Abstract Sorafenib, a tyrosine kinase inhibitor, has an important antitumor effect as a ferroptosis inducer in multiple cancers, including gastric cancer (GC). However, the status of sorafenib as a ferroptosis inducer has recently been questioned. There is very limited information about the relationship between ferroptosis and ATF2, and the role of ATF2 in sorafenib-induced ferroptosis has not been studied. In this study, we investigated the role and underlying molecular mechanisms of ATF2 in sorafenib-induced ferroptosis in GC. We found that ATF2 was significantly upregulated in GC tissues and predicted a poor clinical prognosis. Silencing ATF2 significantly inhibited the malignant phenotype of GC cells. In addition, we observed that ATF2 was activated during sorafenib-induced ferroptosis in GC cells. ATF2 knockdown promoted sorafenib-induced ferroptosis, while ATF2 overexpression showed the opposite results in GC cells. Using ChIP-Seq and RNA-Seq, we identified HSPH1 as a target of ATF2 and further validated it by ChIP‒qPCR analysis. HSPH1 can interact with SLC7A11 (cystine/glutamate transporter) and increase its protein stability. Importantly, knockdown of HSPH1 partly reversed the effects caused by ATF2 overexpression on sorafenib-induced ferroptosis in GC cells. In addition, the results from the tumor xenograft model showed that ATF2 knockdown can effectively enhance sorafenib sensitivity in vivo. Collectively, our study reveals a novel mechanism by which sorafenib induces ferroptosis in GC. Keywords: Gastric cancer, Sorafenib, ATF2, HSPH1, Ferroptosis 1. Introduction Gastric cancer (GC) is one of the most commonly diagnosed tumors and ranks as the fourth leading cause of cancer-related deaths worldwide [[37]1]. Patients in China account for approximately half of all cases worldwide, and most patients are already at an advanced stage at the time of initial diagnosis [[38]2]. The prognosis of GC patients remains poor despite great advances in treatment over the past decades, including surgery, chemotherapy, radiation, immunotherapy and a combined approach [[39]3]. Therefore, it is urgent to identify effective therapeutic strategies and targets for the treatment of GC patients. Ferroptosis, a novel form of programmed cell death, is characterized by lipid peroxidation products accumulating in a cellular-iron dependent manner [[40]4]. Inhibition of cystine/glutamate transporter (SCL7A11 or xCT, also known as system Xc-) and glutathione peroxidase 4 (GPX4) are the most common methods to induce ferroptosis [[41]5]. To date, ferroptosis has been shown to be effective in killing various cancer cells, including GC. Sorafenib restricts cystine input by inhibiting system Xc-, causing endoplasmic reticulum stress, glutathione depletion and iron-dependent accumulation of lipid reactive oxygen species (ROS) and finally inducing ferroptosis [[42][6], [43][7], [44][8]]. Although sorafenib has not been used clinically for treatment of GC, its encouraging anticancer effect in GC has been reported by several studies [[45][9], [46][10], [47][11]]. Notably, considering the adverse side effects of sorafenib, combination therapy may have better clinical prospects to achieve a low dose with high efficacy. In addition, a recent study pointed out that sorafenib does not trigger ferroptosis in all tumor cell lines and questioned its adequacy as a ferroptosis inducer [[48]12]. Thus, whether sorafenib can actually induce ferroptosis in GC cells and the underlying molecular mechanism remain largely unknown. Activation transcription factor 2 (ATF2), a member of the ATF/CREB family of transcription factors (TFs), has been implicated in a broad spectrum of cancer-related biological functions, such as cell proliferation, apoptosis