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image of Comprehensive Analysis and Experimental Validation of HEPACAM2 as a Potential Prognosis Biomarker and Immunotherapy Target in Colorectal Cancer

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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2024-11-01
2025-06-18
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References

  1. Almatroudi A. The incidence rate of colorectal cancer in Saudi Arabia: An observational descriptive epidemiological analysis. Int. J. Gen. Med. 2020 13 977 990 10.2147/IJGM.S277272 33149661
    [Google Scholar]
  2. Bray F. Ferlay J. Soerjomataram I. Siegel R.L. Torre L.A. Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018 68 6 394 424 10.3322/caac.21492 30207593
    [Google Scholar]
  3. Schreuders E.H. Ruco A. Rabeneck L. Schoen R.E. Sung J.J.Y. Young G.P. Kuipers E.J. Colorectal cancer screening: A global overview of existing programmes. Gut 2015 64 10 1637 1649 10.1136/gutjnl‑2014‑309086 26041752
    [Google Scholar]
  4. Yachida S. Mizutani S. Shiroma H. Shiba S. Nakajima T. Sakamoto T. Watanabe H. Masuda K. Nishimoto Y. Kubo M. Hosoda F. Rokutan H. Matsumoto M. Takamaru H. Yamada M. Matsuda T. Iwasaki M. Yamaji T. Yachida T. Soga T. Kurokawa K. Toyoda A. Ogura Y. Hayashi T. Hatakeyama M. Nakagama H. Saito Y. Fukuda S. Shibata T. Yamada T. Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer. Nat. Med. 2019 25 6 968 976 10.1038/s41591‑019‑0458‑7 31171880
    [Google Scholar]
  5. Jones S. Chen W. Parmigiani G. Diehl F. Beerenwinkel N. Antal T. Traulsen A. Nowak M.A. Siegel C. Velculescu V.E. Kinzler K.W. Vogelstein B. Willis J. Markowitz S.D. Comparative lesion sequencing provides insights into tumor evolution. Proc. Natl. Acad. Sci. USA 2008 105 11 4283 4288 10.1073/pnas.0712345105 18337506
    [Google Scholar]
  6. Zhai Z. Yu X. Yang B. Zhang Y. Zhang L. Li X. Sun H. Colorectal cancer heterogeneity and targeted therapy: Clinical implications, challenges and solutions for treatment resistance. Semin. Cell Dev. Biol. 2017 64 107 115 10.1016/j.semcdb.2016.08.033 27578007
    [Google Scholar]
  7. He Y. Wu X. Luo C. Wang L. Lin J. Functional significance of the hepaCAM gene in bladder cancer. BMC Cancer 2010 10 1 83 10.1186/1471‑2407‑10‑83 20205955
    [Google Scholar]
  8. Kim S.J. Kim S.Y. Kim J.H. Kim D.J. Effects of smoking cessation on gene expression in human leukocytes of chronic smoker. Psychiatry Investig. 2014 11 3 290 296 10.4306/pi.2014.11.3.290 25110502
    [Google Scholar]
  9. Moh M.C. Zhang T. Lee L.H. Shen S. Expression of hepaCAM is downregulated in cancers and induces senescence-like growth arrest via a p53/p21-dependent pathway in human breast cancer cells. Carcinogenesis 2008 29 12 2298 2305 10.1093/carcin/bgn226 18845560
    [Google Scholar]
  10. Yang D. Liu M. Jiang J. Luo Y. Wang Y. Chen H. Li D. Wang D. Yang Z. Chen H. 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) 2022 14 24 6220 10.3390/cancers14246220 36551704
    [Google Scholar]
  11. Ding X. Wan A. Qi X. Jiang K. Liu Z. Chen B. ZNF695, a potential prognostic biomarker, correlates with im mune infiltrates in cervical squamous cell carcinoma and endoce rvical adenocarcinoma: Bioinformatic analysis and experimental verification. Curr. Gene Ther. 2024 24 5 441 452 10.2174/0115665232285216240228071244 38441026
    [Google Scholar]
  12. Hong J. Lin X. Hu X. Wu X. Fang W. A five-gene signature for predicting the prognosis of colorectal cancer. Curr. Gene Ther. 2021 21 4 280 289 10.2174/1566523220666201012151803 33045967
    [Google Scholar]
  13. Dong Y. Jin F. Wang J. Li Q. Huang Z. Xia L. Yang M. SFXN3 is associated with poor clinical outcomes and sensitivity to the hypomethylating therapy in non-M3 acute myeloid leukemia patients. Curr. Gene Ther. 2023 23 5 410 418 10.2174/1566523223666230724121515 37491851
    [Google Scholar]
  14. Han Q. Cui Z. Wang Q. Pang F. Li D. Wang D. Upregulation of OTX2-AS1 is associated with immune infiltration and predicts prognosis of gastric cancer. Technol. Cancer Res. Treat. 2023 22 10.1177/15330338231154091 36740995
    [Google Scholar]
  15. Liang W. Lu Y. Pan X. Zeng Y. Zheng W. Li Y. Nie Y. Li D. Wang D. Decreased expression of a novel lncRNA FAM181A-AS1 is associated with poor prognosis and immune infiltration in lung adenocarcinoma. Pharm. Genomics Pers. Med. 2022 15 985 998 10.2147/PGPM.S384901 36482943
    [Google Scholar]
  16. Wang J. Dai W. Zhang M. GATA3 positively regulates PAR1 to facilitate in vitro disease progression and decrease cisplatin sensitivity in neuroblastoma via inhibiting the hippo pathway. Anticancer Drugs 2023 34 1 57 72 10.1097/CAD.0000000000001341 35946556
    [Google Scholar]
  17. Pan H. Liu Q. Zhang F. Wang X. Wang S. Shi X. High STK40 expression as an independent prognostic biomarker and correlated with immune infiltrates in low-grade gliomas. Int. J. Gen. Med. 2021 14 6389 6400 10.2147/IJGM.S335821 34675607
    [Google Scholar]
  18. Xue J. Song Y. Xu W. Zhu Y. The CDK1-related lncRNA and CXCL8 mediated immune resistance in lung adenocarcinoma. Cells 2022 11 17 2688 10.3390/cells11172688 36078096
    [Google Scholar]
  19. Lin Z. Huang W. Yi Y. Li D. Xie Z. Li Z. Ye M. LncRNA ADAMTS9-AS2 is a prognostic biomarker and correlated with immune infiltrates in lung adenocarcinoma. Int. J. Gen. Med. 2021 14 8541 8555 10.2147/IJGM.S340683 34849000
    [Google Scholar]
  20. Yi W. Shen H. Sun D. Xu Y. Feng Y. Li D. Wang C. 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. 2022 28 e934522 10.12659/MSM.934522 34880202
    [Google Scholar]
  21. Chen J. Tang H. Li T. Jiang K. Zhong H. Wu Y. He J. Li D. Li M. Cai X. Comprehensive analysis of the expression, prognosis, and biological significance of OVOLs in breast cancer. Int. J. Gen. Med. 2021 14 3951 3960 10.2147/IJGM.S326402 34345183
    [Google Scholar]
  22. Liu J. Lichtenberg T. Hoadley K.A. An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics. Cell 2018 173 2 400 416.e11 10.1016/j.cell.2018.02.052 29625055
    [Google Scholar]
  23. Love M.I. Huber W. Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014 15 12 550 10.1186/s13059‑014‑0550‑8 25516281
    [Google Scholar]
  24. Yu G. Wang L.G. Han Y. He Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS 2012 16 5 284 287 10.1089/omi.2011.0118 22455463
    [Google Scholar]
  25. Subramanian A. Tamayo P. Mootha V.K. Mukherjee S. Ebert B.L. Gillette M.A. Paulovich A. Pomeroy S.L. Golub T.R. Lander E.S. Mesirov J.P. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 2005 102 43 15545 15550 10.1073/pnas.0506580102 16199517
    [Google Scholar]
  26. Chen T. Zhu C. Wang X. Pan Y. LncRNA ELF3-AS1 is a prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma. Can. J. Gastroenterol. Hepatol. 2021 2021 1 12 10.1155/2021/8323487 34336727
    [Google Scholar]
  27. Hänzelmann S. Castelo R. Guinney J. GSVA: Gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics 2013 14 1 7 10.1186/1471‑2105‑14‑7 23323831
    [Google Scholar]
  28. Bindea G. Mlecnik B. Tosolini M. Kirilovsky A. Waldner M. Obenauf A.C. Angell H. Fredriksen T. Lafontaine L. Berger A. Bruneval P. Fridman W.H. Becker C. Pagès F. Speicher M.R. Trajanoski Z. Galon J. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity 2013 39 4 782 795 10.1016/j.immuni.2013.10.003 24138885
