Application of serum protein fingerprint in diagnosis of pancreatic cancer / 浙江大学学报·医学版

ABSTRACT

<p><b>OBJECTIVE</b>To establish serum protein fingerprint model for early diagnosis of pancreatic cancer with surface enhanced laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS) and bioinformatics techniques.</p><p><b>METHODS</b>A total of 73 samples were analyzed in this study, including 31 cases of pancreatic cancers, 22 cases of pancreatitis and 20 healthy individuals. Samples were first analyzed by SELDI-TOF-MS and two patterns of differentiation model were constructed with support vector machine arithmetic method.</p><p><b>RESULTS</b>The pattern 1 model differentiating pancreatic cancer patients from healthy individuals had a specificity and a sensitivity of both 100.0%. The pattern 2 model differentiating pancreatic cancer from pancreatitis had a specificity of 95.5% and a sensitivity of 93.5%.</p><p><b>CONCLUSION</b>SELDI-TOF-MS technique combined with bioinformatics can facilitate to identify biomarkers for pancreatic cancer.</p>