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2000
Volume 25, Issue 4
  • ISSN: 1566-5232
  • E-ISSN: 1875-5631

Abstract

Background

The role of HEPACAM family member 2 (HEPACAM2) is unclear in colorectal cancer (CRC).

Objective

The objective of this study was to perform an extensive examination of HEPACAM2 and validate it experimentally in CRC.

Methods

This study investigated the significance of HEPACAM2 in CRC and its potential diagnostic utility utilizing data from the Cancer Genome Atlas (TCGA) database. Additionally, the study examined potential regulatory networks involving HEPACAM2, including its associations with immune infiltration, immune checkpoint genes, tumor mutational burden (TMB), microsatellite instability (MSI), mRNA expression-based stemness index (mRNAsi), and drug sensitivity in CRC. The expression of HEPACAM2 was further validated using the GSE89076 dataset, and quantitative reverse transcription PCR (qRT-PCR) was employed to confirm HEPACAM2 expression levels in six pairs of CRC tissue samples.

Results

HEPACAM2 exhibited abnormal expression patterns in various types of cancer, including CRC. A decrease in HEPACAM2 expression levels in CRC was found to be significantly correlated with the T stage ( < 0.001). Reduced HEPACAM2 expression in CRC patients was also linked to poorer overall survival (OS) ( = 0.007). The expression levels of HEPACAM2 in CRC patients were identified as an independent prognostic factor ( = 0.016). Furthermore, HEPACAM2 was associated with TCF-dependent signaling in response to WNT, G2/M checkpoints, and other pathways. The expression of HEPACAM2 in CRC was found to be associated with immune infiltration, immune checkpoint genes, TMB / MSI, and mRNAsi. Additionally, the expression of HEPACAM2 in CRC was significantly and inversely correlated with the drug sensitivities to gw772405x and 6-phenyl-6h-indeno[1,2-c]isoquinoline-5,11-dione. qRT-PCR confirmed that the expression level of HEPACAM2 was found to be lowly expressed in CRC tissues.

Conclusion

These findings suggest that HEPACAM2 may serve as a potential prognostic biomarker and immunotherapeutic target for CRC patients.

