HIF-independent synthetic lethality between CDK4/6 inhibition and VHL loss across species

This is the author accepted manuscript. The final version is available from AAAS via the DOI in this recordData and materials availability: The full dataset of the dsRNA screen in Drosophila S2R+cells is available at www.flyrnai.org/screensummary. All other data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials.Inactivation of the VHL tumor suppressor gene is the signature initiating event in clear cell renal cell carcinoma (ccRCC), the most common form of kidney cancer, and causes the accumulation of hypoxia-inducible factor 2α (HIF-2α). HIF-2α inhibitors are effective in some ccRCC cases, but both de novo and acquired resistance have been observed in the laboratory and in the clinic. Here, we identified synthetic lethality between decreased activity of cyclin-dependent kinases 4 and 6 (CDK4/6) and VHL inactivation in two species (human and Drosophila) and across diverse human ccRCC cell lines in culture and xenografts. Although HIF-2α transcriptionally induced the CDK4/6 partner cyclin D1, HIF-2α was not required for the increased CDK4/6 requirement of VHL−/− ccRCC cells. Accordingly, the antiproliferative effects of CDK4/6 inhibition were synergistic with HIF-2α inhibition in HIF-2α–dependent VHL−/− ccRCC cells and not antagonistic with HIF-2α inhibition in HIF-2α–independent cells. These findings support testing CDK4/6 inhibitors as treatments for ccRCC, alone and in combination with HIF-2α inhibitors.National Cancer InstituteDana-Farber Cancer InstituteHoward Hughes Medical InstituteNational Institute of General Medical Science

Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods

BACKGROUND: Accurate fusion transcript detection is essential for comprehensive characterization of cancer transcriptomes. Over the last decade, multiple bioinformatic tools have been developed to predict fusions from RNA-seq, based on either read mapping or de novo fusion transcript assembly. RESULTS: We benchmark 23 different methods including applications we develop, STAR-Fusion and TrinityFusion, leveraging both simulated and real RNA-seq. Overall, STAR-Fusion, Arriba, and STAR-SEQR are the most accurate and fastest for fusion detection on cancer transcriptomes. CONCLUSION: The lower accuracy of de novo assembly-based methods notwithstanding, they are useful for reconstructing fusion isoforms and tumor viruses, both of which are important in cancer research

Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A \emph{shapelet} is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $k$ shapelets, which are used to produce a transformed dataset, where each of the $k$ features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselve

A Small Molecule that Binds and Inhibits the ETV1 Transcription Factor Oncoprotein

Members of the ETS transcription factor family have been implicated in several cancers, where they are often dysregulated by genomic derangement. ETS variant 1 (ETV1) is an ETS factor gene that undergoes chromosomal translocation in prostate cancers and Ewing\u27s sarcomas, amplification in melanomas, and lineage dysregulation in gastrointestinal stromal tumors. Pharmacologic perturbation of ETV1 would be appealing in these cancers; however, oncogenic transcription factors are often deemed “undruggable” by conventional methods. Here, we used small-molecule microarray (SMM) screens to identify and characterize drug-like compounds that modulate the biological function of ETV1. We identified the 1,3,5-triazine small molecule BRD32048 as a top candidate ETV1 perturbagen. BRD32048 binds ETV1 directly, modulating both ETV1-mediated transcriptional activity and invasion of ETV1-driven cancer cells. Moreover, BRD32048 inhibits p300-dependent acetylation of ETV1, thereby promoting its degradation. These results point to a new avenue for pharmacological ETV1 inhibition and may inform a general means to discover small molecule perturbagens of transcription factor oncoproteins

Dopamine and opioid systems interact within the nucleus accumbens to maintain monogamous pair bonds

