On the decreasing trend of the number of monsoon depressions in the Bay of Bengal

This study unravels the physical link between the weakening of the monsoon circulation and the decreasing trend in the frequency of monsoon depressions over the Bay of Bengal. Based on the analysis of the terms of Genesis Potential Index, an empirical index to quantify the relative contribution of large scale environmental variables responsible for the modulation of storms, it is shown here that the reduction in the mid-tropospheric relative humidity is the most important reason for the decrease in the number of monsoon depressions. The net reduction of relative humidity over the Bay of Bengal is primarily due to the decrease in the moisture flux convergence, which is attributed to the weakening of the low level jet, a characteristic feature of monsoon circulation. Further, the anomalous moisture convergence over the western equatorial Indian Ocean associated with the rapid warming of the sea surface, reduces the moisture advection into the Bay of Bengal and hence adversely affect the genesis/intensification of monsoon depressions. Hence, the reduction in the number of monsoon depression over the Bay of Bengal could be one of the manifestations of the differential rates in the observed warming trend of the Indian Ocean basi

Cooperative and Antagonistic Contributions of Two Heterochromatin Proteins to Transcriptional Regulation of the Drosophila Sex Determination Decision

Eukaryotic nuclei contain regions of differentially staining chromatin (heterochromatin), which remain condensed throughout the cell cycle and are largely transcriptionally silent. RNAi knockdown of the highly conserved heterochromatin protein HP1 in Drosophila was previously shown to preferentially reduce male viability. Here we report a similar phenotype for the telomeric partner of HP1, HOAP, and roles for both proteins in regulating the Drosophila sex determination pathway. Specifically, these proteins regulate the critical decision in this pathway, firing of the establishment promoter of the masterswitch gene, Sex-lethal (Sxl). Female-specific activation of this promoter, SxlPe, is essential to females, as it provides SXL protein to initiate the productive female-specific splicing of later Sxl transcripts, which are transcribed from the maintenance promoter (SxlPm) in both sexes. HOAP mutants show inappropriate SxlPe firing in males and the concomitant inappropriate splicing of SxlPm-derived transcripts, while females show premature firing of SxlPe. HP1 mutants, by contrast, display SxlPm splicing defects in both sexes. Chromatin immunoprecipitation assays show both proteins are associated with SxlPe sequences. In embryos from HP1 mutant mothers and Sxl mutant fathers, female viability and RNA polymerase II recruitment to SxlPe are severely compromised. Our genetic and biochemical assays indicate a repressing activity for HOAP and both activating and repressing roles for HP1 at SxlPe

Identification of Candidate Growth Promoting Genes in Ovarian Cancer through Integrated Copy Number and Expression Analysis

Ovarian cancer is a disease characterised by complex genomic rearrangements but the majority of the genes that are the target of these alterations remain unidentified. Cataloguing these target genes will provide useful insights into the disease etiology and may provide an opportunity to develop novel diagnostic and therapeutic interventions. High resolution genome wide copy number and matching expression data from 68 primary epithelial ovarian carcinomas of various histotypes was integrated to identify genes in regions of most frequent amplification with the strongest correlation with expression and copy number. Regions on chromosomes 3, 7, 8, and 20 were most frequently increased in copy number (>40% of samples). Within these regions, 703/1370 (51%) unique gene expression probesets were differentially expressed when samples with gain were compared to samples without gain. 30% of these differentially expressed probesets also showed a strong positive correlation (r≥0.6) between expression and copy number. We also identified 21 regions of high amplitude copy number gain, in which 32 known protein coding genes showed a strong positive correlation between expression and copy number. Overall, our data validates previously known ovarian cancer genes, such as ERBB2, and also identified novel potential drivers such as MYNN, PUF60 and TPX2

Beta-Carotene Reduces Body Adiposity of Mice via BCMO1

Evidence from cell culture studies indicates that β-carotene-(BC)-derived apocarotenoid signaling molecules can modulate the activities of nuclear receptors that regulate many aspects of adipocyte physiology. Two BC metabolizing enzymes, the BC-15,15′-oxygenase (Bcmo1) and the BC-9′,10′-oxygenase (Bcdo2) are expressed in adipocytes. Bcmo1 catalyzes the conversion of BC into retinaldehyde and Bcdo2 into β-10′-apocarotenal and β-ionone. Here we analyzed the impact of BC on body adiposity of mice. To genetically dissect the roles of Bcmo1 and Bcdo2 in this process, we used wild-type and Bcmo1-/- mice for this study. In wild-type mice, BC was converted into retinoids. In contrast, Bcmo1-/- mice showed increased expression of Bcdo2 in adipocytes and β-10′-apocarotenol accumulated as the major BC derivative. In wild-type mice, BC significantly reduced body adiposity (by 28%), leptinemia and adipocyte size. Genome wide microarray analysis of inguinal white adipose tissue revealed a generalized decrease of mRNA expression of peroxisome proliferator-activated receptor γ (PPARγ) target genes. Consistently, the expression of this key transcription factor for lipogenesis was significantly reduced both on the mRNA and protein levels. Despite β-10′-apocarotenoid production, this effect of BC was absent in Bcmo1-/- mice, demonstrating that it was dependent on the Bcmo1-mediated production of retinoids. Our study evidences an important role of BC for the control of body adiposity in mice and identifies Bcmo1 as critical molecular player for the regulation of PPARγ activity in adipocyte

Identification of Tumor Suppressors and Oncogenes from Genomic and Epigenetic Features in Ovarian Cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates

Subclonal diversification of primary breast cancer revealed by multiregion sequencing.

The sequencing of cancer genomes may enable tailoring of therapeutics to the underlying biological abnormalities driving a particular patient's tumor. However, sequencing-based strategies rely heavily on representative sampling of tumors. To understand the subclonal structure of primary breast cancer, we applied whole-genome and targeted sequencing to multiple samples from each of 50 patients' tumors (303 samples in total). The extent of subclonal diversification varied among cases and followed spatial patterns. No strict temporal order was evident, with point mutations and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2 and MYC, occurring early in some tumors and late in others. In 13 out of 50 cancers, potentially targetable mutations were subclonal. Landmarks of disease progression, such as resistance to chemotherapy and the acquisition of invasive or metastatic potential, arose within detectable subclones of antecedent lesions. These findings highlight the importance of including analyses of subclonal structure and tumor evolution in clinical trials of primary breast cancer

An Analysis of Vascular Access Thrombosis Events From the Proactive IV irOn Therapy in hemodiALysis Patients Trial

INTRODUCTION: Treatment of anemia in dialysis patients has been associated with increased risk of vascular access thrombosis (VAT). Proactive IV irOn Therapy in hemodiALysis Patients (PIVOTAL) was a clinical trial of proactive compared with reactive i.v. iron therapy in patients requiring hemodialysis. We analyzed the trial data to determine whether randomized treatment arm, alongside other clinical and laboratory variables, independently associated with VAT. METHODS: In PIVOTAL, 2141 adult patients were randomized. The type of vascular access (arteriovenous fistula [AVF], arteriovenous graft [AVG], or central venous catheter [CVC]) was recorded at baseline and every month after randomization. The associations between clinical and laboratory data and first VAT were evaluated in a multivariate analysis. RESULTS: A total of 480 (22.4%) participants experienced VAT in a median of 2.1 years of follow-up. In multivariable analyses, treatment arm (proactive vs. reactive) was not an independent predictor of VAT (hazard ratio [HR] 1.13, P = 0.18). Diabetic kidney disease (HR 1.45, P < 0.001), AVG use (HR 2.29, P < 0.001), digoxin use (HR 2.48, P < 0.001), diuretic use (HR 1.25, P = 0.02), female sex (HR 1.33, P = 0.002), and previous/current smoker (HR 1.47, P = 0.004) were independently associated with a higher risk of VAT. Angiotensin receptor blocker (ARB) use (HR 0.66, P = 0.01) was independently associated with a lower risk of VAT. CONCLUSION: In PIVOTAL, VAT occurred in nearly 1 quarter of participants in a median of just >2 years. In this post hoc analysis, randomization to proactive i.v. iron treatment arms did not increase the risk of VAT

Using State Space Exploration to Determine How Gene Regulatory Networks Constrain Mutation Order in Cancer Evolution

Cancer develops via the progressive accumulation of somatic mutations, which subvert the normal operation of the gene regulatory network of the cell. However, little is known about the order in which mutations are acquired in successful clones. A particular sequence of mutations may confer an early selective advantage to a clone by increasing survival or proliferation, or lead to negative selection by triggering cell death. The space of allowed sequences of mutations is therefore constrained by the gene regulatory network. Here, we introduce a methodology for the systematic exploration of the effect of every possible sequence of oncogenic mutations in a cancer cell modelled as a qualitative network. Our method uses attractor identification using binary decision diagrams and can be applied to both synchronous and asynchronous systems. We demonstrate our method using a recently developed model of ER-negative breast cancer. We show that there are differing levels of constraint in the order of mutations for different combinations of oncogenes, and that the effects of ErbB2/HER2 over-expression depend on the preceding mutations

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

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe