A comprehensive survey of genomic alterations in gastric cancer reveals systematic patterns of molecular exclusivity and co-occurrence among distinct therapeutic targets

Objective: Gastric cancer is a major gastrointestinal malignancy for which targeted therapies are emerging as treatment options. This study sought to identify the most prevalent molecular targets in gastric cancer and to elucidate systematic patterns of exclusivity and co-occurrence among these targets, through comprehensive genomic analysis of a large panel of gastric cancers. Design: Using high-resolution single nucleotide polymorphism arrays, copy number alterations were profiled in a panel of 233 gastric cancers (193 primary tumours, 40 cell lines) and 98 primary matched gastric non-malignant samples. For selected alterations, their impact on gene expression and clinical outcome were evaluated. Results: 22 recurrent focal alterations (13 amplifications and nine deletions) were identified. These included both known targets (FGFR2, ERBB2) and also novel genes in gastric cancer (KLF5, GATA6). Receptor tyrosine kinase (RTK)/RAS alterations were found to be frequent in gastric cancer. This study also demonstrates, for the first time, that these alterations occur in a mutually exclusive fashion, with KRAS gene amplifications highlighting a clinically relevant but previously underappreciated gastric cancer subgroup. FGFR2-amplified gastric cancers were also shown to be sensitive to dovitinib, an orally bioavailable FGFR/VEGFR targeting agent, potentially representing a subtype-specific therapy for FGFR2-amplified gastric cancers. Conclusion: The study demonstrates the existence of five distinct gastric cancer patient subgroups, defined by the signature genomic alterations FGFR2 (9% of tumours), KRAS (9%), EGFR (8%), ERBB2 (7%) and MET (4%). Collectively, these subgroups suggest that at least 37% of gastric cancer patients may be potentially treatable by RTK/RAS directed therapies

Post-Partum Pituitary Insufficiency and Livedo Reticularis Presenting a Diagnostic Challenge in a Resource Limited Setting in Tanzania: A Case Report, Clinical Discussion and Brief Review of Existing Literature.

Pituitary disorders following pregnancy are an important yet under reported clinical entity in the developing world. Conversely, post partum panhypopituitarism has a more devastating impact on women in such settings due to high fertility rates, poor obstetric care and scarcity of diagnostic and therapeutic resources available. A 37 year old African female presented ten years post partum with features of multiple endocrine deficiencies including hypothyroidism, hypoadrenalism, lactation failure and secondary amenorrhea. In addition she had clinical features of an underlying autoimmune condition. These included a history of post-partum thyroiditis, alopecia areata, livedo reticularis and deranged coagulation indices. A remarkable clinical response followed appropriate hormone replacement therapy including steroids. This constellation has never been reported before; we therefore present an interesting clinical discussion including a brief review of existing literature. Post partum pituitary insufficiency is an under-reported condition of immense clinical importance especially in the developing world. A high clinical index of suspicion is vital to ensure an early and correct diagnosis which will have a direct bearing on management and patient outcome

Mitochondrial Mutations in Adenoid Cystic Carcinoma of the Salivary Glands

Background: The MitoChip v2.0 resequencing array is an array-based technique allowing for accurate and complete sequencing of the mitochondrial genome. No studies have investigated mitochondrial mutation in salivary gland adenoid cystic carcinomas. Methodology: The entire mitochondrial genome of 22 salivary gland adenoid cystic carcinomas (ACC) of salivary glands and matched leukocyte DNA was sequenced to determine the frequency and distribution of mitochondrial mutations in ACC tumors. Principal Findings: Seventeen of 22 ACCs (77%) carried mitochondrial mutations, ranging in number from 1 to 37 mutations. A disproportionate number of mutations occurred in the D-loop. Twelve of 17 tumors (70.6%) carried mutations resulting in amino acid changes of translated proteins. Nine of 17 tumors (52.9%) with a mutation carried an amino acid changing mutation in the nicotinamide adenine dinucleotide dehydrogenase (NADH) complex. Conclusions/Significance: Mitochondrial mutation is frequent in salivary ACCs. The high incidence of amino acid changing mutations implicates alterations in aerobic respiration in ACC carcinogenesis. D-loop mutations are of unclear significance

