ATF4 and ATF6 produce diverse transcriptional signatures affecting metabolic genes and cell death under glucose deprivation

ATF4 and ATF6 produce diverse transcriptional signatures affecting metabolic genes and cell death under glucose deprivation | 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 ATF4 and ATF6 produce diverse transcriptional signatures affecting metabolic genes and cell death under glucose deprivation Cristina Munoz-Pinedo, Mabel Cruz-Rodríguez, Francesca Favaro, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7829324/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Tumours grow faster than the local vasculature, resulting in a shortage of oxygen and nutrients. Among nutrients reduced in the tumor microenvironment, glucose is essential for tumour growth and survival. To explore how lung cancer cells cope with a low-glucose environment, we analysed transcriptional changes in glucose-starved A549 cells using RNA-sequencing. This showed downregulation of multiple pathways related to DNA replication and cell cycle. Many pathways were upregulated, and among them, the most upregulated transcriptional response to glucose deprivation was the Unfolded Protein Response (UPR), which has been shown to promote adaptation to proteotoxic and endoplasmic reticulum stress. The UPR involves three signalling branches, the PERK/ATF4, IRE1/XBP1, and ATF6 pathways. Glucose shortage robustly induced the three branches of the UPR in several non-small cell lung carcinoma cell lines, as indicated by ATF4 accumulation, XBP1 mRNA splicing and ATF6 cleavage. Transcriptional network analysis indicated that the transcriptional response to glucose deprivation was primarily driven by ATF6 and ATF4. Their silencing revealed that they cooperate to regulate multiple metabolic genes and pathways related to lipid synthesis and to amino acid synthesis and transport. ATF4 additionally regulated the transcriptional induction of mitochondrial OXPHOS-associated pathways. Functionally, ATF4 contributed to cell death, while ATF6 and IRE1/XBP1s did not impact survival. Interestingly, the ATF4 targets CHOP, Noxa and DR4 (TRAIL-R1) did not mediate cell death, which was only partially dependent on TRAIL-R2 (DR5) and only partially prevented by caspase inhibitors. Of note, both ATF4 and ATF6 regulated CHOP, and the absence of ATF6 enhanced the activation of XBP1 and ATF4 under glucose deprivation. These findings indicate that glucose deprivation initiates a complex interplay between the different branches of the UPR, which shape the balance between metabolic homeostasis and cell death. Biological sciences/Cancer/Cancer metabolism Biological sciences/Cell biology/Protein folding Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Tumours cells are frequently stressed due to their high metabolic needs and the exhaustion of nutrients in the microenvironment. Lung adenocarcinoma, which is the most common subtype of non-small cell lung carcinoma (NSCLC), has been shown to be capable of dealing with and adapt to metabolic stress through constitutive activation of the ISR ( 1 ). This stress response partially overlaps with the PERK branch of the Unfolded Protein Response (UPR), which responds to protein stress and accumulation of misfolded proteins in the endoplasmic reticulum (ER). Several consequences of nutrient shortage converge towards the activation of the UPR ( 2 ). For instance, a decrease in ATP levels reduces SERCa 2+ pump activity and chaperone functionality ( 3 ). NADPH and glutathione deficiency cause impairment of redox homeostasis also leading to protein misfolding. Moreover, in response to low glucose, impaired N-glycosylation generated by a reduction in sugar donors affects proper glycoprotein folding ( 3 ). The accumulation of misfolded proteins in the endoplasmic reticulum (ER) activates three transmembrane ER stress sensors: Protein Kinase RNA-like ER kinase (PERK), the kinase/endonuclease Inositol-Requiring Enzyme 1 (IRE) 1, and Activating Transcription Factor (ATF) 6α. Dissociation of these sensors from the chaperone-binding immunoglobulin protein BiP (also known as GRP78) activates them and initiates the three distinct branches of the UPR ( 4 ). During stress, PERK phosphorylates eIF2α, which reduces overall protein synthesis while selectively increases the translation of specific adaptive response mRNAs, such as ATF4. In turn, this activates target gene like CHOP, which help coordinate the stress response ( 5 , 6 ). ATF6α dissociation from BiP, and changes in redox status with the participation of PDIA5 and ERp18, promote its traffic to Golgi, where is cleaved by S1/S2 proteases to release its active form ( 7 – 9 ). ATF6α hypo-glycosylation also promotes its activation ( 10 ). IRE1 activation promotes the splicing of X-box Binding Protein 1 (XBP1) mRNA, producing the active transcription factor XBP1s, which promotes cell survival. Additionally, the RNase activity of IRE1 also contributes to reducing the protein load though IRE1-Dependent Decay (RIDD) of mRNA, which degrades selected mRNAs ( 11 ). The canonical function of the UPR is to restore proteostasis and ER homeostasis upon stress by enhancing ER-associated degradation of misfolded proteins, increasing ER folding capacity and attenuating protein synthesis to reduce the ER load ( 12 ). If the adaptation is successful, the cell resumes function at an elevated homeostatic state. However, if adaptation fails, unresolvable ER stress and chronic UPR activation leads to cell death ( 13 ). Since NSCLC cells are highly dependent on glucose for their growth, we aimed to characterize their response to glucose deprivation by analysing transcriptomic changes upon glucose removal. We investigated whether starvation-induced and/or ATF4/ATF6-mediated transcriptional programs are required for NSCLC cell survival or other adaptation mechanisms to cope with metabolic stress. Materials and methods Cell Lines and Treatments A panel of non-small cell lung cancer (NSCLC) cells was used: the lung adenocarcinoma (LUAD) cell line A549 (ATCC), lung squamous carcinoma (LUSC), SW900 (ATCC), and large cell lung cancer cell lines H1299, (gifted by Montserrat Sanchez Cespedes) and H460 (ATCC). A549 and H1299 cells were cultured in pyruvate-free high-glucose DMEM (25mM Glc); SW900 and H460 cells were cultured in RPMI-1640 medium (10mM Glc). Cells were supplemented with 10% FBS and 2mM L-glutamine and incubated at 37°C in a 5% CO 2 atmosphere. Glucose deprivation experiments were performed by seeding 300,000 cells per well for A549, H1299 and H460, or 600,000 cells per well for SW900, in 6-well plates. Next day, or 48h later in case of transfection (see below), they were washed twice with FBS-pyruvate-and glucose-free DMEM or RPMI media and incubated with its respective glucose-free media (-Glc), while the control cells were supplemented with 25mM or 10mM Glc (+ Glc). Both conditions were supplemented with 10% dialysed FBS (dFBS) and 2mM L-glutamine. For FBS dialysis, the dialyzing membrane (SERVA) was prepared according to the manufacturer’s recommendations and filled with FBS. The pipe was washed twice for 1h and once overnight in 1L of PBS at 4°C with continuous stirring, and further filtered for sterilization. For H460 treatments, non-dialysed 10% FBS was used to avoid excessive cell death. MKC8866 (Selleckchem) was diluted in media at 10µM and added to the cells one hour prior to medium change, and readded at the same concentration in glucose deprivation medium. Western Blot Western Blot Cells were collected and lysed in RIPA buffer (ThermoFisher) supplemented with protease and phosphatase inhibitors (Roche). Proteins were quantified by the BCA assay Kit (Pierce, Cultek). 30 micrograms of protein per sample were loaded in acrylamide gels. Proteins were transferred to nitrocellulose membranes which were blocked in 5% non-fat dry milk in TBS-T (0.1 M Tris-HCl; 1.5 M NaCl; 0.1% Tween-20, pH 7.5). Membranes were incubated with the primary antibody for 2 hours at room temperature or overnight at 4°C in 2.5% milk in TBS-T. Primary antibodies were diluted 1:1000 except for β-actin, which were diluted 1:2000. Membranes were developed using freshly prepared ECL reagent (Promega) with the Amersham 600 Imager (Life Science). Proteins bands were then quantified using ImageJ (Version 1.50i) and values were normalised to β-actin. Fold change was calculated by normalizing against each control in each experiment. Antibodies are described in Supplementary table 1 . Transfection with Small Interfering RNA (siRNA) For siRNA transfections, cells were seeded in 6-well plates, trypsinised and transfected while plated with a transfection mixture of unsupplemented media with 1µL/mL DharmaFECT and either non-targeting (NT) siRNA, ATF4-targeting siRNA, or ATF6-targeting siRNA at a final concentration of 100nM siRNA. 24h later cells were trypsinised and plated in two wells, and 24h later, cells were washed, and medium was replaced with glucose deprivation medium. Transfections with CHOP, DR5 and DR4 used the same protocol, while Noxa and XBP1-targeting siRNAs were incubated for 24h and not trypsinized. Sequences are listed in Supplementary table 1 . Gene Expression Analysis RNA was extracted using the PureLink RNA Mini Kit (Invitrogen, ThermoFisher), following the manufacturer’s instructions. One microgram of RNA per sample was retrotranscribed into cDNA using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Invitrogen). For each experiment, quantitative PCR (qPCR) reactions were performed in duplicate using the LightCycler 480 SYBR green (Roche). Each reaction contained 10ng of cDNA, 1mM of primer mix (forward and reverse) and PowerUp SYBR Green Master mix (Applied Biosystems, Invitrogen). CT values were determined and normalised to L32 as the housekeeping gene. Fold changes were calculated relative to the control sample. Differential expression and Gene Set Enrichment Analysis (GSEA) RNAseq was performed on mRNA from A549 cells. 3 biological replicates were used. Differentially expressed genes (DEGs) were identified using the DESeq2 package in R ( 16 ). Differentially expressed genes were considered significant with an adjusted p -value (padj) < 0.05. Gene Set Enrichment Analysis (GSEA) was conducted using the fgsea package( 14 ) and gene sets from the Reactome pathways collection, available at MSigDB resource ( 15 , 16 ). Enrichment was considered significant for gene sets with an adjusted p -value (padj) < 0.05 ( 15 , 16 ). Transcription factor network inference and motif enrichment analysis DecoupleR package ( 17 ) and Dorothea ( 18 ) gene regulatory network database (i.e., signed transcription factor - target gene interactions) were used for inference of relative transcription factor network activity versus its control. Motif enrichment analysis was performed using the marge R package ( 19 ), which provides an interface to the HOMER motif discovery framework ( 20 ). Target promoter regions were supplied as BED files representing differential expressed genes identified in each comparison. The package identifies known enriched motifs in those target sequences, relative to a genomic background set, which in this case corresponds to all promoter regions of all genes measured in the RNA-Seq experiment. Cell Death Measurement Cells were trypsinised using a 0.05% trypsin EDTA solution at 37ºC and collected with their supernatants and the PBS used for washing. Cells were centrifuged for 5 min at 450g and resuspended in 300µl PBS containing 0.5µl/ml propidium iodide (PI). The percentage of PI positive cells were measured with the Gallios Flow Cytometer Beckman Coulter©, and the quantification was done using the Kaluza Analysis Software version 2.1. Data is shown as the percentage of PI positive cells ± SEM. Statistical Analysis Significance of the experimental data was calculated using Two-way ANOVA followed by Tukey’s multiple comparison test and performed using Prism GraphPad. Error bars represent the SEM. The significance was indicated as follows: P < 0.05, one asterisk (*); P < 0.01, two asterisks (**); P < 0.001, three asterisks (***), P < 0.0001, four asterisks (****). Results Glucose deprivation induces the Unfolded Protein Response in NSCLC Glucose is an essential nutrient for tumour cells, and we aim to decipher how NSCLC adapt to low glucose conditions. To address this, we cultured A549 cells in either glucose-free (-Glc) or glucose-rich (+ Glc) media for 6 or 16 hours, and analysed their transcriptomes. Gene-Set Enrichment Analysis (GSEA) using Reactome revealed that the pathways downregulated upon starvation (negative normalised enrichment score (NES), were related to DNA synthesis, replication and mitosis, and collectively mainly involved in cell replication (Fig. 1 A, Figure S1 A, Supplementary file 1 ). When we analysed the upregulated pathways (positive NES), we found that the “UPR” was the most upregulated pathway when comparing cells without glucose with the control cells, both at 6 and 16h (Fig. 1 B, Figure S1 B, Supplementary file 1 ). Other pathways related to the UPR like those related to gene regulation by PERK, IRE1alpha and GCN2 were also upregulated (Fig. 1 B, Figure S1 B, Supplementary file 1 ). To verify induction of the UPR in cells exposed to low glucose, we characterised the kinetic response to glucose deprivation in A549 cells. PERK displayed reduced electrophoretic mobility, indicative of increased phosphorylation, as early as 3 hours after glucose deprivation, compared to cells maintained in glucose-rich medium (Fig. 1 C). An accumulation of ATF4 and CHOP proteins was detected 3–6 hours post glucose removal (Fig. 1 C). A consistent increase in PERK , ATF4 and DDTI3 (CHOP) mRNA was observed in glucose starved A549 cells (Fig. 1 D). ATF6 activation was assessed by proteolysis. A decrease in the p90ATF6 band, accompanied by accumulation of the cleaved p50ATF6 fragment, was detected from 6 hours after glucose deprivation (Fig. 1 C). A shift in p90ATF6 was also observed, possibly indicating its hypo-glycosylation (Fig. 1 C). ATF6 mRNA levels did not increase upon glucose deprivation at the times measured (Fig. 1 D). The third main branch of the UPR, IRE1/XBP1, was also activated (Fig. 1 D-E). An increase in the spliced XBP1 mRNA variant ( XBP1s ) was observed as an indicator of IRE1 endonuclease activation, together with an increment in IRE1 mRNA expression (Fig. 1 D-E). Although the UPR induction kinetics changed in four NSCLC cell lines ( Figure S1 C-H ), glucose removal was sufficient to induce the three branches of the UPR in all cases ( Figure S1 C-H ). ATF4 and ATF6 control the transcriptional response to glucose removal We further looked for transcription factors regulated by glucose by using inference methods based on gene enrichment analysis and the Dorothea database ( 18 ). The analysis of the transcriptional networks downregulated by glucose deprivation showed myc-n and several E2F factors among the most downregulated in the absence of glucose, while ATF6 and ATF4 networks were the most upregulated (Fig. 2 A). Additional networks of metabolic stress-related transcription factors such as HIF1A, p53 or FOXO3 were also upregulated upon glucose deprivation (Fig. 2 A). However, their increase was not as pronounced as that of the UPR factors. We therefore examined the contribution of ATF4 and ATF6 to the transcriptional response induced by glucose deprivation by silencing them using siRNA (Fig. 2 B-C). We analysed the subset of differentially expressed genes that were upregulated under glucose deprivation and their regulation by ATF4 or ATF6 ( Supplementary file 2 ). After 16h without glucose, 4176 genes were upregulated; from these, 367 (8.78%) were downregulated by silencing ATF4, and 744 (17.8%) were downregulated by silencing ATF6 (Fig. 2 D). The presence of ATF4 and ATF6 during glucose deprivation also affected levels of many genes reduced by glucose deprivation; that is, when ATF4 or ATF6 (or both) were present, the downregulation of many genes was prevented (Fig. 2 E). Reactome pathway enrichment analysis revealed significant changes upon glucose deprivation and their modulation by siRNA-mediated knockdown of ATF4 or ATF6 (Fig. 2 F). A total of 51 pathways were upregulated at 6 and 16 hours of starvation, while 63 and 153 pathways were downregulated at 6 and 16 hours, respectively ( Supplementary file 1 ). ATF4 and ATF6 contributed to the activation of several pathways (red in the Glc columns that turn blue in the siRNA columns), as well as the reversal of starvation downregulated pathways (blue in Glc columns that turn red in siRNAs columns) (Fig. 2 F, Figure S2 and Supplementary file 1 ). Since ATF4 and ATF6 work as positive regulators of gene expression, we aimed to understand whether they contributed to downregulate targets of other transcription factors, perhaps indirectly. For this, transcriptional network analysis was performed in cells subjected to glucose deprivation while depleted of ATF4 or ATF6. As expected, depletion of ATF4 led to downregulation of the ATF4 transcriptional network, and depletion of ATF6 led to downregulation of the ATF6 transcriptional network (Fig. 2 G-H). In both cases, myc networks and those of several E2F transcription factors, whose transcriptional networks were downregulated without glucose (Fig. 2 A), were now upregulated compared to glucose-deprived samples (Fig. 2 G-H). This suggested that the presence of ATF4 or ATF6 provides signals or nutrients that prevent these proliferating cells from shutting down transcription of genes involved in cycling when glucose is absent. Regulation of stress and metabolic pathways by ATF4 and ATF6 Pathways upregulated by glucose deprivation which were downregulated by ATF4 or ATF6 siRNAs are likely to represent the cellular functions of active ATF4 and ATF6 (Fig. 2 F). Several of these pathways were related to stress responses, including the UPR and the “cellular response to starvation” (Fig. 3 A). Among them, we found some pathways related to translation and to protein synthesis and modification in the ER-Golgi. Two pathways related to glycosylation were regulated by ATF6 (“Asparagine linked N-glycosylation” and “N-glycan trimming in the ER and calnexin/calreticulin cycle”), consistent with known roles of ATF6 in ER homeostasis ( 21 ). Cells deprived of glucose switch to alternative nutrient usage by mitochondrial metabolism ( 22 ). Reactome analysis indicated that indeed, glucose deprivation upregulated transcriptionally some pathways related to mitochondrial respiration and the TCA. These pathways were regulated by ATF4 but not ATF6 (Fig. 3 B). On the other hand, “glucose metabolism” and “glycolysis” pathways were downregulated by glucose starvation, while the lack of ATF6 or ATF4 reversed this downregulation (Fig. 3 B). The “carbohydrate metabolism” pathway downregulated by ATF6 siRNA after 16h of glucose deprivation (Fig. 3 B) included mostly glycosaminoglycan modification enzymes ( Supplementary file 2 ). Both siRNAs increased nucleotide metabolism related pathways, although glucose deprivation did not significantly regulate this pathway (Fig. 3 B). Additionally, several pathways related to amino acid metabolism and transport were induced transcriptionally during starvation, with some of them being regulated by ATF4, ATF6 or both (Fig. 3 C). Regardless of their regulation by glucose, we observed regulation of multiple lipid-related metabolic pathways by ATF4 and ATF6, with substantial co-regulation at the pathway level (Fig. 3 C-D). For instance, “glycerophospholipid biosynthesis”, and SREBP-mediated transcription were downregulated in the absence of either ATF4 or ATF6 ( Fig. 3 D ) . ATF4, but not ATF6, CHOP or XBP1, promoted glucose-starvation induced cell death NSCLC cell lines were sensitive to glucose deprivation, and cell death was apparent within 24-48h, with different kinetics ( Figure S3A-B ). We explored whether Reactome pathways associated to cell death were significantly induced upon glucose deprivation, but only “regulation of TNFR1 signalling” was upregulated (Fig. 4 A, Supplementary file 2 ). However, regardless of their regulation by glucose, several Reactome pathways related to cell death were regulated by ATF4 and/or ATF6 (Fig. 4 A). Therefore, we investigated whether expression of ATF4 or ATF6 might contribute to the adaptative survival response. In all cell lines tested, instead of sensitizing to cell death, ATF4 knockdown significantly reduced cell death induced by glucose deprivation ( 23 , 24 ) (Fig. 4 B-E). ATF6 knockdown had no significant effect on cell death rate (Fig. 4 B-E). The third well studied UPR pathway, the IRE1/XBP1s axis, also did not appear to contribute to glucose deprivation-induced cell death in A549 cells, as neither pharmacological inhibition of IRE1 using MKC8866 nor XBP1 silencing affected cell death after 48h in glucose-starved A549 cells (Fig. 4 E-F ) . However, both approaches effectively reduced XBP1 mRNA splicing and downregulated the mRNA of the XBP1s target gene AGR2 ( Figure S3D-G ). We wondered whether the stimulation of cell death by ATF4 occurred through CHOP expression, since glucose starvation induced CHOP expression by 20–50 fold in NSCLC cells (Fig. 1 C-D, Figure S1 ) . CHOP was silenced using siRNA ( Figure S3G ), and cell death was measured in A549 cells after 48h of glucose starvation. The results showed that CHOP knockdown did not protect cells from death (Fig. 4 H). Additionally, we found that both ATF4 and ATF6 regulated CHOP mRNA and protein expression under glucose deprivation in A549 cells (Fig. 4 I-K). A similar trend was observed in other cell lines (Fig. 4 L), with a significant effect observed in SW900 cells, where CHOP mRNA levels were reduced after 16h of glucose deprivation in the absence of ATF6. Together, these results indicated that CHOP is co-regulated by ATF4 and ATF6, and that ATF4 does not mediate cell death under glucose deprivation through CHOP. ATF4 regulates apoptotic genes with minor or no involvement in cell death by glucose deprivation To further explore the pro-death role of ATF4 in starvation-induced cell death, we selected, from the RNA-sequencing experiment, genes related with cell death that were differentially regulated by glucose deprivation, ATF4, or ATF6 (Fig. 5 A). Known ATF4 targets that were elevated during starvation and may contribute to cell death during glucose starvation were the BH3-only protein Noxa (gene name PMAIP1 ) and both TRAIL death receptors (TNFRSF10A/TRAIL-R1/DR4 and TNFRSF10B/TRAIL-R2/DR5). Additionally, ATF6 also downregulated Noxa (Fig. 5 A). Noxa and both TRAIL receptors, DR4 and DR5, were also upregulated at the protein level in A549 cells upon glucose deprivation (Fig. 5 B-C), while only Noxa and DR5 were regulated transcriptionally at the times measured when measured by qPCR, contrasting with the mild upregulation of DR4 mRNA in the RNAseq (Fig. 5 D-F). ATF4 regulated Noxa and DR5 (TNFRSF10B) but not DR4 ( TNFRSF10A ) mRNA expression, while ATF6 did not regulate these proteins (Fig. 5 G-I). In this line, we assessed if these proteins participate in cell death of A549 cells by silencing them using siRNA and measuring cell death after 48h of glucose deprivation (Figure S3H-I , Fig. 5 J-L ) . The results showed a small reduction in the percentage of PI-positive cells in DR5-silenced cells compared to non-targeting control (Fig. 5 K). DR4 or Noxa knockdown did not affect the cell death rate in glucose-starved A549, although there was a trend towards a small reduction (Fig. 5 J, L). In A549, starvation-induced cell death was not only apoptotic, since pan-caspase inhibitors (Q-VD, and z-VAD) only partially reversed cell death (Fig. 5 M). This could explain the small effect of the knockdown of these apoptotic proteins, which mediate apoptosis induced by glucose deprivation in other contexts. ATF4 and ATF6 cooperate in gene transcription but also show antagonism in gene subsets To try to further explain the discrepancies in the effects of ATF4 and ATF6 in cell death, we analysed individual genes regulated by ATF4 and ATF6 within the subset of genes induced by glucose deprivation. 166 genes were downregulated by either siRNA, and 43 genes were upregulated by silencing either ATF4 or ATF6. For instance, both transcription factors negatively regulated the NF-kappaB target genes IL6 and BL2L1 (Bcl-X), and the transcription factor MYC (Fig. 6 A). Both ATF4 and ATF6 regulated positively the levels of some known ATF4 targets like LCN2 (lipocalin 2) and the amino-acyl tRNA synthetase WARS1 , as well as genes involved in amino acid metabolism like BCAT1 and ARG2 , and the IL-6 receptor family LIFR (Supplementary file 2) . Analysis of enrichment of transcription factor binding sites in the promoters of these genes suggested that the co-regulation of some of these genes may occur via CHOP, a target of ATF4 and ATF6 ( Figure S5A ). 6 genes were upregulated following ATF4 knockdown but downregulated by ATF6 knockdown ( Fig. 6 B ). Interestingly, 35 genes were upregulated by ATF6 knockdown and downregulated by ATF4 silencing. This subset included some known ATF4 targets, and the genes were enriched in ATF4 binding sites ( Figure S5B ). This suggested that ATF4 is further activated in the absence of ATF6 function. This could be due to the absence of ATF6 further enhancing ER stress, since ATF6 target genes participate in protein folding and glycan quality control (Fig. 6 C). Many of these known ATF6 target genes were regulated glucose and ATF6 but not ATF4 (Fig. 6 C). Silencing ATF6 further stimulates ATF4 and XBP1s induction. Since many known ATF4 target genes, as well as ATF4 itself, were upregulated upon ATF6 knockdown (Fig. 6 B and Supplementary file 2 and 3 ), we further explored a possible antagonism between ATF4 and ATF6, which has been described between several branches of the UPR as “compensatory activation”. To this end, we performed siRNA-mediated knock-down of each factor and analysed their reciprocal effects after 6 or 16 hours of glucose deprivation (Fig. 7 ). In the absence of ATF6, several cell lines showed a trend toward increased ATF4 mRNA and protein accumulation (Fig. 7 A-F). A significant increase in ATF4 protein levels following ATF6 silencing was detected at 6h in A549 cells (Fig. 7 A-B). ATF4 mRNA significantly increases after 16h of glucose deprivation in H460 and A549 cells, while in H1299, the increase was observed after 6h (Fig. 7 C-F). Consistent with previous reports ( 23 ), ATF6 downregulation increased XBP1 splicing (Fig. 7 G-J). After 16h of glucose deprivation, XBP1s mRNA levels significantly increased in A549 and H460 cells, with a similar albeit not significant trend observed in H1299 and SW900 cells (Fig. 7 G-J). Discussion The tumour microenvironment is characterized by low nutrient availability, primarily because of the high proliferation rate of cancer cells. Despite these adverse conditions, cancer cells exhibit remarkable adaptability, enabling them to survive in hypoxic and hypoglycaemic environments. Glucose is highly important for cancer cells, and our research focuses on the response of NSCLC cells to glucose deprivation. We demonstrate that glucose deprivation activates the UPR in four distinct NSCLC cell lines. Previous studies have established that glucose deprivation alone is sufficient to trigger the UPR. ATF6 activation in response to glucose starvation was comprehensively characterised by Nadanaka et al . ( 24 ). Furthermore, activation of the IRE1 and PERK branches of the UPR has been documented in cortical neuron cultures subjected to oxygen-glucose deprivation ( 25 ). UPR induction, along with mTOR inactivation, was also observed in glucose-starved NSCLC cells, like A549, in which ATF4 regulated cytokine production ( 26 ). ATF6 and ATF4 were the primary transcriptional regulators upon glucose deprivation in A549 cells. Both regulated several stress responses and metabolic pathways. An extensive overlap was observed among the pathways regulated by both factors. This overlap could be attributed to the number of co-regulated genes or to the fact that some genes regulated specifically by ATF4 or ATF6 are involved in the same pathways. In addition, several genes co-regulated by both were CHOP targets, suggesting indirect regulation. Whether ATF4 and ATF6 contribute directly, as transcription factors, to many of the pathways analysed here, or indirectly through restoration of general homeostasis should be further analysed. Nevertheless, several pathways were regulated specifically by ATF4 or ATF6. ATF4 regulates mitochondrial respiration, TCA and amino acid metabolism as described ( 27 , 28 ). ATF6 regulated several pathways related to translation and N-glycosylation and protein synthesis and modification in the ER-Golgi, consistent with known roles of ATF6 in ER homeostasis ( 21 ). This may possibly reflect an attempt of ATF6 to restoring N-glycosylation, which is reduced when glucose levels are down (Luciano-Mateo et al, under revision)( 2 ). Pathways associated with lipid metabolism, cholesterol synthesis, and the activation of the SREBP response were downregulated when ATF4 or ATF6 were absent in glucose-starved cells. SREBP has been described to cooperate with ATF4 and ATF6 biosynthetic networks ( 29 – 31 ). Our data further support an underexplored role of ATF4 and ATF6 on lipid metabolism. The data also indicated a previously unappreciated regulation of SLC mediated membrane transport by ATF6. Considering the relevance of ATF4 and ATF6 activation we investigated whether they regulate cell survival or cell death under glucose deprivation. We observed that ATF4 promotes cell death under glucose starvation in NSCLC cells, while ATF6 and XBP1s had little or no effect on cell death or survival. Interestingly, the ATF4 targets CHOP, Noxa and DR4 (TRAIL-R1) did not mediate cell death, which was only partially dependent on TRAIL-R2 (DR5) and only partially prevented by caspase inhibitors. Our groups and others had also previously shown ATF4-mediated regulation of non-apoptotic cell death induced by glucose deprivation ( 32 ). On the other hand, the role of ATF4 and TRAIL-R2 (DR5) in starvation-induced cell death was previously described. In HeLa cells, glucose starvation leads to ATF4-mediated, non-transcriptional accumulation of TRAIL-R2 (DR5), which in turn participates in ligand-independent apoptosis ( 33 ). The regulation of DR5 in response to ER stressors is shaped by the interplay between the PERK and IRE1 branches of the UPR ( 44 ). A549 cell death was only partially apoptotic, which may explain the modest reduction in overall cell death observed following DR5 knockdown. CHOP overexpression has been shown to sensitize multiple cell lines to ER stress, among other reasons, by downregulating Bcl2 expression ( 13 , 34 ). In our study, CHOP knockdown did not reduce cell death in starved A549 cells. Moreover, CHOP expression was modulated by both ATF4 and ATF6. CHOP co-regulation by both transcription factors had been previously described ( 35 , 36 ) Our results, consistent with previous studies, revealed that ATF4 is a key regulator of amino acid synthesis pathways. For instance, Torrence et al. demonstrated that ATF4 regulates amino acid metabolism both in the context of ER stress and mTORC1 anabolic signalling ( 37 ). In the context of glucose deprivation, we observed that ATF4 regulated a set of metabolic genes such as PCK2 , PHGDH, PSAT1, ASNS, that coordinate central carbon metabolism and amino acid biosynthesis ( 28 , 38 , 39 ). The glutamine transporter SLC1A5 was also regulated by ATF4. Another one-carbon metabolism enzyme regulated by ATF4 was MTHFD2, which participates in nucleotide metabolism ( 38 ). ATF4 affects cellular bioenergetics, rerouting carbon utilization towards amino acid production, as recently reported by Labbe et al . in a non-stress ISR setting based on PERK activation ( 28 ).This leads us to hypothesize that the pro-death role of ATF4 during nutrient deprivation may be linked to further metabolite depletion. ATF4 regulates genes involved in extracting remaining cellular nutrients, such as residual glucose or glucose derived from glycogen, and could be channelling these resources toward amino acid biosynthesis. Metabolic studies should be performed in the future to understand if (and what) key metabolites are depleted by ATF4 that prevent cell death by glucose deprivation, which could include glutamate ( 40 ). Conversely, ATF6 and IRE1/XBP1 did not contribute to cell death under glucose starvation in the evaluated NSCLC cell lines. However, those factors had historically been described as pro-survival as its major targets contribute to enhanced ER capacity ( 41 ). Our transcriptomic analysis of starved ATF6-knockdown cells confirmed that ATF6 regulates several chaperones and ER-resident proteins. ATF6 is a transcription factor specialized in the regulation of quality control proteins within the ER ( 21 ). Although ATF6 and XBP1 frequently function cooperatively, a stress-independent activation model demonstrated that ATF6 alone is sufficient to regulate ER major chaperones, including BiP, Sel1L, and calreticulin ( 42 ). In our study, ATF6 knockdown resulted in a “compensatory” upregulation of ATF4 and