DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, GaRyoung | ko |
dc.contributor.author | Lee, Sang Mi | ko |
dc.contributor.author | Lee, Sungyoung | ko |
dc.contributor.author | Jeong, Chang Wook | ko |
dc.contributor.author | Song, Hyojin | ko |
dc.contributor.author | Lee, Sang Yup | ko |
dc.contributor.author | Yun, Hongseok | ko |
dc.contributor.author | Koh, Youngil | ko |
dc.contributor.author | Kim, Hyun Uk | ko |
dc.date.accessioned | 2024-04-11T09:00:12Z | - |
dc.date.available | 2024-04-11T09:00:12Z | - |
dc.date.created | 2024-04-01 | - |
dc.date.issued | 2024-03 | - |
dc.identifier.citation | GENOME BIOLOGY, v.25, no.1 | - |
dc.identifier.issn | 1474-760X | - |
dc.identifier.uri | http://hdl.handle.net/10203/318986 | - |
dc.description.abstract | BackgroundOncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to the large number of metabolites in a cell and the presence of multiple genes associated with cancer development.ResultsHere we report the development of a computational workflow that predicts metabolite-gene-pathway sets. Metabolite-gene-pathway sets present metabolites and metabolic pathways significantly associated with specific somatic mutations in cancers. The computational workflow uses both cancer patient-specific genome-scale metabolic models (GEMs) and mutation data to generate metabolite-gene-pathway sets. A GEM is a computational model that predicts reaction fluxes at a genome scale and can be constructed in a cell-specific manner by using omics data. The computational workflow is first validated by comparing the resulting metabolite-gene pairs with multi-omics data (i.e., mutation data, RNA-seq data, and metabolome data) from acute myeloid leukemia and renal cell carcinoma samples collected in this study. The computational workflow is further validated by evaluating the metabolite-gene-pathway sets predicted for 18 cancer types, by using RNA-seq data publicly available, in comparison with the reported studies. Therapeutic potential of the resulting metabolite-gene-pathway sets is also discussed.ConclusionsValidation of the metabolite-gene-pathway set-predicting computational workflow indicates that a decent number of metabolites and metabolic pathways appear to be significantly associated with specific somatic mutations. The computational workflow and the resulting metabolite-gene-pathway sets will help identify novel oncometabolites and also suggest cancer treatment strategies. | - |
dc.language | English | - |
dc.publisher | BMC | - |
dc.title | Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data | - |
dc.type | Article | - |
dc.identifier.wosid | 001182376700004 | - |
dc.identifier.scopusid | 2-s2.0-85187415502 | - |
dc.type.rims | ART | - |
dc.citation.volume | 25 | - |
dc.citation.issue | 1 | - |
dc.citation.publicationname | GENOME BIOLOGY | - |
dc.identifier.doi | 10.1186/s13059-024-03208-8 | - |
dc.contributor.localauthor | Lee, Sang Yup | - |
dc.contributor.localauthor | Kim, Hyun Uk | - |
dc.contributor.nonIdAuthor | Lee, GaRyoung | - |
dc.contributor.nonIdAuthor | Lee, Sang Mi | - |
dc.contributor.nonIdAuthor | Lee, Sungyoung | - |
dc.contributor.nonIdAuthor | Jeong, Chang Wook | - |
dc.contributor.nonIdAuthor | Song, Hyojin | - |
dc.contributor.nonIdAuthor | Yun, Hongseok | - |
dc.contributor.nonIdAuthor | Koh, Youngil | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Cancer | - |
dc.subject.keywordAuthor | Oncometabolite | - |
dc.subject.keywordAuthor | Genome-scale metabolic model | - |
dc.subject.keywordAuthor | Mutation data | - |
dc.subject.keywordAuthor | RNA-seq | - |
dc.subject.keywordPlus | TRASTUZUMAB RESISTANCE | - |
dc.subject.keywordPlus | BIOMARKER DISCOVERY | - |
dc.subject.keywordPlus | BREAST-CANCER | - |
dc.subject.keywordPlus | MUTANT P53 | - |
dc.subject.keywordPlus | 2-HYDROXYGLUTARATE | - |
dc.subject.keywordPlus | IDENTIFICATION | - |
dc.subject.keywordPlus | FRAMEWORK | - |
dc.subject.keywordPlus | PROGRAM | - |
dc.subject.keywordPlus | BIOLOGY | - |
dc.subject.keywordPlus | PATHWAY | - |
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