Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이동환 | * |
dc.date.accessioned | 2016-12-27T02:12:21Z | - |
dc.date.available | 2016-12-27T02:12:21Z | - |
dc.date.issued | 2016 | * |
dc.identifier.issn | 1949-2553 | * |
dc.identifier.other | OAK-19864 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/233135 | - |
dc.description.abstract | Molecular classification of breast cancer into clinically relevant subtypes helps improve prognosis and adjuvant-treatment decisions. The aim of this study is to provide a better characterization of the molecular subtypes by providing a comprehensive landscape of subtype-specific isoforms including coding, long non-coding RNA and microRNA transcripts. Isoform-level expression of all coding and non-coding RNAs is estimated from RNA-sequence data of 1168 breast samples obtained from The Cancer Genome Atlas (TCGA) project. We then search the whole transcriptome systematically for subtype-specific isoforms using a novel algorithm based on a robust quasi-Poisson model. We discover 5451 isoforms specific to single subtypes. A total of 27% of the subtype-specific isoforms have better accuracy in classifying the intrinsic subtypes than that of their corresponding genes. We find three subtype-specific miRNA and 707 subtype-specific long non-coding RNAs. The isoforms from long non-coding RNAs also show high performance for separation between Luminal A and Luminal B subtypes with an AUC of 0.97 in the discovery set and 0.90 in the validation set. In addition, we discover 1500 isoforms preferentially co-expressed in two subtypes, including 369 isoforms co-expressed in both Normal-like and Basal subtypes, which are commonly considered to have distinct ER-receptor status. Finally, analyses at protein level reveal four subtype-specific proteins and two subtype co-expression proteins that successfully validate results from the isoform level. | * |
dc.language | English | * |
dc.publisher | IMPACT JOURNALS LLC | * |
dc.subject | breast cancer | * |
dc.subject | RNA sequencing | * |
dc.subject | subtype-specific isoforms | * |
dc.subject | subtype co-expression | * |
dc.subject | non-coding RNAs | * |
dc.title | Comprehensive landscape of subtype-specific coding and non-coding RNA transcripts in breast cancer | * |
dc.type | Article | * |
dc.relation.issue | 42 | * |
dc.relation.volume | 7 | * |
dc.relation.index | SCIE | * |
dc.relation.index | SCOPUS | * |
dc.relation.startpage | 68851 | * |
dc.relation.lastpage | 68863 | * |
dc.relation.journaltitle | ONCOTARGET | * |
dc.identifier.doi | 10.18632/oncotarget.11998 | * |
dc.identifier.wosid | WOS:000387446800089 | * |
dc.author.google | Vu, Trung Nghia | * |
dc.author.google | Pramana, Setia | * |
dc.author.google | Calza, Stefano | * |
dc.author.google | Suo, Chen | * |
dc.author.google | Lee, Donghwan | * |
dc.author.google | Pawitan, Yudi | * |
dc.contributor.scopusid | 이동환(56434427300;58539708000) | * |
dc.date.modifydate | 20231123114357 | * |