The cells used in this study were the human embryonic kidney cell line HEK293T (CL-0005, Procell, Wuhan, Hubei, China) and the human triple-negative breast cancer cell line MDA-MB-231 (CL-0150, Procell, Wuhan, Hubei, China). Both were maintained in DMEM medium (11995065, Gibco, Shanghai, China) enriched with 10% fetal bovine serum (FBS, 164210, Procell, Wuhan, Hubei, China) and containing 100 U/mL penicillin and 100 U/mL streptomycin. Penicillin/streptomycin was obtained from NCM (C100C5, NCM, Suzhou, Jiangsu, China). Cells were grown at 37 °C in an atmosphere containing 5% carbon dioxide. The cell lines used in this study underwent short tandem repeat (STR) profiling and tested negative for mycoplasma contamination.

Lentiviral technology was used to construct MDA-MB-231 cell lines that were stably transfected with vector and AKR1B10 and then screened with puromycin. The cell model for induction of ferroptosis was established using RSL3 (HY-100218A, MCE, Shanghai, China). Initial verification of the ferroptosis cell model was conducted using a 96-well plate format. MDA-MB-231 cells with high or low expression of AKR1B10 were exposed to varying concentrations (0–10 µM) of RSL3, either alone or in combination with the specific inhibitor OSU-T315 (0–5 µM), for 24 h. For the experiments involving fatty acid pretreatment, cells were first incubated for 2 h with fatty acids [300 µM palmitic acid (PA) or 50 µM arachidonic acid (AA)] dissolved in basal or complete culture medium, then treated with RSL3 (0–10 µM) for 24 h. Cell viability was assessed using a cell counting kit-8 (CCK8) assay following the manufacturer’s protocol. For the experimental protocol, vector and AKR1B10 cells were divided into the following treatment groups: RSL3 at various concentrations (0–10 µM) for 24 h, OSU-T315 (T5485, Topscience, Shanghai, China) at various concentrations (0–5 µM) for 24 h, a combination of OSU-T315 (2.5 µM or 5 µM) and RSL3 (2.5 µM) for 24 h, a combination of PA (300 µM, KC001, Xi’an Kunchuang, Xi’an, Shaanxi, China) and RSL3 (0–10 µM) for 24 h, a combination of AA (50 µM, KC014, Xi’an Kunchuang, Xi’an, Shaanxi, China) and RSL3 (0–10 µM) for 24 h, and fatty acids at various concentrations (0–600 µM PA or 0–100 µM AA) for 24 h or 48 h. For cell rescue experiments, the ferroptosis inhibitor ferrostatin-1 (Fer-1, 5 µM, S7243, Selleck, Shanghai, China) was applied 2 h prior to single or combination therapies and maintained throughout treatment.

The AKR1B10 DNA sequence was retrieved from the NCBI website (https://www.ncbi.nlm.nih.gov). The detailed sequence can be found in the Supplementary Materials. Lentiviral transduction was performed using the pCDH plasmid to establish MDA-MB-231 cell lines with or without AKR1B10 overexpression. Plasmids were obtained from Shanghai Kelei Biotechnology (Shanghai, China) and transfected using Lipofectamine 2000 reagent (11668019, Invitrogen, Shanghai, China). A mixture (4:3:1) of the target plasmid, packaging plasmid (psPAX2), and envelope plasmid (pMD2.G) was introduced into HEK293T cells to generate lentivirus and subsequently harvested to infect MDA-MB-231 cells. After 48 h of infection, 2 µg/mL puromycin (ST551, Beyotime, Shanghai, China) was added to select for stably expressing cell lines.

A total of 3000 cells were seeded (100 µL per well) in a 96-well plate and incubated overnight at 37 °C. Complete or basic culture medium containing various concentrations of drugs was added and the cells incubated for the required time. The medium was subsequently substituted with complete medium containing 10% CCK8 reagent (C6005, NCM, Suzhou, Jiangsu, China), and the absorbance was recorded at 450 nm using a microplate reader (SpectraMax® iD3, Molecular Devices, Shanghai, China). Cell viability was calculated using the following formula: cell viability (%) = (A_sample – A_blank)/(A_control – A_blank) $\times$ 100, where A represents the absorbance value.

MDA-MB-231 cells were cultured in 6-well plates, and stable cell lines of vector and AKR1B10 were established via lentiviral infection. Total RNA was extracted and purified from these cells using TRIzol reagent (15596018, Thermo Fisher Scientific, Shanghai, China) as recommended by the manufacturer. Oligo (dT) magnetic beads (61005, Thermo Fisher Scientific, Shanghai, China) were used to specifically isolate polyA mRNA from the samples. mRNA fragmentation occurred at elevated temperatures using a magnesium ion disruption kit (E6150S, NEB, Beijing, China), followed by cDNA synthesis using a reverse transcriptase kit (1896649, Thermo Fisher Scientific, Shanghai, China). The cDNA was subsequently converted into dsDNA through a double-stranding reaction using E. coli DNA polymerase I (m0209, NEB, Beijing, China) and RNase H (m0297, NEB, Beijing, China), during which dUTP solution (R0133, Thermo Fisher Scientific, Shanghai, China) was incorporated. End repair was then performed, and the product was subsequently purified using magnetic bead technology. A cDNA library was constructed via PCR amplification, and paired-end sequencing was carried out on the Illumina Novaseq^TM 6000 platform (LC Bio Technology Co., Ltd., Hangzhou, China) using standard operating procedures.

Data analysis and visualization were performed using the online platform https://www.omicstudio.cn/home. For the analysis of differentially expressed genes (DEGs) and associated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, datasets were screened using predefined thresholds. Gene expression levels were compared between the AKR1B10 expression group and the control vector group using the following specific screening criteria: Fold-Change (FC) $\ge$1.25, Fragments Per Kilobase of transcript per Million mapped reads (FPKM) $>$1, and p-value 0.05. In contrast, Gene Set Enrichment Analysis (GSEA) was performed without any preliminary data filtering. KEGG pathway analysis was performed to identify the biological pathways most relevant to the study. GSEA does not rely on predefined threshold values for differential gene selection and was conducted to identify significantly enriched biological pathways. Gene sets for GSEA were obtained from public databases such as the Molecular Signatures Database (MSigDB).

After discarding the culture medium, cells were incubated with complete medium containing 10 µM C11 581/591 BODIPY (D3861, Invitrogen, Shanghai, China) for 1 h, then rinsed with PBS (G4202, Servicebio, Wuhan, Hubei, China), digested with trypsin, and resuspended in 500 µL of PBS. To quantify lipid reactive oxygen species (ROS) levels, fluorescence intensity values in the FITC channel were assessed using flow cytometry (NAVIOS, Beckman Coulter, Brea, CA, USA). FlowJo v10.8.1 software (FlowJo LLC, Ashland, OR, USA) was employed for data analysis. The fluorescence intensity of the control group was used to set the gating threshold, ensuring that signals from negative cells were confined to the designated negative region. The fluorescence intensities of all groups were then compared to determine the proportion of positive cells. Data from replicate wells (FITC measurements) were combined and presented as the mean $\pm$ SD.

