Skip directly to search Skip directly to A to Z list Skip directly to page options Skip directly to site content

NIOSHTIC-2 Publications Search

Search Results

Confirmation of gene expression-based prediction of survival in non-small cell lung cancer.

Authors
Guo-NL; Wan-YW; Tosun-K; Lin-H; Msiska-Z; Flynn-DC; Remick-SC; Vallyathan-V; Dowlati-A; Shi-X; Castranova-V; Beer-DG; Qian-Y
Source
Clin Cancer Res 2008 Dec; 14(24):8213-8220
NIOSHTIC No.
20034852
Abstract
Purpose: it is a critical challenge to determine the risk of recurrence in early stage non-small cell lung cancer (NSCLC) patients. Accurate gene expression signatures are needed to classify patients into high- and low-risk groups to improve the selection of patients for adjuvant therapy. Experimental Design: multiple published microarray data sets were used to evaluate our previously identified lung cancer prognostic gene signature. Expression of the signature genes was further validated with real-time reverse transcription-PCR and Western blot assays of snap-frozen lung cancer tumor tissues. Results: our previously identified 35-gene signature stratified 264 patients with NSCLC into high- and low-risk groups with distinct overall survival rates (P < 0.05, Kaplan-Meier analysis, log-rank tests). The 35-gene signature further stratified patients with clinical stage 1A diseases into poor prognostic and good prognostic subgroups (P = 0.0007, Kaplan-Meier analysis, log-rank tests). This signature is independent of other prognostic factors for NSCLC, including age, sex, tumor differentiation, tumor grade, and tumor stage. The expression of the signature genes was validated with real-time reverse transcription-PCR analysis of lung cancer tumor specimens. Protein expression of two signature genes, TAL2 and ILF3, was confirmed in lung adenocarcinoma tumors by using Western blot analysis. These two biomarkers showed correlated mRNA and protein overexpression in lung cancer development and progression. Conclusions: the results indicate that the identified 35-gene signature is an accurate predictor of survival in NSCLC. It provides independent prognostic information in addition to traditional clinicopathologic criteria.
Keywords
Cancer-rates; Statistical-analysis; Mathematical-models; Treatment; Clinical-diagnosis; Genetic-factors; Genes; Pulmonary-system-disorders; Adenocarcinomas; Tumorigenesis; Tumorigens; Tumors; Lung-cells; Lung-disease; Biological-factors; Biomarkers; Cell-biology; Cellular-function; Cellular-reactions
Contact
Nancy L. Guo, Mary Babb Randolph Cancer Center/Department of Community Medicine, West Virginia University, 1814 HSS, 1 Medical Center Drive, Morgantown, WV 26506-9300
CODEN
CCREF4
Publication Date
20081201
Document Type
Journal Article
Email Address
lguo@hsc.wvu.edu
Fiscal Year
2009
NTIS Accession No.
NTIS Price
Issue of Publication
24
ISSN
1078-0432
NIOSH Division
HELD
Priority Area
Manufacturing
Source Name
Clinical Cancer Research
State
WV
TOP