Targeting proteasomal deubiquitinases USP14 and UCHL5 with b-AP15 reduces 5-fluorouracil resistance in colorectal cancer cells.

5-Fluorouracil (5-FU) is the first-line treatment for colorectal cancer (CRC) patients, but the development of acquired resistance to 5-FU remains a big challenge. Deubiquitinases play a key role in the protein degradation pathway, which is involved in cancer development and chemotherapy resistance. In this study, we investigated the effects of targeted inhibition of the proteasomal deubiquitinases USP14 and UCHL5 on the development of CRC and resistance to 5-FU. By analyzing GEO datasets, we found that the mRNA expression levels of USP14 and UCHL5 in CRC tissues were significantly increased, and negatively correlated with the survival of CRC patients. Knockdown of both USP14 and UCHL5 led to increased 5-FU sensitivity in 5-FU-resistant CRC cell lines (RKO-R and HCT-15R), whereas overexpression of USP14 and UCHL5 in 5-FU-sensitive CRC cells decreased 5-FU sensitivity. B-AP15, a specific inhibitor of USP14 and UCHL5, (1-5 µM) dose-dependently inhibited the viability of RKO, RKO-R, HCT-15, and HCT-15R cells. Furthermore, treatment with b-AP15 reduced the malignant phenotype of CRC cells including cell proliferation and migration, and induced cell death in both 5-FU-sensitive and 5-FU-resistant CRC cells by impairing proteasome function and increasing reactive oxygen species (ROS) production. In addition, b-AP15 inhibited the activation of NF-κB pathway, suppressing cell proliferation. In 5-FU-sensitive and 5-FU-resistant CRC xenografts nude mice, administration of b-AP15 (8 mg·kg-1·d-1, intraperitoneal injection) effectively suppressed the growth of both types of tumors. These results demonstrate that USP14 and UCHL5 play an important role in the development of CRC and resistance to 5-FU. Targeting USP14 and UCHL5 with b-AP15 may represent a promising therapeutic strategy for the treatment of CRC.

Serum metabolic profiling of human gastric cancer based on gas chromatography/mass spectrometry.

Research on molecular mechanisms of carcinogenesis plays an important role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to non-invasively identify the potential biomarkers for the early diagnosis of human gastric cancer. The aims of this study were to explore the underlying metabolic mechanisms of gastric cancer and to identify biomarkers associated with morbidity. Gas chromatography/mass spectrometry (GC/MS) was used to analyze the serum metabolites of 30 Chinese gastric cancer patients and 30 healthy controls. Diagnostic models for gastric cancer were constructed using orthogonal partial least squares discriminant analysis (OPLS-DA). Acquired metabolomic data were analyzed by the nonparametric Wilcoxon test to find serum metabolic biomarkers for gastric cancer. The OPLS-DA model showed adequate discrimination between cancer and non-cancer cohorts while the model failed to discriminate different pathological stages (I-IV) of gastric cancer patients. A total of 44 endogenous metabolites such as amino acids, organic acids, carbohydrates, fatty acids, and steroids were detected, of which 18 differential metabolites were identified with significant differences. A total of 13 variables were obtained for their greatest contribution in the discriminating OPLS-DA model [variable importance in the projection (VIP) value >1.0], among which 11 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test. These metabolites potentially revealed perturbations of glycolysis and of amino acid, fatty acid, cholesterol, and nucleotide metabolism of gastric cancer patients. These results suggest that gastric cancer serum metabolic profiling has great potential in detecting this disease and helping to understand its metabolic mechanisms.

Serum metabolic profiling of human gastric cancer based on gas chromatography/mass spectrometry

Research on molecular mechanisms of carcinogenesis plays an important role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to non-invasively identify the potential biomarkers for the early diagnosis of human gastric cancer. The aims of this study were to explore the underlying metabolic mechanisms of gastric cancer and to identify biomarkers associated with morbidity. Gas chromatography/mass spectrometry (GC/MS) was used to analyze the serum metabolites of 30 Chinese gastric cancer patients and 30 healthy controls. Diagnostic models for gastric cancer were constructed using orthogonal partial least squares discriminant analysis (OPLS-DA). Acquired metabolomic data were analyzed by the nonparametric Wilcoxon test to find serum metabolic biomarkers for gastric cancer. The OPLS-DA model showed adequate discrimination between cancer and non-cancer cohorts while the model failed to discriminate different pathological stages (I-IV) of gastric cancer patients. A total of 44 endogenous metabolites such as amino acids, organic acids, carbohydrates, fatty acids, and steroids were detected, of which 18 differential metabolites were identified with significant differences. A total of 13 variables were obtained for their greatest contribution in the discriminating OPLS-DA model [variable importance in the projection (VIP) value >1.0], among which 11 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test. These metabolites potentially revealed perturbations of glycolysis and of amino acid, fatty acid, cholesterol, and nucleotide metabolism of gastric cancer patients. These results suggest that gastric cancer serum metabolic profiling has great potential in detecting this disease and helping to understand its metabolic mechanisms.