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RBM45 reprograms lipid metabolism promoting hepatocellular carcinoma via Rictor and ACSL1/ACSL4

Oncogene volume 43, pages 328–340 (2024)Cite this article

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Abstract

Reprogramming of lipid metabolism during hepatocarcinogenesis is not well elucidated. Here, we aimed to explore pivotal RNA-binding motif proteins (RBMs) in lipid metabolism and their therapeutic potential in hepatocellular carcinoma (HCC). Through bioinformatic analysis, we identified RBM45 as a critical gene of interest among differentially expressed RBMs in HCC, with significant prognostic relevance. RBM45 influenced the malignant biological phenotype and lipid metabolism of HCC cells. Mechanically, RBM45 promotes de novo lipogenesis in HCC by directly targeting two key enzymes involved in long-chain fatty acid synthesis, ACSL1 and ACSL4. RBM45 also targets Rictor, which has been demonstrated to modulate lipid metabolism profoundly. RBM45 also aided lipid degradation through activating a key fatty acid β oxidation enzyme, CPT1A. Thus, RBM45 boosted lipid synthesis and decomposition, indicating an enhanced utility of lipid fuels in HCC. Clinically, body mass index was positively correlated with RBM45 in human HCCs. The combination of a PI3K/AKT/mTOR pathway inhibitor in vitro or Sorafenib in orthotopic liver cancer mouse models with shRBM45 has a more significant therapeutic effect on liver cancer than the drug alone. In summary, our findings highlight the versatile roles of RBM45 in lipid metabolism reprogramming and its therapeutic potential in HCC.

Lipids induced RBM45 expression. In turn, RBM45 promoted the utility of lipid in HCCs through accelerating both de novo lipogenesis and fatty acid β oxidation, which required the participation of Rictor, a core component of mTORC2 that has been demonstrated to modulate lipid metabolism potently, as well as ACSL1/ACSL4, two key enzymes of long-chain fatty acid synthesis. When the first-line chemotherapy drug sorafenib is combined with a PI3K/AKT/mTOR pathway inhibitor (MK2206 is an AKT inhibitor, rapamycin is a mTOR inhibitor, and inhibiting RBM45 can significantly inhibit Rictor), cell cycle, proliferation, lipid metabolism reprogramming, and hepatocarcinogenesis can be significantly inhibited, while apoptosis can be significantly enhanced.

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Fig. 1: Identification of RBM45 as a gene of interest in TCGA-LIHC cohort.
Fig. 2: Clinical significance and upregulation of RBM45 in HCCs.
Fig. 3: Activation of the PI3K-AKT-mTOR pathway by the oncogene RBM45, primarily dependent on Rictor.
Fig. 4: Induction of RBM45 by lipids and subsequent promotion of lipid storage.
Fig. 5: RBM45 accelerates fatty acid flow via PI3K/AKT/mTOR and de novo lipogenesis pathways.
Fig. 6: Enhanced anticancer effects by combining RBM45 silencing with MK-2206 or Rapamycin.
Fig. 7: Therapeutic potential of Rbm45 knockdown combined with sorafenib in AKT/N-Ras induced mouse liver cancer.

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Data availability

Source data, computer code, and reagents are available from Ying Chang upon reasonable request.

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49. https://doi.org/10.3322/caac.21660

    Article  PubMed  Google Scholar 

  2. Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73:17–48. https://doi.org/10.3322/caac.21763

    Article  PubMed  Google Scholar 

  3. Tang W, Chen Z, Zhang W, Cheng Y, Zhang B, Wu F, et al. The mechanisms of sorafenib resistance in hepatocellular carcinoma: theoretical basis and therapeutic aspects. Signal Transduct Target Ther. 2020;5:87. https://doi.org/10.1038/s41392-020-0187-x

    Article  PubMed  PubMed Central  Google Scholar 

  4. Berndt N, Eckstein J, Heucke N, Gajowski R, Stockmann M, Meierhofer D, et al. Characterization of lipid and lipid droplet metabolism in human HCC. Cells. 2019;8. https://doi.org/10.3390/cells8050512.