and DNA repair [[49]13,[50]14]. Growing evidence indicates that ATF2 acts as an oncogene or a tumor suppressor in different cancer types depending on its expression level and subcellular localization [[51]15]. Generally, in response to many forms of cellular stress, especially oxidative stress, ATF2 is phosphorylated by multiple upstream kinases, translocates to the nucleus and increases transcriptional activity [[52]16]. Although the oncogenic role of ATF2 in GC has been reported in several studies [[53][17], [54][18], [55][19]], there is still a lack of experimental evidence in vitro and in vivo, especially its relationship with clinicopathological parameters and prognosis. In this study, we confirmed that sorafenib can induce ferroptosis in GC cells, and observed an accompanying increase in the phosphorylation level and transcriptional activity of ATF2. We found increased ATF2 expression in GC and that it is associated with a malignant phenotype and poor prognosis. Inhibition of ATF2 expression in vitro and in vivo increased sorafenib-induced ferroptosis in GC. Mechanistically, ATF2 protects GC cells from sorafenib-mediated ferroptosis by inhibiting SLC7A11 protein degradation through the promotion of the expression of heat shock protein-110 (HSPH1, also called HSP105 or HSP110). Here, we demonstrate that promoting sorafenib-induced ferroptosis may be a promising new strategy for GC treatment. 2. Materials and methods 2.1. Patient samples and follow-up In the present study, a total of 107 formalin-fixed paraffin-embedded GC tissues and 22 randomly selected corresponding adjacent normal tissues following radical gastrectomy without preoperative chemotherapy or radiotherapy were obtained from the First Affiliated Hospital of Anhui Medical University between October 2012 and December 2013 for tissue microarray (TMA) construction. The follow-up time ranged from 8 months to 71 months. The clinical and pathological data are summarized in [56]Table 1, and the GC patients were staged according to the 8th edition AJCC staging system. Additionally, 12 fresh primary cancer and paired adjacent normal tissue specimens were also collected. The Ethics Committee of Anhui Medical University approved the study, and written informed consent was obtained from all the patients enrolled in this study. Table 1. Correlation of ATF2 expression with clinicopathologic parameters in GC patients. Parameters Cases ATF2 expression __________________________________________________________________ χ^2 P-value High Low Gender 1.383 0.240 Male 71 41 30 Female 36 25 11 Age (years) 0.382 0.537 <61 43 25 18 ≥61 64 41 23 Tumor location 0.570 0.450 Upper 36 24 12 Middle + lower 71 42 29 Tumor size (cm) 0.915 0.339 <6 48 32 16 ≥6 59 34 25 Depth of invasion 1.669 0.196 T1 + T2 29 15 14 T3 + T4 78 51 27 Lymph node metastasis 8.969 0.003[57]^a Absent 23 8 15 Present 84 58 26 Differentiation 1.811 0.178 Well + moderate 41 22 19 Poor + undifferentiated 66 44 22 TNM stage 4.509 0.034[58]^a I + Ⅱ 34 16 18 Ⅲ + IV 73 50 23 [59]Open in a new tab ^a Statistically significant (P < 0.05). 2.2. Cell culture, lentiviral infection and siRNA transfection The normal gastric epithelial cell line GES-1 and the GC cell lines SGC7901, HGC27, AGS, MGC803 and MKN45 were obtained from GeneChem (Shanghai, China). The cells were cultured in RPMI 1640 medium (Corning, NY, USA) supplemented with 10% fetal bovine serum (FBS, Clark Bioscience, Richmond, VA, USA) and 1% penicillin–streptomycin (HyClone, Logan, UT, USA) in a humidified incubator at 37 °C containing 5% CO[2]. The ATF2-overexpressing lentiviral GV341 vector (Ubi-MCS-3FLAG-SV40-puromycin), ATF2 small hairpin RNA (shRNA) lentiviral GV112 vector (hU6-MCS-CMV-puromycin) and control lentiviral vector