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2000
Volume 26, Issue 4
  • ISSN: 1389-2029
  • E-ISSN: 1875-5488

Abstract

Background

Yin Yang 2 (YY2) plays a pivotal role in various tumorigenic processes; however, its specific involvement in esophageal carcinoma (ESCA) remains elusive. This study aims to investigate the expression and potential functional significance of YY2 in ESCA.

Methods

The expression and functions of YY2 in ESCA were analyzed using a broad range of bioinformatics databases and tools, including TCGA, TIMER, TISIDB, QUANTISEQ, cBioPortal, DNMIVD, LinkedOmics, DAVID, GSEA, GEPIA2, LASSO, miRWalk, miRDB, and TargetScan. Furthermore, RT-qPCR, immunohistochemical staining, western blot, CCK8 assay, and wound healing assay were employed to validate the involvement of YY2 in ESCA pathogenesis.

Results

Bioinformatics analyses revealed that the YY2 gene is upregulated in ESCA tissues, with its high expression significantly associated with poor prognosis and elevated levels of M2 macrophages, NK cells, Tregs, CTLA4, TIGIT, and Siglec-15. Validating the ESCA samples demonstrated that knockdown of YY2 effectively inhibited cell proliferation and migration in ESCA cells. The biological functions of YY2 and its co-expressed genes were primarily associated with transcriptional regulation, DNA methylation, glycometabolism, and ubiquitination. Moreover, the regulatory network of YY2 in the glycolysis pathway was found to involve multiple genes and miRNAs. Finally, a prognostic model based on YY2 and its associated glycolysis genes revealed a strong inverse correlation between higher risk scores and lower survival rates in esophageal adenocarcinoma (EAC).

Conclusion

YY2 may serve as a promising prognostic biomarker and an innovative therapeutic target for patients with ESCA, regulating cell proliferation, migration, immune microenvironment, and glycolysis.

This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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References

  1. BrayF. LaversanneM. SungH. FerlayJ. SiegelR.L. SoerjomataramI. JemalA. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J. Clin.202474322926310.3322/caac.21834 38572751
    [Google Scholar]
  2. LiY. XuJ. GuY. SunX. DongH. ChenC. The disease and economic burdens of esophageal cancer in China from 2013 to 2030: Dynamic cohort modeling study.JMIR Public Health Surveill.202283e3319110.2196/33191 34963658
    [Google Scholar]
  3. MorganE. SoerjomataramI. RumgayH. ColemanH.G. ThriftA.P. VignatJ. LaversanneM. FerlayJ. ArnoldM. The global landscape of esophageal squamous cell carcinoma and esophageal adenocarcinoma incidence and mortality in 2020 and projections to 2040: New estimates from GLOBOCAN 2020.Gastroenterology20221633649658.e210.1053/j.gastro.2022.05.054 35671803
    [Google Scholar]
  4. ArnalM.J.D. Ferrández ArenasÁ. Lanas ArbeloaÁ. Esophageal cancer: Risk factors, screening and endoscopic treatment in Western and Eastern countries.World J. Gastroenterol.201521267933794310.3748/wjg.v21.i26.7933 26185366
    [Google Scholar]
  5. UhlenhoppD.J. ThenE.O. SunkaraT. GaduputiV. Epidemiology of esophageal cancer: Update in global trends, etiology and risk factors.Clin. J. Gastroenterol.20201361010102110.1007/s12328‑020‑01237‑x 32965635
    [Google Scholar]
  6. LiL. LiY. Timothy Sembiring MelialaI. KasimV. WuS. Biological roles of Yin Yang 2: Its implications in physiological and pathological events.J. Cell. Mol. Med.20202422128861289910.1111/jcmm.15919 32969187
    [Google Scholar]
  7. LiY. LiJ. LiZ. WeiM. ZhaoH. MiyagishiM. WuS. KasimV. Homeostasis imbalance of YY2 and YY1 promotes tumor growth by manipulating ferroptosis.Adv. Sci.2022913210483610.1002/advs.202104836 35246964
    [Google Scholar]
  8. KimJ.D. FaulkC. KimJ. Retroposition and evolution of the DNA-binding motifs of YY1, YY2 and REX1.Nucleic Acids Res.200735103442345210.1093/nar/gkm235 17478514
    [Google Scholar]
  9. ChenL. ShiodaT. CoserK.R. LynchM.C. YangC. SchmidtE.V. Genome-wide analysis of YY2 versus YY1 target genes.Nucleic Acids Res.201038124011402610.1093/nar/gkq112 20215434
    [Google Scholar]
  10. WangZ. GanX. QiuC. YangD. SunX. ZengZ. Role of polypyrimidine tract-binding protein 1/yin yang 2 signaling in regulating vascular smooth muscle cell proliferation and neointima hyperplasia.Toxicol. Appl. Pharmacol.201938311474710.1016/j.taap.2019.114747 31499192
    [Google Scholar]
  11. TahmasebiS. JafarnejadS.M. TamI.S. Gonatopoulos-PournatzisT. Matta-CamachoE. TsukumoY. YanagiyaA. LiW. AtlasiY. CaronM. BraunschweigU. PearlD. KhoutorskyA. GkogkasC.G. NadonR. BourqueG. YangX.J. TianB. StunnenbergH.G. YamanakaY. BlencoweB.J. GiguèreV. SonenbergN. Control of embryonic stem cell self-renewal and differentiation via coordinated alternative splicing and translation of YY2.Proc. Natl. Acad. Sci. USA201611344123601236710.1073/pnas.1615540113 27791185
    [Google Scholar]
  12. DrewsD. KlarM. DameC. BräuerA.U. Developmental expression profile of the YY2 gene in mice.BMC Dev. Biol.200994510.1186/1471‑213X‑9‑45
    [Google Scholar]
  13. KlarM. FenskeP. VegaF.R. DameC. BräuerA.U. Transcription factor Yin-Yang 2 alters neuronal outgrowth in vitro.Cell Tissue Res.2015362245346010.1007/s00441‑015‑2268‑7 26350623
    [Google Scholar]
  14. KhachigianL.M. The Yin and Yang of YY 1 in tumor growth and suppression.Int. J. Cancer2018143346046510.1002/ijc.31255 29322514
    [Google Scholar]
  15. LiM. DuanY. WeiJ. ChenS. XueC. ZhengL. DengH. FanS. XiongW. LiG. TanM. TangF. SheK. ZhouM. Yin Yang 1 suppresses tumor invasion and metastasis in nasopharyngeal carcinoma by negatively regulating eIF4E transcriptional activity and expression.Am. J. Cancer Res.202313837633780 37693135
    [Google Scholar]
  16. WuS. KasimV. KanoM.R. TanakaS. OhbaS. MiuraY. MiyataK. LiuX. MatsuhashiA. ChungU. YangL. KataokaK. NishiyamaN. MiyagishiM. Transcription factor YY1 contributes to tumor growth by stabilizing hypoxia factor HIF-1α in a p53-independent manner.Cancer Res.20137361787179910.1158/0008‑5472.CAN‑12‑0366 23328582
    [Google Scholar]
  17. LiY. KasimV. YanX. LiL. MelialaI.T.S. HuangC. LiZ. LeiK. SongG. ZhengX. WuS. Yin Yang 1 facilitates hepatocellular carcinoma cell lipid metabolism and tumor progression by inhibiting PGC-1β-induced fatty acid oxidation.Theranostics20199257599761510.7150/thno.34931 31695789
    [Google Scholar]
  18. WangY. WuS. HuangC. LiY. ZhaoH. KasimV. Yin Yang 1 promotes the Warburg effect and tumorigenesis via glucose transporter GLUT3.Cancer Sci.201810982423243410.1111/cas.13662 29869834
    [Google Scholar]
  19. LuoC. ChenX. BaiY. XuL. WangS. YaoL. GuoX. WangD. ZhongX. Upregulation of Yin-Yang-1 associates with proliferation and glutamine metabolism in Esophageal carcinoma.Int. J. Genomics2022202212710.1155/2022/9305081 35359580
    [Google Scholar]
  20. WuX. ShiT. HeY. WangF. SangR. DingJ. ZhangW. ShuX. ShenH. YiJ. GaoX. LiuW. Methylation of transcription factor YY2 regulates its transcriptional activity and cell proliferation.Cell Discov.2017311703510.1038/celldisc.2017.35 29098080
    [Google Scholar]
  21. KasimV. XieY.D. WangH.M. HuangC. YanX.S. NianW.Q. ZhengX.D. MiyagishiM. WuS.R. Transcription factor Yin Yang 2 is a novel regulator of the p53/p21 axis.Oncotarget2017833546945470710.18632/oncotarget.18005 28903375
    [Google Scholar]
  22. WeiM. NurjanahU. LiJ. LuoX. HoseaR. LiY. ZengJ. DuanW. SongG. MiyagishiM. KasimV. WuS. YY2‐DRP1 axis regulates mitochondrial fission and determines cancer stem cell asymmetric division.Adv. Sci.20231023220734910.1002/advs.202207349 37300334
    [Google Scholar]
  23. LiJ. LuoX. WeiM. LiZ. LiY. ZhaoH. MiyagishiM. KasimV. WuS. YY2/PHGDH axis suppresses tumorigenesis by inhibiting tumor cell de novo serine biosynthesis.Biomed. Pharmacother.202316511500610.1016/j.biopha.2023.115006 37327589
    [Google Scholar]
  24. LiT. FanJ. WangB. TraughN. ChenQ. LiuJ.S. LiB. LiuX.S. TIMER: A web server for comprehensive analysis of tumor-infiltrating immune cells.Cancer Res.20177721e108e11010.1158/0008‑5472.CAN‑17‑0307 29092952
    [Google Scholar]
  25. VasaikarS.V. StraubP. WangJ. ZhangB. LinkedOmics: Analyzing multi-omics data within and across 32 cancer types.Nucleic Acids Res.201846D1D956D96310.1093/nar/gkx1090 29136207
    [Google Scholar]
  26. CeramiE. GaoJ. DogrusozU. GrossB.E. SumerS.O. AksoyB.A. JacobsenA. ByrneC.J. HeuerM.L. LarssonE. AntipinY. RevaB. GoldbergA.P. SanderC. SchultzN. The cBio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data.Cancer Discov.20122540140410.1158/2159‑8290.CD‑12‑0095 22588877
    [Google Scholar]
  27. DingW. ChenJ. FengG. ChenG. WuJ. GuoY. NiX. ShiT. DNMIVD: DNA methylation interactive visualization database.Nucleic Acids Res.202048D1D856D86210.1093/nar/gkz830 31598709
    [Google Scholar]
  28. RuB. WongC.N. TongY. ZhongJ.Y. ZhongS.S.W. WuW.C. ChuK.C. WongC.Y. LauC.Y. ChenI. ChanN.W. ZhangJ. TISIDB: An integrated repository portal for tumor–immune system interactions.Bioinformatics201935204200420210.1093/bioinformatics/btz210 30903160
    [Google Scholar]