  5. Bidkhori G, Benfeitas R, Klevstig M, Zhang C, Nielsen J, Uhlen M, et al. Metabolic network-based stratification of hepatocellular carcinoma reveals three distinct tumor subtypes. Proc Natl Acad Sci USA. 2018;115:E11874–e11883. https://doi.org/10.1073/pnas.1807305115

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Currie E, Schulze A, Zechner R, Walther TC, Farese RV Jr. Cellular fatty acid metabolism and cancer. Cell Metab. 2013;18:153–61. https://doi.org/10.1016/j.cmet.2013.05.017

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Calvisi DF, Wang C, Ho C, Ladu S, Lee SA, Mattu S, et al. Increased lipogenesis, induced by AKT-mTORC1-RPS6 signaling, promotes development of human hepatocellular carcinoma. Gastroenterology. 2011;140:1071–83. https://doi.org/10.1053/j.gastro.2010.12.006

    Article  PubMed  CAS  Google Scholar 

  8. Menendez JA, Lupu R. Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis. Nat Rev Cancer. 2007;7:763–77. https://doi.org/10.1038/nrc2222

    Article  PubMed  CAS  Google Scholar 

  9. Peck B, Schug ZT, Zhang Q, Dankworth B, Jones DT, Smethurst E, et al. Inhibition of fatty acid desaturation is detrimental to cancer cell survival in metabolically compromised environments. Cancer Metab. 2016;4:6 https://doi.org/10.1186/s40170-016-0146-8

    Article  PubMed  PubMed Central  Google Scholar 

  10. Sounni NE, Cimino J, Blacher S, Primac I, Truong A, Mazzucchelli G, et al. Blocking lipid synthesis overcomes tumor regrowth and metastasis after antiangiogenic therapy withdrawal. Cell Metab. 2014;20:280–94. https://doi.org/10.1016/j.cmet.2014.05.022

    Article  PubMed  CAS  Google Scholar 

  11. Koundouros N, Poulogiannis G. Reprogramming of fatty acid metabolism in cancer. Br J Cancer. 2020;122:4–22. https://doi.org/10.1038/s41416-019-0650-z

    Article  PubMed  CAS  Google Scholar 

  12. Bacci M, Lorito N, Smiriglia A, Morandi A. Fat and furious: lipid metabolism in antitumoral therapy response and resistance. Trends Cancer. 2021;7:198–213. https://doi.org/10.1016/j.trecan.2020.10.004

    Article  PubMed  CAS  Google Scholar 

  13. Del Río-Moreno M, Alors-Pérez E, González-Rubio S, Ferrín G, Reyes O, Rodríguez-Perálvarez M, et al. Dysregulation of the splicing machinery is associated to the development of nonalcoholic fatty liver disease. J Clin Endocrinol Metab. 2019;104:3389–402. https://doi.org/10.1210/jc.2019-00021

    Article  PubMed  PubMed Central  Google Scholar 

  14. Choi SH, Flamand MN, Liu B, Zhu H, Hu M, Wang M, et al. RBM45 is an m(6)A-binding protein that affects neuronal differentiation and the splicing of a subset of mRNAs. Cell Rep. 2022;40:111293. https://doi.org/10.1016/j.celrep.2022.111293

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Du D, Qin M, Shi L, Liu C, Jiang J, Liao Z, et al. RNA binding motif protein 45-mediated phosphorylation enhances protein stability of ASCT2 to promote hepatocellular carcinoma progression. Oncogene. https://doi.org/10.1038/s41388-023-02795-3 (2023).

