Prognostic significance of hypoxia-inducible factor-1α expression in advanced pharyngeal cancer without human papillomavirus infection.

OBJECTIVE: This study aimed to clarify the association between both hypoxia-inducible factor-1α and glucose transporter type-1 expression and survival outcome in advanced pharyngeal cancer without human papillomavirus infection. METHOD: Twenty-five oropharyngeal and 55 hypopharyngeal cancer patients without human papillomavirus infection were enrolled. All patients had stage III-IV lesions and underwent concurrent chemoradiotherapy or surgery. Hypoxia-inducible factor-1α and glucose transporter type-1 expression were investigated in primary lesions by immunohistochemistry. RESULTS: There were 41 and 39 cases with low and high hypoxia-inducible factor-1α expression, and 28 and 52 cases with low and high glucose transporter type-1 expression, respectively. There was no significant correlation between hypoxia-inducible factor-1α and glucose transporter type-1 expression. In univariate analysis, nodal metastasis, clinical stage and high hypoxia-inducible factor-1α expression, but not glucose transporter type-1 expression, predicted significantly worse prognosis. In multivariate analysis, hypoxia-inducible factor-1α overexpression was significantly correlated with poor overall survival, disease-specific survival and recurrence-free survival. CONCLUSION: High hypoxia-inducible factor-1α expression was an independent risk factor for poor prognosis for advanced human papillomavirus-unrelated pharyngeal cancer.

Protein solubility modeling.

A thermodynamic framework (UNIQUAC model with temperature dependent parameters) is applied to model the salt-induced protein crystallization equilibrium, i.e., protein solubility. The framework introduces a term for the solubility product describing protein transfer between the liquid and solid phase and a term for the solution behavior describing deviation from ideal solution. Protein solubility is modeled as a function of salt concentration and temperature for a four-component system consisting of a protein, pseudo solvent (water and buffer), cation, and anion (salt). Two different systems, lysozyme with sodium chloride and concanavalin A with ammonium sulfate, are investigated. Comparison of the modeled and experimental protein solubility data results in an average root mean square deviation of 5.8%, demonstrating that the model closely follows the experimental behavior. Model calculations and model parameters are reviewed to examine the model and protein crystallization process.

An activity coefficient model for proteins.

Modeling of the properties of biochemical components is gaining increasing interest due to its potential for further application within the area of biochemical process development. Generally protein solution properties such as protein solubility are expressed through component activity coefficients which are studied here. The original UNIQUAC model is chosen for the representation of protein activity coefficients and, to the best of our knowledge, this is the first time it has been directly applied to protein solutions. Ten different protein-salt-water systems with four different proteins, serum albumin, alphacymotrypsin, beta-lactoglobulin and ovalbumin, are investigated. A root-mean-squared deviation of 0.54% is obtained for the model by comparing calculated protein activity coefficients and protein activity coefficients deduced from osmotic measurements through virial expansion. Model predictions are used to analyze the effect of salt concentrations, pH, salt types, and temperature on protein activity coefficients and also on protein solubility and demonstrate consistency with results from other references.