Following cell lysis, the total protein content was isolated using RIPA buffer (P0013B, Beyotime, Shanghai, China) containing protease inhibitor (G2008, Servicebio, Wuhan, Hubei, China) and phosphatase inhibitor (G2007, Servicebio, Wuhan, Hubei, China) to preserve protein integrity. The extracted proteins were then resolved via sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) (P0014C, Beyotime, Shanghai, China) and transferred onto a PVDF membrane (ISEQ00010, Merck, Tipperary, Ireland) using transfer buffer (E173-01, Genstar, Beijing, China). The membrane was then blocked with a 5% non-fat milk solution (232100, BD Difco, Franklin Lakes, NJ, USA) for 2 h to prevent nonspecific binding. Following this, the membrane was incubated overnight at 4 °C with the primary antibody and then washed three times for 10 minutes each before incubation with the secondary antibody. The primary antibodies used in this study were as follows: AKR1B10 (1:1000, 18252-1-AP, Proteintech, Wuhan, Hubei, China), protein kinase B (AKT, 1:5000, ab179463, Abcam, Shanghai, China), Phospho-AKT Ser473 (1:2000, 4060T, CST, Danvers, MA, USA), glycogen synthase kinase 3 beta (GSK-3β, 1:1000, 12456T, CST, Danvers, MA, USA), Phospho-GSK-3β Ser9 (1:1000, 5558T, CST, Danvers, MA, USA), erythroid 2-related factor 2 (NRF2, 1:500, 12721T, CST, Danvers, MA, USA), Kelch-like ECH-associated protein 1 (KEAP1, 1:1000, D6B12, CST, Danvers, MA, USA), and GPX4 (1:1000, 52455T, CST, Danvers, MA, USA). The secondary antibody was goat anti-rabbit IgG conjugated to horseradish peroxidase (1:10,000, 7074, CST, Danvers, MA, USA). The PVDF membrane was immersed in the secondary antibody solution and incubated at room temperature for 1 h. After three membrane washes, the protein bands were detected using an ECL substrate (BL520B, Biosharp, Tallinn, Estonia), and the protein levels were evaluated using a chemiluminescence imaging system (OI 600 MF, BIO-OI, Guangzhou, China). ImageJ 1.53t software (National Institutes of Health, Bethesda, MD, USA) was used to quantify the signal intensity.

The relative expression level of the target protein was calculated using the following formula: relative expression of target protein = (signal intensity of target protein)/(signal intensity of internal reference protein). The relative expression level of the target protein in the experimental groups was determined by normalizing to the control group, which is defined as 1.

RNA was extracted from adherent cells using the TransZol Regular RNA Extraction Kit (ET101-01-V2, TransGen, Beijing, China) as recommended by the manufacturer. Briefly, cells were lysed with guanidine isothiocyanate (G108673, Aladdin, Shanghai, China) before adding the RNA extraction reagent. The solution was then separated into a colorless aqueous phase and a pink organic phase. RNA was present in the aqueous phase and was precipitated and recovered using isopropanol. qPCR experiments were conducted using HiScript III RT SuperMix (R323, Vazyme, Nanjing, Jiangsu, China) and PerfectStart® Green qPCR SuperMix (AQ602, TransGen, Beijing, China). The extracted RNA was reverse transcribed into cDNA and then amplified with the following human-specific primers (Shenzhen Hechengyuan Biotechnology Co., Ltd.): AKR1B10, 5^′-CAGCAACAGAGAGCAGGACG-3^′ and 5^′-TGCCAAGAGGAGACTTCCAA-3^′; GPX4, 5^′-AAGATCCAACCCAAGGGCAA-3^′, and 5^′-AGACGGTGTCCAAACTTGGTG-3^′; heme oxygenase 1 (HO-1), 5^′-ACTGCGTTCCTGCTCAACAT-3^′ and 5^′-GGGGGCAGAATCTTGCACT-3^′; NAD(P)H quinone dehydrogenase 1 (NQO-1), 5^′-GCTGGTTTGAGCGAGTGTTC-3^′ and 5^′-CTGCCTTCTTACTCCGGAAGG-3^′; ferritin heavy chain 1 (FTH1), 5^′-ACTACCACCAGGACTCAGAGG-3^′ and 5^′-CAGTCATCACAGTCTGGTTTCTTG-3^′; prostaglandin-endoperoxide synthase 2 (PTGS2), 5^′-GCAAATTGCTGGCAGGGTTG-3^′ and 5^′-GCTCTGGTCAATGGAAGCCT-3^′. The Applied Biosystems 7300 Real-Time PCR System (Thermo Fisher Scientific, Foster City, CA, USA) was used to analyze gene expression.

