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- Menden, MP, et al.
(författare)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Tidskriftsartikel (refereegranskat)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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| 6. |
- Van, T. L., et al.
(författare)
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Simultaneous discovery of cancer subtypes and subtype features by molecular data integration
- 2016
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Ingår i: Bioinformatics. - Oxford : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 32:17, s. 445-454
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Subtyping cancer is key to an improved and more personalized prognosis/treatment. The increasing availability of tumor related molecular data provides the opportunity to identify molecular subtypes in a data-driven way. Molecular subtypes are defined as groups of samples that have a similar molecular mechanism at the origin of the carcinogenesis. The molecular mechanisms are reflected by subtype-specific mutational and expression features. Data-driven subtyping is a complex problem as subtyping and identifying the molecular mechanisms that drive carcinogenesis are confounded problems. Many current integrative subtyping methods use global mutational and/or expression tumor profiles to group tumor samples in subtypes but do not explicitly extract the subtype-specific features. We therefore present a method that solves both tasks of subtyping and identification of subtype-specific features simultaneously. Hereto our method integrates' mutational and expression data while taking into account the clonal properties of carcinogenesis. Key to our method is a formalization of the problem as a rank matrix factorization of ranked data that approaches the subtyping problem as multi-view bi-clustering. Results: We introduce a novel integrative framework to identify subtypes by combining mutational and expression features. The incomparable measurement data is integrated by transformation into ranked data and subtypes are defined as multi-view bi-clusters. We formalize the model using rank matrix factorization, resulting in the SRF algorithm. Experiments on simulated data and the TCGA breast cancer data demonstrate that SRF is able to capture subtle differences that existing methods may miss.
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- Comasco, Erika, 1982-, et al.
(författare)
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Constitutive serotonin transporter reduction resembles maternal separation with regard to stress-related gene expression
- 2019
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Ingår i: ACS Chemical Neuroscience. - : American Chemical Society (ACS). - 1948-7193. ; 10:7, s. 3132-3142
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Tidskriftsartikel (refereegranskat)abstract
- Interactive effects between allelic variants of the serotonin transporter (5-HTT) promoter-linked polymorphic region (5-HTTLPR) and stressors on depression symptoms have been documented, as well as questioned, by meta-analyses. Translational models of constitutive 5-htt reduction and experimentally controlled stressors often led to inconsistent behavioral and molecular findings and often did not include females. The present study sought to investigate the effect of 5-htt genotype, maternal separation, and sex on the expression of stress-related candidate genes in the rat hippocampus and frontal cortex. The mRNA expression levels of Avp, Pomc, Crh, Crhbp, Crhr1, Bdnf, Ntrk2, Maoa, Maob, and Comt were assessed in the hippocampus and frontal cortex of 5-htt± and 5-htt+/+ male and female adult rats exposed, or not, to daily maternal separation for 180 min during the first 2 postnatal weeks. Gene- and brain region-dependent, but sex-independent, interactions between 5-htt genotype and maternal separation were found. Gene expression levels were higher in 5-htt+/+ rats not exposed to maternal separation compared with the other experimental groups. Maternal separation and 5-htt+/− genotype did not yield additive effects on gene expression. Correlative relationships, mainly positive, were observed within, but not across, brain regions in all groups except in non-maternally separated 5-htt+/+ rats. Gene expression patterns in the hippocampus and frontal cortex of rats exposed to maternal separation resembled the ones observed in rats with reduced 5-htt expression regardless of sex. These results suggest that floor effects of 5-htt reduction and maternal separation might explain inconsistent findings in humans and rodents.
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