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References

  1. AlmatroudiA. The incidence rate of colorectal cancer in Saudi Arabia: An observational descriptive epidemiological analysis.Int. J. Gen. Med.20201397799010.2147/IJGM.S27727233149661
    [Google Scholar]
  2. BrayF. FerlayJ. SoerjomataramI. SiegelR.L. TorreL.A. JemalA. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J. Clin.201868639442410.3322/caac.2149230207593
    [Google Scholar]
  3. SchreudersE.H. RucoA. RabeneckL. SchoenR.E. SungJ.J.Y. YoungG.P. KuipersE.J. Colorectal cancer screening: A global overview of existing programmes.Gut201564101637164910.1136/gutjnl‑2014‑30908626041752
    [Google Scholar]
  4. YachidaS. MizutaniS. ShiromaH. ShibaS. NakajimaT. SakamotoT. WatanabeH. MasudaK. NishimotoY. KuboM. HosodaF. RokutanH. MatsumotoM. TakamaruH. YamadaM. MatsudaT. IwasakiM. YamajiT. YachidaT. SogaT. KurokawaK. ToyodaA. OguraY. HayashiT. HatakeyamaM. NakagamaH. SaitoY. FukudaS. ShibataT. YamadaT. Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer.Nat. Med.201925696897610.1038/s41591‑019‑0458‑731171880
    [Google Scholar]
  5. JonesS. ChenW. ParmigianiG. DiehlF. BeerenwinkelN. AntalT. TraulsenA. NowakM.A. SiegelC. VelculescuV.E. KinzlerK.W. VogelsteinB. WillisJ. MarkowitzS.D. Comparative lesion sequencing provides insights into tumor evolution.Proc. Natl. Acad. Sci. USA2008105114283428810.1073/pnas.071234510518337506
    [Google Scholar]
  6. ZhaiZ. YuX. YangB. ZhangY. ZhangL. LiX. SunH. Colorectal cancer heterogeneity and targeted therapy: Clinical implications, challenges and solutions for treatment resistance.Semin. Cell Dev. Biol.20176410711510.1016/j.semcdb.2016.08.03327578007
    [Google Scholar]
  7. HuangZ HuX WeiY LaiY QiJ Pang J, Huang K, Li H, Cai P. ADAMTSL2 is a potential prognostic biomarker and immunotherapeutic target for colorectal cancer: Bioinformatic analysis and experimental verification.PloS one2024195e030390910.1371/journal.pone.0303909
    [Google Scholar]
  8. HeY. WuX. LuoC. WangL. LinJ. Functional significance of the hepaCAM gene in bladder cancer.BMC Cancer20101018310.1186/1471‑2407‑10‑8320205955
    [Google Scholar]
  9. KimS.J. KimS.Y. KimJ.H. KimD.J. Effects of smoking cessation on gene expression in human leukocytes of chronic smoker.Psychiatry Investig.201411329029610.4306/pi.2014.11.3.29025110502
    [Google Scholar]
  10. MohM.C. ZhangT. LeeL.H. ShenS. Expression of hepaCAM is downregulated in cancers and induces senescence-like growth arrest via a p53/p21-dependent pathway in human breast cancer cells.Carcinogenesis200829122298230510.1093/carcin/bgn22618845560
    [Google Scholar]
  11. YangD. LiuM. JiangJ. LuoY. WangY. ChenH. LiD. WangD. YangZ. ChenH. Comprehensive analysis of DMRT3 as a potential biomarker associated with the immune infiltration in a pan-cancer analysis and validation in lung adenocarcinoma.Cancers (Basel)20221424622010.3390/cancers1424622036551704
    [Google Scholar]
  12. DingX. WanA. QiX. JiangK. LiuZ. ChenB. ZNF695, a potential prognostic biomarker, correlates with immune infiltrates in cervical squamous cell carcinoma and endoce rvical adenocarcinoma: Bioinformatic analysis and experimental verification.Curr. Gene Ther.202424544145210.2174/011566523228521624022807124438441026
    [Google Scholar]
  13. HongJ. LinX. HuX. WuX. FangW. A five-gene signature for predicting the prognosis of colorectal cancer.Curr. Gene Ther.202121428028910.2174/156652322066620101215180333045967
    [Google Scholar]