XBP1. Pharmacological inhibition of site-1-protease (S1P), which inhibits ATF6 cleavage, enhances activation of both IRE1 and PERK (49). Similar results were shown upon tunicamycin treatment in ATF6 knockout cells (50). In mice without any of the two isoforms of ATF6 in pancreatic β cells or in the embryonic brain, overactivation of IRE1α and PERK has also been also described (45,46). Therefore, in the absence of ATF6, ER stress is exacerbated, possibly due to insufficient production of ER chaperones, leading to earlier and/or more robust activation of both the PERK/ATF4 and IRE1/XBP1 pathways ( 28 ). In conclusion, our findings demonstrate that lung cancer cells react to glucose deprivation through a complex interplay of UPR pathways, with ATF6 and ATF4 as the primary transcriptional regulators. Together, ATF4 and ATF6 may contribute to cellular adaptation by regulating metabolic genes, although this is not reflected in increased survival to acute glucose deprivation in vitro . Both factors co-regulated several genes, including CHOP. Moreover, our findings reveal an underappreciated crosstalk among UPR branches: ATF6 represses or delays ATF4 induction. Understanding these pathways not only expands our knowledge of cancer cell plasticity under metabolic stress but also highlights potential therapeutic targets to disrupt these adaptive responses. Abbreviations ATF4, Activating Transcription Factor 4 ATF6, Activating Transcription Factor 6 BiP, Binding immunoglobulin protein CHOP, CCAAT-enhancer-binding protein Homologous Protein eIF2, Eukaryotic Initiation Factor 2 (B, beta or A, alpha) ER, Endoplasmic Reticulum ERAD, ER-associated degradation GSEA, Gene-Set Enrichment Analysis Glc, Glucose IRE1, Inositol-Requiring Enzyme 1 ISR, Integrated Stress Response mTORC1, mammalian Target of Rapamycin Complex 1 PERK, PKR-like Endoplasmic Reticulum Kinase SREBP, Sterol Regulatory Element Binding Protein UPR, Unfolded Protein Response XBP1, X-box Binding Protein 1 Declarations Funding We thank CERCA Programme / Generalitat de Catalunya for institutional support. This study has been funded by Ministerio de Ciencia e Innovación y Universidades (MCIN/AEI, DOI:10.13039/501100011033), through the Generación de Conocimiento grant numbers PID2022-140457OB-I00 and PID2019-107213GB-I00, and by the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie Grant Agreements 675448 (TRAINERS) and 766214 (META-CAN). M.Cruz-Rodríguez was supported by AGAUR (Co-funded by European Social Fund. ESF investing in your future) 2021FI_B 00485. D. Palau-Gallinat was supported with funding of the INVESTIGO 2024 program from AGAUR. S. P-M has received funding from FPU grant agreement FPU21/06884. EC’s lab was funded by grants from INCa (PLBIO) and FRM (EQU202403018041). E. Nadal received support from Instituto de Salud Carlos III (PI21/00789, PI24/00702 and INT22/00066), co-funded by European Regional Development Fund (ERDF), a way to build Europe. Acknowledgements We thank Eric Eldering (AMC) and Ingrid Derks for a non-included MLPA analysis. Grammarly AI was used as text editor. Conflicts of interest Eric Chevet is the founder of Thabor Tx (www.thabor-tx.com), and Ernest Nadal has had research funding from Roche, Pfizer, Merck-Serono, Bristol Myers Squibb. Advisory board and consulting: Amgen, Apollomics, AstraZeneca, BeiGene, BMS, Boehringer-Ingelheim, Daiichi-Sankyo, Genmab, Johnson & Johnson, Lilly, Merck Sharp & Dohme (MSD), Merck-Serono, Pfizer, Pierre Fabre, Qiagen, Regeneron, Roche, Sanofi and Takeda. Honoraria for lectures: Amgen, AstraZeneca, BeiGene, BMS, Boehringer-Ingelheim, Daiichi-Sankyo, Illumina, Johnson & Johnson, Lilly, Merck Sharp & Dohme (MSD), Merck-Serono, Pfizer, Pierre Fabre, Qiagen, Regeneron, Roche, Sanofi and Takeda. Travel support: Roche, Takeda, Johnson and Johnson, and MSD. References Ghaddar N, Wang S, Woodvine B, Krishnamoorthy J, van Hoef V, Darini C, et al. The integrated stress response is tumorigenic and constitutes a therapeutic liability in KRAS-driven lung cancer. Nat Commun. 2021;12(1). Cruz-Rodríguez M, Chevet E, Muñoz-Pinedo C. Glucose sensing and the unfolded protein response. FEBS Journal. 2025; Moore CE, Omikorede O, Gomez E, Willars GB, Herbert TP. PERK activation at low glucose concentration is mediated by SERCA pump inhibition and confers preemptive cytoprotection to pancreatic β-cells. Molecular Endocrinology. 2011;25(2):315–26. Kopp MC, Larburu N, Durairaj V, Adams CJ, Ali MMU. UPR proteins IRE1 and PERK switch BiP from chaperone to ER stress sensor. Nat Struct Mol Biol [Internet]. 2019;26(11):1053–62. Available from: http://dx.doi.org/10.1038/s41594-019-0324-9 Uppala JK, Ghosh C, Sathe L, Dey M. Phosphorylation of translation initiation factor eIF2α at Ser51 depends on site- and context-specific information. FEBS Lett. 2018;592(18):3116–25. Xiao W, Sun Y, Xu J, Zhang N, Dong L. uORF-Mediated Translational Regulation of ATF4 Serves as an Evolutionarily Conserved Mechanism Contributing to Non-Small-Cell Lung Cancer (NSCLC) and Stress Response. J Mol Evol [Internet]. 2022;90(5):375–88. Available from: https://link.springer.com/ 10.1007/s00239-022-10068-y Haze K, Yoshida H, Yanagi H, Yura T, Mori K. Mammalian transcription factor ATF6 is synthesized as a transmembrane protein and activated by proteolysis in response to endoplasmic reticulum stress. Mol Biol Cell. 1999;10(11):3787–99. Higa A, Taouji S, Lhomond S, Jensen D, Fernandez-Zapico ME, Simpson JC, et al. Endoplasmic Reticulum Stress-Activated Transcription Factor ATF6α Requires the Disulfide Isomerase PDIA5 To Modulate Chemoresistance. Mol Cell Biol. 2014;34(10):1839–49. Oka OBV, Pierre AS, Pringle MA, Tungkum W, Cao Z, Fleming B, et al. Activation of the UPR sensor ATF6α is regulated by its redox-dependent dimerization and ER retention by ERp18. Proceedings of the National Academy of Sciences [Internet]. 2022;119(12). Available from: https://pnas.org/doi/full/10.1073/pnas.2122657119 Guan D, Wang H, Li VE, Xu Y, Yang M, Shen Z. N-glycosylation of ATF6β is essential for its proteolytic cleavage and transcriptional repressor function to ATF6α. J Cell Biochem. 2009;108(4). Adams CJ, Kopp MC, Larburu N, Nowak PR, Ali MMU. Structure and molecular mechanism of ER stress signaling by the unfolded protein response signal activator IRE1. Front Mol Biosci. 2019;6(MAR):1–12. Ma Y, Hendershot LM. The unfolding tale of the unfolded protein response. Cell. 2001;107(7):827–30. Iurlaro R, Muñoz-Pinedo C. Cell death induced by endoplasmic reticulum stress. FEBS Journal. 2016;2640–52. Korotkevich G, Sukhov V, Sergushichev A. fgsea: Fast Gene Set Enrichment Analysis. 2023;1–29. Available from: https://bioconductor.org/packages/fgsea Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545–50. Milacic M, Beavers D, Conley P, Gong C, Gillespie M, Griss J, et al. The Reactome Pathway Knowledgebase 2024. Nucleic Acids Res. 2024;52(D1):D672–8. Badia-I-Mompel P, Vélez Santiago J, Braunger J, Geiss C, Dimitrov D, Müller-Dott S, et al. decoupleR: ensemble of computational methods to infer biological activities from omics data. Bioinformatics Advances. 2022;2(1):1–3. Garcia-Alonso L, Holland CH, Ibrahim MM, Turei D, Saez-Rodriguez J. Benchmark and integration of resources for the estimation of human transcription factor activities. Genome Res. 2019;29(8):1363–75. Amezquita RA. marge : An API for Analysis of Motifs Using HOMER in R [Internet]. 2018. Available from: http://biorxiv.org/lookup/doi/10.1101/249268 Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell [Internet]. 2010;38(4):576–89. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20513432 Adachi Y, Yamamoto K, Okada T, Yoshida H, Harada A, Mori K. ATF6 is a transcription factor specializing in the regulation of quality control proteins in the endoplasmic reticulum. Cell Struct Funct. 2008;33(1):75–89. Birsoy K, Possemato R, Lorbeer FK, Bayraktar EC, Thiru P, Yucel B. Metabolic determinants of cancer cell sensitivity to glucose limitation and biguanides. Nature [Internet]. 2014;508(7494):108–12. Available from: http://dx.doi.org/10.1038/nature13110 Yoshida H, Matsui T, Yamamoto A, Okada T, Mori K. XBP1 mRNA Is Induced by ATF6 and Spliced by IRE1 in Response to ER Stress to Produce a Highly Active Transcription Factor. Cell. 2001;107:881–91. Nadanaka S, Yoshida H, Mori K. Reduction of disulfide bridges in the lumenal domain of ATF6 in response to glucose starvation. Cell Struct Funct. 2006;31(2):127–34. Badiola N, Penas C, Miñano-Molina A, Barneda-Zahonero B, Fadó R, Sánchez-Opazo G, et al. Induction of ER stress in response to oxygen-glucose deprivation of cortical cultures involves the activation of the PERK and IRE-1 pathways and of caspase-12. Cell Death Dis [Internet]. 2011;2(4):e149–e149. Available from: https://www.nature.com/articles/cddis201131 Puschel F, Favaro F, Redondo-Pedraza J, Lucendo E, Iurlaro R, Marchetti S, et al. Starvation and antimetabolic therapy promote cytokine release and recruitment of immune cells. Proc Natl Acad Sci U S A. 2020;117(18):9932–41. Balsa E, Soustek MS, Thomas A, Cogliati S, García-Poyatos C, Martín-García E, et al. ER and Nutrient Stress Promote Assembly of Respiratory Chain Supercomplexes through the PERK-eIF2α Axis. Mol Cell. 2019;74(5):877–890.e6. Labbé K, LeBon L, King B, Vu N, Stoops EH, Ly N, et al. Specific activation of the integrated stress response uncovers regulation of central carbon metabolism and lipid droplet biogenesis. Nat Commun [Internet]. 2024;15(1):8301. Available from: http://dx.doi.org/10.1038/s41467-024-52538-5 Zeng L, Lu M, Mori K, Luo S, Lee AS, Zhu Y, et al. ATF6 modulates SREBP2-mediated lipogenesis. EMBO Journal. 2004;23(4):950–8. Cheng C, Ru P, Geng F, Liu J, Yoo JY, Wu X, et al. Glucose-Mediated N-glycosylation of SCAP Is Essential for SREBP-1 Activation and Tumor Growth. Cancer Cell. 2015;28(5):569–81. Chen H, Yuan R, Zhang Y, Zhang X, Chen L, Zhou X, et al. ATF4 regulates SREBP1c expression to control fatty acids synthesis in 3T3-L1 adipocytes differentiation. Biochim Biophys Acta Gene Regul Mech [Internet]. 2016;1859(11):1459–69. Available from: http://dx.doi.org/10.1016/j.bbagrm.2016.07.010 León-Annicchiarico CL, Ramírez-Peinado S, Domínguez-Villanueva D, Gonsberg A, Lampidis TJ, Muñoz-Pinedo C. ATF4 mediates necrosis induced by glucose deprivation and apoptosis induced by 2-deoxyglucose in the same cells. FEBS Journal [Internet]. 2015 Sep [cited 2025 May 7];282(18):3647–58. Available from: https://onlinelibrary.wiley.com/doi/ 10.1111/febs.13369 Iurlaro R, Püschel F, León-Annicchiarico, Lucía C, O’Connor H, Martin SJ, et al. Glucose Deprivation Induces ATF4- Mediated Apoptosis through TRAIL Death Receptors. 2017;37(10):1–17. McCullough KD, Martindale JL, Klotz LO, Aw TY, Holbrook NJ. Gadd153 Sensitizes Cells to Endoplasmic Reticulum Stress by Down-Regulating Bcl2 and Perturbing the Cellular Redox State. Mol Cell Biol [Internet]. 2001;21(4):1249–59. Available from: https://www.tandfonline.com/doi/full/ 10.1128/MCB.21.4.1249-1259.2001 Ma Y, Brewer JW, Alan Diehl J, Hendershot LM. Two distinct stress signaling pathways converge upon the CHOP promoter during the mammalian unfolded protein response. J Mol Biol. 2002;318(5):1351–65. Yang H, Niemeijer M, van de Water B, Beltman JB. ATF6 Is a Critical Determinant of CHOP Dynamics during the Unfolded Protein Response. iScience [Internet]. 2020;23(2):100860. Available from: https://doi.org/10.1016/j.isci.2020.100860 Torrence ME, Macarthur MR, Hosios AM, Valvezan AJ, Asara JM, Mitchell JR, et al. The mtorc1-mediated activation of atf4 promotes protein and glutathione synthesis downstream of growth signals. Elife. 2021;10. Tameire F, Verginadis II, Leli NM, Polte C, Conn CS, Ojha R, et al. ATF4 couples MYC-dependent translational activity to bioenergetic demands during tumour progression. Nat Cell Biol. 2019;21(7):889–99. Hyroššová P, Aragó M, Moreno-Felici J, Fu X, Mendez-Lucas A, García-Rovés PM, et al. PEPCK-M recoups tumor cell anabolic potential in a PKC-ζ-dependent manner. Cancer Metab. 2021;9(1):1–15. Koppula P, Zhang Y, Shi J, Li W, Gan B. The glutamate/cystine antiporter SLC7A11/xCT enhances cancer cell dependency on glucose by exporting glutamate. Journal of Biological Chemistry [Internet]. 2017;292(34):14240–9. Available from: http://dx.doi.org/10.1074/jbc.M117.798405 Yamamoto K, Sato T, Matsui T, Sato M, Okada T, Yoshida H, et al. Transcriptional Induction of Mammalian ER Quality Control Proteins Is Mediated by Single or Combined Action of ATF6α and XBP1. Dev Cell. 2007;13(3):365–76. Shoulders MD, Ryno LM, Genereux JC, Moresco JJ, Tu PG, Wu C, et al. Stress-Independent Activation of XBP1s and/or ATF6 Reveals Three Functionally Diverse ER Proteostasis Environments. Cell Rep. 2013;3(4):1279–92. Lebeau P, Byun JH, Yousof T, Austin RC. Pharmacologic inhibition of S1P attenuates ATF6 expression, causes ER stress and contributes to apoptotic cell death. Toxicol Appl Pharmacol [Internet]. 2018;349(December 2017):1–7. Available from: https://doi.org/10.1016/j.taap.2018.04.020 Jin S, Jin B, Ishikawa T, Ninagawa S, Okada T, Koyasu S, et al. Loss of ATF6α in a human carcinoma cell line is compensated not by its paralogue ATF6β but by sustained activation of the IRE1 and PERK arms for tumor growth in nude mice. Mol Biol Cell. 2023;34(3):ar20. Additional Declarations There is a duality of interest Supplementary Files SupplementaryFile1REACTOMEPathways.xlsx Supplemental data Supplementary file 1: Reactome pathways significantly regulated when comparing glucose deprived versus glucose rich incubation (“Glc”, columns), or when comparing an siRNA versus the NT siRNA in glucose deprived cells (“ATF4” and “ATF6” columns). Cells were collected after 6 or 16h of glucose deprivation. Supplementaryfile2DEGsinglcstarvedA54916h.xlsx Supplementary file 2: Differentially expressed genes ( p -value (padj) < 0.05) when comparing incubation in glucose deprived versus glucose rich conditions (“Glc”, columns), or siRNAs versus NT siRNA in glucose deprived cells (“ATF4” and “ATF6” columns) after 16h of glucose deprivation. SupplementaryMaterial1westernblotsRawdata.pptx Supplementary table 1: Antibodies, siRNA and primer sequences Supplementarytable1AntibodiesandsiRNAsequences.docx Supplementary material 1: Full membrane western blot images. FigureS1.tif Figure S1. Glucose deprivation induces the Unfolded Protein Response in NSCLC. A-B).A549 cells were incubated with glucose-free media (-Glc) or glucose-rich media (+Glc) for 6h. mRNA extracts were analysed by RNA-Sequencing. Top 30 Reactome Pathways organised by Normalised enrichment score (NES) after 6h of glucose deprivation are shown. A, Upregulated pathways NES>0, B, Downregulated pathways NES<0. C-H)H1299, H460 and SW900 cells were incubated with (+) or without (-) Glcfor the indicated time points. Cells without treatment were used as T0 control. C-E)Whole cell extracts were analysed by immunoblotting. Representative western blots are shown for ATF4, ATF6α and, β-actin as loading control. D-H) mRNA extracts were analysed by qPCR for ATF4, ATF6, XBP1s, DDIT3 (CHOP) and HSPA5 (BiP). Results are shown normalised to their housekeeping gene L32 and then as fold change vs T0. Statistical analysis performed using One-way ANOVA with multiple comparison tests within samples. n=2-3. FigureS2.tif Figure S2. Transcriptional pathways downregulated by glucose deprivation and upregulated by siRNA against ATF4 or ATF6. A549 cells were transfected with 100nM siRNA for ATF4, siRNA for ATF6, or non-targeting sequence (NT). After 48h, the cells were incubated with (+) or without (-) Glc for 16h. The heatmap shows the 30 most downregulated Reactome pathways when comparing -Glc vs +Glc. Pathways are organised by lowest normalised enrichment score (NES). The second and third colums indicate further significant regulation with siRNA against ATF4 (comparing ATF4 siRNA vs NT siRNA in -Glc) or siRNA against ATF6 (comparing ATF6 siRNA vs NT siRNA in -Glc). FigureS3.tif Figure S3. Glucose deprivation induces cell death in NSCLC. A)A549, H460, H1299 or SW900 cells were incubated with medium with (+) or without (-) Glc for 24h. A representative picture for each condition is shown. B) Cells from A, were subsequently collected, stained using propidium iodide (PI) and analysed by flow cytometry. Bar graphs show percent of PI positive cells (Mean ± SEM) (n=2-3). C-D) A549 cells were transfected with indicated siRNA. After incubation for 24h, mRNA extracts were analysed by qPCR for the indicated genes. Results are shown normalised to their housekeeping gene L32 and then as fold change vs NT siRNA or non-treated control. Mean ± SEM (n=3). E-F) A549 cells were pretreated with IRE1 inhibitor MKC8866 (10µM), then washed and incubated with medium with (+) or without (-) Glc in the presence of the inhibitor. After incubation for 24h, mRNA extracts were analysed by qPCR for the indicated genes. G-H) A549 cells were transfected with CHOP (G), Noxa (H) or non-targeting siRNA and incubated for 24h. CHOP and Noxa were measured by qPCR. I) After transfection with indicated siRNAs and 24h of glucose deprivation, whole cell extracts were analysed by immunoblotting. Representative western blots are shown for DR4, DR5, β-actin as loading control. Statistical analysis performed using One-way ANOVA with multiple comparison test within samples (n=2-3). FigureS4.tif Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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1","display":"","copyAsset":false,"role":"figure","size":454706,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGlucose deprivation induces the Unfolded Protein Response in NSCLC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA549 (300x10³ cells per well) were incubated with glucose-free media (-Glc) or glucose-rich media (+Glc) for 16h. mRNA extracts were analysed by RNA-Sequencing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA-B)\u003c/strong\u003eGene-set enrichment analysis (GSEA) from Reactome Gene Set was performed. The top 30 pathways are shown organised by Normalised enrichment score (NES) when comparing -Glc vs +Glc. \u003cstrong\u003eA, \u003c/strong\u003eDownregulated pathways, NES\u0026lt;0. \u003cstrong\u003eB,\u003c/strong\u003e Upregulated pathways, NES\u0026gt;0.