Skip to content
2000
image of Comprehensive Analysis to Reveal Nitrogen Metabolism-Associated Genes as a Prognostic Index in Head and Neck Squamous Cell Cancer

Abstract

Background

Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis and a high fatality rate. To predict the prognosis of HNSCC, this study developed a prognostic model based on nitrogen metabolism (NM)-related genes.

Methods

This study utilized transcriptomic data and clinical information from HNSCC obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify differentially expressed NM-related genes. Subsequently, an NM-related prognostic risk model was established by integrating univariate Cox regression, LASSO regression, and multivariate Cox regression. Its predictive value was validated using Kaplan-Meier and ROC curves. Further analysis using GSVA and CIBERSORT examined the relationship between the risk model and the tumor microenvironment immune status, while also evaluating chemotherapy drug sensitivity across different risk groups. Finally, protein-protein interaction (PPI) networks and key gene screening were employed, and the functional validation of the core genes was conducted through experiments.

Results

We identified 10 key NM-related genes (GLS, ASNS, EXT2, HPRT1, SLC7A5, SMS, B3GNT8, GATM, NAGK, and SULT1B1) to construct a prognostic risk model. The GSVA analysis revealed that the low-risk group was enriched in immune-related pathways, while the high-risk group favored metabolic pathways. Additionally, the low-risk group exhibited higher levels of immune cell infiltration. We discovered that gefitinib, belinostat, erlotinib, and phenformin were more effective against cancer cells with lower risk scores. The PPI network screening identified key hub genes, including LORICRIN. Experimental validation demonstrated that LORICRIN overexpression significantly suppressed migration and invasion in HNSCC cells, suggesting its potential tumor-suppressive role in carcinogenesis and progression.

Discussion

This study emphasizes the links between NM signatures, immune regulation, and signaling pathways, underscoring their potential in the HNSCC mechanism research.

Conclusion

Our study established a NM-related gene signature closely linked to immune microenvironment and drug sensitivity, highlighting potential biomarkers and therapeutic targets for prognosis and personalized therapy in HNSCC.

© 2026 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cmc/10.2174/0109298673427009251022060122
2026-01-09
2026-02-19

  • From This Site

    /content/journals/cmc/10.2174/0109298673427009251022060122
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Sharifi S. Khan H. Abdolahinia E.D. Ahmadian S. Bohlouli S. Gharehbagh F.J. Jahandizi N.G. Vahed S.Z. Saadat Y.R. Aghbali A. Dizaj S.M. Alsharif K.F. Effect of curcumin on the head and neck squamous cell carcinoma cell line HN5. Curr. Mol. Pharmacol. 2023 16 3 374 380 10.2174/1874467215666220414143441 35431006
    [Google Scholar]
  2. Zhang X. Zu T. Wen J. Zhou Q. Y27632 induces tongue squamous cell carcinoma cell apoptosis through MAPK-ERK/JNK signal. Oncologie 2024 26 6 957 967 10.1515/oncologie‑2024‑0272
    [Google Scholar]
  3. Li H.X. Gong Y.W. Yan P.J. Xu Y. Qin G. Wen W.P. Teng F.Y. Revolutionizing head and neck squamous cell carcinoma treatment with nanomedicine in the era of immunotherapy. Front. Immunol. 2024 15 1453753 10.3389/fimmu.2024.1453753 39676875
    [Google Scholar]
  4. Wang S. Liu Y. Feng Y. Zhang J. Swinnen J. Li Y. Ni Y. A review on curability of cancers: More efforts for novel therapeutic options are needed. Cancers 2019 11 11 1782 10.3390/cancers11111782 31766180
    [Google Scholar]
  5. Bishop J.A. Gagan J. Paterson C. McLellan D. Sandison A. Nonkeratinizing squamous cell carcinoma of the sinonasal tract with DEK-AFF2. Am. J. Surg. Pathol. 2021 45 5 718 720 10.1097/PAS.0000000000001596 33002918
    [Google Scholar]
  6. Zhou C. Wang S. Shen Z. Shen Y. Li Q. Shen Y. Huang J. Deng H. Ye D. Zhan G. Li J. Construction of an m6A-related lncRNA pair prognostic signature and prediction of the immune landscape in head and neck squamous cell carcinoma. J. Clin. Lab. Anal. 2022 36 1 e24113 10.1002/jcla.24113 34783061
    [Google Scholar]
  7. Kurmi K. Haigis M.C. Nitrogen metabolism in cancer and immunity. Trends Cell Biol. 2020 30 5 408 424 10.1016/j.tcb.2020.02.005 32302552
    [Google Scholar]
  8. Pavlova N.N. Thompson C.B. The emerging hallmarks of cancer metabolism. Cell Metab. 2016 23 1 27 47 10.1016/j.cmet.2015.12.006 26771115
    [Google Scholar]
  9. Sciacovelli M. Dugourd A. Jimenez L.V. Yang M. Nikitopoulou E. Costa A.S.H. Tronci L. Caraffini V. Rodrigues P. Schmidt C. Ryan D.G. Young T. Zecchini V.R. Rossi S.H. Massie C. Lohoff C. Masid M. Hatzimanikatis V. Kuppe C. Von Kriegsheim A. Kramann R. Gnanapragasam V. Warren A.Y. Stewart G.D. Erez A. Vanharanta S. Saez-Rodriguez J. Frezza C. Dynamic partitioning of branched-chain amino acids-derived nitrogen supports renal cancer progression. Nat. Commun. 2022 13 1 7830 10.1038/s41467‑022‑35036‑4 36539415
    [Google Scholar]
  10. Zhang Z. Xiahou Z. Wu W. Song Y. Nitrogen metabolism disorder accelerates occurrence and development of lung adenocarcinoma: A bioinformatic analysis and in vitro experiments. Front. Oncol. 2022 12 916777 10.3389/fonc.2022.916777 35903696
    [Google Scholar]
  11. Fox C.J. Hammerman P.S. Thompson C.B. Fuel feeds function: Energy metabolism and the T-cell response. Nat. Rev. Immunol. 2005 5 11 844 852 10.1038/nri1710 16239903
    [Google Scholar]
  12. Ron-Harel N. Ghergurovich J.M. Notarangelo G. LaFleur M.W. Tsubosaka Y. Sharpe A.H. Rabinowitz J.D. Haigis M.C. T cell activation depends on extracellular alanine. Cell Rep. 2019 28 12 3011 3021.e4 10.1016/j.celrep.2019.08.034 31533027
    [Google Scholar]
  13. Yang L. Chu Z. Liu M. Zou Q. Li J. Liu Q. Wang Y. Wang T. Xiang J. Wang B. Amino acid metabolism in immune cells: Essential regulators of the effector functions, and promising opportunities to enhance cancer immunotherapy. J. Hematol. Oncol. 2023 16 1 59 10.1186/s13045‑023‑01453‑1 37277776
    [Google Scholar]
  14. Yoo H.C. Han J.M. Amino acid metabolism in cancer drug resistance. Cells 2022 11 1 140 10.3390/cells11010140 35011702
    [Google Scholar]
  15. Song Z. Yu J. Wang M. Shen W. Wang C. Lu T. Shan G. Dong G. Wang Y. Zhao J. CHDTEPDB: Transcriptome expression profile database and interactive analysis platform for congenital heart disease. Congenit. Heart Dis. 2023 18 6 693 701 10.32604/chd.2024.048081
    [Google Scholar]
  16. Dong Z. Zhao C. Hu S. Yang K. Yu J. Sun X. Zheng J. Bioinformatic analysis and in vivo validation of angiogenesis related genes in inflammatory bowel disease. Biocell 2023 47 12 2735 2745 10.32604/biocell.2023.043422
    [Google Scholar]
  17. Li Y. Dong Y. Xu C. Su G. Xiao L. Liu Y. Mei H. Clinical neutrophil-related gene helps treat bladder urothelial carcinoma. Oncologie 2023 25 5 529 542 10.1515/oncologie‑2023‑0140
    [Google Scholar]
  18. Yan S. Han Z. Wang T. Wang A. Liu F. Yu S. Xu L. Shen H. Liu L. Lin Z. Na M. Exploring the immune-related molecular mechanisms underlying the comorbidity of temporal lobe epilepsy and major depressive disorder through integrated data set analysis. Curr. Mol. Pharmacol. 2025 17 17 10.2174/0118761429380394250217093030 39976098
    [Google Scholar]
  19. Tian S. Chen M. Jing W. Meng Q. Wu J. miR-1204 positioning in 8q24.21 involved in the tumorigenesis of colorectal cancer by targeting MASPIN. Protein Pept. Lett. 2024 31 7 544 558 10.2174/0109298665305114240718072029 39082173
    [Google Scholar]
  20. Liu Z. Sun Y. Yu M. Huang Y. Ma L. Kong L. Novel STAT3 inhibitor exerts anti-breast cancer effects both in vitro and in vivo. Lett. Drug Des. Discov. 2023 20 12 2070 2079 10.2174/1570180820666230116153822
    [Google Scholar]
  21. 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]
  22. Begum S. Cao D. Gillison M. Zahurak M. Westra W.H. Tissue distribution of human papillomavirus 16 DNA integration in patients with tonsillar carcinoma. Clin. Cancer Res. 2005 11 16 5694 5699 10.1158/1078‑0432.CCR‑05‑0587 16115905
    [Google Scholar]
  23. Ferlay J. Colombet M. Soerjomataram I. Mathers C. Parkin D.M. Piñeros M. Znaor A. Bray F. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int. J. Cancer 2019 144 8 1941 1953 10.1002/ijc.31937 30350310
    [Google Scholar]
  24. Chatfield-Reed K. Gui S. O’Neill W.Q. Teknos T.N. Pan Q. HPV33+ HNSCC is associated with poor prognosis and has unique genomic and immunologic landscapes. Oral Oncol. 2020 100 104488 10.1016/j.oraloncology.2019.104488 31835137
    [Google Scholar]
  25. Hosios A.M. Hecht V.C. Danai L.V. Johnson M.O. Rathmell J.C. Steinhauser M.L. Manalis S.R. Vander Heiden M.G. Amino acids rather than glucose account for the majority of cell mass in proliferating mammalian cells. Dev. Cell 2016 36 5 540 549 10.1016/j.devcel.2016.02.012 26954548
    [Google Scholar]
  26. Lane A.N. Fan T.W.M. Regulation of mammalian nucleotide metabolism and biosynthesis. Nucleic Acids Res. 2015 43 4 2466 2485 10.1093/nar/gkv047 25628363
    [Google Scholar]
  27. Griffin J.W.D. Liu Y. Bradshaw P.C. Wang K. In silico preliminary association of ammonia metabolism genes GLS, CPS1, and GLUL with risk of Alzheimer’s disease, major depressive disorder, and type 2 diabetes. J. Mol. Neurosci. 2018 64 3 385 396 10.1007/s12031‑018‑1035‑0 29441491
    [Google Scholar]
  28. Kim H.M. Koo J.S. Expression of Glutamine metabolism-related and amino acid transporter proteins in adrenal cortical neoplasms and pheochromocytomas. Dis. Markers 2021 2021 1 9 10.1155/2021/8850990 33505538
    [Google Scholar]
  29. Akahane K. Kimura S. Miyake K. Watanabe A. Kagami K. Yoshimura K. Shinohara T. Harama D. Kasai S. Goi K. Kawai T. Hata K. Kiyokawa N. Koh K. Imamura T. Horibe K. Look A.T. Minegishi M. Sugita K. Takita J. Inukai T. Association of allele-specific methylation of the ASNS gene with asparaginase sensitivity and prognosis in T-ALL. Blood Adv. 2022 6 1 212 224 10.1182/bloodadvances.2021004271 34535013
    [Google Scholar]
  30. Shen L. Dong X. Wang Y. Qiu L. Peng F. Luo Z. β3GnT8 regulates oxaliplatin resistance by altering integrin β1 glycosylation in colon cancer cells. Oncol. Rep. 2018 39 4 2006 2014 29393491
    [Google Scholar]
  31. Xian C. Zhu M. Nong T. Li Y. Xie X. Li X. Li J. Li J. Wu J. Shi W. Wei P. Xu H. Tang Y. A novel mutation in ext2 caused hereditary multiple exostoses through reducing the synthesis of heparan sulfate. Genet. Mol. Biol. 2021 44 2 e20200334 10.1590/1678‑4685‑gmb‑2020‑0334 34042151
    [Google Scholar]
  32. Forst A.L. Reichold M. Kleta R. Warth R. Distinct mitochondrial pathologies caused by mutations of the proximal tubular enzymes EHHADH and GATM. Front. Physiol. 2021 12 715485 10.3389/fphys.2021.715485 34349672
    [Google Scholar]
  33. Ahmadi M. Eftekhari Kenzerki M. Akrami S.M. Pashangzadeh S. Hajiesmaeili F. Rahnavard S. Habibipour L. Saffarzadeh N. Mousavi P. Overexpression of HPRT1 is associated with poor prognosis in head and neck squamous cell carcinoma. FEBS Open Bio 2021 11 9 2525 2540 10.1002/2211‑5463.13250 34231338
    [Google Scholar]
  34. Campbell S. Mesaros C. Izzo L. Affronti H. Noji M. Schaffer B.E. Tsang T. Sun K. Trefely S. Kruijning S. Blenis J. Blair I.A. Wellen K.E. Glutamine deprivation triggers NAGK-dependent hexosamine salvage. eLife 2021 10 e62644 10.7554/eLife.62644 34844667
    [Google Scholar]
  35. Lian W. Jin H. Cao J. Zhang X. Zhu T. Zhao S. Wu S. Zou K. Zhang X. Zhang M. Zheng X. Peng M. Identification of novel biomarkers affecting the metastasis of colorectal cancer through bioinformatics analysis and validation through qRT-PCR. Cancer Cell Int. 2020 20 1 105 10.1186/s12935‑020‑01180‑4 32256214
    [Google Scholar]
  36. Ping Y. Shan J. Qin H. Li F. Qu J. Guo R. Han D. Jing W. Liu Y. Liu J. Liu Z. Li J. Yue D. Wang F. Wang L. Zhang B. Huang B. Zhang Y. PD-1 signaling limits expression of phospholipid phosphatase 1 and promotes intratumoral CD8+ T cell ferroptosis. Immunity 2024 57 9 2122 2139.e9 10.1016/j.immuni.2024.08.003 39208806
    [Google Scholar]
  37. Wang R. Li C. Cheng Z. Li M. Shi J. Zhang Z. Jin S. Ma H. H3K9 lactylation in malignant cells facilitates CD8+ T cell dysfunction and poor immunotherapy response. Cell Rep. 2024 43 9 114686 10.1016/j.celrep.2024.114686 39216002
    [Google Scholar]
  38. Maimela N.R. Liu S. Zhang Y. Fates of CD8+ T cells in tumor microenvironment. Comput. Struct. Biotechnol. J. 2019 17 1 13 10.1016/j.csbj.2018.11.004 30581539
    [Google Scholar]
  39. Liu X. Song J. Zhang H. Liu X. Zuo F. Zhao Y. Zhao Y. Yin X. Guo X. Wu X. Zhang H. Xu J. Hu J. Jing J. Ma X. Shi H. Immune checkpoint HLA-E:CD94-NKG2A mediates evasion of circulating tumor cells from NK cell surveillance. Cancer Cell 2023 41 2 272 287 10.1016/j.ccell.2023.01.001 36706761
    [Google Scholar]
  40. Huang J. Xu Z. Teh B.M. Zhou C. Yuan Z. Shi Y. Shen Y. Construction of a necroptosis-related lncRNA signature to predict the prognosis and immune microenvironment of head and neck squamous cell carcinoma. J. Clin. Lab. Anal. 2022 36 6 e24480 10.1002/jcla.24480 35522142
    [Google Scholar]
  41. Yuan Z. Huang J. Teh B.M. Hu S. Hu Y. Shen Y. Exploration of a predictive model based on genes associated with fatty acid metabolism and clinical treatment for head and neck squamous cell carcinoma. J. Clin. Lab. Anal. 2022 36 11 e24722 10.1002/jcla.24722 36181275
    [Google Scholar]
  42. Huang R. Li Z. Zhu X. Yan P. Song D. Yin H. Hu P. Lin R. Wu S. Meng T. Zhang J. Huang Z. Collagen Type III Alpha 1 chain regulated by GATA-Binding Protein 6 affects Type II IFN response and propanoate metabolism in the recurrence of lower grade glioma. J. Cell. Mol. Med. 2020 24 18 10803 10815 10.1111/jcmm.15705 32757451
    [Google Scholar]
  43. Jin Y. Qin X. Co-expression network-based identification of biomarkers correlated with the lymph node metastasis of patients with head and neck squamous cell carcinoma. Biosci. Rep. 2020 40 2 BSR20194067 10.1042/BSR20194067 32076707
    [Google Scholar]
  44. S N. Joshua E. K R. Thavarajah R. Rao U.K. Loricrin expression and its implication in oral submucous fibrosis, hyperkeratosis and normal mucosa with association to habits – An immunohistochemical study. J. Oral Biol. Craniofac. Res. 2019 9 3 226 231 10.1016/j.jobcr.2019.05.004 31193624
    [Google Scholar]
/content/journals/cmc/10.2174/0109298673427009251022060122
Loading
Comprehensive Analysis to Reveal Nitrogen Metabolism-Associated Genes as a Prognostic Index in Head and Neck Squamous Cell Cancer
Bentham Science Publishers ; https://doi.org/10.2174/0109298673427009251022060122
/content/journals/cmc/10.2174/0109298673427009251022060122
/content/journals/cmc/10.2174/0109298673427009251022060122
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

file format download Download

  • Article Type:     Research Article
Keywords: DNA ; tumor microenvironment ; prognosis ; immune cell ; Head and neck squamous cell carcinoma ; nitrogen metabolism

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test