Journal
CLINICAL CANCER RESEARCH
Volume 17, Issue 17, Pages 5705-5714Publisher
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-11-0196
Keywords
-
Categories
Funding
- Department of Defense [W81XWH-07-1-0306 03]
- Specialized Program of Research Excellence in Lung Cancer [P50CA70907]
- NCI [1R01CA152301-01]
- Cancer Center [CA-16672]
- NIH [5R21DA027592]
- NSF [DMS0907562]
Ask authors/readers for more resources
Purpose: The requirement of frozen tissues for microarray experiments limits the clinical usage of genome-wide expression profiling by using microarray technology. The goal of this study is to test the feasibility of developing lung cancer prognosis gene signatures by using genome-wide expression profiling of formalin-fixed paraffin-embedded (FFPE) samples, which are widely available and provide a valuable rich source for studying the association of molecular changes in cancer and associated clinical outcomes. Experimental Design: We randomly selected 100 Non-Small-Cell lung cancer (NSCLC) FFPE samples with annotated clinical information from the UT-Lung SPORE Tissue Bank. We microdissected tumor area from FFPE specimens and used Affymetrix U133 plus 2.0 arrays to attain gene expression data. After strict quality control and analysis procedures, a supervised principal component analysis was used to develop a robust prognosis signature for NSCLC. Three independent published microarray datasets were used to validate the prognosis model. Results: This study showed that the robust gene signature derived from genome-wide expression profiling of FFPE samples is strongly associated with lung cancer clinical outcomes and can be used to refine the prognosis for stage I lung cancer patients, and the prognostic signature is independent of clinical variables. This signature was validated in several independent studies and was refined to a 59-gene lung cancer prognosis signature. Conclusions: We conclude that genome-wide profiling of FFPE lung cancer samples can identify a set of genes whose expression level provides prognostic information across different platforms and studies, which will allow its application in clinical settings. Clin Cancer Res; 17(17); 5705-14. (C)2011 AACR.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available