were constructed by GeneChem (Shanghai, China). Small interfering RNA (siRNA) against HSPH1 and control siRNA were purchased from Hippo Biotechnology (Huzhou, China). To generate stable ATF2 knockdown and overexpression cell lines, the cells were infected with lentivirus at an MOI of 10 and then selected with 2 μg/ml puromycin for 2 weeks. The established stable cell lines were maintained in 1 μg/ml puromycin for further experiments. For HSPH1 siRNA transfection, the cells were seeded at 50% confluency and transfected with siRNA duplexes at a final concentration of 30 nM for 48 h using LipoJet reagent (SignaGen, Rockville, MD, USA) according to the manufacturer's protocol. The shRNA and siRNA sequences are listed in [60]Table S1. 2.3. Western blot analysis Total proteins were extracted using mammalian protein extraction reagent (M-PER) (#78501, Thermo Scientific, USA) supplemented with protease and phosphatase inhibitor cocktails. Protein concentrations were determined using a BCA protein assay kit (A045-4, Jiancheng Bioengineering Institute, Nanjing, China). Equal amounts of protein samples were separated by SDS-polyacrylamide gel electrophoresis and then transferred onto PVDF membranes (Millipore, MA, USA). After blocking in 5% skim milk in TBST for 1 h at room temperature, the membranes were incubated with primary antibodies against ATF2 (1:1000, ab32160, Abcam, Cambridge, UK), p-ATF2 (1:1,000, sc-8398, Santa Cruz Biotechnology, TX, USA), SLC7A11 (1:1000, ab175186, Abcam, Cambridge, UK), HSPH1 (1:1000, ab109624, Abcam, Cambridge, UK), and GAPDH (1:2500, #5174, Cell Signaling Technology, MA, USA) overnight at 4 °C. Following incubation with the secondary antibody for 1 h at room temperature, the protein bands were visualized using enhanced chemiluminescence (Bridgen, Beijing, China) and imaged using a Tanon-5200 chemiluminescence detection system (Tanon Science, Shanghai, China). 2.4. Quantitative real-time polymerase chain reaction (qRT‒PCR) Total RNA was extracted from cells using TRIzol (Invitrogen, CA, USA), and then cDNA was synthesized with Hifair® III 1st Strand cDNA Synthesis SuperMix for qPCR (11141ES60, Yeasen Biotechnology, Shanghai, China). Subsequently, qPCR was performed using Hieff® qPCR SYBR Green Master Mix (11202ES03, Yeasen Biotechnology, Shanghai, China) on the Agilent Mx3000P qPCR Platform (Agilent, CA, USA). Relative gene expression was calculated using the 2^−ΔΔCt method, and GAPDH served as an internal control. All primers were synthesized by General Biosystems (Anhui, China) and are shown in [61]Table S2. 2.5. Immunohistochemical staining ATF2 protein expression was evaluated by immunohistochemistry (IHC) in a TMA as described previously [[62]20]. The TMA was incubated with anti-ATF2 (1:500 dilution) and then scored independently for staining area (0, no staining; 1, 0–25%; 2, 26%–50%; 3, 51%–75%; 4, 76%–100%) and staining intensity (0, negative; 1, weak; 2, moderate; 3, strong) by two clinical pathologists. The final score was the product of the staining area and the staining intensity. High expression was defined as a final score of ≥5, and low expression was defined as a final score of 0–4. 2.6. Cell growth curve For cell growth curve analysis, GC cells were plated onto 96-well plates at a density of 5 × 10^3 cells per well. At the indicated times, 10 μL of Cell Counting Kit-8 (CCK-8; 40203ES76, Yeasen Biotechnology, Shanghai, China) solution was added to each well, followed by incubation at 37 °C for 1 h. The relative optical density (OD) was measured at 450 nm using a microplate reader (Biotek, USA). 