Enhancing ferroptosis and inhibiting ABCB1 make the novel aldose reductase inhibitor 5F-E a promising sensitizer in liver cancer

Abstract

Multidrug resistance (MDR) poses a critical barrier to chemotherapy efficacy. While the promising agents, aldose reductase inhibitors (ARIs), to overcome multidrug resistance (MDR) has been investigated over recent decades, their underlying mechanisms remain unclear and clinically viable candidates are still lacking. In our study, we identified a novel ARI, 5F-E, which exhibited a more potent sensitizing effect on doxorubicin (DOX) resistant HepG2 cells (HepG2/ADR) compared to epalrestat (EPA). Both 5F-E and EPA were observed to decrease intracellular GSH levels while elevating reactive oxygen species (ROS), Fe²⁺ and lipid peroxidation; these effects could be reversed by N-acetyl cysteine (NAC), suggesting that enhanced ferroptosis may be involved in restoring DOX sensitivity. Furthermore, inhibition of AKR1B1 by either compound led to marked reductions in p-STAT3 and SLC7A11 expression, an outcome that was recapitulated by AKR1B1 gene knockdown. The results demonstrate that ARIs exert antitumor effects on HepG2/ADR cells by triggering ferroptosis, a process dependent on AKR1B1/STAT3/SLC7A11 signaling. And, 5F-E, but not EPA, was found to increase intracellular DOX accumulation by inhibiting ABCB1. Our integrated experimental approach reveals that 5F-E exhibits strong chemosensitizing effects against multidrug-resistant liver cancer, highlighting its therapeutic promise.

Keywords

Inhibitor of aldose reductase / Chemoresistance / Ferroptotic cell death / AKR1B1-STAT3-SLC7A11 signaling axis / ABCB1 transporter

CRediT authorship contribution statement

Ziyou Zheng: Writing - original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation. Zhenqiang Chen: Writing - original draft, Visualization, Software, Methodology, Formal analysis, Data curation. Chao Zhang: Visualization, Validation, Formal analysis, Data curation. Shuling Peng: Visualization, Validation, Data curation. Jianling Hu: Validation, Formal analysis, Data curation. Chanxi Wang: Validation, Formal analysis, Data curation. Lujie Liu: Validation, Formal analysis, Data curation. Mao-xun Yang: Validation, Project administration, Funding acquisition. Heru Chen: Writing - review & editing, Writing - original draft, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization.

Ethics approval

All experimental protocols and animal procedures were ratified by the Laboratory Animal Ethics Committee of Jinan University (approval number 20230216-0016) and carried out on the basis of the guiding principles summarized in the National Institutes of Health's 7th Edition Guide for the Care and Use of Laboratory Animals (USA).

Declaration of generative AI in scientific writing

Not applicable.

Funding information

This research was financially supported by Guangdong Basic and Applied Basic Research Foundation, China (Nos. 2020A1515010857 and 2021A1515011238), the Dongguan Science and Technology Commissioner Project (20231800500332), the Undergraduate Teaching Quality and Teaching Reform Project Construction Project of Guangdong Province (1JG23080), the Graduate Education Innovation Program of Guangdong Province, China (4SG24170G).

Data availability

All data generated or analyzed during this study are included in this published article.

Declaration of interest statement

All the authors including Ziyou Zheng, Zhenqiang Chen, Chao Zhang, Shuling Peng, Jianling Hu, Chanxi Wang, Lujie Liu, Mao-xun Yang, and Heru Chen, hereby declare that there is no interest conflict in this publication.

Acknowledgements

We thank Dr. Zhang Zhang from the College of Pharmacy, Jinan University, China, for offering us resistant cancer cell lines. Prof. Yaolan Li was acknowledged for useful discussion in cancer resistance. We would like to thank all software including Adobe Illustrator, ChemDraw, Origin, which are used to create figures.

References

[1] C. Holohan, et al., Cancer drug resistance: an evolving paradigm, Nat. Rev. Cancer 13 (10) (2013) 714-726, https://doi.org/10.1038/nrc3599.

[2] K. Bukowski, et al., Mechanisms of multidrug resistance in cancer chemotherapy, Int. J. Mol. Sci. 21 (9) (2020) 3233, https://doi.org/10.3390/ijms21093233.

[3] M.M. Gottesman, Mechanisms of cancer drug resistance, Annu. Rev. Med. 53 (1) (2002) 615-627, https://doi.org/10.1146/annurev.med.53.082901.103929.

[4] Z. Chen, et al., Non-small cell lung cancers: a heterogeneous set of diseases, Nat. Rev. Cancer 14 (8) (2014) 535-546, https://doi.org/10.1038/nrc3775.

[5] B. Laffin, J.M. Petrash, Expression of the aldo-keto reductases AKR1B1 and AKR1B10 in human cancers, Front. Pharmacol. 3 (2012) 104, https://doi.org/10.3389/fphar201200104.

[6] C. Bailly, Moving toward a new horizon for the aldose reductase inhibitor epalrestat to treat drug-resistant cancer, Eur. J. Pharmacol. 931 (2022) 175191, https://doi.org/10.1016/j.ejphar.2022.175191.

[7] O.A. Barski, et al., The aldo-keto reductase superfamily and its role in drug metabolism and detoxification, Drug Metab. Rev. 40 (4) (2008) 553-624, https://doi.org/10.1080/03602530802431439.

[8] P.A. Kumar, G.B. Reddy, Focus on molecules: aldose reductase, Exp. Eye Res. 85 (6) (2007) 739-740, https://doi.org/10.1016/j.exer.2006.08.002.

[9] B. Faubert, et al., Metabolic reprogramming and cancer progression, Science 368 (6487) (2020) eaaw5473, https://doi.org/10.1126/science.aaw5473.

[10] N. Geng, et al., AKR1B10 inhibitor epalrestat facilitates sorafenib-induced apoptosis and autophagy via targeting the mTOR pathway in hepatocellular carcinoma, Int. J. Med. Sci. 17 (10) (2020) 1246, https://doi.org/10.7150/ijms.42956.

[11] J. Han, et al., Rapid emergence and mechanisms of resistance by U87 glioblastoma cells to doxorubicin in an in vitro tumor microfluidic ecology, Proc. Natl. Acad. Sci. USA 113 (50) (2016) 14283-14288, https://doi.org/10.1073/pnas.1614898113.

[12] T. Matsunaga, et al., Involvement of the aldo-keto reductase, AKR1B10, in Mitomycin-C resistance through reactive oxygen species-dependent mechanisms, Anti Cancer Drugs 22 (5) (2011) 402-408, https://doi.org/10.1097/CAD.0b013e3283448df0.

[13] M. Kikuya, et al., Aldo-keto reductase inhibitors increase the anticancer effects of tyrosine kinase inhibitors in chronic myelogenous leukemia, J. Pharmacol. Sci. 147 (1) (2021) 1-8, https://doi.org/10.1016/j.jphs.2021.05.001.

[14] C. Zhang, et al., Ferroptosis in cancer therapy: a novel approach to reversing drug resistance, Mol. Cancer 21 (1) (2022) 47, https://doi.org/10.1186/s12943-022-01530-y.

[15] M.J. Hangauer, et al., Drug-tolerant persister cancer cells are vulnerable to GPX4 inhibition, Nature 551 (7679) (2017) 247-250, https://doi.org/10.1038/nature24297.

[16] W.S. Yang, et al., Regulation of ferroptotic cancer cell death by GPX4, Cell 156 (1-2) (2014) 317-331, https://doi.org/10.1016/j.cell.2013.12.010.

[17] M.R. Liu, et al., System Xc-: a key regulatory target of ferroptosis in cancer, Invest. N. Drugs 39 (4) (2021) 1123-1131, https://doi.org/10.1007/s10637-021-010700.

[18] F. Ursini, M. Maiorino, Lipid peroxidation and ferroptosis: the role of GSH and GPx4, Free Radical Biol. Med. 152 (2020) 175-185, https://doi.org/10.1016/j.freeradbiomed2020.02027.

[19] J.L. Parker, et al., Molecular basis for redox control by the human cystine/ glutamate antiporter system Xc-, Nat. Commun. 12 (1) (2021) 7147, https://doi.org/10.1038/s41467-021-27414-1.

[20] W. Lin, et al., SLC7A11/xCT in cancer: biological functions and therapeutic implications, Am. J. Cancer Res. 10 (10) (2020) 3106. PMCID: PMC7642655.

[21] C. Carvalho, et al., Doxorubicin: the good, the bad and the ugly effect, Curr. Med. Chem. 16 (25) (2009) 3267-3285, https://doi.org/10.2174/092986709788803312.

[22] J. Zhang, et al., Heparanase-driven sequential released nanoparticles for ferroptosis and tumor microenvironment modulations synergism in breast cancer therapy, Biomaterials 266 (2021) 120429, https://doi.org/10.1016/jbiomaterials.2020120429.

[23] F. Xu, et al., Differential drug resistance acquisition to doxorubicin and paclitaxel in breast cancer cells, Cancer Cell Int. 14 (1) (2014) 1-13, https://doi.org/10.1186/s12935-014-0142-4.

[24] N.P. Syamprasad, et al., AKR1B1 inhibition using NARI-29-an epalrestat analogalleviates doxorubicin-induced cardiotoxicity via modulating Calcium/CaMKII/ MuRF-1 axis, Chem. Biol. Interact. 381 (2023) 110566, https://doi.org/10.1016/jcbi2023110566.

[25] H. Sonowal, et al., Aldose reductase inhibitor increases doxorubicin-sensitivity of Colon cancer cells and decreases cardiotoxicity, Sci. Rep. 7 (1) (2017) 3182, https://doi.org/10.1038/s41598-017-03284-w.

[26] K. Tomczak, et al., The cancer genome atlas (TCGA): an immeasurable source of knowledge, Contemp. Oncol. 19 (5) (2015) A68-A77, https://doi.org/10.105114/wo.201447136.

[27] M. Love, et al., Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2, Genome Biol. 15 (12) (2014) 550, https://doi.org/10.1186/s13059-014-0550-8.

[28] R. Gaujoux, C. Seoighe, A flexible R package for nonnegative matrix factorization, BMC Bioinf. 11 (1) (2010) 367, https://doi.org/10.1186/1471-2105-11-367.

[29] B.L. Fridley, et al., Self-contained gene-set analysis of expression data: an evaluation of existing and novel methods, PLoS One 5 (11) (2010) e12693, https://doi.org/10.1371/journalpone0012693.

[30] D. Maeser, et al., oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data, Briefings Bioinf. 22 (6) (2021) bbab260, https://doi.org/10.1093/bib/bbab260.

[31] G.C. Yu, et al., clusterProfiler: an R package for comparing biological themes among gene clusters, OMICS A J. Integr. Biol. 16 (5) (2012) 284-287, https://doi.org/10.1089/omi20110118.

[32] Y. Zeng, Z. Zheng, M. Yin, et al., Of the 5F-like ARIs in a dual-occupied mode, Bioorg. Chem. 131 (2023) 106300, https://doi.org/10.1016/j.bioorg.2022.106300.

[33] T.C. Chou, Drug combination studies and their synergy quantification using the chou-talalay method, Cancer Res. 70 (2010) 440-446, https://doi.org/10.1158/0008-5472CAN-09-1947.

[34] B. Chen, P. Fan, X. Song, M. Duan, The role and possible mechanism of the ferroptosis-related SLC7A11/GSH/GPX4 pathway in myocardial ischemiareperfusion injury, BMC Cardiovasc. Disord. 24 (2024) 531, https://doi.org/10.1186/s12872-024-04220-3.

[35] Y. Wang, et al., Digoxin enhances the anticancer effect on non-small cell lung cancer while reducing the cardiotoxicity of adriamycin, Front. Pharmacol. 11 (2020) 186, https://doi.org/10.3389/fphar.2020.00186.

[36] L. Zhang, et al., Overexpression of SLC7A11: a novel oncogene and an indicator of unfavorable prognosis for liver carcinoma, Future Oncol. 14 (10) (2018) 927-936, https://doi.org/10.2217/fon-2017-0540.

[37] D.S. Chandrashekar, et al., UALCAN: a portal for facilitating tumor subgroup gene expression and survival analyses, Neoplasia 19 (8) (2017) 649-658, https://doi.org/10.1016/j.neo201705002.

[38] K.R. Zhang, et al., Targeting AKR1B1 Inhibits Glutathione De Novo Synthesis to Overcome Acquired Resistance to EGFR-Targeted Therapy in Lung Cancer, Sci. Transl. Med. 13 (606) (2021) eabg6428, https://doi.org/10.1126/scitranslmed.abg6428.

[39] K.W.Y. Lee, et al., Overexpression of aldose reductase in liver cancers may contribute to drug resistance, Anti Cancer Drugs 12 (2) (2001) 129-132, https://doi.org/10.1097/00001813-200102000-00005.

[40] D. Maru, A. Hothi, C. Bagariya, Targeting ferroptosis pathways: a novel strategy for cancer therapy, Curr. Cancer Drug Targets 22 (2022) 234-244, https://doi.org/10.2174/1568009622666220211122745.