    [Google Scholar]
  29. Cai H. Chen S. Wu Z. Wang F. Tang S. Li D. Wang D. Guo W. 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) 2023 15 22 13041 13058 10.18632/aging.205218 37980166
    [Google Scholar]
  30. Chalmers Z.R. Connelly C.F. Fabrizio D. Gay L. Ali S.M. Ennis R. Schrock A. Campbell B. Shlien A. Chmielecki J. Huang F. He Y. Sun J. Tabori U. Kennedy M. Lieber D.S. Roels S. White J. Otto G.A. Ross J.S. Garraway L. Miller V.A. Stephens P.J. Frampton G.M. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017 9 1 34 10.1186/s13073‑017‑0424‑2 28420421
    [Google Scholar]
  31. Jardim D.L. Goodman A. de Melo Gagliato D. Kurzrock R. The challenges of tumor mutational burden as an immunotherapy biomarker. Cancer Cell 2021 39 2 154 173 10.1016/j.ccell.2020.10.001 33125859
    [Google Scholar]
  32. Yamamoto H. Watanabe Y. Maehata T. Imai K. Itoh F. Microsatellite instability in cancer: A novel landscape for diagnostic and therapeutic approach. Arch. Toxicol. 2020 94 10 3349 3357 10.1007/s00204‑020‑02833‑z 32632538
    [Google Scholar]
  33. Bonneville R. Krook M.A. Kautto E.A. Miya J. Wing M.R. Chen H.Z. Reeser J.W. Yu L. Roychowdhury S. Landscape of microsatellite instability across 39 cancer types. JCO Precis. Oncol. 2017 2017 1 1 15 10.1200/PO.17.00073 29850653
    [Google Scholar]
  34. Zhong F. Liu J. Gao C. Chen T. Li B. Downstream regulatory network of MYBL2 mediating its oncogenic role in melanoma. Front. Oncol. 2022 12 816070 10.3389/fonc.2022.816070 35664780
    [Google Scholar]
  35. Chen B. Ding X. Wan A. Qi X. Lin X. Wang H. Mu W. Wang G. Zheng J. Comprehensive analysis of TLX2 in pan cancer as a prognostic and immunologic biomarker and validation in ovarian cancer. Sci. Rep. 2023 13 1 16244 10.1038/s41598‑023‑42171‑5 37758722
    [Google Scholar]
  36. Lu X. Li G. Liu S. Wang H. Zhang Z. Chen B. Bioinformatics analysis of KIF1A expression and gene regulation network in ovarian carcinoma. Int. J. Gen. Med. 2021 14 3707 3717 10.2147/IJGM.S323591 34321916
    [Google Scholar]
  37. Cui G. Cai F. Ding Z. Gao L. MMP14 predicts a poor prognosis in patients with colorectal cancer. Hum. Pathol. 2019 83 36 42 10.1016/j.humpath.2018.03.030 30120968
    [Google Scholar]
  38. Rao X. Wang J. Song H.M. Deng B. Li J.G. KRT15 overexpression predicts poor prognosis in colorectal cancer. Neoplasma 2020 67 2 410 414 10.4149/neo_2019_190531N475 31884802
    [Google Scholar]
  39. Sun X. Feng Z. Wang Y. Qu Y. Gai Y. Expression of Foxp3 and its prognostic significance in colorectal cancer. Int. J. Immunopathol. Pharmacol. 2017 30 2 201 206 10.1177/0394632017710415 28560891
    [Google Scholar]
  40. Zhu Y.F. Dong M. Expression of TUSC3 and its prognostic significance in colorectal cancer. Pathol. Res. Pract. 2018 214 9 1497 1503 10.1016/j.prp.2018.07.004 30115537
    [Google Scholar]
  41. Jeong D. Heo S. Sung Ahn T. Lee S. Park S. Kim H. Park D. Byung Bae S. Lee S.S. Soo Lee M. Kim C.J. Jun Baek M. Cyr61 expression is associated with prognosis in patients with colorectal cancer. BMC Cancer 2014 14 1 164 10.1186/1471‑2407‑14‑164 24606730
    [Google Scholar]
  42. Zhang G.L. Pan L.L. Huang T. Wang J.H. The transcriptome difference between colorectal tumor and normal tissues revealed by single-cell sequencing. J. Cancer 2019 10 23 5883 5890 10.7150/jca.32267 31737124
    [Google Scholar]
  43. Wu Z. Liu Z. Ge W. Shou J. You L. Pan H. Han W. Analysis of potential genes and pathways associated with the colorectal normal mucosa–adenoma–carcinoma sequence. Cancer Med. 2018 7 6 2555 2566 10.1002/cam4.1484 29659199
    [Google Scholar]
  44. Lv G. Wang Q. Lin L. Ye Q. Li X. Zhou Q. Kong X. Deng H. You F. Chen H. Wu S. Yuan L. mTORC2-driven chromatin cGAS mediates chemoresistance through epigenetic reprogramming in colorectal cancer. Nat. Cell Biol. 2024 26 9 1585 1596 Epub ahead of print 10.1038/s41556‑024‑01473‑0 39080411
    [Google Scholar]
  45. Meng L. Chromatin-modifying enzymes as modulators of nuclear size during lineage differentiation. Cell Death Discov. 2023 9 1 384 10.1038/s41420‑023‑01639‑z 37863956
    [Google Scholar]
  46. Huang W. Hickson L.J. Eirin A. Kirkland J.L. Lerman L.O. Cellular senescence: The good, the bad and the unknown. Nat. Rev. Nephrol. 2022 18 10 611 627 10.1038/s41581‑022‑00601‑z 35922662
    [Google Scholar]
  47. Zhao P. Sun L. Zhao C. TCF1/LEF1 triggers Wnt-dependent chemokine/cytokine-induced inflammation and cadherin pathways to drive T-ALL cell migration. Biochem. Biophys. Rep. 2023 34 101457 10.1016/j.bbrep.2023.101457 36942321
    [Google Scholar]
  48. Chelbi H. Jelassi R. Belfkih S. Ben Amor A. Saidi N. Ben Salah H. Mzoughi N. Ben Dhifallah I. Boujelben N. Ammi R. Bouratbine A. Zidi I. Aoun K. Association of CCR5Δ32 deletion and human cytomegalovirus infection with colorectal cancer in Tunisia. Front. Genet. 2021 12 598635 10.3389/fgene.2021.598635 34976001
    [Google Scholar]
  49. Murphy E. Yu D. Grimwood J. Schmutz J. Dickson M. Jarvis M.A. Hahn G. Nelson J.A. Myers R.M. Shenk T.E. Coding potential of laboratory and clinical strains of human cytomegalovirus. Proc. Natl. Acad. Sci. USA 2003 100 25 14976 14981 10.1073/pnas.2136652100 14657367
    [Google Scholar]
  50. Kishore C. Epigenetic regulation and promising therapies in colorectal cancer. Curr. Mol. Pharmacol. 2021 14 5 838 852 10.2174/1874467214666210126105345 33573584
    [Google Scholar]
  51. Park C.K. Kim H.S. Clinicopathological characteristics of ovarian metastasis from colorectal and pancreatobiliary carcinomas mimicking primary ovarian mucinous tumor. Anticancer Res. 2018 38 9 5465 5473 10.21873/anticanres.12879 30194204
    [Google Scholar]
  52. Gong X. Tian X. Xie H. Li Z. The structural maintenance of chromosomes 5 is a possible biomarker for individualized treatment of colorectal cancer. Cancer Med. 2023 12 3 3276 3287 10.1002/cam4.5074 35894836
    [Google Scholar]
  53. Picard E. Verschoor C.P. Ma G.W. Pawelec G. Relationships between immune landscapes, genetic subtypes and responses to immunotherapy in colorectal cancer. Front. Immunol. 2020 11 369 10.3389/fimmu.2020.00369 32210966
    [Google Scholar]
  54. Farkona S. Diamandis E.P. Blasutig I.M. Cancer immunotherapy: The beginning of the end of cancer? BMC Med. 2016 14 1 73 10.1186/s12916‑016‑0623‑5 27151159
    [Google Scholar]
  55. Berry J. Vreeland T. Trappey A. Hale D. Peace K. Tyler J. Walker A. Brown R. Herbert G. Yi F. Jackson D. Clifton G. Peoples G.E. Cancer vaccines in colon and rectal cancer over the last decade: Lessons learned and future directions. Expert Rev. Clin. Immunol. 2017 13 3 235 245 10.1080/1744666X.2016.1226132 27552944
    [Google Scholar]
  56. Munro M.J. Wickremesekera S.K. Peng L. Tan S.T. Itinteang T. Cancer stem cells in colorectal cancer: A review. J. Clin. Pathol. 2018 71 2 110 116 10.1136/jclinpath‑2017‑204739 28942428
    [Google Scholar]
  57. Wang L. Liu W. Liu J. Wang Y. Tai J. Yin X. Tan J. 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. 2021 10 554138 10.3389/fonc.2020.554138 33718103
    [Google Scholar]
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  • Article Type:
    Research Article
Keywords: prognosis ; pathway ; drug sensitivity ; HEPACAM2 ; immune infiltration ; Colorectal cancer
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