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To screen and evaluate protein biomarkers for the detection of gliomas(Astrocytoma grade Ⅰ-Ⅳ) from healthy in-dividuals and gliomas from brain benign tumors by using surface enhanced laser desorption/ionization time of flight mass spec-trometry(SELDI-TOF-MS)coupled with an artificial neural network(ANN)algorithm.SELDI-TOF-MS protein fingerprinting ofserum from 105 brain tumor patients and healthy individuals,included 28 patients with glioma(Astrocytoma Ⅰ-Ⅳ),37 patientswith brain benign tumor,and 40 age-matched healthy individuals.Two thirds of the total samples of every compared pair as trainingset were used to set up discriminating patterns,and one third of total samples of every compared pair as test set were used tocross-validate;simultaneously,discriminate-cluster analysis derived SPSS 10.0 software was used to compare Astrocytoma gradeⅠ-Ⅱ with grade Ⅲ-Ⅳ ones.An accuracy of 95.7%,sensitivity of 88.9%,specificity of 100%,positive predictive value of 90% andnegative predictive value of 100% wer
To screen and evaluate protein biomarkers for the detection of gliomas (Astrocytoma grade I-IV) from healthy in-dividuals and gliomas from brain benign tumors by using surface enhanced laser desorption / ionization time of flight mass spec-trometry (SELDI-TOF-MS ) coupled with an artificial neural network (ANN) algorithm. SELDI-TOF-MS protein fingerprinting of serum from 105 brain tumor patients and healthy individuals, 28 patients with glioma (Astrocytoma I-IV), 37 patients with brain benign tumor, and 40 age -matched healthy individuals. Two thirds of the total samples of each compared pair as training set were used to set up discriminating patterns, and one third of total samples of every compared pair as test set were used tocross-validate; simultaneously, discriminate-cluster analysis derived SPSS 10.0 software was used to compare Astrocytoma grade I-II with grade III-IV ones. An accuracy of 95.7%, sensitivity of 88.9%, specificity of 100%, positive predictive value of 90% and negative p redictive value of 100% wer