Proteomic Profiling of Thyroid Papillary Carcinoma

Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy. We performed shotgun liquid chromatography (LC)/tandem mass spectrometry (MS/MS) analysis on pooled protein extracts from patients with PTC and compared the results with those from normal thyroid tissue validated by real-time (RT) PCR and immunohistochemistry (IHC). We detected 524 types of protein in PTC and 432 in normal thyroid gland. Among these proteins, 145 were specific to PTC and 53 were specific to normal thyroid gland. We have also identified two important new markers, nephronectin (NPNT) and malectin (MLEC). Reproducibility was confirmed with several known markers, but the one of two new candidate markers such as MLEC did not show large variations in expression levels. Furthermore, IHC confirmed the overexpression of both those markers in PTCs compared with normal surrounding tissues. Our protein data suggest that NPNT and MLEC could be a characteristic marker for PTC

Comparison of positive rates between glutamic acid decarboxylase antibodies and ElisaRSR™ 3 Screen ICA™ in recently obtained sera from patients who had been previously diagnosed with slowly progressive type 1 diabetes

Abstract Aims/Introduction This study aimed to compare the positivity rates of glutamic acid decarboxylase autoantibodies (GADA) and ElisaRSR™ 3 Screen ICA™ (3 Screen ICA), a newly developed assay for the simultaneous measurement of GADA, insulinoma‐associated antigen‐2 autoantibodies (IA‐2A), and zinc transporter 8 autoantibodies (ZnT8A), in recently obtained sera from patients who had been previously diagnosed with slowly progressive type 1 diabetes (SPIDDM). Materials and Methods We enrolled 53 patients with SPIDDM who were positive for GADA at the diagnosis and 98 non‐diabetic individuals, and investigated the diagnostic accuracy of the 3 Screen ICA (cutoff index ≥30 units) compared with that of GADA. In addition, we compared the clinical characteristics of patients with SPIDDM who were negative or positive on 3 Screen ICA. Results The positivity rates of 3 Screen ICA, GADA, IA‐2A, and ZnT8A were 88.7, 86.8, 24.5, and 13.2%, respectively. The respective sensitivity, specificity, and positive and negative predictive values for SPIDDM were 88.7, 100, 100, and 94.2% by 3 Screen ICA and 86.8, 100, 100.0, and 93.3% by GADA. There were no significant differences in age at onset, duration of diabetes, body mass index, glycated hemoglobin and C‐peptide levels, and the prevalence of autoimmune thyroiditis between patients with SPIDDM who were positive or negative on 3 Screen ICA. However, the prevalence of insulin users was significantly higher in those who were positive than in those who were negative on 3 Screen ICA. Conclusions Similar to GADA, 3 Screen ICA may be a useful diagnostic tool for detecting patients with SPIDDM