IRF1-mediated thioredoxin (TXN) protects multiple myeloma cells from ferroptosis by regulating polyunsaturated fatty acids (PUFAs) and PUFA-containing phospholipid metabolism

IRF1-mediated thioredoxin (TXN) protects multiple myeloma cells from ferroptosis by regulating polyunsaturated fatty acids (PUFAs) and PUFA-containing phospholipid metabolism | 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 IRF1-mediated thioredoxin (TXN) protects multiple myeloma cells from ferroptosis by regulating polyunsaturated fatty acids (PUFAs) and PUFA-containing phospholipid metabolism Aili He, Jiaxi Liu, Jiyu Miao, Yang Lv, Bingjie Fu, Xiaomin Ren, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8988709/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Multiple myeloma (MM) is a hematologic malignancy characterized by uncontrolled plasma cell proliferation. Patients with relapsed or refractory MM face poor survival, highlighting the need for novel therapeutic targets. Ferroptosis, an iron-dependent form of regulated cell death, is governed by a complex network of enzymes, proteins, pathways, and organelles, and has been implicated in various diseases. In this study, we identified thioredoxin (TXN), as a key suppressor of ferroptosis, was among the top ferroptosis-related genes linked to poor prognosis in MM patients. Functionally, TXN loss impaired MM progression by enhancing ferroptosis largely through regulating polyunsaturated fatty acids (PUFAs) and PUFA-containing phospholipids (PUFA-PLs), the major substrates for lipid peroxidation. TXN deficiency promoted ferroptosis by increasing PUFA biosynthesis and their incorporation into lipid peroxidation pathways. We further discovered that interferon regulatory factor 1 (IRF1), downregulated in MM, acts as a transcriptional repressor of TXN. Additionally, we demonstrated that bortezomib (BTZ)-resistant MM displayed elevated TXN expression, which enabled them to evade ferroptosis and diminished their sensitivity to BTZ. In conclusion, our findings revealed that IRF1-mediated regulation of TXN modulates PUFA/PUFA-PL metabolism to protect MM cells from ferroptosis, establishing TXN as a promising therapeutic target for overcoming ferroptosis resistance and improving treatment outcomes in MM. Biological sciences/Cancer/Haematological cancer/Myeloma Biological sciences/Cancer/Cancer metabolism Biological sciences/Cell biology/Cell death Biological sciences/Cell biology/Mechanisms of disease Biological sciences/Cell biology/Cell signalling/Lipid signalling multiple myeloma ferroptosis PUFA PUFA-PL bortezomib drug-resistance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 INTRODUCTION Multiple myeloma (MM) is the second most common hematologic malignancy, driven by the uncontrolled clonal proliferation of malignant plasma cells in the bone marrow[1]. The age-adjusted global incidence of MM is approximately 2.1% in men and 1.5% in women, and MM caused more than 120,000 deaths in 2022[2, 3]. The introduction of proteasome inhibitors (PIs), monoclonal antibodies, and chimeric antigen receptor-engineered T cells (CAR-T)—has markedly improved patient outcomes[4]. Nevertheless, MM remains incurable; most patients relapse and eventually acquire drug resistance, underscoring the need to better understand disease pathogenesis and develop new therapeutic strategies. Ferroptosis, first proposed by Dixon in 2012[5], is an iron-dependent form of regulated cell death (RCD) characterized by mitochondrial shrinkage, reduced cristae, and structural damage[6]. Unlike apoptosis or necrosis initiating by protein cascades, ferroptosis is governed by three interconnected processes: initiation, defense, and regulation network[7]. Initiation involves the Fenton reaction, in which ferrous iron (Fe²⁺) reacts with hydrogen peroxide (H₂O₂) to generate reactive oxygen species (ROS). These ROS subsequently drive the oxidation of PUFA-PLs in cell membranes, causing lethal lipid peroxidation [5, 8]. The primary defense system relies on the glutathione peroxidase 4 (GPX4)–glutathione (GSH) axis[9], with radical-trapping antioxidants (RTAs) providing additional protection against lipid peroxidation[10]. Beyond these, a broad regulatory network of enzymes, proteins, pathways, and organelles modulates ferroptosis susceptibility[11, 12, 13, 14]. Over the past decade, ferroptosis has been implicated in tumorigenesis [15] and immune escape[16], but its contribution to MM progression remains poorly defined. TXN, an antioxidant protein that forms the thioredoxin system alongside thioredoxin reductase (TXNRD1) and NADPH, regulates multiple cellular processes including proliferation, antioxidant defense, apoptosis, and ferroptosis[17, 18, 19, 20]. Cancer cells frequently exploit TXN to buffer redox stressand support survival under hostile microenvironmental conditions[21]. For example, TXN maintains STAT3 in a reduced, active state, thereby promoting proliferation, metabolic reprogramming, and immune evasion [22]. Inhibition of TXN enhances p53 activity and triggers cell death in castration-resistant prostate cancer, underscoring its role in mutant p53-driven tumors[23]. Moreover, the tumor-promoting effect of TXN is partly attributable to its ability to suppress ferroptosis: the TXN inhibitor ferroptocide (FCD) efficiently induces ferroptosis in breast cancer cells[20], while TXN overexpression rescues GPX4 and GSH depletion in Parkinson’s disease models, preventing ferroptosis[24]. Despite these findings, the role of TXN in MM remains unclear. In this study, we demonstrate that TXN is highly expressed in MM and correlates with poor prognosis. Mechanistically, TXN promotes MM cell proliferation and ferroptosis resistance by regulating lipid peroxidation through the IRF1/TXN/PUFA/PUFA-PL axis. We further show that bortezomib (BTZ) resistance is linked to TXN upregulation, which enables MM cells to evade ferroptosis and reduces their sensitivity to BTZ. Together, these results identify TXN as a potential therapeutic target in MM. MATERIALS AND METHODS Cell Lines and Cell Culture Human multiple myeloma (MM) cell lines MM.1S, RPMI-8226, and NCI-H929 were obtained from ATCC (USA). ARD and KMS-11 cells were purchased from Procell (Wuhan, China), and OPM2 and U266 cells were kindly provided by Professor Jinsong Hu (Xi’an Jiaotong University Health Science Center, China). All cell lines were cultured in RPMI-1640 medium (HyClone, USA) supplemented with 10% fetal bovine serum (Biological Industries, Israel), 10,000 U/L penicillin, and 100 mg/L streptomycin (BioSharp, China). Cells were maintained at 37 °C in a humidified incubator with 5% CO₂. Patient Samples Bone marrow specimens were collected from MM patients at the Department of Hematology, Second Affiliated Hospital of Xi’an Jiaotong University (2019–2023). Sample collection and analysis were approved by the institutional ethics committee (Approval No. 2015186). Written informed consent was obtained from all patients for the use of their blood and bone marrow samples in this study. Reagents RSL3 (HY-100218A, purity ≥ 99.9%), Ferrostatin-1 (HY-100579 , purity ≥ 99.71%), Z-VAD (HY-164388, purity ≥ 99.20%), Necrostatin-1 (HY-15760, purity ≥ 99.89%), and Bortezomib (HY-10227, purity ≥ 98.0%) was purchased from MCE. Erastin(HY-15763, purity ≥99.62%) was purchased from Solarbio. Ferroptocide (2505218-38-0, purity ≥ 90%) was purchased from Aladdin. All compounds were dissolved in DMSO, aliquoted, and stored at −80 °C. Public Dataset Analysis and GSEA Gene expression data and clinical information were retrieved from GEO (https://www.ncbi.nlm.nih.gov/geo/), including datasets GSE6477, GSE6691, GSE13591, GSE47552, GSE136400, GSE24080, and GSE31161. Ferroptosis-related genes were obtained from FerrDb (http://www.zhounan.org/ferrdb/current/). Differentially expressed genes were identified across GSE6477, GSE6691, GSE13591, and GSE47552. In GSE24080, patients were stratified into poor- (4 years) groups for target screening. TXN expression across MM progression (MGUS, SMM, NDMM, and RRMM) was analyzed using GSE6477. Associations with ISS and R-ISS stages were assessed in GSE24080 and GSE136400. Survival analysis was performed using Kaplan-Meier curves and log-rank tests (p < 0.05 considered significant). Cell Viability Assays Cell viability was measured using the CCK-8 kit (Beyotime, China). MM cells (7 × 10³/well) were seeded in 96-well plates and treated with siRNA, single agents, or drug combinations for up to five days. At designated timepoints, 10 µL of CCK-8 solution was added to each well for 1-4 h before measuring absorbance at 450 nm. Synergy was assessed using CompuSyn software, with combination index (CI) <1 indicating synergy. Gene Knockdown TXN knockdown was achieved using siRNAs (GenePharma, China) or lentiviral shRNA constructs (GeneChem, China). IRF1 knockdown siRNAs were purchased from Stingke (Beijing, China). Transfection efficiency was confirmed by qRT-PCR and Western blot. Lipid Peroxidation Assay Lipid peroxidation was assessed using BODIPY™ 581/591 C11 (Thermo Fisher Scientific). Cells were incubated with the probe for 30 min at 37 °C, washed, and analyzed by flow cytometry. A fluorescence shift from red to green indicated lipid peroxidation. Intracellular ROS Measurement Cells were incubated with 10 µM DCFH-DA (Sigma-Aldrich) for 30 min at 37 °C. After washing, ROS levels were quantified by flow cytometry (excitation 488 nm, emission 525 nm). RNA Sequencing RNA-seq was performed on siNC- and siTXN-transfected RPMI-8226 cells, and on BTZ-sensitive and BTZ-resistant RPMI-8226 cells (LC-Bio Technologies, Hangzhou, China). Differential expression was analyzed using DESeq2. GO and KEGG analyses were performed to identify dysregulated pathways. Lipidomic Analysis Lipidomics was conducted on siNC- and siTXN-transfected RPMI-8226 cells, and on Ferroptocide-treated cells (8 µM, 6 h) (LC-Bio). Lipids were extracted using organic solvent precipitation and analyzed by LC-MS. Data processing was performed with XCMS. Metabolites were annotated using MS/MS spectra matched to an in-house library and the LIPID MAPS database. Pathway enrichment was analyzed using KEGG. Chromatin Immunoprecipitation (ChIP) ChIP was performed using a commercial kit (Beyotime, China). Crosslinked chromatin was sonicated and incubated with anti-IRF1 antibody or IgG control. Immunoprecipitated DNA was analyzed by qPCR. IRF1-binding motifs in the TXN promoter were predicted using JASPAR(https://jaspar.genereg.net/)[48]. Promoter Reporter and Dual-Luciferase Assay The TXN promoter was cloned into pGL3 reporter vectors (Tsingke, China). Cells were co-transfected with firefly luciferase constructs, Renilla luciferase control plasmid, and where indicated, IRF1 siRNA. Luciferase activity was measured after 48 h using the Dual-Luciferase Reporter Assay System (Yeasen, China). Apoptosis Assay Apoptosis was assessed using Annexin V-PE/RedNucleus II (Bioscience, China). Cells were transfected with siRNA, stained, and analyzed by flow cytometry (FlowJo software). Transmission Electron Microscopy (TEM) Cells were fixed with 2.5% glutaraldehyde, post-fixed in osmium tetroxide, dehydrated, embedded in epoxy resin, sectioned (~90 nm), stained with uranyl acetate and lead citrate, and imaged with a Hitachi HT7800 TEM a 120 kV. Quantitative PCR (qPCR) Total RNA from human samples, mouse tumors and MM cell lines was extracted using TRIzol reagent (GenStar, China) and reverse transcribed into cDNA using HiFiScript cDNA Synthesis Kit (Cwbio, China). qPCR was performed using SuperStar Universal SYBR Master Mix (Cwbio, China) according to the manufacturer's protocol. The primers used are listed in Table S1. Immunoblotting Total protein from human samples, mouse tumors and MM cell lines was extracted with RIPA lysis buffer (Cwbio, China), and the protein concentration was measured using the BCA Protein Quantification Kit (Yeasen, China). The primary antibodies used were as follows: anti‐TXN (1:5000, 12 kDa, 66475-1-Ig, Proteintech, China), anti‐GAPDH (1:5000, 36 kDa, 10494-1-AP, Proteintech, China), anti‐IRF1 (1:2000, 50 kDa, Proteintech, China). Animal Studies All animal experiments were approved by the Ethics Committee of Xi’an Jiaotong University Health Science Center (Approval No. 2025-2662) and were conducted in accordance with the institutional guidelines for the care and use of laboratory animals. Male BALB/c nude mice (3 weeks old) were purchased from GemPharmatech (China). Mice were allowed to acclimate for at least one week prior to any experimental procedures. Mice were housed under specific pathogen-free (SPF) conditions in individually ventilated cages (IVCs). Animal health and welfare were monitored daily by trained personnel. To establish subcutaneous xenograft models, RPMI-8226 cells stably transduced with LV-NC and LV-TXNkd were injected into the right/left flank of each mouse. Tumor dimensions (length and width) were measured every two days using a caliper, and tumor volume was calculated using the formula: Volume (mm³) = (width² × length) / 2. Once tumors reached 100 mm³, mice received intraperitoneal BTZ (0.5 mg/kg, every other day) or PBS. Mice were humanely euthanized when any individual tumor diameter reached 15 mm to prevent undue suffering. Euthanasia was performed by carbon dioxide (CO 2 ) asphyxiation in a gradual-fill chamber, followed by cervical dislocation as a secondary confirmation of death. Immediately after euthanasia, tumors were resected, weighed, and divided for subsequent analyses: one portion was fixed in 4% paraformaldehyde for immunohistochemistry (IHC), and the remainder was snap-frozen in liquid nitrogen for ROS and lipid ROS assays. Tumor size/burden limitations and compliance: The animal study protocol, as approved by the Ethics Committee of Xi’an Jiaotong University Health Science Center, stipulated a maximum permitted tumor burden of 1.5 cm in the longest diameter to prevent undue animal suffering. Throughout the study, tumor growth was closely monitored. We confirm that this maximum tumor size/burden was not exceeded in any animal. Humane endpoints were strictly enforced to ensure compliance with this ethical standard. In accordance with journal policy, no images of