2.7. Half-maximal inhibitory concentration (IC50) assay GC cells were seeded at 1 × 10^4 cells per well in 96-well plates and treated with a range of concentrations of sorafenib (0–80 μM) for 24 h. Ten microliters of CCK-8 solution was added to each well and incubated for 1 h at 37 °C. The absorbance was measured at 450 nm using a microplate reader (Biotek, USA), and IC50 values were calculated using GraphPad Prism software 6.0 (GraphPad Software, Inc., San Diego, CA, USA). 2.8. Transwell migration and invasion assays Cell migration and invasion assays were performed using 24-well Transwell chambers with a pore size of 8 μm (Corning, USA). Briefly, 8 × 10^4 GC cells were seeded in the upper chamber with Matrigel (BD Biosciences, USA) for the invasion assay or without Matrigel for the migration assay. Then, 650 μl of culture medium containing 20% FBS was added to the lower chamber. After incubation for 24 h, the GC cells were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. Finally, the nonmigrating or noninvading cells were carefully removed with a wet cotton swab and then photographed under a Leica microscope (DMI1; Wetzlar, Germany). 2.9. Calcein-AM/PI staining Live/dead cell staining was performed using a calcein-AM/PI Double Staining Kit (C2015S, Beyotime, Shanghai, China) according to the protocol. After different treatments, the GC cells were washed with PBS and stained by a mixture of calcein-AM and PI solution for 30 min at 37 °C in the dark. Fluorescence signals were analyzed with a fluorescence microscope. Live cells appeared green due to calcein-AM staining, while dead cells appeared red after PI staining. 2.10. Intracellular reactive oxygen species (ROS) and lipid peroxidation detection Intracellular ROS levels were determined using DCFH–DA (D6883, Sigma, MO, USA). In brief, cultured GC cells in 6-well plates were incubated with 5 μM DCFH-DA in serum-free medium at 37 °C for 30 min in the dark. After washing three times with PBS, the cells were resuspended in 500 μL of PBS and then analyzed by flow cytometry (Beckman Coulter, CA, USA). For lipid peroxidation detection, GC cells were loaded with 1 ml of fresh medium containing 10 μM C11 BODIPY 581/591 (GC40165, GlpBio, CA, USA) for 30 min at 37 °C. Following two washes with PBS, the cells were resuspended in 500 μL of PBS containing 5% FBS for flow cytometry analysis. 2.11. MDA and glutathione (GSH) detection MDA is a final product of lipid peroxidation, which shows a positive correlation with ferroptosis [[63]21]. The MDA concentration in GC cells was measured by the thiobarbituric acid method using a cell MDA assay kit (A003-4, Jiancheng Bioengineering Institute, Nanjing, China). MDA was calculated based on cellular protein concentration and expressed as nmol of MDA per milligram of protein (nmol/mgprot). The lethal metabolic imbalance resulted from GSH depletion is a major feature of ferroptosis [[64]4]. For GSH detection, a Micro Reduced Glutathione Assay Kit (BC1175, Solarbio, Beijing, China) was used according to the manufacturer's instructions. The concentration of cellular GSH was determined from a GSH standard curve and normalized to the cell number. 2.12. Mitochondrial membrane potential (MMP) measurement The change in MMP was assessed using a JC-1 MMP Assay Kit (40706ES60, Yeasen Biotechnology, Shanghai, China). Briefly, after incubating with JC-1 staining work solution for 20 min at 37 °C, the GC cells were washed twice with JC-1 staining buffer and imaged using a fluorescence microscope. The red fluorescent aggregate indicates a healthy mitochondrion with normal membrane potential, whereas the green fluorescent monomer indicates loss of MMP. 2.13. Transmission electron microscopy (TEM) After treatment with sorafenib (HY-10201, MedChemExpress, NJ, USA), ferrostatin-1 (Fer-1, HY-100579, MedChemExpress, NJ, USA) or DMSO for 24 h, the cells were fixed in 4% paraformaldehyde (P0099, Beyotime, Shanghai, China) for 2 min. Following cell harvest by centrifugation, 2.5% glutaraldehyde (P1126; Solarbio, Beijing, China) was carefully added to the cell pellet along the tube wall. Finally, ultrathin sections were cut, and the morphological changes of mitochondria were observed under TEM (TECNA I20; Philips, Eindhoven, Netherlands). 