Despite considerable efforts to identify cancer metabolic alterations that might unveil druggable vulnerabilities, systematic characterizations of metabolism as it relates to functional genomic ...features and associated dependencies remain uncommon. To further understand the metabolic diversity of cancer, we profiled 225 metabolites in 928 cell lines from more than 20 cancer types in the Cancer Cell Line Encyclopedia (CCLE) using liquid chromatography-mass spectrometry (LC-MS). This resource enables unbiased association analysis linking the cancer metabolome to genetic alterations, epigenetic features and gene dependencies. Additionally, by screening barcoded cell lines, we demonstrated that aberrant ASNS hypermethylation sensitizes subsets of gastric and hepatic cancers to asparaginase therapy. Finally, our analysis revealed distinct synthesis and secretion patterns of kynurenine, an immune-suppressive metabolite, in model cancer cell lines. Together, these findings and related methodology provide comprehensive resources that will help clarify the landscape of cancer metabolism.
Despite remarkable success of immune checkpoint inhibitors, the majority of cancer patients have yet to receive durable benefits. Here, in order to investigate the metabolic alterations in response ...to immune checkpoint blockade, we comprehensively profile serum metabolites in advanced melanoma and renal cell carcinoma patients treated with nivolumab, an antibody against programmed cell death protein 1 (PD1). We identify serum kynurenine/tryptophan ratio increases as an adaptive resistance mechanism associated with worse overall survival. This advocates for patient stratification and metabolic monitoring in immunotherapy clinical trials including those combining PD1 blockade with indoleamine 2,3-dioxygenase/tryptophan 2,3-dioxygenase (IDO/TDO) inhibitors.
BACKGROUND:Although metabolomic profiling offers promise for the prediction of coronary heart disease (CHD), and metabolic risk factors are more strongly associated with CHD in women than men, ...limited data are available for women.
METHODS:We applied a liquid chromatography–tandem mass spectrometry metabolomics platform to measure 371 metabolites in a discovery set of postmenopausal women (472 incident CHD cases, 472 controls) with validation in an independent set of postmenopausal women (312 incident CHD cases, 315 controls).
RESULTS:Eight metabolites, primarily oxidized lipids, were significantly dysregulated in cases after the adjustment for matching and CHD risk factors in both the discovery and validation data sets. One oxidized phospholipid, C34:2 hydroxy-phosphatidylcholine, remained associated with CHD after further adjustment for other validated metabolites. Subjects with C34:2 hydroxy-phosphatidylcholine levels in the highest quartile had a 4.7-fold increase in CHD odds in comparison with the lowest quartile; C34:2 hydroxy-phosphatidylcholine also significantly improved the area under the curve (P<0.01) for CHD. The C34:2 hydroxy-phosphatidylcholine findings were replicated in a third replication data set of 980 men and women (230 cardiovascular events) with a stronger association observed in women.
CONCLUSIONS:These data replicate known metabolite predictors, identify novel markers, and support the relationship between lipid oxidation and subsequent CHD.
Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation ...and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing. All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines. When combined with genomic characterization of these cell lines, this dataset facilitates the linkage of genetic dependencies with specific cellular contexts (e.g., gene mutations or cell lineage). To enable such comparisons, we developed and provided a bioinformatics tool to identify linear and nonlinear correlations between these features.
Genome-scale RNAi libraries enable the systematic interrogation of gene function. However, the interpretation of RNAi screens is complicated by the observation that RNAi reagents designed to suppress ...the mRNA transcripts of the same gene often produce a spectrum of phenotypic outcomes due to differential on-target gene suppression or perturbation of off-target transcripts. Here we present a computational method, Analytic Technique for Assessment of RNAi by Similarity (ATARiS), that takes advantage of patterns in RNAi data across multiple samples in order to enrich for RNAi reagents whose phenotypic effects relate to suppression of their intended targets. By summarizing only such reagent effects for each gene, ATARiS produces quantitative, gene-level phenotype values, which provide an intuitive measure of the effect of gene suppression in each sample. This method is robust for data sets that contain as few as 10 samples and can be used to analyze screens of any number of targeted genes. We used this analytic approach to interrogate RNAi data derived from screening more than 100 human cancer cell lines and identified HNF1B as a transforming oncogene required for the survival of cancer cells that harbor HNF1B amplifications. ATARiS is publicly available at http://broadinstitute.org/ataris.
RNA editing is one of several post-transcriptional modifications that may contribute to organismal complexity in the face of limited gene complement in a genome. One form, known as C --> U editing, ...appears to exist in a wide range of organisms, but most instances of this form of RNA editing have been discovered serendipitously. With the large amount of genomic and transcriptomic data now available, a computational analysis could provide a more rapid means of identifying novel sites of C --> U RNA editing. Previous efforts have had some success but also some limitations. We present a computational method for identifying C --> U RNA editing sites in genomic sequences that is both robust and generalizable. We evaluate its potential use on the best data set available for these purposes: C --> U editing sites in plant mitochondrial genomes.
