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Annals of Surgical Oncology

, Volume 21, Supplement 4, pp 736–742 | Cite as

Noninvasive Diagnosis and Evaluation of Curative Surgery for Gastric Cancer by Using NMR-based Metabolomic Profiling

  • Jeeyoun Jung
  • Youngae Jung
  • Eun Jung Bang
  • Sung-il Cho
  • You-Jin Jang
  • Jung-Myun Kwak
  • Do Hyun Ryu
  • Sungsoo Park
  • Geum-Sook Hwang
Translational Research and Biomarkers

Abstract

Background

Mass screening for gastric cancer (GC), particularly using endoscopy, may not be the most practical approach as a result of its high cost, lack of acceptance, and poor availability. Thus, novel markers that can be used in cost-effective diagnosis and noninvasive screening for GC are needed.

Methods

A total of 154 urine samples from GC patients and healthy individuals and 30 pairs of matched tumor and normal stomach tissues were collected. Multivariate analysis was performed on urinary and tissue metabolic profiles acquired using 1H nuclear magnetic resonance and 1H high-resolution magic angle spinning spectroscopy, respectively. In addition, metabolic profiling of urine from GC patients after curative surgery was performed.

Results

Multivariate statistical analysis showed significant separation in the urinary and tissue data of GC patients and healthy individuals. The metabolites altered in the urine of GC patients were related to amino acid and lipid metabolism, consistent with changes in GC tissue. In the external validation, the presence of GC (early or advanced) from the urine model was predicted with high accuracy, which showed much higher sensitivity than carbohydrate antigen 19-9 and carcinoembryonic antigen. Furthermore, 4-hydroxyphenylacetate, alanine, phenylacetylglycine, mannitol, glycolate, and arginine levels were significantly correlated with cancer T stage and, together with hypoxanthine level, showed a recovery tendency toward healthy controls in the postoperative samples compared to the preoperative samples.

Conclusions

An urinary metabolomics approach may be useful for the effective diagnosis of GC.

Keywords

Gastric Cancer Nuclear Magnetic Resonance Gastric Cancer Patient Gastric Cancer Tissue Urinary Metabolic Profile 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

This work was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning, Korea (2010-0024825, NRF-2010-0019394, 2013M3A9B6046418, and Creative Allied Project (CAP)), the Korea Institute of Oriental Medicine (K14281), and the Korea Basic Science Institute (T33409).

Disclosure

The authors declare no conflict of interest.

Supplementary material

10434_2014_3886_MOESM1_ESM.doc (2.4 mb)
Supplementary material 1 (DOC 2481 kb)

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Copyright information

© Society of Surgical Oncology 2014

Authors and Affiliations

  • Jeeyoun Jung
    • 1
    • 2
  • Youngae Jung
    • 1
  • Eun Jung Bang
    • 1
  • Sung-il Cho
    • 3
  • You-Jin Jang
    • 3
  • Jung-Myun Kwak
    • 3
  • Do Hyun Ryu
    • 4
  • Sungsoo Park
    • 3
  • Geum-Sook Hwang
    • 1
  1. 1.Integrated Metabolomics Research Group, Western Seoul CenterKorea Basic Science InstituteSeoulRepublic of Korea
  2. 2.KM Health Technology Research GroupKorea Institute of Oriental MedicineDaejeonRepublic of Korea
  3. 3.Department of Surgery, College of MedicineKorea UniversitySeoulRepublic of Korea
  4. 4.Department of ChemistrySungkyunkwan UniversitySuwonRepublic of Korea

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