  14. DongY. JinF. WangJ. LiQ. HuangZ. XiaL. YangM. SFXN3 is associated with poor clinical outcomes and sensitivity to the hypomethylating therapy in non-M3 acute myeloid leukemia patients.Curr. Gene Ther.202323541041810.2174/156652322366623072412151537491851
    [Google Scholar]
  15. HanQ. CuiZ. WangQ. PangF. LiD. WangD. Upregulation of OTX2-AS1 is associated with immune infiltration and predicts prognosis of gastric cancer.Technol. Cancer Res. Treat.20232210.1177/1533033823115409136740995
    [Google Scholar]
  16. LiangW. LuY. PanX. ZengY. ZhengW. LiY. NieY. LiD. WangD. Decreased expression of a novel lncRNA FAM181A-AS1 is associated with poor prognosis and immune infiltration in lung adenocarcinoma.Pharm. Genomics Pers. Med.20221598599810.2147/PGPM.S38490136482943
    [Google Scholar]
  17. WangJ. DaiW. ZhangM. GATA3 positively regulates PAR1 to facilitate in vitro disease progression and decrease cisplatin sensitivity in neuroblastoma via inhibiting the hippo pathway.Anticancer Drugs2023341577210.1097/CAD.000000000000134135946556
    [Google Scholar]
  18. PanH. LiuQ. ZhangF. WangX. WangS. ShiX. High STK40 expression as an independent prognostic biomarker and correlated with immune infiltrates in low-grade gliomas.Int. J. Gen. Med.2021146389640010.2147/IJGM.S33582134675607
    [Google Scholar]
  19. XueJ. SongY. XuW. ZhuY. The CDK1-related lncRNA and CXCL8 mediated immune resistance in lung adenocarcinoma.Cells20221117268810.3390/cells1117268836078096
    [Google Scholar]
  20. LinZ. HuangW. YiY. LiD. XieZ. LiZ. YeM. LncRNA ADAMTS9-AS2 is a prognostic biomarker and correlated with immune infiltrates in lung adenocarcinoma.Int. J. Gen. Med.2021148541855510.2147/IJGM.S34068334849000
    [Google Scholar]
  21. YiW. ShenH. SunD. XuY. FengY. LiD. WangC. Low expression of long noncoding RNA SLC26A4 antisense RNA 1 is an independent prognostic biomarker and correlate of immune infiltrates in breast cancer.Med. Sci. Monit.202228e93452210.12659/MSM.93452234880202
    [Google Scholar]
  22. ChenJ. TangH. LiT. JiangK. ZhongH. WuY. HeJ. LiD. LiM. CaiX. Comprehensive analysis of the expression, prognosis, and biological significance of OVOLs in breast cancer.Int. J. Gen. Med.2021143951396010.2147/IJGM.S32640234345183
    [Google Scholar]
  23. LiuJ. LichtenbergT. HoadleyK.A. An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics.Cell20181732400416.e1110.1016/j.cell.2018.02.05229625055
    [Google Scholar]
  24. LoveM.I. HuberW. AndersS. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.Genome Biol.2014151255010.1186/s13059‑014‑0550‑825516281
    [Google Scholar]
  25. YuG. WangL.G. HanY. HeQ.Y. ClusterProfiler: An R package for comparing biological themes among gene clusters.OMICS201216528428710.1089/omi.2011.011822455463
    [Google Scholar]
  26. SubramanianA. TamayoP. MoothaV.K. MukherjeeS. EbertB.L. GilletteM.A. PaulovichA. PomeroyS.L. GolubT.R. LanderE.S. MesirovJ.P. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles.Proc. Natl. Acad. Sci. USA200510243155451555010.1073/pnas.050658010216199517
    [Google Scholar]
  27. ChenT. ZhuC. WangX. PanY. LncRNA ELF3-AS1 is a prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma.Can. J. Gastroenterol. Hepatol.2021202111210.1155/2021/832348734336727
    [Google Scholar]
  28. HänzelmannS. CasteloR. GuinneyJ. GSVA: Gene set variation analysis for microarray and RNA-Seq data.BMC Bioinformatics2013141710.1186/1471‑2105‑14‑723323831
    [Google Scholar]
  29. BindeaG. MlecnikB. TosoliniM. KirilovskyA. WaldnerM. ObenaufA.C. AngellH. FredriksenT. LafontaineL. BergerA. BrunevalP. FridmanW.H. BeckerC. PagèsF. SpeicherM.R. TrajanoskiZ. GalonJ. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer.Immunity201339478279510.1016/j.immuni.2013.10.00324138885
    [Google Scholar]
  30. CaiH. ChenS. WuZ. WangF. TangS. LiD. WangD. GuoW. Comprehensive analysis of ZNF692 as a potential biomarker associated with immune infiltration in a pan cancer analysis and validation in hepatocellular carcinoma.Aging (Albany NY)20231522130411305810.18632/aging.20521837980166
    [Google Scholar]
  31. ChalmersZ.R. ConnellyC.F. FabrizioD. GayL. AliS.M. EnnisR. SchrockA. CampbellB. ShlienA. ChmieleckiJ. HuangF. HeY. SunJ. TaboriU. KennedyM. LieberD.S. RoelsS. WhiteJ. OttoG.A. RossJ.S. GarrawayL. MillerV.A. StephensP.J. FramptonG.M. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden.Genome Med.2017913410.1186/s13073‑017‑0424‑228420421
    [Google Scholar]
  32. JardimD.L. GoodmanA. de Melo GagliatoD. KurzrockR. The challenges of tumor mutational burden as an immunotherapy biomarker.Cancer Cell202139215417310.1016/j.ccell.2020.10.00133125859
    [Google Scholar]
  33. YamamotoH. WatanabeY. MaehataT. ImaiK. ItohF. Microsatellite instability in cancer: A novel landscape for diagnostic and therapeutic approach.Arch. Toxicol.202094103349335710.1007/s00204‑020‑02833‑z32632538
    [Google Scholar]
  34. BonnevilleR. KrookM.A. KauttoE.A. MiyaJ. WingM.R. ChenH.Z. ReeserJ.W. YuL. RoychowdhuryS. Landscape of microsatellite instability across 39 cancer types.JCO Precis. Oncol.20172017111510.1200/PO.17.0007329850653
    [Google Scholar]
  35. ZhongF. LiuJ. GaoC. ChenT. LiB. Downstream regulatory network of MYBL2 mediating its oncogenic role in melanoma.Front. Oncol.20221281607010.3389/fonc.2022.81607035664780
    [Google Scholar]
  36. ChenB. DingX. WanA. QiX. LinX. WangH. MuW. WangG. ZhengJ. Comprehensive analysis of TLX2 in pan cancer as a prognostic and immunologic biomarker and validation in ovarian cancer.Sci. Rep.20231311624410.1038/s41598‑023‑42171‑537758722
    [Google Scholar]
  37. LuX. LiG. LiuS. WangH. ZhangZ. ChenB. Bioinformatics analysis of KIF1A expression and gene regulation network in ovarian carcinoma.Int. J. Gen. Med.2021143707371710.2147/IJGM.S32359134321916
    [Google Scholar]
  38. CuiG. CaiF. DingZ. GaoL. MMP14 predicts a poor prognosis in patients with colorectal cancer.Hum. Pathol.201983364210.1016/j.humpath.2018.03.03030120968
    [Google Scholar]
  39. RaoX. WangJ. SongH.M. DengB. LiJ.G. KRT15 overexpression predicts poor prognosis in colorectal cancer.Neoplasma202067241041410.4149/neo_2019_190531N47531884802
    [Google Scholar]
  40. SunX. FengZ. WangY. QuY. GaiY. Expression of Foxp3 and its prognostic significance in colorectal cancer.Int. J. Immunopathol. Pharmacol.201730220120610.1177/039463201771041528560891
    [Google Scholar]
  41. ZhuY.F. DongM. Expression of TUSC3 and its prognostic significance in colorectal cancer.Pathol. Res. Pract.201821491497150310.1016/j.prp.2018.07.00430115537
    [Google Scholar]
  42. JeongD. HeoS. Sung AhnT. LeeS. ParkS. KimH. ParkD. Byung BaeS. LeeS.S. Soo LeeM. KimC.J. Jun BaekM. Cyr61 expression is associated with prognosis in patients with colorectal cancer.BMC Cancer201414116410.1186/1471‑2407‑14‑16424606730
    [Google Scholar]
  43. ZhangG.L. PanL.L. HuangT. WangJ.H. The transcriptome difference between colorectal tumor and normal tissues revealed by single-cell sequencing.J. Cancer201910235883589010.7150/jca.3226731737124
    [Google Scholar]
  44. WuZ. LiuZ. GeW. ShouJ. YouL. PanH. HanW. Analysis of potential genes and pathways associated with the colorectal normal mucosa–adenoma–carcinoma sequence.Cancer Med.2018762555256610.1002/cam4.148429659199
    [Google Scholar]
  45. LvG. WangQ. LinL. YeQ. LiX. ZhouQ. KongX. DengH. YouF. ChenH. WuS. YuanL. mTORC2-driven chromatin cGAS mediates chemoresistance through epigenetic reprogramming in colorectal cancer.Nat. Cell Biol.202426915851596Epub ahead of print10.1038/s41556‑024‑01473‑039080411
    [Google Scholar]
  46. MengL. Chromatin-modifying enzymes as modulators of nuclear size during lineage differentiation.Cell Death Discov.20239138410.1038/s41420‑023‑01639‑z37863956
    [Google Scholar]
  47. HuangW. HicksonL.J. EirinA. KirklandJ.L. LermanL.O. Cellular senescence: The good, the bad and the unknown.Nat. Rev. Nephrol.2022181061162710.1038/s41581‑022‑00601‑z35922662
    [Google Scholar]
  48. ZhaoP. SunL. ZhaoC. TCF1/LEF1 triggers Wnt-dependent chemokine/cytokine-induced inflammation and cadherin pathways to drive T-ALL cell migration.Biochem. Biophys. Rep.20233410145710.1016/j.bbrep.2023.10145736942321
    [Google Scholar]
  49. ChelbiH. JelassiR. BelfkihS. Ben AmorA. SaidiN. Ben SalahH. MzoughiN. Ben DhifallahI. BoujelbenN. AmmiR. BouratbineA. ZidiI. AounK. Association of CCR5Δ32 deletion and human cytomegalovirus infection with colorectal cancer in Tunisia.Front. Genet.20211259863510.3389/fgene.2021.59863534976001
    [Google Scholar]
  50. MurphyE. YuD. GrimwoodJ. SchmutzJ. DicksonM. JarvisM.A. HahnG. NelsonJ.A. MyersR.M. ShenkT.E. Coding potential of laboratory and clinical strains of human cytomegalovirus.Proc. Natl. Acad. Sci. USA200310025149761498110.1073/pnas.213665210014657367
    [Google Scholar]
  51. KishoreC. Epigenetic regulation and promising therapies in colorectal cancer.Curr. Mol. Pharmacol.202114583885210.2174/187446721466621012610534533573584
    [Google Scholar]
  52. ParkC.K. KimH.S. Clinicopathological characteristics of ovarian metastasis from colorectal and pancreatobiliary carcinomas mimicking primary ovarian mucinous tumor.Anticancer Res.20183895465547310.21873/anticanres.1287930194204
    [Google Scholar]
  53. GongX. TianX. XieH. LiZ. The structural maintenance of chromosomes 5 is a possible biomarker for individualized treatment of colorectal cancer.Cancer Med.20231233276328710.1002/cam4.507435894836
    [Google Scholar]
  54. PicardE. VerschoorC.P. MaG.W. PawelecG. Relationships between immune landscapes, genetic subtypes and responses to immunotherapy in colorectal cancer.Front. Immunol.20201136910.3389/fimmu.2020.0036932210966
    [Google Scholar]
  55. FarkonaS. DiamandisE.P. BlasutigI.M. Cancer immunotherapy: The beginning of the end of cancer?BMC Med.20161417310.1186/s12916‑016‑0623‑527151159
    [Google Scholar]
  56. BerryJ. VreelandT. TrappeyA. HaleD. PeaceK. TylerJ. WalkerA. BrownR. HerbertG. YiF. JacksonD. CliftonG. PeoplesG.E. Cancer vaccines in colon and rectal cancer over the last decade: Lessons learned and future directions.Expert Rev. Clin. Immunol.201713323524510.1080/1744666X.2016.122613227552944
    [Google Scholar]
  57. MunroM.J. WickremesekeraS.K. PengL. TanS.T. ItinteangT. Cancer stem cells in colorectal cancer: A review.J. Clin. Pathol.201871211011610.1136/jclinpath‑2017‑20473928942428
    [Google Scholar]
  58. WangL. LiuW. LiuJ. WangY. TaiJ. YinX. TanJ. Identification of immune-related therapeutically relevant biomarkers in breast cancer and breast cancer stem cells by transcriptome-wide analysis: A clinical prospective study.Front. Oncol.20211055413810.3389/fonc.2020.55413833718103
    [Google Scholar]
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  • Article Type:
    Research Article
Keyword(s): Colorectal cancer; drug sensitivity; HEPACAM2; immune infiltration; pathway; prognosis
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