Src kinase becomes preferentially associated with the VEGFR, KDR/Flk-1, following VEGF stimulation of vascular endothelial cells.

BACKGROUND: The cytoplasmic tyrosine kinase, Src, has been found to play a crucial role in VEGF (vascular endothelial growth factor) - dependent vascular permeability involved in angiogenesis. The two main VEGFRs present on vascular endothelial cells are KDR/Flk-1 (kinase insert domain-containing receptor/fetal liver kinase-1) and Flt-1 (Fms-like tyrosine kinase-1). However, to date, it has not been determined which VEGF receptor (VEGFR) is involved in binding to and activating Src kinase following VEGF stimulation of the receptors. RESULTS: In this report, we demonstrate that Src preferentially associates with KDR/Flk-1 rather than Flt-1 in human umbilical vein endothelial cells (HUVECs), and that VEGF stimulation resulted in an increase of Src activity associated with activated KDR/Flk-1. These findings were determined through immunoprecipitation-kinase experiments and coimmunoprecipitation studies, and were further confirmed by GST-pull-down assays and Far Western studies. However, Fyn and Yes, unlike Src, were found to associate preferentially with Flt-1. CONCLUSIONS: Thus, Src preferentially associates with KDR/Flk-1, rather than with Flt-1, upon VEGF stimulation in endothelial cells. Our findings further highlight the potential significance of upregulated KDR/Flk-1-associated Src activity in the process of angiogenesis, and help to elucidate more clearly the specific roles and mechanisms involving Src family tyrosine kinase in VEGF-stimulated signal transduction events.

The von Hippel-Lindau Tumor Suppressor Protein Is Destabilized by Src: Implications for Tumor Angiogenesis and Progression.

The von Hippel-Lindau tumor suppressor protein (VHL), when mutated and inactivated, has been associated with renal and CNS cancer development. VHL normally plays an important role in targeting for degradation of the HIF-1α (hypoxia inducible factor-1α) transcription factor, a primary positive regulator of vascular endothelial growth factor (VEGF) production. In this report we demonstrate that VHL destabilization can be induced by Src kinase and may be involved in other cancers, including breast cancer. We have found that elevated Src can trigger a drastic reduction in VHL stability even under normoxic conditions, through phosphorylation of VHL tyrosine residue 185, leading to ubiquitination and proteasome-mediated degradation of VHL. The Src-induced degradation of VHL protein leads to increased HIF-1α levels and transcriptional activity and increased VEGF production. In this manner, Src regulation of VHL protein stability may play an important role in promoting VEGF expression, tumor angiogenesis, and cancer progression.

MR classification of renal masses with pathologic correlation.

To perform a feature analysis of malignant renal tumors evaluated with magnetic resonance (MR) imaging and to investigate the correlation between MR imaging features and histopathological findings. MR examinations in 79 malignant renal masses were retrospectively evaluated, and a feature analysis was performed. Each renal mass was assigned to one of eight categories from a proposed MRI classification system. The sensitivity and specificity of the MRI classification system to predict the histologic subtype and nuclear grade was calculated. Subvoxel fat on chemical shift imaging correlated to clear cell type (p < 0.05); sensitivity = 42%, specificity = 100%. Large size, intratumoral necrosis, retroperitoneal vascular collaterals, and renal vein thrombosis predicted high-grade clear cell type (p < 0.05). Small size, peripheral location, low intratumoral SI on T2-weighted images, and low-level enhancement were associated with low-grade papillary carcinomas (p < 0.05). The sensitivity and specificity of the MRI classification system for diagnosing low grade clear cell, high-grade clear cell, all clear cell, all papillary, and transitional carcinomas were 50% and 94%, 93% and 75%, 92% and 83%, 80% and 94%, and 100% and 99%, respectively. The MRI feature analysis and proposed classification system help predict the histological type and nuclear grade of renal masses.