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cancer, genes, pubmed, data, moonlight, tumor, article, gene, google, scholar, cas, driver, cell, analysis, supplementary, central, expression, breast, oncogenes, fig, types, suppressors, methods, oncogene, chromatin, predicted, samples, identified, biological, mutation, dualrole, molecular, carcinoma, proliferation, information, oncogenic, mutations, suppressor, function, study, nature, mediators, apoptosis, approach, process, promoter, tcga, methylation, number, processes,

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gov/resources-tcga-users/tcga-code-tables/tcga-study-abbreviations uk/pub/project/cancerrxgene/releases/current_release/sanger1018_brainarray_ensemblgene_rma uk/pub/project/cancerrxgene/releases/current_release/cell_lines_details nature portfolio supplementary information files privacy policy org/data/protocol/pancan-mutation-set {\epsilon }}s_i}y_{kj}} }}{{\sqrt additional multi-omics data /β-trcp/β-catenin pathways advertising n-wasp/fak/f-actin }}_{{\mathrm{kj}}}={\mathrm{ increased}} }}_{{\mathrm{kj}}}{\mathrm{ = affected}} }}_{{\mathrm{kj}}}={\mathrm{ decreased}} supplementary software 1 national research council social media nature 489 nature 483 nature io/ reprints incorporating additional data gdc data portal supplementary data 1 supplementary data 3 supplementary data 4 supplementary data 5 supplementary data 6 supplementary data 7 supplementary data 8 supplementary data 9 supplementary data 10 supplementary data 11 supplementary data 12 supplementary data 13 supplementary data 2 supplementary data 14 additional data integration single-cell -omics data data portal xi steven chen reporting summary k-nearest neighbor distances lettres research university folate-coupled enzyme mthfd2 atac-seq data ep300 identifies ep300-r1627w renal clear-cell carcinoma

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         headline:Interpreting pathways to discover cancer driver genes with Moonlight
         description:Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveiling their roles in cancer mechanisms. To this end, we present Moonlight, a tool that incorporates multiple -omics data to identify critical cancer driver genes. With Moonlight, we analyze 8000+ tumor samples from 18 cancer types, discovering 3310 oncogenic mediators, 151 having dual roles. By incorporating additional data (amplification, mutation, DNA methylation, chromatin accessibility), we reveal 1000+ cancer driver genes, corroborating known molecular mechanisms. Additionally, we confirm critical cancer driver genes by analysing cell-line datasets. We discover inactivation of tumor suppressors in intron regions and that tissue type and subtype indicate dual role status. These findings help explain tumor heterogeneity and could guide therapeutic decisions. Identification of cancer driver genes, especially those that can act as tumour suppressors or oncogenes depending on context, remains a challenge. Here, the authors introduce Moonlight, a tool that integrates multi-omic data to address this challenge and identify numerous dual-role cancer genes.
         datePublished:2020-01-03T00:00:00Z
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      headline:Interpreting pathways to discover cancer driver genes with Moonlight
      description:Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveiling their roles in cancer mechanisms. To this end, we present Moonlight, a tool that incorporates multiple -omics data to identify critical cancer driver genes. With Moonlight, we analyze 8000+ tumor samples from 18 cancer types, discovering 3310 oncogenic mediators, 151 having dual roles. By incorporating additional data (amplification, mutation, DNA methylation, chromatin accessibility), we reveal 1000+ cancer driver genes, corroborating known molecular mechanisms. Additionally, we confirm critical cancer driver genes by analysing cell-line datasets. We discover inactivation of tumor suppressors in intron regions and that tissue type and subtype indicate dual role status. These findings help explain tumor heterogeneity and could guide therapeutic decisions. Identification of cancer driver genes, especially those that can act as tumour suppressors or oncogenes depending on context, remains a challenge. Here, the authors introduce Moonlight, a tool that integrates multi-omic data to address this challenge and identify numerous dual-role cancer genes.
      datePublished:2020-01-03T00:00:00Z
      dateModified:2020-01-03T00:00:00Z
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         Cancer genomics
         Oncogenes
         Software
         Science
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         multidisciplinary
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