Skip to main content
Log in

1H-NMR-based metabolomics reveals the biomarker panel and molecular mechanism of hepatocellular carcinoma progression

  • Research Paper
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

Abstract

Hepatocellular carcinoma (HCC) is one of the most extensive and most deadly cancers in the world. Biomarkers for early diagnosis of HCC are still lacking, and noninvasive and effective biomarkers are urgently needed. Metabolomics is committed to studying the changes of metabolites under stimulation, and provides a new approach for discovery of potential biomarkers. In the current work, 1H nuclear magnetic resonance (NMR) metabolomics approach was utilized to explore the potential biomarkers in HCC progression, and the biomarker panel was evaluated by receiver operating characteristic (ROC) curve analyses. Our results revealed that a biomarker panel consisting of hippurate, creatinine, putrescine, choline, and taurine might be involved in HCC progression. Functional pathway analysis showed that taurine and hypotaurine metabolism is markedly involved in the occurrence and development of HCC. Furthermore, our results indicated that the TPA activity and the level and expression of PKM2 were gradually increased in HCC progression. This research provides a scientific basis for screening potential biomarkers of HCC.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Abbreviations

HCC:

Hepatocellular carcinoma

NMR:

Nuclear magnetic resonance

ROC:

Receiver operating characteristic

AFP:

Alpha-fetoprotein

DEN:

Diethylnitrosamine

LC:

Liver cirrhosis

AKP:

Alkaline phosphatase

AST:

Aspartate aminotransferase

ALT:

Alanine aminotransferase

γ-GT:

Gamma-glutamyl transpeptidase

ELISA:

Enzyme-linked immunosorbent assay

TPA:

Taurine-pyruvate aminotransferase

SPF:

Specific pathogen-free

HE:

Hematoxylin and eosin

PCA:

Principal component analysis

PLS-DA:

Partial least-squares discriminant analysis

OPLS-DA:

Orthogonal partial least-squares discriminant analysis

FDR:

False discovery rate

AUC:

Area under the ROC curve

References

  1. Njei B, Rotman Y, Ditah I, Lim JK. Emerging trends in hepatocellular carcinoma incidence and mortality. Hepatology. 2015;61:191–9.

    Article  Google Scholar 

  2. Ma C, Han MJ, Heinrich B, Fu Q, Zhang QF, Sandhu M, et al. Gut microbiome-mediated bile acid metabolism regulates liver cancer via NKT cells. Science. 2018;360:eaan5931.

  3. Wang XJ, Zhang AH, Sun H. Power of metabolomics in diagnosis and biomarker discovery of hepatocellular carcinoma. Hepatology. 2013;57:2072–7.

    Article  CAS  Google Scholar 

  4. Shao YP, Zhu B, Zheng RY, Zhao XJ, Yin PY, Lu X, et al. Development of urinary pseudotargeted LC-MS-based metabolomics method and its application in hepatocellular carcinoma biomarker discovery. J Proteome Res. 2015;14:906–16.

    Article  CAS  Google Scholar 

  5. Marrero JA, Lok AS. Newer markers for hepatocellular carcinoma. Gastroenterology. 2004;127:S113–9.

    Article  CAS  Google Scholar 

  6. Chen XL, Zhou L, Yang J, Shen FK, Zhao SP, Wang YL. Hepatocellular carcinoma-associated protein markers investigated by MALDI-TOF MS. Mol Med Rep. 2010;3:589–96.

    CAS  PubMed  Google Scholar 

  7. Luo P, Yin PY, Hua R, Tan YX, Li ZF, Qiu GK, et al. A large-scale, multicenter serum metabolite biomarker identification study for the early detection of hepatocellular carcinoma. Hepatology. 2018;67:662–75.

    Article  CAS  Google Scholar 

  8. Caviglia JM, Schwabe RF. Schwabe, mouse models of liver cancer. Methods Mol Biol. 2015;1267:165–83.

    Article  CAS  Google Scholar 

  9. Simonetti RG, Cammà C, Fiorello F, Politi F, D'Amico G, Pagliaro L. Hepatocellular carcinoma. A worldwide problem and the major risk factors. Dig Dis Sci. 1991;36:962–72.

    Article  CAS  Google Scholar 

  10. Nie CY, Han T, Zhang L, Li Y, Liu H, Xiao SX, et al. Cross-sectional and dynamic change of serum metabolite profiling for hepatitis B-related acute-on-chronic liver failure by UPLC/MS. J Viral Hepat. 2014;21:53–63.

    Article  CAS  Google Scholar 

  11. Yang YX, Li CL, Nie X, Feng XS, Chen WX, Yue Y, et al. Metabonomic studies of human hepatocellular carcinoma using high-resolution magic-angle spinning 1H NMR spectroscopy in conjunction with multivariate data analysis. J Proteome Res. 2007;6:2605–14.

    Article  CAS  Google Scholar 

  12. Kimhofer T, Fye H, Taylor-Robinson S, Thursz M, Holmes E. Proteomic and metabonomic biomarkers for hepatocellular carcinoma: a comprehensive review. Br J Cancer. 2015;112:1141–56.

    Article  CAS  Google Scholar 

  13. Tavallaie R, De Almeida SR, Gooding JJ. Toward biosensors for the detection of circulating microRNA as a cancer biomarker: an overview of the challenges and successes. Wiley Interdiscip Rev Nanomed Nanobiotechnol. 2015;7:580–92.

    Article  CAS  Google Scholar 

  14. Liang Q, Liu H, Wang C, Li BB. Phenotypic characterization analysis of human Hepatocarcinoma by urine metabolomics approach. Sci Rep. 2016;6:19763.

    Article  CAS  Google Scholar 

  15. Shariff MI, Gomaa AI, Cox IJ, Patel M, Williams HR, Crossey MM, et al. Urinary metabolic biomarkers of hepatocellular carcinoma in an Egyptian population: a validation study. J Proteome Res. 2011;10:1828–36.

    Article  CAS  Google Scholar 

  16. Chen TL, Xie GX, Wang XY, Fan J, Qiu YP, Zheng XJ, et al. Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma. Mol Cell Proteomics. 2011;10:M110.004945.

    Article  Google Scholar 

  17. Gao HC, Lu Q, Liu X, Cong H, Zhao LC, Wang HM, et al. Application of 1H NMR-based metabonomics in the study of metabolic profiling of human hepatocellular carcinoma and liver cirrhosis. Cancer Sci. 2009;100:782–5.

    Article  CAS  Google Scholar 

  18. Liu Y, Hong ZY, Tan GG, Dong X, Yang GJ, Zhao L, et al. NMR and LC/MS-based global metabolomics to identify serum biomarkers differentiating hepatocellular carcinoma from liver cirrhosis. Int J Cancer. 2014;135:658–68.

    Article  CAS  Google Scholar 

  19. Casadei-Gardini A, Del Coco L, Marisi G, Conti F, Rovesti G, Ulivi P, et al. (1)H-NMR based serum metabolomics highlights different specific biomarkers between early and advanced hepatocellular carcinoma stages. Cancers (Basel). 2020;12:241.

    Article  CAS  Google Scholar 

  20. Carloni V, Lulli M, Madiai S, Mello T, Hall A, Luong TV, et al. CHK2 overexpression and mislocalisation within mitotic structures enhances chromosomal instability and hepatocellular carcinoma progression. Gut. 2018;67:348–61.

    Article  CAS  Google Scholar 

  21. Wang KX, Du GH, Qin XM, Gao L. Compound Kushen injection intervenes metabolic reprogramming and epithelial-mesenchymal transition of HCC via regulating β-catenin/c-Myc signaling. Phytomedicine. 2021;153781:93.

    Google Scholar 

  22. Beyoğlu D, Imbeaud S, Maurhofer O, Bioulac-Sage P, Zucman-Rossi J, Dufour JF, et al. Tissue metabolomics of hepatocellular carcinoma: tumor energy metabolism and the role of transcriptomic classification. Hepatology. 2013;58:229–38.

    Article  Google Scholar 

  23. Van der Sluis R, Ungerer V, Nortje C. A, van Dijk A, Erasmus E. New insights into the catalytic mechanism of human glycine N-acyltransferase. J Biochem Mol Toxicol. 2017;31:11.

  24. Coude FX, Coude M, Grimber G, Pelet A, Charpentier C. Potentiation by piridoxilate of the synthesis of hippurate from benzoate in isolated rat hepatocytes. An approach to the determination of new pathways of nitrogen excretion in inborn errors of urea synthesis. Clin Chim Acta. 1984;136:211–7.