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC)\u003c/strong\u003eA549 cells were incubated with (+) or without (-) Glc for the indicated time points. Cells from time 0h (T0) were used as control. Representative western blots are shown for PERK, ATF4, CHOP and ATF6α, and β-actin as loading control (n=3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eD)\u003c/strong\u003emRNA extracts were analysed by qPCR for the following genes\u003cem\u003e: PERK, ATF4, DDIT3 (CHOP), ATF6,\u003c/em\u003e \u003cem\u003eHSPA5 \u003c/em\u003e(BiP),\u003cem\u003e IRE1, XBP1, XBP1s\u003c/em\u003e. Results are shown normalised to their housekeeping gene \u003cem\u003eL32\u003c/em\u003e and then as fold change vs T0 (n=3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eE) \u003c/strong\u003eRT-PCR was performed using primers for \u003cem\u003eXBP1\u003c/em\u003eand loaded in a 2% Agarose gel. An image for the electrophoresis result is show (MWM, Molecular weight marker).\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using One-way ANOVA with Tukey’s multiple comparison test within samples.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/e3fcd7a859a023cf673d9ee7.png"},{"id":95042773,"identity":"7186bb9e-96ab-402a-8108-4f9d3f867e26","added_by":"auto","created_at":"2025-11-03 16:21:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":408443,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eATF4 and ATF6 dominate the transcriptional response to glucose deprivation in A549.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA549 cells were transfected with siRNA for ATF4, ATF6, or non-targeting sequence (NT). 48h after transfection, they were incubated with (+) or without (-) Glc for 16h.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003eBar graph of the transcription factor networks (TFN) differentially downregulated (blue) or upregulated (red) in NT-transfected, glucose deprived versus non deprived cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB)\u003c/strong\u003eWhole cell extracts were analysed by immunoblotting. Representative western blots are shown for ATF4, ATF6α and, β-actin as loading control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC)\u003c/strong\u003emRNA extracts were analysed by qPCR for \u003cem\u003eATF4\u003c/em\u003e and \u003cem\u003eATF6\u003c/em\u003e. Results are shown normalised to their housekeeping gene \u003cem\u003eL32\u003c/em\u003e and then as fold change vs NT +Glc (n=3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eD) \u003c/strong\u003eVenn diagram of the differentially expressed genes (DEGs) upregulated upon 16h of glucose deprivation in A549, and the genes downregulated by siRNAs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eE) \u003c/strong\u003eVenn diagram of the downregulated DEGs upon 16h of glucose deprivation in A549, and the genes upregulated by siRNAs. \u003cem\u003ep\u003c/em\u003e-value (padj) \u0026lt;0.05 and |log2 (Fold Change) |\u0026gt;0.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eF)\u003c/strong\u003e Heatmaps showing the Reactome pathways regulated by glucose deprivation, and by the siRNAs in A549 cells after 6h or 16h of glucose deprivation. Upregulated pathways NES\u0026gt;0 (in red)\u003cstrong\u003e,\u003c/strong\u003edownregulated pathways NES\u0026lt;0 (in blue); non-significantly regulated pathways in grey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG-H) \u003c/strong\u003eBar graph of the transcriptional networks differentially downregulated (blue) or upregulated (red) in glucose starved A549 after 16h, comparing ATF4 siRNA vs NT siRNA (G) or ATF6 siRNA vs NT (H).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/2c3f8849bb7193fbe838f826.png"},{"id":95221905,"identity":"5b31482d-8c1e-4c37-a0ab-5ce5967deadd","added_by":"auto","created_at":"2025-11-05 16:19:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":391622,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eATF4 and ATF6 regulate stress responses and metabolic pathways.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA549 cells were transfected with siRNA for ATF4, ATF6, or non-targeting sequence (NT) and incubated with (+) or without (-) Glc for 6 or 16h. mRNA extracts were analysed by RNA-Sequencing, and GSEA enrichment was performed.\u003cstrong\u003e \u003c/strong\u003eHeatmaps show a selection of Reactome pathways significantly upregulated (NES\u0026gt;0, in red) or downregulated (NES\u0026lt;0, in blue) when comparing glucose deprived versus glucose rich incubation (-Glc, columns), or the siRNAs versus the NT siRNA glucose deprivation (“ATF4 siRNA” and “ATF6 siRNA” columns, respectively). Non-significantly regulated pathways are shown in grey. \u003cstrong\u003eA)\u003c/strong\u003eStress responses, protein translation and glycosylation related pathways. \u003cstrong\u003eB) \u003c/strong\u003eAmino acid transport and metabolism related pathways. \u003cstrong\u003eC) \u003c/strong\u003eMitochondrial respiration and beta-oxidation, carbohydrate and nucleotide metabolism related pathways. \u003cstrong\u003eD) \u003c/strong\u003eLipid metabolism related pathways.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/82f57f974801d6422cfc1613.png"},{"id":95042776,"identity":"8c19e596-aa2a-4a9c-be9d-0e5d7289bafe","added_by":"auto","created_at":"2025-11-03 16:21:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":380403,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCell death induced by glucose deprivation is regulated by ATF4 but not ATF6, XBP1 or CHOP.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e. A549 cells were transfected with the indicated siRNA or non-targeting sequence (NT) and incubated with medium with (+) or without (-) Glc.\u003cstrong\u003eA) \u003c/strong\u003eA549 mRNA extracts were analysed by RNA-Sequencing. The heatmap shows cell death related Reactome pathways regulated by glucose or/and by the siRNAs after 6 or 16h of glucose deprivation. Upregulated pathways upon silencing the gene (NES\u0026gt;0) are shown in red\u003cstrong\u003e,\u003c/strong\u003e downregulated pathways (NES\u0026lt;0) in blue; non-significantly regulated pathways in grey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB-F) \u003c/strong\u003eCells transfected with indicated siRNA and subjected to glucose deprivation for 48h were stained using propidium iodide (PI) and analysed by flow cytometry. Bar graphs show percent of PI positive cells (Mean ± SEM) (n=3-4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG)\u003c/strong\u003eA549 cells were pretreated with the IRE1 inhibitor MKC8866 (10µM), then washed and incubated with or without glucose in the presence of the inhibitor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH)\u003c/strong\u003e Cells were transfected with NT or CHOP siRNA, treated with or without glucose and collected for PI staining 48h later (n=3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eI-J) \u003c/strong\u003esiRNA against indicated proteins was performed as in A.\u003cstrong\u003e I)\u003c/strong\u003e Representative western blots of A549 are shown for CHOP, and β-Actin as loading control. \u003cstrong\u003eJ)\u003c/strong\u003e Densitometric analysis for I (n=2).\u003cstrong\u003e \u003c/strong\u003emRNA extracts were analysed by qPCR for \u003cem\u003eDDIT3\u003c/em\u003e in A549 \u003cstrong\u003e(K)\u003c/strong\u003e and other cell lines \u003cstrong\u003e(L).\u003c/strong\u003e Results are shown normalised to the housekeeping gene \u003cem\u003eL32\u003c/em\u003e and then as fold change vs NT siRNA with glucose (n=3). Statistical analysis was performed using One-way ANOVA with Tukey’s multiple comparison test within samples.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/bacd803660993e65ec0275cd.png"},{"id":95042778,"identity":"c4a9e2cb-584c-44ef-a2c6-672db55ca458","added_by":"auto","created_at":"2025-11-03 16:21:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":332566,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eATF4 regulates apoptotic genes with minor or no involvement in cell death by glucose deprivation\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eA549cells were transfected the indicated siRNAs or non-targeting sequence (NT) and incubated with medium with (+) or without (-) Glc.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003e After 16h, mRNA extracts were analysed by RNA-Sequencing. A heatmap with a selection of cell death related genes expressed in foldchange (FC) is shown.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB)\u003c/strong\u003e Whole cell extracts from Noxa siRNA transfection, after 24h of glucose deprivation, were analysed by immunoblotting. Representative western blots are shown for Noxa, with β-actin as loading control. Right panel: densitometry analysis (n=2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC)\u003c/strong\u003e A549 cells were incubated with medium with (+) or without (-) Glc for the indicated time points. Whole cell extracts were analysed by immunoblotting. Representative western blots are shown for DR4, DR5, β-actin as loading control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eD-F)\u003c/strong\u003e mRNA extracts were analysed by qPCR primer for \u003cem\u003ePMAIP1\u003c/em\u003e (gene for Noxa), \u003cem\u003eTNFRSF10B \u003c/em\u003e(gene name for DR5) and\u003cem\u003e TNFRSF10A \u003c/em\u003e(gene name for DR4). Results are shown normalised to their housekeeping gene \u003cem\u003eL32\u003c/em\u003eand then as fold change vs T0. Mean ± SEM (n=3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG-I)\u003c/strong\u003e Cells were transfected with indicated siRNA and incubated with medium with (+) or without (-) Glc for 16h. mRNA extracts were analysed by qPCR for indicated transcripts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJ-L)\u003c/strong\u003e Cells were transfected with indicated siRNA and incubated with medium with (+) or without (-) Glc. After 48h the cells were collected, stained using (PI) and analysed by flow cytometry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM)\u003c/strong\u003e A549 cells were incubated with medium with (+) or without (-) Glc and, with or without Q-VD-OPH (20μM) or Z-VAD (50 μM) for the indicated times. Cells were collected, stained for PI and analysed by flow cytometry. Results show Mean ± SEM (n=3). Statistical analysis performed using One-way ANOVA with multiple comparison test within samples.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/94135bca51a5860c9a067353.png"},{"id":95222425,"identity":"5354df35-c9d9-4573-85f4-e165e12f3321","added_by":"auto","created_at":"2025-11-05 16:20:38","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":284862,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCooperation or antagonism of ATF4 and ATF6 in gene subsets.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA549 were transfected with siRNA against ATF4, ATF6, or non-targeting sequence (NT). After 48h, cells were incubated with (+) or without (-) Glc media for 16h. mRNA extracts were analysed by RNA-Sequencing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA) \u003c/strong\u003eScatterplot of the log2 (Fold Change) of the differentially expressed genes regulated by ATF4 and ATF6 in glucose deprivation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB) \u003c/strong\u003eBar graph of the genes antagonistically regulated by ATF4 and ATF6, padj \u0026lt;0.05 and |log2 (Fold Change) |\u0026gt;0.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC) \u003c/strong\u003eHeatmap with a selection of known ATF6 targets that were upregulated by glucose deprivation but not affected by siRNA against ATF4.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/fd9147269a7b871c75d3ebe8.png"},{"id":95222214,"identity":"610edb3d-7cae-469b-9bd6-adfc5bb72ef0","added_by":"auto","created_at":"2025-11-05 16:20:19","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":239981,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSilencing ATF6 further stimulates ATF4 and XBP1s induction.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndicated cell lines were transfected with siRNA against ATF4, ATF6, or with non-targeting sequence (NT) and incubated with medium with (+) or without (-) Glc for the indicated times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA) \u003c/strong\u003eWhole cell extracts were analysed by immunoblotting. Representative western blots are shown for ATF4 and, β-actin as loading control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB) \u003c/strong\u003eDensitometry analysis of the blots in A, expressed as fold expression vs NT in glucose-free medium, for each time. Mean ± SEM (n=5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG-J)\u003c/strong\u003emRNA extracts were analysed by qPCR for \u003cem\u003eATF4\u003c/em\u003e and \u003cem\u003eXBP1s\u003c/em\u003e. Results are shown normalised to their housekeeping gene \u003cem\u003eL32\u003c/em\u003e and then as fold change vs NT in +Glc, for each time. Mean ± SEM (n=2-4). Statistical analysis performed using One-way ANOVA with multiple comparison test within samples. P-value: *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/a6f3487aba2901cdfad055a1.png"},{"id":97366945,"identity":"a2ad5b85-01fd-42d6-ba95-8ac8247bf0c9","added_by":"auto","created_at":"2025-12-03 16:14:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3631215,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/0920ea38-e94a-4e38-ae1b-d855738a5450.pdf"},{"id":95042774,"identity":"4243dc74-58c4-4f21-a4e4-7a7847b996dd","added_by":"auto","created_at":"2025-11-03 16:21:14","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":104647,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary file 1: \u003c/strong\u003eReactome pathways significantly regulated when comparing glucose deprived versus glucose rich incubation (“Glc”, columns), or when comparing an siRNA versus the NT siRNA in glucose deprived cells (“ATF4” and “ATF6” columns). Cells were collected after 6 or 16h of glucose deprivation.\u003c/p\u003e","description":"","filename":"SupplementaryFile1REACTOMEPathways.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/ea670eba52f283ec2193cc71.xlsx"},{"id":95222503,"identity":"f114157d-684c-47aa-9751-a419f8d41092","added_by":"auto","created_at":"2025-11-05 16:20:43","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1655402,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary file 2: \u003c/strong\u003eDifferentially expressed genes (\u003cem\u003ep\u003c/em\u003e-value (padj) \u0026lt; 0.05) when comparing incubation in glucose deprived versus glucose rich conditions (“Glc”, columns), or siRNAs versus NT siRNA in glucose deprived cells (“ATF4” and “ATF6” columns) after 16h of glucose deprivation.\u003c/p\u003e","description":"","filename":"Supplementaryfile2DEGsinglcstarvedA54916h.