live animals bearing tumors are presented; all excised tumors were photographed adjacent to a scale ruler for size documentation. Statistical Analysis All experiments were performed with 3-6 biological replicates. Differences between two groups were analyzed using Student’s t-test or Mann-Whitney U test. Multiple group comparisons were performed by one-way ANOVA with Bonferroni post hoc test. p < 0.05 was considered statistically significant. RESULTS TXN is highly expressed in MM and associated with poor prognosis To identify ferroptosis-related genes linked to aggressive MM, we first analyzed four MM-related RNA sequencing datasets from GEO (GSE6477, GSE6691, GSE13591, and GSE47552) and identified 14 differentially expressed genes (DEGs) were identified between MM patients and healthy donors (Fig. 1a), including CKS2 [25], GADD45A [12], and TXN, which are associated with cancer progression and ferroptosis. Next, we examined prognosis-related ferroptosis regulators using the GSE24080 dataset and ferroptosis-related gene sets from FerrDb. Comparing patients with good prognosis (overall survival >4 years) versus poor prognosis (overall survival <2 years), gene set enrichment analysis (GSEA) revealed 41 ferroptosis suppressor genes associated with poor outcomes (Fig. 1b). TXN was among these prognosis-related suppressors. Comprehensive analysis across GEO datasets showed that TXN expression was significantly higher in MM compared with normal plasma cells (NPCs), monoclonal gammopathy of undetermined significance (MGUS), and smoldering MM (SMM) (Fig. 1c). High TXN expression correlated with advanced International Staging System (ISS) and Revised ISS (R-ISS) stages (Fig. 1d-e) and was significantly elevated in relapsed versus newly diagnosed patients, indicating a role in disease recurrence (Fig. 1f). Kaplan–Meier analysis confirmed that high TXN expression predicted shorter overall survival (OS) and event-free survival (EFS) (Fig. 1g-h). Furthermore, we examined TXN expression in both MM patients and MM cell lines. Compared with healthy donors, MM patients showed higher TXN expression than healthy donors, with relapsed/refractory MM (RRMM) patients exhibiting higher levels than newly diagnosed MM (NDMM) patients (Fig. 1i). TXN expression also increased with more advanced ISS and R-ISS stages (Fig. 1j). MM cell lines (MM.1S, U266, ARD, RPMI-8226, H929, OPM2, and KMS-11) expressed higher TXN at both mRNA and protein levels compared with bone marrow stromal cells (HS-5) (Fig. 1k). Taken together, these findings suggested that TXN, as a key regulator of ferroptosis, is highly expressed in MM and orrelates with advanced disease stage and poor prognosis. Silencing TXN inhibited MM cell proliferation and tumor growth To determine whether TXN contributes to MM progression through ferroptosis, we silenced TXN expression in two human MM cell lines with high endogenous TXN levels (RPMI-8226 and MM.1S) using specific small interfering RNAs (siRNAs) (Fig. 2a-b). CCK-8 assays demonstrated that TXN knockdown (siTXN) significantly reduced cell viability compared with negative control siRNA-treated cells (siNC) (Fig. 2c). Similarly, treatment with the TXN inhibitor Ferroptocide (FCD) decreased MM cell viability (Fig. 2d, Supplementary Fig. 1d-e). Notably, TXN knockdown did not significantly affect apoptosis in MM cells (Supplementary Fig. 1a-b), suggesting that reduced proliferation rather than apoptosis contributed to the observed growth inhibition. To evaluate the effects of TXN inhibition in vivo , we generated stable TXN knockdown MM cell lines using lentiviral transduction (LV-TXNkd) (Supplementary Fig. 1c). BALB/c nude mice injected with LV-TXNkd MM cells exhibited significantly reduced tumor burden than controls (Fig. 2e), concomitant with successful knockdown of TXN protein (Fig. 2f). Slower tumor growth, and higher body weight compared with mice bearing control LV-NC MM cells (Fig. 2g-h). Immunohistochemistry (IHC) analysis confirmed markedly decreased TXN and Ki-67 expression in tumors derived from LV-TXNkd cells relative to controls (Fig. 2i, Supplementary Fig. 1f). Collectively, these findings indicate that TXN is critical for MM cell proliferation and tumor progression, highlighting its potential as a therapeutic target in MM. TXN protects MM cells from lipid peroxidation-induced ferroptosis To further investigate whether TXN promotes MM progression by suppressing lipid peroxidation-induced ferroptosis, we measured lipid ROS levels in TXN-knockdown MM cells. Compared with control siRNA-treated cells (siNC), TXN knockdown (siTXN) significantly increased lipid ROS (Fig. 3a) and total intracellular ROS levels (Fig. 3b). Similarly, treatment with the TXN inhibitor Ferroptocide (FCD) markedly elevated both lipid ROS and total ROS in MM cells (Fig. 3c-d). To confirm that these effects were mediated by ferroptosis, we performed rescue experiments using ferroptosis inhibitor Ferrostatin-1 (Fer-1). Fer-1 significantly reversed FCD-induced lipid peroxidation, ROS accumulation, and cell death, whereas the apoptosis inhibitor Z-VAD and the necroptosis inhibitor Necrostatin-1 (NEC-1) had minimal effect (Fig. 3e-f, Supplementary Fig. 2a). Consistent with these in vitro findings, tumor cells derived from mice bearing LV-TXNkd MM cells exhibited elevated lipid ROS and total ROS compared with LV-NC controls (Fig. 3g-h). IHC results further confirmed increased levels of 4-Hydroxynonenal (4-HNE), a lipid peroxidation byproduct and well-recognized ferroptosis marker, in tumors from LV-TXN knockdown mice (Fig. 3i, Supplementary Fig. 2b). To further validate the role of TXN in ferroptosis, we treated TXN-knockdow MM cells with the ferroptosis inducer RSL3. siTXN cells displayed higher lipid peroxidation and ROS levels than siNC cells (Supplementary Fig. 2c-d). Additionally, we examined mitochondrial morphology in MM cells treated with siNC, siTXN, FCD (8 μM, 6 h), or RSL3 (5 μM, 6 h) using transmission electron microscopy (TEM). Mitochondria in TXN-deficient, FCD-treated, or RSL3-treated cells exhibited classic ferroptotic changes, including swelling, reduced electron density, and cristae loss (Fig. 3j). Taken together, these results demonstrate that TXN protects MM cells from lipid peroxidation-induced ferroptosis, highlighting its role as a key ferroptosis suppressor in MM. Negligible impact of TXN knockdown on transcriptomic profiles To explore how TXN regulates lipid peroxidation-induced ferroptosis in MM cells, we performed transcriptomic sequencing in MM cells transfected with either siNC or siTXN. Surprisingly, TXN knockdown induced only modest changes in gene expression, with 115 genes upregulated and 139 genes downregulated, and did not significantly alter classical ferroptosis-related genes such as SLC7A11, GPX4, or ACSL4 (Fig. 4a). DEGs were subsequently subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. No significant enrichment of ferroptosis pathways was observed in TXN-deficient cells (Fig. 4b-d, Supplementary Fig. 3a-b). However, DEGs were enriched in PUFA-related enzymatic activities and PUFA metabolism pathways, including linolenic acid and arachidonic acid (AA) epoxygenase activity (Fig. 4b-d). These results suggest that TXN, as an antioxidant protein, was more likely functions downstream in the redox cascade—modulating the terminal stages of lipid peroxidation—without broadly impacting upstream gene expression networks. Based on this, we focused subsequent investigations on the regulation of PUFA metabolism. TXN knockdown promoted ferroptosis by facilitating PUFA and PUFA-PL biosynthesis Given the potential role of TXN in lipid metabolism, we performed a comprehensive lipidomic profiling of TXN-knockdown (TXN-KD) MM cells using liquid chromatography-mass spectrometry (LC-MS) (Fig. 4e). Cells treated with the TXN inhibitor Ferroptocide (FCD, 8 µM, 6 h) were also profiled. Over 2,000 lipid metabolites were identified (Fig. 4f) and classified into six major categories: fatty acids (FA), glycerolipids (GL), glycerophospholipids (GP), sphingolipids (SP), sterol lipids (ST), and prenol lipids (PR). In total, 1,969 lipid species were quantified, of which 183 were significantly altered in TXN-KD cells compared with controls (Fig. 4g-h). KEGG enrichment analysis revealed significant enrichment in PUFA metabolism pathways, consistent with transcriptomic results (Fig. 4i). A regulatory network based on KEGG annotations highlighted alterations in linoleic acid, α-linolenic acid, and arachidonic acid metabolism (Fig. 4j). Global lipid composition analysis revealed that glycerophospholipids (GP) constituted the largest proportion of lipids, followed by GL and SP (Fig. 5a). FCD treatment increased GL and decreased GP, prompting a detailed analysis of GP subclasses, which included phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylglycerol (PG), and phosphatidylinositol (PI)—collectively referred to as phospholipids (PLs). Cardiolipin (CL), lysophospholipids (Lyso-PL), and phosphatidylinositol phosphates (PLP) were also included in the GP category, with PLs being the most abundant (Supplementary Fig. 4a). The relative composition of PLs was broadly similar across groups, dominated by PC and PE (Fig. 5b). PLs were further subclassified into diacyl-PLs, ether-linked PLs (PL-O), and vinyl ether-linked PLs (PL-P), with diacyl-PC and diacyl-PE prevailing in all groups (Fig. 5c, Supplementary Fig. 4b). Analysis of FA composition revealed that TXN deficiency, whether by knockdown or pharmacological inhibition, induced broad alterations in FA profiles (Fig. 5d-e). Notably, PUFA abundance was significantly increased in both TXN-KD and FCD-treated cells (Fig. 5f-g), including key substrates for PL biosynthesis such as FA 22:4 and FA 20:5, as well as FA 18:2 (linoleic acid), FA 18:3 (α-linolenic acid), and FA 22:5 (docosapentaenoic acid) (Supplementary Fig. 4c). Treatment with AA further confirmed the role of PUFA in ferroptosis, significantly reducing MM cell viability in a dose-dependent manner (Supplementary Fig. 4d). PLs were categorized by fatty acid content into saturated (SFA-PLs), monounsaturated (MUFA-PLs), and polyunsaturated (PUFA-PLs), the latter serving as terminal substrates for lipid peroxidation during ferroptosis. TXN knockdown altered both MUFA-PLs and PUFA-PLs (Fig. 5h, Supplementary Fig. 4e), while FCD treatment caused more pronounced increases in PUFA-PLs (Fig. 5i, Supplementary Fig. 4f). Then, we calculated an estimated cellular phospholipid peroxidation index (CPI) based on the known relative hydrogen atom transfer propagation rate constants of fatty acids[26, 27]. The results showed that FCD-treated cells had the highest CPI, with TXN-KD cells showing a trend toward increased CPI (Fig. 5j). Analysis of PL double bond content showed no significant change in TXN-KD cells, whereas FCD treatment enriched PLs with more than two double bonds (Supplementary Fig. 4g-h), further supporting enhanced ferroptosis susceptibility. Finally, examination of specific PUFA-PL species showed that TXN knockdown increased PUFA-PC 22:4 levels, a key pro-ferroptotic lipid (Fig. 5m), whereas FCD treatment broadly elevated total PUFA-PLs, reduced MUFA-PLs, and specifically increased PUFA-PC and PUFA-PE species containing 22:4 and 20:4 (Fig. 5k-o). In summary, TXN deficiency enhances PUFA and PUFA-PL biosynthesis, indicating that TXN protects MM cells from lipid peroxidation-induced ferroptosis by suppressing the formation of pro-ferroptotic lipids. IRF1 promoted ferroptosis in MM cells by repressing TXN expression To identify upstream regulators of TXN in ferroptosis, we analyzed the promoter of TXN gene using the NCBI, JASPAR, and UCSC Genome Browser databases. These analyses revealed several candidate transcription factors (TFs), including KLF5, EGR1, and IRF1. To determine which TF regulates TXN in MM, we examined their expression in bone marrow samples from healthy donors and MM patients and performed Kaplan-Meier survival analysis. Among the candidates, IRF1 was significantly downregulated in MM patients compared with healthy donors (Fig. 6a), and lower IRF1 expression correlated with poorer overall survival (Fig. 6b). An analysis of MM patient samples demonstrated a significant inverse correlation between the expression of IRF1 and TXN (Fig. 6c). Next, we knocked down IRF1 in MM cells using siRNA. This led to a marked increase in TXN expression at both the mRNA and protein levels (Fig. 6d-e), suggesting that IRF1 may functions as a transcriptional repressor of TXN. To confirm this regulatory relationship, we identified a potential IRF1-binding motif on the TXN promoter using JASPAR (Fig. 6f) and performed chromatin immunoprecipitation (ChIP) assays. These assays demonstrated strong IRF1 binding to the TXN promoter in MM.1S cells (Fig. 6g-h). We then constructed PGL3-BASIC luciferase reporter plasmids containing either the wild-type (WT) or mutated (Mut) IRF1-binding motif. Dual-luciferase assays showed that IRF1 knockdown partially restored TXN promoter activity (Fig. 6i), further supporting its role as a negative regulator of TXN transcription. Finally, we assessed whether IRF1 modulates ferroptosis in MM cells through TXN. While IRF1 knockdown alone did not significantly affect lipid ROS levels, it markedly reduced RSL3-induced lipid ROS and total ROS accumulation (Fig. 6j), indicating that downregulating IRF1 could relieve RSL3-induced ferroptosis in MM cells by upregulating TXN. In summary, IRF1 is downregulated in MM and acts as a transcriptional repressor of TXN. Reduced IRF1 expression elevates TXN levels, which protects MM cells from ferroptosis and may contribute to disease progression. TXN deficiency-induced ferroptosis synergized with bortezomib to effectively target MM cells Bortezomib (BTZ), the first proteasome inhibitor approved by the U.S. Food and Drug Administration (FDA) for multiple myeloma (MM) [28], exerts its therapeutic effects through multiple mechanisms, including the induction of apoptosis [29] , endoplasmic reticulum and Golgi stress [30], and disruption of diverse cellular pathways [31]. We hypothesized that ferroptosis may act synergistically with BTZ to enhance its anti-myeloma efficacy. To test this, we