2.14. RNA sequencing (RNA‐seq) analysis RNA‐seq was carried out by Seqhealth Technology Co., Ltd. (Wuhan, China). Total RNA was extracted from MGC803 cells with lentivirus-mediated knockdown of ATF2 (sh-ATF2) or the negative control (sh-Ctrl). After RNA quality evaluation and library preparation, the library products were further sequenced with the Illumina NovaSeq 6000 sequencing platform. Differentially expressed genes (DEGs) were screened using thresholds of | log2 (fold change) | > 1 and p-value <0.05. 2.15. Chromatin immunoprecipitation-sequencing (ChIP-seq) and ChIP‒qPCR The ChIP assay and high-throughput sequencing were conducted by Seqhealth Technology Co., Ltd. (Wuhan, China). Briefly, approximately 2 × 10^7 AGS cells stably overexpressing ATF2 were fixed in 1% formaldehyde for 10 min at room temperature, after which 125 mM glycine was added and left for 5 min to terminate the crosslinking reaction. After ChIP lysis buffer (5 mM PIPES, pH 8.0, 85 mM KCl, 0.5% NP-40, protease inhibitors) treatment, the nuclear pellet was collected by centrifugation at 2000×g for 5 min at 4 °C. The chromatin was sonicated to an average DNA fragment length of 200–500 bp and then incubated with ChIP-grade antibody against ATF2 (ab32160, Abcam, Cambridge, UK) at 4 °C overnight for chromatin immunoprecipitation. After DNA extraction with the phenol‒chloroform method, the purified products were sequenced on a NovaSeq 6000 sequencer (Illumina) with a PE150 model. The raw sequencing data were evaluated using FastQC and filtered by Trimmomatic. MACS2 (narrow peak mode) was used for peak calling with a p-value threshold of 0.01. In addition, de novo motif analysis of the ATF2 binding site was performed with HOMER software. For ChIP‒qPCR, immunoprecipitation was performed at 4 °C overnight with anti-ATF2 or normal rabbit IgG antibody. Then, qRT‒PCR was utilized to quantify the immunoprecipitated DNA, and the data were normalized to the input. The primers used for ChIP‒qPCR are listed in [65]Table S2. 2.16. Coimmunoprecipitation (co-IP) GC cells were lysed in ice‐cold M-PER buffer supplemented with protease and phosphatase inhibitor cocktails. After preclearing with 20 μl of protein A/G plus-agarose (sc-2003; Santa Cruz Biotechnology, USA) at 4 °C for 30 min, the cell lysates were incubated with anti‐HSPH1, anti‐SLC7A11, or IgG at 4 °C overnight on a gyratory shaker. Following incubation with 20 μl of protein A/G plus-agarose at 4 °C for 6 h, immunoprecipitated beads were washed with ice‐cold lysis buffer three times and boiled in 50 μL of 1 × SDS sample buffer for 8 min at 95 °C. Then, the immunoprecipitated protein complexes were analyzed by western blotting. To avoid the influence of the heavy chain, a specific secondary antibody against the mouse anti-rabbit IgG light chain (A25022, Abbkine Scientific, Wuhan, China) was used. 2.17. Protein stability assay To assess SLC7A11 protein stability, a cycloheximide (CHX) chase assay was performed. Cells were treated with 20 μg/ml CHX (S7418, Selleck Chemicals, TX, USA) for the indicated time periods (0, 2, 4, 6, and 8 h). Cell lysates were collected and analyzed by western blotting with GAPDH as a loading control. 