  29. HuangD.W. ShermanB.T. LempickiR.A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.Nat. Protoc.200941445710.1038/nprot.2008.211 19131956
    [Google Scholar]
  30. TangZ. KangB. LiC. ChenT. ZhangZ. GEPIA2: An enhanced web server for large-scale expression profiling and interactive analysis.Nucleic Acids Res.201947W1W556W56010.1093/nar/gkz430 31114875
    [Google Scholar]
  31. WangH. LengerichB.J. AragamB. XingE.P. Precision Lasso: Accounting for correlations and linear dependencies in high-dimensional genomic data.Bioinformatics20193571181118710.1093/bioinformatics/bty750 30184048
    [Google Scholar]
  32. LorentM. GiralM. FoucherY. Net time‐dependent ROC curves: A solution for evaluating the accuracy of a marker to predict disease‐related mortality.Stat. Med.201433142379238910.1002/sim.6079 24399671
    [Google Scholar]
  33. HarrellF.Jr LeeK.L. MarkD.B. Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.Stat. Med.199615436138710.1002/(SICI)1097‑0258(19960229)15:4<361:AID‑SIM168>3.0.CO;2‑4 8668867
    [Google Scholar]
  34. ZhangY. BeketaevI. SeguraA.M. YuW. XiY. ChangJ. MaY. WangJ. Contribution of increased expression of Yin Yang 2 to development of cardiomyopathy.Front. Mol. Biosci.202073510.3389/fmolb.2020.00035 32195266
    [Google Scholar]
  35. KakizakiF. SonoshitaM. MiyoshiH. ItataniY. ItoS. KawadaK. SakaiY. TaketoM.M. Expression of metastasis suppressor geneAES driven by a Yin Yang (YY) element in a CpG island promoter and transcription factor YY 2.Cancer Sci.2016107111622163110.1111/cas.13063 27561171
    [Google Scholar]
  36. KaufholdS. AzizN. BonavidaB. The forgotten YY2 in reported YY1 expression levels in human cancers.Crit. Rev. Oncog.2017221-2637310.1615/CritRevOncog.2017020475 29604937
    [Google Scholar]
  37. LiuH.J. DuH. KhabibullinD. ZareiM. WeiK. FreemanG.J. KwiatkowskiD.J. HenskeE.P. mTORC1 upregulates B7-H3/CD276 to inhibit antitumor T cells and drive tumor immune evasion.Nat. Commun.2023141121410.1038/s41467‑023‑36881‑7 36869048
    [Google Scholar]
  38. RuanX. ZhengJ. LiuX. LiuY. LiuL. MaJ. HeQ. YangC. WangD. CaiH. LiZ. LiuJ. XueY. lncRNA LINC00665 stabilized by TAF15 impeded the malignant biological behaviors of glioma cells via STAU1-mediated mRNA degradation.Mol. Ther. Nucleic Acids20202082384010.1016/j.omtn.2020.05.003 32464546
    [Google Scholar]
  39. ZhangJ.J. ZhuY. XieK.L. PengY.P. TaoJ.Q. TangJ. LiZ. XuZ.K. DaiC.C. QianZ.Y. JiangK.R. WuJ.L. GaoW.T. DuQ. MiaoY. Yin Yang-1 suppresses invasion and metastasis of pancreatic ductal adenocarcinoma by downregulating MMP10 in a MUC4/ErbB2/p38/MEF2C-dependent mechanism.Mol. Cancer201413113010.1186/1476‑4598‑13‑130 24884523
    [Google Scholar]
  40. LeeM-H. LahusenT. WangR-H. XiaoC. XuX. HwangY-S. HeW-W. ShiY. DengC-X. Yin Yang 1 positively regulates BRCA1 and inhibits mammary cancer formation.Oncogene201231111612710.1038/onc.2011.217 21666725
    [Google Scholar]
  41. ShenY. ChenT.J. LacorazzaH.D. Novel tumor-suppressor function of KLF4 in pediatric T-cell acute lymphoblastic leukemia.Exp. Hematol.201753162510.1016/j.exphem.2017.04.009 28479419
    [Google Scholar]
  42. LiR. YanL. JiuJ. LiuH. LiD. LiX. ZhangJ. LiS. FanZ. LvZ. ZhuY. WangB. PSME2 offers value as a biomarker of M1 macrophage infiltration in pan-cancer and inhibits osteosarcoma malignant phenotypes.Int. J. Biol. Sci.20242041452147010.7150/ijbs.90226 38385075
    [Google Scholar]
