Dataset Information

Development of micoRNA expression signatures for invasive ductal breast carcinoma

ABSTRACT: To further develop gene expression approach to miRNA biomarker discovery, we have employed miRNA microarray expression profiling as a discovery platform to identify miRNA with the potential to regulated the gene expression signatures in the process of tumor development. Human FFPE tissues from grade 1, 2 and 3 were used to profile miRNA. The miRNA targeted genes were also studied for expression along with the selected miRNA, from this signature in the same RNA samples by real-time PCR, confirming the selected miRNA has regulatory action on the target gene expression.

ORGANISM(S): Homo sapiens

PROVIDER: GSE51233 | GEO | 2013/09/28

SECONDARY ACCESSION(S): PRJNA221780

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer where cells restricted to the ducts exhibit an atypical phenotype. Some DCIS lesions are believed to rapidly transit to invasive ductal carcinomas (IDCs), while others remain unchanged. Existing classification systems for DCIS fail to identify those lesions that transit to IDC. We studied gene expression patterns of 31 pure DCIS, 36 pure invasive cancers and 42 cases of mixed diagnosis (invasive cancer with an in situ component) using Agilent Whole Human Genome Oligo Microarrays 44k. Six normal breast tissue samples were also included as controls. qRT-PCR was used for validation. All DCIS and invasive samples could be classified into the intrinsic molecular subtypes defined for invasive breast cancer. Hierarchical clustering establishes that samples group by intrinsic subtype, and not by diagnosis. We observed heterogeneity in the transcriptomes among DCIS of high histological grade and identified a distinct subgroup containing seven of the 31 DCIS samples with gene expression characteristics more similar to advanced tumours. A set of genes independent of grade, ER-status and HER2-status was identified by logistic regression that univariately classified a sample as belonging to this distinct DCIS subgroup. qRT-PCR of single markers clearly separated this DCIS subgroup from the other DCIS, and contains samples from several histopathological and intrinsic molecular subtypes. The genes that differentiate between these two types of DCIS suggest several processes related to the re-organisation of the microenvironment. This raises interesting possibilities for identification of DCIS lesions both with and without invasive characteristics, which potentially could be used in clinical assessment of a woman's risk of progression, and lead to improved management that would avoid the current over- and under-treatment of patients. Breast cancer samples, 31 pure DCIS patients, 36 IDC patients, 42 mixed and 6 normal.

Dataset Information

Development of micoRNA expression signatures for invasive ductal breast carcinoma

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets