Skip to main content
Log in

Metabolomic profiling of human serum in lung cancer patients using liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry and gas chromatography/mass spectrometry

  • Original Article – Clinical Oncology
  • Published:
Journal of Cancer Research and Clinical Oncology Aims and scope Submit manuscript

Abstract

Purpose

Lung cancer is one of the most common causes of death from cancer. Serum markers that enable diagnosis of the disease in the early stage have not been found.

Methods

Serum samples were collected from 30 healthy volunteers and from 30 lung cancer patients preoperatively and postoperatively. Samples were subjected to metabolomic analysis using liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry and gas chromatography/mass spectrometry. Differences in metabolomic profiles among the three groups were characterized by multivariate statistical techniques such as principal components analysis and partial least squares discriminant analysis (PLS-DA). An independent t test was used to determine whether levels of biomarker candidates identified using PLS-DA modeling were significantly different among groups at the univariate analysis level (p < 0.05).

Results

Based on pattern recognition results and univariate analysis, we showed that levels of ten potential biomarkers in serum were significantly different in the preoperative lung cancer patients compared with healthy volunteers and/or the postoperative lung cancer patients. The levels of sphingosine, phosphorylcholine, glycerophospho-N-arachidonoyl ethanolamine, γ-linolenic acid, 9,12-octadecadienoic acid, oleic acid, and serine were significantly different in preoperative lung cancer patients compared to healthy volunteers and to postoperative lung cancer patients. For prasterone sulfate, α-hydroxyisobutyric acid, 2,3,4-trihydroxybutyric acid, the levels were statistically different in preoperative and postoperative lung cancer patients compared with the healthy volunteers.

Conclusions

Our study identified potential metabolic biomarkers for diagnosis of lung cancer.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • An ZL, Chen YH, Zhang RP, Song YM, Sun JH, He JM, Bai JF, Dong LJ, Zhan QM, Chan EC, Koh PK, Mal M, Cheah PY, Eu KW, Backshall A, Cavill R, Nicholson JK, Chen J, Wang W, Lv S, Yin P, Zhao X, Lu X, Zhang F, Xu G (2009) Metabonomics study of liver cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations. Anal Chim Acta 650(1):3–9

    Article  Google Scholar 

  • Cerne D, Zitnik IP, Sok M (2010) Increased fatty acid synthase activity in non-small cell lung cancer tissue is a weaker predictor of shorter patient survival than increased lipoprotein lipase activity. Arch Med Res 41(6):405–409

    Article  CAS  PubMed  Google Scholar 

  • Chen JH, Enloe BM, Fletcher CD, Cory DG, Singer S (2001) Biochemical analysis using high-resolution magic angle spinning NMR spectroscopy distinguishes lipoma-like well-differentiated liposarcoma from normal fat. J Am Chem Soc 123(37):9200–9201

    Article  CAS  PubMed  Google Scholar 

  • Chong IG, Jun CH (2005) Performance of some variable selection methods when multicollinearity is present. Chemom Intell Lab Syst 78(1–2):103–112

    Article  CAS  Google Scholar 

  • Gosetti F, Mazzucco E, Gennaro MC, Marengo E (2013) Ultra high performance liquid chromatography tandem mass spectrometry determination and profiling of prohibited steroids in human biological matrices. A review. J Chromatogr B Anal Technol Biomed Life Sci 15:22–36

    Article  Google Scholar 

  • Griffin JL, Kauppinen RA (2007) A metabolomics perspective of human brain tumours. FEBS J 274(5):1132–1139

    Article  CAS  PubMed  Google Scholar 

  • Hori S, Nishiumi S, Kobayashi K, Shinohara M, Hatakeyama Y, Kotani Y, Hatano N, Maniwa Y, Nishio W, Bamba T, Fukusaki E, Azuma T, Takenawa T, Nishimura Y, Yoshida M (2011) A metabolomic approach to lung cancer. Lung Cancer 74(2):284–292

    Article  PubMed  Google Scholar 

  • Jemal A, Siegel R, Ward E, Hao Y, Xu J, Thun MJ (2008) Cancer statistics. CA Cancer J Clin 58(2):71–96

    Article  PubMed  Google Scholar 

  • Kuhajda FP (2006) Fatty acid synthase and cancer: new application of an old pathway. Cancer Res 66(12):5977–5980