  16. Mashiko T, Sakashita E, Kasashima K, Tominaga K, Kuroiwa K, Nozaki Y, et al. Developmentally regulated RNA-binding Protein 1 (Drb1)/RNA-binding Motif Protein 45 (RBM45), a nuclear-cytoplasmic trafficking protein, forms TAR DNA-binding Protein 43 (TDP-43)-mediated cytoplasmic aggregates. J Biol Chem. 2016;291:14996–5007. https://doi.org/10.1074/jbc.M115.712232

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Gebauer F, Schwarzl T, Valcarcel J, Hentze MW. RNA-binding proteins in human genetic disease. Nat Rev Genet. 2021;22:185–98. https://doi.org/10.1038/s41576-020-00302-y

    Article  PubMed  CAS  Google Scholar 

  18. Blackinton JG, Keene JD. Post-transcriptional RNA regulons affecting cell cycle and proliferation. Semin Cell Dev Biol. 2014;34:44–54. https://doi.org/10.1016/j.semcdb.2014.05.014

    Article  PubMed  CAS  Google Scholar 

  19. Singh AK, Aryal B, Zhang X, Fan Y, Price NL, Suárez Y, et al. Posttranscriptional regulation of lipid metabolism by non-coding RNAs and RNA binding proteins. Semin Cell Dev Biol. 2018;81:129–40. https://doi.org/10.1016/j.semcdb.2017.11.026

    Article  PubMed  CAS  Google Scholar 

  20. Sutherland LC, Rintala-Maki ND, White RD, Morin CD. RNA binding motif (RBM) proteins: a novel family of apoptosis modulators? J Cell Biochem. 2005;94:5–24. https://doi.org/10.1002/jcb.20204

    Article  PubMed  CAS  Google Scholar 

  21. Li Z, Guo Q, Zhang J, Fu Z, Wang Y, Wang T, et al. The RNA-binding motif protein family in cancer: friend or foe? Front Oncol. 2021;11:757135. https://doi.org/10.3389/fonc.2021.757135

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Glisovic T, Bachorik JL, Yong J, Dreyfuss G. RNA-binding proteins and post-transcriptional gene regulation. FEBS Lett. 2008;582:1977–86. https://doi.org/10.1016/j.febslet.2008.03.004

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Li Y, Collins M, An J, Geiser R, Tegeler T, Tsantilas K, et al. Immunoprecipitation and mass spectrometry defines an extensive RBM45 protein-protein interaction network. Brain Res. 2016;1647:79–93. https://doi.org/10.1016/j.brainres.2016.02.047

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Caron A, Richard D, Laplante M. The Roles of mTOR complexes in lipid metabolism. Annu Rev Nutr. 2015;35:321–48. https://doi.org/10.1146/annurev-nutr-071714-034355

    Article  PubMed  CAS  Google Scholar 

  25. Liu GY, Sabatini DM. mTOR at the nexus of nutrition, growth, ageing and disease. Nat Rev Mol Cell Biol. 2020;21:183–203. https://doi.org/10.1038/s41580-019-0199-y

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Grabinski N, Ewald F, Hofmann BT, Staufer K, Schumacher U, Nashan B, et al. Combined targeting of AKT and mTOR synergistically inhibits proliferation of hepatocellular carcinoma cells. Mol Cancer. 2012;11:85. https://doi.org/10.1186/1476-4598-11-85

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. O’Reilly KE, Rojo F, She QB, Solit D, Mills GB, Smith D, et al. mTOR inhibition induces upstream receptor tyrosine kinase signaling and activates Akt. Cancer Res. 2006;66:1500–8. https://doi.org/10.1158/0008-5472.Can-05-2925

    Article  PubMed  PubMed Central  Google Scholar 

  28. Copp J, Manning G, Hunter T. TORC-specific phosphorylation of mammalian target of rapamycin (mTOR): phospho-Ser2481 is a marker for intact mTOR signaling complex 2. Cancer Res. 2009;69:1821–7. https://doi.org/10.1158/0008-5472.CAN-08-3014

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Tang Y, Zhou J, Hooi SC, Jiang YM, Lu GD. Fatty acid activation in carcinogenesis and cancer development: Essential roles of long-chain acyl-CoA synthetases. Oncol Lett. 2018;16:1390–6. https://doi.org/10.3892/ol.2018.8843