The Ct value of the target gene was first normalized to the Ct value of an internal reference gene ($\mathrm{\Delta }$Ct). Subsequently, the difference in $\mathrm{\Delta }$Ct between the target sample and the control sample was calculated ($\mathrm{\Delta }\mathrm{\Delta }$Ct), followed by the calculation of the relative expression level of the target gene using the formula 2^{-Δ⁢Δ⁢Ct}.

Each experimental procedure was carried out in triplicate. Statistical analysis was conducted using GraphPad Prism 10.3.0 software (GraphPad Software Inc., La Jolla, CA, USA). Data are presented as the mean $\pm$ SD. Comparisons between two groups were conducted using a two-tailed Student’s t-test. Comparisons among multiple groups were performed using either one-way ANOVA or two-way ANOVA, followed by post hoc multiple comparison analyses using Tukey’s, Dunnett’s, and Sidak’s tests. A p-value ˂ 0.05 was considered statistically significant. For complex multiple comparison analysis, the Compact Letter Display (CLD) was used to replace the commonly used asterisks or p-values to present pairwise comparison results. Each experimental group was designated with at least one letter, with shared letters between groups indicating statistically insignificant differences (p $\ge$ 0.05).

Lentiviral technology was used to construct stable cell lines with either AKR1B10 overexpression or the control vector. Ectopic expression of AKR1B10 was confirmed at both the protein and mRNA levels (Fig. 1A,B). To explore how AKR1B10 influences the therapeutic efficacy of RSL3, we performed an in vitro assessment of the effect of the drug treatment. Overexpression of AKR1B10 caused a marked shift in the cell survival curve, indicating a potential protective effect (Fig. 1C). Furthermore, the ferroptosis inhibitor Fer-1 mitigated the cell death induced by RSL3 (Fig. 1D). Additionally, the C11 BODIPY 581/591 probe was used to label cells in order to assess the level of lipid peroxidation by flow cytometry. AKR1B10 overexpression was associated with a significant decrease (p 0.01) in lipid peroxidation within the cells (Fig. 1E,F), suggesting a potential protective function for AKR1B10 against ferroptosis in MDA-MB-231 cells.

Fig. 1.

Overexpression of aldo-keto reductase 1B10 (AKR1B10) protects MDA-MB-231 cells from ferroptosis. (A) Ectopic expression of the AKR1B10 protein in triple-negative breast cancer MDA-MB-231 cells was confirmed by Western blot analysis (n = 3). (B) Quantitative real-time polymerase chain reaction (qPCR) was used to verify the establishment of the control vector and AKR1B10 stably transfected cell lines (n = 4). (C) Cell viability was evaluated using the cell counting kit-8 (CCK8) assay following treatment with varying concentrations of the ferroptosis activator RSL3 (n = 6). (D) Cells were pretreated with the ferroptosis-specific inhibitor ferrostatin-1 (Fer-1) (5 µM) before co-incubation with RSL3 (5 µM) for 24 h. Cell viability was then assessed with the CCK8 assay (n = 6). (E,F) Following the same treatment as in (D) for 8 h, cells were labeled with the C11 BODIPY581/591 probe to measure lipid peroxidation levels using flow cytometry (n = 3). The overall levels of lipid reactive oxygen species (ROS) were presented as the mean $\pm$ SD of the fluorescence intensity of lipid peroxidation (FITC) (E). After setting a negative gate based on the control cells, the percentage of positive lipid ROS in each group was shown in (F). The data were analyzed by two-tailed Student’s t-test (B), one-way ANOVA corrected by Tukey’s (A,E) test, and two-way ANOVA corrected by Sidak’s (C,D) test. ns, not significant; ** p 0.01, **** p 0.0001.

We next conducted RNA-seq analysis to study the mechanism underlying the effect of RSL3 treatment in the presence of AKR1B10 overexpression. This identified a set of DEGs (Fig. 2A), as shown in the heat map in Fig. 2B. KEGG pathway analysis of these DEGs showed significant enrichment of the top 20 pathways across various biological processes, including metabolism, PI3K-AKT, RAS and other signaling pathways (Fig. 2C). Further statistical evaluation of the classical pathways indicated significant enrichment in the PI3K-AKT pathway (Fig. 2D). To investigate the potential molecular mechanisms in more detail, GSEA was performed on the complete RNA-seq gene set, as well as KEGG pathway analysis. The results revealed notable differences in ferroptosis-related pathways, including PI3K-AKT, p53, proteasome, and the cell cycle (Fig. 2E,F).