2.18. Xenograft mouse model Animal studies were approved by the Ethics Committee for Animal Studies of Anhui Medical University. Four-week-old female BALB/c nude mice were purchased from SLAC Laboratory Animal Co., Ltd. (Shanghai, China) and maintained under special pathogen-free (SPF) conditions. For subsequent studies, the nude mice were randomly divided into four groups as follows: sh-Ctrl, sh-ATF2, sh-Ctrl + sorafenib and sh-ATF2 + sorafenib. Approximately 5 × 10^6 ATF2 knockdown or control MGC803 cells were subcutaneously injected into the axilla of nude mice. Beginning on Day 8, mice in the sorafenib treatment group received 10 mg/kg sorafenib by intraperitoneal injection every 2 days for 3 weeks. Tumor length (L) and width (W) were measured every 3 days, and tumor volume (V) was calculated as follows: (3.14 × L × W^2)/6. Finally, all the mice were sacrificed and dissected immediately to measure the tumor weights. Tumors were fixed in 4% paraformaldehyde and stained with ATF2 antibody (1:500) or 4-hydroxynonenal (4-HNE) antibody (1:100, ab48506, Abcam, Cambridge, UK) for IHC analysis. 2.19. Bioinformatic analysis We downloaded the gastric cancer mRNA data from The Cancer Genome Atlas (TCGA) ([66]https://tcga-data.nci.nih.gov/tcga/) and performed bioinformatic analysis using Sangerbox ([67]http://www.sangerbox.com/tool). The survival curve of GC patients with high and low ATF2 expression was generated using Kaplan‒Meier Plotter ([68]www.kmplot.com). The GeneMANIA ([69]http://genemania.org/) online database was used to predict potential interactions between ATF2 target genes and SLC7A11. 2.20. Statistical analysis The statistical analysis was performed using SPSS 22.0 (SPSS Inc., USA) and GraphPad Prism 7.0 (GraphPad Software Inc., USA). All data are shown as the mean ± standard deviation (SD) and were compared using a Student's t-test or one-way ANOVA. The relationship between ATF2 expression and pathological variables was analyzed using Pearson's chi-squared test. Survival analysis was performed by the Cox proportional hazards regression model and Kaplan‒Meier method with the log-rank test. P < 0.05 was considered significant (*P < 0.05; **P < 0.01; ***P < 0.001). 3. Results 3.1. ATF2 expression is upregulated in GC and predicts an unfavorable prognosis To investigate the expression pattern of ATF2 in GC, we first utilized the TCGA database. The results demonstrated that ATF2 mRNA expression was significantly higher in GC tissues than in normal tissues ([70]Fig. 1A). ATF2 expression was higher in GC cell lines (SGC7901, HGC27, AGS, MGC803 and MKN45) than in a nonmalignant cell line (GES-1; [71]Fig. 1B). In addition, we examined ATF2 protein expression in 12 pairs of fresh GC tissues and adjacent normal tissues, and found a similar result that ATF2 expression was increased in GC tissues ([72]Fig. 1C). Fig. 1. [73]Fig. 1 [74]Open in a new tab ATF2 is upregulated in GC and predicts a poor prognosis. (A) The expression of ATF2 was determined based on the TCGA databases. (B) Western blot was used to detect the protein level of ATF2 in the GES-1 and GC cell lines. (C) ATF2 expression was analyzed by Western blot in GC and adjacent normal tissues. (D) Representative ATF2 IHC staining images in GC tissue microarray. (E) The statistical analysis of ATF2 expression in GC and adjacent normal tissues. The final score was the product of the staining area and the staining intensity. High expression was defined as a final score of ≥5, and low expression was defined as a final score of 0–4. (F) Kaplan–Meier survival curve of GC patients with low and high ATF2 expression in our study. (G) Kaplan-Meier survival curve of ATF2 expression was obtained from the KM plotter database. Data are shown as the mean ± SD (n = 3). *P < 0.05, **P < 0.01, ***P < 0.001. Furthermore, we also evaluated ATF2 expression by IHC on a TMA containing 107 GC tissues and 22 adjacent normal tissues. Representative images with different ATF2 expression levels are shown in [75]Fig. 1D. Notably, high ATF2 protein expression was observed in 61.7% (66/107) of GC tissues, while 63.6% (14/22) of adjacent normal tissues exhibited low ATF2 expression ([76]Fig. 1E). To determine the clinical significance of ATF2 in GC, we analyzed the relationship between ATF2 expression and clinicopathological parameters. As shown in [77]Table 1, the results demonstrated that increased ATF2 expression was markedly correlated with lymph node metastasis (P = 0.003) and distant metastasis (P = 0.034). In addition, overall survival (OS) analysis demonstrated that GC patients with increased ATF2 expression had a shorter survival time than those with decreased ATF2 expression (log-rank P = 0.011, [78]Fig. 1F). Similarly, high ATF2 expression associated with poor outcome was also verified in a large cohort using the KM plotter database (log-rank P = 0.005, [79]Fig. 1G). Subsequently, Cox regression was performed for both univariate and multivariate processes, including sex, age, tumor location, tumor size, depth of invasion, lymph node metastasis, differentiation, TNM stage, and ATF2 expression. Univariate Cox regression analysis showed that lymph node metastasis (P = 0.005), TNM stage (P = 0.039) and ATF2 expression (P = 0.013) were significantly correlated with the OS of GC patients ([80]Table 2). Multivariate Cox regression analysis showed that lymph node metastasis (P = 0.034) and ATF2 expression (P = 0.045) were independent prognostic factors for the OS of GC patients ([81]Table 2). Collectively, these results indicate that ATF2 expression is upregulated in GC and represents a valuable predictive biomarker for OS. Table 2. Univariate and multivariate analysis of clinicopathological variables and ATF2 expression associated with overall survival. Parameters Univariate analysis __________________________________________________________________ Multivariate analysis __________________________________________________________________ HR (95% CI) P-value HR (95% CI) P-value Gender (male vs female) 0.910 (0.511–1.622) 0.750 Age (years) (<61 vs ≥ 61) 1.272 (0.732–2.212) 0.393 Tumor location (upper vs middle + lower) 1.153 (0.643–2.068) 0.634 Tumor size (cm) (<6 vs ≥ 6) 0.824 (0.482–1.408) 0.479 Depth of invasion (T1 + T2 vs T3 + T4) 1.578 (0.827–3.008) 0.166 Lymph node metastasis (absent vs present) 3.713 (1.474–9.353) 0.005[82]^a 3.254 (1.095–9.667) 0.034[83]^a Differentiation (well + moderate vs poor + undifferentiated) 1.648 (0.918–2.957) 0.094 TNM stage (I + Ⅱ vs Ⅲ + IV) 1.967 (1.034–3.739) 0.039[84]^a 1.026 (0.484–2.173) 0.946 ATF2 expression (low vs high) 2.122 (1.169–3.853) 0.013[85]^a 1.850 (1.013–3.379) 0.045[86]^a [87]Open in a new tab ^a Statistically significant (P < 0.05). 3.2. Knockdown of ATF2 expression suppresses GC cell malignant phenotypes To elucidate the role of ATF2 in GC, further investigation was conducted with a series of functional assays. First, according to the expression level of ATF2 in GC cell lines, we chose the MGC803 cell line to knockdown ATF2, and the AGS cell line was selected to overexpress ATF2. The efficiency of ATF2 knockdown and overexpression was confirmed by qRT‒PCR and western blot analysis ([88]Fig. 2A and B). The results of the CCK-8 assay showed that ATF2 knockdown significantly decreased cell proliferative capacity, although ATF2 overexpression had no significant effect ([89]Fig. 2C and D). As shown in [90]Fig. 2E, ATF2 overexpression significantly enhanced the migration but not the invasion of GC cells. Notably, ATF2 knockdown dramatically attenuated the migration and invasion capacities of GC cells ([91]Fig. 2F). Taken together, these results suggest that ATF2 knockdown had a much greater effect on GC cell malignant phenotypes than ATF2 overexpression in vitro. Fig. 2. [92]Fig. 2 [93]Open in a new tab ATF2 knockdown inhibits GC cell malignant phenotypes. (A-B) The overexpression and knockdown efficiency of ATF2 were confirmed by Western blot analysis and qRT-PCR. (C–D) CCK-8 assays were used to evaluate the effect of ATF2 overexpression or knockdown on GC cell proliferation. (E–F) The migratory and invasive ability of the indicated stable transfection GC cells were detected using Transwell assays. Data are shown as the mean ± SD (n = 3). *P < 0.05, **P < 0.01, ***P < 0.001. 