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2000
Volume 26, Issue 17
  • ISSN: 1389-2010
  • E-ISSN: 1873-4316

Abstract

Objectives

This study aimed to comprehensively investigate the molecular landscape of gastric cancer (GC) by integrating various bioinformatics tools and experimental validations.

Methods

GSE79973 dataset, limma package, STRING, UALCAN, GEPIA, OncoDB, cBioPortal, DAVID, TISIDB, Gene Set Cancer Analysis (GSCA), tissue samples, RT-qPCR, and cell proliferation assay were employed in this study.

Results

Analysis of the GSE79973 dataset identified 300 differentially expressed genes (DEGs), from which COL1A1, COL1A2, CHN1, and FN1 emerged as pivotal hub genes using protein-protein interaction network analysis. Subsequent validation across The Cancer Genome Atlas (TCGA) datasets confirmed their up-regulation in GC tissues compared to normal controls. Promoter methylation analysis revealed decreased methylation levels of these hubs in GC tissues, suggesting their potential role in tumorigenesis. Mutational analysis using cBioPortal showcased frequent mutations in these genes, particularly FN1, further highlighting their significance in GC pathogenesis. Survival analysis indicated their correlation with reduced overall survival rates among GC patients, supported by the development of a robust prognostic model. Prediction of hub-associated miRNAs and gene enrichment analysis provided insights into their regulatory mechanisms and downstream pathways, implicating their involvement in extracellular matrix remodeling and cell migration. Drug sensitivity analysis revealed correlations between hub gene expression and drug response, while RT-qPCR validation confirmed their up-regulation in clinical GC samples. Finally, functional assays demonstrated the impact of FN1 knockdown on cellular proliferation, colony formation, and wound healing capacities.

Conclusion

Overall, this study elucidates the crucial role of COL1A1, COL1A2, CHN1, and FN1 in GC pathogenesis and underscores their potential as diagnostic markers and therapeutic targets.