Fig. 2.

RNA sequencing revealed that the protective role of AKR1B10 in ferroptosis may be related to the phosphatidylinositol 3-kinase/protein kinase B (PI3K-AKT) signaling pathway. Gene expression changes caused by AKR1B10 overexpression were detected by RNA-seq technology. The results are presented as differentially expressed genes (DEGs) (A) and as a heatmap (B). (C) The DEGs identified in (A) underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, with the top 20 pathways showing significant enrichment. (D) Statistical analysis of the relative signaling pathways revealed that the PI3K-AKT pathway was the most significantly enriched. (E,F) KEGG pathway analysis using Gene Set Enrichment Analysis (GSEA) revealed significant differences in ferroptosis-related pathways, including PI3K-AKT, p53, the proteasome, and the cell cycle. This figure was generated using the online platform https://www.omicstudio.cn/home.

GPX4 facilitates the reduction in lipid peroxides within the complex environment of the cellular membrane. Under normal conditions, we observed that AKR1B10 overexpression resulted in elevated GPX4 (p 0.001) protein levels (Fig. 3A). To further elucidate the mechanism by which AKR1B10 modulates GPX4, we assessed the phosphorylation status of AKT protein, as suggested by involvement of the PI3K-AKT pathway in the previous RNA sequencing enrichment. AKR1B10 overexpression was found to increase the ratio of p-AKT Ser473/AKT (p 0.001) and p-GSK3$\beta$ Ser9/GSK3$\beta$ (p 0.01). The level of NRF2 protein was also elevated (p 0.05) (Fig. 3B). NRF2 is a key upstream regulator of GPX4 and is tightly controlled by regulatory factors such as GSK3$\beta$ and KEAP1. These factors influence the nuclear import of NRF2, as well as its binding to antioxidant response elements (ARE), nuclear export, and degradation in both normal and stressful environments. KEAP1 facilitates the ubiquitination and degradation of NRF2 and also serves as a crucial sensor for oxidative and electrical stress [11]. Phosphorylated AKT (Ser473) inhibits the activity of GSK3$\beta$ by phosphorylating its Ser9 residue. In the resting state, GSK3$\beta$ is unphosphorylated and active and continuously phosphorylates downstream components resulting in the constitutive degradation of NRF2. The present study found that AKR1B10 increases the phosphorylation of AKT at Ser473, thereby causing it to phosphorylate and hence inactivate GSK3$\beta$ (Fig. 3B). Inactivation of GSK3$\beta$ overcomes the suppression of NRF2 entry into the nucleus [12], thus ultimately stabilizing NRF2 expression. Western blot analysis revealed differential expression of associated proteins following treatment with varying concentrations of RSL3 for 6 h (Fig. 3C). As the drug concentration increased, RSL3 treatment triggered an oxidative stress response in cells, characterized by increased phosphorylation of AKT at Ser473 and GSK3$\beta$ at Ser9. This cascade leads to increased protein levels of NRF2 and its downstream target GPX4, especially in AKR1B10-overexpressing cells. During the induction of ferroptosis mediated by RSL3, elevated AKR1B10 expression promotes higher phosphorylation of AKT and GSK3, while also increasing activation of the NRF2 system. Notably, AKR1B10 itself was previously shown to be directly transcribed by NRF2 [13]. The current study highlights this positive feedback loop which strengthens the antioxidant defense mechanisms of tumor cells.

Fig. 3.

