On a functional satisfying a weak Palais-Smale condition

In this paper we study a quasilinear elliptic problem whose functional satisfies a weak version of the well known Palais-Smale condition. An existence result is proved under general assumptions on the nonlinearities.Comment: 18 page

Boceprevir is highly effective in treatment-experienced hepatitis C virus-positive genotype-1 menopausal women

AIM: To investigate the safety/efficacy of Boceprevirbased triple therapy in hepatitis C virus (HCV)-G1 menopausal women who were historic relapsers, partial-responders and null-responders. METHODS: In this single-assignment, unblinded study, we treated fifty-six menopausal women with HCV-G1, 46% F3-F4, and previous PEG-α/RBV failure (7% null, 41% non-responder, and 52% relapser) with 4 wk lead-in with PEG-IFNα2b/RBV followed by PEGIFNα2b/RBV+Boceprevir for 32 wk, with an additional 12 wk of PEG-IFN-α-2b/RBV if patients were HCV-RNA-positive by week 8. In previous null-responders, 44 wk of triple therapy was used. The primary objective of retreatment was to verify whether a sustained virological response (SVR) (HCV RNA undetectable at 24 wk of follow-up) rate of at least 20% could be obtained. The secondary objective was the evaluation of the percent of patients with negative HCV RNA at week 4 (RVR), 8 (RVR BOC), 12 (EVR), or at the end-of-treatment (ETR) that reached SVR. To assess the relationship between SVR and clinical and biochemical parameters, multiple logistic regression analysis was used. RESULTS: After lead-in, only two patients had RVR; HCV-RNA was unchanged in all but 62% who had ≤ 1 logio decrease. After Boceprevir, HCV RNA became undetectable at week 8 in 32/56 (57.1%) and at week 12 in 41/56 (73.2%). Of these, 53.8% and 52.0%, respectively, achieved SVR. Overall, SVR was obtained in 25/56 (44.6%). SVR was achieved in 55% previous relapsers vs. 41% non-responders (Ρ = 0.250), in 44% F0-F2 vs 54% F3-F4 (Ρ = 0.488), and in 11/19 (57.9%) of patients with cirrhosis. At univariate analysis for baseline predictors of SVR, only previous response to antiviral therapy (OR = 2.662, 95%CI: 0.957-6.881, Ρ= 0.043), was related with SVR. When considering "on treatment" factors, 1 log10 HCV RNA decline at week 4 (3.733, 95%CI: 1.676-12.658, Ρ= 0.034) and achievement of RVR BOC (7.347, 95%CI: 2.156-25.035, Ρ= 0.001) were significantly related with the SVR, al-though RVR BOC only (6.794, 95%CI: 1.596-21.644, Ρ = 0.010) maintained significance at multivariate logistic regression analysis. Anemia and neutropenia were managed with Erythropoietin and Filgrastim supplementation, respectively. Only six patients discontinued therapy. CONCLUSION: Boceprevir obtained high SVR response independent of previous response, RVR or baseline fibrosis or cirrhosis. RVR BOC was the only independent predictor of SVR

The cBio cancer Genomics portal: An open platform for exploring multidimensional cancer genomics data

Cataloged from PDF version of article.The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications. © 2012 American Association for Cancer Research

Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma.

Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies

SerpinB2 regulates stromal remodelling and local invasion in pancreatic cancer

Pancreatic cancer has a devastating prognosis, with an overall 5-year survival rate of ~8%, restricted treatment options and characteristic molecular heterogeneity. SerpinB2 expression, particularly in the stromal compartment, is associated with reduced metastasis and prolonged survival in pancreatic ductal adenocarcinoma (PDAC) and our genomic analysis revealed that SERPINB2 is frequently deleted in PDAC. We show that SerpinB2 is required by stromal cells for normal collagen remodelling in vitro, regulating fibroblast interaction and engagement with collagen in the contracting matrix. In a pancreatic cancer allograft model, co-injection of PDAC cancer cells and SerpinB2(-/-) mouse embryonic fibroblasts (MEFs) resulted in increased tumour growth, aberrant remodelling of the extracellular matrix (ECM) and increased local invasion from the primary tumour. These tumours also displayed elevated proteolytic activity of the primary biochemical target of SerpinB2-urokinase plasminogen activator (uPA). In a large cohort of patients with resected PDAC, we show that increasing uPA mRNA expression was significantly associated with poorer survival following pancreatectomy. This study establishes a novel role for SerpinB2 in the stromal compartment in PDAC invasion through regulation of stromal remodelling and highlights the SerpinB2/uPA axis for further investigation as a potential therapeutic target in pancreatic cancer

Mammary molecular portraits reveal lineage-specific features and progenitor cell vulnerabilities.

The mammary epithelium depends on specific lineages and their stem and progenitor function to accommodate hormone-triggered physiological demands in the adult female. Perturbations of these lineages underpin breast cancer risk, yet our understanding of normal mammary cell composition is incomplete. Here, we build a multimodal resource for the adult gland through comprehensive profiling of primary cell epigenomes, transcriptomes, and proteomes. We define systems-level relationships between chromatin-DNA-RNA-protein states, identify lineage-specific DNA methylation of transcription factor binding sites, and pinpoint proteins underlying progesterone responsiveness. Comparative proteomics of estrogen and progesterone receptor-positive and -negative cell populations, extensive target validation, and drug testing lead to discovery of stem and progenitor cell vulnerabilities. Top epigenetic drugs exert cytostatic effects; prevent adult mammary cell expansion, clonogenicity, and mammopoiesis; and deplete stem cell frequency. Select drugs also abrogate human breast progenitor cell activity in normal and high-risk patient samples. This integrative computational and functional study provides fundamental insight into mammary lineage and stem cell biology

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Lysyl oxidase drives tumour progression by trapping EGF receptors at the cell surface

Lysyl oxidase (LOX) remodels the tumour microenvironment by cross-linking the extracellular matrix. LOX overexpression is associated with poor cancer outcomes. Here, we find that LOX regulates the epidermal growth factor receptor (EGFR) to drive tumour progression. We show that LOX regulates EGFR by suppressing TGFβ1 signalling through the secreted protease HTRA1. This increases the expression of Matrilin2 (MATN2), an EGF-like domain-containing protein that traps EGFR at the cell surface to facilitate its activation by EGF. We describe a pharmacological inhibitor of LOX, CCT365623, which disrupts EGFR cell surface retention and delays the growth of primary and metastatic tumour cells in vivo. Thus, we show that LOX regulates EGFR cell surface retention to drive tumour progression, and we validate the therapeutic potential of inhibiting this pathway with the small molecule inhibitor CCT365623

Statistical Inference for Valued-Edge Networks: Generalized Exponential Random Graph Models

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We solve this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges are valued, thus greatly expanding the scope of networks applied researchers can subject to statistical analysis

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON