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Cancer Cell International
Published in: Cancer Cell International 1/2024

Open Access 01-12-2024 | Hepatocellular Carcinoma | Research

Comprehensive analysis of m6A modification in immune infiltration, metabolism and drug resistance in hepatocellular carcinoma

Authors: Yunxing Shi, Kai Li, Yichuan Yuan, Chenwei Wang, Zhiwen Yang, Dinglan Zuo, Yi Niu, Jiliang Qiu, Binkui Li, Yunfei Yuan, Wei He

Published in: Cancer Cell International | Issue 1/2024

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Abstract

N6-methyladenosine (m6A) is important in regulating mRNA stability, splicing, and translation, and it also contributes to tumor development. However, there is still limited understanding of the comprehensive effects of m6A modification patterns on the tumor immune microenvironment, metabolism, and drug resistance in hepatocellular carcinoma (HCC). In this study, we utilized unsupervised clustering based on the expression of 23 m6A regulators to identify m6A clusters. We identified differential m6A modification patterns and characterized m6A-gene-cluster A, which exhibited poorer survival rates, a higher abundance of Treg cells, and increased expression of TGFβ in the tumor microenvironment (TME). Additionally, m6A-gene-cluster A demonstrated higher levels of glycolysis activity, cholesterol metabolism, and fatty acid biosynthesis. We also found that the m6A score was associated with prognosis and drug resistance. Patients with a low m6A score experienced worse prognoses, which were linked to an abundance of Treg cells, upregulation of TGFβ, and increased metabolic activity. HCC patients with a higher m6A score showed improved prognosis following sorafenib treatment and immunotherapy. In conclusion, we reveals the association between m6A modification patterns and the tumor immune microenvironment, metabolism, and drug resistance in HCC. Furthermore, the m6A score holds potential as a predictive factor for the efficacy of targeted therapy and immunotherapy in HCC.
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Literature
1.
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2021;71(3):209–2490007.CrossRef
2.
3.
Kudo M, Finn RS, Qin S, Han KH, Ikeda K, Piscaglia F, Baron A, Park JW, Han G, Jassem J, et al. Lenvatinib versus Sorafenib in first-line treatment of patients with unresectable hepatocellular carcinoma: a randomised phase 3 non-inferiority trial. Lancet (London England). 2018;391(10126):1163–73.PubMedCrossRef
4.
EASL Clinical Practice Guidelines. Management of hepatocellular carcinoma. J Hepatol. 2018;69(1):182–236.CrossRef
5.
Finn RS, Qin S, Ikeda M, Galle PR, Ducreux M, Kim TY, Kudo M, Breder V, Merle P, Kaseb AO, et al. Atezolizumab plus Bevacizumab in Unresectable Hepatocellular Carcinoma. N Engl J Med. 2020;382(20):1894–905.PubMedCrossRef
6.
Casak SJ, Donoghue M, Fashoyin-Aje L, Jiang X, Rodriguez L, Shen YL, Xu Y, Jiang X, Liu J, Zhao H et al. FDA approval Summary: Atezolizumab plus Bevacizumab for the treatment of patients with advanced unresectable or metastatic hepatocellular carcinoma. Clin cancer Research: Official J Am Association Cancer Res 2020.
7.
Chen M, Wei L, Law CT, Tsang FH, Shen J, Cheng CL, Tsang LH, Ho DW, Chiu DK, Lee JM, et al. RNA N6-methyladenosine methyltransferase-like 3 promotes liver cancer progression through YTHDF2-dependent posttranscriptional silencing of SOCS2. Hepatology (Baltimore MD). 2018;67(6):2254–70.PubMedCrossRef
8.
Meyer KD, Saletore Y, Zumbo P, Elemento O, Mason CE, Jaffrey SR. Comprehensive analysis of mRNA methylation reveals enrichment in 3’ UTRs and near stop codons. Cell. 2012;149(7):1635–46.PubMedPubMedCentralCrossRef
9.
Yang Y, Hsu PJ, Chen YS, Yang YG. Dynamic transcriptomic m(6)a decoration: writers, erasers, readers and functions in RNA metabolism. Cell Res. 2018;28(6):616–24.PubMedPubMedCentralCrossRef
10.
11.