Our method is derived from a machine learning approach known as a genetic algorithm. REGAL (RNA Editing site prediction by Genetic Algorithm Learning) is 87% accurate when tested on three mitochondrial genomes, with an overall sensitivity of 82% and an overall specificity of 91%. REGAL's performance significantly improves on other ab initio approaches to predicting RNA editing sites in this data set. REGAL has a comparable sensitivity and higher specificity than approaches which rely on sequence homology, and it has the advantage that strong sequence conservation is not required for reliable prediction of edit sites.
Our results suggest that ab initio methods can generate robust classifiers of putative edit sites, and we highlight the value of combinatorial approaches as embodied by genetic algorithms. We present REGAL as one approach with the potential to be generalized to other organisms exhibiting C --> U RNA editing.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Genome-wide screening in human and mouse cells using RNA interference and open reading frame over-expression libraries is rapidly becoming a viable experimental approach for many research labs. There ...are a variety of gene expression modulation libraries commercially available, however, detailed and validated protocols as well as the reagents necessary for deconvolving genome-scale gene screens using these libraries are lacking. As a solution, we designed a comprehensive platform for highly multiplexed functional genetic screens in human, mouse and yeast cells using popular, commercially available gene modulation libraries. The Gene Modulation Array Platform (GMAP) is a single microarray-based detection solution for deconvolution of loss and gain-of-function pooled screens.
Experiments with specially constructed lentiviral-based plasmid pools containing ~78,000 shRNAs demonstrated that the GMAP is capable of deconvolving genome-wide shRNA "dropout" screens. Further experiments with a larger, ~90,000 shRNA pool demonstrate that equivalent results are obtained from plasmid pools and from genomic DNA derived from lentivirus infected cells. Parallel testing of large shRNA pools using GMAP and next-generation sequencing methods revealed that the two methods provide valid and complementary approaches to deconvolution of genome-wide shRNA screens. Additional experiments demonstrated that GMAP is equivalent to similar microarray-based products when used for deconvolution of open reading frame over-expression screens.
Herein, we demonstrate four major applications for the GMAP resource, including deconvolution of pooled RNAi screens in cells with at least 90,000 distinct shRNAs. We also provide detailed methodologies for pooled shRNA screen readout using GMAP and compare next-generation sequencing to GMAP (i.e. microarray) based deconvolution methods.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
After the publication of 1, we were alerted to an error in our data. The error was an one-off miscalculation in the extraction of position information for our set of true negatives. Our data set ...should have used randomly selected non-edited cytosines (C) as true negatives, but the data generation phase resulted in a set of nucleotides that were each one nucleotide downstream of known, unedited cytosines. The consequences of this error are reflected in changes to our results, although the general conclusions presented in our original publication remain largely unchanged.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Purpose
The purpose of this study was to assess whether a simple intervention could sustain new hires’ high engagement levels beyond the first six months. This case study illustrates how a simple ...intervention can extend the “job honeymoon“ – a brief period of high engagement – up to a year post hire.
Design/methodology/approach
This study reports the results of a randomized, controlled study in one organization using a “wise intervention,” a method derived from social science research in educational settings.
Findings
This case study illustrates that it is possible to extend the job honeymoon up to a year post-hire. Acknowledging to new hires that transitions are challenging produced a statistically significantly higher sense of belonging and higher employee satisfaction up to 9+ months post-hire.
Research limitations/implications
This work was inspired by research from Gregory M. Walton, and it illustrates the potential value for application in the workplace. However, its generalizability to all organizations will require further study.
Practical implications
This work is most relevant for human resources leaders and managers who want to ensure new hires are well supported. This study found that acknowledging the difficulty of a transition increases the engagement of new team members substantially and likely enhances productivity and team effectiveness for months to come.
Originality/value
The highly counterintuitive but critically important idea of this study is that people need reassurance that transitions might feel hard but are a shared experience. Providing that reassurance is a simple, easy-to-apply approach to support the newest members of a team or organization and sustain their engagement for months to come.
A comprehensive understanding of the molecular vulnerabilities of every type of cancer will provide a powerful roadmap to guide therapeutic approaches. Efforts such as The Cancer Genome Atlas Project ...will identify genes with aberrant copy number, sequence, or expression in various cancer types, providing a survey of the genes that may have a causal role in cancer. A complementary approach is to perform systematic loss-of-function studies to identify essential genes in particular cancer cell types. We have begun a systematic effort, termed Project Achilles, aimed at identifying genetic vulnerabilities across large numbers of cancer cell lines. Here, we report the assessment of the essentiality of 11,194 genes in 102 human cancer cell lines. We show that the integration of these functional data with information derived from surveying cancer genomes pinpoints known and previously undescribed lineage-specific dependencies across a wide spectrum of cancers. In particular, we found 54 genes that are specifically essential for the proliferation and viability of ovarian cancer cells and also amplified in primary tumors or differentially overexpressed in ovarian cancer cell lines. One such gene, PAX8, is focally amplified in 16% of high-grade serous ovarian cancers and expressed at higher levels in ovarian tumors. Suppression of PAX8 selectively induces apoptotic cell death of ovarian cancer cells. These results identify PAX8 as an ovarian lineage-specific dependency. More generally, these observations demonstrate that the integration of genome-scale functional and structural studies provides an efficient path to identify dependencies of specific cancer types on particular genes and pathways.
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