Preoperative predictors for residual tumor after surgery in patients with ovarian carcinoma

Objectives: Suboptimal debulking (>1 cm residual tumor) results in poor survival rates for patients with an advanced stage of ovarian cancer. The purpose of this study was to develop a prediction model, based on simple preoperative parameters, for patients with an advanced stage of ovarian cancer who are at risk of suboptimal cytoreduction despite maximal surgical effort. Methods: Retrospective analysis of 187 consecutive patients with a suspected clinical diagnosis of advanced-stage ovarian cancer undergoing upfront debulking between January 1998 and December 2003. Preoperative parameters were Karnofsky performance status, ascites and serum concentrations of CA 125, hemoglobin, albumin, LDH and blood platelets. The main outcome parameter was residual tumor >1 cm. Univariate and multivariate logistic regression was employed for testing possible prediction models. A clinically applicable graphic model (nomogram) for this prediction was to be developed. Results: Serum concentrations of CA 125 and blood platelets in the group with residual tumor >1 cm were higher in comparison to the optimally cytoreduced group (p 1 cm based on serum levels of CA 125 and albumin was established. Conclusion: Postoperative residual tumor despite maximal surgical effort can be predicted by preoperative CA 125 and serum albumin levels. With a nomogram based on these two parameters, probability of postoperative residual tumor in each individual patient can be predicted. This proposed nomogram may be valuable in daily routine practice for counseling and to select treatment modality. Copyrigh

G protein-coupled receptor kinase 2 positively regulates epithelial cell migration

Cell migration requires integration of signals arising from both the extracellular matrix and messengers acting through G protein-coupled receptors (GPCRs). We find that increased levels of G protein-coupled receptor kinase 2 (GRK2), a key player in GPCR regulation, potentiate migration of epithelial cells towards fibronectin, whereas such process is decreased in embryonic fibroblasts from hemizygous GRK2 mice or upon knockdown of GRK2 expression. Interestingly, the GRK2 effect on fibronectin-mediated cell migration involves the paracrine/autocrine activation of a sphingosine-1-phosphate (S1P) Gi-coupled GPCR. GRK2 positively modulates the activity of the Rac/PAK/MEK/ERK pathway in response to adhesion and S1P by a mechanism involving the phosphorylation-dependent, dynamic interaction of GRK2 with GIT1, a key scaffolding protein in cell migration processes. Furthermore, decreased GRK2 levels in hemizygous mice result in delayed wound healing rate in vivo, consistent with a physiological role of GRK2 as a regulator of coordinated integrin and GPCR-directed epithelial cell migration

Integrative topological analysis of mass spectrometry data reveals molecular features with clinical relevance in esophageal squamous cell carcinoma

Combining MS-based proteomic data with network and topological features of such network would identify more clinically relevant molecules and meaningfully expand the repertoire of proteins derived from MS analysis. The integrative topological indexes representing 95.96% information of seven individual topological measures of node proteins were calculated within a protein-protein interaction (PPI) network, built using 244 differentially expressed proteins (DEPs) identified by iTRAQ 2D-LC-MS/MS. Compared with DEPs, differentially expressed genes (DEGs) and comprehensive features (CFs), structurally dominant nodes (SDNs) based on integrative topological index distribution produced comparable classification performance in three different clinical settings using five independent gene expression data sets. The signature molecules of SDN-based classifier for distinction of early from late clinical TNM stages were enriched in biological traits of protein synthesis, intracellular localization and ribosome biogenesis, which suggests that ribosome biogenesis represents a promising therapeutic target for treating ESCC. In addition, ITGB1 expression selected exclusively by integrative topological measures correlated with clinical stages and prognosis, which was further validated with two independent cohorts of ESCC samples. Thus the integrative topological analysis of PPI networks proposed in this study provides an alternative approach to identify potential biomarkers and therapeutic targets from MS/MS data with functional insights in ESCC