GEO DataSets

(Submitter supplied) We performed high throughput transcriptome of breast cancer and normal tissues, identifying lincRNA associated molecular subtype with powerful capacity to distinct breast cancer population and predict prognosis. We also identified subtype-specific lincRNAs that may be a useful complement to intrinsic molecular subtype classification when divergence emerges among pathologists.Paired-end transcriptome sequencing were carried out on a cohort of 33 breast tissues from 11 groups including five breast cancer subtypes including luminal A (LA), luminal B (HER2 negative)(LB, HER2-), luminal B (HER2 positive) (LB, HER2+), HER2 and tripple negative breast cancer (TNB), adjacent noncancerous breast tissue (ANT, three samples for each subtype) and the complete normal breast tissues (three samples)

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL9115

33 Samples

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