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Leamy AK, Egnatchik RA, Young JD. Molecular mechanisms and the role of saturated fatty acids in the progression of non-alcoholic fatty liver disease. Prog Lipid Res. 2013;52:165–74. https://doi.org/10.1016/j.plipres.2012.10.004

    Article  PubMed  CAS  Google Scholar 

  31. Li LO, Ellis JM, Paich HA, Wang S, Gong N, Altshuller G, et al. Liver-specific loss of long chain acyl-CoA synthetase-1 decreases triacylglycerol synthesis and beta-oxidation and alters phospholipid fatty acid composition. J Biol Chem. 2009;284:27816–26. https://doi.org/10.1074/jbc.M109.022467

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Yan S, Yang XF, Liu HL, Fu N, Ouyang Y, Qing K. Long-chain acyl-CoA synthetase in fatty acid metabolism involved in liver and other diseases: an update. World J Gastroenterol. 2015;21:3492–8. https://doi.org/10.3748/wjg.v21.i12.3492

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Friedmann Angeli JP, Krysko DV, Conrad M. Ferroptosis at the crossroads of cancer-acquired drug resistance and immune evasion. Nat Rev Cancer. 2019;19:405–14. https://doi.org/10.1038/s41568-019-0149-1

    Article  PubMed  CAS  Google Scholar 

  34. Stockwell BR, Friedmann Angeli JP, Bayir H, Bush AI, Conrad M, Dixon SJ, et al. Ferroptosis: a regulated cell death nexus linking metabolism, redox biology, and disease. Cell. 2017;171:273–85. https://doi.org/10.1016/j.cell.2017.09.021

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Doll S, Proneth B, Tyurina YY, Panzilius E, Kobayashi S, Ingold I, et al. ACSL4 dictates ferroptosis sensitivity by shaping cellular lipid composition. Nat Chem Biol. 2017;13:91–98. https://doi.org/10.1038/nchembio.2239

    Article  PubMed  CAS  Google Scholar 

  36. Beatty A, Singh T, Tyurina YY, Tyurin VA, Samovich S, Nicolas E, et al. Ferroptotic cell death triggered by conjugated linolenic acids is mediated by ACSL1. Nat Commun. 2021;12:2244. https://doi.org/10.1038/s41467-021-22471-y

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Chen J, Li X, Ge C, Min J, Wang F. The multifaceted role of ferroptosis in liver disease. Cell Death Differ. 2022;29:467–80. https://doi.org/10.1038/s41418-022-00941-0

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Xu Z, Xu M, Liu P, Zhang S, Shang R, Qiao Y, et al. The mTORC2-Akt1 cascade is Crucial for c-Myc to promote hepatocarcinogenesis in mice and humans. Hepatology. 2019;70:1600–13. https://doi.org/10.1002/hep.30697

    Article  PubMed  CAS  Google Scholar 

  39. Yu L, Wei J, Liu P. Attacking the PI3K/Akt/mTOR signaling pathway for targeted therapeutic treatment in human cancer. Semin Cancer Biol. 2022;85:69–94. https://doi.org/10.1016/j.semcancer.2021.06.019

    Article  PubMed  CAS  Google Scholar 

  40. Zhang Y, Kwok-Shing Ng P, Kucherlapati M, Chen F, Liu Y, Tsang YH, et al. A pan-cancer proteogenomic atlas of PI3K/AKT/mTOR pathway alterations. Cancer Cell. 2017;31:820–832.e823. https://doi.org/10.1016/j.ccell.2017.04.013

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Yuan M, Pino E, Wu L, Kacergis M, Soukas AA. Identification of Akt-independent regulation of hepatic lipogenesis by mammalian target of rapamycin (mTOR) complex 2. J Biol Chem. 2012;287:29579–88. https://doi.org/10.1074/jbc.M112.386854

