ALDH18A1 Expression Profiling in Non-small Cell Lung Cancer through Bioinformatics and Experimental Approaches

Authors

  • Wurihan Graduate School of Medical Sciences, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia https://orcid.org/0009-0007-5373-2845
  • Yirigui School of Preclinical and Forensic Medicine, Baotou Medical College, Inner Mongolia University of Science and Technology, Inner Mongolia, China
  • Jie Cheng Tumor Center, The First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology, Inner Mongolia, China https://orcid.org/0000-0002-2977-8671
  • Sarantuya Enkhjargal Graduate School of Medical Sciences, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia https://orcid.org/0000-0003-4730-1110
  • Nyamdorj Dagdanbazar School of Bio-medicine, Mongolian National University of Medical Sciences, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia https://orcid.org/0000-0002-7646-6865
  • Hanjun Pei Department of Cardiology, The First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology, Inner Mongolia, China https://orcid.org/0009-0009-4712-0150
  • Shiirevnyamba Avirmed Department of Surgery, School of Medicine, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia https://orcid.org/0000-0002-1010-8221
  • Uurtuya Shuumarjav Graduate School of Medical Sciences, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia https://orcid.org/0000-0002-9951-2457

Keywords:

Non-small cell lung cancer, ALDH18A1, Immunohistochemistry, Gene Expression , Bioinformatics

Abstract

Objective: Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related death worldwide. The molecular mechanisms of NSCLC are still not fully understood. This study used bioinformatics analysis of public databases to identify potential biomarkers and therapeutic targets. This study used integrated bioinformatics analyses to identify candidate oncogenes associated with in NSCLC. Tissue microarray-based immunohistochemistry was then performed to characterize the protein expression pattern of ALDH18A1 in NSCLC tissues and to preliminarily evaluate its potential as a biomarker. Methods: In this study, TCGA transcriptomic data were analyzed by weighted gene co-expression network analysis (WGCNA), differential expression analysis, least absolute shrinkage and selection operator (LASSO) regression, and random forest analysis to identify ALDH18A1 as a candidate gene in NSCLC. The protein expression of ALDH18A1 was then examined by immunohistochemistry (IHC) using tissue microarrays (TMAs) containing 80 lung squamous cell carcinoma samples, 52 lung adenocarcinoma samples, and their paired adjacent normal tissues. Results: In this study, WGCNA, differential expression analysis, LASSO regression, and random forest analysis identified ALDH18A1 as a key candidate gene in NSCLC. Immunohistochemical analysis showed that the expression level of ALDH18A1 protein was significantly higher in NSCLC tissues than in paired adjacent normal tissues (p < 0.05). Conclusions: ALDH18A1 is markedly upregulated in NSCLC and appears to contribute to tumorigenesis and disease progression, highlighting its promise as a potential diagnostic biomarker and a candidate target for therapeutic intervention.

Abstract
0
PDF
0

Author Biography

Wurihan, Graduate School of Medical Sciences, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia

Tumor Center, The First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology, Inner Mongolia, China

References

1. Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249. https://doi.org/10.3322/caac.21660

2. Bray F, Laversanne M, Weiderpass E, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74(3):229-263. https://doi.org/10.3322/caac.21834

3. Bade BC, Dela Cruz CS. Lung cancer 2020: epidemiology, etiology, and prevention. Clin Chest Med. 2020;41(1):1-24. https://doi.org/10.1016/j.ccm.2019.10.001

4. Siegel RL, Kratzer TB, Giaquinto AN, et al. Cancer statistics, 2025. CA Cancer J Clin. 2025;75(1):10-45. https://doi.org/10.3322/caac.21871

5. Thai AA, Solomon BJ, Sequist LV, et al. Lung cancer. Lancet. 2021;398(10299):535-554. https://doi.org/10.1016/S0140-6736(21)00317-0

6. Chan LW, Ding T, Shao H, et al. Augmented features synergize radiomics in postoperative survival prediction and adjuvant therapy recommendation for non-small cell lung cancer. Front Oncol. 2022;12:659096. https://doi.org/10.3389/fonc.2022.659096

7. Xiong Q, Qin B, Xin L, et al. Real-world efficacy and safety of anlotinib with and without immunotherapy in advanced non-small cell lung cancer. Front Oncol. 2021;11:659380. https://doi.org/10.3389/fonc.2021.659380

8. Jeon H, Wang S, Song J, et al. Update 2025: Management of non-small-cell lung cancer. Lung. 2025;203(1):53. https://doi.org/10.1007/s00408-024-00700-9

9. Zhou Y, Li H, Chen Y, et al. Comprehensive analysis of differential gene expression to identify common gene signatures in multiple cancers. Biomed Res Int. 2021;2021:6616700. https://doi.org/10.1155/2021/6616700

10. Perkel JM. Data visualization tools drive interactivity and reproducibility in online publishing. Nature. 2020;587(7832):147-149. https://doi.org/10.1038/d41586-020-02831-4

11. Tzec-Interián JA, González-Padilla D, Góngora-Castillo EB. Bioinformatics perspectives on transcriptomics: a comprehensive review of bulk and single-cell RNA sequencing analyses. Quant Biol. 2025;13(2):e78. https://doi.org/10.1007/s40484-025-00378-1

12. Isaic A, Motofelea N, Hoinoiu T, et al. Next-generation sequencing: a review of its transformative impact on cancer diagnosis, treatment, and resistance management. Diagnostics (Basel). 2025;15(19):2425. https://doi.org/10.3390/diagnostics15192425

13. Geng P, Qin W, Xu G. Proline metabolism in cancer. Amino Acids. 2021;53(12):1769-1777. https://doi.org/10.1007/s00726-021-03046-5

14. Xu X, Zhang G, Chen Y, et al. Can proline dehydrogenase a key enzyme involved in proline metabolism be a novel target for cancer therapy? Front Oncol. 2023;13:1254439. https://doi.org/10.3389/fonc.2023.1254439

15. Marchitti SA, Orlicky DJ, Vasiliou V. Non-P450 aldehyde oxidizing enzymes: the aldehyde dehydrogenase superfamily. Expert Opin Drug Metab Toxicol. 2008;4(6): 697-720. https://doi.org/10.1517/17425255.4.6.697

16. Liu G, Snetsinger S, De Jong PJ, et al. Assignment of the human gene encoding the delta1-pyrroline-5-carboxylate synthetase (P5CS) to 10q24.3 by in situ hybridization. Genomics. 1996;37(1):145-146. https://doi.org/10.1006/geno.1996.0396

17. Kardos GR, Wastyk HC, Robertson GP. Disruption of Proline Synthesis in Melanoma Inhibits Protein Production Mediated by the GCN2 Pathway. Mol Cancer Res. 2017;15(3):281-293. https://doi.org/10.1158/1541-7786.MCR-16-0118

18. Phang JM. Proline metabolism in cell regulation and cancer biology: recent advances and hypotheses. Antioxid Redox Signal. 2019;30(4):635-649. https://doi.org/10.1089/ars.2017.7342

19. Boroughs LK, DeBerardinis RJ. Metabolic pathways promoting cancer cell survival and growth. Nat Cell Biol. 2015;17(4):351-359. https://doi.org/10.1038/ncb3124

20. Xia J, Chen J, Wang H, et al. Aldehyde dehydrogenase in solid tumors and other diseases. MedComm (2020). 2023;4(1):e195. https://doi.org/10.1002/mco2.195

21. Bray F, Laversanne M, Weiderpass E. The ever-increasing importance of cancer as a leading cause of premature death worldwide. Cancer. 2021;127(16):3029-3030. https://doi. org/10.1002/cncr.33687

22. Phang JM, Liu W, Hancock C, Christian KJ. The proline regulatory axis and cancer. Curr Opin Clin Nutr Metab Care. 2015;18(1):71–77. https://doi.org/10.1097/MCO.0000000000000122

23. Barr T, Ma SB, Li ZX, et al. Recent advances and remaining challenges in lung cancer therapy. Chin Med J (Engl). 2024;137(5):533-546. https://doi.org/10.1097/ CM9.0000000000002991

24. Wei G, Dong Y, He Z, et al. Identification of hub genes and construction of an mRNA-miRNA-lncRNA regulatory network in gastric carcinoma using integrated bioinformatics analysis. PLoS One. 2021;16(12):e0261728. https://doi.org/10.1371/journal.pone.0261728

25. Zhou X, Hao M, Guo X, et al. Identification and validation of differentially expressed genes for non-small cell lung cancer using multiple GEO microarray datasets. Front Oncol. 2023;13:1206768. https://doi.org/10.3389/fonc.2023.1206768

26. Zhu S, Zhao J, Li X, et al. Regulation of glucose, fatty acid and amino acid metabolism by ubiquitination and SUMOylation in disease. Front Cell Dev Biol. 2022;10:849625. https://doi.org/10.3389/fcell.2022.849625

27. Daniello C, Patriarca E, Phang J, et al. Proline metabolism in tumor growth and metastatic progression. Front Oncol. 2020;10:776. https://doi.org/10.3389/fonc. 2020.00776

28. Linder SJ, Bernasocchi T, Martínez-Pastor B, et al. Inhibition of the proline metabolism rate-limiting enzyme P5CS allows proliferation of glutamine-restricted cancer cells. Nat Metab. 2023;5(12):2131-2147. https://doi.org/10.1038/s42255- 023-00819-3

29. Zhang Y, Li X, Wang Y, et al. ALDH18A1 has carcinogenic functions and regulates alternative splicing events of DNA repair-related genes in esophageal carcinoma cells. Sci Rep. 2022;12(1):10203. https://doi.org/10.1038/s41598-022- 14337-1

30. Duan JJ, Wang J, Wang D, et al. Glutamine-arginine-proline axis: a key node in cancer metabolism. Front Oncol. 2022;12:963444. https://doi.org/10.3389/fonc.2022.963444

Downloads

Published

2026-05-21

How to Cite

Wurihan, Yirigui, Cheng, J., Enkhjargal, S., Dagdanbazar, N., Pei, H., Avirmed, S., & Shuumarjav, U. (2026). ALDH18A1 Expression Profiling in Non-small Cell Lung Cancer through Bioinformatics and Experimental Approaches. Central Asian Journal of Medical Sciences, 12(2), 58-68. https://doi.org/10.24079/cajms.2026.02.006

Issue

Section

Articles

How to Cite

Wurihan, Yirigui, Cheng, J., Enkhjargal, S., Dagdanbazar, N., Pei, H., Avirmed, S., & Shuumarjav, U. (2026). ALDH18A1 Expression Profiling in Non-small Cell Lung Cancer through Bioinformatics and Experimental Approaches. Central Asian Journal of Medical Sciences, 12(2), 58-68. https://doi.org/10.24079/cajms.2026.02.006

Most read articles by the same author(s)

1 2 > >>