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References

  1. GuanW.L. HeY. XuR.H. Gastric cancer treatment: recent progress and future perspectives.J. Hematol. Oncol.20231615710.1186/s13045‑023‑01451‑337245017
     [Google Scholar]
  2. LuJ. WangQ. ZhangH. LiuJ. RenJ. FanJ. GongJ. SuiY. ChenX. Analysis of endoscopic and pathological features of 6961 cases of gastric cancer.Sci. Rep.2024141715910.1038/s41598‑024‑58018‑638532198
     [Google Scholar]
  3. GatashehM.K. NatarajanS.R. KrishnamoorthyR. AlsulamiT.S. RajagopalP. PalanisamyC.P. VeeraraghavanV.P. JayaramanS. Molecular analysis to identify novel potential biomarkers as drug targets in colorectal cancer therapy: An integrated bioinformatics analysis.Mol. Cell. Oncol.2024111232669910.1080/23723556.2024.232669938505173
     [Google Scholar]
  4. YuqinL. ZhuY. NiyaziG. HaoranY. GaohengD. GongjianD. Trend in incidence and mortality of cancer, a high -risk area in Gansu province: Analysis of the 2010 to 2018 in Gansu Central Cancer Registry.Res. Sq202210.21203/rs.3.rs‑1600018/v1
     [Google Scholar]
  5. YangW.J. ZhaoH.P. YuY. WangJ.H. GuoL. LiuJ.Y. PuJ. LvJ. Updates on global epidemiology, risk and prognostic factors of gastric cancer.World J. Gastroenterol.202329162452246810.3748/wjg.v29.i16.245237179585
     [Google Scholar]
  6. LópezM.J. CarbajalJ. AlfaroA.L. SaraviaL.G. ZanabriaD. AraujoJ.M. QuispeL. ZevallosA. BulejeJ.L. ChoC.E. SarmientoM. PintoJ.A. FajardoW. Characteristics of gastric cancer around the world.Crit. Rev. Oncol. Hematol.202318110384110.1016/j.critrevonc.2022.10384136240980
     [Google Scholar]
  7. YangQ. XuD. YangY. LuS. WangD. WangL. Global, regional, and national burden of gastric cancer in adolescents and young adults, 1990–2019: A systematic analysis for the global burden of disease study 2019.Am. J. Gastroenterol2024119345446710.14309/ajg.0000000000002551
     [Google Scholar]
  8. Morazán-FernándezD. MoraJ. Molina-MoraJ.A. In silico pipeline to identify tumor-specific antigens for cancer immunotherapy using exome sequencing data.Phenomics20233213013710.1007/s43657‑022‑00084‑937197645
     [Google Scholar]
  9. HuangN. HeH. HeY. GuW. XuM. LiuL. Xiaotan Sanjie recipe, a compound Chinese herbal medicine, inhibits gastric cancer metastasis by regulating GnT-V-mediated E-cadherin glycosylation.J. Integr. Med.202321656157410.1016/j.joim.2023.11.00137980180
     [Google Scholar]
  10. ZhangX.L. YangY.S. XuD.P. QuJ.H. GuoM.Z. GongY. HuangJ. Comparative study on overexpression of HER2/neu and HER3 in gastric cancer.World J. Surg.200933102112211810.1007/s00268‑009‑0142‑z19636613
     [Google Scholar]
  11. HameedY. UsmanM. AhmadM. Does mouse mammary tumor-like virus cause human breast cancer? Applying Bradford Hill criteria postulates.Bull. Natl. Res. Cent.202044118310.1186/s42269‑020‑00439‑0
     [Google Scholar]
  12. AhmadM. KhanM. AsifR. SialN. AbidU. ShamimT. HameedZ. IqbalM.J. SarfrazU. SaeedH. AsgharZ. AkramM. UllahQ. YounasQ.A. RaufL. HadiA. MaryamS. HameedY. KhanM.R. TariqE. SaeedS. Expression characteristics and significant diagnostic and prognostic values of ANLN in human cancers.Int. J. Gen. Med.2022151957197210.2147/IJGM.S343975
     [Google Scholar]
  13. XuW. LiH. HameedY. Abdel-MaksoudM.A. AlmutairiS.M. MubarakA. AufyM. AlturaikiW. AlshalaniA.J. MahmoudA.M. LiC. Elucidating the clinical and immunological value of m6A regulator-mediated methylation modification patterns in adrenocortical carcinoma.Oncol. Res.202331581983110.32604/or.2023.02941437547754
     [Google Scholar]