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/194150afaf4d31fc7c67b0de.xlsx"},{"id":95042795,"identity":"94ff7551-0bbf-4118-9b3c-25f12d955bd7","added_by":"auto","created_at":"2025-11-03 16:21:14","extension":"pptx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":16614787,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 1: \u003c/strong\u003eAntibodies, siRNA and primer sequences\u003c/p\u003e","description":"","filename":"SupplementaryMaterial1westernblotsRawdata.pptx","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/e2a4aa4185b8356de4f6cdbe.pptx"},{"id":95042785,"identity":"1f407689-df0d-4a45-9e51-1d5688a0a70f","added_by":"auto","created_at":"2025-11-03 16:21:14","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":27564,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary material 1: \u003c/strong\u003eFull membrane western blot images.\u003c/p\u003e","description":"","filename":"Supplementarytable1AntibodiesandsiRNAsequences.docx","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/e51a8d636aa74619df2032a7.docx"},{"id":95222124,"identity":"d65398d6-df99-4e82-9940-16f5e3da7c0d","added_by":"auto","created_at":"2025-11-05 16:20:10","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":278046,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S1. Glucose deprivation induces the Unfolded Protein Response in NSCLC.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA-B).\u003c/strong\u003eA549 cells were incubated with glucose-free media (-Glc) or glucose-rich media (+Glc) for 6h. mRNA extracts were analysed by RNA-Sequencing. Top 30 Reactome Pathways organised by Normalised enrichment score (NES) after 6h of glucose deprivation are shown. \u003cstrong\u003eA\u003c/strong\u003e, Upregulated pathways NES\u0026gt;0, \u003cstrong\u003eB\u003c/strong\u003e, Downregulated pathways NES\u0026lt;0.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC-H)\u003c/strong\u003eH1299, H460 and SW900 cells were incubated with (+) or without (-) Glcfor the indicated time points. Cells without treatment were used as T0 control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC-E)\u003c/strong\u003eWhole cell extracts were analysed by immunoblotting. Representative western blots are shown for ATF4, ATF6α and, β-actin as loading control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eD-H\u003c/strong\u003e) mRNA extracts were analysed by qPCR for \u003cem\u003eATF4, ATF6, XBP1s, DDIT3 \u003c/em\u003e(CHOP) and \u003cem\u003eHSPA5 \u003c/em\u003e(BiP). Results are shown normalised to their housekeeping gene \u003cem\u003eL32\u003c/em\u003e and then as fold change vs T0. Statistical analysis performed using One-way ANOVA with multiple comparison tests within samples. n=2-3.\u003c/p\u003e","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/ed506395c3b61826e398ebfe.tif"},{"id":95221922,"identity":"17ada4b4-b0c1-4ae1-8520-11d670a87699","added_by":"auto","created_at":"2025-11-05 16:19:55","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":59544,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S2. Transcriptional pathways downregulated by glucose deprivation and upregulated by siRNA against ATF4 or ATF6.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA549 cells were transfected with 100nM siRNA for ATF4, siRNA for ATF6, or non-targeting sequence (NT). After 48h, the cells were incubated with (+) or without (-) Glc for 16h. The heatmap shows the 30 most downregulated Reactome pathways when comparing -Glc vs +Glc. Pathways are organised by lowest normalised enrichment score (NES). The second and third colums indicate further significant regulation with siRNA against ATF4 (comparing ATF4 siRNA vs NT siRNA in -Glc) or siRNA against ATF6 (comparing ATF6 siRNA vs NT siRNA in -Glc).\u003c/p\u003e","description":"","filename":"FigureS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/a736925db7ab7fba5310ee79.tif"},{"id":95222130,"identity":"7096b1ef-8fb2-4db5-9df9-96d6106ea0e0","added_by":"auto","created_at":"2025-11-05 16:20:10","extension":"tif","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":245732,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S3. Glucose deprivation induces cell death in NSCLC\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA)\u003c/strong\u003eA549, H460, H1299 or SW900 cells were incubated with medium with (+) or without (-) Glc for 24h. A representative picture for each condition is shown. \u003cstrong\u003eB\u003c/strong\u003e) Cells from \u003cstrong\u003eA\u003c/strong\u003e, were subsequently collected, stained using propidium iodide (PI) and analysed by flow cytometry. Bar graphs show percent of PI positive cells (Mean ± SEM) (n=2-3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC-D)\u003c/strong\u003e A549 cells were transfected with indicated siRNA. After incubation for 24h, mRNA extracts were analysed by qPCR for the indicated genes. Results are shown normalised to their housekeeping gene \u003cem\u003eL32\u003c/em\u003e and then as fold change vs NT siRNA or non-treated control. Mean ± SEM (n=3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eE-F)\u003c/strong\u003e A549 cells were pretreated with IRE1 inhibitor MKC8866 (10µM), then washed and incubated with medium with (+) or without (-) Glc in the presence of the inhibitor. After incubation for 24h, mRNA extracts were analysed by qPCR for the indicated genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eG-H)\u003c/strong\u003e A549 cells were transfected with CHOP (\u003cstrong\u003eG\u003c/strong\u003e), Noxa (\u003cstrong\u003eH\u003c/strong\u003e) or non-targeting siRNA and incubated for 24h. CHOP and Noxa were measured by qPCR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eI)\u003c/strong\u003e After transfection with indicated siRNAs and 24h of glucose deprivation, whole cell extracts were analysed by immunoblotting. Representative western blots are shown for DR4, DR5, β-actin as loading control.\u003c/p\u003e\n\u003cp\u003eStatistical analysis performed using One-way ANOVA with multiple comparison test within samples (n=2-3).\u003c/p\u003e","description":"","filename":"FigureS3.tif","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/76a798470435055aa090572a.tif"},{"id":95042783,"identity":"b6f542d4-1c5e-4f6e-acaa-565e6cba911b","added_by":"auto","created_at":"2025-11-03 16:21:14","extension":"tif","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":280610,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS4.tif","url":"https://assets-eu.researchsquare.com/files/rs-7829324/v1/c6eb174f2484b728c88f35b6.tif"}],"financialInterests":"There is a duality of interest","formattedTitle":"ATF4 and ATF6 produce diverse transcriptional signatures affecting metabolic genes and cell death under glucose deprivation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTumours cells are frequently stressed due to their high metabolic needs and the exhaustion of nutrients in the microenvironment. Lung adenocarcinoma, which is the most common subtype of non-small cell lung carcinoma (NSCLC), has been shown to be capable of dealing with and adapt to metabolic stress through constitutive activation of the ISR (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This stress response partially overlaps with the PERK branch of the Unfolded Protein Response (UPR), which responds to protein stress and accumulation of misfolded proteins in the endoplasmic reticulum (ER). Several consequences of nutrient shortage converge towards the activation of the UPR (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). For instance, a decrease in ATP levels reduces SERCa\u003csup\u003e2+\u003c/sup\u003e pump activity and chaperone functionality (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). NADPH and glutathione deficiency cause impairment of redox homeostasis also leading to protein misfolding. Moreover, in response to low glucose, impaired N-glycosylation generated by a reduction in sugar donors affects proper glycoprotein folding (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe accumulation of misfolded proteins in the endoplasmic reticulum (ER) activates three transmembrane ER stress sensors: Protein Kinase RNA-like ER kinase (PERK), the kinase/endonuclease Inositol-Requiring Enzyme 1 (IRE) 1, and Activating Transcription Factor (ATF) 6α. Dissociation of these sensors from the chaperone-binding immunoglobulin protein BiP (also known as GRP78) activates them and initiates the three distinct branches of the UPR (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). During stress, PERK phosphorylates eIF2α, which reduces overall protein synthesis while selectively increases the translation of specific adaptive response mRNAs, such as ATF4. In turn, this activates target gene like CHOP, which help coordinate the stress response (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). ATF6α dissociation from BiP, and changes in redox status with the participation of PDIA5 and ERp18, promote its traffic to Golgi, where is cleaved by S1/S2 proteases to release its active form (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). ATF6α hypo-glycosylation also promotes its activation (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). IRE1 activation promotes the splicing of X-box Binding Protein 1 (XBP1) mRNA, producing the active transcription factor XBP1s, which promotes cell survival. Additionally, the RNase activity of IRE1 also contributes to reducing the protein load though IRE1-Dependent Decay (RIDD) of mRNA, which degrades selected mRNAs (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe canonical function of the UPR is to restore proteostasis and ER homeostasis upon stress by enhancing ER-associated degradation of misfolded proteins, increasing ER folding capacity and attenuating protein synthesis to reduce the ER load (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). If the adaptation is successful, the cell resumes function at an elevated homeostatic state. However, if adaptation fails, unresolvable ER stress and chronic UPR activation leads to cell death (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Since NSCLC cells are highly dependent on glucose for their growth, we aimed to characterize their response to glucose deprivation by analysing transcriptomic changes upon glucose removal. We investigated whether starvation-induced and/or ATF4/ATF6-mediated transcriptional programs are required for NSCLC cell survival or other adaptation mechanisms to cope with metabolic stress.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eCell Lines and Treatments\u003c/h2\u003e\u003cp\u003eA panel of non-small cell lung cancer (NSCLC) cells was used: the lung adenocarcinoma (LUAD) cell line A549 (ATCC), lung squamous carcinoma (LUSC), SW900 (ATCC), and large cell lung cancer cell lines H1299, (gifted by Montserrat Sanchez Cespedes) and H460 (ATCC). A549 and H1299 cells were cultured in pyruvate-free high-glucose DMEM (25mM Glc); SW900 and H460 cells were cultured in RPMI-1640 medium (10mM Glc). Cells were supplemented with 10% FBS and 2mM L-glutamine and incubated at 37\u0026deg;C in a 5% CO\u003csub\u003e2\u003c/sub\u003e atmosphere.\u003c/p\u003e\u003cp\u003eGlucose deprivation experiments were performed by seeding 300,000 cells per well for A549, H1299 and H460, or 600,000 cells per well for SW900, in 6-well plates. Next day, or 48h later in case of transfection (see below), they were washed twice with FBS-pyruvate-and glucose-free DMEM or RPMI media and incubated with its respective glucose-free media (-Glc), while the control cells were supplemented with 25mM or 10mM Glc (+\u0026thinsp;Glc). Both conditions were supplemented with 10% dialysed FBS (dFBS) and 2mM L-glutamine. For FBS dialysis, the dialyzing membrane (SERVA) was prepared according to the manufacturer\u0026rsquo;s recommendations and filled with FBS. The pipe was washed twice for 1h and once overnight in 1L of PBS at 4\u0026deg;C with continuous stirring, and further filtered for sterilization. For H460 treatments, non-dialysed 10% FBS was used to avoid excessive cell death.\u003c/p\u003e\u003cp\u003eMKC8866 (Selleckchem) was diluted in media at 10\u0026micro;M and added to the cells one hour prior to medium change, and readded at the same concentration in glucose deprivation medium.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eWestern Blot\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eWestern Blot\u003c/div\u003e\u003cp\u003eCells were collected and lysed in RIPA buffer (ThermoFisher) supplemented with protease and phosphatase inhibitors (Roche). Proteins were quantified by the BCA assay Kit (Pierce, Cultek). 30 micrograms of protein per sample were loaded in acrylamide gels. Proteins were transferred to nitrocellulose membranes which were blocked in 5% non-fat dry milk in TBS-T (0.1 M Tris-HCl; 1.5 M NaCl; 0.1% Tween-20, pH 7.5). Membranes were incubated with the primary antibody for 2 hours at room temperature or overnight at 4\u0026deg;C in 2.5% milk in TBS-T. Primary antibodies were diluted 1:1000 except for β-actin, which were diluted 1:2000. Membranes were developed using freshly prepared ECL reagent (Promega) with the Amersham 600 Imager (Life Science). Proteins bands were then quantified using ImageJ (Version 1.50i) and values were normalised to β-actin. Fold change was calculated by normalizing against each control in each experiment. Antibodies are described in \u003cb\u003eSupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e\n\u003ch3\u003eTransfection with Small Interfering RNA (siRNA)\u003c/h3\u003e\n\u003cp\u003eFor siRNA transfections, cells were seeded in 6-well plates, trypsinised and transfected while plated with a transfection mixture of unsupplemented media with 1\u0026micro;L/mL DharmaFECT and either non-targeting (NT) siRNA, ATF4-targeting siRNA, or ATF6-targeting siRNA at a final concentration of 100nM siRNA. 24h later cells were trypsinised and plated in two wells, and 24h later, cells were washed, and medium was replaced with glucose deprivation medium. Transfections with CHOP, DR5 and DR4 used the same protocol, while Noxa and XBP1-targeting siRNAs were incubated for 24h and not trypsinized. Sequences are listed in \u003cb\u003eSupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e\n\u003ch3\u003eGene Expression Analysis\u003c/h3\u003e\n\u003cp\u003eRNA was extracted using the PureLink RNA Mini Kit (Invitrogen, ThermoFisher), following the manufacturer\u0026rsquo;s instructions. One microgram of RNA per sample was retrotranscribed into cDNA using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Invitrogen). For each experiment, quantitative PCR (qPCR) reactions were performed in duplicate using the LightCycler 480 SYBR green (Roche). Each reaction contained 10ng of cDNA, 1mM of primer mix (forward and reverse) and PowerUp SYBR Green Master mix (Applied Biosystems, Invitrogen). CT values were determined and normalised to \u003cem\u003eL32\u003c/em\u003e as the housekeeping gene. Fold changes were calculated relative to the control sample.\u003c/p\u003e\n\u003ch3\u003eDifferential expression and Gene Set Enrichment Analysis (GSEA)\u003c/h3\u003e\n\u003cp\u003eRNAseq was performed on mRNA from A549 cells. 3 biological replicates were used. Differentially expressed genes (DEGs) were identified using the DESeq2 package in R (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Differentially expressed genes were considered significant with an adjusted \u003cem\u003ep\u003c/em\u003e-value (padj)\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eGene Set Enrichment Analysis (GSEA) was conducted using the fgsea package(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) and gene sets from the Reactome pathways collection, available at MSigDB resource (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Enrichment was considered significant for gene sets with an adjusted \u003cem\u003ep\u003c/em\u003e-value (padj)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eTranscription factor network inference and motif enrichment analysis\u003c/h2\u003e\u003cp\u003eDecoupleR package (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and Dorothea (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) gene regulatory network database (i.e., signed transcription factor - target gene interactions) were used for inference of relative transcription factor network activity versus its control.\u003c/p\u003e\u003cp\u003eMotif enrichment analysis was performed using the marge R package (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), which provides an interface to the HOMER motif discovery framework (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Target promoter regions were supplied as BED files representing differential expressed genes identified in each comparison. The package identifies known enriched motifs in those target sequences, relative to a genomic background set, which in this case corresponds to all promoter regions of all genes measured in the RNA-Seq experiment.