OUP accepted manuscript

Lee, Myunggyo; Lee, Kyubum; Yu, Namhee; Jang, In-Su; Choi, Ikjung; Kim, Pora; Jang, Ye Eun; Kim, Byounggun; Kim, Sunkyu; Lee, Byung-Wook; Kang, Jaewoo

doi:10.1093/nar/gkw1083

Cited by 57 publications

(35 citation statements)

References 25 publications

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“…The difference in percentages of fusions supported by a DNA level alteration likely reflected the sensitivity differences between SNP arrays and DNA sequencing. For benchmarking purposes, we curated a list of 321 known fusions ( Supplementary Table S1 ) by integrating Mitelman ( 13 ), ChimerPub ( 11 ) and Cosmic fusions ( 14 ). We applied the same validation strategies to this list and observed validation rates of 68 and 52%, respectively, for sequencing-based and array-based approaches.…”

Section: Resultsmentioning

confidence: 99%

“…All fusion candidates were subject to six additional filters ( Supplementary Methods ). We integrated three resources including Mitelman ( 13 ), ChimerPub ( 11 ) and Cosmic fusions ( 14 ) to build a positive control fusion list (the white list). Each fusion on the list had support from at least three independent publications, leading to a list of 321 unique gene–gene fusions.…”

Section: Methodsmentioning

confidence: 99%

“…In fact, fusion identification has become a standard analysis performed by every working group for every cancer type included in TCGA ( 6 – 8 ). Our group and others have previously reported pan-cancer analysis of transcript fusion frequencies ( 9 – 11 ). Here, we describe our results on expanding our pan-cancer analysis from 13 to 33 tumor types, including a large cohort of non-neoplastic tissues and whole genome sequencing on >500 cancer samples to validate our findings.…”

Section: Introductionmentioning

confidence: 92%

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TumorFusions: an integrative resource for cancer-associated transcript fusions

Wang

Tang

et al. 2017

Nucleic Acids Research

211

210

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Gene fusion represents a class of molecular aberrations in cancer and has been exploited for therapeutic purposes. In this paper we describe TumorFusions, a data portal that catalogues 20 731 gene fusions detected in 9966 well characterized cancer samples and 648 normal specimens from The Cancer Genome Atlas (TCGA). The portal spans 33 cancer types in TCGA. Fusion transcripts were identified via a uniform pipeline, including filtering against a list of 3838 transcript fusions detected in a panel of 648 non-neoplastic samples. Fusions were mapped to somatic DNA rearrangements identified using whole genome sequencing data from 561 cancer samples as a means of validation. We observed that 65% of transcript fusions were associated with a chromosomal alteration, which is annotated in the portal. Other features of the portal include links to SNP array-based copy number levels and mutational patterns, exon and transcript level expressions of the partner genes, and a network-based centrality score for prioritizing functional fusions. Our portal aims to be a broadly applicable and user friendly resource for cancer gene annotation and is publicly available at http://www.tumorfusions.org.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

See 1 more Smart Citation

TumorFusions: an integrative resource for cancer-associated transcript fusions

Wang

Tang

et al. 2017

Nucleic Acids Research

211

210

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show abstract

“…30 001 and 7992 fusion transcript candidates and their related information were downloaded from the ChimerDB 3.0 ( http://ercsb.ewha.ac.kr/fusiongene , December 2016) ( 16 ) and TCGA fusion Data Portal ( http://54.84.12.177/PanCanFusV2/ , December 2014) ( 17 ), respectively. For the ChimerDB fusion transcripts, we found that 13 729 were derived from TCGA samples.…”