The influence of polygenic risk for bipolar disorder on neural activation assessed using fMRI

Genome-wide association studies (GWAS) have demonstrated a significant polygenic contribution to bipolar disorder (BD) where disease risk is determined by the summation of many alleles of small individual magnitude. Modelling polygenic risk scores may be a powerful way of identifying disrupted brain regions whose genetic architecture is related to that of BD. We determined the extent to which common genetic variation underlying risk to BD affected neural activation during an executive processing/language task in individuals at familial risk of BD and healthy controls. Polygenic risk scores were calculated for each individual based on GWAS data from the Psychiatric GWAS Consortium Bipolar Disorder Working Group (PGC-BD) of over 16 000 subjects. The familial group had a significantly higher polygene score than the control group (P=0.04). There were no significant group by polygene interaction effects in terms of association with brain activation. However, we did find that an increasing polygenic risk allele load for BD was associated with increased activation in limbic regions previously implicated in BD, including the anterior cingulate cortex and amygdala, across both groups. The findings suggest that this novel polygenic approach to examine brain-imaging data may be a useful means of identifying genetically mediated traits mechanistically linked to the aetiology of BD

Validation of graft and standard liver size predictions in right liver living donor liver transplantation

Purpose: To assess the accuracy of a formula derived from 159 living liver donors to estimate the liver size of a normal subject: standard liver weight (g) = 218 + body weight (kg) × 12.3 + 51 (if male). Standard liver volume (SLV) is attained by a conversion factor of 1.19 mL/g. Methods: The total liver volume (TLV) of each of the subsequent consecutive 126 living liver donors was determined using the right liver graft weight (RGW) on the back table, right/left liver volume ratio on computed tomography, and the conversion factor. The estimated right liver graft weight (ERGW) was determined by the right liver volume on computed tomography (CT) and the conversion factor. SLV and ERGW were compared with TLV and RGW, respectively, by paired sample t test. Results: Donor characteristics of both series were similar. SLV and TLV were 1,099.6 ± 139.6 and 1,108.5 ± 175.2 mL, respectively, (R 2 = 0.476) (p = 0.435). The difference between SLV and TLV was only -8.9 ± 128.2 mL (-1.0 ± 11.7%). ERGW and RGW were 601.5 ± 104.1 and 597.1 ± 102.2 g, respectively (R 2 = 0.781) (p = 0.332). The conversion factor from liver weight to volume for this series was 1.20 mL/g. The difference between ERGW and RGW was 4.3 ± 49.8 g (0.3 ± 8.8%). ERGW was smaller than RGW for over 10% (range 0.21-40.66 g) in 18 of the 126 donors. None had the underestimation of RGW by over 20%. Conclusion: SLV and graft weight estimations were accurate using the formula and conversion factor. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

Heterologous expression of cytotoxic sesquiterpenoids from the medicinal mushroom Lignosus rhinocerotis in yeast

Background: Genome mining facilitated by heterologous systems is an emerging approach to access the chemical diversity encoded in basidiomycete genomes. In this study, three sesquiterpene synthase genes, GME3634, GME3638, and GME9210, which were highly expressed in the sclerotium of the medicinal mushroom Lignosus rhinocerotis, were cloned and heterologously expressed in a yeast system. Results: Metabolite profile analysis of the yeast culture extracts by GC-MS showed the production of several sesquiterpene alcohols (C 15 H 26 O), including cadinols and germacrene D-4-ol as major products. Other detected sesquiterpenes include selina-6-en-4-ol, ß-elemene, ß-cubebene, and cedrene. Two purified major compounds namely (+)-torreyol and a-cadinol synthesised by GME3638 and GME3634 respectively, are stereoisomers and their chemical structures were confirmed by 1 H and 13 C NMR. Phylogenetic analysis revealed that GME3638 and GME3634 are a pair of orthologues, and are grouped together with terpene synthases that synthesise cadinenes and related sesquiterpenes. (+)-Torreyol and a-cadinol were tested against a panel of human cancer cell lines and the latter was found to exhibit selective potent cytotoxicity in breast adenocarcinoma cells (MCF7) with IC 50 value of 3.5 ± 0.58 µg/ml while a-cadinol is less active (IC 50 = 18.0 ± 3.27 µg/ml). Conclusions: This demonstrates that yeast-based genome mining, guided by transcriptomics, is a promising approach for uncovering bioactive compounds from medicinal mushrooms

Following Ariadne's thread: a new perspective on RBR ubiquitin ligases

Ubiquitin signaling pathways rely on E3 ligases for effecting the final transfer of ubiquitin from E2 ubiquitin conjugating enzymes to a protein target. Here we re-evaluate the hybrid RING/HECT mechanism used by the E3 family RING-between-RINGs (RBRs) to transfer ubiquitin to substrates. We place RBRs into the context of current knowledge of HECT and RING E3s. Although not as abundant as the other types of E3s (there are only slightly more than a dozen RBR E3s in the human genome), RBRs are conserved in all eukaryotes and play important roles in biology. Re-evaluation of RBR ligases as RING/HECT E3s provokes new questions and challenges the field

Comprehensive evaluation of matrix factorization methods for the analysis of DNA microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Clustering-based methods on gene-expression analysis have been shown to be useful in biomedical applications such as cancer subtype discovery. Among them, Matrix factorization (MF) is advantageous for clustering gene expression patterns from DNA microarray experiments, as it efficiently reduces the dimension of gene expression data. Although several MF methods have been proposed for clustering gene expression patterns, a systematic evaluation has not been reported yet.</p> <p>Results</p> <p>Here we evaluated the clustering performance of orthogonal and non-orthogonal MFs by a total of nine measurements for performance in four gene expression datasets and one well-known dataset for clustering. Specifically, we employed a non-orthogonal MF algorithm, BSNMF (Bi-directional Sparse Non-negative Matrix Factorization), that applies bi-directional sparseness constraints superimposed on non-negative constraints, comprising a few dominantly co-expressed genes and samples together. Non-orthogonal MFs tended to show better clustering-quality and prediction-accuracy indices than orthogonal MFs as well as a traditional method, K-means. Moreover, BSNMF showed improved performance in these measurements. Non-orthogonal MFs including BSNMF showed also good performance in the functional enrichment test using Gene Ontology terms and biological pathways.</p> <p>Conclusions</p> <p>In conclusion, the clustering performance of orthogonal and non-orthogonal MFs was appropriately evaluated for clustering microarray data by comprehensive measurements. This study showed that non-orthogonal MFs have better performance than orthogonal MFs and <it>K</it>-means for clustering microarray data.</p

An empirical analysis of the determinants of mobile instant messaging appropriation in university learning

Published ArticleResearch on technology adoption often profiles device usability (such as perceived usefulness) and user dispositions (such as perceived ease of use) as the prime determinants of effective technology adoption. Since any process of technology adoption cannot be conceived out of its situated contexts, this paper argues that any pre-occupation with technology acceptance from the perspective of device usability and user dispositions potentially negates enabling contexts that make successful adoption a reality. Contributing to contemporary debates on technology adoption, this study presents flexible mobile learning contexts comprising cost (device cost and communication cost), device capabilities (portability, collaborative capabilities), and learner traits (learner control) as antecedents that enable the sustainable uptake of emerging technologies. To explore the acceptance and capacity of mobile instant messaging systems to improve student performance, the study draws on these antecedents, develops a factor model and empirically tests it on tertiary students at a South African University of Technology. The study involved 223 national diploma and bachelor’s degree students and employed partial least squares for statistical analysis. Overall, the proposed model displayed a good fit with the data and rendered satisfactory explanatory power for students’ acceptance of mobile learning. Findings suggest that device portability, communication cost, collaborative capabilities of device and learner control are the main drivers of flexible learning in mobile environments. Flexible learning context facilitated by learner control was found to have a positive influence on attitude towards mobile learning and exhibited the highest path coefficient of the overall model. The study implication is that educators need to create varied learning opportunities that leverage learner control of learning in mobile learning systems to enhance flexible mobile learning. The study also confirmed the statistical significance of the original Technology Acceptance Model constructs