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Chen Y, Qian J, He Q, Zhao H, Toral-Barza L, Shi C, et al. mTOR complex-2 stimulates acetyl-CoA and de novo lipogenesis through ATP citrate lyase in HER2/PIK3CA-hyperactive breast cancer. Oncotarget. 2016;7:25224–40. https://doi.org/10.18632/oncotarget.8279

    Article  PubMed  PubMed Central  Google Scholar 

  43. Hagiwara A, Cornu M, Cybulski N, Polak P, Betz C, Trapani F, et al. Hepatic mTORC2 activates glycolysis and lipogenesis through Akt, glucokinase, and SREBP1c. Cell Metab. 2012;15:725–38. https://doi.org/10.1016/j.cmet.2012.03.015

    Article  PubMed  CAS  Google Scholar 

  44. Umemura A, Park EJ, Taniguchi K, Lee JH, Shalapour S, Valasek MA, et al. Liver damage, inflammation, and enhanced tumorigenesis after persistent mTORC1 inhibition. Cell Metab. 2014;20:133–44. https://doi.org/10.1016/j.cmet.2014.05.001

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Lu X, Paliogiannis P, Calvisi DF, Chen X. Role of the mammalian target of rapamycin pathway in liver cancer: from molecular genetics to targeted therapies. Hepatology. 2021;73:49–61. https://doi.org/10.1002/hep.31310

    Article  PubMed  CAS  Google Scholar 

  46. Manzari MT, Shamay Y, Kiguchi H, Rosen N, Scaltriti M, Heller DA. Targeted drug delivery strategies for precision medicines. Nat Rev Mater. 2021;6:351–70. https://doi.org/10.1038/s41578-020-00269-6

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Llovet JM, Ricci S, Mazzaferro V, Hilgard P, Gane E, Blanc JF, et al. Sorafenib in advanced hepatocellular carcinoma. N Engl J Med. 2008;359:378–90. https://doi.org/10.1056/NEJMoa0708857

    Article  PubMed  CAS  Google Scholar 

  48. Cheng Z, Wei-Qi J, Jin D. New insights on sorafenib resistance in liver cancer with correlation of individualized therapy. Biochim Biophys Acta Rev Cancer. 2020;1874:188382. https://doi.org/10.1016/j.bbcan.2020.188382

    Article  PubMed  CAS  Google Scholar 

  49. Finn RS, Qin S, Ikeda M, Galle PR, Ducreux M, Kim TY, et al. Atezolizumab plus Bevacizumab in Unresectable Hepatocellular Carcinoma. N Engl J Med. 2020;382:1894–905. https://doi.org/10.1056/NEJMoa1915745

    Article  PubMed  CAS  Google Scholar 

  50. Jiménez-Valerio G, Casanovas O. Angiogenesis and metabolism: entwined for therapy resistance. Trends Cancer. 2017;3:10–18. https://doi.org/10.1016/j.trecan.2016.11.007

    Article  PubMed  CAS  Google Scholar 

  51. Hoy AJ, Nagarajan SR, Butler LM. Tumour fatty acid metabolism in the context of therapy resistance and obesity. Nat Rev Cancer. 2021;21:753–66. https://doi.org/10.1038/s41568-021-00388-4

    Article  PubMed  CAS  Google Scholar 

  52. Yin F, Feng F, Wang L, Wang X, Li Z, Cao Y. SREBP-1 inhibitor Betulin enhances the antitumor effect of Sorafenib on hepatocellular carcinoma via restricting cellular glycolytic activity. Cell Death Dis. 2019;10:672. https://doi.org/10.1038/s41419-019-1884-7

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018;15:11–20. https://doi.org/10.1038/nrgastro.2017.109

    Article  PubMed  Google Scholar 

  54. Orci LA, Sanduzzi-Zamparelli M, Caballol B, Sapena V, Colucci N, Torres F, et al. Incidence of hepatocellular carcinoma in patients with nonalcoholic fatty liver disease: a systematic review, meta-analysis, and meta-regression. Clin Gastroenterol Hepatol. 2022;20:283–292.e210. https://doi.org/10.1016/j.cgh.2021.05.002