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCell Death Measurement\u003c/h3\u003e\n\u003cp\u003eCells were trypsinised using a 0.05% trypsin EDTA solution at 37\u0026ordm;C and collected with their supernatants and the PBS used for washing. Cells were centrifuged for 5 min at 450g and resuspended in 300\u0026micro;l PBS containing 0.5\u0026micro;l/ml propidium iodide (PI). The percentage of PI positive cells were measured with the Gallios Flow Cytometer Beckman Coulter\u0026copy;, and the quantification was done using the Kaluza Analysis Software version 2.1. Data is shown as the percentage of PI positive cells\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM.\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eSignificance of the experimental data was calculated using Two-way ANOVA followed by Tukey\u0026rsquo;s multiple comparison test and performed using Prism GraphPad. Error bars represent the SEM. The significance was indicated as follows: P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, one asterisk (*); P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, two asterisks (**); P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, three asterisks (***), P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, four asterisks (****).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eGlucose deprivation induces the Unfolded Protein Response in NSCLC\u003c/h2\u003e\u003cp\u003eGlucose is an essential nutrient for tumour cells, and we aim to decipher how NSCLC adapt to low glucose conditions. To address this, we cultured A549 cells in either glucose-free (-Glc) or glucose-rich (+\u0026thinsp;Glc) media for 6 or 16 hours, and analysed their transcriptomes. Gene-Set Enrichment Analysis (GSEA) using Reactome revealed that the pathways downregulated upon starvation (negative normalised enrichment score (NES), were related to DNA synthesis, replication and mitosis, and collectively mainly involved in cell replication (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, \u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA, Supplementary file 1\u003c/b\u003e). When we analysed the upregulated pathways (positive NES), we found that the \u0026ldquo;UPR\u0026rdquo; was the most upregulated pathway when comparing cells without glucose with the control cells, both at 6 and 16h (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, \u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB, Supplementary file 1\u003c/b\u003e). Other pathways related to the UPR like those related to gene regulation by PERK, IRE1alpha and GCN2 were also upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, \u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB, Supplementary file 1\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo verify induction of the UPR in cells exposed to low glucose, we characterised the kinetic response to glucose deprivation in A549 cells. PERK displayed reduced electrophoretic mobility, indicative of increased phosphorylation, as early as 3 hours after glucose deprivation, compared to cells maintained in glucose-rich medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). An accumulation of ATF4 and CHOP proteins was detected 3\u0026ndash;6 hours post glucose removal (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). A consistent increase in \u003cem\u003ePERK\u003c/em\u003e, \u003cem\u003eATF4\u003c/em\u003e and \u003cem\u003eDDTI3\u003c/em\u003e (CHOP) mRNA was observed in glucose starved A549 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). ATF6 activation was assessed by proteolysis. A decrease in the p90ATF6 band, accompanied by accumulation of the cleaved p50ATF6 fragment, was detected from 6 hours after glucose deprivation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). A shift in p90ATF6 was also observed, possibly indicating its hypo-glycosylation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). \u003cem\u003eATF6\u003c/em\u003e mRNA levels did not increase upon glucose deprivation at the times measured (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). The third main branch of the UPR, IRE1/XBP1, was also activated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD-E). An increase in the spliced \u003cem\u003eXBP1\u003c/em\u003e mRNA variant (\u003cem\u003eXBP1s\u003c/em\u003e) was observed as an indicator of IRE1 endonuclease activation, together with an increment in \u003cem\u003eIRE1\u003c/em\u003e mRNA expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD-E).\u003c/p\u003e\u003cp\u003eAlthough the UPR induction kinetics changed in four NSCLC cell lines (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC-H\u003c/b\u003e), glucose removal was sufficient to induce the three branches of the UPR in all cases (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC-H\u003c/b\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eATF4 and ATF6 control the transcriptional response to glucose removal\u003c/h2\u003e\u003cp\u003eWe further looked for transcription factors regulated by glucose by using inference methods based on gene enrichment analysis and the Dorothea database (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The analysis of the transcriptional networks downregulated by glucose deprivation showed myc-n and several E2F factors among the most downregulated in the absence of glucose, while ATF6 and ATF4 networks were the most upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Additional networks of metabolic stress-related transcription factors such as HIF1A, p53 or FOXO3 were also upregulated upon glucose deprivation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). However, their increase was not as pronounced as that of the UPR factors. We therefore examined the contribution of ATF4 and ATF6 to the transcriptional response induced by glucose deprivation by silencing them using siRNA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-C).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe analysed the subset of differentially expressed genes that were upregulated under glucose deprivation and their regulation by ATF4 or ATF6 (\u003cb\u003eSupplementary file 2\u003c/b\u003e). After 16h without glucose, 4176 genes were upregulated; from these, 367 (8.78%) were downregulated by silencing ATF4, and 744 (17.8%) were downregulated by silencing ATF6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). The presence of ATF4 and ATF6 during glucose deprivation also affected levels of many genes reduced by glucose deprivation; that is, when ATF4 or ATF6 (or both) were present, the downregulation of many genes was prevented (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eReactome pathway enrichment analysis revealed significant changes upon glucose deprivation and their modulation by siRNA-mediated knockdown of ATF4 or ATF6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). A total of 51 pathways were upregulated at 6 and 16 hours of starvation, while 63 and 153 pathways were downregulated at 6 and 16 hours, respectively (\u003cb\u003eSupplementary file 1\u003c/b\u003e). ATF4 and ATF6 contributed to the activation of several pathways (red in the Glc columns that turn blue in the siRNA columns), as well as the reversal of starvation downregulated pathways (blue in Glc columns that turn red in siRNAs columns) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eF, \u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e and Supplementary file 1\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSince ATF4 and ATF6 work as positive regulators of gene expression, we aimed to understand whether they contributed to downregulate targets of other transcription factors, perhaps indirectly. For this, transcriptional network analysis was performed in cells subjected to glucose deprivation while depleted of ATF4 or ATF6. As expected, depletion of ATF4 led to downregulation of the ATF4 transcriptional network, and depletion of ATF6 led to downregulation of the ATF6 transcriptional network (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eG-H). In both cases, myc networks and those of several E2F transcription factors, whose transcriptional networks were downregulated without glucose (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), were now upregulated compared to glucose-deprived samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eG-H). This suggested that the presence of ATF4 or ATF6 provides signals or nutrients that prevent these proliferating cells from shutting down transcription of genes involved in cycling when glucose is absent.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eRegulation of stress and metabolic pathways by ATF4 and ATF6\u003c/h2\u003e\u003cp\u003ePathways upregulated by glucose deprivation which were downregulated by ATF4 or ATF6 siRNAs are likely to represent the cellular functions of active ATF4 and ATF6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Several of these pathways were related to stress responses, including the UPR and the \u0026ldquo;cellular response to starvation\u0026rdquo; (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Among them, we found some pathways related to translation and to protein synthesis and modification in the ER-Golgi. Two pathways related to glycosylation were regulated by ATF6 (\u0026ldquo;Asparagine linked N-glycosylation\u0026rdquo; and \u0026ldquo;N-glycan trimming in the ER and calnexin/calreticulin cycle\u0026rdquo;), consistent with known roles of ATF6 in ER homeostasis (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eCells deprived of glucose switch to alternative nutrient usage by mitochondrial metabolism (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Reactome analysis indicated that indeed, glucose deprivation upregulated transcriptionally some pathways related to mitochondrial respiration and the TCA. These pathways were regulated by ATF4 but not ATF6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). On the other hand, \u0026ldquo;glucose metabolism\u0026rdquo; and \u0026ldquo;glycolysis\u0026rdquo; pathways were downregulated by glucose starvation, while the lack of ATF6 or ATF4 reversed this downregulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). The \u0026ldquo;carbohydrate metabolism\u0026rdquo; pathway downregulated by ATF6 siRNA after 16h of glucose deprivation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) included mostly glycosaminoglycan modification enzymes (\u003cb\u003eSupplementary file 2\u003c/b\u003e). Both siRNAs increased nucleotide metabolism related pathways, although glucose deprivation did not significantly regulate this pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Additionally, several pathways related to amino acid metabolism and transport were induced transcriptionally during starvation, with some of them being regulated by ATF4, ATF6 or both (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eRegardless of their regulation by glucose, we observed regulation of multiple lipid-related metabolic pathways by ATF4 and ATF6, with substantial co-regulation at the pathway level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D). For instance, \u0026ldquo;glycerophospholipid biosynthesis\u0026rdquo;, and SREBP-mediated transcription were downregulated in the absence of either ATF4 or ATF6 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eATF4, but not ATF6, CHOP or XBP1, promoted glucose-starvation induced cell death\u003c/h2\u003e\u003cp\u003eNSCLC cell lines were sensitive to glucose deprivation, and cell death was apparent within 24-48h, with different kinetics (\u003cb\u003eFigure S3A-B\u003c/b\u003e). We explored whether Reactome pathways associated to cell death were significantly induced upon glucose deprivation, but only \u0026ldquo;regulation of TNFR1 signalling\u0026rdquo; was upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, \u003cb\u003eSupplementary file 2\u003c/b\u003e). However, regardless of their regulation by glucose, several Reactome pathways related to cell death were regulated by ATF4 and/or ATF6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Therefore, we investigated whether expression of ATF4 or ATF6 might contribute to the adaptative survival response. In all cell lines tested, instead of sensitizing to cell death, ATF4 knockdown significantly reduced cell death induced by glucose deprivation (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-E). ATF6 knockdown had no significant effect on cell death rate (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-E). The third well studied UPR pathway, the IRE1/XBP1s axis, also did not appear to contribute to glucose deprivation-induced cell death in A549 cells, as neither pharmacological inhibition of IRE1 using MKC8866 nor XBP1 silencing affected cell death after 48h in glucose-starved A549 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eE-F\u003cb\u003e)\u003c/b\u003e. However, both approaches effectively reduced XBP1 mRNA splicing and downregulated the mRNA of the XBP1s target gene AGR2 (\u003cb\u003eFigure S3D-G\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe wondered whether the stimulation of cell death by ATF4 occurred through CHOP expression, since glucose starvation induced CHOP expression by 20\u0026ndash;50 fold in NSCLC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D, \u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/b\u003e. CHOP was silenced using siRNA (\u003cb\u003eFigure S3G\u003c/b\u003e), and cell death was measured in A549 cells after 48h of glucose starvation. The results showed that CHOP knockdown did not protect cells from death (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eH).\u003c/p\u003e\u003cp\u003eAdditionally, we found that both ATF4 and ATF6 regulated \u003cem\u003eCHOP\u003c/em\u003e mRNA and protein expression under glucose deprivation in A549 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eI-K). A similar trend was observed in other cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eL), with a significant effect observed in SW900 cells, where \u003cem\u003eCHOP\u003c/em\u003e mRNA levels were reduced after 16h of glucose deprivation in the absence of ATF6. Together, these results indicated that CHOP is co-regulated by ATF4 and ATF6, and that ATF4 does not mediate cell death under glucose deprivation through CHOP.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eATF4 regulates apoptotic genes with minor or no involvement in cell death by glucose deprivation\u003c/h2\u003e\u003cp\u003eTo further explore the pro-death role of ATF4 in starvation-induced cell death, we selected, from the RNA-sequencing experiment, genes related with cell death that were differentially regulated by glucose deprivation, ATF4, or ATF6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Known ATF4 targets that were elevated during starvation and may contribute to cell death during glucose starvation were the BH3-only protein Noxa (gene name \u003cem\u003ePMAIP1\u003c/em\u003e) and both TRAIL death receptors (TNFRSF10A/TRAIL-R1/DR4 and TNFRSF10B/TRAIL-R2/DR5). Additionally, ATF6 also downregulated Noxa (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNoxa and both TRAIL receptors, DR4 and DR5, were also upregulated at the protein level in A549 cells upon glucose deprivation (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-C), while only Noxa and DR5 were regulated transcriptionally at the times measured when measured by qPCR, contrasting with the mild upregulation of DR4 mRNA in the RNAseq (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eD-F). ATF4 regulated Noxa and DR5 \u003cem\u003e(TNFRSF10B)\u003c/em\u003e but not DR4 (\u003cem\u003eTNFRSF10A\u003c/em\u003e) mRNA expression, while ATF6 did not regulate these proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eG-I). In this line, we assessed if these proteins participate in cell death of A549 cells by silencing them using siRNA and measuring cell death after 48h of glucose deprivation \u003cb\u003e(Figure S3H-I\u003c/b\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ-L\u003cb\u003e)\u003c/b\u003e. The results showed a small reduction in the percentage of PI-positive cells in DR5-silenced cells compared to non-targeting control (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eK). DR4 or Noxa knockdown did not affect the cell death rate in glucose-starved A549, although there was a trend towards a small reduction (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ, L). In A549, starvation-induced cell death was not only apoptotic, since pan-caspase inhibitors (Q-VD, and z-VAD) only partially reversed cell death (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eM). This could explain the small effect of the knockdown of these apoptotic proteins, which mediate apoptosis induced by glucose deprivation in other contexts.