[41] K.T. Skinner, et al., Genetics of ABCB1 in cancer, Cancers 15 (17) (2023) 4236, https://doi.org/10.3390/cancers15174236.

[42] E. Fox, S.E. Bates, Tariquidar (XR9576): a P-Glycoprotein drug efflux pump inhibitor, Expet Rev. Anticancer Ther. 7 (4) (2007) 447-459, https://doi.org/10.1586/14737140.7.4.447.

[43] M. Konantz, et al., Zebrafish xenografts as a tool for in vivo studies on human cancer, Ann. N. Y. Acad. Sci. 1266 (1) (2012) 124-137, https://doi.org/10.1111/j1749-6632201206575.x.

[44] Y. Liu, et al., HERC 2 promotes inflammation-driven cancer stemness and immune evasion in hepatocellular carcinoma by activating STAT3 pathway, J. Exp. Clin. Cancer Res. 42 (1) (2023) 1-20, https://doi.org/10.1186/s13046-023-02609-0.

[45] V. Poli, A. Camporeale, STAT3-Mediated metabolic reprograming in cellular transformation and implications for drug resistance, Front. Oncol. 5 (2015) 121, https://doi.org/10.3389/fonc.2015.00121.

[46] H. Lee, et al., Highlighted STAT3 as a potential drug target for cancer therapy, BMP Reports 52 (7) (2019) 415-423, https://doi.org/10.5483/BMBRep.2019.52.7.152.

[47] J. Lewerenz, et al., The cystine/glutamate antiporter system Xc- in health and disease: from molecular mechanisms to novel therapeutic opportunities, Antioxidants Redox Signal. 18 (5) (2013) 522-555, https://doi.org/10.1089/ars.2011.4391.

[48] P. Koppula, et al., Cystine transporter SLC7A11/xCT in cancer: ferroptosis, nutrient dependency, and cancer therapy, Protein Cell 12 (8) (2021) 599-620, https://doi.org/10.1007/s13238-020-00789-5.

[49] L. Liu, et al., The N6-Methyladenosine modification enhances ferroptosis resistance through inhibiting SLC7A 11 mRNA deadenylation in hepatoblastoma, Clin. Transl. Med. 12 (7) (2022) e778, https://doi.org/10.1002/ctm2.778.

[50] Y. Zhang, et al., BAP 1 suppresses tumor development by inducing ferroptosis upon SLC7A11 repression, Mol. & Cell. Oncol. 6 (6) (2019) e1536845, https://doi.org/10.1080/2372355620181536845.

[51] J.P.F. Angeli, et al., Ferroptosis at the crossroads of cancer-acquired drug resistance and immune evasion, Nat. Rev. Cancer 19 (7) (2019) 405-414, https://doi.org/10.1038/s41568-019-0149-1.

[52] J. Li, et al., Ferroptosis: past, present and future, Cell Death Dis. 11 (2) (2020) 88, https://doi.org/10.1038/s41419-020-2298-2.

[53] A. Vaidyanathan, et al., ABCB1 (MDR1) induction defines a common resistance mechanism in paclitaxel-And olaparib-resistant ovarian cancer cells, BJC (Br. J. Cancer) 115 (4) (2016) 431-441, https://doi.org/10.1038/bjc.2016.203.

[54] K. Engle, G. Kumar, Cancer multidrug-resistance reversal by ABCB1 inhibition: a recent update, Eur. J. Med. Chem. 239 (2022) 114542, https://doi.org/10.1016/jejmech2022114542.

[55] L.D. Cripe, et al., Zosuquidar, a novel modulator of P-Glycoprotein, does not improve the outcome of older patients with newly diagnosed acute myeloid leukemia: a randomized, placebo-controlled trial of the eastern cooperative oncology group 3999, Blood 116 (20) (2010) 4077-4085, https://doi.org/10.1182/blood-2010-04-277269.

[56] J. Abraham, et al., A phase I study of the P-Glycoprotein antagonist tariquidar in combination with vinorelbine, Clin. Cancer Res. 15 (10) (2009) 3574-3582, https://doi.org/10.1158/1078-0432.CCR-08-0938.

[57] A. Sandler, et al., A phase I trial of a potent P-Glycoprotein inhibitor, zosuquidar trihydrochloride (LY335979), administered intravenously in combination with doxorubicin in patients with advanced malignancy, Clin. Cancer Res. 10 (10) (2004) 3265-3272, https://doi.org/10.1158/1078-0432.CCR-03-0644.