The contribution for the diagnosis of the tumor-like polypoid lesions of the gallbladder by SELDI-TOF-MS / 中华外科杂志

<p><b>OBJECTIVE</b>To detect the serum specific proteins in tumor-like polypoid lesions of the gallbladder patients and establish diagnostic model.</p><p><b>METHODS</b>Surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) technique and WCX Magnetic Beads were used to detect the serum proteomic patterns of 23 patients with tumor-like PLG, 21 patients with non tumor-like PLG and 26 normal persons. Biomarker Wizard and Biomarker Patterns Software were used in combination to analyze the data.</p><p><b>RESULTS</b>Preliminary screening out 22 representative specific proteins for the diagnosis of the tumor-like PLG. Analysis system under the conditions set selected 3 specific proteins to establish diagnostic model for the tumor-like PLG. The sensitivity and specificity of the model for the diagnosis of the tumor-like PLG were 100% and 89.4%, respectively.</p><p><b>CONCLUSION</b>SELDI-TOF-MS technique can select specific protein of the tumor-like PLG, and establish diagnostic model of the tumor-like PLG.</p>

Establishment of serum protein pattern model for screening pancreatic cancers by SELDI-TOF-MS technique / 中华外科杂志

<p><b>OBJECTIVE</b>To detect the serum specific proteins in pancreatic cancer patients and establish diagnostic model by surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) technique.</p><p><b>METHODS</b>Twenty-nine serum samples from patients of pancreatic cancer were collected before surgery and an additional 57 serum samples from age and sex matched individuals without cancer were used as controls, SELDI-TOF-MS technique and WCX magnetic beads were used to detect the protein fingerprint expression of all the serum samples and the resulting profiles between pancreatic cancer patients and controls were analyzed with biomarker wizard system, established the model using biomarker patterns system software. A double-blind test was used to determine the sensitivity and specificity of the classification model.</p><p><b>RESULTS</b>A panel of four biomarkers (relative molecular weight are 5705, 4935, 5318 and 3243 Da) were selected to set up a decision trees as the classification model for screening pancreatic cancer effectively. The result yielded a sensitivity of 100%, specificity of 97.4%. The double-blind test challenged the model with a sensitivity of 88.9% and a specificity of 89.5%.</p><p><b>CONCLUSIONS</b>SELDI-TOF-MS offers a unique platform for the proteomic detection of serum in pancreatic cancer patients. It also offers a noninvasive method to further study the proteomic changes in the development and progression of pancreatic cancer.</p>