ArticleOncotarget2016
Comprehensive landscape of subtype-specific coding and non-coding RNA transcripts in breast cancer.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Landscape of circular RNAs in acute myeloid leukemia and their clinical significance.NPJ precision oncology · 2026Article
- Histology image analysis of 13 healthy tissues reveals molecular-histological correlations.Scientific reports · 2025Article
- A cluster-based cell-type deconvolution of spatial transcriptomic data.Nucleic acids research · 2025Article
- A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue.Sensors (Basel, Switzerland) · 2023Article
- Discovery of druggable cancer-specific pathways with application in acute myeloid leukemia.GigaScience · 2022Article
- Article
- Transcriptomic profiling of Indian breast cancer patients revealed subtype-specific mRNA and lncRNA signatures.Frontiers in genetics · 2022Article
- DSCAM-AS1-Driven Proliferation of Breast Cancer Cells Involves Regulation of Alternative Exon Splicing and 3'-End Usage.Cancers · 2020Article
- Identification of lncRNAs associated with early-stage breast cancer and their prognostic implications.Molecular oncology · 2019Article
- Article
- lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis.Genes · 2018Article
- A five-long non-coding RNA signature to improve prognosis prediction of clear cell renal cell carcinoma.Oncotarget · 2017Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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.
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Registered trials
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