miRNA expression data from primary tumors, metastasis and matched normals.
MicroRNAs (miRs) have been recognized as promising biomarkers. It is unknown to what extent tumor-derived miRs are differentially expressed between primary colorectal cancers (pCRCs) and metastatic lesions, and to what extent the expression profiles of tumor tissue differ from the surrounding normal tissue. Next-generation sequencing (NGS) of 220 fresh-frozen samples, including paired primary and metastatic tumor tissue and non-tumorous tissue from 38 patients, revealed expression of 2245 known unique mature miRs and 515 novel candidate miRs. Unsupervised clustering of miR expression profiles of pCRC tissue with paired metastases did not separate the two entities, whereas unsupervised clustering of miR expression profiles of pCRC with normal colorectal mucosa demonstrated complete separation of the tumor samples from their paired normal mucosa. Two hundred and twenty-two miRs differentiated both pCRC and metastases from normal tissue samples (false discovery rate (FDR) <0.05). The highest expressed tumor-specific miRs were miR-21 and miR-92a, both previously described to be involved in CRC with potential as circulating biomarker for early detection. Only eight miRs, 0.5% of the analysed miR transcriptome, were differentially expressed between pCRC and the corresponding metastases (FDR <0.1), consisting of five known miRs (miR-320b, miR-320d, miR-3117, miR-1246 and miR-663b) and three novel candidate miRs (chr 1-2552-5p, chr 8-20656-5p and chr 10-25333-3p). These results indicate that previously unrecognized candidate miRs expressed in advanced CRC were identified using NGS. In addition, miR expression profiles of pCRC and metastatic lesions are highly comparable and may be of similar predictive value for prognosis or response to treatment in patients with advanced CRC.
- 12/11/2015
- 125 samples
- DAC: EGAC00001000181
- Technology: Illumina HiSeq 2000
Data originating from patient samples
The Amsterdam UMC, tumor genome analysis core, allows access to published datasets upon written application and signature of a Data Access Agreement (DAA). In addition, applications to clinical datasets require approval by a Data Access Committee (DAC), who assess whether the proposed work is allowed given patient consent, as well as the scientific purpose. To aid this process we ask you to provide the information below. Requests will be prioritised according to novelty of the research question. Applications with insufficient detail on objectives, justification, and methods/planned analyses are unlikely to be accepted. 1.Reference number for the dataset 2.Full legal name and address of university/institution 3.Name(s) of the Principle Investigator who will use the data: 4.Name(s) and job title(s) of any other investigators who will use the data: 5.Please provide a minimum of one reference to a publication that can be found on PubMed and where the Principle Investigator is an author: 6.How will the data be stored and where will it be stored? 7.What is the proposed study title and what are the objectives and outcomes of the study in which the data will be used 8.Please provide a brief justification or rationale for the proposed study (max 250 words) 9.Please provide a brief description of planned data analyses (max 250 words): 10.Will the results arising from use of the data be used for the creation of products for sale or for any commercial purpose?
Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.
Study ID | Study Title | Study Type |
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EGAS00001001127 | Other |
This table displays only public information pertaining to the files in the dataset. If you wish to access this dataset, please submit a request. If you already have access to these data files, please consult the download documentation.