO treatment for NRF1-WT tumors, whereas there were no significant differences in the growth of NRF1-KO tumors between the GSK343 group and the DMSO group (Fig. 7 A). The growth of NRF1-WT tumors was greater than that of NRF1-KO tumors in the mice treated with DMSO. This difference was not observed in the mice treated with GSK343. Moreover, the Ki67 staining results were consistent with the volume of the tumors (Fig. 7 B). All the mice exhibited a decrease in body weight, particularly those in the NRF1-WT group (Fig. 7 C). Taken together, these in vivo results confirmed that NRF1 increased the sensitivity of cancer cells to EZH2i. NRF1 loss abolished the effect of EZH2i treatment on the growth of tumors. DISCUSSIONS EZH2 is a cancer driver and therapeutic target that is consistently upregulated in many cancers. How EZH2 is upregulated in cancer cells and why most cancer patients cannot benefit from EZH2i treatment are not clear [ 21 , 22 ]. NRF1 is a typical transcription factor [ 25 , 42 – 44 ]. In this study, via bioinformatics analyses and systemic experiments, we found that NRF1 is a master transcription factor of the EZH2 gene and that NRF1 upregulation is a determinant of EZH2 overexpression in human cancers. Most importantly, our findings demonstrate that active NRF1 expression significantly increases the sensitivity of colon cancer cells to EZH2i in an EZH2-dependent manner and that NRF1 loss disrupts the anticancer effect of EZH2i treatment. EZH2 is the key catalytic subunit of PRC2, and its overexpression drives cancer development via the H3K27me3 and nonhistone protein methylation pathways [ 1 , 10 ]. There are numerous reports on target genes of the EZH2 protein and its posttranslational modifications, including phosphorylation, acetylation, ubiquitination, GlcNAcylation, and SUMOylation [ 45 ]. Somatic copy number amplification of the EZH2 gene may partially account for EZH2 overexpression in a small proportion of human cancers because the frequency of EZH2 amplification is less than 1% in cancer samples in the TCGA project. EZH2 is reportedly regulated by several transcription factors. For example, the transcription factors BRD4 and E2Fs induce EZH2 transcriptional activation in bladder tumors [ 46 , 47 ]. C-MYC promotes EZH2 overexpression in leukemia and prostate cancers [ 48 , 49 ]. STAT3 upregulates EZH2 transcriptional activation and is associated with poor prognosis in patients with gastric cancer [ 50 ]. However, the determinants and exact mechanisms underlying EZH2 overexpression in human cancers are not clear. Both the EZH2 and NRF1 genes are overexpressed in a variety of cancers [ 7 , 12 , 51 – 53 ], and we speculate that NRF1 may play an important role in this process. For this purpose, we analyzed RNA-seq datasets from the CCLE and TCGA databases and found that the transcription levels of NRF1 and EZH2 were mostly correlated with each other in cancers. Notably, the correlation between NRF1 and EZH2 transcription gradually decreased from cancer cell lines to cancer tissues, noncancerous tissues from cancer patients, and normal human tissues, suggesting a tumor-specific effect of NRF1 to EZH2 overexpression. In contrast, the transcriptional correlation between NRF1 and EZH1 (normally expressed in nonproliferative adult cells) gradually increased from cancer cells to normal cells. Our bioinformatics and experimental findings indicate that NRF1 is a master regulator of EZH2 and that its overexpression is the determinant of EZH2 overexpression in human cancers. As an epigenetic silencer, EZH2 plays essential roles in multiple biological processes. EZH2 overexpression is common in human cancers and is associated with aggressiveness, poor prognosis, and recurrence as a cancer driver [ 6 , 54 ]. Researchers have synthesized various small EZH2i chemicals, some of which have entered clinical trials or been approved for clinical treatment [ 55 – 57 ]. For example, CPI-1205 [ 58 ], GSK343 [ 59 ], GSK126 [ 18 ], and SHR2554 [ 60 ] are in clinical trials. Tazemetostat and valemetostat have been marketed for the treatment of rare adult sarcomas in the USA [ 14 ] and T-cell leukemia/lymphoma in Japan [ 16 ]. Unfortunately, only a limited proportion of cancer patients benefit from treatment with EZH2i. Thus, predictors of the sensitivity of cancer patients to treatment with EZH2i are urgently needed. In this study, we analyzed the correlation between the levels of NRF1 and/or EZH2 transcripts and the sensitivity of cancer cell lines to GSK343 in the GDSC2 datasets. We found that the expression levels of both the NRF1 and EZH2 genes were inversely correlated with the IC50 of GSK343, and the cells with high NRF1 and EZH2 coexpression were more sensitive to GSK343 than were the cells with high individual NRF1 or EZH2 expression or low NRF1 and EZH2 coexpression. In addition, the correlation coefficient of NRF1 mRNA with the AUC of GSK343 is the third highest among 71 transcription factor candidates for EZH2 , according to the public ENCODE and GDSC2 data [ 36 , 39 ]. Knockdown or knockout of NRF1 decreased the sensitivity of cancer cells to GSK343 and tazemetostat in an EZH2-dependent manner. Similar phenomena was also observed for another EZH2i BRD-K62801835, according to the CTRCv2 data [ 37 ]. These results suggest that NRF1 overexpression increases the sensitivity of EZH2- expressing cells to EZH2is and may be a potential biomarker for predicting the therapeutic efficacy of EZH2is. Further clinical trials are warranted to study the feasibility of using high NRF1 and EZH2 coexpression as a combined biomarker for predicting the therapeutic effects of EZH2is. The causes of NRF1 overexpression in cancer cells and whether NRF1 itself is a therapeutic target are also worthy of study. In conclusion, we found that NRF1, as a transcription factor, predominantly upregulates the transcription of the EZH2 gene. NRF1 overexpression not only causes EZH2 overexpression in cancer cells but also increases the sensitivity of cancer cells to EZH2i. High NRF1 and EZH2 coexpression is a potential combined biomarker for predicting the therapeutic effects of EZH2is. Declarations COMPETING INTERESTS : The authors declare that they have no competing interests. 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(\u003cstrong\u003eB\u003c/strong\u003e) The mRNA and protein levels of EZH2 in RKO and SW480 cells with transient NRF1 overexpression (NRF1-OE) for 48 hrs, as determined by qRT‒PCR and western blotting. The mRNA level of \u003cem\u003eEZH2\u003c/em\u003e was normalized to that of \u003cem\u003eGAPDH\u003c/em\u003e. (\u003cstrong\u003eC\u003c/strong\u003e) Effects of siRNA-mediated knockdown of \u003cem\u003eNRF1\u003c/em\u003e (siNRF1) on the mRNA and protein levels of \u003cem\u003eEZH2\u003c/em\u003e in HCT116 and Lovo cells for 48 hrs. (\u003cstrong\u003eD\u003c/strong\u003e) Effect of \u003cem\u003eNRF1\u003c/em\u003e knockout (NRF1-KO) via CRISPR-Cas9 and restoration of \u003cem\u003eNRF1\u003c/em\u003eexpression on the mRNA and protein levels of \u003cem\u003eEZH2\u003c/em\u003e in HCT116 cells. The PCR-sequencing results, sgRNA-matched sites within the DNA binding domain of the NRF1 protein, and the \u003cem\u003eNRF1\u003c/em\u003e exon sequence are labeled on the left. (\u003cstrong\u003eE\u003c/strong\u003e) Comparison of the abundance of EZH1 in pooled NRF1-WT and KO (GFP-labeled) HCT116 cells, as determined by confocal immunofluorescence microscopy analysis. (\u003cstrong\u003eF\u003c/strong\u003e) Comparison of the abundance of EZH1 in NRF1-KO HCT116 cells with and without the restoration of NRF1 expression by the FLAG-NRF1 vector. The data are presented as the means ± SDs for 3 biological replicates. Student’s t test: */***P\u0026lt;0.05/0.001.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/5aca732ef96d3745fccb30e7.png"},{"id":92874163,"identity":"a35a7e86-f406-42f8-9e15-f2655336a7ba","added_by":"auto","created_at":"2025-10-06 14:25:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":219731,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNRF1 increases EZH2 promoter activity. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Chromatin immunoprecipitation (ChIP)-PCR was used to detect NRF1 binding to the \u003cem\u003eEZH2\u003c/em\u003e promoter. The NRF1 binding consensus sequence predicted by Jaspar is listed at the top. (\u003cstrong\u003eB\u003c/strong\u003e) Schematic representation of the human EZH2 promoter, its luciferase reporter constructs, and the predicated NRF1 binding site (marked in red). (\u003cstrong\u003eC\u003c/strong\u003e) Comparison of the activity of various \u003cem\u003eEZH2\u003c/em\u003e promoter reporters in HEK293T and HCT116 cells with and without NRF1-OE. (\u003cstrong\u003eD\u003c/strong\u003e) Effects of deleting the DNA binding domain (amino acids 177-284) of the NRF1 protein on \u003cem\u003eEZH2\u003c/em\u003e promoter activity. All the data are presented as the means ± SDs. Statistical analysis was performed via two-tailed Student’s t test. **P \u0026lt; 0.01; ***P \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/1935e7983e1a13e1683e1b40.png"},{"id":92875100,"identity":"dbae6701-a3d3-4ddb-9ec3-4ff08f1051a7","added_by":"auto","created_at":"2025-10-06 14:33:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":278766,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDirect binding of NRF1 to the EZH2 promoter.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) Location and sequence information of the \u003cem\u003eEZH2\u003c/em\u003e promoter probes. (\u003cstrong\u003eB\u003c/strong\u003e) The results of EMSA analysis to detect direct interactions between the biotin-labeled EZH2 probes containing or not containing the predicted NRF1 binding site. The EZH2 probe-GST-NRF1 binding band is indicated with arrows. (\u003cstrong\u003eC\u003c/strong\u003e) Comparison of differences in NRF1 binding affinity between the wild-type EZH2-bio1 probe and its mutant not containing the NRF1 binding sequence.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/ddb188bc371d8a881aea0429.png"},{"id":92874167,"identity":"c8f99288-3981-49d9-a348-9986881c7ae6","added_by":"auto","created_at":"2025-10-06 14:25:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":476562,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between the expression levels of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNRF1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eEZH2\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e/\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e in normal and cancer tissues and cancer cell lines.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) \u003cem\u003eEZH2\u003c/em\u003e and \u003cem\u003eNRF1\u003c/em\u003e mRNA levels in colon carcinoma and surgical margin tissue samples from 15 patients, as determined via qRT‒PCR. Correlation between \u003cem\u003eEZH2\u003c/em\u003e and \u003cem\u003eNRF1\u003c/em\u003e mRNA levels among these sample is illustrated in the left. (\u003cstrong\u003eB\u003c/strong\u003e) The correlation between \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2/1\u003c/em\u003e mRNA levels according to publicly available RNA-seq datasets. (\u003cstrong\u003eC\u003c/strong\u003e) Correlations between \u003cem\u003eEZH2\u003c/em\u003emRNA levels and \u003cem\u003eNRF1\u003c/em\u003e copy number in various cancer subgroups with different states of copy number alterations of the \u003cem\u003eEZH2\u003c/em\u003e gene according to the TCGA datasets. These charts were adapted with images downloaded from the GEPIA and cBioPortal for cancer genomics websites [30,32-35].\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/0001da246f80831202446df9.png"},{"id":92875104,"identity":"4963ccaf-8536-4260-bf8e-bc73102b60c3","added_by":"auto","created_at":"2025-10-06 14:33:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":380128,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of changes in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNRF1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e expression on the dose‒response curve and viability of cells treated with GSK343.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003eand \u003cstrong\u003eB\u003c/strong\u003e) Effect of siNRF1 on the sensitivity of HCT116 and Lovo cells to GSK343. The status of \u003cem\u003eNRF1\u003c/em\u003e knockdown was monitored by Western blotting and qRT‒PCR.\u003cstrong\u003e \u003c/strong\u003e(\u003cstrong\u003eC\u003c/strong\u003e) Effect of NRF1-KO and restoration of \u003cem\u003eNRF1\u003c/em\u003e expression on the sensitivity of HCT116 cells to GSK343. The status of \u003cem\u003eNRF1\u003c/em\u003erestoration was monitored by Western blotting. The GSK343-IC50 values are labeled.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/9f76d338284ac22ad3dc7a84.png"},{"id":92875106,"identity":"e454086e-13cd-4910-8670-2e594135d9c8","added_by":"auto","created_at":"2025-10-06 14:33:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":383248,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eEZH2\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eknockout and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNRF1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e expression changes on the dose‒response curve and viability of H460 cells in response to GSK343.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) Location of the sgRNA and characterization of \u003cem\u003eEZH2\u003c/em\u003e knockout, as determined by PCR sequencing (left) and Western blotting (right). (\u003cstrong\u003eB\u003c/strong\u003e and \u003cstrong\u003eC\u003c/strong\u003e) Effects of NRF1-OE and siNRF1 on the sensitivity of EZH2-WT and EZH2-KO cells to GSK343. The states of \u003cem\u003eNRF1\u003c/em\u003e expression and knockdown were monitored by Western blotting. EPZ6438-IC50 values are labeled.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/c803db9064cbdf7eb45c60e0.png"},{"id":92875103,"identity":"85b5a943-adec-45f2-8761-c8b1a6539e2e","added_by":"auto","created_at":"2025-10-06 14:33:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":978653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of NRF1-KO and the EZH2i GSK343 on the proliferation of HCT116 cells\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e in vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003eGSK343 and the DMSO\u003cstrong\u003e \u003c/strong\u003econtrol were injected into nude mice (WT-DMSO: n=4; WT-GSK343: n=4; NRF1-KO_DMSO: n=7; NRF1-KO_GSK343: n=7). (\u003cstrong\u003eA\u003c/strong\u003e) Relative tumor volumes. (\u003cstrong\u003eB\u003c/strong\u003e) Histological HE and Ki67-stained tissue images of representative tumor xenografts. The Ki67-positive index is presented as the mean ± SD. (\u003cstrong\u003eC\u003c/strong\u003e) Mouse body weight.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/dd5e3ddab03672e741082df7.png"},{"id":92876120,"identity":"392c1088-74da-4745-9570-373db81e606f","added_by":"auto","created_at":"2025-10-06 14:41:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4092814,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/a55410ca-1e2c-4c6e-96b9-c3d137d308c1.pdf"},{"id":92874166,"identity":"54c8db7b-84bc-40c1-aabb-341b011ab211","added_by":"auto","created_at":"2025-10-06 14:25:23","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1477327,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental file\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw images for Western blot analyses.\u003c/p\u003e","description":"","filename":"Suppl.fileforwesternblot.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/c17feded8bd4477cbc8880fa.pdf"},{"id":92874171,"identity":"93f95c4e-466e-4c64-85a4-3712c9bc804a","added_by":"auto","created_at":"2025-10-06 14:25:23","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":6652380,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-7217912/v1/ceb9da8ec69e933c91529025.docx"}],"financialInterests":"(Not answered)","formattedTitle":"NRF1 Predominantly Causes EZH2 Overexpression in Cancer Cells","fulltext":[{"header":"Significance","content":"\u003cp\u003eWe found that NRF1, as a transcription factor, predominantly drives EZH2 overexpression in cancers, and high NRF1 and EZH2 coexpression is a predictor of the sensitivity of cancer cells to EZH2 inhibitors.\u003c/p\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eThe epigenetic modulator Enhancer of Zeste Homolog 2 (EZH2) is the core catalytic subunit of Polycomb Repressive Complex 2 (PRC2), which typically represses the transcription of target genes by catalyzing the trimethylation of lysine 27 of histone H3 (H3K27me3) in chromatin and activating target gene transcription via a noncanonical pathway [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Whereas EZH2 physiologically regulates a wide range of biological processes, including cell cycle progression, autophagy, apoptosis, DNA damage responses, cellular senescence, and cell fate decisions [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], it is also universally overexpressed in human cancers across many organs as a master determinant of cancer phenotypes [\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10 CR11\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. EZH2 overexpression not only enhances cancer cell proliferation, migration, and invasion but also leads to poor prognosis in cancers [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, the mechanisms underlying EZH2 overexpression in cancer cells remain unclear.\u003c/p\u003e\u003cp\u003eAs a cancer driver, EZH2 overexpression is a therapeutic target in the treatment of cancers. For example, the EZH2 inhibitors (EZH2is) tazemetostat and valemetostat have been approved for the treatment of non-Hodgkin's lymphoma, rare adult sarcoma, and T-cell leukemia/lymphoma [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A number of other EZH2is, such as GSK343 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and GSK126 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], are under development. EZH2is may inhibit the growth of cancer cells not only by blocking H3K27me3 modification but also by improving immunotherapy responses through reactivating antigenic retrovirus elements in the genome [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Unfortunately, EZH2i resistance is unavoidable [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and clinical biomarkers to predict the efficiency of EZH2i are in demand.\u003c/p\u003e\u003cp\u003eNuclear respiratory factor 1, encoded by the \u003cem\u003eNRF1\u003c/em\u003e gene (NCBI Gene: 4899), is a transcription factor that directly regulates several nuclear-encoded electron transport chain proteins [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. NRF1 plays an essential role in mitochondrial biogenesis by coactivation with peroxisome proliferator-activated receptor gamma coactivator 1α (PGC-1α) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. NRF1 also controls the expression of genes that are associated with DNA replication, cell proliferation, and apoptosis [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Many studies have shown that NRF1 may participate in tumor progression. For example, NRF1 promotes spheroid survival and mesenchymal transition in breast cancer [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, the effects of the \u003cem\u003eNRF1\u003c/em\u003e gene on cancer development and its mechanisms are largely unknown.\u003c/p\u003e\u003cp\u003eIn accordance with the extensive coexpression status of the \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e genes in various cancer tissues and our pilot study [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], in the present study, we systemically studied the contribution of NRF1, a transcription factor, to EZH2 overexpression in cancer cells. Its effect on the sensitivity of cancer cells to EZH2i was also investigated \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cb\u003eCell lines and cultures\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe human HCT116 and SW480 colon cancer cell lines were kindly provided by Professor Yuanjia Chen at Peking Union Medical College Hospital. The RKO cell line was kindly provided by Professor Guoren Deng at the University of California. The cell lines LoVo, HEK293T, H1299, A549, and HepG2 were kindly provided by Professors Chengchao Shou, Zhiqian Zhang, and Qingyun Zhang at Peking University Cancer Hospital. The H460 cell line was purchased from the Cell Resource Center, Peking Union Medical College. These cells were grown in a 5% CO\u003csub\u003e2\u003c/sub\u003e atmosphere at 37\u003csup\u003e\u0026deg;\u003c/sup\u003eC in RPMI 1640 medium (GIBCO, Carlsbad, USA) supplemented with 10% fetal bovine serum (GIBCO) and 1% penicillin‒streptomycin‒glutamine (GIBCO). These cell lines were tested and authenticated by Beijing Jianlian Genes Technology Co., Ltd. Short tandem repeat (STR) patterns were analyzed via Goldeneye20A STR Identifiler PCR Amplification kit. Gene Mapper v3.2 software (ABI) was used to match the STR pattern with the online databases of ATCC.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHuman tissue samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFrozen colon cancer and the paired surgical margin tissue samples were collected from 15 patients. The Institutional Review Board of Peking University Cancer Hospital and Institute approved this study. Informed consent was obtained from each patient prior to inclusion in this study.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePlasmid construction and transfection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe pEZ-M35-NRF1 expression vector and pEZ-M35 empty control vector were purchased from FulenGen Co. (Guangzhou, China). The human DNA binding domain-deleted \u003cem\u003eNRF1\u003c/em\u003e mutant (Δ177\u0026ndash;284) plasmid was kindly provided by Professor Jinrong Min at Central China Normal University [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Transient transfection was performed with X-tremeGENE HP DNA Transfection Reagent (Roche, Mannheim, Germany). Transfection efficiency was monitored by Western blotting.\u003c/p\u003e\u003cp\u003e\u003cb\u003eChemicals\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDMSO and the EZH2i tazemetostat (EPZ-6438; E-7438) were purchased from MCE (New Jersey, USA), and tazemetostat was dissolved in DMSO at a stock concentration of 10 mmol/L. EZH2i GSK343 was purchased from Selleckchem (Houston, TX, USA). GSK343 was dissolved in DMSO at stock concentrations of 100 mg/mL and 10 mmol/L according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA extraction and quantitative RT‒PCR (qRT‒PCR)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal RNA was extracted via a Direct-Zol RNA MiniPrep Kit (Tianmo Sci \u0026amp; Tech Develop, Beijing, China) according to the manufacturer\u0026rsquo;s instructions. cDNA was synthesized via a First-Strand cDNA Synthesis Kit (TransGen Biotech, Beijing, China). SYBR Green PCR master mix reagents (Roche, Mannheim, Germany) were used to perform qRT‒PCR with an Applied Biosystems 7500 Real-Time PCR device (Thermo Fisher, Massachusetts, USA). The samples were analyzed in triplicate, and the expression levels of the target genes were normalized to those of the \u003cem\u003eGAPDH\u003c/em\u003e gene. The 2\u003csup\u003e\u0026minus;ΔCt\u003c/sup\u003e method was used to calculate the relative expression levels. The specific primer sets used in the qRT‒PCR assay were as follows (5'-3'): gagat ggtga tggga tttc and gaagg tgaag gtcgg agt for \u003cem\u003eGAPDH\u003c/em\u003e mRNA; ttgtt ggcgg aagcg tgtaa aatc and tccct agtcc cgcgc aatgagc for \u003cem\u003eEZH2\u003c/em\u003e mRNA; and atgtc cgcac agaag agcaa and ttccc gccca tgctg tttat for \u003cem\u003eNRF1\u003c/em\u003e mRNA.\u003c/p\u003e\u003cp\u003e\u003cb\u003eWestern blot\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe cells were collected and lysed at approximately 80% confluence. The proteins were subjected to 10% SDS‒PAGE and then transferred onto PVDF membranes. After being blocked with 5% fat-free milk at 4\u0026deg;C overnight, the membranes were incubated for 1 hr at room temperature with primary antibodies against NRF1, EZH2 (1:2500; Cell Signaling Technology, USA), or GAPDH (1:15000; ProteinTech, China) at room temperature for 1 hr. After being washed with PBST (PBS with 0.1% Tween 20), the membrane was incubated with a specific horseradish peroxidase-conjugated anti-rabbit/mouse IgG antibody (SE131, Solarbio, China) at room temperature for 1 hr. The signals were visualized via an enhanced chemiluminescence kit (New Cell \u0026amp; Molecular Biotech, China) (Supplemental file).\u003c/p\u003e\u003cp\u003e\u003cb\u003eKnockdown of gene expression by siRNA\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor knockdown of gene expression, small interfering double-stranded RNAs (siRNAs) targeting human \u003cem\u003eNRF1\u003c/em\u003e mRNAs, including siNRF#1 (sense [5'-3'], gccac agcca cacau aguatt; antisense, uacua ugugu ggcug uggctt), siNRF1#2 (sense, gcacu acgga ccaua guuatt; antisense, uaacu auggu ccgua gugctt), and scramble control RNA (sense, uucuc cgaac guguc acgutt; antisense, acgug acacg uucgg agaatt), were synthesized by Gene Pharma (Shanghai, China). When the cells reached 70\u0026ndash;80% confluence, they were transfected with these siRNAs or scramble controls via PEI MAX (Polysciences, PA, USA) according to the manufacturer's instructions. The knockdown status of target gene expression was determined by Western blotting and qRT‒PCR.\u003c/p\u003e\u003cp\u003e\u003cb\u003eKnockout of the\u003c/b\u003e \u003cb\u003eNRF1\u003c/b\u003e \u003cb\u003eor\u003c/b\u003e \u003cb\u003eEZH2\u003c/b\u003e \u003cb\u003egenes via CRISPR-Cas9\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA single guide RNA (sgRNA; 5'-aagac agggt taggt ttgga-3' or 5'-gactt ctgtg agctc attgc-3'; from Thermo Scientific) was used to knock out the genetic sequence in exon 3 of the \u003cem\u003eNRF1\u003c/em\u003e or exon 2 of the \u003cem\u003eEZH2\u003c/em\u003e gene. The sgRNA was inserted into the PX458 vector (Plasmid #48138, Addgene, USA) and used to transfect HCT116 or H460 cells. A flow-sorting assay was performed for green fluorescence with a FACS Calibur flow cytometer (BD Biosciences, Franklin Lakes, USA) 48 hrs posttransfection. The cells were subsequently seeded on 96-well plates to select monoclonal cells. Initial identification of \u003cem\u003eNRF1-\u003c/em\u003e or \u003cem\u003eEZH2-\u003c/em\u003eknockout (NRF1-KO or EZH2-KO) cell clones was carried out via genomic PCR sequencing and Western blotting. The primers used were as follows (5'-3'): sense, acctc acatt cccct tttcaca; antisense, gcctg gatta ggggg taacag for \u003cem\u003eNRF1\u003c/em\u003e; sense, gagta tgttt agttc caatcgt; and antisense, ctaca gcagt catta acagtt for \u003cem\u003eEZH2\u003c/em\u003e. Two monoclonal cells were pooled for each experiment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConfocal immunofluorescence assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCells grown on glass cover slips were fixed with 10% neutral formalin and permeabilized with 0.5% Triton X-100/PBS for 10 min. After being blocked with 5% BSA for 60 min, the sections were incubated with an antibody against FLAG (1:400, Protein Tech, USA) and a rabbit antibody against EZH2 (1:100) at 4\u0026deg;C overnight. Normal rabbit IgG was used as the negative control. Then, the slides were washed with PBST and incubated with Alexa Fluor 647-conjugated goat anti-rabbit IgG (H\u0026thinsp;+\u0026thinsp;L) (1:100, Beyotime Biotech, China) and FITC-labeled goat anti-mouse IgG (1:200, Beijing Zhongshan Golden Bridge Biotech, China) at room temperature for 1 hr. Nuclei were counterstained with DAPI. The cells were visualized, and images were obtained with a Zeiss confocal microscope (Oberkochen, Germany).\u003c/p\u003e\u003cp\u003e\u003cb\u003eLuciferase reporter assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe promoter regions of the \u003cem\u003eEZH2\u003c/em\u003e gene, including \u0026minus;\u0026thinsp;704 to -28, named EZH2-pro1; -520 to -28, named EZH2-pro2; and \u0026minus;\u0026thinsp;714 to -200, named EZH2-pro3, were inserted into the pGL3-Basic vector (Promega) between the \u003cem\u003eKpnI\u003c/em\u003e and \u003cem\u003eBg1II\u003c/em\u003e restriction sites. HCT116 cells and HEK239T cells were transfected with a Renilla luciferase plasmid, and these \u003cem\u003eEZH2\u003c/em\u003e promoter reporter vectors were cotransfected with the \u003cem\u003eNRF1\u003c/em\u003e expression vector or its mutant via PEI MAX (Polysciences, USA) for 24 hrs. Then, the cells were washed, lysed, and evaluated sequentially for firefly luciferase and Renilla luciferase activities according to the Dual-Luciferase Reporter Assay System (Yeasen, Shanghai, China). The results obtained were normalized to Renilla luciferase activity. The average promoter activity for 3 biological replicates was calculated. These experiments were repeated 2 times.\u003c/p\u003e\u003cp\u003e\u003cb\u003eChromatin immunoprecipitation assay (ChIP)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe cells were fixed with 1% formaldehyde, lysed at 37\u0026deg;C for 10 min, and sonicated to obtain sheared DNA fragments of approximately 200\u0026thinsp;~\u0026thinsp;1000 bp. The chromatin was then incubated and precipitated with the NRF1 antibody or control IgG (Millipore, USA). Protein A/G-agarose beads (Roche, Mannheim, Germany) were used to collect the DNA‒protein immunocomplexes. The precipitated DNA was subsequently purified via a DNA, RNA, and protein purification kit (Macherey-Nagel, Germany). The abundance of the NRF1 antibody-precipitated \u003cem\u003eEZH2\u003c/em\u003e promoter was detected via quantitative PCR via the primer set (5'-3') (sense, gccgtg tgttc agcga aaga; antisense, ccgtc caatc acagg gccc).\u003c/p\u003e\u003cp\u003e\u003cb\u003eGST-NRF1 purification\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo construct an \u003cem\u003eNRF1\u003c/em\u003e expression vector, the full-length coding region of the \u003cem\u003eNRF1\u003c/em\u003e gene was amplified via PCR via the primers (5'-3') (sense, tcccc ccggg gggaa tggag gaaca cggag tgac; antisense, ccgct cgagc ggtca ctgtt ccaat gtcac cacctcc) and inserted into the region between the \u003cem\u003eXma1\u003c/em\u003e and \u003cem\u003eXhoI\u003c/em\u003e restriction sites in the pGEX-4T-1 vector. The \u003cem\u003eNRF1\u003c/em\u003e vector was used to transfect BL21 chemically competent cells (TransGen Biotech, Beijing, China). The GST-NRF1 protein was extracted from bacteria and purified with glutathione Sepharose beads (GE Healthcare, Sweden).\u003c/p\u003e\u003cp\u003e\u003cb\u003eElectrophoresis mobility shift assay (EMSA)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe GST-NRF1 protein was used to detect NRF1-DNA binding activity via EMSA. An \u003cem\u003eEZH2\u003c/em\u003e promoter fragment (5'-3') (EZH2-bio1, ttaca gcgaa ccccg ccgc\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ec gcccg cg\u003c/span\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ecgc gcacg cgct\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eg ccagt;\u003c/span\u003e containing \u003cem\u003ethe NRF1 binding motif\u003c/em\u003e), its mutant not containing the NRF1 binding motif (EZH2-mut, ttaca gcgaa ccccg ccgc\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003et ggagg tcagt ccgtt ggtct gcgcc\u003c/span\u003e), and two other \u003cem\u003eEZH2\u003c/em\u003e promoter fragments not containing the NRF1 binding motif (EZH2-bio2, atcgc gccat tgcac tccag; and EZH2-bio3, gcgcg cgggg aaacg agcgc) were synthesized and used as EMSA probes. These probes were labeled with biotin at their 3\u0026prime;-end. A 10 \u0026times; EZH2-bio1 probe or its mutant probe without biotin labeling was used as the competitive EMSA probe to assess the specificity of NRF1-DNA binding. A chemiluminescent EMSA kit (Beyotime, Shanghai, China) was used for EMSA analysis according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCell treatment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHCT116 and LoVo cells were seeded at a density of 3 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cells/well in 96-well plates. After being cultured for 24 hrs, the cells were treated with increasing concentrations of GSK343 (0.16, 0.8, 4, 20 and 100 [\u0026micro;M]) dissolved in culture medium containing 0.001% DMSO for 72 hrs or with tazemetostat at increasing concentrations of 1.85, 5.56, 16.67, 50 and 150 [\u0026micro;M]. H460 cells were treated with increasing concentrations of GSK343 (1.67, 3.33, 10, 20 and 40 [\u0026micro;M]) dissolved in culture medium.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIn vivo\u003c/b\u003e \u003cb\u003exenograft experiment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFive-week-old female nude BALB/c mice (18\u0026ndash;20 g) were purchased from Beijing Huafukang Bioscience (Beijing, China) and housed under specific pathogen-free conditions. For subcutaneous tumor xenografts, 1\u0026times;10\u003csup\u003e7\u003c/sup\u003e HCT116 NRF1-WT and NRF1-KO cells were suspended in 100 \u0026micro;L of phosphate-buffered saline (PBS) and then inoculated subcutaneously into the left/right posterior dorsal region of each mouse (n\u0026thinsp;=\u0026thinsp;9). The mice were euthanized when the tumors reached approximately 1 cm in diameter.\u003c/p\u003e\u003cp\u003eFor drug treatment, HCT116 NRF1-wild-type (WT) and NRF1-KO cells (2.5 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e) were suspended in 100 \u0026micro;L of PBS and then inoculated subcutaneously into the posterior dorsal region of each mouse. When the tumors reached a volume of approximately 50 mm\u003csup\u003e3\u003c/sup\u003e (approximately 5 mm in diameter), the mice were randomly divided into groups (NRF1-WT: n\u0026thinsp;=\u0026thinsp;4/group; NRF1-KO: n\u0026thinsp;=\u0026thinsp;7/group) to receive DMSO (as a solvent control) or GSK343 treatment (dissolved in a solution of 2% DMSO, 40% PEG300 and 5% Tween 80). GSK343 was administered at a dose of 10 mg/kg via intraperitoneal (ip) injection five times a week for 42 days. The mice were weighed, and the tumor diameter was measured with a caliper every 2 days. The tumor volume was calculated via an empirical formula (tumor volume\u0026thinsp;=\u0026thinsp;0.5 \u0026times; length \u0026times; width\u003csup\u003e2\u003c/sup\u003e). The subcutaneous tumors were surgically excised, photographed, sectioned, and fixed in 10% formalin. This study was approved by the institute animal ethics committee.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImmunohistochemical (IHC) staining\u003c/b\u003e\u003c/p\u003e\u003cp\u003eXenograft-derived tumor IHC staining was performed on formaldehyde-fixed paraffin-embedded (FFPE) tissue blocks. Immunohistochemistry was carried out with an anti-Ki67 (Beijing Zhongshan Golden Bridge Biotech, China) antibody. Briefly, tissue slides were dewaxed in xylene, rehydrated, subjected to antigen retrieval in 10 mM citrate buffer (pH 6.0) at 98\u0026deg;C for 3 min and treated with 3% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e for 10 min to block endogenous peroxidase. The slides were then blocked with 5% BSA in PBS for 30 min and incubated with primary antibody overnight at 4\u0026deg;C. The PBS-washed sections were further treated with Histostain\u0026trade;-Plus and DAB Kits and counterstained with hematoxylin. The sections were dehydrated and stabilized with mounting medium, and images were taken with an optical microscope. Under 20\u0026times; magnification, the percentage of Ki67-positive cells relative to the total number of cells (Ki67-positive index) in six fields of view for each group was calculated.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDownload of publicly available RNA-seq datasets\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe mRNA levels of genes associated with \u003cem\u003eEZH2\u003c/em\u003e transcription were extracted from cDNA array datasets for 921 cell lines from the Cancer Cell Line Encyclopedia (CCLE, Broad, 2019) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and for 991 samples from the pancancer analysis of whole genomes [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These datasets were downloaded from the cBioPortal database [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The coexpression analysis results were downloaded from the GEPIA2 website (gepia2.cancer-pku.cn) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The drug sensitivity data for the cancer cell lines were obtained from the Genomics of Drug Sensitivity in Cancer (GDSC2) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and the Cancer Therapeutics Response Portal (CTRP) v2 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analysis was carried out using SPSS 22.0 software (SPSS Inc., Chicago, IL, USA). Data are presented as the mean \u0026plusmn; SD or as the median or the median (25\u0026ndash;75 percentiles). Statistical analysis methods included Student's t test, one-way analysis of variance (ANOVA), and two-way ANOVA. All tests are two-sides. A \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cb\u003eNRF1 upregulates\u003c/b\u003e \u003cb\u003eEZH2\u003c/b\u003e \u003cb\u003etranscription\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe basal levels of the NRF1 protein and mRNA in colon RKO and SW480 cancer cells were lower than those in HCT116 and LoVo cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Thus, these cell lines were used in NRF1 gain- and loss-of-function experiments. The level of \u003cem\u003eEZH2\u003c/em\u003e mRNA was significantly elevated in RKO and SW480 cells with transient \u003cem\u003eNRF1\u003c/em\u003e overexpression (NRF1-OE) for 48 hrs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Conversely, the level of \u003cem\u003eEZH2\u003c/em\u003e mRNA was significantly reduced by transient siRNA-mediated knockdown of \u003cem\u003eNRF1\u003c/em\u003e (siNRF1) in HCT116 and LoVo cells for 48 hrs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). In addition, siNRF1 decreased both the protein and mRNA levels of the \u003cem\u003eEZH2\u003c/em\u003e gene in lung A549 and H1299 cancer cells but not in liver HepG2 cancer cells (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWhen the \u003cem\u003eNRF1\u003c/em\u003e exon sequence encoding the DNA binding domain was knocked out via CRISPR-Cas9 (NRF1-KO), both the mRNA and protein levels of the \u003cem\u003eEZH2\u003c/em\u003e gene were markedly reduced in NRF1-KO HCT116 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). In the rescue experiment, NRF1-OE mostly mitigated the effect of NRF1-KO on \u003cem\u003eEZH2\u003c/em\u003e expression.\u003c/p\u003e\u003cp\u003eTo confirm the effect of NRF1 on \u003cem\u003eEZH2\u003c/em\u003e expression, we further performed confocal immunofluorescence microscopy analyses. We initially mixed wild-type (WT) and NRF1-KO cells, seeded them on the same slide as the NRF1 positive and negative controls, and observed an obvious decrease in EZH2 abundance in NRF1-KO cells (GFP-labeled) relative to that in NRF1-WT cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). Then, we performed the rescue experiment and found that the EZH2 level in NRF1-KO cells with FLAG-NRF1 expression was significantly greater than that in cells without FLAG-NRF1 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). These results strongly reveal that NRF1 upregulates \u003cem\u003eEZH2\u003c/em\u003e transcription in cancer cells.\u003c/p\u003e\u003cp\u003e\u003cb\u003eNRF1 binds the\u003c/b\u003e \u003cb\u003eEZH2\u003c/b\u003e \u003cb\u003epromoter as a transcription factor\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo determine whether NRF1 directly upregulates \u003cem\u003eEZH2\u003c/em\u003e expression as a transcription factor, we searched the online promoter analysis tool Jaspar [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] and identified a putative NRF1-binding site (-118 to -129 nt) in the proximal promoter flanking the transcription start site (TSS) of the \u003cem\u003eEZH2\u003c/em\u003e gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Chromatin immunoprecipitation (ChIP)-PCR analysis revealed that \u003cem\u003eEZH2\u003c/em\u003e promoter DNA was enriched by NRF1 in HCT116 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). To evaluate the importance of the NRF1 binding site in regulating \u003cem\u003eEZH2\u003c/em\u003e transcription by NRF1, we constructed three \u003cem\u003eEZH2\u003c/em\u003e promoter reporter vectors, including the full-length \u003cem\u003eEZH2\u003c/em\u003e promoter (EZH2-pro1: -28 to -704 nt) and its truncated mutants with the 184 nt deletion of the distal fragment (EZH2-pro2: -28 to -520 nt) or the 172 nt deletion of the proximal fragment (EZH2-pro3: -200 to -714 nt) not containing the NRF1 binding site (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Luciferase reporter experiments revealed that the promoter activity of EZH2-pro3 was significantly lower than that of EZH2-pro1 and EZH2-pro2 in both NRF1-OE HCT116 and HEK293T cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The baseline promoter activity of EZH2-pro3 was also lower than that of EZH2-pro1 and EZH2-pro2 in HCT116 cells. These findings reveal that the NRF1 binding site may play an important role in increasing \u003cem\u003eEZH2\u003c/em\u003e transcription via NRF1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThen, we constructed an NRF1 mutant (Δ177\u0026ndash;284) that does not contain the DNA-binding domain. Whereas wild-type NRF1 overexpression greatly increased \u003cem\u003eEZH2\u003c/em\u003e promoter activity, NRF1 mutation did not affect \u003cem\u003eEZH2\u003c/em\u003e promoter activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eD), suggesting that the DNA-binding domain is essential for NRF1 to upregulate \u003cem\u003eEZH2\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eWe further used EMSA to validate the direct binding between the NRF1 protein and the \u003cem\u003eEZH2\u003c/em\u003e promoter. EMSAs revealed that the biotin-labeled \u003cem\u003eEZH2\u003c/em\u003e-bio1 probe (containing the NRF1-binding site) bound the purified GST-NRF1 protein and that the interaction of the NRF1 protein with the \u003cem\u003eEZH2\u003c/em\u003e promoter DNA was blocked by the addition of the \"cold\" \u003cem\u003eEZH2\u003c/em\u003e-bio1 probe without biotin labeling. No interaction was detected between the GST-NRF1 protein and the EZH2-bio2 or EZH2-bio3 control probes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In addition, the \"cold\" EZH2-mut probe (not containing the NRF1-binding site) did not block the interaction between NRF1 and the \u003cem\u003eEZH2-\u003c/em\u003ebio1 probe (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). These results suggest that NRF1 directly activates \u003cem\u003eEZH2\u003c/em\u003e transcription as a transcription factor.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNRF1 is a dominant cause of cancer-specific\u003c/b\u003e \u003cb\u003eEZH2\u003c/b\u003e \u003cb\u003eoverexpression\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThere are two histone H3-lysine 27 methyltransferase genes (\u003cem\u003eEZH2\u003c/em\u003e and \u003cem\u003eEZH1\u003c/em\u003e) in the human genome with distinct functions. For example, \u003cem\u003eEZH1\u003c/em\u003e is more abundant in nonproliferative adult organs, whereas \u003cem\u003eEZH2\u003c/em\u003e expression is tightly associated with proliferation [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. \u003cem\u003eEZH2\u003c/em\u003e is frequently upregulated in many cancers (Figure S2A), whereas \u003cem\u003eEZH1\u003c/em\u003e is always downregulated in these cancers (Figure S2B). Unexpectedly, no inverse correlation between the levels of \u003cem\u003eEZH2\u003c/em\u003e and \u003cem\u003eEZH1\u003c/em\u003e transcripts was observed in either cancer or normal tissues from more than ten thousand patients in the TCGA or GTEx (Figure S2C), excluding the possibility that \u003cem\u003eEZH1\u003c/em\u003e downregulation leads to \u003cem\u003eEZH2\u003c/em\u003e upregulation in cancers.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the importance of NRF1 to \u003cem\u003eEZH2\u003c/em\u003e overexpression in cancer cells, we compared the levels of \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e expression in colon carcinoma and paired surgical margin tissue samples from 15 patients. The results of qRT‒PCR revealed that both these two genes were significantly upregulated in colon carcinoma tissues relative to the surgical margin tissues and that the \u003cem\u003eNRF1\u003c/em\u003e mRNA levels were significantly correlated with the \u003cem\u003eEZH2\u003c/em\u003e mRNA levels (the correlation coefficient (R, Pearson)\u0026thinsp;=\u0026thinsp;0.90, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, left).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe further performed bioinformatics analyses. We found that the correlation coefficient (R, Spearman) between the levels of \u003cem\u003eEZH2\u003c/em\u003e and \u003cem\u003eNRF1\u003c/em\u003e transcripts was much greater in cancer cell lines (R\u0026thinsp;=\u0026thinsp;0.70) than in cancer tissues (containing noncancer stroma cells; R\u0026thinsp;=\u0026thinsp;0.48) than in normal tissues (R\u0026thinsp;=\u0026thinsp;0.29 or 0.28), whereas the correlation coefficient between \u003cem\u003eEZH1\u003c/em\u003e and \u003cem\u003eNRF1\u003c/em\u003e transcript levels was much lower in cancer cell lines (R\u0026thinsp;=\u0026thinsp;0.29) than in cancer tissues (R\u0026thinsp;=\u0026thinsp;0.59) than in normal tissues (R\u0026thinsp;=\u0026thinsp;0.73 or 0.74) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). In addition, \u003cem\u003eEZH2\u003c/em\u003e transcript levels in cancer cell lines or tissues were consistently and positively associated with the number of copies of the \u003cem\u003eNRF1\u003c/em\u003e gene (Figure S3A and S3B). EZH2 protein levels in cancer cell lines were also significantly associated with NRF1 protein levels (Figure S3D; R\u0026thinsp;=\u0026thinsp;0.47). These data suggest that NRF1 may upregulate \u003cem\u003eEZH2\u003c/em\u003e in a cancer-specific fashion.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAlthough somatic copy number amplification caused upregulation of the \u003cem\u003eEZH2\u003c/em\u003e gene (Figure S3C), the frequency of copy number amplification of \u003cem\u003eEZH2\u003c/em\u003e across cancers was very low (0.79%; 78 of 9889 samples). A positive correlation between the levels of \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e transcripts was consistently observed in various pancancer subgroups with and without copy number alterations in the \u003cem\u003eEZH2\u003c/em\u003e gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), suggesting that NRF1 has a dominant effect on \u003cem\u003eEZH2\u003c/em\u003e overexpression in cancer cells. Furthermore, \u003cem\u003eNRF1\u003c/em\u003e is among the top genes whose expression is correlated mostly with \u003cem\u003eEZH2\u003c/em\u003e expression and vice versa according to transcriptome datasets in the CCLE project (Figure S4A and S4B). In fact, NRF1 is the only transcription factor among these top 20 \u003cem\u003eEZH2\u003c/em\u003e-cotranscribing genes. These phenomena suggest that NRF1 may be a master transcription factor for the \u003cem\u003eEZH2\u003c/em\u003e gene.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo investigate the role of NRF1 in colon cancer, we detected the effect of NRF1-KO on the proliferation of HCT116 cells \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e. The results of long-term dynamic monitoring of live cells revealed that compared with NRF1-WT, NRF1-KO significantly inhibited cell proliferation (Figure S5A). Furthermore, we established a tumor xenograft mouse model by subcutaneously implanting NRF1-WT and NRF1-KO HCT116 cells into nude mice. The results revealed that NRF1-KO cell-derived xenografts were observed in only one of these mice (1/9), whereas NRF1-WT cell-derived xenografts were observed in all nine mice (9/9) (Figure S5B, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). These results suggest that NRF1 promotes tumor growth.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNRF1 increases the sensitivity of cancer cells to EZH2 inhibitors\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGSK343 is an EZH2i. By analyzing the GDSC2 datasets [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and Cancer Cell Line Encyclopedia (CCLE) datasets [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], we found that among the transcription factor ChIP-seq clusters from ENCODE with factorbook motifs (Figure S4C) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], information on both the area under curve (AUC) of GSK343 and the mRNA levels was available for 71 transcription factors that can bind the \u003cem\u003eEZH2\u003c/em\u003e promoter in human cancer cell lines (n\u0026thinsp;=\u0026thinsp;845) and that the correlation coefficient between the levels of the \u003cem\u003eNRF1\u003c/em\u003e transcript and the AUC of GSK343 was among the top three (Figure S6A). A similar relationship was also observed between the sensitivity of cancer cell lines (n\u0026thinsp;=\u0026thinsp;750) to BRD-K62801835, another EZH2i, by analyzing the CTRPv2 datasets (Figure S6B) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn addition, the levels of both \u003cem\u003eEZH2\u003c/em\u003e and \u003cem\u003eNRF1\u003c/em\u003e transcripts were inversely correlated with the half maximal inhibitory concentration (IC50) of GSK343 (R=-0.267 and \u0026minus;\u0026thinsp;0.320, respectively) (Figure S7A). When these cell lines were subclassified as \u003cem\u003eNRF1\u003c/em\u003e or \u003cem\u003eEZH2\u003c/em\u003e expression-high or -low according to the median mRNA level, the GSK343-IC50 of the \u003cem\u003eNRF1\u003c/em\u003e or \u003cem\u003eEZH2\u003c/em\u003e expression-high cancer cell lines was significantly lower than that of the \u003cem\u003eNRF1\u003c/em\u003e or \u003cem\u003eEZH2\u003c/em\u003e expression-low cancer cell lines (Figure S7B). Notably, the GSK343-IC50 of cell lines with high \u003cem\u003eNRF1\u003c/em\u003e expression was significantly lower than that of cells with low \u003cem\u003eNRF1\u003c/em\u003e expression among the cell lines with high \u003cem\u003eEZH2\u003c/em\u003e expression, whereas no significant difference in the GSK343-IC50 was detected between \u003cem\u003eNRF1\u003c/em\u003e-high cell lines and \u003cem\u003eNRF1\u003c/em\u003e-low cell lines among the cell lines with low \u003cem\u003eEZH2\u003c/em\u003e expression (Figure S7C). These results suggest that NRF1 may affect the sensitivity of cancer cells to GSK343 through the upregulation of \u003cem\u003eEZH2\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe further found that the GSK343-IC50 was increased by siNRF1 in both HCT116 cells (9.8 to 11.6 or 12.2 [\u0026micro;M]) and LoVo cells (5.1 to 7.0 or 6.8) (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). We also found that the GSK343-IC50 was increased by NRF1-KO in HCT116 cells (8.9 to 14.5). NRF1-OE clearly mitigated the effect of NRF1-KO (14.5 to 10.8) on the GSK343-IC50 in the rescue experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Similar effects of changes in \u003cem\u003eNRF1\u003c/em\u003e expression on the sensitivity of another EZH2i, tazemetostat, were also detected (Figure S8).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo evaluate whether NRF1 affects the sensitivity of cancer cells to EZH2is through the upregulation of \u003cem\u003eEZH2\u003c/em\u003e, we knocked out the \u003cem\u003eEZH2\u003c/em\u003e gene (EZH2-KO) in H460 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e6\u003c/span\u003eA) and used these cells to determine whether EZH2-KO cancels the effects of NRF1 on the sensitivity of cancer cells to EZH2is. EZH2-KO alone weakly increased the GSK343-IC50 (5.2 to 5.9 or 9.2 to 10.0). While NRF1-OE or siNRF1 decreased or increased the GSK343-IC50 only in EZH2-WT cells, such effects were not detected in EZH2-KO cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e6\u003c/span\u003eB and \u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), demonstrating that the effects of NRF1 expression changes on the GSK343-IC50 were dependent on the effect of NRF1 on \u003cem\u003eEZH2\u003c/em\u003e transcription.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo confirm the impact of NRF1 on the sensitivity of cancer cells to EZH2i \u003cem\u003ein vivo\u003c/em\u003e, we established xenograft mouse models by subcutaneously implanting NRF1-WT and NRF1-KO HCT116 cells into nude mice. When the tumors became palpable (approximately 50 mm\u003csup\u003e3\u003c/sup\u003e), the mice were treated with DMSO (as a solvent control) or GSK343 at a dose of 10 mg/kg. After 42 days of GSK343 treatment, the tumors in the control group reached the predetermined endpoint. Strikingly, GSK343 treatment was much more effective than DMSO treatment for NRF1-WT tumors, whereas there were no significant differences in the growth of NRF1-KO tumors between the GSK343 group and the DMSO group (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). The growth of NRF1-WT tumors was greater than that of NRF1-KO tumors in the mice treated with DMSO. This difference was not observed in the mice treated with GSK343. Moreover, the Ki67 staining results were consistent with the volume of the tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). All the mice exhibited a decrease in body weight, particularly those in the NRF1-WT group (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). Taken together, these \u003cem\u003ein vivo\u003c/em\u003e results confirmed that NRF1 increased the sensitivity of cancer cells to EZH2i. \u003cem\u003eNRF1\u003c/em\u003e loss abolished the effect of EZH2i treatment on the growth of tumors.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSIONS","content":"\u003cp\u003eEZH2 is a cancer driver and therapeutic target that is consistently upregulated in many cancers. How EZH2 is upregulated in cancer cells and why most cancer patients cannot benefit from EZH2i treatment are not clear [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. NRF1 is a typical transcription factor [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In this study, via bioinformatics analyses and systemic experiments, we found that NRF1 is a master transcription factor of the \u003cem\u003eEZH2\u003c/em\u003e gene and that \u003cem\u003eNRF1\u003c/em\u003e upregulation is a determinant of \u003cem\u003eEZH2\u003c/em\u003e overexpression in human cancers. Most importantly, our findings demonstrate that active \u003cem\u003eNRF1\u003c/em\u003e expression significantly increases the sensitivity of colon cancer cells to EZH2i in an EZH2-dependent manner and that NRF1 loss disrupts the anticancer effect of EZH2i treatment.\u003c/p\u003e\u003cp\u003eEZH2 is the key catalytic subunit of PRC2, and its overexpression drives cancer development via the H3K27me3 and nonhistone protein methylation pathways [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. There are numerous reports on target genes of the EZH2 protein and its posttranslational modifications, including phosphorylation, acetylation, ubiquitination, GlcNAcylation, and SUMOylation [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Somatic copy number amplification of the \u003cem\u003eEZH2\u003c/em\u003e gene may partially account for \u003cem\u003eEZH2\u003c/em\u003e overexpression in a small proportion of human cancers because the frequency of \u003cem\u003eEZH2\u003c/em\u003e amplification is less than 1% in cancer samples in the TCGA project.\u003c/p\u003e\u003cp\u003eEZH2 is reportedly regulated by several transcription factors. For example, the transcription factors BRD4 and E2Fs induce \u003cem\u003eEZH2\u003c/em\u003e transcriptional activation in bladder tumors [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. C-MYC promotes \u003cem\u003eEZH2\u003c/em\u003e overexpression in leukemia and prostate cancers [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. STAT3 upregulates \u003cem\u003eEZH2\u003c/em\u003e transcriptional activation and is associated with poor prognosis in patients with gastric cancer [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. However, the determinants and exact mechanisms underlying \u003cem\u003eEZH2\u003c/em\u003e overexpression in human cancers are not clear. Both the \u003cem\u003eEZH2\u003c/em\u003e and \u003cem\u003eNRF1\u003c/em\u003e genes are overexpressed in a variety of cancers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], and we speculate that NRF1 may play an important role in this process. For this purpose, we analyzed RNA-seq datasets from the CCLE and TCGA databases and found that the transcription levels of \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e were mostly correlated with each other in cancers. Notably, the correlation between \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e transcription gradually decreased from cancer cell lines to cancer tissues, noncancerous tissues from cancer patients, and normal human tissues, suggesting a tumor-specific effect of NRF1 to \u003cem\u003eEZH2\u003c/em\u003e overexpression. In contrast, the transcriptional correlation between \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH1\u003c/em\u003e (normally expressed in nonproliferative adult cells) gradually increased from cancer cells to normal cells. Our bioinformatics and experimental findings indicate that NRF1 is a master regulator of \u003cem\u003eEZH2\u003c/em\u003e and that its overexpression is the determinant of \u003cem\u003eEZH2\u003c/em\u003e overexpression in human cancers.\u003c/p\u003e\u003cp\u003eAs an epigenetic silencer, EZH2 plays essential roles in multiple biological processes. \u003cem\u003eEZH2\u003c/em\u003e overexpression is common in human cancers and is associated with aggressiveness, poor prognosis, and recurrence as a cancer driver [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Researchers have synthesized various small EZH2i chemicals, some of which have entered clinical trials or been approved for clinical treatment [\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. For example, CPI-1205 [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], GSK343 [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], GSK126 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and SHR2554 [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] are in clinical trials. Tazemetostat and valemetostat have been marketed for the treatment of rare adult sarcomas in the USA [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and T-cell leukemia/lymphoma in Japan [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Unfortunately, only a limited proportion of cancer patients benefit from treatment with EZH2i. Thus, predictors of the sensitivity of cancer patients to treatment with EZH2i are urgently needed. In this study, we analyzed the correlation between the levels of \u003cem\u003eNRF1\u003c/em\u003e and/or \u003cem\u003eEZH2\u003c/em\u003e transcripts and the sensitivity of cancer cell lines to GSK343 in the GDSC2 datasets. We found that the expression levels of both the \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e genes were inversely correlated with the IC50 of GSK343, and the cells with high \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e coexpression were more sensitive to GSK343 than were the cells with high individual \u003cem\u003eNRF1\u003c/em\u003e or \u003cem\u003eEZH2\u003c/em\u003e expression or low \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e coexpression. In addition, the correlation coefficient of \u003cem\u003eNRF1\u003c/em\u003e mRNA with the AUC of GSK343 is the third highest among 71 transcription factor candidates for \u003cem\u003eEZH2\u003c/em\u003e, according to the public ENCODE and GDSC2 data [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Knockdown or knockout of \u003cem\u003eNRF1\u003c/em\u003e decreased the sensitivity of cancer cells to GSK343 and tazemetostat in an EZH2-dependent manner. Similar phenomena was also observed for another EZH2i BRD-K62801835, according to the CTRCv2 data [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These results suggest that \u003cem\u003eNRF1\u003c/em\u003e overexpression increases the sensitivity of \u003cem\u003eEZH2-\u003c/em\u003eexpressing cells to EZH2is and may be a potential biomarker for predicting the therapeutic efficacy of EZH2is. Further clinical trials are warranted to study the feasibility of using high \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e coexpression as a combined biomarker for predicting the therapeutic effects of EZH2is. The causes of \u003cem\u003eNRF1\u003c/em\u003e overexpression in cancer cells and whether NRF1 itself is a therapeutic target are also worthy of study.\u003c/p\u003e\u003cp\u003eIn conclusion, we found that NRF1, as a transcription factor, predominantly upregulates the transcription of the \u003cem\u003eEZH2\u003c/em\u003e gene. \u003cem\u003eNRF1\u003c/em\u003e overexpression not only causes \u003cem\u003eEZH2\u003c/em\u003e overexpression in cancer cells but also increases the sensitivity of cancer cells to EZH2i. High \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e coexpression is a potential combined biomarker for predicting the therapeutic effects of EZH2is.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e: The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding: This work was supported by the Natural Science Foundation of China (#82073102) to DD, the Science Foundation of Peking University Cancer Hospital (PY202304) to QJ, and the Science Foundation of Peking University Cancer Hospital (PY202328) to L.Z.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCao R, Wang L, Wang H, Xia L, Erdjument-Bromage H, Tempst P, Jones RS, Zhang Y: Role of histone H3 lysine 27 methylation in Polycomb-group silencing. \u003cem\u003eScience\u003c/em\u003e 2002, 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30(7):1248\u0026ndash;1255.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NRF1, EZH2, EZH2 inhibitor, cancer, prediction of therapeutic sensitivity","lastPublishedDoi":"10.21203/rs.3.rs-7217912/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7217912/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEZH2 is an oncogene and therapeutic target. Only a small proportion of cancer patients benefit from treatment with EZH2 inhibitors (EZH2is). The mechanisms underlying EZH2 overexpression and EZH2i resistance are not clear. Here, we reported that the nuclear respiratory factor 1 gene (\u003cem\u003eNRF1\u003c/em\u003e) is the gene whose expression is most strongly correlated with that of the \u003cem\u003eEZH2\u003c/em\u003e gene in various cancer cell lines and that changes in \u003cem\u003eNRF1\u003c/em\u003e expression consistently cause changes in \u003cem\u003eEZH2\u003c/em\u003e expression in cancer cells. Mechanistically, as a transcription factor, NRF1 directly binds to the NRF1-binding sequence within the \u003cem\u003eEZH2\u003c/em\u003e promoter and increases \u003cem\u003eEZH2\u003c/em\u003e promoter activity. Deletion of the DNA-binding motif within the NRF1 or NRF1-binding sequence within the \u003cem\u003eEZH2\u003c/em\u003e promoter abolishes the effects of NRF1 on \u003cem\u003eEZH2\u003c/em\u003e expression. Notably, we further found that the status of NRF1 expression affected the sensitivity of human cancer cells to EZH2is, including GSK343 and tazemetostat. The sensitivity of cancer cells actively expressing both \u003cem\u003eNRF1\u003c/em\u003e and \u003cem\u003eEZH2\u003c/em\u003e to EZH2i is significantly greater than that of cancer cells actively expressing individual \u003cem\u003eEZH2\u003c/em\u003e or \u003cem\u003eNRF1\u003c/em\u003e alone and much greater than that of cancer cells expressing low levels of \u003cem\u003eEZH2\u003c/em\u003e and \u003cem\u003eNRF1\u003c/em\u003e. The effect of NRF1 on the sensitivity of cancer cells to EZH2i is EZH2 dependent. In conclusion, our findings reveal that NRF1 is a dominant cause of EZH2 overexpression in human cancers and that NRF1 overexpression increases the sensitivity of cancer cells to EZH2i. Active NRF1 and EZH2 expression may be useful combined predictors for the treatment of cancers with EZH2i.\u003c/p\u003e","manuscriptTitle":"NRF1 Predominantly Causes EZH2 Overexpression in Cancer Cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-06 14:25:18","doi":"10.21203/rs.3.rs-7217912/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-09-29T14:30:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-09-25T07:56:23+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-09-22T11:05:12+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-09-12T11:07:13+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-09-10T02:39:44+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-09-10T02:34:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-01T09:36:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-01T00:30:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Death \u0026 Disease","date":"2025-08-01T00:30:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c62f0d27-69af-4afd-928b-41e0666d3f4f","owner":[],"postedDate":"October 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55113567,"name":"Health sciences/Diseases/Cancer/Cancer therapy/Targeted therapies"},{"id":55113568,"name":"Health sciences/Medical research/Translational research"},{"id":55113569,"name":"Biological sciences/Molecular biology/Transcription/Transcriptional regulatory elements"}],"tags":[],"updatedAt":"2026-05-07T09:13:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-06 14:25:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7217912","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7217912","identity":"rs-7217912","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}