JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES)

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Classification and diagnostic prediction of lung cancer using protein profiling of serum and bioinformatics

HAN Ming-yong1, LIU Qi1, YU Jie-kai2, ZHENG Shu2   

  1. 1. Cancer Center, Provincial Hospital Affiliated to Shandong University, Jinan 250021, China; 2. Institute of Cancer, Zhejiang University
  • Received:2008-01-17 Revised:1900-01-01 Online:2008-06-16 Published:2008-06-16
  • Contact: LIU Qi

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Abstract: To identify serum biomarkers that distinguish lung cancer from healthy individuals by protein fingerprint pattern. Methods86 lung cancer patients and 80 healthy controls were determined by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Results4 protein peaks were selected and used by artificial neural network (ANN) to establish a diagnostic model. The specificity of the diagnostic pattern was 100% and sensitivity of the pattern was 93.6％. ConclusionsA diagnostic model of lung cancer was successfully established, which has high sensitivity and specificity.

Key words: Lung neoplasms, Surface enhanced laser desorption/ionization timeofflight mass spectrometry, Bioinformatics, Diagnosis, Proteomics

CLC Number: 

  • R322.81
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