Taiwanese Journal of Obstetrics and Gynecology
Volume 45, Issue 1 , Pages 26-32, March 2006

Seldi-tof MS Profiling of Plasma Proteins in Ovarian Cancer

  • Shao-Pai Wu

      Affiliations

    • Department of Obstetrics and Gynecology, Army Forces Tao-Yuan General Hospital, Tao-Yuan, Taipei, Taiwan
    • ,
  • Ya-Wen Lin

      Affiliations

    • Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
    • ,
  • Hung-Cheng Lai

      Affiliations

    • Department of Obstetrics and Gynecology, Tri-Service General Hospital, Taipei, Taiwan
    • ,
  • Tang-Yuan Chu

      Affiliations

    • Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
    • Department of Obstetrics and Gynecology, Tri-Service General Hospital, Taipei, Taiwan
    • ,
  • Yu-Liang Kuo

      Affiliations

    • Department of Obstetrics and Gynecology, Army Forces Tao-Yuan General Hospital, Tao-Yuan, Taipei, Taiwan
    • ,
  • Hang-Seng Liu

      Affiliations

    • Department of Obstetrics and Gynecology, Army Forces Tao-Yuan General Hospital, Tao-Yuan, Taipei, Taiwan
    • Corresponding Author InformationCorrespondence to: Dr. Hang-Seng Liu, Department of Obstetrics and Gynecology, Army Forces Tao-Yuan General Hospital, 168 Chong-Shin Road, Lungtan Tao-Yuan County 325, Taiwan

Received 14 July 2005; received in revised form 19 July 2005; accepted 19 July 2005.

Article Outline

Summary 

Objective

Proteomic profiling of plasma or serum is a technique to identify new biomarkers in disease. The objective of this study was to identify new plasma biomarkers in ovarian cancer patients using mass spectrometry protein profiling and artificial intelligence.

Methods

A total of 65 plasma samples obtained from women with ovarian cancer (n = 35) and age-matched disease-free controls (n = 30) were applied to anion exchange protein chips for protein profiling by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS).

Results

SELDI-TOF MS was highly reproducible in detecting ovarian tumor-specific protein profiles. One protein peak (relative molecular mass, Mr, 11,537 Da) was identified in plasma from women with ovarian cancer but not in controls. Two peaks, Mr 5,147 and 8,780 Da, were present in the plasma of controls but not of women with ovarian cancer. After a training analysis, classification analysis generated by univariant or linear combination split was performed to reach a discriminant protein signature pattern. After cross validation, a sensitivity of 84% and specificity of 89% for all studied cases and controls was reached.

Conclusion

This study clearly demonstrates that the combined technology of SELDI-TOF MS and artificial intelligence is effective in distinguishing protein expression between normal and ovarian cancer plasma. The identified protein peaks may be candidate proteins for early detection of ovarian cancer or evaluation of therapeutic response.

Key Words:  protein chip , ovarian cancer , SELDI-TOF mass spectrometry

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PII: S1028-4559(09)60186-8

doi:10.1016/S1028-4559(09)60186-8

Taiwanese Journal of Obstetrics and Gynecology
Volume 45, Issue 1 , Pages 26-32, March 2006

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