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- W2885991505 abstract "Abstract Triple-negative breast cancers (TNBC) lack estrogen and progesterone receptors and HER2 amplification, and are resistant to therapies that target these receptors. Tumors from TNBC patients are heterogeneous based on genetic variations, tumor histology, and clinical outcomes. We used high throughput genomic data for TNBC patients (n = 137) from TCGA to characterize inter-tumor heterogeneity. Similarity network fusion (SNF)-based integrative clustering combining gene expression, miRNA expression, and copy number variation, revealed three distinct patient clusters. Integrating multiple types of data resulted in more distinct clusters than analyses with a single datatype. Whereas most TNBCs are classified by PAM50 as basal subtype, one of the clusters was enriched in the non-basal PAM50 subtypes, exhibited more aggressive clinical features and had a distinctive signature of oncogenic mutations, miRNAs and expressed genes. Our analyses provide a new classification scheme for TNBC based on multiple omics datasets and provide insight into molecular features that underlie TNBC heterogeneity." @default.
- W2885991505 created "2018-08-22" @default.
- W2885991505 creator A5016023951 @default.
- W2885991505 creator A5034147737 @default.
- W2885991505 creator A5046514514 @default.
- W2885991505 creator A5061666775 @default.
- W2885991505 date "2018-08-07" @default.
- W2885991505 modified "2023-10-11" @default.
- W2885991505 title "Integrative analysis of the inter-tumoral heterogeneity of triple-negative breast cancer" @default.
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- W2885991505 doi "https://doi.org/10.1038/s41598-018-29992-5" @default.
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- W2885991505 hasPublicationYear "2018" @default.
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