    Article  PubMed  Google Scholar 

  55. Barr J, Caballería J, Martínez-Arranz I, Domínguez-Díez A, Alonso C, Muntané J, et al. Obesity-dependent metabolic signatures associated with nonalcoholic fatty liver disease progression. J Proteome Res. 2012;11:2521–32. https://doi.org/10.1021/pr201223p

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Kimura I, Ichimura A, Ohue-Kitano R, Igarashi M. Free fatty acid receptors in health and disease. Physiol Rev. 2020;100:171–210. https://doi.org/10.1152/physrev.00041.2018

    Article  PubMed  CAS  Google Scholar 

  57. Lingwood D, Simons K. Lipid rafts as a membrane-organizing principle. Science. 2010;327:46–50. https://doi.org/10.1126/science.1174621

    Article  PubMed  CAS  Google Scholar 

  58. Ringel AE, Drijvers JM, Baker GJ, Catozzi A, García-Cañaveras JC, Gassaway BM, et al. Obesity shapes metabolism in the tumor microenvironment to suppress anti-tumor immunity. Cell. 2020;183:1848–1866.e1826. https://doi.org/10.1016/j.cell.2020.11.009

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Wang C, Cigliano A, Jiang L, Li X, Fan B, Pilo MG, et al. 4EBP1/eIF4E and p70S6K/RPS6 axes play critical and distinct roles in hepatocarcinogenesis driven by AKT and N-Ras proto-oncogenes in mice. Hepatology. 2015;61:200–13. https://doi.org/10.1002/hep.27396

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

This work was supported by research grants from the National Natural Science Foundation of China (Nos. 82172983(YC), 81870390 (QZ), 81670554 (YC), 82073095 (XH)), Wuhan Science and Technology Plan (No. 2020020601012208 (YC)), science and technology innovation and cultivation fund in Zhongnan Hospital of Wuhan University (No. CXPY2020042 (YC)), subjects and platform construction in Zhongnan Hospital of Wuhan University (No. PTMX2020003 (YC)), and the Fundamental Research Funds for the Central Universities (No. 2042023kf0086 (FX). In addition, we appreciate the assistance of Professor Chuanrui Xu of the School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology in the construction of the plasmid.

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  1. These authors contributed equally: Chun Wang, Zhihang Chen, Yun Yi.

Authors and Affiliations

  1. Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China

    Chun Wang, Yun Yi, Yang Ding, Fei Xu, Hui Kang, Kun Lin, Xiawen Shu, Jing Liu, Zhong Xu, Lan Liu, Xingxing He, Ying Chang & Qiu Zhao

  2. Hubei Clinical Center & Key Lab of Intestinal & Colorectal Diseases, Wuhan, 430071, China

    Chun Wang, Yun Yi, Yang Ding, Fei Xu, Hui Kang, Kun Lin, Xiawen Shu, Jing Liu, Zhong Xu, Lan Liu, Xingxing He, Ying Chang & Qiu Zhao

  3. Department of Respiratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China

    Zhihang Chen

  4. Transplant Center of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China

    Zibiao Zhong

  5. Department of Hepatobiliary & Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China

    Zhonglin Zhang

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Contributions

CW: design experiment, data collection, formal analysis, drafting and editing the manuscript. ZC: bioinformatic analysis and drafting the manuscript. YY: drafting and revise the manuscript. YD, FX, HK, XS, KL, ZZ, ZZ, JL, LL and ZX: assist in the experimen. XXH, YC and QZ: experimental guidance, revise the manuscript and financial support. All authors read and approved the final manuscript.

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Correspondence to Xingxing He, Ying Chang or Qiu Zhao.

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Wang, C., Chen, Z., Yi, Y. et al. RBM45 reprograms lipid metabolism promoting hepatocellular carcinoma via Rictor and ACSL1/ACSL4. Oncogene 43, 328–340 (2024). https://doi.org/10.1038/s41388-023-02902-4

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