Prairie vole breeder pairs form monogamous pair bonds, which are maintained through the expression of selective aggression toward novel conspecifics. Here, we utilize behavioral and anatomical techniques to extend the current understanding of neural mechanisms that mediate pair bond maintenance. For both sexes, we show that pair bonding up-regulates mRNA expression for genes encoding D1-like dopamine (DA) receptors and dynorphin as well as enhances stimulated DA release within the nucleus accumbens (NAc). We next show that D1-like receptor regulation of selective aggression is mediated through downstream activation of kappa-opioid receptors (KORs) and that activation of these receptors mediates social avoidance. Finally, we also identified sex-specific alterations in KOR binding density within the NAc shell of paired males and demonstrate that this alteration contributes to the neuroprotective effect of pair bonding against drug reward. Together, these findings suggest motivational and valence processing systems interact to mediate the maintenance of social bonds

CORUM: the comprehensive resource of mammalian protein complexes

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. The CORUM (http://mips.gsf.de/genre/proj/corum/index.html) database is a collection of experimentally verified mammalian protein complexes. Information is manually derived by critical reading of the scientific literature from expert annotators. Information about protein complexes includes protein complex names, subunits, literature references as well as the function of the complexes. For functional annotation, we use the FunCat catalogue that enables to organize the protein complex space into biologically meaningful subsets. The database contains more than 1750 protein complexes that are built from 2400 different genes, thus representing 12% of the protein-coding genes in human. A web-based system is available to query, view and download the data. CORUM provides a comprehensive dataset of protein complexes for discoveries in systems biology, analyses of protein networks and protein complex-associated diseases. Comparable to the MIPS reference dataset of protein complexes from yeast, CORUM intends to serve as a reference for mammalian protein complexes

37^th plenary meeting report of the scientific, technical and economic committee for fisheries (PLEN-11-02)

The Scientific, Technical and Economic Committee for Fisheries hold its 37th plenary on 11-15 July 2011 in Copenhagen (Denmark). The terms of reference included both issues assessments of STECF Expert Working Group reports and additional requests submitted to the STECF by the Commission. Topics dealt with ranged from fisheries economics to management plan evaluation issues

Intratumor genetic heterogeneity in squamous cell carcinoma of the oral cavity

BackgroundWe sought to evaluate intratumor heterogeneity in squamous cell carcinoma of the oral cavity (OCC) and specifically determine the effect of physical separation and histologic differentiation within the same tumor.MethodsWe performed whole exome sequencing on five biopsy sites—two from well‐differentiated, two from poorly differentiated regions, and one from normal parenchyma—from five primary OCC specimens.ResultsWe found high levels of intratumor heterogeneity and, in four primary tumors, identified only 0 to 2 identical mutations in all subsites. We found that the heterogeneity inversely correlated with physical separation and that pairs of well‐differentiated samples were more similar to each other than analogous poorly differentiated specimens. Only TP53 mutations, but not other purported “driver mutations” in head and neck squamous cell carcinoma, were found in multiple biopsy sites.ConclusionThese data highlight the challenges to characterization of the mutational landscape of OCC with single site biopsy and have implications for personalized medicine.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150549/1/hed25719.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150549/2/hed25719_am.pd

DLEC1 and MLH1 promoter methylation are associated with poor prognosis in non-small cell lung carcinoma

The significance of chromosome 3p gene alterations in lung cancer is poorly understood. This study set out to investigate promoter methylation in the deleted in lung and oesophageal cancer 1 (DLEC1), MLH1 and other 3p genes in 239 non-small cell lung carcinomas (NSCLC). DLEC1 was methylated in 38.7%, MLH1 in 35.7%, RARβ in 51.7%, RASSF1A in 32.4% and BLU in 35.3% of tumours. Any two of the gene alterations were associated with each other except RARβ. DLEC1 methylation was an independent marker of poor survival in the whole cohort (P=0.025) and in squamous cell carcinoma (P=0.041). MLH1 methylation was also prognostic, particularly in large cell cancer (P=0.006). Concordant methylation of DLEC1/MLH1 was the strongest independent indicator of poor prognosis in the whole cohort (P=0.009). However, microsatellite instability and loss of MLH1 expression was rare, suggesting that MLH1 promoter methylation does not usually lead to gene silencing in lung cancer. This is the first study describing the prognostic value of DLEC1 and MLH1 methylation in NSCLC. The concordant methylation is possibly a consequence of a long-range epigenetic effect in this region of chromosome 3p, which has recently been described in other cancers