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Identification of Serum Biomarkers for Biliary Tract Cancers by a Proteomic Approach Based on Time-of-Flight Mass Spectrometry

Biliary tract cancers (BTCs) are lethal malignancies currently lacking satisfactory methods for early detection and accurate diagnosis. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is a promising diagnostic tool for this disease. In this pilot study, s...

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Detalles Bibliográficos
Autores principales: Wang, Wen-Jing, Xu, Wang-Hong, Liu, Cha-Zhen, Rashid, Asif, Cheng, Jia-Rong, Liao, Ping, Hu, Heng, Chu, Lisa W., Gao, Yu-Tang, Yu, Kai, Hsing, Ann W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3837325/
https://www.ncbi.nlm.nih.gov/pubmed/24281176
http://dx.doi.org/10.3390/cancers2031602
Descripción
Sumario:Biliary tract cancers (BTCs) are lethal malignancies currently lacking satisfactory methods for early detection and accurate diagnosis. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is a promising diagnostic tool for this disease. In this pilot study, sera samples from 50 BTCs and 30 cholelithiasis patients as well as 30 healthy subjects from a population-based case-control study were randomly grouped into training set (30 BTCs, 20 cholelithiasis and 20 controls), duplicate of training set, and blind set (20 BTCs, 10 cholelithiasis and 10 controls); all sets were analyzed on Immobilized Metal Affinity Capture ProteinChips via SELDI-TOF-MS. A decision tree classifier was built using the training set and applied to all test sets. The classification tree constructed with the 3,400, 4,502, 5,680, 7,598, and 11,242 mass-to-charge ratio (m/z) protein peaks had a sensitivity of 96.7% and a specificity of 85.0% when comparing BTCs with non-cancers. When applied to the duplicate set, sensitivity was 66.7% and specificity was 70.0%, while in the blind set, sensitivity was 95.0% and specificity was 75.0%. Positive predictive values of the training, duplicate, and blind sets were 82.9%, 62.5% and 79.2%, respectively. The agreement of the training and duplicate sets was 71.4% (Kappa = 0.43, u = 3.98, P < 0.01). The coefficient of variations based on 10 replicates of one sample for the five differential peaks were 15.8–68.8% for intensity and 0–0.05% for m/z. These pilot results suggest that serum protein profiling by SELDI-TOF-MS may be a promising approach for identifying BTCs but low assay reproducibility may limit its application in clinical practice.