treated MM cells with the ferroptosis inducers RSL3 or erastin in combination with BTZ. Compared to monotherapy, the combination treatment significantly enhanced the inhibition of MM cell viability (Fig. 7a-b). Consistently, co-treatment with the TXN inhibitor FCD and BTZ further suppressed cell viability compared with either agent alone (Fig. 7c), suggesting that TXN inhibition can potentiate the anti-myeloma effect of BTZ. The calculated combination index (CI) values, which quantify the drug synergy, are summarized in Table 1. Table.1 Synergistic effect of bortezomib and ferroptosis inducers BTZ (nM) RSL3 （ μM ） RPMI-8226 MM.1S Effect Cl Effect Cl 12.5 0.1 0.68299 0.50239 0.68797 0.74150 12.5 0.2 0.51537 0.51607 0.41920 0.67980 12.5 0.4 0.44158 0.78583 0.32532 0.99838 25.0 0.1 0.56054 0.34467 0.58795 0.73805 25.0 0.2 0.39133 0.34737 0.35666 0.67694 25.0 0.4 0.33386 0.54319 0.22850 0.82191 50.0 0.1 0.41539 0.22930 0.26200 0.47361 50.0 0.2 0.32644 0.28802 0.21705 0.57825 50.0 0.4 0.25912 0.41062 0.19542 0.84727 Erastion （ μM ） Effect Cl Effect Cl 12.5 5.0 0.88105 1.33501 0.97224 3.56292 12.5 10.0 0.74353 1.18148 0.91211 1.73011 12.5 20.0 0.56578 1.27673 0.69590 0.76883 25.0 5.0 0.83072 1.24596 0.44208 0.20032 25.0 10.0 0.64335 0.95094 0.14310 0.06821 25.0 20.0 0.44096 0.95541 0.12395 0.08961 50.0 5.0 0.70118 0.96899 0.35307 0.24255 50.0 10.0 0.25657 0.33671 0.11693 0.08278 50.0 20.0 0.23386 0.53647 0.06712 0.06603 Ferrotpcide （ μM) Effect Cl Effect Cl 25.0 1.0 0.71841 0.65960 0.80794 0.55951 50.0 1.0 0.65624 0.79739 0.76495 0.46769 100.0 1.0 0.59104 0.99473 0.72070 0.41067 25.0 2.0 0.50542 0.51309 0.71820 0.46462 50.0 2.0 0.44228 0.55140 0.74633 0.61884 10.0 2.0 0.38902 0.62127 0.64657 0.38916 25.0 4.0 0.30667 0.76359 0.71285 0.86104 50.0 4.0 0.27898 0.77853 0.60198 0.58272 100.0 4.0 0.23881 0.79394 0.53656 0.47799 Two multiple myeloma cell lines (RPMI-8226 and MM.1S) were treated with bortezomib (BTZ) in combination with either RSL3, erastin, or ferroptocide at the indicated concentrations for 24 h. “Effect” corresponds to cell viability. The combination index (CI) was calculated using CompuSyn software to evaluate drug synergy, where CI < 1 indicates a synergistic interaction. We next evaluated this synergistic effect in vivo . Nude mice were subcutaneously injected with RPMI-8226 cells transfected with either LV-NC or LV-TXNkd. Once tumors reached ~100 mm³, mice received intraperitoneal BTZ (0.5 mg/kg, every other day) or PBS (Fig. 2g). As expected, BTZ alone suppressed tumor growth, but the LV-TXNkd + BTZ group showed a significantly greater reduction in tumor volume and growth rate compared with the LV-NC + BTZ group (Fig. 7d-e). Collectively, these findings demonstrated that TXN deficiency-induced ferroptosis could synergize with BTZ both to suppress MM progression in vitro and i n vivo . TXN overexpression promotes bortezomib resistance in MM cells via ferroptosis evasion To investigate whether TXN contributes to BTZ resistance, we established BTZ-resistant (BTZ-R) RPMI-8226 and OPM2 cell lines by stepwise exposure to increasing BTZ concentrations. RNA sequencing showed TXN was significantly upregulated in BTZ-R RPMI-8226 cells (Fig. 8a), which was validated by RT-qPCR and Western blot (Fig. 8b). We next examined ferroptosis sensitivity. When treated with the ferroptosis inducer RSL3, BTZ-R RPMI-8226 cells exhibited significantly higher viability than parental cells (IC50: 0.981 μM vs. 1.784 μM), and similar results were observed in BTZ-R OPM2 cells (IC50: 2.059 μM vs. 6.462 μM) (Fig. 8c-d). Consistently, BTZ-R MM cells accumulated less lipid ROS and total ROS than parental cells following RSL3 treatment (Fig. 8e-f), indicating that ferroptosis evasion contributes to BTZ resistance, likely through elevated TXN expression. To directly assess the role of TXN, we established stable TXN knockdown in BTZ-R RPMI-8226 cells via lentiviral transduction (Fig. 8g). TXN knockdown increased lipid ROS and total ROS levels in BTZ-R cells (Fig. 8h), suggesting that loss of TXN restores susceptibility to lipid peroxidation–driven ferroptosis. Moreover, RSL3 treatment further reduced cell viability in TXN-deficient BTZ-R cells compared with controls (IC50: 2.044 μM vs. 1.868 μM) (Fig. 8h). In summary, BTZ-resistant MM cells evade ferroptosis by upregulating TXN, thereby reducing their sensitivity to BTZ. Targeting TXN may therefore help overcome BTZ resistance in MM. DISCUSSION Ferroptosis, a recently recognized form of RCD, has emerged as a critical process in cancer biology and a promising therapeutic target[5]. MM is a highly heterogeneous hematological malignancy. Dysregulated iron and lipid metabolism in MM contributes to uncontrolled cell proliferation, abnormal differentiation, and drug resistance[32, 33], and may also influence the process of ferroptosis. Yet, the role of ferroptosis in MM progression has remained unclear. In this context, we identify thioredoxin (TXN) as a ferroptosis suppressor in MM. Mechanistically, TXN limits lipid peroxidation and protects cells from ferroptotic death through the IRF1–TXN–PUFA/PUFA-PL axis. We also show that BTZ-resistant MM cells upregulate TXN, enabling ferroptosis evasion and diminishing drug sensitivity. Together, these findings establish TXN as a central regulator of ferroptosis and a potential therapeutic target in MM, especially in the setting of drug resistance. TXN is a key antioxidant protein that maintains redox homeostasis by reducing protein disulfides and modulating redox-sensitive signaling pathways. Prior studies have implicated TXN in ferroptosis regulation. For example, Bai et al.[24] showed that TXN protects against MPP+/MPTP-induced ferroptosis through GPX4 upregulation. While in lung adenocarcinoma, pharmacological activation of retinoic acid receptor α enhanced TXN expression and suppressed ferroptosis[34]. These observations underscore the relevance of the System XC - /Cys/TXN/TXNRD axis in ferroptosis control. However, the ferroptosis-related role of TXN in MM has been largely unexplored. Our data demonstrate that TXN is significantly upregulated in MM, correlating with disease progression, advanced stage, relapse, and poor prognosis. Both genetic silencing and pharmacological inhibition of TXN reduced MM cell viability and triggered ferroptosis, consistent with prior work showing that thioredoxin inhibitors such as ferroptocide induce ferroptosis in solid tumors[35]. A defining feature of ferroptosis is the peroxidation of PUFAs incorporated into phospholipids, particularly those with chains longer than 20 carbons[36, 37, 38]. Our lipidomic analysis showed that TXN knockdown or pharmacological inhibition enriched PUFA species, such as FA 18:2, FA 18:3, FA 20:5, FA 22:4, and FA 22:5. Treatment with arachidonic acid (AA, FA 20:4) alone induced MM cell death in a dose- and time-dependent manner, supporting the functional role of PUFA enrichment. Consistently, Lee et al.[36] conducted a lipid profiling analysis in the mesenchymal-type gastric cancer cells following upregulation of ELOVL5 and FADS1. Their results showed enrichment of AA (FA 20:4) and adrenic acid (AdA, FA 22:4), which are required for ferroptosis, thereby enhancing ferroptotic sensitivity. Dierge et al[34]. reported that excess uptake of n-3 and n-6 PUFA could trigger ferroptosis in cancer cells under ambient acidosis. Collectively, these findings suggest that PUFAs are primary targets of lipid peroxidation in ferroptosis, and modulation of PUFA biosynthesis can influence ferroptotic sensitivity across different cancer cells. PUFA-PLs are equally critical, as their incorporation into membranes makes them primary substrates for lethal lipid peroxidation. We observed that TXN knockdown preferentially elevated PUFA-PC species containing FA 22:4, while pharmacological inhibition produced a broader increase in PUFA-PLs, especially PUFA-PC and PUFA-PE species containing FA 20:4 and FA 22:4. This suggests that pharmacological inhibition exerts a stronger metabolic effect than knockdown alone. Kagan et al.[37] performed global redox phospholipidomics LC-MS/MS analysis of RSL3-treated Pfa1 cells, demonstrating that AA- and AdA-containing phospholipid species were most responsive, highlighting these species as key lipid death signals. Additionally, Morgan et al.[39] demonstrated that variations in PUFA-PLs content underpin the differential susceptibility of immune cells to ferroptosis, specifically, with low PUFA-PL content conferring resistance in activated neutrophils. Collectively, our findings align with reports that AA- and AdA-containing phospholipids act as key death signals and that PUFA-PL content determines cell-type-specific ferroptotic susceptibility. We further identified IRF1 as a direct transcriptional repressor of TXN. IRF1 downregulation in MM was associated with worse prognosis, and IRF1 knockdown increased TXN levels and reduced ferroptotic sensitivity. IRF1 has been widely studied for its tumor-suppressive functions[40, 41]. These findings extend the tumor-suppressive role of IRF1 and establish a new regulatory axis in which IRF1 represses TXN to promote ferroptosis. To explore therapeutic relevance, we combined BTZ with the TXN inhibitor FCD or ferroptosis inducers. Co-treatment produced strong synergy in suppressing MM cell viability in vitro and tumor growth in vivo . This suggests that the efficacy of BTZ can be enhanced by promoting ferroptosis. Prior studies support this concept: RSL3 and BTZ have been shown to synergize through glutathione depletion[42]; AP-1 inhibition sensitizes MM cells to BTZ by inducing ferroptosis[43]; and BTZ promotes ferritinophagy-mediated iron release, reinforcing synergy with ferroptosis inducers[44]. Importantly, we demonstrated that BTZ-resistant MM cells display reduced sensitivity to ferroptosis and upregulate TXN, suggesting that TXN-mediated ferroptosis evasion contributes to drug resistance. Similar mechanisms have been reported in other malignancies, where ferroptosis modulation impacts BTZ sensitivity[45, 46]. TXN has also been implicated in BTZ resistance through mitophagy suppression and mTOR/ERK activation, underscoring its multifaceted role in therapy resistance[47]. Together, these findings indicated that ferroptosis dysregulation underlies BTZ resistance in MM, and that targeting TXN or related pathways may provide a strategy to overcome relapse. However, our study has several limitations. Firstly, most of our functional experiments were performed using MM cell lines rather than primary MM cells from patients. Secondly, it remains unclear whether the combination treatment could impact extramedullary infiltration of MM. In summary, we show that TXN protects MM cells from ferroptosis by suppressing PUFA and PUFA-PL accumulation, and that IRF1 represses TXN transcription to enhance ferroptotic sensitivity. Elevated TXN expression contributes to BTZ resistance by enabling ferroptosis escape. These findings identify TXN as a potential therapeutic target for MM and highlight ferroptosis modulation as a promising strategy to improve outcomes, particularly in relapsed or refractory disease. Declarations ACKNOWLEGEMENT We acknowledge the colleagues at the Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, for their assistance in sample collection. CONFLICT OF INTEREST The authors declare that they have no competing interests. DATA AVAILABILITY STATEMENT The raw sequencing data generated in this study have not been deposited in a public repository at the time of submission. These data will be made available in the NCBI Gene Expression Omnibus (GEO) prior to publication. During the review process, the data are available from the corresponding author upon reasonable request. Ethics approval and consent to participate This study involving human participants was approved by the Institutional Ethics Committee of The Second Affiliated Hospital of Xi’an Jiaotong University (Approval No.: 2015186). The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. All participants provided written informed consent prior to participation. The animal experiments were approved by the Ethics Committee of Xi’an Jiaotong University Health Science Center (Approval No.: 2025-2662). 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University","correspondingAuthor":false,"prefix":"","firstName":"Wanhong","middleName":"","lastName":"Zhao","suffix":""},{"id":600720412,"identity":"b3f14c52-126c-4ad9-acc6-fecd43cef403","order_by":14,"name":"Rui Liu","email":"","orcid":"https://orcid.org/0000-0001-5229-829X","institution":"the Second Affiliated Hospital of Xi'an Jiaotong University","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-02-27 13:47:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8988709/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8988709/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104322803,"identity":"ad17fdf4-5b5f-414a-a831-d7a355f4686d","added_by":"auto","created_at":"2026-03-10 13:27:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":12091241,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTXN was highly expressed in MM patients and related to poor survival.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e Venn diagram of differentially expressed genes anaylsis from four MM realted GEO databases. \u003cstrong\u003eb\u003c/strong\u003e GSEA anaylsis between high risk MM patients (survival \u0026lt;2 years, n = 19) and low risk MM patients (survival \u0026gt;4 years n = 282) in GSE24808 database, the ferroptosis-suppressor gene TXN were enriched progressively with the MM patients with high risk.\u003cstrong\u003e c-f \u003c/strong\u003ethe TXN expression in MM progression:NPC, MGUS, SMM, MM (\u003cstrong\u003ec\u003c/strong\u003e), ISS (\u003cstrong\u003ed\u003c/strong\u003e), R-ISS stages (\u003cstrong\u003ee\u003c/strong\u003e) and disease relapsed status (\u003cstrong\u003ef\u003c/strong\u003e). \u003cstrong\u003eg-h\u003c/strong\u003e Kaplan-Meier survival analysis showing the OS and EFS of MM patients having the low TXN expression (red) and high TXN expression (blue). \u003cstrong\u003ei-j \u003c/strong\u003eThe expression of TXN in normal plasm cells by RT-qPCR, and MM patients grouped by NDMM, RRMM, ISS and R-ISS stages. \u003cstrong\u003ek\u003c/strong\u003e The expression of TXN in MM cell lines by RT-qPCR and WB. NPC, normal plasma cells; MGUS, monoclonal gammopathy of undetermined significance; SMM, smoldering MM; NDMM, newly diagnosed MM; RRMM, \u0026nbsp;relapsed/refractory MM. Data are mean ± SD values. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001, ns. not significant. Note: all experiments were performed at least 3 different biological replicates, the representative results shown in the main manuscript figures.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/6a7defe5a7eed2d35ec87049.png"},{"id":104322790,"identity":"56d61849-4b17-4e58-869b-c2ba5e9d98f7","added_by":"auto","created_at":"2026-03-10 13:27:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":41893197,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInhibiting TXN suppressed MM development and reduced tumor burden in vitro and vivo.\u003c/strong\u003e \u003cstrong\u003ea-b\u003c/strong\u003e Validation of TXN knockdown at both mRNA and protein levels in RPMI-8226 and MM.1S MM cell lines. \u003cstrong\u003ec \u003c/strong\u003eCell viability was detected by CCK8 assays in RPMI-8226 and MM.1S cells transfected with siNC and siTXN for 72h. \u003cstrong\u003ed\u003c/strong\u003e Cell viability was detected by CCK8 assays in RPMI-8226 treated with DMSO(1%) and FCD in different concentrations. \u003cstrong\u003ee-f \u003c/strong\u003eBALB/c nude male mice were injected with LV-NC (n=5) or LV-TXNkd (n=5) RPMI-8226 cells. Mice were sacrificed when tumor diameter was more than 15 mm, xenograft tumors were completely dissected (\u003cstrong\u003ee\u003c/strong\u003e). TXN protein levels in the harvested tumors were analyzed by Western Blot (\u003cstrong\u003ef\u003c/strong\u003e). \u003cstrong\u003eg-h \u003c/strong\u003eTumor volume was recorded every 2 days and calculated by the formula:(width\u003csup\u003e2\u003c/sup\u003e×length×0.5), tumor weight was recorded when mice were sacrificed, and shown as mean ±SE. \u003cstrong\u003ei\u003c/strong\u003e Representative hematoxylin-eosin (H\u0026amp;E) staining and IHC staining of TXN in tumors from LV-NC and LV-TXNkd nude mice. Data are mean ± SD values. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001, ns. not significant. Note: Data are representative of at least three independent biological replicates; the mouse xenograft model is an exception.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/6980cd5d833ef087f6adaee7.png"},{"id":104779877,"identity":"d1fb9008-3118-4785-8866-1409428c9762","added_by":"auto","created_at":"2026-03-17 07:47:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":57117970,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTXN deficiency enhanced MM cell susceptibility to ferroptosis.\u003c/strong\u003e \u003cstrong\u003ea-b\u003c/strong\u003e Lipid ROS and intracellular total ROS were detected by flow cytometry in RPMI-8226 and MM.1S cells transfected with siNC and siTXN for 48 h. \u003cstrong\u003ec-d\u003c/strong\u003e Lipid ROS and intracellular total ROS was detected by flow cytometry in RPMI-8226 and MM.1S cells treated with different concentrations FCD for 12 h. \u003cstrong\u003ee-f\u003c/strong\u003e RPMI-8226 and MM.1S cells was pre-treated with ferroptosis inhibitor Fer-1 (1 μM), apoptosis inhibitor Z-VAD (40 μM) and \u003ca href=\"https://www.medchemexpress.cn/Targets/necroptosis/effect/inhibitor.html\" target=\"https://www.medchemexpress.cn/_blank\"\u003enecroptosis inhibitor\u003c/a\u003e Nec-1 (10 μM)for 2h, followed by FCD (8μM) for 9 h, lipid ROS was detected by flow cytometry, and cell viability was detected by CCK-8 assays. BALB/c nude male mice injected with RPMI-8226 cells were sacrificed, cells of xenograft tumors were acquired for Lipid ROS and intracellular total ROS detect (\u003cstrong\u003eg-h\u003c/strong\u003e), IHC staining of 4-HNE in xenograft tumors(\u003cstrong\u003ei\u003c/strong\u003e). \u003cstrong\u003ej\u003c/strong\u003e Mitochondrial morphological were observed by TEM in RPMI-8226 cells and MM.1S cells with siNC, siTXN, FCD (8 μM, 6 h), and RSL3 (5 μM, 6 h). FCD, Ferroptocide; Fer-1; Ferrostatin-1; NEC-1, Necrostatin-1. Data are mean ± SD values. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001, ns. not significant. Note: all experiments were performed at least 3 different biological replicates, the representative results shown in the main manuscript figures.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/fc51b98d9f3940a6b902a0dd.png"},{"id":104322759,"identity":"694a0e1b-dea0-4554-8ba1-ce7d9dc54f38","added_by":"auto","created_at":"2026-03-10 13:27:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":22029572,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTXN knockdown had minimal transcriptomic impact but was critical for lipid metabolism. a \u003c/strong\u003etotal DEGs were detected in RPMI-8226 cells transfected with siNC and siTXN for 48h, showed by bar graph, volcano plot and heat map. Heatmap (z-score normalized) showing the top 100 DEGs ranked by lowest p-values. \u003cstrong\u003eb-c\u003c/strong\u003e GO enrichment analysis of the top 20 GO tem with the most significant p-values(\u003cstrong\u003eb\u003c/strong\u003e), the top 20 biological process with the most significant p-values(\u003cstrong\u003ec\u003c/strong\u003e). \u003cstrong\u003ed\u003c/strong\u003e top 20 KEGG pathway enrichment analysis of DEGs in different pathways with the most significant p-values. Y-axis represents GO or KEGG terms, while the x-axis indicates either raw p-values or their -log₁₀ transformations. \u003cstrong\u003ee \u003c/strong\u003eWorkflow schematic of lipidomics analysis. RPMI-8226 cells were transfected with either siNC or siTXN for 72 hours. \u003cstrong\u003ef\u003c/strong\u003e Identified IDMS2 metabolites were annotated using the LIPID MAPS database. Classification and annotation results are displayed, with the x-axis representing the number of metabolites and the y-axis indicating Level 1 and Level 2 LIPID MAPS classifications. \u003cstrong\u003eg\u003c/strong\u003e Volcano plot illustrating changes in global lipid species between siNC- and siTXN-transfected RPMI-8226 cells. \u003cstrong\u003eh\u003c/strong\u003e Heatmap (z-score normalized) displaying the top 50 differentially expressed lipid metabolites ranked by lowest p-values. \u003cstrong\u003ei \u003c/strong\u003eKEGG pathway enrichment analysis shown as a bubble plot of the top 20 significantly enriched pathways. The RichFactor (ratio of differentially expressed metabolites to the total number of metabolites in a given pathway) reflects the degree of pathway enrichment. In the plot, bubble size indicates the number of differential metabolites per pathway, while color represents the statistical significance (p-value) of enrichment. \u003cstrong\u003ej\u003c/strong\u003e Network diagram depicting the regulatory relationships between differential metabolites and KEGG pathways. The diagram integrates enrichment and association data to highlight key pathways. The top 30 differential metabolites (by p-value) were selected for visualization. Triangles represent metabolites; circles represent pathways. The number of connecting edges indicates the centrality of a given metabolite or pathway in the regulatory network. GC, Gas Chromatography; HILIC, Hydrophilic Interaction Chromatography; RP, Reversed-Phase Chromatography; TDF, Timing Digitizer. IDMS2, Isotope Dilution Mass Spectrometry with MS/MS. Data are mean ± SD values. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001, ns. not significant. The lipidomic analysis was performed on 6 independent biological replicates for each group.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/edb2cc367797b3f6af70f51c.png"},{"id":104322757,"identity":"9a3401d3-46f1-4389-a2b0-2efa23c37e00","added_by":"auto","created_at":"2026-03-10 13:27:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":26313564,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTXN deficiency promoted ferroptotic sensitivity in MM cells by enhancing PUFA and PUFA-PL biosynthesis. a-c\u003c/strong\u003e Classification of lipid features in siNC-transfected RPMI-8226 cells, siTXN-transfected RPMI-8226 cells, and RPMI-8226 cells treated with FCD (8 µM, 6 h): by lipid class (\u003cstrong\u003ea\u003c/strong\u003e), phospholipid headgroup type (\u003cstrong\u003eb\u003c/strong\u003e), and Sn-1 chemical linkage type in phosphatidylcholine (PC) (\u003cstrong\u003ec\u003c/strong\u003e).\u003cbr\u003e\n \u003cstrong\u003ed-e\u003c/strong\u003e Heatmap (z-score normalized) showing all differentially expressed FAs ranked by p-value between siNC and siTXN RPMI-8226 cells or FCD-treated RPMI-8226 cells. \u003cstrong\u003ef-g\u003c/strong\u003e Quantification of total PUFA levels, FA 20:5 and FA 22:4 between siNC and siTXN RPMI-8226 cells or FCD-treated RPMI-8226 cells. \u003cstrong\u003eh-i\u003c/strong\u003eVolcano plots displaying changes in PL species between siNC and siTXN RPMI-8226 cells or FCD-treated RPMI-8226 cells. \u003cstrong\u003ej\u003c/strong\u003e Cellular phospholipid peroxidation index (CPI) values in siNC, siTXN, and FCD-treated RPMI-8226 cells. Data are presented as box-and-whisker plots: the box represents the interquartile range (25th-75th percentiles), the line within the box denotes the median, and whiskers extend to the minimum and maximum values. \u003cstrong\u003ek-o\u003c/strong\u003eProportions of specific PL subtypes across the three groups. Proportions of PUFA-PLs and MUFA-PLs across the three groups (\u003cstrong\u003ek\u003c/strong\u003e). Proportions of PUFA-PC/PE and MUFA-PC/PE between siNC and siTXN RPMI-8226 cells (\u003cstrong\u003el\u003c/strong\u003e). Proportions of PUFA-PC species containing FA 22:4 and PUFA-PE species containing FA 20:4 between siNC and siTXN RPMI-8226 cells (\u003cstrong\u003em\u003c/strong\u003e). Proportions of PUFA-PC/PE and MUFA-PC/PE between siNC and FCD-treated RPMI-8226 cells(\u003cstrong\u003en\u003c/strong\u003e). Proportions of PUFA-PC species containing FA 22:4 and PUFA-PE species containing FA 20:4 between siNC and FCD-treated RPMI-8226 cells(\u003cstrong\u003eo\u003c/strong\u003e). FA, fatty acids; GL, glycerolipids; GP, glycerophospholipids; SP, sphingolipids; ST, terol lipids; PR, prenol lipids; PA, phosphatidic acid; PC, phosphatidylcholine; PE, phosphatidylethanolamine; PS, phosphatidylserine; PG, phosphatidylglycerol; PL, phosphatidylinositol; PL-O, ether-linked PLs; PL-P, vinyl ether-linked PLs. Data are expressed as mean ±SD. Statistical significance: *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns., not significant. The lipidomic analysis was performed on 6 independent biological replicates for each group.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/3dffad8a0b7864a9083b2c4b.png"},{"id":104322787,"identity":"4aae586e-50fa-4ff2-8eb4-051d3a3092bf","added_by":"auto","created_at":"2026-03-10 13:27:22","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":8722639,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIRF1 was downregulated in MM and act as a transcriptional repressor of TXN. a \u003c/strong\u003eRT-qPCR analysis of IRF1 expression in plasmocyte cells from healthy donors versus MM patients. \u003cstrong\u003eb \u003c/strong\u003eKaplan-Meier survival analysis showing OS of MM patients with low (blue) versus high (red) IRF1 expression. \u003cstrong\u003ed \u003c/strong\u003eCorrelation analysis of IRF1 and TXN mRNA expression in plasma cells from MM patients.\u003cstrong\u003e d-e \u003c/strong\u003eValidation of IRF1 knockdown at both mRNA and protein levels in RPMI-8226 and MM.1S cells, and analysis of TXN expression following IRF1 knockdown at mRNA and protein levels. \u003cstrong\u003ef \u003c/strong\u003eThe predicted IRF1-binding motif within the TXN promoter, identified via the JASPAR database.\u003cstrong\u003e g-h\u003c/strong\u003e ChIP assays analyzed by agarose gel electrophoresis and RT-qPCR demonstrating IRF1 binding to the TXN promoter. \u003cstrong\u003ei\u003c/strong\u003e Dual-luciferase reporter assay comparing wild-type (WT) and mutant (Mut) TXN promoter activity following IRF1 knockdown. \u003cstrong\u003ej\u003c/strong\u003e Lipid ROS and intracellular total ROS levels detected by flow cytometry in RPMI-8226 and MM.1S cells transfected with siNC or siIRF1 for 72 hours or treated with RSL3 (5 μM, 12 hours). WT, wild-type IRF1-binding motif; Mut, mutated IRF1-binding motif. Data are mean ± SD values. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001, ns. not significant. Note: all experiments were performed at least 3 different biological replicates, the representative results shown in the main manuscript figures.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/f692cd49259a982754bc4f45.png"},{"id":104322758,"identity":"e7c03b70-fb1a-48fd-8ad0-0e5425cc0787","added_by":"auto","created_at":"2026-03-10 13:27:19","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":15403666,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTXN deficiency-induced ferroptosis synergized with bortezomib to effectively kill MM cells \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro and vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. a-c \u003c/strong\u003eCell viability in RPMI-8226 cells and MM.1S cells treated with BTZ and RSL3(\u003cstrong\u003ea\u003c/strong\u003e), Erastin(\u003cstrong\u003eb\u003c/strong\u003e), and Ferroptocide(\u003cstrong\u003ec\u003c/strong\u003e) in different concentreation for 24 hours. \u003cstrong\u003ed\u003c/strong\u003e BALB/c nude male mice were injected with\u0026nbsp; LV-NC(n=5) or LV-TXNkd(n=5) RPMI-8226 cells. Once tumor volumes exceeded 100 mm³(Day12), mice were treated with intraperitoneal injections of BTZ (0.5 mg/kg, every other day) for BTZ group, or treated with intraperitoneal injections of PBS (same volume as BTZ, every other day) for NC group. Mice were sacrificed when tumor diameter was more than 15 mm, xenograft tumors were completely dissected. \u003cstrong\u003ee\u003c/strong\u003e Tumor volume was recorded every 2 days and calculated by the formula:(width\u003csup\u003e2\u003c/sup\u003e×length×0.5), and shown as mean ±SE. Data are mean ± SD values. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001, ns. not significant. Note: Data are representative of at least three independent biological replicates; the mouse xenograft model is an exception.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/03101e6e71b2831fde43acec.png"},{"id":104322804,"identity":"1b9b7f67-d2fc-4f51-9516-44e29427c4bd","added_by":"auto","created_at":"2026-03-10 13:27:30","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":21966610,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTXN overexpression led to bortezomib resistance in MM cells. a\u003c/strong\u003e RNA-seq analysis showing elevated TXN expression in BTZ-resistant (BTZ-R) RPMI-8226 cells compared to parental RPMI-8226 cells. \u003cstrong\u003eb \u003c/strong\u003eValidation of TXN overexpression at both the mRNA and protein levels in RPMI-8226 and BTZ-R RPMI-8226 cells. \u003cstrong\u003ec\u003c/strong\u003e Cell viability assay of RPMI-8226/BTZ-R RPMI-8226 cells and OPM2/BTZ-R OPM2 cells treated with increasing concentrations of the ferroptosis inducer RSL3 for 24 hours, attached with IC50 curve graphs. \u003cstrong\u003ed-e\u003c/strong\u003e Lipid ROS and intracellular total ROS levels detected by flow cytometry in RPMI-8226/BTZ-R RPMI-8226 cells and OPM2/BTZ-R OPM2 cells treated with RSL3(5μM) for 12 hours. \u003cstrong\u003ef\u003c/strong\u003e Validation of TXN knockdown using lentiviral vector containing shRNA-TXN at mRNA and protein levels in BTZ-R RPMI-8226 MM cell lines. \u003cstrong\u003eg\u003c/strong\u003e Lipid ROS and intracellular total ROS levels detected by flow cytometry in LV-NC BTZ-R RPMI-8226 cells and LV-TXNkd BTZ-R RPMI-8226 cells. \u003cstrong\u003eh\u003c/strong\u003e Cell viability assay of LV-NC and LV-TXNkd BTZ-R RPMI-8226 cells treated with increasing concentrations of the ferroptosis inducer RSL3 for 24 hours, attached with IC50 curve graphs. Data are presented as mean ± SD. *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001, ****P \u0026lt; 0.0001; ns., not significant. Note: all experiments were performed at least 3 different biological replicates, the representative results shown in the main manuscript figures.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/287a6dbb0fc0cf6931cc60b8.png"},{"id":104322669,"identity":"86f93a24-8378-41ba-a6e0-b3c75677e89a","added_by":"auto","created_at":"2026-03-10 13:26:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1176030,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/11ec3ba7-e3d1-4e54-9ebf-40c93631b048.pdf"},{"id":104322817,"identity":"d336f45d-5620-4ac8-94ad-926576490564","added_by":"auto","created_at":"2026-03-10 13:27:36","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3469354,"visible":true,"origin":"","legend":"Supplementary-Figure1","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/ca7f4046f795f1fbbf9c4057.tif"},{"id":104322801,"identity":"88dc2d2e-8ec9-4919-a496-7c4286adb81c","added_by":"auto","created_at":"2026-03-10 13:27:30","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2541000,"visible":true,"origin":"","legend":"Supplementary-Figure2","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/b40f23dee1483dd04d36a204.tif"},{"id":104322819,"identity":"bfccfbe7-8a3f-4a10-80a6-ca0ce60c4b76","added_by":"auto","created_at":"2026-03-10 13:27:36","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":3167928,"visible":true,"origin":"","legend":"Supplementary-Figure3","description":"","filename":"SupplementaryFigure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/0c17dc181ebd328727279cbf.tif"},{"id":104405447,"identity":"8f2f20f7-34f0-4978-81d6-86e5f117251b","added_by":"auto","created_at":"2026-03-11 12:22:55","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":29891628,"visible":true,"origin":"","legend":"Supplementary-Figure4","description":"","filename":"SupplementaryFigure4.tif","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/6a7337ef67eab664c9b432e0.tif"},{"id":104322811,"identity":"0248a46a-d9c6-4e58-993c-b79b0bcab5eb","added_by":"auto","created_at":"2026-03-10 13:27:31","extension":"doc","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":31744,"visible":true,"origin":"","legend":"Supplementary Materials","description":"","filename":"SupplementaryMaterials.doc","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/8523fdbb4a9b90deb6bf6165.doc"},{"id":104322840,"identity":"cfac5112-c267-427f-86db-bf9992896309","added_by":"auto","created_at":"2026-03-10 13:27:40","extension":"tif","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":165888538,"visible":true,"origin":"","legend":"WB-supplementary","description":"","filename":"WBsupplementary.tif","url":"https://assets-eu.researchsquare.com/files/rs-8988709/v1/a41e63c1a007c3e93a49e49b.tif"}],"financialInterests":"(Not answered)","formattedTitle":"IRF1-mediated thioredoxin (TXN) protects multiple myeloma cells from ferroptosis by regulating polyunsaturated fatty acids (PUFAs) and PUFA-containing phospholipid metabolism","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMultiple myeloma (MM) is the second most common hematologic malignancy, driven by the uncontrolled clonal proliferation of malignant plasma cells in the bone marrow[1]. The age-adjusted global incidence of MM is approximately 2.1% in men and 1.5% in women, and MM caused more than 120,000 deaths in 2022[2, 3]. The introduction of proteasome inhibitors (PIs), monoclonal antibodies, and chimeric antigen receptor-engineered T cells (CAR-T)—has markedly improved patient outcomes[4]. Nevertheless, MM remains incurable; most patients relapse and eventually acquire drug resistance, underscoring the need to better understand disease pathogenesis and develop new therapeutic strategies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFerroptosis, first proposed by Dixon in 2012[5], is an iron-dependent form of regulated cell death (RCD) characterized by mitochondrial shrinkage, reduced cristae, and structural damage[6].\u0026nbsp;Unlike apoptosis or necrosis initiating by protein cascades, ferroptosis is governed by three interconnected processes: initiation, defense, and regulation network[7].\u0026nbsp;Initiation involves the Fenton reaction, in which ferrous iron (Fe²⁺) reacts with hydrogen peroxide (H₂O₂) to generate reactive oxygen species (ROS). These ROS subsequently drive the oxidation of PUFA-PLs in cell membranes, causing lethal lipid peroxidation\u0026nbsp;[5, 8]. The primary defense system relies on the glutathione peroxidase 4 (GPX4)–glutathione (GSH) axis[9],\u0026nbsp;with radical-trapping antioxidants (RTAs) providing additional protection against lipid peroxidation[10].\u0026nbsp;Beyond these, a broad regulatory network of enzymes, proteins, pathways, and organelles modulates ferroptosis susceptibility[11, 12, 13, 14].\u0026nbsp;Over the past decade, ferroptosis has been implicated in tumorigenesis [15]\u0026nbsp;and immune escape[16], but its contribution to MM progression remains poorly defined.\u003c/p\u003e\n\u003cp\u003eTXN, an antioxidant protein that forms the thioredoxin system alongside thioredoxin reductase (TXNRD1) and NADPH, regulates multiple cellular processes including proliferation, antioxidant defense, apoptosis, and ferroptosis[17, 18, 19, 20]. Cancer cells frequently exploit TXN to buffer redox stressand support survival under hostile microenvironmental conditions[21]. For example, TXN maintains STAT3 in a reduced, active state, thereby promoting proliferation, metabolic reprogramming, and immune evasion [22]. Inhibition of TXN enhances p53 activity and triggers cell death in castration-resistant prostate cancer, underscoring its role in mutant p53-driven tumors[23]. Moreover, the tumor-promoting effect of TXN is partly attributable to its ability to suppress ferroptosis: the TXN inhibitor ferroptocide (FCD) efficiently induces ferroptosis in breast cancer cells[20], while TXN overexpression rescues GPX4 and GSH depletion in Parkinson’s disease models, preventing ferroptosis[24]. Despite these findings, the role of TXN in MM remains unclear.\u003c/p\u003e\n\u003cp\u003eIn this study, we demonstrate that TXN is highly expressed in MM and correlates with poor prognosis. Mechanistically, TXN promotes MM cell proliferation and ferroptosis resistance by regulating lipid peroxidation through the IRF1/TXN/PUFA/PUFA-PL axis. We further show that bortezomib (BTZ) resistance is linked to TXN upregulation, which enables MM cells to evade ferroptosis and reduces their sensitivity to BTZ. Together, these results identify TXN as a potential therapeutic target in MM.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS ","content":"\u003cp\u003e\u003cstrong\u003eCell Lines and Cell Culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman multiple myeloma (MM) cell lines MM.1S, RPMI-8226, and NCI-H929 were obtained from ATCC (USA). ARD and KMS-11 cells were purchased from Procell (Wuhan, China), and OPM2 and U266 cells were kindly provided by Professor Jinsong Hu (Xi\u0026rsquo;an Jiaotong University Health Science Center, China). All cell lines were cultured in RPMI-1640 medium (HyClone, USA) supplemented with 10% fetal bovine serum (Biological Industries, Israel), 10,000 U/L penicillin, and 100 mg/L streptomycin (BioSharp, China). Cells were maintained at 37 \u0026deg;C in a humidified incubator with 5% CO₂.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBone marrow specimens were collected from MM patients at the Department of Hematology, Second Affiliated Hospital of Xi\u0026rsquo;an Jiaotong University (2019\u0026ndash;2023). Sample collection and analysis were approved by the institutional ethics committee (Approval No. 2015186). Written informed consent was obtained from all patients for the use of their blood and bone marrow samples in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReagents\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRSL3 (HY-100218A, purity \u0026ge; 99.9%), Ferrostatin-1 (HY-100579 , purity \u0026ge; 99.71%), Z-VAD (HY-164388, purity \u0026ge; 99.20%), Necrostatin-1 (HY-15760, purity \u0026ge; 99.89%), and Bortezomib (HY-10227, purity \u0026ge; 98.0%) was purchased from MCE. Erastin(HY-15763, purity \u0026ge;99.62%) was purchased from Solarbio. Ferroptocide (2505218-38-0, purity \u0026ge; 90%) was purchased from Aladdin. All compounds were dissolved in DMSO, aliquoted, and stored at \u0026minus;80 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublic Dataset Analysis and GSEA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGene expression data and clinical information were retrieved from GEO (https://www.ncbi.nlm.nih.gov/geo/), including datasets GSE6477, GSE6691, GSE13591, GSE47552, GSE136400, GSE24080, and GSE31161. Ferroptosis-related genes were obtained from FerrDb (http://www.zhounan.org/ferrdb/current/). Differentially expressed genes were identified across GSE6477, GSE6691, GSE13591, and GSE47552. In GSE24080, patients were stratified into poor- (\u0026lt;2 years) and good-prognosis (\u0026gt;4 years) groups for target screening. TXN expression across MM progression (MGUS, SMM, NDMM, and RRMM) was analyzed using GSE6477. Associations with ISS and R-ISS stages were assessed in GSE24080 and GSE136400. Survival analysis was performed using Kaplan-Meier curves and log-rank tests (p \u0026lt; 0.05 considered significant).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell Viability Assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell viability was measured using the CCK-8 kit (Beyotime, China). MM cells (7 \u0026times; 10\u0026sup3;/well) were seeded in 96-well plates and treated with siRNA, single agents, or drug combinations for up to five days. At designated timepoints, 10 \u0026micro;L of CCK-8 solution was added to each well for 1-4 h before measuring absorbance at 450 nm. Synergy was assessed using CompuSyn software, with combination index (CI) \u0026lt;1 indicating synergy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene Knockdown\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTXN knockdown was achieved using siRNAs (GenePharma, China) or lentiviral shRNA constructs (GeneChem, China). IRF1 knockdown siRNAs were purchased from Stingke (Beijing, China). Transfection efficiency was confirmed by qRT-PCR and Western blot.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLipid Peroxidation Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLipid peroxidation was assessed using BODIPY\u0026trade; 581/591 C11 (Thermo Fisher Scientific). Cells were incubated with the probe for 30 min at 37 \u0026deg;C, washed, and analyzed by flow cytometry. A fluorescence shift from red to green indicated lipid peroxidation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntracellular ROS Measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were incubated with 10 \u0026micro;M DCFH-DA (Sigma-Aldrich) for 30 min at 37 \u0026deg;C. After washing, ROS levels were quantified by flow cytometry (excitation 488 nm, emission 525 nm).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA Sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA-seq was performed on siNC- and siTXN-transfected RPMI-8226 cells, and on BTZ-sensitive and BTZ-resistant RPMI-8226 cells (LC-Bio Technologies, Hangzhou, China). Differential expression was analyzed using DESeq2. GO and KEGG analyses were performed to identify dysregulated pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLipidomic Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLipidomics was conducted on siNC- and siTXN-transfected RPMI-8226 cells, and on Ferroptocide-treated cells (8 \u0026micro;M, 6 h) (LC-Bio). Lipids were extracted using organic solvent precipitation and analyzed by LC-MS. Data processing was performed with XCMS. Metabolites were annotated using MS/MS spectra matched to an in-house library and the LIPID MAPS database. Pathway enrichment was analyzed using KEGG.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChromatin Immunoprecipitation (ChIP)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChIP was performed using a commercial kit (Beyotime, China). Crosslinked chromatin was sonicated and incubated with anti-IRF1 antibody or IgG control. Immunoprecipitated DNA was analyzed by qPCR. IRF1-binding motifs in the TXN promoter were predicted using JASPAR(https://jaspar.genereg.net/)[48].