    Article  CAS  Google Scholar 

  25. Papalazarou V, Zhang T, Paul NR, Juin A, Cantini M, Maddocks ODK, et al. The creatinine-phosphagen system is mechanoresponsive in pancreatic adenocarcinoma and fuels invasion and metastasis. Nat Metab. 2020;2:62–80.

    Article  CAS  Google Scholar 

  26. Bardócz S, Grant G, Brown DS, Ralph A, Pusztai A. Polyamines in food-implications for growth and health. J Nutr Biochem. 1993;4:66–71.

    Article  Google Scholar 

  27. Wang J, Zhang S, Li ZF, Yang J, Huang C, Liang RR, et al. (1)H-NMR-based metabolomics of tumor tissue for the metabolic characterization of rat hepatocellular carcinoma formation and metastasis. Tumour Biol. 2011;32:223–31.

    Article  Google Scholar 

  28. Skill NJ, Scott RE, Wu J, Maluccio MA. Hepatocellular carcinoma associated lipid metabolism reprogramming. J Surg Res. 2011;169:51–6.

    Article  CAS  Google Scholar 

  29. Moreno A, Rey M, Montane JM, Alonso J, Arús C. 1H NMR spectroscopy of colon tumors and normal mucosal biopsies; elevated taurine levels and reduced polyethyleneglycol absorption in tumors may have diagnostic significance. NMR Biomed. 1993;6:111–8.

    Article  CAS  Google Scholar 

  30. Petrick JL, Florio AA, Koshiol J, Pfeiffer RM, Yang B, Yu K, et al. Prediagnostic concentrations of circulating bile acids and hepatocellular carcinoma risk: REVEAL-HBV and HCV studies. Int J Cancer. 2020;147:2743–53.

    Article  CAS  Google Scholar 

  31. Alves AP, Mamede AC, Alves MG, Oliveira PF, Rocha SM, Botelho MF, et al. Glycolysis inhibition as a strategy for hepatocellular carcinoma treatment? Curr Cancer Drug Targets. 2019;19:26–40.

    Article  CAS  Google Scholar 

  32. Mazurek S. Pyruvate kinase type M2: a key regulator within the tumour metabolome and a tool or metabolic profiling of tumours. Ernst Schering Found Symp Proc. 2007;4:99–124.

    Google Scholar 

  33. Buddington RK, Sangild PT. Companion animals symposium: development of the mammalian gastrointestinal tract, the resident microbiota, and the role of diet in early life. J Anim Sci. 2011;89:1506–19.

    Article  CAS  Google Scholar 

  34. Dyar KA, Lutter D, Artati A, Ceglia NJ, Liu Y, Armenta D, et al. Atlas of circadian metabolism reveals system-wide coordination and communication between clocks. Cell. 2018;174:1571–85.

    Article  CAS  Google Scholar 

Download references

Funding

This project was supported by the Base Program of Joint training graduate student of Shanxi Province (no. 2016JD05), Science and Technology Innovation Team of Shanxi Province (no. 201605D131045–18), and the Key laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, China (201705D111008–21).

Author information

Authors and Affiliations

Authors

Contributions

X.-M. Qin and L. Gao provided the concept and designed the study. K.-X. Wang performed the experiments and drafted the manuscript. K-X. Wang and L. Gao participated in data analysis. X.-M. Qin, G.-H. Du and L. Gao provided oversight. L. Gao contributed to revising and proofreading the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Xue-mei Qin or Li Gao.

Ethics declarations

Ethics approval

This study was approved in accordance with the ethical standards and approved by SXU Ethics Committee. All the recommendations in the National Institutes of Health Guidelines for Care and Use of Laboratory Animals were strictly followed in this study.

Conflict of interest

The authors have no conflicts of interest, either real or potential, associated with this work.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

ESM 1

(DOCX 990 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Kx., Du, Gh., Qin, Xm. et al. 1H-NMR-based metabolomics reveals the biomarker panel and molecular mechanism of hepatocellular carcinoma progression. Anal Bioanal Chem 414, 1525–1537 (2022). https://doi.org/10.1007/s00216-021-03768-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-021-03768-9

Keywords

Navigation