Tong J, Flavell RA, Li HB. RNA m(6)a modification and its function in diseases. Front Med. 2018;12(4):481–9.PubMedCrossRef
12.
Chen Y, Peng C, Chen J, Chen D, Yang B, He B, Hu W, Zhang Y, Liu H, Dai L, et al. WTAP facilitates progression of hepatocellular carcinoma via m6A-HuR-dependent epigenetic silencing of ETS1. Mol Cancer. 2019;18(1):127.PubMedPubMedCentralCrossRef
13.
Jin D, Guo J, Wu Y, Du J, Yang L, Wang X, Di W, Hu B, An J, Kong L, et al. M(6)a mRNA methylation initiated by METTL3 directly promotes YAP translation and increases YAP activity by regulating the MALAT1-miR-1914-3p-YAP axis to induce NSCLC drug resistance and metastasis. J Hematol Oncol. 2019;12(1):135.PubMedPubMedCentralCrossRef
14.
Shen C, Xuan B, Yan T, Ma Y, Xu P, Tian X, Zhang X, Cao Y, Ma D, Zhu X, et al. M(6)A-dependent glycolysis enhances colorectal cancer progression. Mol Cancer. 2020;19(1):72.PubMedPubMedCentralCrossRef
15.
Liu J, Eckert MA, Harada BT, Liu SM, Lu Z, Yu K, Tienda SM, Chryplewicz A, Zhu AC, Yang Y, et al. M(6)a mRNA methylation regulates AKT activity to promote the proliferation and tumorigenicity of endometrial cancer. Nat Cell Biol. 2018;20(9):1074–83.PubMedPubMedCentralCrossRef
16.
Lin S, Choe J, Du P, Triboulet R, Gregory RI. The m(6)a methyltransferase METTL3 promotes translation in Human Cancer cells. Mol Cell. 2016;62(3):335–45.PubMedPubMedCentralCrossRef
17.
Han B, Yan S, Wei S, Xiang J, Liu K, Chen Z, Bai R, Sheng J, Xu Z, Gao X. YTHDF1-mediated translation amplifies wnt-driven intestinal stemness. EMBO Rep. 2020;21(4):e49229.PubMedPubMedCentralCrossRef
18.
Wang L, Wen M, Cao X. Nuclear hnRNPA2B1 initiates and amplifies the innate immune response to DNA viruses. Science (New York, NY) 2019, 365(6454).
19.
Winkler R, Gillis E, Lasman L, Safra M, Geula S, Soyris C, Nachshon A, Tai-Schmiedel J, Friedman N, Le-Trilling VTK, et al. M(6)a modification controls the innate immune response to infection by targeting type I interferons. Nat Immunol. 2019;20(2):173–82.PubMedCrossRef
20.
Zheng Q, Hou J, Zhou Y, Li Z, Cao X. The RNA helicase DDX46 inhibits innate immunity by entrapping m(6)A-demethylated antiviral transcripts in the nucleus. Nat Immunol. 2017;18(10):1094–103.PubMedCrossRef
21.
Han D, Liu J, Chen C, Dong L, Liu Y, Chang R, Huang X, Liu Y, Wang J, Dougherty U, et al. Anti-tumour immunity controlled through mRNA m(6)a methylation and YTHDF1 in dendritic cells. Nature. 2019;566(7743):270–4.PubMedPubMedCentralCrossRef
22.
Wang H, Hu X, Huang M, Liu J, Gu Y, Ma L, Zhou Q, Cao X. Mettl3-mediated mRNA m(6)a methylation promotes dendritic cell activation. Nat Commun. 2019;10(1):1898.PubMedPubMedCentralCrossRef
23.
Li HB, Tong J, Zhu S, Batista PJ, Duffy EE, Zhao J, Bailis W, Cao G, Kroehling L, Chen Y, et al. M(6)a mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways. Nature. 2017;548(7667):338–42.PubMedPubMedCentralCrossRef
24.
Tong J, Cao G, Zhang T, Sefik E, Amezcua Vesely MC, Broughton JP, Zhu S, Li H, Li B, Chen L, et al. M(6)a mRNA methylation sustains Treg suppressive functions. Cell Res. 2018;28(2):253–6.PubMedPubMedCentralCrossRef
25.
Yang S, Wei J, Cui YH, Park G, Shah P, Deng Y, Aplin AE, Lu Z, Hwang S, He C, et al. M(6)a mRNA demethylase FTO regulates melanoma tumorigenicity and response to anti-PD-1 blockade. Nat Commun. 2019;10(1):2782.PubMedPubMedCentralCrossRef
26.
Zhang B, Wu Q, Li B, Wang D, Wang L, Zhou YL. M(6)a regulator-mediated methylation modification patterns and tumor microenvironment infiltration characterization in gastric cancer. Mol Cancer. 2020;19(1):53.PubMedPubMedCentralCrossRef
27.
Wang Y, Lu JH, Wu QN, Jin Y, Wang DS, Chen YX, Liu J, Luo XJ, Meng Q, Pu HY, et al. LncRNA LINRIS stabilizes IGF2BP2 and promotes the aerobic glycolysis in colorectal cancer. Mol Cancer. 2019;18(1):174.PubMedPubMedCentralCrossRef
28.
Wang Q, Chen C, Ding Q, Zhao Y, Wang Z, Chen J, Jiang Z, Zhang Y, Xu G, Zhang J, et al. METTL3-mediated m(6)a modification of HDGF mRNA promotes gastric cancer progression and has prognostic significance. Gut. 2020;69(7):1193–205.PubMedCrossRef
