Inhibition of activated fibroblast growth factor receptor 2 in endometrial cancer cells induces cell death despite PTEN abrogation

KRAS activation and PTEN inactivation are frequent events in endometrial tumorigenesis, occurring in 10% to 30% and 26% to 80% of endometrial cancers, respectively. Because we have recently shown activating mutations in fibroblast growth factor receptor 2 (FGFR2) in 16% of endometrioid endometrial cancers, we sought to determine the genetic context in which FGFR2 mutations occur. Analysis of 116 primary endometrioid endometrial cancers revealed that FGFR2 and KRAS mutations were mutually exclusive, whereas FGFR2 mutations were seen concomitantly with PTEN mutations. Here, we show that shRNA knockdown of FGFR2 or treatment with a pan-FGFR inhibitor, PD173074, resulted in cell cycle arrest and induction of cell death in endometrial cancer cells with activating mutations in FGFR2. This cell death in response to FGFR2 inhibition occurred within the context of loss-of-function mutations in PTEN and constitutive AKT phosphorylation, and was associated with a marked reduction in extracellular signal-regulated kinase 1/2 activation. Together, these data suggest that inhibition of FGFR2 may be a viable therapeutic option in endometrial tumors possessing activating mutations in FGFR2, despite the frequent abrogation of PTEN in this cancer type.

Brivanib alaninate, a dual inhibitor of vascular endothelial growth factor receptor and fibroblast growth factor receptor tyrosine kinases, induces growth inhibition in mouse models of human hepatocellular carcinoma

PURPOSE: Hreceptor (VEGFR) and FGF receptor (FGFR) signaling pathways. EXPERIMENTAL DESIGN: Six different s.c. patient-derived HCC xenografts were implanted into mice. Tumor growth was evaluated in mice treated with brivanib compared with control. The effects of brivanib on apoptosis and cell proliferation were evaluated by immunohistochemistry. The SK-HEP1 and HepG2 cells were used to investigate the effects of brivanib on the VEGFR-2 and FGFR-1 signaling pathways in vitro. Western blotting was used to determine changes in proteins in these xenografts and cell lines. RESULTS: Brivanib significantly suppressed tumor growth in five of six xenograft lines. Furthermore, brivanib-induced growth inhibition was associated with a decrease in phosphorylated VEGFR-2 at Tyr(1054/1059), increased apoptosis, reduced microvessel density, inhibition of cell proliferation, and down-regulation of cell cycle regulators. The levels of FGFR-1 and FGFR-2 expression in these xenograft lines were positively correlated with its sensitivity to brivanib-induced growth inhibition. In VEGF-stimulated and basic FGF stimulated SK-HEP1 cells, brivanib significantly inhibited VEGFR-2, FGFR-1, extracellular signal-regulated kinase 1/2, and Akt phosphorylation. CONCLUSION: This study provides a strong rationale for clinical investigation of brivanib in patients with HCC.

Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information

Background The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. Results In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. Conclusion A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.