| Experiment ID | EXP00072 |
| Reference | Title: MicroRNA classifiers for predicting prognosis of squamous cell lung cancer. Author: Raponi M, Dossey L, Jatkoe T, Wu X, Chen G, Fan H, Beer DG. Journal: Cancer Res. 2009 Jul 15;69(14):5776-83. doi: 10.1158/0008-5472.CAN-09-0587. Epub 2009 Jul 7. Abstract: Non-small cell lung cancer (NSCLC), which is comprised mainly of adenocarcinomaand squamous cell carcinoma (SCC), is the cause of 80% of all lung cancer deaths in the United States. NSCLC is also associated with a high rate of relapse after clinical treatment and, therefore, requires robust prognostic markers to bettermanage therapy options. The aim of this study was to identify microRNA (miRNA)expression profiles in SCC of the lung that would better predict prognosis. TotalRNA from 61 SCC samples and 10 matched normal lung samples was processed forsmall RNA species and profiled on MirVana miRNA Bioarrays (version 2, Ambion). Weidentified 15 miRNAs that were differentially expressed between normal lung andSCC, including members of the miR-17-92 cluster and its paralogues. We alsoidentified miRNAs, including miR-155 and let-7, which had previously been shownto have prognostic value in adenocarcinoma. Based on cross-fold validationanalyses, miR-146b alone was found to have the strongest prediction accuracy for stratifying prognostic groups at approximately 78%. The miRNA signatures weresuperior in predicting overall survival than a previously described 50-geneprognostic signature. Whereas there was no overlap between the mRNAs targeted by the prognostic miRNAs and the 50-gene expression signature, there was asignificant overlap in the corresponding biological pathways, includingfibroblast growth factor and interleukin-6 signaling. Our data indicate thatmiRNAs may have greater clinical utility in predicting the prognosis of patients with squamous cell lung carcinomas than mRNA-based signatures. PMID: 19584273 |
| Expressiion Profile | Description: miRNA prognostic profiles in lung cancer Organism: Homo sapiens GEO ID: GSE16025 Platform: GPL5106 Number of samples: 71 |
| Design and Sample | Cancer Type: lung cancer Cancer SubType: lung squamous cell carcinoma Cell Line: N/D Experimental Design: cancer vs normal Case Sample: lung squamous cell carcinoma stage I Control Sample: normal lung Num of Case: 37 Num of Control: 10 Quantification Software: Limma Num of miRNAs: 328 |
| Identification | Num of Up: 56 Num of Down: 76 |