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePromoter Reporter and Dual-Luciferase Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe TXN promoter was cloned into pGL3 reporter vectors (Tsingke, China). Cells were co-transfected with firefly luciferase constructs, Renilla luciferase control plasmid, and where indicated, IRF1 siRNA. Luciferase activity was measured after 48 h using the Dual-Luciferase Reporter Assay System (Yeasen, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eApoptosis Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApoptosis was assessed using Annexin V-PE/RedNucleus II (Bioscience, China). Cells were transfected with siRNA, stained, and analyzed by flow cytometry (FlowJo software).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTransmission Electron Microscopy (TEM)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were fixed with 2.5% glutaraldehyde, post-fixed in osmium tetroxide, dehydrated, embedded in epoxy resin, sectioned (~90 nm), stained with uranyl acetate and lead citrate, and imaged with a Hitachi HT7800 TEM a 120 kV.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative PCR (qPCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA from human samples, mouse tumors and MM cell lines was extracted using TRIzol reagent (GenStar, China) and reverse transcribed into cDNA using HiFiScript cDNA Synthesis Kit (Cwbio, China). qPCR was performed using SuperStar Universal SYBR Master Mix (Cwbio, China) according to the manufacturer\u0026apos;s protocol. The primers used are listed in Table S1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoblotting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal protein from human samples, mouse tumors and MM cell lines was extracted with RIPA lysis buffer (Cwbio, China), and the protein concentration was measured using the BCA Protein Quantification Kit (Yeasen, China). The primary antibodies used were as follows: anti‐TXN (1:5000, 12 kDa, 66475-1-Ig, Proteintech, China), anti‐GAPDH (1:5000, 36 kDa, 10494-1-AP, \u0026nbsp;Proteintech, China), anti‐IRF1 (1:2000, 50 kDa, Proteintech, China).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal Studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal experiments were approved by the Ethics Committee of Xi\u0026rsquo;an Jiaotong University Health Science Center (Approval No. 2025-2662) and were conducted in accordance with the institutional guidelines for the care and use of laboratory animals. Male BALB/c nude mice (3 weeks old) were purchased from GemPharmatech (China). Mice were allowed to acclimate for at least one week prior to any experimental procedures. Mice were housed under specific pathogen-free (SPF) conditions in individually ventilated cages (IVCs).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnimal health and welfare were monitored daily by trained personnel. To establish subcutaneous xenograft models, RPMI-8226 cells stably transduced with LV-NC and LV-TXNkd were injected into the right/left flank of each mouse. Tumor dimensions (length and width) were measured every two days using a caliper, and tumor volume was calculated using the formula: Volume (mm\u0026sup3;) = (width\u0026sup2; \u0026times; length) / 2. Once tumors reached 100 mm\u0026sup3;, mice received intraperitoneal BTZ (0.5 mg/kg, every other day) or PBS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMice were humanely euthanized when any individual tumor diameter reached 15 mm to prevent undue suffering. Euthanasia was performed by carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) asphyxiation in a gradual-fill chamber, followed by cervical dislocation as a secondary confirmation of death. Immediately after euthanasia, tumors were resected, weighed, and divided for subsequent analyses: one portion was fixed in 4% paraformaldehyde for immunohistochemistry (IHC), and the remainder was snap-frozen in liquid nitrogen for ROS and lipid ROS assays.\u003c/p\u003e\n\u003cp\u003eTumor size/burden limitations and compliance: The animal study protocol, as approved by the Ethics Committee of Xi\u0026rsquo;an Jiaotong University Health Science Center, stipulated a maximum permitted tumor burden of 1.5 cm in the longest diameter to prevent undue animal suffering. Throughout the study, tumor growth was closely monitored. We confirm that this maximum tumor size/burden was not exceeded in any animal. Humane endpoints were strictly enforced to ensure compliance with this ethical standard. In accordance with journal policy, no images of live animals bearing tumors are presented; all excised tumors were photographed adjacent to a scale ruler for size documentation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experiments were performed with 3-6 biological replicates. Differences between two groups were analyzed using Student\u0026rsquo;s t-test or Mann-Whitney U test. Multiple group comparisons were performed by one-way ANOVA with Bonferroni post hoc test. p \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch4\u003eTXN is highly expressed in MM and associated with poor prognosis\u003c/h4\u003e\n\u003cp\u003eTo identify ferroptosis-related genes linked to aggressive MM, we first analyzed four MM-related RNA sequencing datasets from GEO (GSE6477, GSE6691, GSE13591, and GSE47552) and identified 14 differentially expressed genes (DEGs) were identified between MM patients and healthy donors (Fig. 1a), including CKS2 [25], GADD45A [12], and TXN, which are associated with cancer progression and ferroptosis. Next, we examined prognosis-related ferroptosis regulators using the GSE24080 dataset and ferroptosis-related gene sets from FerrDb.\u0026nbsp;Comparing patients with good prognosis (overall survival \u0026gt;4 years) versus poor prognosis (overall survival \u0026lt;2 years), gene set enrichment analysis (GSEA) revealed 41 ferroptosis suppressor genes associated with poor outcomes (Fig. 1b). TXN was among these prognosis-related suppressors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eComprehensive analysis across GEO datasets showed that TXN expression was significantly higher in MM compared with normal plasma cells (NPCs), monoclonal gammopathy of undetermined significance (MGUS), and smoldering MM (SMM) (Fig. 1c). High TXN expression correlated with advanced International Staging System (ISS) and Revised ISS (R-ISS) stages (Fig. 1d-e) and was significantly elevated in relapsed versus newly diagnosed patients, indicating a role in disease recurrence (Fig. 1f). Kaplan–Meier analysis confirmed that high TXN expression predicted shorter overall survival (OS) and event-free survival (EFS) (Fig. 1g-h).\u003c/p\u003e\n\u003cp\u003eFurthermore, we examined TXN expression in both MM patients and MM cell lines. Compared with healthy donors, MM patients showed higher TXN expression than healthy donors, with relapsed/refractory MM (RRMM) patients exhibiting higher levels than newly diagnosed MM (NDMM) patients (Fig. 1i). TXN expression also increased with more advanced ISS and R-ISS stages (Fig. 1j). MM cell lines (MM.1S, U266, ARD, RPMI-8226, H929, OPM2, and KMS-11) expressed higher TXN at both mRNA and protein levels compared with bone marrow stromal cells (HS-5) (Fig. 1k).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Taken together, these findings suggested that TXN, as a key regulator of ferroptosis, is highly expressed in MM and orrelates with advanced disease stage and poor prognosis.\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eSilencing TXN inhibited MM cell proliferation and tumor growth\u003c/h4\u003e\n\u003cp\u003eTo determine whether TXN contributes to MM progression through ferroptosis, we silenced TXN expression in two human MM cell lines with high endogenous TXN levels (RPMI-8226 and MM.1S) using specific small interfering RNAs (siRNAs) (Fig. 2a-b). CCK-8 assays demonstrated that TXN knockdown (siTXN) significantly reduced cell viability compared with negative control siRNA-treated cells (siNC) (Fig. 2c). Similarly, treatment with the TXN inhibitor Ferroptocide (FCD) decreased MM cell viability (Fig. 2d, Supplementary Fig. 1d-e). Notably, TXN knockdown did not significantly affect apoptosis in MM cells (Supplementary Fig. 1a-b), suggesting that reduced proliferation rather than apoptosis contributed to the observed growth inhibition.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; To evaluate the effects of TXN inhibition \u003cem\u003ein vivo\u003c/em\u003e, we generated stable TXN knockdown MM cell lines using lentiviral transduction (LV-TXNkd) (Supplementary Fig. 1c). BALB/c nude mice injected with LV-TXNkd MM cells exhibited significantly reduced tumor burden than controls (Fig. 2e), concomitant with successful knockdown of TXN protein (Fig. 2f). Slower tumor growth, and higher body weight compared with mice bearing control LV-NC MM cells (Fig. 2g-h). Immunohistochemistry (IHC) analysis confirmed markedly decreased TXN and Ki-67 expression in tumors derived from LV-TXNkd cells relative to controls (Fig. 2i, Supplementary Fig. 1f).\u003c/p\u003e\n\u003cp\u003eCollectively, these findings indicate that TXN is critical for MM cell proliferation and tumor progression, highlighting its potential as a therapeutic target in MM.\u003c/p\u003e\n\u003ch3\u003eTXN protects MM cells from lipid peroxidation-induced ferroptosis\u003c/h3\u003e\n\u003cp\u003eTo further investigate whether TXN promotes MM progression by suppressing lipid peroxidation-induced ferroptosis, we measured lipid ROS levels in TXN-knockdown MM cells. Compared with control siRNA-treated cells (siNC), TXN knockdown (siTXN) significantly increased lipid ROS (Fig. 3a) and total intracellular ROS levels (Fig. 3b). Similarly, treatment with the TXN inhibitor Ferroptocide (FCD) markedly elevated both lipid ROS and total ROS in MM cells (Fig. 3c-d).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo confirm that these effects were mediated by ferroptosis, we performed rescue experiments using ferroptosis inhibitor Ferrostatin-1 (Fer-1). Fer-1 significantly reversed FCD-induced lipid peroxidation, ROS accumulation, and cell death, whereas the apoptosis inhibitor Z-VAD and the necroptosis inhibitor Necrostatin-1 (NEC-1) had minimal effect (Fig. 3e-f, Supplementary Fig. 2a). Consistent with these \u003cem\u003ein vitro\u003c/em\u003e findings, tumor cells derived from mice bearing LV-TXNkd MM cells exhibited elevated lipid ROS and total ROS compared with LV-NC controls (Fig. 3g-h). IHC results further confirmed increased levels of 4-Hydroxynonenal (4-HNE), a lipid peroxidation byproduct and well-recognized ferroptosis marker, in tumors from LV-TXN knockdown mice (Fig. 3i, Supplementary Fig. 2b).\u003c/p\u003e\n\u003cp\u003eTo further validate the role of TXN in ferroptosis, we treated TXN-knockdow MM cells with the ferroptosis inducer RSL3. siTXN cells displayed higher lipid peroxidation and ROS levels than siNC cells (Supplementary Fig. 2c-d). Additionally, we examined mitochondrial morphology in MM cells treated with siNC, siTXN, FCD (8 μM, 6 h), or RSL3 (5 μM, 6 h) using transmission electron microscopy (TEM). Mitochondria in TXN-deficient, FCD-treated, or RSL3-treated cells exhibited classic ferroptotic changes, including swelling, reduced electron density, and cristae loss (Fig. 3j).\u003c/p\u003e\n\u003cp\u003eTaken together, these results demonstrate that TXN protects MM cells from lipid peroxidation-induced ferroptosis, highlighting its role as a key ferroptosis suppressor in MM.\u003c/p\u003e\n\u003ch3\u003eNegligible impact of TXN knockdown on transcriptomic profiles\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003eTo explore how TXN regulates lipid peroxidation-induced ferroptosis in MM cells, we performed transcriptomic sequencing in MM cells transfected with either siNC or siTXN. Surprisingly, TXN knockdown induced only modest changes in gene expression, with 115 genes upregulated and 139 genes downregulated, and did not significantly alter classical ferroptosis-related genes such as SLC7A11, GPX4, or ACSL4 (Fig. 4a). DEGs were subsequently subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. No significant enrichment of ferroptosis pathways was observed in TXN-deficient cells (Fig. 4b-d, Supplementary Fig. 3a-b).\u0026nbsp;However, DEGs were enriched in PUFA-related enzymatic activities and PUFA metabolism pathways, including linolenic acid and arachidonic acid (AA) epoxygenase activity (Fig. 4b-d).\u003c/p\u003e\n\u003cp\u003eThese results suggest that TXN, as an antioxidant protein, was more likely functions downstream in the redox cascade—modulating the terminal stages of lipid peroxidation—without broadly impacting upstream gene expression networks. Based on this, we focused subsequent investigations on the regulation of PUFA metabolism.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTXN knockdown promoted ferroptosis by facilitating PUFA and PUFA-PL biosynthesis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the potential role of TXN in lipid metabolism, we performed a comprehensive lipidomic profiling of TXN-knockdown (TXN-KD) MM cells using liquid chromatography-mass spectrometry (LC-MS) (Fig. 4e). Cells treated with the TXN inhibitor Ferroptocide (FCD, 8 µM, 6 h) were also profiled. Over 2,000 lipid metabolites were identified (Fig. 4f) and classified into six major categories: fatty acids (FA), glycerolipids (GL), glycerophospholipids (GP), sphingolipids (SP), sterol lipids (ST), and prenol lipids (PR). In total, 1,969 lipid species were quantified, of which 183 were significantly altered in TXN-KD cells compared with controls (Fig. 4g-h). KEGG enrichment analysis revealed significant enrichment in PUFA metabolism pathways, consistent with transcriptomic results (Fig. 4i). A regulatory network based on KEGG annotations highlighted alterations in linoleic acid, α-linolenic acid, and arachidonic acid metabolism (Fig. 4j). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGlobal lipid composition analysis revealed that glycerophospholipids (GP) constituted the largest proportion of lipids, followed by GL and SP (Fig. 5a). FCD treatment increased GL and decreased GP, prompting a detailed analysis of GP subclasses, which included phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylglycerol (PG), and phosphatidylinositol (PI)—collectively referred to as phospholipids (PLs). Cardiolipin (CL), lysophospholipids (Lyso-PL), and phosphatidylinositol phosphates (PLP) were also included in the GP category, with PLs being the most abundant (Supplementary Fig. 4a). The relative composition of PLs was broadly similar across groups, dominated by PC and PE (Fig. 5b). PLs were further subclassified into diacyl-PLs, ether-linked PLs (PL-O), and vinyl ether-linked PLs (PL-P), with diacyl-PC and diacyl-PE prevailing in all groups (Fig. 5c, Supplementary Fig. 4b).\u003c/p\u003e\n\u003cp\u003eAnalysis of FA composition revealed that TXN deficiency, whether by knockdown or pharmacological inhibition, induced broad alterations in FA profiles (Fig. 5d-e). Notably, PUFA abundance was significantly increased in both TXN-KD and FCD-treated cells (Fig. 5f-g), including key substrates for PL biosynthesis such as FA 22:4 and FA 20:5, as well as FA 18:2 (linoleic acid), FA 18:3 (α-linolenic acid), and FA 22:5 (docosapentaenoic acid) (Supplementary Fig. 4c). Treatment with AA further confirmed the role of PUFA in ferroptosis, significantly reducing MM cell viability in a dose-dependent manner (Supplementary Fig. 4d).\u003c/p\u003e\n\u003cp\u003ePLs were categorized by fatty acid content into saturated (SFA-PLs), monounsaturated (MUFA-PLs), and polyunsaturated (PUFA-PLs), the latter serving as terminal substrates for lipid peroxidation during ferroptosis. TXN knockdown altered both MUFA-PLs and PUFA-PLs (Fig. 5h, Supplementary Fig. 4e), while FCD treatment caused more pronounced increases in PUFA-PLs (Fig. 5i, Supplementary Fig. 4f). Then, we calculated an estimated cellular phospholipid peroxidation index (CPI) based on the known relative hydrogen atom transfer propagation rate constants of fatty acids[26, 27]. The results showed that FCD-treated cells had the highest CPI, with TXN-KD cells showing a trend toward increased CPI (Fig. 5j). Analysis of PL double bond content showed no significant change in TXN-KD cells, whereas FCD treatment enriched PLs with more than two double bonds (Supplementary Fig. 4g-h), further supporting enhanced ferroptosis susceptibility. Finally, examination of specific PUFA-PL species showed that TXN knockdown increased PUFA-PC 22:4 levels, a key pro-ferroptotic lipid (Fig. 5m), whereas FCD treatment broadly elevated total PUFA-PLs, reduced MUFA-PLs, and specifically increased PUFA-PC and PUFA-PE species containing 22:4 and 20:4 (Fig. 5k-o).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn summary, TXN deficiency enhances PUFA and PUFA-PL biosynthesis, indicating that TXN protects MM cells from lipid peroxidation-induced ferroptosis by suppressing the formation of pro-ferroptotic lipids.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIRF1 promoted ferroptosis in MM cells by repressing TXN expression\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify upstream regulators of TXN in ferroptosis, we analyzed the promoter of \u003cem\u003eTXN\u003c/em\u003e gene using the NCBI, JASPAR, and UCSC Genome Browser databases. These analyses revealed several candidate transcription factors (TFs), including KLF5, EGR1, and IRF1. To determine which TF regulates TXN in MM, we examined their expression in bone marrow samples from healthy donors and MM patients and performed Kaplan-Meier survival analysis. Among the candidates, IRF1 was significantly downregulated in MM patients compared with healthy donors (Fig. 6a), and lower IRF1 expression correlated with poorer overall survival (Fig. 6b). An analysis of MM patient samples demonstrated a significant inverse correlation between the expression of IRF1 and TXN (Fig. 6c).\u003c/p\u003e\n\u003cp\u003eNext, we knocked down IRF1 in MM cells using siRNA. This led to a marked increase in TXN expression at both the mRNA and protein levels (Fig. 6d-e), suggesting that IRF1\u0026nbsp;may\u0026nbsp;functions as a transcriptional repressor of TXN. To confirm this regulatory relationship, we identified a potential IRF1-binding motif on the TXN promoter using JASPAR (Fig. 6f) and performed chromatin immunoprecipitation (ChIP) assays. These assays demonstrated strong IRF1 binding to the TXN promoter in MM.1S cells (Fig. 6g-h). We then constructed PGL3-BASIC luciferase reporter plasmids containing either the wild-type (WT) or mutated (Mut) IRF1-binding motif. Dual-luciferase assays showed that IRF1 knockdown partially restored TXN promoter activity (Fig. 6i), further supporting its role as a negative regulator of TXN transcription.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, we assessed whether IRF1 modulates ferroptosis in MM cells through TXN. While IRF1 knockdown alone did not significantly affect lipid ROS levels, it markedly reduced RSL3-induced lipid ROS and total ROS accumulation (Fig. 6j), indicating that downregulating IRF1 could relieve RSL3-induced ferroptosis in MM cells by upregulating TXN.\u003c/p\u003e\n\u003cp\u003eIn summary, IRF1 is downregulated in MM and acts as a transcriptional repressor of TXN. Reduced IRF1 expression elevates TXN levels, which protects MM cells from ferroptosis and may contribute to disease progression.\u003c/p\u003e\n\u003ch4\u003eTXN deficiency-induced ferroptosis synergized with bortezomib to effectively target MM cells\u003c/h4\u003e\n\u003cp\u003eBortezomib (BTZ), the first proteasome inhibitor approved by the U.S. Food and Drug Administration (FDA) for multiple myeloma (MM) [28], exerts its therapeutic effects through multiple mechanisms, including the induction of apoptosis [29] , endoplasmic reticulum and Golgi stress [30], and disruption of diverse cellular pathways [31]. We hypothesized that ferroptosis may act synergistically with BTZ to enhance its anti-myeloma efficacy. To test this, we treated MM cells with the ferroptosis inducers RSL3 or erastin in combination with BTZ. Compared to monotherapy, the combination treatment significantly enhanced the inhibition of MM cell viability (Fig. 7a-b). Consistently, co-treatment with the TXN inhibitor FCD and BTZ further suppressed cell viability compared with either agent alone (Fig. 7c), suggesting that TXN inhibition can potentiate the anti-myeloma effect of BTZ. The calculated combination index (CI) values, which quantify the drug synergy, are summarized in Table 1.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable.1 Synergistic effect of bortezomib and ferroptosis inducers\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"574\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 97px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBTZ\u0026nbsp;(nM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRSL3\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e\u0026mu;M\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 171px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRPMI-8226\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMM.1S\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.68299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.50239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.68797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.74150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.51537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.51607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.41920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.67980\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.44158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.78583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.32532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.99838\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.56054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.34467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.58795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.73805\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.39133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.34737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.35666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.67694\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.33386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.54319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.22850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.82191\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.41539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.22930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.26200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.47361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.32644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.28802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.21705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.57825\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.25912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.41062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.19542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.84727\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eErastion\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e\u0026mu;M\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.88105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.33501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.97224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e3.56292\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.74353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.18148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.91211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e1.73011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.56578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.27673\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.69590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.76883\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.83072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.24596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.44208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.20032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.64335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.95094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.14310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.06821\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.44096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.95541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.12395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.08961\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.70118\u003c/p\u003e\n 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\u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.23386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.53647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.06712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.06603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFerrotpcide\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e\u0026mu;M)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.71841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.65960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.80794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.55951\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.65624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.79739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.76495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.46769\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.59104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.99473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.72070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.41067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.50542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.51309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.71820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.46462\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.44228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.55140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.74633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.61884\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e10.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.38902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.62127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.64657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.38916\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.30667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.76359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.71285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.86104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.27898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.77853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.60198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.58272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.23881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.79394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.53656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 61px;\"\u003e\n \u003cp\u003e0.47799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTwo multiple myeloma cell lines (RPMI-8226 and MM.1S) were treated with bortezomib (BTZ) in combination with either RSL3, erastin, or ferroptocide at the indicated concentrations for 24 h. \u0026ldquo;Effect\u0026rdquo; corresponds to cell viability. The combination index (CI) was calculated using CompuSyn software to evaluate drug synergy, where CI \u0026lt; 1 indicates a synergistic interaction.\u003c/p\u003e\n\u003cp\u003eWe next evaluated this synergistic effect \u003cem\u003ein vivo\u003c/em\u003e. Nude mice were subcutaneously injected with RPMI-8226 cells transfected with either LV-NC or LV-TXNkd. Once tumors reached ~100 mm\u0026sup3;, mice received intraperitoneal BTZ (0.5 mg/kg, every other day) or PBS (Fig. 2g). As expected, BTZ alone suppressed tumor growth, but the LV-TXNkd + BTZ group showed a significantly greater reduction in tumor volume and growth rate compared with the LV-NC + BTZ group (Fig. 7d-e). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCollectively, these findings demonstrated that TXN deficiency-induced ferroptosis could synergize with BTZ both to suppress MM progression \u003cem\u003ein vitro\u003c/em\u003e and i\u003cem\u003en vivo\u003c/em\u003e.\u003c/p\u003e\n\u003ch4\u003eTXN overexpression promotes bortezomib resistance in MM cells via ferroptosis evasion\u003c/h4\u003e\n\u003cp\u003e\u0026nbsp;To investigate whether TXN contributes to BTZ resistance, we established BTZ-resistant (BTZ-R) RPMI-8226 and OPM2 cell lines by stepwise exposure to increasing BTZ concentrations. RNA sequencing showed TXN was significantly upregulated in BTZ-R RPMI-8226 cells (Fig. 8a), which was validated by RT-qPCR and Western blot (Fig. 8b).\u003c/p\u003e\n\u003cp\u003eWe next examined ferroptosis sensitivity. When treated with the ferroptosis inducer RSL3, BTZ-R RPMI-8226 cells exhibited significantly higher viability than parental cells (IC50: 0.981 \u0026mu;M vs. 1.784 \u0026mu;M), and similar results were observed in BTZ-R OPM2 cells (IC50: 2.059 \u0026mu;M vs. 6.462 \u0026mu;M) (Fig. 8c-d). Consistently, BTZ-R MM cells accumulated less lipid ROS and total ROS than parental cells following RSL3 treatment (Fig. 8e-f), indicating that ferroptosis evasion contributes to BTZ resistance, likely through elevated TXN expression.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo directly assess the role of TXN, we established stable TXN knockdown in BTZ-R RPMI-8226 cells via lentiviral transduction (Fig. 8g). TXN knockdown increased lipid ROS and total ROS levels in BTZ-R cells (Fig. 8h), suggesting that loss of TXN restores susceptibility to lipid peroxidation\u0026ndash;driven ferroptosis. Moreover, RSL3 treatment further reduced cell viability in TXN-deficient BTZ-R cells compared with controls (IC50: 2.044 \u0026mu;M vs. 1.868 \u0026mu;M) (Fig. 8h).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In summary, BTZ-resistant MM cells evade ferroptosis by upregulating TXN, thereby reducing their sensitivity to BTZ. Targeting TXN may therefore help overcome BTZ resistance in MM.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eFerroptosis, a recently recognized form of RCD, has emerged as a critical process in cancer biology and a promising therapeutic target[5]. MM is a highly heterogeneous hematological malignancy. Dysregulated iron and lipid metabolism in MM contributes to uncontrolled cell proliferation, abnormal differentiation, and drug resistance[32, 33], and may also influence the process of ferroptosis. Yet, the role of ferroptosis in MM progression has remained unclear. In this context, we identify thioredoxin (TXN) as a ferroptosis suppressor in MM. Mechanistically, TXN limits lipid peroxidation and protects cells from ferroptotic death through the IRF1–TXN–PUFA/PUFA-PL axis. We also show that BTZ-resistant MM cells upregulate TXN, enabling ferroptosis evasion and diminishing drug sensitivity. Together, these findings establish TXN as a central regulator of ferroptosis and a potential therapeutic target in MM, especially in the setting of drug resistance.\u003c/p\u003e\n\u003cp\u003eTXN is a key antioxidant protein that maintains redox homeostasis by reducing protein disulfides and modulating redox-sensitive signaling pathways. Prior studies have implicated TXN in ferroptosis regulation. For example, Bai et al.[24]\u0026nbsp;showed that TXN protects against MPP+/MPTP-induced ferroptosis through GPX4 upregulation. While in lung adenocarcinoma, pharmacological activation of retinoic acid receptor α enhanced TXN expression and suppressed ferroptosis[34].\u0026nbsp;These observations underscore the relevance of the System XC\u003csup\u003e-\u003c/sup\u003e/Cys/TXN/TXNRD axis in ferroptosis control. However, the ferroptosis-related role of TXN in MM has been largely unexplored. Our data demonstrate that TXN is significantly upregulated in MM, correlating with disease progression, advanced stage, relapse, and poor prognosis.\u0026nbsp;Both genetic silencing and pharmacological inhibition of TXN reduced MM cell viability and triggered ferroptosis, consistent with prior work showing that thioredoxin inhibitors such as ferroptocide induce ferroptosis in solid tumors[35].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;A defining feature of ferroptosis is the peroxidation of PUFAs incorporated into phospholipids, particularly those with chains longer than 20 carbons[36, 37, 38].\u0026nbsp;Our lipidomic analysis showed that TXN knockdown or pharmacological inhibition enriched PUFA species, such as FA 18:2, FA 18:3, FA 20:5, FA 22:4, and FA 22:5. Treatment with arachidonic acid (AA, FA 20:4) alone induced MM cell death in a dose- and time-dependent manner, supporting the functional role of PUFA enrichment. Consistently, Lee et al.[36]\u0026nbsp;conducted a lipid profiling analysis in the mesenchymal-type gastric cancer cells following upregulation of ELOVL5 and FADS1. Their results showed enrichment of AA (FA 20:4) and adrenic acid (AdA, FA 22:4), which are required for ferroptosis, thereby enhancing ferroptotic sensitivity. Dierge et al[34]. reported that excess uptake of n-3 and n-6 PUFA could trigger ferroptosis in cancer cells under ambient acidosis. Collectively, these findings suggest that PUFAs are primary targets of lipid peroxidation in ferroptosis, and modulation of PUFA biosynthesis can influence ferroptotic sensitivity across different cancer cells. PUFA-PLs are equally critical, as their incorporation into membranes makes them primary substrates for lethal lipid peroxidation. We observed that TXN knockdown preferentially elevated PUFA-PC species containing FA 22:4, while pharmacological inhibition produced a broader increase in PUFA-PLs, especially PUFA-PC and PUFA-PE species containing FA 20:4 and FA 22:4. This suggests that pharmacological inhibition exerts a stronger metabolic effect than knockdown alone. Kagan et al.[37]\u0026nbsp;performed global redox phospholipidomics LC-MS/MS analysis of RSL3-treated Pfa1 cells, demonstrating that AA- and AdA-containing phospholipid species were most responsive, highlighting these species as key lipid death signals. Additionally, Morgan et al.[39]\u0026nbsp;demonstrated that variations in PUFA-PLs content underpin the differential susceptibility of immune cells to ferroptosis, specifically, with low PUFA-PL content conferring resistance in activated neutrophils. Collectively, our findings align with reports that AA- and AdA-containing phospholipids act as key death signals and that PUFA-PL content determines cell-type-specific ferroptotic susceptibility.\u003c/p\u003e\n\u003cp\u003eWe further identified IRF1 as a direct transcriptional repressor of TXN. IRF1 downregulation in MM was associated with worse prognosis, and IRF1 knockdown increased TXN levels and reduced ferroptotic sensitivity. IRF1 has been widely studied for its tumor-suppressive functions[40, 41]. These findings extend the tumor-suppressive role of IRF1 and establish a new regulatory axis in which IRF1 represses TXN to promote ferroptosis.\u003c/p\u003e\n\u003cp\u003eTo explore therapeutic relevance, we combined BTZ with the TXN inhibitor FCD or ferroptosis inducers. Co-treatment produced strong synergy in suppressing MM cell viability \u003cem\u003ein vitro\u003c/em\u003e and tumor growth \u003cem\u003ein vivo\u003c/em\u003e. This suggests that the efficacy of BTZ can be enhanced by promoting ferroptosis. Prior studies support this concept: RSL3 and BTZ have been shown to synergize through glutathione depletion[42]; AP-1 inhibition sensitizes MM cells to BTZ by inducing ferroptosis[43]; and BTZ promotes ferritinophagy-mediated iron release, reinforcing synergy with ferroptosis inducers[44]. Importantly, we demonstrated that BTZ-resistant MM cells display reduced sensitivity to ferroptosis and upregulate TXN, suggesting that TXN-mediated ferroptosis evasion contributes to drug resistance. Similar mechanisms have been reported in other malignancies, where ferroptosis modulation impacts BTZ sensitivity[45, 46]. TXN has also been implicated in BTZ resistance through mitophagy suppression and mTOR/ERK activation, underscoring its multifaceted role in therapy resistance[47]. Together, these findings indicated that ferroptosis dysregulation underlies BTZ resistance in MM, and that targeting TXN or related pathways may provide a strategy to overcome relapse.\u003c/p\u003e\n\u003cp\u003eHowever, our study has several limitations. Firstly, most of our functional experiments were performed using MM cell lines rather than primary MM cells from patients. Secondly, it remains unclear whether the combination treatment could impact extramedullary infiltration of MM.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn summary, we show that TXN protects MM cells from ferroptosis by suppressing PUFA and PUFA-PL accumulation, and that IRF1 represses TXN transcription to enhance ferroptotic sensitivity. Elevated TXN expression contributes to BTZ resistance by enabling ferroptosis escape. These findings identify TXN as a potential therapeutic target for MM and highlight ferroptosis modulation as a promising strategy to improve outcomes, particularly in relapsed or refractory disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEGEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the colleagues at the Department of Hematology, The Second Affiliated Hospital of Xi’an Jiaotong University, for their assistance in sample collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequencing data generated in this study have not been deposited in a public repository at the time of submission. These data will be made available in the NCBI Gene Expression Omnibus (GEO) prior to publication. During the review process, the data are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study involving human participants was approved by the Institutional Ethics Committee of The Second Affiliated Hospital of Xi’an Jiaotong University (Approval No.: 2015186). The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. All participants provided written informed consent prior to participation. The animal experiments were approved by the Ethics Committee of Xi’an Jiaotong University Health Science Center (Approval No.: 2025-2662). All procedures were conducted in accordance with institutional and national guidelines for the care and use of laboratory animals. 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Patients with relapsed or refractory MM face poor survival, highlighting the need for novel therapeutic targets. Ferroptosis, an iron-dependent form of regulated cell death, is governed by a complex network of enzymes, proteins, pathways, and organelles, and has been implicated in various diseases. In this study, we identified thioredoxin (TXN), as a key suppressor of ferroptosis, was among the top ferroptosis-related genes linked to poor prognosis in MM patients. Functionally, TXN loss impaired MM progression by enhancing ferroptosis largely through regulating polyunsaturated fatty acids (PUFAs) and PUFA-containing phospholipids (PUFA-PLs), the major substrates for lipid peroxidation. TXN deficiency promoted ferroptosis by increasing PUFA biosynthesis and their incorporation into lipid peroxidation pathways. We further discovered that interferon regulatory factor 1 (IRF1), downregulated in MM, acts as a transcriptional repressor of TXN. Additionally, we demonstrated that bortezomib (BTZ)-resistant MM displayed elevated TXN expression, which enabled them to evade ferroptosis and diminished their sensitivity to BTZ.\u003c/p\u003e\n\u003cp\u003eIn conclusion, our findings revealed that IRF1-mediated regulation of TXN modulates PUFA/PUFA-PL metabolism to protect MM cells from ferroptosis, establishing TXN as a promising therapeutic target for overcoming ferroptosis resistance and improving treatment outcomes in MM.\u003c/p\u003e","manuscriptTitle":"IRF1-mediated thioredoxin (TXN) protects multiple myeloma cells from ferroptosis by regulating polyunsaturated fatty acids (PUFAs) and PUFA-containing phospholipid metabolism","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-10 13:25:06","doi":"10.21203/rs.3.rs-8988709/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2026-03-23T14:35:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-03-23T12:50:49+00:00","index":1,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-03-17T10:44:48+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-04T15:50:16+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-03-04T15:47:02+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-03-04T15:04:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-02T11:25:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Death \u0026 Disease","date":"2026-02-27T13:43:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-27T13:43:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-and-disease","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddis","sideBox":"Learn more about [Cell Death \u0026 Disease](http://www.nature.com/cddis/)","snPcode":"41419","submissionUrl":"https://mts-cddis.nature.com/cgi-bin/main.plex","title":"Cell Death \u0026 Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"56bcea4f-31d8-4363-b66c-e656949aafe5","owner":[],"postedDate":"March 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":63927476,"name":"Biological sciences/Cancer/Haematological cancer/Myeloma"},{"id":63927477,"name":"Biological sciences/Cancer/Cancer metabolism"},{"id":63927478,"name":"Biological sciences/Cell biology/Cell death"},{"id":63927479,"name":"Biological sciences/Cell biology/Mechanisms of disease"},{"id":63927480,"name":"Biological sciences/Cell biology/Cell signalling/Lipid signalling"}],"tags":[],"updatedAt":"2026-03-23T14:42:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-10 13:25:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8988709","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8988709","identity":"rs-8988709","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}