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FusionGDB: fusion gene annotation DataBase
Gene fusion is one of the hallmarks of cancer genome via chromosomal rearrangement initiated by DNA double-strand breakage. To date, many fusion genes (FGs) have been established as important biomarkers and therapeutic targets in multiple cancer types. To better understand the function of FGs in can...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323909/ https://www.ncbi.nlm.nih.gov/pubmed/30407583 http://dx.doi.org/10.1093/nar/gky1067 |
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author | Kim, Pora Zhou, Xiaobo |
author_facet | Kim, Pora Zhou, Xiaobo |
author_sort | Kim, Pora |
collection | PubMed |
description | Gene fusion is one of the hallmarks of cancer genome via chromosomal rearrangement initiated by DNA double-strand breakage. To date, many fusion genes (FGs) have been established as important biomarkers and therapeutic targets in multiple cancer types. To better understand the function of FGs in cancer types and to promote the discovery of clinically relevant FGs, we built FusionGDB (Fusion Gene annotation DataBase) available at https://ccsm.uth.edu/FusionGDB. We collected 48 117 FGs across pan-cancer from three representative fusion gene resources: the improved database of chimeric transcripts and RNA-seq data (ChiTaRS 3.1), an integrative resource for cancer-associated transcript fusions (TumorFusions), and The Cancer Genome Atlas (TCGA) fusions by Gao et al. For these ∼48K FGs, we performed functional annotations including gene assessment across pan-cancer fusion genes, open reading frame (ORF) assignment, and retention search of 39 protein features based on gene structures of multiple isoforms with different breakpoints. We also provided the fusion transcript and amino acid sequences according to multiple breakpoints and transcript isoforms. Our analyses identified 331, 303 and 667 in-frame FGs with retaining kinase, DNA-binding, and epigenetic factor domains, respectively, as well as 976 FGs lost protein-protein interaction. FusionGDB provides six categories of annotations: FusionGeneSummary, FusionProtFeature, FusionGeneSequence, FusionGenePPI, RelatedDrug and RelatedDisease. |
format | Online Article Text |
id | pubmed-6323909 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63239092019-01-10 FusionGDB: fusion gene annotation DataBase Kim, Pora Zhou, Xiaobo Nucleic Acids Res Database Issue Gene fusion is one of the hallmarks of cancer genome via chromosomal rearrangement initiated by DNA double-strand breakage. To date, many fusion genes (FGs) have been established as important biomarkers and therapeutic targets in multiple cancer types. To better understand the function of FGs in cancer types and to promote the discovery of clinically relevant FGs, we built FusionGDB (Fusion Gene annotation DataBase) available at https://ccsm.uth.edu/FusionGDB. We collected 48 117 FGs across pan-cancer from three representative fusion gene resources: the improved database of chimeric transcripts and RNA-seq data (ChiTaRS 3.1), an integrative resource for cancer-associated transcript fusions (TumorFusions), and The Cancer Genome Atlas (TCGA) fusions by Gao et al. For these ∼48K FGs, we performed functional annotations including gene assessment across pan-cancer fusion genes, open reading frame (ORF) assignment, and retention search of 39 protein features based on gene structures of multiple isoforms with different breakpoints. We also provided the fusion transcript and amino acid sequences according to multiple breakpoints and transcript isoforms. Our analyses identified 331, 303 and 667 in-frame FGs with retaining kinase, DNA-binding, and epigenetic factor domains, respectively, as well as 976 FGs lost protein-protein interaction. FusionGDB provides six categories of annotations: FusionGeneSummary, FusionProtFeature, FusionGeneSequence, FusionGenePPI, RelatedDrug and RelatedDisease. Oxford University Press 2019-01-08 2018-11-08 /pmc/articles/PMC6323909/ /pubmed/30407583 http://dx.doi.org/10.1093/nar/gky1067 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Kim, Pora Zhou, Xiaobo FusionGDB: fusion gene annotation DataBase |
title | FusionGDB: fusion gene annotation DataBase |
title_full | FusionGDB: fusion gene annotation DataBase |
title_fullStr | FusionGDB: fusion gene annotation DataBase |
title_full_unstemmed | FusionGDB: fusion gene annotation DataBase |
title_short | FusionGDB: fusion gene annotation DataBase |
title_sort | fusiongdb: fusion gene annotation database |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323909/ https://www.ncbi.nlm.nih.gov/pubmed/30407583 http://dx.doi.org/10.1093/nar/gky1067 |
work_keys_str_mv | AT kimpora fusiongdbfusiongeneannotationdatabase AT zhouxiaobo fusiongdbfusiongeneannotationdatabase |