Section: Data Integration and Annotationsmentioning

confidence: 99%

TissGDB: tissue-specific gene database in cancer

Kim¹,

Park²,

Han³

et al. 2017

Nucleic Acids Research

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Tissue-specific gene expression is critical in understanding biological processes, physiological conditions, and disease. The identification and appropriate use of tissue-specific genes (TissGenes) will provide important insights into disease mechanisms and organ-specific therapeutic targets. To better understand the tissue-specific features for each cancer type and to advance the discovery of clinically relevant genes or mutations, we built TissGDB (Tissue specific Gene DataBase in cancer) available at http://zhaobioinfo.org/TissGDB. We collected and curated 2461 tissue specific genes (TissGenes) across 22 tissue types that matched the 28 cancer types of The Cancer Genome Atlas (TCGA) from three representative tissue-specific gene expression resources: The Human Protein Atlas (HPA), Tissue-specific Gene Expression and Regulation (TiGER), and Genotype-Tissue Expression (GTEx). For these 2461 TissGenes, we performed gene expression, somatic mutation, and prognostic marker-based analyses across 28 cancer types using TCGA data. Our analyses identified hundreds of TissGenes, including genes that universally kept or lost tissue-specific gene expression, with other features: cancer type-specific isoform expression, fusion with oncogenes or tumor suppressor genes, and markers for protective or risk prognosis. TissGDB provides seven categories of annotations: TissGeneSummary, TissGeneExp, TissGene-miRNA, TissGeneMut, TissGeneNet, TissGeneProg, TissGeneClin.

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“…In the past, numerous resources have been developed to maintain a wide range of information related to instabilities in genome and chromosomes such as i) TICdb, which contain information about chromosomal translocation breakpoint in human tumors [20], ii) HYBRIDdb, maintains information of hybrid genes in humans [21], iii) dbCRID, contains information about chromosomal rearrangement in diseases [22], iv) chimerDB3.0 is a resource of fusion genes [23] and v) COSMIC is a Catalogue of Somatic Mutations in Cancer [24]. Since the discovery of CFSs, several lines of evidence suggest their involvement in human disease progression, as CFSs are preferred sites for exogenous DNA insertion, chromosomal translocation, re-arrangement, and breakpoint.…”

Section: Introductionmentioning

confidence: 99%

HumCFS: a database of fragile sites in human chromosomes

et al. 2019

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Background: Fragile sites are the chromosomal regions that are susceptible to breakage, and their frequency varies among the human population. Based on the frequency of fragile site induction, they are categorized as common and rare fragile sites. Common fragile sites are sensitive to replication stress and often rearranged in cancer. Rare fragile sites are the archetypal trinucleotide repeats. Fragile sites are known to be involved in chromosomal rearrangements in tumors. Human miRNA genes are also present at fragile sites. A better understanding of genes and miRNAs lying in the fragile site regions and their association with disease progression is required. Result: HumCFS is a manually curated database of human chromosomal fragile sites. HumCFS provides useful information on fragile sites such as coordinates on the chromosome, cytoband, their chemical inducers and frequency of fragile site (rare or common), genes and miRNAs lying in fragile sites. Protein coding genes in the fragile sites were identified by mapping the coordinates of fragile sites with human genome Ensembl (GRCh38/hg38). Genes present in fragile sites were further mapped to DisGenNET database, to understand their possible link with human diseases. Human miRNAs from miRBase was also mapped on fragile site coordinates. In brief, HumCFS provides useful information about 125 human chromosomal fragile sites and their association with 4921 human protein-coding genes and 917 human miRNA's. Conclusion: User-friendly web-interface of HumCFS and hyper-linking with other resources will help researchers to search for genes, miRNAs efficiently and to intersect the relationship among them. For easy data retrieval and analysis, we have integrated standard web-based tools, such as JBrowse, BLAST etc. Also, the user can download the data in various file formats such as text files, gff3 files and Bed-format files which can be used on UCSC browser.

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OUP accepted manuscript

Cited by 57 publications

References 25 publications

TumorFusions: an integrative resource for cancer-associated transcript fusions

TumorFusions: an integrative resource for cancer-associated transcript fusions

TissGDB: tissue-specific gene database in cancer

HumCFS: a database of fragile sites in human chromosomes

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