BACKGROUND/AIMS: Molecular diagnostic methods have enabled the rapid diagnosis of drug-resistant mutations in hepatitis B virus (HBV) and have reduced both unnecessary therapeutic interventions and medical costs. In this study we evaluated the analytical and clinical performances of the HepB Typer-Entecavir kit (GeneMatrix, Korea) in detecting entecavir-resistance-associated mutations. METHODS: The HepB Typer-Entecavir kit was evaluated for its limit of detection, interference, cross-reactivity, and precision using HBV reference standards made by diluting high-titer viral stocks in HBV-negative human serum. The performance of the HepB Typer-Entecavir kit for detecting mutations related to entecavir resistance was compared with direct sequencing for 396 clinical samples from 108 patients. RESULTS: Using the reference standards, the detection limit of the HepB Typer-Entecavir kit was found to be as low as 500 copies/mL. No cross-reactivity was observed, and elevated levels of various interfering substances did not adversely affect its analytical performance. The precision test conducted by repetitive analysis of 2,400 replicates with reference standards at various concentrations showed 99.9% agreement (2398/2400). The overall concordance rate between the HepB Typer-Entecavir kit and direct sequencing assays in 396 clinical samples was 99.5%. CONCLUSIONS: The HepB Typer-Entecavir kit showed high reliability and precision, and comparable sensitivity and specificity for detecting mutant virus populations in reference and clinical samples in comparison with direct sequencing. Therefore, this assay would be clinically useful in the diagnosis of entecavir-resistance-associated mutations in chronic hepatitis B.
Adult ; Antiviral Agents/*therapeutic use ; Cross Reactions ; DNA, Viral/blood/standards ; Drug Resistance, Viral/*genetics ; Genotype ; Guanine/*analogs & derivatives/therapeutic use ; Hepatitis B virus/genetics ; Hepatitis B, Chronic/*drug therapy/genetics ; Humans ; Mutation ; Polymerase Chain Reaction/standards ; Reagent Kits, Diagnostic/*standards ; Reference Standards ; Sequence Analysis, DNA ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/standards

OBJECTIVETo establish the diagnostic model of cerebrospinal protein profile for gliomas by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) and bioinformatics.

METHODSSeventy-five samples of cerebrospinal fluid from patients with gliomas, benign brain tumors and mild brain traumas were collected. A total of 50 samples from gliomas and non-brain-tumors were divided into training sets (33 cases including 17 gliomas and 16 non-brain-tumors) and testing sets (17 cases including 5 gliomas and 12 non-brain-tumors). The cerebrospinal proteins bound to H4 chip were detected by SELDI-TOF MS, the profiles of cerebrospinal protein were gained and then analyzed with artificial neural network algorithm (ANN); and the diagnostic model of cerebrospinal protein profiles for differentiating gliomas from non-brain-tumors was established. Forty-seven of cerebrospinal samples of gliomas and benign brain tumors were divided into training sets (31 cases including 13 gliomas and 18 benign brain tumors) and testing sets (16 cases including 9 gliomas and 7 benign brain tumors), the diagnostic model of cerebrospinal protein profiles for differentiating gliomas from benign brain tumors was established based on the same method. The support vector machine (SVM) algorithm was also used for evaluation, both results were very similar, but the result derived from ANN was more stable than that from SVM.

RESULTThe diagnostic model of cerebrospinal protein profiles for differentiating gliomas from non-brain-tumors was established and was challenged with the test set randomly, the sensitivity and specificity were 100% and 91.7%, respectively. The cerebrospinal protein profiling model for differentiating gliomas from benign brain tumors was also developed and was challenged with the test set randomly, the sensitivity and specificity were 88.9%, and 100%, respectively.

CONCLUSIONThe technology of SELDI-TOF MS which combined with analysis tools of bioinformatics is a novel effective method for screening and identifying tumor biomarkers of gliomas and it may provide a new approach for the clinical diagnosis of glioma.

Adult ; Aged ; Algorithms ; Biomarkers, Tumor ; Brain Neoplasms ; cerebrospinal fluid ; diagnosis ; Cerebrospinal Fluid Proteins ; genetics ; Diagnosis, Differential ; Female ; Glioma ; cerebrospinal fluid ; diagnosis ; Humans ; Male ; Meningioma ; cerebrospinal fluid ; diagnosis ; Middle Aged ; Neural Networks (Computer) ; Peptide Mapping ; standards ; Sensitivity and Specificity ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization