| Experiment ID | EXP00158 |
| Reference | Title: MicroRNA profiling and prediction of recurrence/relapse-free survival in stage I lung cancer. Author: Lu Y, Govindan R, Wang L, Liu PY, Goodgame B, Wen W, Sezhiyan A, Pfeifer J, LiYF, Hua X, Wang Y, Yang P, You M. Journal: Carcinogenesis. 2012 May;33(5):1046-54. doi: 10.1093/carcin/bgs100. Epub 2012 Feb13. Abstract: About 30% stage I non-small cell lung cancer (NSCLC) patients undergoingresection will recur. Robust prognostic markers are required to better managetherapy options. MicroRNAs (miRNAs) are a class of small non-coding RNAs of 19-25nt and play important roles in gene regulation in human cancers. The purpose ofthis study is to identify miRNA expression profiles that would better predictprognosis of stage I NSCLC. MiRNAs extracted from 527 stage I NSCLC patients wereprofiled on the human miRNA expression profiling v2 panel (Illumina). Theexpression profiles were analyzed for their association with cancer subtypes,lung cancer brain metastasis and recurrence/relapse free survival (RFS). MiRNAexpression patterns between lung adenocarcinoma and squamous cell carcinomadiffered significantly with 171 miRNAs, including Let-7 family members andmiR-205. Ten miRNAs associated with brain metastasis were identified includingmiR-145*, which inhibit cell invasion and metastasis. Two miRNA signatures thatare highly predictive of RFS were identified. The first contained 34 miRNAsderived from 357 stage I NSCLC patients independent of cancer subtype, whereasthe second containing 27 miRNAs was adenocarcinoma specific. Both signatures werevalidated using formalin-fixed paraffin embedded and/or fresh frozen tissues inindependent data set with 170 stage I patients. Our findings have importantprognostic or therapeutic implications for the management of stage I lung cancer patients. The identified miRNAs hold great potential as targets forhistology-specific treatment or prevention and treatment of recurrent disease. PMID: 22331473 |
| Expressiion Profile | Description: MicroRNA profiling and prediction of recurrence/relapse-free survival in stage I lung cancer Organism: Homo sapiens GEO ID: GSE29135 Platform: GPL8179 Number of samples: 387 |
| Design and Sample | Cancer Type: lung cancer Cancer SubType: N/D Cell Line: N/D Experimental Design: subtype1 vs substype2 Case Sample: lung squamous cell carcinoma Control Sample: lung adenocarcinoma Num of Case: 112 Num of Control: 209 Quantification Software: Limma Num of miRNAs: 857 |
| Identification | Num of Up: 157 Num of Down: 170 |