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eATF4 and ATF6 cooperate in gene transcription but also show antagonism in gene subsets\u003c/h2\u003e\u003cp\u003eTo try to further explain the discrepancies in the effects of ATF4 and ATF6 in cell death, we analysed individual genes regulated by ATF4 and ATF6 within the subset of genes induced by glucose deprivation. 166 genes were downregulated by either siRNA, and 43 genes were upregulated by silencing either ATF4 or ATF6. For instance, both transcription factors negatively regulated the NF-kappaB target genes \u003cem\u003eIL6\u003c/em\u003e and \u003cem\u003eBL2L1\u003c/em\u003e (Bcl-X), and the transcription factor \u003cem\u003eMYC\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Both ATF4 and ATF6 regulated positively the levels of some known ATF4 targets like \u003cem\u003eLCN2\u003c/em\u003e (lipocalin 2) and the amino-acyl tRNA synthetase \u003cem\u003eWARS1\u003c/em\u003e, as well as genes involved in amino acid metabolism like \u003cem\u003eBCAT1\u003c/em\u003e and \u003cem\u003eARG2\u003c/em\u003e, and the IL-6 receptor family \u003cem\u003eLIFR\u003c/em\u003e \u003cb\u003e(Supplementary file 2)\u003c/b\u003e. Analysis of enrichment of transcription factor binding sites in the promoters of these genes suggested that the co-regulation of some of these genes may occur via CHOP, a target of ATF4 and ATF6 (\u003cb\u003eFigure S5A\u003c/b\u003e). 6 genes were upregulated following ATF4 knockdown but downregulated by ATF6 knockdown \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e Interestingly, 35 genes were upregulated by ATF6 knockdown and downregulated by ATF4 silencing. This subset included some known ATF4 targets, and the genes were enriched in ATF4 binding sites (\u003cb\u003eFigure S5B\u003c/b\u003e). This suggested that ATF4 is further activated in the absence of ATF6 function. This could be due to the absence of ATF6 further enhancing ER stress, since ATF6 target genes participate in protein folding and glycan quality control (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Many of these known ATF6 target genes were regulated glucose and ATF6 but not ATF4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSilencing ATF6 further stimulates ATF4 and XBP1s induction.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSince many known ATF4 target genes, as well as \u003cem\u003eATF4\u003c/em\u003e itself, were upregulated upon ATF6 knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eB \u003cb\u003eand Supplementary file 2 and 3\u003c/b\u003e), we further explored a possible antagonism between ATF4 and ATF6, which has been described between several branches of the UPR as \u0026ldquo;compensatory activation\u0026rdquo;. To this end, we performed siRNA-mediated knock-down of each factor and analysed their reciprocal effects after 6 or 16 hours of glucose deprivation (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the absence of ATF6, several cell lines showed a trend toward increased ATF4 mRNA and protein accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-F). A significant increase in ATF4 protein levels following ATF6 silencing was detected at 6h in A549 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-B). ATF4 mRNA significantly increases after 16h of glucose deprivation in H460 and A549 cells, while in H1299, the increase was observed after 6h (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e7\u003c/span\u003eC-F). Consistent with previous reports (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), ATF6 downregulation increased XBP1 splicing (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e7\u003c/span\u003eG-J). After 16h of glucose deprivation, XBP1s mRNA levels significantly increased in A549 and H460 cells, with a similar albeit not significant trend observed in H1299 and SW900 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e7\u003c/span\u003eG-J).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe tumour microenvironment is characterized by low nutrient availability, primarily because of the high proliferation rate of cancer cells. Despite these adverse conditions, cancer cells exhibit remarkable adaptability, enabling them to survive in hypoxic and hypoglycaemic environments. Glucose is highly important for cancer cells, and our research focuses on the response of NSCLC cells to glucose deprivation. We demonstrate that glucose deprivation activates the UPR in four distinct NSCLC cell lines. Previous studies have established that glucose deprivation alone is sufficient to trigger the UPR. ATF6 activation in response to glucose starvation was comprehensively characterised by Nadanaka \u003cem\u003eet al\u003c/em\u003e. (\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e). Furthermore, activation of the IRE1 and PERK branches of the UPR has been documented in cortical neuron cultures subjected to oxygen-glucose deprivation (\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e). UPR induction, along with mTOR inactivation, was also observed in glucose-starved NSCLC cells, like A549, in which ATF4 regulated cytokine production (\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eATF6 and ATF4 were the primary transcriptional regulators upon glucose deprivation in A549 cells. Both regulated several stress responses and metabolic pathways. An extensive overlap was observed among the pathways regulated by both factors. This overlap could be attributed to the number of co-regulated genes or to the fact that some genes regulated specifically by ATF4 or ATF6 are involved in the same pathways. In addition, several genes co-regulated by both were CHOP targets, suggesting indirect regulation. Whether ATF4 and ATF6 contribute directly, as transcription factors, to many of the pathways analysed here, or indirectly through restoration of general homeostasis should be further analysed.\u003c/p\u003e\n\u003cp\u003eNevertheless, several pathways were regulated specifically by ATF4 or ATF6. ATF4 regulates mitochondrial respiration, TCA and amino acid metabolism as described (\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e). ATF6 regulated several pathways related to translation and N-glycosylation and protein synthesis and modification in the ER-Golgi, consistent with known roles of ATF6 in ER homeostasis (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e). This may possibly reflect an attempt of ATF6 to restoring N-glycosylation, which is reduced when glucose levels are down (Luciano-Mateo et al, under revision)(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e). Pathways associated with lipid metabolism, cholesterol synthesis, and the activation of the SREBP response were downregulated when ATF4 or ATF6 were absent in glucose-starved cells. SREBP has been described to cooperate with ATF4 and ATF6 biosynthetic networks (\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e). Our data further support an underexplored role of ATF4 and ATF6 on lipid metabolism. The data also indicated a previously unappreciated regulation of SLC mediated membrane transport by ATF6.\u003c/p\u003e\n\u003cp\u003eConsidering the relevance of ATF4 and ATF6 activation we investigated whether they regulate cell survival or cell death under glucose deprivation. We observed that ATF4 promotes cell death under glucose starvation in NSCLC cells, while ATF6 and XBP1s had little or no effect on cell death or survival. Interestingly, the ATF4 targets CHOP, Noxa and DR4 (TRAIL-R1) did not mediate cell death, which was only partially dependent on TRAIL-R2 (DR5) and only partially prevented by caspase inhibitors. Our groups and others had also previously shown ATF4-mediated regulation of non-apoptotic cell death induced by glucose deprivation (\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e). On the other hand, the role of ATF4 and TRAIL-R2 (DR5) in starvation-induced cell death was previously described. In HeLa cells, glucose starvation leads to ATF4-mediated, non-transcriptional accumulation of TRAIL-R2 (DR5), which in turn participates in ligand-independent apoptosis (\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e). The regulation of DR5 in response to ER stressors is shaped by the interplay between the PERK and IRE1 branches of the UPR (\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e). A549 cell death was only partially apoptotic, which may explain the modest reduction in overall cell death observed following DR5 knockdown. CHOP overexpression has been shown to sensitize multiple cell lines to ER stress, among other reasons, by downregulating Bcl2 expression (\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e). In our study, CHOP knockdown did not reduce cell death in starved A549 cells. Moreover, CHOP expression was modulated by both ATF4 and ATF6. CHOP co-regulation by both transcription factors had been previously described (\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003eOur results, consistent with previous studies, revealed that ATF4 is a key regulator of amino acid synthesis pathways. For instance, Torrence et al. demonstrated that ATF4 regulates amino acid metabolism both in the context of ER stress and mTORC1 anabolic signalling (\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e). In the context of glucose deprivation, we observed that ATF4 regulated a set of metabolic genes such as \u003cem\u003ePCK2\u003c/em\u003e, \u003cem\u003ePHGDH, PSAT1, ASNS, that\u003c/em\u003e coordinate central carbon metabolism and amino acid biosynthesis (\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e). The glutamine transporter SLC1A5 was also regulated by ATF4. Another one-carbon metabolism enzyme regulated by ATF4 was MTHFD2, which participates in nucleotide metabolism (\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e). ATF4 affects cellular bioenergetics, rerouting carbon utilization towards amino acid production, as recently reported by Labbe \u003cem\u003eet al\u003c/em\u003e. in a non-stress ISR setting based on PERK activation (\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e).This leads us to hypothesize that the pro-death role of ATF4 during nutrient deprivation may be linked to further metabolite depletion. ATF4 regulates genes involved in extracting remaining cellular nutrients, such as residual glucose or glucose derived from glycogen, and could be channelling these resources toward amino acid biosynthesis. Metabolic studies should be performed in the future to understand if (and what) key metabolites are depleted by ATF4 that prevent cell death by glucose deprivation, which could include glutamate (\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eConversely, ATF6 and IRE1/XBP1 did not contribute to cell death under glucose starvation in the evaluated NSCLC cell lines. However, those factors had historically been described as pro-survival as its major targets contribute to enhanced ER capacity (\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e). Our transcriptomic analysis of starved ATF6-knockdown cells confirmed that ATF6 regulates several chaperones and ER-resident proteins. ATF6 is a transcription factor specialized in the regulation of quality control proteins within the ER (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e). Although ATF6 and XBP1 frequently function cooperatively, a stress-independent activation model demonstrated that ATF6 alone is sufficient to regulate ER major chaperones, including BiP, Sel1L, and calreticulin (\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn our study, ATF6 knockdown resulted in a \u0026ldquo;compensatory\u0026rdquo; upregulation of ATF4 and XBP1. Pharmacological inhibition of site-1-protease (S1P), which inhibits ATF6 cleavage, enhances activation of both IRE1 and PERK (49). Similar results were shown upon tunicamycin treatment in ATF6 knockout cells (50). In mice without any of the two isoforms of ATF6 in pancreatic \u0026beta; cells or in the embryonic brain, overactivation of IRE1\u0026alpha; and PERK has also been also described (45,46). Therefore, in the absence of ATF6, ER stress is exacerbated, possibly due to insufficient production of ER chaperones, leading to earlier and/or more robust activation of both the PERK/ATF4 and IRE1/XBP1 pathways (\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn conclusion, our findings demonstrate that lung cancer cells react to glucose deprivation through a complex interplay of UPR pathways, with ATF6 and ATF4 as the primary transcriptional regulators. Together, ATF4 and ATF6 may contribute to cellular adaptation by regulating metabolic genes, although this is not reflected in increased survival to acute glucose deprivation \u003cem\u003ein vitro\u003c/em\u003e. Both factors co-regulated several genes, including CHOP. Moreover, our findings reveal an underappreciated crosstalk among UPR branches: ATF6 represses or delays ATF4 induction. Understanding these pathways not only expands our knowledge of cancer cell plasticity under metabolic stress but also highlights potential therapeutic targets to disrupt these adaptive responses.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eATF4, Activating Transcription Factor 4\u003c/p\u003e\n\u003cp\u003eATF6, Activating Transcription Factor 6\u003c/p\u003e\n\u003cp\u003eBiP, Binding immunoglobulin protein\u003c/p\u003e\n\u003cp\u003eCHOP, CCAAT-enhancer-binding protein Homologous Protein\u003c/p\u003e\n\u003cp\u003eeIF2, Eukaryotic Initiation Factor 2 (B, beta or A, alpha)\u003c/p\u003e\n\u003cp\u003eER, Endoplasmic Reticulum\u003c/p\u003e\n\u003cp\u003eERAD, ER-associated degradation\u003c/p\u003e\n\u003cp\u003eGSEA, Gene-Set Enrichment Analysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGlc, Glucose\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIRE1, Inositol-Requiring Enzyme 1\u003c/p\u003e\n\u003cp\u003eISR, Integrated Stress Response\u003c/p\u003e\n\u003cp\u003emTORC1, mammalian Target of Rapamycin Complex 1\u003c/p\u003e\n\u003cp\u003ePERK, PKR-like Endoplasmic Reticulum Kinase\u003c/p\u003e\n\u003cp\u003eSREBP, Sterol Regulatory Element Binding Protein\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUPR, Unfolded Protein Response\u003c/p\u003e\n\u003cp\u003eXBP1, X-box Binding Protein 1\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank CERCA Programme / Generalitat de Catalunya for institutional support. This study has been funded by Ministerio de Ciencia e Innovación y Universidades (MCIN/AEI, DOI:10.13039/501100011033), through the Generación de Conocimiento grant numbers PID2022-140457OB-I00 and PID2019-107213GB-I00, and by the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie Grant Agreements 675448 (TRAINERS) and 766214 (META-CAN). M.Cruz-Rodríguez was supported by AGAUR (Co-funded by European Social Fund. ESF investing in your future) 2021FI_B 00485. D. Palau-Gallinat was supported with funding of the INVESTIGO 2024 program from AGAUR. S. P-M has received funding from FPU grant agreement FPU21/06884. EC’s lab was funded by grants from INCa (PLBIO) and FRM (EQU202403018041). E. Nadal received support from Instituto de Salud Carlos III (PI21/00789, PI24/00702 and INT22/00066), co-funded by European Regional Development Fund (ERDF), a way to build Europe.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Eric Eldering (AMC) and Ingrid Derks for a non-included MLPA analysis. Grammarly AI was used as text editor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEric Chevet is the founder of Thabor Tx (www.thabor-tx.com), and Ernest Nadal has had research funding from Roche, Pfizer, Merck-Serono, Bristol Myers Squibb. Advisory board and consulting: Amgen, Apollomics, AstraZeneca, BeiGene, BMS, Boehringer-Ingelheim, Daiichi-Sankyo, Genmab, Johnson \u0026amp; Johnson, Lilly, Merck Sharp \u0026amp; Dohme (MSD), Merck-Serono, Pfizer, Pierre Fabre, Qiagen, Regeneron, Roche, Sanofi and Takeda. Honoraria for lectures: Amgen, AstraZeneca, BeiGene, BMS, Boehringer-Ingelheim, Daiichi-Sankyo, Illumina, Johnson \u0026amp; Johnson, Lilly, Merck Sharp \u0026amp; Dohme (MSD), Merck-Serono, Pfizer, Pierre Fabre, Qiagen, Regeneron, Roche, Sanofi and Takeda. Travel support: Roche, Takeda, Johnson and Johnson, and MSD.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGhaddar N, Wang S, Woodvine B, Krishnamoorthy J, van Hoef V, Darini C, et al. The integrated stress response is tumorigenic and constitutes a therapeutic liability in KRAS-driven lung cancer. Nat Commun. 2021;12(1).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCruz-Rodr\u0026iacute;guez M, Chevet E, Mu\u0026ntilde;oz-Pinedo C. Glucose sensing and the unfolded protein response. FEBS Journal. 2025;\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoore CE, Omikorede O, Gomez E, Willars GB, Herbert TP. PERK activation at low glucose concentration is mediated by SERCA pump inhibition and confers preemptive cytoprotection to pancreatic β-cells. Molecular Endocrinology. 2011;25(2):315\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKopp MC, Larburu N, Durairaj V, Adams CJ, Ali MMU. UPR proteins IRE1 and PERK switch BiP from chaperone to ER stress sensor. Nat Struct Mol Biol [Internet]. 2019;26(11):1053\u0026ndash;62. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41594-019-0324-9\u003c/span\u003e\u003cspan address=\"10.1038/s41594-019-0324-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUppala JK, Ghosh C, Sathe L, Dey M. Phosphorylation of translation initiation factor eIF2α at Ser51 depends on site- and context-specific information. FEBS Lett. 2018;592(18):3116\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiao W, Sun Y, Xu J, Zhang N, Dong L. uORF-Mediated Translational Regulation of ATF4 Serves as an Evolutionarily Conserved Mechanism Contributing to Non-Small-Cell Lung Cancer (NSCLC) and Stress Response. J Mol Evol [Internet]. 2022;90(5):375\u0026ndash;88. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://link.springer.com/\u003c/span\u003e\u003cspan address=\"https://link.springer.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00239-022-10068-y\u003c/span\u003e\u003cspan address=\"10.1007/s00239-022-10068-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaze K, Yoshida H, Yanagi H, Yura T, Mori K. Mammalian transcription factor ATF6 is synthesized as a transmembrane protein and activated by proteolysis in response to endoplasmic reticulum stress. Mol Biol Cell. 1999;10(11):3787\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHiga A, Taouji S, Lhomond S, Jensen D, Fernandez-Zapico ME, Simpson JC, et al. Endoplasmic Reticulum Stress-Activated Transcription Factor ATF6α Requires the Disulfide Isomerase PDIA5 To Modulate Chemoresistance. Mol Cell Biol. 2014;34(10):1839\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOka OBV, Pierre AS, Pringle MA, Tungkum W, Cao Z, Fleming B, et al. Activation of the UPR sensor ATF6α is regulated by its redox-dependent dimerization and ER retention by ERp18. Proceedings of the National Academy of Sciences [Internet]. 2022;119(12). Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pnas.org/doi/full/10.1073/pnas.2122657119\u003c/span\u003e\u003cspan address=\"https://pnas.doi/full/10.1073/pnas.2122657119\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuan D, Wang H, Li VE, Xu Y, Yang M, Shen Z. N-glycosylation of ATF6β is essential for its proteolytic cleavage and transcriptional repressor function to ATF6α. J Cell Biochem. 2009;108(4).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdams CJ, Kopp MC, Larburu N, Nowak PR, Ali MMU. Structure and molecular mechanism of ER stress signaling by the unfolded protein response signal activator IRE1. Front Mol Biosci. 2019;6(MAR):1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa Y, Hendershot LM. The unfolding tale of the unfolded protein response. Cell. 2001;107(7):827\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIurlaro R, Mu\u0026ntilde;oz-Pinedo C. Cell death induced by endoplasmic reticulum stress. FEBS Journal. 2016;2640\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKorotkevich G, Sukhov V, Sergushichev A. fgsea: Fast Gene Set Enrichment Analysis. 2023;1\u0026ndash;29. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioconductor.org/packages/fgsea\u003c/span\u003e\u003cspan address=\"https://bioconductor.org/packages/fgsea\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSubramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMilacic M, Beavers D, Conley P, Gong C, Gillespie M, Griss J, et al. The Reactome Pathway Knowledgebase 2024. Nucleic Acids Res. 2024;52(D1):D672\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBadia-I-Mompel P, V\u0026eacute;lez Santiago J, Braunger J, Geiss C, Dimitrov D, M\u0026uuml;ller-Dott S, et al. decoupleR: ensemble of computational methods to infer biological activities from omics data. Bioinformatics Advances. 2022;2(1):1\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGarcia-Alonso L, Holland CH, Ibrahim MM, Turei D, Saez-Rodriguez J. Benchmark and integration of resources for the estimation of human transcription factor activities. Genome Res. 2019;29(8):1363\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmezquita RA. marge : An API for Analysis of Motifs Using HOMER in R [Internet]. 2018. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://biorxiv.org/lookup/doi/10.1101/249268\u003c/span\u003e\u003cspan address=\"http://biorxiv.org/lookup/doi/10.1101/249268\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHeinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell [Internet]. 2010;38(4):576\u0026ndash;89. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/pubmed/20513432\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/pubmed/20513432\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdachi Y, Yamamoto K, Okada T, Yoshida H, Harada A, Mori K. ATF6 is a transcription factor specializing in the regulation of quality control proteins in the endoplasmic reticulum. Cell Struct Funct. 2008;33(1):75\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBirsoy K, Possemato R, Lorbeer FK, Bayraktar EC, Thiru P, Yucel B. Metabolic determinants of cancer cell sensitivity to glucose limitation and biguanides. Nature [Internet]. 2014;508(7494):108\u0026ndash;12. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/nature13110\u003c/span\u003e\u003cspan address=\"10.1038/nature13110\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYoshida H, Matsui T, Yamamoto A, Okada T, Mori K. XBP1 mRNA Is Induced by ATF6 and Spliced by IRE1 in Response to ER Stress to Produce a Highly Active Transcription Factor. Cell. 2001;107:881\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNadanaka S, Yoshida H, Mori K. Reduction of disulfide bridges in the lumenal domain of ATF6 in response to glucose starvation. Cell Struct Funct. 2006;31(2):127\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBadiola N, Penas C, Mi\u0026ntilde;ano-Molina A, Barneda-Zahonero B, Fad\u0026oacute; R, S\u0026aacute;nchez-Opazo G, et al. Induction of ER stress in response to oxygen-glucose deprivation of cortical cultures involves the activation of the PERK and IRE-1 pathways and of caspase-12. Cell Death Dis [Internet]. 2011;2(4):e149\u0026ndash;e149. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nature.com/articles/cddis201131\u003c/span\u003e\u003cspan address=\"https://www.nature.com/articles/cddis201131\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePuschel F, Favaro F, Redondo-Pedraza J, Lucendo E, Iurlaro R, Marchetti S, et al. Starvation and antimetabolic therapy promote cytokine release and recruitment of immune cells. Proc Natl Acad Sci U S A. 2020;117(18):9932\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBalsa E, Soustek MS, Thomas A, Cogliati S, Garc\u0026iacute;a-Poyatos C, Mart\u0026iacute;n-Garc\u0026iacute;a E, et al. ER and Nutrient Stress Promote Assembly of Respiratory Chain Supercomplexes through the PERK-eIF2α Axis. Mol Cell. 2019;74(5):877\u0026ndash;890.e6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLabb\u0026eacute; K, LeBon L, King B, Vu N, Stoops EH, Ly N, et al. Specific activation of the integrated stress response uncovers regulation of central carbon metabolism and lipid droplet biogenesis. Nat Commun [Internet]. 2024;15(1):8301. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1038/s41467-024-52538-5\u003c/span\u003e\u003cspan address=\"10.1038/s41467-024-52538-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZeng L, Lu M, Mori K, Luo S, Lee AS, Zhu Y, et al. ATF6 modulates SREBP2-mediated lipogenesis. EMBO Journal. 2004;23(4):950\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCheng C, Ru P, Geng F, Liu J, Yoo JY, Wu X, et al. Glucose-Mediated N-glycosylation of SCAP Is Essential for SREBP-1 Activation and Tumor Growth. Cancer Cell. 2015;28(5):569\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen H, Yuan R, Zhang Y, Zhang X, Chen L, Zhou X, et al. ATF4 regulates SREBP1c expression to control fatty acids synthesis in 3T3-L1 adipocytes differentiation. Biochim Biophys Acta Gene Regul Mech [Internet]. 2016;1859(11):1459\u0026ndash;69. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.bbagrm.2016.07.010\u003c/span\u003e\u003cspan address=\"10.1016/j.bbagrm.2016.07.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLe\u0026oacute;n-Annicchiarico CL, Ram\u0026iacute;rez-Peinado S, Dom\u0026iacute;nguez-Villanueva D, Gonsberg A, Lampidis TJ, Mu\u0026ntilde;oz-Pinedo C. ATF4 mediates necrosis induced by glucose deprivation and apoptosis induced by 2-deoxyglucose in the same cells. FEBS Journal [Internet]. 2015 Sep [cited 2025 May 7];282(18):3647\u0026ndash;58. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://onlinelibrary.wiley.com/doi/\u003c/span\u003e\u003cspan address=\"https://onlinelibrary.wiley.com/doi/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/febs.13369\u003c/span\u003e\u003cspan address=\"10.1111/febs.13369\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIurlaro R, P\u0026uuml;schel F, Le\u0026oacute;n-Annicchiarico, Luc\u0026iacute;a C, O\u0026rsquo;Connor H, Martin SJ, et al. Glucose Deprivation Induces ATF4- Mediated Apoptosis through TRAIL Death Receptors. 2017;37(10):1\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcCullough KD, Martindale JL, Klotz LO, Aw TY, Holbrook NJ. Gadd153 Sensitizes Cells to Endoplasmic Reticulum Stress by Down-Regulating Bcl2 and Perturbing the Cellular Redox State. Mol Cell Biol [Internet]. 2001;21(4):1249\u0026ndash;59. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.tandfonline.com/doi/full/\u003c/span\u003e\u003cspan address=\"https://www.tandfonline.com/doi/full/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/MCB.21.4.1249-1259.2001\u003c/span\u003e\u003cspan address=\"10.1128/MCB.21.4.1249-1259.2001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa Y, Brewer JW, Alan Diehl J, Hendershot LM. Two distinct stress signaling pathways converge upon the CHOP promoter during the mammalian unfolded protein response. J Mol Biol. 2002;318(5):1351\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang H, Niemeijer M, van de Water B, Beltman JB. ATF6 Is a Critical Determinant of CHOP Dynamics during the Unfolded Protein Response. iScience [Internet]. 2020;23(2):100860. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.isci.2020.100860\u003c/span\u003e\u003cspan address=\"10.1016/j.isci.2020.100860\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTorrence ME, Macarthur MR, Hosios AM, Valvezan AJ, Asara JM, Mitchell JR, et al. The mtorc1-mediated activation of atf4 promotes protein and glutathione synthesis downstream of growth signals. Elife. 2021;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTameire F, Verginadis II, Leli NM, Polte C, Conn CS, Ojha R, et al. ATF4 couples MYC-dependent translational activity to bioenergetic demands during tumour progression. Nat Cell Biol. 2019;21(7):889\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHyroššov\u0026aacute; P, Arag\u0026oacute; M, Moreno-Felici J, Fu X, Mendez-Lucas A, Garc\u0026iacute;a-Rov\u0026eacute;s PM, et al. PEPCK-M recoups tumor cell anabolic potential in a PKC-ζ-dependent manner. Cancer Metab. 2021;9(1):1\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKoppula P, Zhang Y, Shi J, Li W, Gan B. The glutamate/cystine antiporter SLC7A11/xCT enhances cancer cell dependency on glucose by exporting glutamate. Journal of Biological Chemistry [Internet]. 2017;292(34):14240\u0026ndash;9. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1074/jbc.M117.798405\u003c/span\u003e\u003cspan address=\"10.1074/jbc.M117.798405\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYamamoto K, Sato T, Matsui T, Sato M, Okada T, Yoshida H, et al. Transcriptional Induction of Mammalian ER Quality Control Proteins Is Mediated by Single or Combined Action of ATF6α and XBP1. Dev Cell. 2007;13(3):365\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShoulders MD, Ryno LM, Genereux JC, Moresco JJ, Tu PG, Wu C, et al. Stress-Independent Activation of XBP1s and/or ATF6 Reveals Three Functionally Diverse ER Proteostasis Environments. Cell Rep. 2013;3(4):1279\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLebeau P, Byun JH, Yousof T, Austin RC. Pharmacologic inhibition of S1P attenuates ATF6 expression, causes ER stress and contributes to apoptotic cell death. Toxicol Appl Pharmacol [Internet]. 2018;349(December 2017):1\u0026ndash;7. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.taap.2018.04.020\u003c/span\u003e\u003cspan address=\"10.1016/j.taap.2018.04.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJin S, Jin B, Ishikawa T, Ninagawa S, Okada T, Koyasu S, et al. Loss of ATF6α in a human carcinoma cell line is compensated not by its paralogue ATF6β but by sustained activation of the IRE1 and PERK arms for tumor growth in nude mice. Mol Biol Cell. 2023;34(3):ar20.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7829324/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7829324/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTumours grow faster than the local vasculature, resulting in a shortage of oxygen and nutrients. Among nutrients reduced in the tumor microenvironment, glucose is essential for tumour growth and survival. To explore how lung cancer cells cope with a low-glucose environment, we analysed transcriptional changes in glucose-starved A549 cells using RNA-sequencing. This showed downregulation of multiple pathways related to DNA replication and cell cycle. Many pathways were upregulated, and among them, the most upregulated transcriptional response to glucose deprivation was the Unfolded Protein Response (UPR), which has been shown to promote adaptation to proteotoxic and endoplasmic reticulum stress. The UPR involves three signalling branches, the PERK/ATF4, IRE1/XBP1, and ATF6 pathways. Glucose shortage robustly induced the three branches of the UPR in several non-small cell lung carcinoma cell lines, as indicated by ATF4 accumulation, XBP1 mRNA splicing and ATF6 cleavage. Transcriptional network analysis indicated that the transcriptional response to glucose deprivation was primarily driven by ATF6 and ATF4. Their silencing revealed that they cooperate to regulate multiple metabolic genes and pathways related to lipid synthesis and to amino acid synthesis and transport. ATF4 additionally regulated the transcriptional induction of mitochondrial OXPHOS-associated pathways. Functionally, ATF4 contributed to cell death, while ATF6 and IRE1/XBP1s did not impact survival. Interestingly, the ATF4 targets CHOP, Noxa and DR4 (TRAIL-R1) did not mediate cell death, which was only partially dependent on TRAIL-R2 (DR5) and only partially prevented by caspase inhibitors. Of note, both ATF4 and ATF6 regulated CHOP, and the absence of ATF6 enhanced the activation of XBP1 and ATF4 under glucose deprivation. These findings indicate that glucose deprivation initiates a complex interplay between the different branches of the UPR, which shape the balance between metabolic homeostasis and cell death.\u003c/p\u003e","manuscriptTitle":"ATF4 and ATF6 produce diverse transcriptional signatures affecting metabolic genes and cell death under glucose deprivation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-03 16:21:09","doi":"10.21203/rs.3.rs-7829324/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b1fc7cbd-f3bd-4519-b4b1-94c721371d0f","owner":[],"postedDate":"November 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56659367,"name":"Biological sciences/Cancer/Cancer metabolism"},{"id":56659368,"name":"Biological sciences/Cell biology/Protein folding"}],"tags":[],"updatedAt":"2025-12-01T12:50:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-03 16:21:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7829324","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7829324","identity":"rs-7829324","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}