AKR1B10 reduces sensitivity to ferroptosis via the AKT Ser473/Glycogen Synthase Kinase 3 Beta (GSK3$\beta$) Ser9/Nuclear factor erythroid 2-related factor 2 (NRF2)/glutathione peroxidase 4 (GPX4) axis. (A) Western blot analysis of GPX4 protein levels in cells with ectopic expression of AKR1B10. (B) Western blot analysis showing the ratio of p-AKT/AKT and p-GSK3$\beta$/GSK3$\beta$, as well as the level of NRF2 protein in MDA-MB-231 cells with or without AKR1B10 overexpression. (C) Western blot showing the expression levels of related proteins following treatment of MDA-MB-231 cells (with or without AKR1B10 overexpression) with different concentrations of the ferroptosis activator RSL3 for 6 h. (D) CCK8 assay results showing cell viability after treatment of MDA-MB-231 cells (with or without AKR1B10 overexpression) with different concentrations of RSL3 for 24 h (n = 6). (E) CCK8 assay results showing cell viability after treatment of MDA-MB-231 cells (with or without AKR1B10 overexpression) with different concentrations of OSU-T315 for 24 h (n = 6). (F) CCK8 assay results showing cell viability after treatment of MDA-MB-231 cells (with or without AKR1B10 overexpression) with 2.5 µM RSL3, along with various combinations of OSU-T315 for 24 h. The ferroptosis inhibitor Fer-1 was used to rescue from cell death (n = 6). (G) Transcription profiles of relevant genes following treatment with DMSO or 5 µM RSL3 (n = 4). (H) Transcription profiles of relevant genes following treatment with DMSO or 5 µM OSU-T315 (n = 4). The data were analyzed by two-tailed Student’s t-test (A,B), one-way ANOVA corrected by Dunnett’s (G,H) test, and two-way ANOVA corrected by Tukey’s (C,F) and Sidak’s (D,E) test. Complex pairwise comparison results are presented using the Compact Letter Display (CLD) in (C) and (F). ns, not significant; * p 0.05, ** p 0.01, *** p 0.001, **** p 0.0001.

To further investigate the role of the AKT Ser473/GSK3$\beta$ Ser9 pathway in ferroptosis, MDA-MB-231 cells were treated with the specific inhibitor OSU-T315. This novel inhibitor exerts its therapeutic effect by promoting the dephosphorylation of AKT at Ser473 and of GSK3$\beta$ at Ser9. Lee et al. [14] previously reported that OSU-315 induces autophagy and apoptosis in MDA-MB-231 cells. MDA-MB-231 vector and MDA-MB-231 AKR1B10 cells were treated with varying concentrations of OSU-T315. In the 0–5 µM concentration range of OSU-T315, AKR1B10 had no significant effect on cell viability (Fig. 3E). However, the combination of RSL3 and OSU-T315 (Fig. 3F) resulted in a reduction in cell survival compared to RSL3 treatment alone (Fig. 3D). This combined effect could still be rescued by the specific ferroptosis inhibitor Fer-1 (Fig. 3F), suggesting that OSU-T315 can enhance the cell sensitivity to ferroptosis induced by RSL3. We next examined mRNA expression to assess whether this process involves the differential expression of NRF2-dependent antioxidant genes. The results of qPCR showed that RSL3 induced AKR1B10 high-expression cells to increase the transcription levels of GPX4 (p 0.01), FTH1, p 0.0001, HO-1, p 0.001, and NQO-1, p 0.0001, while decreasing that of PTGS2, p 0.0001 (Fig. 3G), thereby protecting cells from ferroptosis. Similar effects were observed in cells treated with OSU-T315 (Fig. 3H). We speculated these changes may be due to downstream NRF2-related detoxifying proteins that inhibit phosphorylation of AKT Ser473 and GSK3$\beta$ Ser9, thereby reducing the sensitivity of AKR1B10 overexpressing cells to ferroptosis.