  43. XuJ. AcharyaS. SahinO. ZhangQ. SaitoY. YaoJ. WangH. LiP. ZhangL. LoweryF.J. KuoW.L. XiaoY. EnsorJ. SahinA.A. ZhangX.H.F. HungM.C. ZhangJ.D. YuD. 14-3-3ζ turns TGF-β’s function from tumor suppressor to metastasis promoter in breast cancer by contextual changes of Smad partners from p53 to Gli2.Cancer Cell201527217719210.1016/j.ccell.2014.11.025 25670079
    [Google Scholar]
  44. KulisM. EstellerM. DNA methylation and cancer.Adv. Genet.201070275610.1016/B978‑0‑12‑380866‑0.60002‑2 20920744
    [Google Scholar]
  45. SingalR. WangS.Z. SargentT. ZhuS.Z. GinderG.D. Methylation of promoter proximal-transcribed sequences of an embryonic globin gene inhibits transcription in primary erythroid cells and promotes formation of a cell type-specific methyl cytosine binding complex.J. Biol. Chem.200227731897190510.1074/jbc.M105580200 11684679
    [Google Scholar]
  46. KlarM. DrewsD. DameC. Transcriptional activity of the novel identified human yy2 promoter is modified by DNA methylation.Gene20094301-2586310.1016/j.gene.2008.10.013 19026728
    [Google Scholar]
  47. MehlaK. SinghP.K. Metabolic regulation of macrophage polarization in cancer.Trends Cancer201951282283410.1016/j.trecan.2019.10.007 31813459
    [Google Scholar]
  48. LiC. JiangP. WeiS. XuX. WangJ. Regulatory T cells in tumor microenvironment: New mechanisms, potential therapeutic strategies and future prospects.Mol. Cancer202019111610.1186/s12943‑020‑01234‑1 32680511
    [Google Scholar]
  49. MichaudD. StewardC.R. MirlekarB. Pylayeva-GuptaY. Regulatory B cells in cancer.Immunol. Rev.20212991749210.1111/imr.12939 33368346
    [Google Scholar]
  50. ShimasakiN. JainA. CampanaD. NK cells for cancer immunotherapy.Nat. Rev. Drug Discov.202019320021810.1038/s41573‑019‑0052‑1 31907401
    [Google Scholar]
  51. HegdeP.S. KaranikasV. EversS. The where, the when, and the how of immune monitoring for cancer immunotherapies in the era of checkpoint inhibition.Clin. Cancer Res.20162281865187410.1158/1078‑0432.CCR‑15‑1507 27084740
    [Google Scholar]
  52. LeeS.H. ChoY.C. JeongH.M. KimK.H. ChoiH.J. LeeK.Y. KangB.Y. Yin-Yang 1 and Yin-Yang 2 exert opposing effects on the promoter activity of interleukin 4.Arch. Pharm. Res.201639454755410.1007/s12272‑015‑0622‑7 26345265
    [Google Scholar]
  53. KlarM. BodeJ. Enhanceosome formation over the beta interferon promoter underlies a remote-control mechanism mediated by YY1 and YY2.Mol. Cell. Biol.20052522101591017010.1128/MCB.25.22.10159‑10170.2005 16260628
    [Google Scholar]
  54. LiuZ. YuM. FeiB. FangX. MaT. WangD. miR 21 5p targets PDHA1 to regulate glycolysis and cancer progression in gastric cancer.Oncol. Rep.20184052955296310.3892/or.2018.6695 30226598
    [Google Scholar]
  55. SantosN.J. BarquilhaC.N. BarbosaI.C. Syndecan family gene and protein expression and their prognostic values for prostate cancer.Int. J. Mol. Sci.20212216866910.3390/ijms22168669
    [Google Scholar]
  56. SuX. WangX. LaiJ. MaoS. LiH. Unraveling a novel hippo-associated immunological prognostic signature: The contribution of SERPINE1 in facilitating colorectal cancer progression via the notch signaling pathway.Genomics2024116211079410.1016/j.ygeno.2024.110794 38224823
    [Google Scholar]
  57. CuiZ. SunG. BhandariR. Comprehensive analysis of glycolysis-related genes for prognosis, immune features, and candidate drug development in colon cancer.Front. Cell Dev. Biol.20219684322
    [Google Scholar]
  58. KuoY.H. ChanT.C. LaiH.Y. Overexpression of pyruvate dehydrogenase kinase-3 predicts poor prognosis in urothelial carcinoma.Front. Oncol.20211174914210.3389/fonc.2021.749142
    [Google Scholar]
  59. CuiL. ChengZ. LiuY. DaiY. PangY. JiaoY. KeX. CuiW. ZhangQ. ShiJ. FuL. Overexpression of PDK2 and PDK3 reflects poor prognosis in acute myeloid leukemia.Cancer Gene Ther.2020271-2152110.1038/s41417‑018‑0071‑9 30578412
    [Google Scholar]
  60. LiuK. ZhaoT. WangJ. ChenY. ZhangR. LanX. QueJ. Etiology, cancer stem cells and potential diagnostic biomarkers for esophageal cancer.Cancer Lett.2019458212810.1016/j.canlet.2019.05.018 31125642
    [Google Scholar]
  61. ZhangX. WangY. MengL. Comparative genomic analysis of esophageal squamous cell carcinoma and adenocarcinoma: New opportunities towards molecularly targeted therapy.Acta Pharm. Sin. B20221231054106710.1016/j.apsb.2021.09.028 35530133
    [Google Scholar]
  62. LiX. WangY. MinQ. Comparative transcriptome characterization of esophageal squamous cell carcinoma and adenocarcinoma.Comput. Struct. Biotechnol. J.2023213841385310.1016/j.csbj.2023.07.030
    [Google Scholar]
  63. BedardP.L. HymanD.M. DavidsM.S. SiuL.L. Small molecules, big impact: 20 years of targeted therapy in oncology.Lancet2020395102291078108810.1016/S0140‑6736(20)30164‑1 32222192
    [Google Scholar]
  64. HanH. JainA.D. TruicaM.I. Izquierdo-FerrerJ. AnkerJ.F. LysyB. SagarV. LuanY. ChalmersZ.R. UnnoK. MokH. VatapalliR. YooY.A. RodriguezY. KandelaI. ParkerJ.B. ChakravartiD. MishraR.K. SchiltzG.E. AbdulkadirS.A. Small-molecule MYC inhibitors suppress tumor growth and enhance immunotherapy.Cancer Cell2019365483497.e1510.1016/j.ccell.2019.10.001 31679823
    [Google Scholar]
  65. BlayV. TolaniB. HoS.P. ArkinM.R. High-throughput screening: Today’s biochemical and cell-based approaches.Drug Discov. Today202025101807182110.1016/j.drudis.2020.07.024 32801051
    [Google Scholar]
  66. WangY. JeonH. 3D cell cultures toward quantitative high-throughput drug screening.Trends Pharmacol. Sci.202243756958110.1016/j.tips.2022.03.014 35504760
    [Google Scholar]
  67. GuptaR. SrivastavaD. SahuM. TiwariS. AmbastaR.K. KumarP. Artificial intelligence to deep learning: Machine intelligence approach for drug discovery.Mol. Divers.20212531315136010.1007/s11030‑021‑10217‑3 33844136
    [Google Scholar]
  68. HeB. GuoJ. TongH.H.Y. ToW.M. Artificial intelligence in drug discovery: A bibliometric analysis and literature review.Mini Rev. Med. Chem.202424141353136710.2174/0113895575271267231123160503 38243944
    [Google Scholar]
  69. BonM. BilslandA. BowerJ. McAulayK. Fragment‐based drug discovery—the importance of high‐quality molecule libraries.Mol. Oncol.202216213761377710.1002/1878‑0261.13277 35749608
    [Google Scholar]
  70. ChilingaryanZ. YinZ. OakleyA.J. Fragment-based screening by protein crystallography: Successes and pitfalls.Int. J. Mol. Sci.20121310128571287910.3390/ijms131012857
    [Google Scholar]
  71. van MontfortR.L.M. WorkmanP. Structure-based drug design: Aiming for a perfect fit.Essays Biochem.201761543143710.1042/EBC20170052
    [Google Scholar]
  72. WangX. SongK. LiL. ChenL. Structure-based drug design strategies and challenges.Curr. Top. Med. Chem.20181812998100610.2174/1568026618666180813152921 30101712
    [Google Scholar]
  73. DixitA. BarhooshH. PaegelB.M. Translating the genome into drugs.Acc. Chem. Res.202356448949910.1021/acs.accounts.2c00791 36757774
    [Google Scholar]
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  • Article Type:
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Keyword(s): biomarker; Esophageal carcinoma; glycolysis; immune microenvironment; prognosis; YY2
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