29.
Zong X, Zhao J, Wang H, Lu Z, Wang F, Du H, Wang Y. Mettl3 Deficiency sustains long-chain fatty acid absorption through suppressing Traf6-Dependent inflammation response. J Immunol (Baltimore Md: 1950). 2019;202(2):567–78.CrossRef
30.
Donoso FI, Figueroa RL, Lecannelier EA, Pino EJ, Rojas AJ. Clustering of atrial fibrillation based on surface ECG measurements. Conference proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual Conference 2013, 2013:4203–4206.
31.
Wilkerson MD, Hayes DN. ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinf (Oxford England). 2010;26(12):1572–3.
32.
Miao YR, Zhang Q, Lei Q, Luo M, Xie GY, Wang H, Guo AY. ImmuCellAI: a Unique Method for Comprehensive T-Cell subsets abundance prediction and its application in Cancer Immunotherapy. Adv Sci (Weinheim Baden-Wurttemberg Germany). 2020;7(7):1902880.
33.
Yoshihara K, Shahmoradgoli M, Martínez E, Vegesna R, Kim H, Torres-Garcia W, Treviño V, Shen H, Laird PW, Levine DA, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun. 2013;4:2612.PubMedCrossRef
34.
Rooney MS, Shukla SA, Wu CJ, Getz G, Hacohen N. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 2015;160(1–2):48–61.PubMedPubMedCentralCrossRef
35.
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102(43):15545–50.PubMedPubMedCentralCrossRef
36.
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.PubMedPubMedCentralCrossRef
37.
Wang J, Duncan D, Shi Z, Zhang B. WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013. Nucleic Acids Res. 2013;41(Web Server issue):W77–83.PubMedPubMedCentralCrossRef
38.
Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, Santos A, Doncheva NT, Roth A, Bork P, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(D1):D362–8.PubMedCrossRef
39.
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.PubMedPubMedCentralCrossRef
40.
Liberzon A, Subramanian A, Pinchback R, Thorvaldsdóttir H, Tamayo P, Mesirov JP. Molecular signatures database (MSigDB) 3.0. Bioinf (Oxford England). 2011;27(12):1739–40.
41.
Takahashi K, Tanabe K, Ohnuki M, Narita M, Ichisaka T, Tomoda K, Yamanaka S. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131(5):861–72.PubMedCrossRef
42.
Malta TM, Sokolov A, Gentles AJ, Burzykowski T, Poisson L, Weinstein JN, Kamińska B, Huelsken J, Omberg L, Gevaert O, et al. Machine learning identifies stemness features Associated with Oncogenic Dedifferentiation. Cell. 2018;173(2):338–e354315.PubMedPubMedCentralCrossRef
43.
44.
Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin cancer Research: Official J Am Association Cancer Res. 2004;10(21):7252–9.CrossRef
45.
Hazra A, Gogtay N. Biostatistics Series Module 3: comparing groups: Numerical variables. Indian J Dermatology. 2016;61(3):251–60.CrossRef
46.
47.
Lin X, Chai G, Wu Y, Li J, Chen F, Liu J, Luo G, Tauler J, Du J, Lin S, et al. RNA m(6)a methylation regulates the epithelial mesenchymal transition of cancer cells and translation of snail. Nat Commun. 2019;10(1):2065.PubMedPubMedCentralCrossRef
48.
Li B, Qiu B, Lee DS, Walton ZE, Ochocki JD, Mathew LK, Mancuso A, Gade TP, Keith B, Nissim I, et al. Fructose-1,6-bisphosphatase opposes renal carcinoma progression. Nature. 2014;513(7517):251–5.PubMedPubMedCentralCrossRef
49.
Liu LP, Ho RL, Chen GG, Lai PB. Sorafenib inhibits hypoxia-inducible factor-1α synthesis: implications for antiangiogenic activity in hepatocellular carcinoma. Clin cancer Research: Official J Am Association Cancer Res. 2012;18(20):5662–71.CrossRef
50.
Ezzoukhry Z, Louandre C, Trécherel E, Godin C, Chauffert B, Dupont S, Diouf M, Barbare JC, Mazière JC, Galmiche A. EGFR activation is a potential determinant of primary resistance of hepatocellular carcinoma cells to sorafenib. Int J Cancer. 2012;131(12):2961–9.PubMedCrossRef
51.
Tovar V, Cornella H, Moeini A, Vidal S, Hoshida Y, Sia D, Peix J, Cabellos L, Alsinet C, Torrecilla S, et al. Tumour initiating cells and IGF/FGF signalling contribute to sorafenib resistance in hepatocellular carcinoma. Gut. 2017;66(3):530–40.PubMedCrossRef
52.
Chen KF, Chen HL, Tai WT, Feng WC, Hsu CH, Chen PJ, Cheng AL. Activation of phosphatidylinositol 3-kinase/Akt signaling pathway mediates acquired resistance to sorafenib in hepatocellular carcinoma cells. J Pharmacol Exp Ther. 2011;337(1):155–61.PubMedCrossRef
53.
Ma MKF, Lau EYT, Leung DHW, Lo J, Ho NPY, Cheng LKW, Ma S, Lin CH, Copland JA, Ding J, et al. Stearoyl-CoA desaturase regulates sorafenib resistance via modulation of ER stress-induced differentiation. J Hepatol. 2017;67(5):979–90.PubMedCrossRef
54.
Mariathasan S, Turley SJ, Nickles D, Castiglioni A, Yuen K, Wang Y, Kadel EE III, Koeppen H, Astarita JL, Cubas R, et al. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature. 2018;554(7693):544–8.PubMedPubMedCentralCrossRef
55.
Barsoum IB, Smallwood CA, Siemens DR, Graham CH. A mechanism of hypoxia-mediated escape from adaptive immunity in cancer cells. Cancer Res. 2014;74(3):665–74.PubMedCrossRef
56.
Codd AS, Kanaseki T, Torigo T, Tabi Z. Cancer stem cells as targets for immunotherapy. Immunology. 2018;153(3):304–14.PubMedCrossRef
57.
Luke JJ, Bao R, Sweis RF, Spranger S, Gajewski TF. WNT/β-catenin pathway activation correlates with Immune Exclusion across Human cancers. Clin cancer Research: Official J Am Association Cancer Res. 2019;25(10):3074–83.CrossRef
58.
Li X, Wenes M, Romero P, Huang SC, Fendt SM, Ho PC. Navigating metabolic pathways to enhance antitumour immunity and immunotherapy. Nat Reviews Clin Oncol. 2019;16(7):425–41.CrossRef
59.
Pavlova NN, Thompson CB. The emerging Hallmarks of Cancer Metabolism. Cell Metabol. 2016;23(1):27–47.CrossRef
60.
Jiang Y, Sun A, Zhao Y, Ying W, Sun H, Yang X, Xing B, Sun W, Ren L, Hu B, et al. Proteomics identifies new therapeutic targets of early-stage hepatocellular carcinoma. Nature. 2019;567(7747):257–61.PubMedCrossRef
61.
62.
63.
Shulman Z, Stern-Ginossar N. The RNA modification N(6)-methyladenosine as a novel regulator of the immune system. Nat Immunol. 2020;21(5):501–12.PubMedCrossRef
64.
65.
Tauriello DVF, Palomo-Ponce S, Stork D, Berenguer-Llergo A, Badia-Ramentol J, Iglesias M, Sevillano M, Ibiza S, Cañellas A, Hernando-Momblona X, et al. TGFβ drives immune evasion in genetically reconstituted colon cancer metastasis. Nature. 2018;554(7693):538–43.PubMedCrossRef
66.
Ali K, Soond DR, Pineiro R, Hagemann T, Pearce W, Lim EL, Bouabe H, Scudamore CL, Hancox T, Maecker H, et al. Inactivation of PI(3)K p110δ breaks regulatory T-cell-mediated immune tolerance to cancer. Nature. 2014;510(7505):407–11.PubMedPubMedCentralCrossRef
67.
Spranger S, Bao R, Gajewski TF. Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature. 2015;523(7559):231–5.PubMedCrossRef
68.
Jayaprakash P, Ai M, Liu A, Budhani P, Bartkowiak T, Sheng J, Ager C, Nicholas C, Jaiswal AR, Sun Y, et al. Targeted hypoxia reduction restores T cell infiltration and sensitizes prostate cancer to immunotherapy. J Clin Investig. 2018;128(11):5137–49.PubMedPubMedCentralCrossRef
69.
van Malenstein H, Dekervel J, Verslype C, Van Cutsem E, Windmolders P, Nevens F, van Pelt J. Long-term exposure to sorafenib of liver cancer cells induces resistance with epithelial-to-mesenchymal transition, increased invasion and risk of rebound growth. Cancer Lett. 2013;329(1):74–83.PubMedCrossRef
70.
Metadata
Title
Comprehensive analysis of m6A modification in immune infiltration, metabolism and drug resistance in hepatocellular carcinoma
Authors
Yunxing Shi
Kai Li
Yichuan Yuan
Chenwei Wang
Zhiwen Yang
Dinglan Zuo
Yi Niu
Jiliang Qiu
Binkui Li
Yunfei Yuan
Wei He
Publication date
01-12-2024
Publisher
BioMed Central
Published in
Cancer Cell International / Issue 1/2024
Electronic ISSN: 1475-2867
DOI
https://doi.org/10.1186/s12935-024-03307-3

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