BCNU for recurrent glioblastoma multiforme: efficacy, toxicity and prognostic factors

<p>Abstract</p> <p>Background</p> <p>The prognosis for patients with recurrent glioblastoma is still poor with a median survival between 3 and 6 months. Reports about the application of carmustine (BCNU), one of the standard chemotherapeutic drugs in the treatment of newly diagnosed glioblastoma, in the recurrent situation are rare.</p> <p>Methods</p> <p>We performed a retrospective analysis of 35 patients with recurrent or progressive glioblastoma treated with 80 mg/m²BCNU on days 1 on 3 intravenously at our department for efficacy, toxicity and prognostic factors. Progression free survival and overall survival were estimated by the Kaplan-Meier method. The influence of age, Karnofsky performance status (KPS), tumor burden, pretreatment with temozolomide (TMZ), type of surgery for initial diagnosis and number of previous relapses on outcome was analyzed in a proportional hazards regression model.</p> <p>Results</p> <p>The median age of the group was 53 years, median KPS was 70. Median progression free survival was 11 weeks (95% confidence interval [CI]: 8-15), median overall survival 22 weeks (95% CI: 18-27). The rate of adverse events, especially hematological toxicity, is relatively high, and in 3 patients treatment had to be terminated due to adverse events (one pulmonary embolism, one pulmonary fibrosis, and one severe bone marrow suppression). No influence of age, KPS, tumor burden, pre-treatment with TMZ and number of previous relapses on outcome could be demonstrated, while gross total resection prior to recurrence showed a borderline statistically significant negative impact on PFS and OS. These data compare well with historical survival figures. However prospective randomized studies are needed to evaluate BCNU efficacy against newer drugs like bevacizumab or the intensified temozolomide regime (one week on/one week off).</p> <p>Conclusion</p> <p>In summary, BCNU treatment appears to be a valuable therapeutic option for recurrent glioblastomas, where no other validated radio- and/or chemotherapy are available.</p

Variations in Stress Sensitivity and Genomic Expression in Diverse S. cerevisiae Isolates

Interactions between an organism and its environment can significantly influence phenotypic evolution. A first step toward understanding this process is to characterize phenotypic diversity within and between populations. We explored the phenotypic variation in stress sensitivity and genomic expression in a large panel of Saccharomyces strains collected from diverse environments. We measured the sensitivity of 52 strains to 14 environmental conditions, compared genomic expression in 18 strains, and identified gene copy-number variations in six of these isolates. Our results demonstrate a large degree of phenotypic variation in stress sensitivity and gene expression. Analysis of these datasets reveals relationships between strains from similar niches, suggests common and unique features of yeast habitats, and implicates genes whose variable expression is linked to stress resistance. Using a simple metric to suggest cases of selection, we found that strains collected from oak exudates are phenotypically more similar than expected based on their genetic diversity, while sake and vineyard isolates display more diverse phenotypes than expected under a neutral model. We also show that the laboratory strain S288c is phenotypically distinct from all of the other strains studied here, in terms of stress sensitivity, gene expression, Ty copy number, mitochondrial content, and gene-dosage control. These results highlight the value of understanding the genetic basis of phenotypic variation and raise caution about using laboratory strains for comparative genomics

Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies

<p>Abstract</p> <p>Background</p> <p>The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem in the analysis of gene expression data since genes may only jointly respond over a subset of conditions. Biclustering algorithms also have important applications in sample classification where, for instance, tissue samples can be classified as cancerous or normal. Many of the methods for biclustering, and clustering algorithms in general, utilize simplified models or heuristic strategies for identifying the "best" grouping of elements according to some metric and cluster definition and thus result in suboptimal clusters.</p> <p>Results</p> <p>In this article, we present a rigorous approach to biclustering, OREO, which is based on the Optimal RE-Ordering of the rows and columns of a data matrix so as to globally minimize the dissimilarity metric. The physical permutations of the rows and columns of the data matrix can be modeled as either a network flow problem or a traveling salesman problem. Cluster boundaries in one dimension are used to partition and re-order the other dimensions of the corresponding submatrices to generate biclusters. The performance of OREO is tested on (a) metabolite concentration data, (b) an image reconstruction matrix, (c) synthetic data with implanted biclusters, and gene expression data for (d) colon cancer data, (e) breast cancer data, as well as (f) yeast segregant data to validate the ability of the proposed method and compare it to existing biclustering and clustering methods.</p> <p>Conclusion</p> <p>We demonstrate that this rigorous global optimization method for biclustering produces clusters with more insightful groupings of similar entities, such as genes or metabolites sharing common functions, than other clustering and biclustering algorithms and can reconstruct underlying fundamental patterns in the data for several distinct sets of data matrices arising in important biological applications.</p

Activation of Thiazide-Sensitive Co-Transport by Angiotensin II in the cyp1a1-Ren2 Hypertensive Rat

Transgenic rats with inducible expression of the mouse Ren2 gene were used to elucidate mechanisms leading to the development of hypertension and renal injury. Ren2 transgene activation was induced by administration of a naturally occurring aryl hydrocarbon, indole-3-carbinol (100 mg/kg/day by gastric gavage). Blood pressure and renal parameters were recorded in both conscious and anesthetized (butabarbital sodium; 120 mg/kg IP) rats at selected time-points during the development of hypertension. Hypertension was evident by the second day of treatment, being preceded by reduced renal sodium excretion due to activation of the thiazide-sensitive sodium-chloride co-transporter. Renal injury was evident after the first day of transgene induction, being initially limited to the pre-glomerular vasculature. Mircoalbuminuria and tubuloinsterstitial injury developed once hypertension was established. Chronic treatment with either hydrochlorothiazide or an AT1 receptor antagonist normalized sodium reabsorption, significantly blunted hypertension and prevented renal injury. Urinary aldosterone excretion was increased ∼20 fold, but chronic mineralocorticoid receptor antagonism with spironolactone neither restored natriuretic capacity nor prevented hypertension. Spironolactone nevertheless ameliorated vascular damage and prevented albuminuria. This study finds activation of sodium-chloride co-transport to be a key mechanism in angiotensin II-dependent hypertension. Furthermore, renal vascular injury in this setting reflects both barotrauma and pressure-independent pathways associated with direct detrimental effects of angiotensin II and aldosterone

CD105 (Endoglin) exerts prognostic effects via its role in the microvascular niche of paediatric high grade glioma

Paediatric high grade glioma (pHGG) (World Health Organisation astrocytoma grades III and IV) remains poor prognosis tumours, with a median survival of only 15 months following diagnosis. Current investigation of anti-angiogenic strategies has focused on adult glioblastoma multiforme (GBM) with phase III trials targeting vascular endothelial growth factor continuing. In this study we investigated whether the degree of vascularity correlated with prognosis in a large cohort of pHGG (n = 150) and whether different vessel markers carried different prognostic value. We found that CD105 (endoglin) had a strongly significant association with poor prognosis on multivariate analysis (p = <0.001). Supervised hierarchical clustering of genome wide gene expression data identified 13 genes associated with differential degrees of vascularity in the cohort. The novel angiogenesis-associated genes identified in this analysis (including MIPOL-1 and ENPP5) were validated by realtime polymerase chain reaction. We also demonstrate that CD105 positive blood vessels associate with CD133 positive tumour cells and that a proportion of CD105 positive vessel cells demonstrates co-positivity for CD133, suggesting that the recently described phenomenon of vasculogenic mimicry occurs in pHGG. Together, the data suggest that targeting angiogenesis, and in particular CD105, is a valid therapeutic strategy for pHGG

Long-term outcome of chronic dialysis in children

As the prevalence of children on renal replacement therapy (RRT) increases world wide and such therapy comprises at least 2% of any national dialysis or transplant programme, it is essential that paediatric nephrologists are able to advise families on the possible outcome for their child on dialysis. Most children start dialysis with the expectation that successful renal transplantation is an achievable goal and will provide the best survival and quality of life. However, some will require long-term dialysis or may return intermittently to dialysis during the course of their chronic kidney disease (CKD). This article reviews the available outcome data for children on chronic dialysis as well as extrapolating data from the larger adult dialysis experience to inform our paediatric practice. The multiple factors that may influence outcome, and, particularly, those that can potentially be modified, are discussed

Gene Expression Profiling in Cells with Enhanced γ-Secretase Activity

BACKGROUND: Processing by gamma-secretase of many type-I membrane protein substrates triggers signaling cascades by releasing intracellular domains (ICDs) that, following nuclear translocation, modulate the transcription of different genes regulating a diverse array of cellular and biological processes. Because the list of gamma-secretase substrates is growing quickly and this enzyme is a cancer and Alzheimer's disease therapeutic target, the mapping of gamma-secretase activity susceptible gene transcription is important for sharpening our view of specific affected genes, molecular functions and biological pathways. METHODOLOGY/PRINCIPAL FINDINGS: To identify genes and molecular functions transcriptionally affected by gamma-secretase activity, the cellular transcriptomes of Chinese hamster ovary (CHO) cells with enhanced and inhibited gamma-secretase activity were analyzed and compared by cDNA microarray. The functional clustering by FatiGO of the 1,981 identified genes revealed over- and under-represented groups with multiple activities and functions. Single genes with the most pronounced transcriptional susceptibility to gamma-secretase activity were evaluated by real-time PCR. Among the 21 validated genes, the strikingly decreased transcription of PTPRG and AMN1 and increased transcription of UPP1 potentially support data on cell cycle disturbances relevant to cancer, stem cell and neurodegenerative diseases' research. The mapping of interactions of proteins encoded by the validated genes exclusively relied on evidence-based data and revealed broad effects on Wnt pathway members, including WNT3A and DVL3. Intriguingly, the transcription of TERA, a gene of unknown function, is affected by gamma-secretase activity and was significantly altered in the analyzed human Alzheimer's disease brain cortices. CONCLUSIONS/SIGNIFICANCE: Investigating the effects of gamma-secretase activity on gene transcription has revealed several affected clusters of molecular functions and, more specifically, 21 genes that hold significant potential for a better understanding of the biology of gamma-secretase and its roles in cancer and Alzheimer's disease pathology

Breast tumour angiogenesis

The central importance of tumour neovascularization has been emphasized by clinical trials using antiangiogenic therapy in breast cancer. This review gives a background to breast tumour neovascularization in in situ and invasive breast cancer, outlines the mechanisms by which this is achieved and discusses the influence of the microenvironment, focusing on hypoxia. The regulation of angiogenesis and the antivascular agents that are used in an antiangiogenic dosing schedule, both novel and conventional, are also summarized

Patient-derived xenograft (PDX) models in basic and translational breast cancer research

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research