  14. YıldırımM.E. Genetic and Epigenetic Changes of CDKN2A in Gastric Cancer.Cumhuriyet Medical Journal202446299103
     [Google Scholar]
  15. ZhaoJ. DingX. PengC. TianX. WangM. FuY. GuoH. BaiX. ZhaiX. HuangQ. Assessment of Ki-67 proliferation index in prognosis prediction in patients with nonmetastatic clear cell renal cell carcinoma and tumor thrombus.Urol. Oncol202442123.e523.e1310.1016/j.urolonc.2023.11.00138030468
     [Google Scholar]
  16. KumarS. PandeyJ. BhartiS. SenapatiS. Analysis of the Ki-67 proliferation index in relation to tumor, node, and metastasis (TNM) stage in patients with oral cavity squamous cell carcinoma.Cureus2024167e6375110.7759/cureus.6375139100007
     [Google Scholar]
  17. UsmanM. HameedY. GNB1, a novel diagnostic and prognostic potential biomarker of head and neck and liver hepatocellular carcinoma.J. Cancer Res. Ther.2023
     [Google Scholar]
  18. ZhouD. FanX. XieS. LuM. GaoL. ZhangR. ZhuM. Clinical application of serum CST4 combined with tumor markers in the diagnosis of digestive system malignant tumors.Oncol. Lett.202428238410.3892/ol.2024.1451738966578
     [Google Scholar]
  19. TutanM.B. CanalK. AslanO. Sezikliİ. YüksekM.A. TopçuR. TurhanV.B. KendirciM. Şahinerİ.T. Prognostic significance of tumor and inflammatory markers in disease-free and overall survival duration in colonic adenocarcinoma patients.Cureus2024169e6866710.7759/cureus.6866739371828
     [Google Scholar]
  20. JoshiS.S. BadgwellB.D. Current treatment and recent progress in gastric cancer.CA Cancer J. Clin.202171326427910.3322/caac.2165733592120
     [Google Scholar]
  21. ShinW.S. XieF. ChenB. YuP. YuJ. ToK.F. KangW. Updated epidemiology of gastric cancer in Asia: Decreased incidence but still a big challenge.Cancers (Basel)2023159263910.3390/cancers1509263937174105
     [Google Scholar]
  22. WangF.H. ZhangX.T. TangL. WuQ. CaiM.Y. LiY.F. QuX.J. QiuH. ZhangY.J. YingJ.E. ZhangJ. SunL.Y. LinR.B. WangC. LiuH. QiuM.Z. GuanW.L. RaoS.X. JiJ.F. XinY. ShengW.Q. XuH.M. ZhouZ.W. ZhouA.P. JinJ. YuanX.L. BiF. LiuT.S. LiangH. ZhangY.Q. LiG.X. LiangJ. LiuB.R. ShenL. LiJ. XuR.H. The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2023.Cancer Commun. (Lond.)202444112717210.1002/cac2.1251638160327
     [Google Scholar]
  23. OgunjobiT.T. Bioinformatics applications in chronic diseases: A comprehensive review of genomic, transcriptomics, proteomic, metabolomics, and machine learning approaches.Medinformatics202411810.47852/bonviewMEDIN42022335
     [Google Scholar]
  24. PanchalS. Biomarkers for disease identification.Biomarkers in Environmental and Human Health Biomonitoring.Elsevier202426929110.1016/B978‑0‑443‑13860‑7.00011‑2
     [Google Scholar]
  25. WangY. CottmanM. SchiffmanJ.D. Molecular inversion probes: A novel microarray technology and its application in cancer research.Cancer Genet.20122057-834135510.1016/j.cancergen.2012.06.00522867995
     [Google Scholar]
  26. MaY. JiangZ. PanL. ZhouY. XiaR. LiuZ. YuanL. Current development of molecular classifications of gastric cancer based on omics (Review).Int. J. Oncol.20246538910.3892/ijo.2024.567739092559
     [Google Scholar]
  27. UllahI. YangL. YinF.T. SunY. LiX.H. LiJ. WangX.J. Multi-omics approaches in colorectal cancer screening and diagnosis, recent updates and future perspectives.Cancers (Basel)20221422554510.3390/cancers1422554536428637
     [Google Scholar]
  28. LongF. LiS. XuY. LiuM. ZhangX. ZhouJ. ChenY. RongY. MengX. WangF. Dynamic gene screening enabled identification of a 10-gene panel for early detection and progression assessment of gastric cancer.Comput. Struct. Biotechnol. J.20232167768710.1016/j.csbj.2022.12.03636659923
     [Google Scholar]
  29. OrsiniA. DiquigiovanniC. BonoraE. Omics technologies improving breast cancer research and diagnostics.Int. J. Mol. Sci.202324161269010.3390/ijms24161269037628869
     [Google Scholar]
  30. MeringC. HuynenM. JaeggiD. SchmidtS. BorkP. SnelB. STRING: A database of predicted functional associations between proteins.Nucleic Acids Res.200331125826110.1093/nar/gkg03412519996
     [Google Scholar]
  31. ChandrashekarD.S. BashelB. BalasubramanyaS.A.H. CreightonC.J. Ponce-RodriguezI. ChakravarthiB.V.S.K. VaramballyS. UALCAN: A portal for facilitating tumor subgroup gene expression and survival analyses.Neoplasia201719864965810.1016/j.neo.2017.05.00228732212
     [Google Scholar]
  32. TangZ. KangB. LiC. ChenT. ZhangZ. GEPIA2: An enhanced web server for large-scale expression profiling and interactive analysis.Nucleic Acids Res.201947W1W556W56010.1093/nar/gkz43031114875
     [Google Scholar]
  33. ThulP.J. LindskogC. The human protein atlas: A spatial map of the human proteome.Protein Sci.201827123324410.1002/pro.330728940711
     [Google Scholar]
  34. TangG. ChoM. WangX. OncoDB An interactive online database for analysis of gene expression and viral infection in cancer.Nucleic Acids Res.202250D1D1334D133910.1093/nar/gkab97034718715
     [Google Scholar]
  35. 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‑12‑009522588877
     [Google Scholar]
  36. MusoroJ.Z. ZwindermanA.H. PuhanM.A. ter RietG. GeskusR.B. Validation of prediction models based on lasso regression with multiply imputed data.BMC Med. Res. Methodol.201414111610.1186/1471‑2288‑14‑11625323009
     [Google Scholar]
  37. DennisG. ShermanB.T. HosackD.A. YangJ. GaoW. LaneH.C. LempickiR.A. DAVID: Database for annotation, visualization, and integrated discovery.Genome Biol.200345310.1186/gb‑2003‑4‑5‑p312734009
     [Google Scholar]
  38. ChenY. WangX. miRDB: An online database for prediction of functional microRNA targets.Nucleic Acids Res.202048D1D127D13110.1093/nar/gkz75731504780
     [Google Scholar]
  39. LiuC.J. HuF.F. XieG.Y. MiaoY.R. LiX.W. ZengY. GuoA.Y. GSCA: An integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels.Brief. Bioinform.2023241bbac55810.1093/bib/bbac55836549921
     [Google Scholar]
  40. 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/btz21030903160
     [Google Scholar]
  41. SunW. BunnP. JinC. LittleP. ZhabotynskyV. PerouC.M. HayesD.N. ChenM. LinD.Y. The association between copy number aberration, DNA methylation and gene expression in tumor samples.Nucleic Acids Res.20184663009301810.1093/nar/gky13129529299
     [Google Scholar]
  42. WangX. DongY. ZhangH. ZhaoY. MiaoT. MohseniG. DuL. WangC. DNA methylation drives a new path in gastric cancer early detection: Current impact and prospects.Genes Dis.202411284786010.1016/j.gendis.2023.02.03837692483
     [Google Scholar]
  43. ZangY. RanX. YuanJ. WuH. WangY. LiH. TengH. SunZ. Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer.Brief. Bioinform.2024252bbae02310.1093/bib/bbae02338343327
     [Google Scholar]
  44. ClarkA.J. LillardJ.W. A comprehensive review of bioinformatics tools for genomic biomarker discovery driving precision oncology.Genes (Basel)2024158103610.3390/genes1508103639202397
     [Google Scholar]
  45. MatsuokaT. YashiroM. Bioinformatics analysis and validation of potential markers associated with prediction and prognosis of gastric cancer.Int. J. Mol. Sci.20242511588010.3390/ijms2511588038892067
     [Google Scholar]
  46. ZhengS. YangL. DaiY. JiangL. WeiY. WenH. XuY. Screening and survival analysis of hub genes in gastric cancer based on bioinformatics.J. Comput. Biol.201926111316132510.1089/cmb.2019.011931233344
     [Google Scholar]
  47. LiuX. WuJ. ZhangD. BingZ. TianJ. NiM. ZhangX. MengZ. LiuS. Identification of potential key genes associated with the pathogenesis and prognosis of gastric cancer based on integrated bioinformatics analysis.Front. Genet.2018926510.3389/fgene.2018.0026530065754
     [Google Scholar]
  48. LiC.Y. LiangG.Y. YaoW.Z. SuiJ. ShenX. ZhangY.Q. PengH. HongW.W. YeY.C. ZhangZ.Y. ZhangW.H. YinL.H. PuY.P. Identification and functional characterization of microRNAs reveal a potential role in gastric cancer progression.Clin. Transl. Oncol.201719216217210.1007/s12094‑016‑1516‑y27173517
     [Google Scholar]
  49. LiC.Y. LiangG.Y. YaoW.Z. SuiJ. ShenX. ZhangY.Q. PengH. HongW.W. YeY.C. ZhangZ.Y. ZhangW.H. YinL.H. PuY.P. Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer.Int. J. Oncol.20164851965197610.3892/ijo.2016.340726935047
     [Google Scholar]
  50. XuS. XuH. WangW. LiS. LiH. LiT. ZhangW. YuX. LiuL. The role of collagen in cancer: From bench to bedside.J. Transl. Med.201917130910.1186/s12967‑019‑2058‑131521169
     [Google Scholar]
  51. Martins CavacoA.C. DâmasoS. CasimiroS. CostaL. Collagen biology making inroads into prognosis and treatment of cancer progression and metastasis.Cancer Metastasis Rev.202039360362310.1007/s10555‑020‑09888‑532447477
     [Google Scholar]
  52. Chivu-EconomescuM. NeculaL.G. MateiL. DraguD. BleotuC. SoropA. HerleaV. DimaS. PopescuI. DiaconuC.C. Collagen family and other matrix remodeling proteins identified by bioinformatics analysis as hub genes involved in gastric cancer progression and prognosis.Int. J. Mol. Sci.2022236321410.3390/ijms2306321435328635
     [Google Scholar]
  53. NiftullayevS. Lamarche-VaneN. Regulators of Rho GTPases in the nervous system: Molecular implication in axon guidance and neurological disorders.Int. J. Mol. Sci.2019206149710.3390/ijms2006149730934641
     [Google Scholar]
  54. DongY. WuX. XuC. HameedY. Abdel-MaksoudM.A. AlmanaaT.N. KotobM.H. Al-QahtaniW.H. MahmoudA.M. ChoW.C. LiC. Prognostic model development and molecular subtypes identification in bladder urothelial cancer by oxidative stress signatures.Aging (Albany NY)20241632591261610.18632/aging.20549938305808
     [Google Scholar]
  55. PengD.H. The role of the epithelial-to-mesenchymal transition (emt) in lung cancer progression. Doctor of Philosophy.The University of Texas MD Anderson Cancer2017
     [Google Scholar]
  56. Abdel-MaksoudM.A. UllahS. NadeemA. ShaikhA. ZiaM.K. ZakriA.M. AlmanaaT.N. AlfuraydiA.A. MubarakA. HameedY. Unlocking the diagnostic, prognostic roles, and immune implications of BAX gene expression in pan-cancer analysis.Am. J. Transl. Res.2024161637410.62347/TWOY168138322551
     [Google Scholar]
  57. HameedY. Decoding the significant diagnostic and prognostic importance of maternal embryonic leucine zipper kinase in human cancers through deep integrative analyses.J. Cancer Res. Ther.20231971852186410.4103/jcrt.jcrt_1902_2138376289
     [Google Scholar]
  58. EfthymiouG. SaintA. RuffM. RekadZ. CiaisD. Van Obberghen-SchillingE. Shaping up the tumor microenvironment with cellular fibronectin.Front. Oncol.20201064110.3389/fonc.2020.0064132426283
     [Google Scholar]
  59. ShengS. GuoB. WangZ. ZhangZ. ZhouJ. HuoZ. Aberrant methylation and immune microenvironment are associated with overexpressed fibronectin 1: A diagnostic and prognostic target in head and neck squamous cell carcinoma.Front. Mol. Biosci.2021875356310.3389/fmolb.2021.75356334746236
     [Google Scholar]
  60. PaolilloM. SchinelliS. Extracellular matrix alterations in metastatic processes.Int. J. Mol. Sci.20192019494710.3390/ijms2019494731591367
     [Google Scholar]
  61. KciukM. YahyaE.B. Mohamed Ibrahim MohamedM. RashidS. IqbalM.O. KontekR. AbdulsamadM.A. AllaqA.A. Recent advances in molecular mechanisms of cancer immunotherapy.Cancers (Basel)20231510272110.3390/cancers1510272137345057
     [Google Scholar]
  62. GalboP.M. Cancer associated fibroblasts: Functional diversity across cancer types and roles in glioblastoma. Doctor of Philosophy.Albert Einstein College of Medicine2022
     [Google Scholar]
  63. VastradB. VastradC. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses.bioRxiv202010.1101/2020.12.20.423656
     [Google Scholar]
  64. ZhangL. SaharA.M. LiC. ChaudharyA. YousafI. SaeedahM.A. MubarakA. HarisM. NawazM. ReemM.A. RamadanF.A. MostafaA.A.M. FengW. HameedY. A detailed multi-omics analysis of GNB2 gene in human cancers.Braz. J. Biol.202484e26016910.1590/1519‑6984.26016935730811
     [Google Scholar]
  65. KumarS. PatelG.K. GhoshalU.C. Helicobacter pylori-induced inflammation: Possible factors modulating the risk of gastric cancer.Pathogens2021109109910.3390/pathogens1009109934578132
     [Google Scholar]
  66. AlzahraniS. LinaT.T. GonzalezJ. PinchukI.V. BeswickE.J. ReyesV.E. Effect of Helicobacter pylori on gastric epithelial cells.World J. Gastroenterol.20142036127671278010.3748/wjg.v20.i36.1276725278677
     [Google Scholar]
  67. HardbowerD.M. de SabletT. ChaturvediR. WilsonK.T. Chronic inflammation and oxidative stress.Gut Microbes20134647548110.4161/gmic.2558323811829
     [Google Scholar]
  68. SalvatoriS. MarafiniI. LaudisiF. MonteleoneG. StolfiC. Helicobacter pylori and gastric cancer: Pathogenetic mechanisms.Int. J. Mol. Sci.2023243289510.3390/ijms2403289536769214
     [Google Scholar]
  69. TorresJ. TouatiE. Mitochondrial function in health and disease: Responses to Helicobacter pylori metabolism and impact in gastric cancer development.Helicobacter pylori and Gastric Cancer. BackertS. ChamSpringer2024538110.1007/978‑3‑031‑47331‑9_3
     [Google Scholar]
  70. YanL. LiW. ChenF. WangJ. ChenJ. ChenY. YeW. Inflammation as a mediator of microbiome dysbiosis-associated DNA methylation changes in gastric premalignant lesions.Phenomics20233549650110.1007/s43657‑023‑00118‑w37881317
     [Google Scholar]
  71. BaiS. XiongX. TangB. JiT. LiX. QuX. LiW. hsa-miR-199b-3p prevents the epithelial-mesenchymal transition and dysfunction of the renal tubule by regulating E-cadherin through targeting kdm6a in diabetic nephropathy.Oxid. Med. Cell Longev., 2021202110.1155/2021/881416334257820
     [Google Scholar]
  72. TangB. LiW. JiT. LiX. QuX. BaiS. MiR-199b-3p prevent the epithelial-mesenchymal transition (EMT) and brosis of renal tubule by regulating E-cadherin through targeting KDM6A in Diabetic nephropathy (DN).Res. Sq202010.21203/rs.3.rs‑24819/v1
     [Google Scholar]
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COL1A1, COL1A2, CHN1, and FN1 Promote Tumorogenesis and Act as Markers of Diagnosis and Survival in Gastric Cancer Patients
Current Pharmaceutical Biotechnology 26, 2697 (2025); https://doi.org/10.2174/0113892010332329241119104430
/content/journals/cpb/10.2174/0113892010332329241119104430
/content/journals/cpb/10.2174/0113892010332329241119104430
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  • Article Type:     Research Article
Keyword(s): diagnosis; Gastric cancer; GSE79973; hub genes; prognosis; tumorogenesis

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