Research on Patterns of Cancer Markers Based on Cross Section Imaging of Serum Proteomic Data

  • Wenxue Hong
  • Hui Meng
  • Liqiang Wang
  • Jialin Song
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4681)


New proteomic technologies have brought the hope of discovering novel early cancer-specific biomarkers in complex biological samples. Novel mass spectrometry (MS) based technologies in particular, such as surface-enhanced laser desorption/ionisation time of flight (SELDI-TOF-MS), have shown promising results in recent years. To find new potential biomarkers and establish the patterns for detection of cancers, we proposed a novel method to analysis SELDI-TOF-MS using binary cross section imaging and energy curve technology. The proposed method with advantage of visualization is to mining local information adequately so as to discriminate cancer samples from non-cancer ones. Applying the procedure to MS data of proteomic analysis of serum from ovarian cancer patients and serum from cancer-free individuals in the Food and Drug Administration/National Cancer Institute Clinical Proteomics Database, we find that there are outputs of the cancerous when the threshold is above 90 and M/Z is in the range 9362.3296-9747.2723, while outputs of the non-cancerous will appear when the threshold is 60 80 and M/Z is 243.4940-247.8824.


Prostate Cancer Ovarian Cancer Binary Image Ovarian Cancer Patient Cancer Marker 
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.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Wenxue Hong
    • 1
  • Hui Meng
    • 1
  • Liqiang Wang
    • 1
  • Jialin Song
    • 1
  1. 1.Department of Biomedical Engineering, Yanshan University, Qinhuangdao, Hebei, 066004China

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