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pubmed:abstractText |
We used hierarchical clustering to examine gene expression profiles generated by serial analysis of gene expression (SAGE) in a total of nine normal lung epithelial cells and non-small cell lung cancers. Separation of normal and tumor, as well as histopathological subtypes, was evident by using the 3,921 most abundant transcript tags. This distinction remained when only 115 highly differentially expressed tags were used. Furthermore, these 115 transcript tags clustered into groups suggestive of the unique biological and pathological features of the different tissues examined. Adenocarcinomas were characterized by high-level expression of small airway-associated or immunologically related proteins, whereas squamous cell carcinomas overexpressed genes involved in cellular detoxification or antioxidation. The messages of two p53-regulated genes, p21(WAF1/CIP1) and 14-3-3final sigma, were consistently underexpressed in the adenocarcinomas, suggesting that the p53 pathway itself might be compromised in this cancer type. Gene expression patterns observed by SAGE were consistent with results obtained by quantitative real-time PCR or cDNA array analyses by using a total of 43 lung tumor and normal samples. Thus, although derived from only a few tissue libraries, gene expression profiles obtained by using SAGE most likely represent an unbiased yet distinctive molecular signature for the most common forms of human lung cancer.
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