    Article  CAS  PubMed  Google Scholar 

  • Mashima T, Seimiya H, Tsuruo T (2009) De novo fatty-acid synthesis and related pathways as molecular targets for cancer therapy. Br J Cancer 100(9):1369–1372

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Niu YJ, Jiang YL, Xu CJ, Wang XY, Liu YR, Zhao H, Han BH, Jiang LY (2012) Preliminary results of metabolite in serum and urine of lung cancer patients detected by metabolomics. Zhongguo Fei Ai Za Zhi 15(4):195–201

    CAS  PubMed  Google Scholar 

  • Orita H, Coulter J, Lemmon C, Tully E, Vadlamudi A, Medghalchi SM, Kuhajda FP, Gabrielson E (2007) Selective inhibition of fatty acid synthase for lung cancer treatment. Clin Cancer Res 13(23):7139–7145

    CAS  PubMed  Google Scholar 

  • Pasikanti KK, Ho PC, Chan EC (2008) Gas chromatography/mass spectrometry in metabolic profiling of biological fluids. J Chromatogr B Anal Technol Biomed Life Sci 871(2):202–211

    Article  CAS  Google Scholar 

  • Pirozynski M (2006) 100 years of lung cancer. Respir Med 100:2073–2084

    Article  PubMed  Google Scholar 

  • Postic C, Dentin R, Girard J (2004) Role of the liver in the control of carbohydrate and lipid homeostasis. Diabetes Metab 30(5):398–408

    Article  CAS  PubMed  Google Scholar 

  • Preter VD, Verbeke K (2013) Metabolomics as a diagnostic tool in gastroenterology. World J Gastrointest Pharmacol Ther 4(4):97–107

    PubMed Central  PubMed  Google Scholar 

  • Saddoughi SA, Song P (2008) Ogretmen B. Roles of bioactive sphingolipids in cancer biology and therapeutics. Subcell Biochem 49:413–440

    Article  PubMed Central  PubMed  Google Scholar 

  • Schwartz AG, Prysak GM, Bock CH, Cote ML (2007) The molecular epidemiology of lung cancer. Carcinogenesis 28(3):507–518

    Article  CAS  PubMed  Google Scholar 

  • Swanson MG, Zektzer AS, Tabatabai ZL, Simko J, Jarso S, Keshari KR, Schmitt L, Carroll PR, Shinohara K, Vigneron DB, Kurhanewicz J (2006) Quantitative analysis of prostate metabolites using 1H HR-MAS spectroscopy. Magn Reson Med 55(6):1257–1264

    Article  CAS  PubMed  Google Scholar 

  • Uddin S, Jehan Z, Ahmed M, Alyan A, Ai-Dayel F, Hussain A, Bavi P, Ai-Kuiaya KS (2011) Overexpression of fatty acid synthase in middle eastern epithelial ovarian carcinoma activates AKT and its inhibition potentiates cisplatin-induced apoptosis. Mol Med 17(7–8):635–645

    PubMed Central  CAS  PubMed  Google Scholar 

  • Watanabe J, Ishihara K (2008) Establishing ultimate biointerfaces covered with phosphorylcholine groups. Colloid Surf B Biointerfaces 65(2):155–165

    Article  CAS  Google Scholar 

  • Yu YY, Pinsky PF, Caporaso NE, Chatterjee N, Baumgarten M, Langenberg P, Furuno JP, Lan Q, Engels EA (2008) Lung cancer risk following detection of pulmonary scarring by chest radiography in the prostate, lung, colorectal, and ovarian cancer screening trial. Arch Intern Med 168(21):2326–2332

    Article  PubMed Central  PubMed  Google Scholar 

  • Yu XW, Wu Q, Lv W, Wang Y, Ma XQ, Chen Z, Yan C (2013) Metabonomics study of lung cancer cells based on liquid chromatography–mass spectrometry. Chin J Chromosom 31(7):691–696

    CAS  Google Scholar 

Download references

Acknowledgments

Financial support from Zhejiang Province Department of Science and Technology (2011C23131) is gratefully acknowledged.

Conflict of interest

None.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Licheng Dai.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Ma, Z., Li, A. et al. Metabolomic profiling of human serum in lung cancer patients using liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry and gas chromatography/mass spectrometry. J Cancer Res Clin Oncol 141, 705–718 (2015). https://doi.org/10.1007/s00432-014-1846-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00432-014-1846-5

Keywords

Navigation