3.3. Sorafenib induces ferroptosis and activates ATF2 expression in GC cells Due to a previous study indicating the uncertainty in sorafenib-induced ferroptosis [[94]12], we first investigated whether sorafenib induced ferroptosis in GC cells. As shown in [95]Fig. 3A, after treatment with 10 μM sorafenib for 24 h, the morphology of AGS and MGC803 cells both shrank, became round and were loosely arranged. Treatment with sorafenib could sharply decrease the proliferation rate relative to untreated GC cells, while cotreatment with a ferroptosis inhibitor (Fer-1) partly reversed these changes ([96]Fig. S1). Consistently, the live/dead cell staining of MGC803 cells revealed a similar result ([97]Fig. S2). Treatment with sorafenib led to an increase in total cellular ROS and lipid ROS compared to the control group ([98]Fig. 3B and C). Furthermore, incubation with sorafenib resulted in a dramatic increase in MDA but a decrease in GSH, and this effect was effectively inhibited by Fer-1 ([99]Fig. 3D and E). Given that ferroptosis is closely related to mitochondrial function, we next examined changes in mitochondrial membrane potential (MMP) and morphology. The results of JC-1 staining showed that sorafenib treatment significantly decreased the MMP compared with that in the control group ([100]Fig. 4A). In addition, TEM revealed significantly decreased or absent mitochondrial cristae and increased mitochondrial membrane density in sorafenib-treated MGC803 cells ([101]Fig. 4B). These results demonstrate that sorafenib can induce ferroptotic cell death in GC cells. Fig. 3. [102]Fig. 3 [103]Open in a new tab Sorafenib induces ferroptosis in AGS and MGC-803 cells. (A) Morphologic changes of GC cells were observed under a light microscope after treatment with 10 μM sorafenib for 24 h in the absence or presence of 1 μM Fer-1. (B-C) Lipid peroxidation and intracellular ROS levels were detected using C11-BODIPY and DCFH-DA staining respectively, after treatment with 10 μM sorafenib for 24 h in the absence or presence of 1 μM Fer-1. (D–E) AGS and MGC-803 cells were incubated with 10 μM sorafenib for 24 h in the absence or presence of 1 μM Fer-1, cellular MDA and GSH levels were detected. Data are shown as the mean ± SD (n = 3). *P < 0.05, **P < 0.01, ***P < 0.001. Fig. 4. [104]Fig. 4 [105]Open in a new tab Sorafenib treatment increases ATF2 expression and promotes its nuclear translocation in GC cells. (A) Mitochondrial membrane potential was detected with JC-1 staining after treatment with 10 μM sorafenib for 24 h. Red fluorescence (JC-1 aggregate form) represents normal membrane potential, and green fluorescence (JC-1 JC-1 monomer form) represents mitochondrial membrane potential depolarization. (B) The morphology of MGC803 cells was observed via TEM after treatment with 10 μM sorafenib for 24 h in the absence or presence of 1 μM Fer-1. (C) The levels of ATF2, p-ATF2 and SLC7A11 proteins were assessed by western blot after treatment with10 μM sorafenib at the indicated time points in MGC803 cells. (D) Immunofluorescence localization of ATF2 in AGS cells after treatment with or without 10 μM sorafenib for 24 h. (For interpretation of the references to color in this figure legend, the