Novel HRPT2/CDC73 Gene Mutations and Loss of Expression of Parafibromin in Chinese Patients with Clinically Sporadic Parathyroid Carcinomas

Objective

It is widely recognized that the diagnosis of parathyroid carcinoma (PC) is often difficult because of the overlap of characteristics between malignant and benign parathyroid tumors, especially at an early stage. Based on the identification of tumor suppressor gene HRPT2/CDC73 and its association with hereditary and sporadic PC, screening of gene mutations and detection of parafibromin immunoreactivity have been suggested as diagnostic instruments of PC in Whites. There is little information about HRPT2/CDC73 mutations and its corresponding protein expression in patients with sporadic PC in Chinese population, and the long-term follow-up data is scarce.

Methods

Paraffin-embedded tissues were obtained from 13 patients with PC, 13 patients with parathyroid adenoma (PA) and 7 patients with parathyroid hyperplasia(PH), and 6 normal parathyroid (NP) tissues as controls. Peripheral blood from 11 patients with PC was collected. PCR products using Genomic DNA extracted from tumor tissues or blood as template was sequenced for HRPT2/CDC73 gene. Expression of parafibromin in tumor tissues was evaluated by immunohistochemical analysis.

Results

Six mutations in 6 of 13 patients with PC were identified, with three being novel. Four of them were germ-line mutations. Patients with mutations were susceptible to recurrence of the PC. Complete (8/13, 61.5%) or partial (5/13, 38.5%) loss of parafibromin expression was observed in PC tissues. All of tissue samples from normal parathyroid or benign parathyroid tumors displayed positive immunostaining of parafibromin except one adenoma.

Conclusions

The present study supplies information on the mutations and protein expression of HRPT2/CDC73 gene and phenotypes of parathyroid carcinoma in Chinese population. And the expanded mutation database of this gene may benefit patients in the diagnosis and treatment of this disease.     

A method for handling metabonomics data from liquid chromatography/mass spectrometry: combinational use of support vector machine recursive feature elimination, genetic algorithm and random forest for feature selection

Metabolic markers are the core of metabonomic surveys. Hence selection of differential metabolites is of great importance for either biological or clinical purpose. Here, a feature selection method was developed for complex metabonomic data set. As an effective tool for metabonomics data analysis, support vector machine (SVM) was employed as the basic classifier. To find out meaningful features effectively, support vector machine recursive feature elimination (SVM-RFE) was firstly applied. Then, genetic algorithm (GA) and random forest (RF) which consider the interaction among the metabolites and independent performance of each metabolite in all samples, respectively, were used to obtain more informative metabolic difference and avoid the risk of false positive. A data set from plasma metabonomics study of rat liver diseases developed from hepatitis, cirrhosis to hepatocellular carcinoma was applied for the validation of the method. Besides the good classification results for 3 kinds of liver diseases, 31 important metabolites including lysophosphatidylethanolamine (LPE) C16:0, palmitoylcarnitine, lysophosphatidylethanolamine (LPC) C18:0 were also selected for further studies. A better complementary effect of the three feature selection methods could be seen from the current results. The combinational method also represented more differential metabolites and provided more metabolic information for a “global” understanding of diseases than any single method. Further more, this method is also suitable for other complex biological data sets.     

Ultrasound Pretreatment Increases the Bioavailability of Dietary Proteins by Dissociating Protein Structure and Composition

Food Biophysics - Bioavailability is an important indicator for evaluating the nutritional value of protein. In this study, we investigated the effect of ultrasound on improving the bioavailability...     

A one‐pot process for synthesis of mitomycin analogs catalyzed by laccase/lipase optimized by response surface methodology

To reach the excellent yield as well as environmental friendliness, an efficient one‐pot process for the synthesis of 2‐methyl‐3‐n‐butylaminoyl‐1,4‐benzoquinone, a mitomycin‐like compound by the domino reaction of 2‐methyl‐1,4‐hydroquinone and butylamine using laccase/lipase as co‐catalysts, has been developed. In this present study, the process proposed here was further improved by optimizing the relevant factors using the response surface methodology based on Box–Benkhen Design. The optimum condition that afforded the highest yield (98%) of 2‐methyl‐3‐n‐butylaminoyl‐1,4‐benzoquinone was obtained as follows: molar ratio of amines to hydroquinones 1.16:1, activity ratio of laccase to lipase 1.14:2, and reaction temperature 38.9°C. The results obtained indicate that this process may be useful as a green alternative method for higher yield production of mitomycin analogs.