Given the pivotal role of AKR1B10 in fatty acid metabolism, we next investigated the impact of various fatty acid environments on the therapeutic efficacy of ferroptosis in tumor cells. Previous research found that mice injected with MDA-MB-231-Luc cells with high AKR1B10 expression showed a marked increase in lung tumor burden [15]. High-fat diets are known to exacerbate cancer progression. Palmitic acid (PA), a saturated fatty acid, was previously identified as a promoter of cancer metastasis [16], while arachidonic acid (AA) is a common polyunsaturated fatty acid (PUFA), that was recently studied in relation to ferroptosis. Our earlier work showed that AKR1B10 reduces the sensitivity of MDA-MB-231 cells to RSL3-induced ferroptosis. To explore the potential of combined fatty acid and RSL3 therapy, cells were pretreated with 300 µM PA or 50 µM AA for 2 h in either complete or serum-free medium. These conditions simulate the complex fatty acid environment that tumor cells encounter during lung metastasis and in other biological contexts. The cells were then treated with RSL3 for 24 h to simulate lipid peroxide-induced stress damage. The combination of these fatty acids with RSL3 resulted in greater cytotoxicity than single-agent treatments, regardless of the presence of serum during pretreatment. Moreover, the sensitizing effect of these therapies could be rescued by Fer-1. AKR1B10 remained the determining factor for differential cell viability induced by the combined treatments (Fig. 4A–H). To assess whether the fatty acid concentrations used were cytotoxic, the cells underwent prolonged culture with either PA or AA alone. After 24 h of exposure to PA at concentrations ranging from 0 to 600 µM, the overexpression of AKR1B10 showed no significant effect on cell viability (Fig. 4I). However, after 48 h of incubation, AKR1B10 conferred protection against lipid toxicity induced by PA at a concentration of 300 µM (p 0.0001) (Fig. 4J). In contrast, the expression of AKR1B10 had no significant impact on cell viability after 24 h (Fig. 4K) and 48 h (Fig. 4L) of treatment with AA at concentrations ranging from 0 to 100 µM. After 24 h of combined treatment, the fatty acid concentrations used here did not result in a significant difference in cell viability between cell lines with or without AKR1B10 overexpression. These findings indicate that both PA and AA fatty acids can sensitize cells to ferroptosis and that AKR1B10 is a protective factor against ferroptosis.

Fig. 4.

AKR1B10 influences the efficacy of RSL3 therapy in the presence of different exogenous fatty acids. (A) MDA-MB-231 cells with or without overexpression of AKR1B10 were pre-incubated with 300 µM palmitic acid (PA) in complete culture medium for 2 h, followed by treatment with varying concentrations of RSL3 for 24 h. (B) MDA-MB-231 cells with or without high expression of AKR1B10 were pre-incubated with 300 µM PA in complete culture medium for 2 h, followed by 5 µM RSL3 for 24 h. Fer-1 was used to rescue from cell death. (C) MDA-MB-231 cells with or without high expression of AKR1B10 were pre-incubated with 300 µM PA in basal culture medium for 2 h, followed by treatment with varying concentrations of RSL3 in complete medium for 24 h; (D) MDA-MB-231 cells with or without high expression of AKR1B10 were pre-incubated with 300 µM PA in basal culture medium for 2 h, followed by 5 µM RSL3 in complete medium for 24 h. Fer-1 was used to rescue from cell death. (E–H) Using a treatment regimen analogous to that employed in (A–D) pre-incubation was carried out with 50 µM arachidonic acid (AA). Extended culture with varying concentrations of PA (I,J). Extended culture with varying concentrations of AA (K,L). In all experiments, the CCK8 assay was utilized to measure cell viability (n = 6). The data were analyzed by two-way ANOVA corrected by Sidak’s test. ns, not significant; * p 0.05, *** p 0.001, **** p 0.0001.

In summary, our results suggest that AKR1B10 can activate the NRF2-mediated antioxidant pathway via phosphorylation of the AKT/GSK3$\beta$ pathway, thereby increasing the GPX4 protein level and protecting triple-negative breast cancer MDA-MB-231 cells from ferroptosis (Fig. 5).

Fig. 5.

Ectopic expression of AKR1B10 enables cells to survive in ferroptosis. This figure was created using the website www.biorender.com.