Research on Patterns of Cancer Markers Based on Cross Section Imaging of Serum Proteomic Data
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.
KeywordsProstate Cancer Ovarian Cancer Binary Image Ovarian Cancer Patient Cancer Marker
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