Gene expression profiles of lung adenocarcinoma linked to histopathological grading and survival but not to EGF-R status: a microarray study.

ABSTRACT:

Background

Several different gene expression signatures have been proposed to predict response to therapy and clinical outcome in lung adenocarcinoma. Herein, we investigate if elements of published gene sets can be reproduced in a small dataset, and how gene expression profiles based on limited sample size relate to clinical parameters including histopathological grade and EGFR protein expression.

Methods

Affymetrix Human Genome U133A platform was used to obtain gene expression profiles of 28 pathologically and clinically annotated adenocarcinomas of the lung. EGFR status was determined by fluorescent in situ hybridization and immunohistochemistry.

Results

Using unsupervised clustering algorithms, the predominant gene expression signatures correlated with the histopa

SUBMITTER: Neumann J 

PROVIDER: S-EPMC2843676 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature