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A Preliminary Transcriptome Map of Non-Small Cell Lung Cancer

Laboratory of Population Genetics, Center for Cancer Research [T. F., T. D., A. P., R. C., K. B., J. J.], Cancer Genomics Office [R. L. S.], National Cancer Institute, and Center for Information Technology [S. C.], NIH, Bethesda, Maryland 20892; Department of Pathology, Georgetown University Medical Center, Washington, D.C. 20007 [N. A.]; and Department of Pulmonary and Mediastinal Pathology, Armed Forces Institute of Pathology, Washington, D.C. 20306-6000 [W. D. T.]

We constructed a genome-wide transcriptome map of non-small cell lung carcinomas based on gene-expression profiles generated by serial analysis of gene expression (SAGE) using primary tumors and bronchial epithelial cells of the lung. Using the human genome working draft and the public databases, 25,135 nonredundant UniGene clusters were mapped onto unambiguous chromosomal positions. Of the 23,056 SAGE tags that appeared more than once among the nine SAGE libraries, 11,156 tags representing 7,097 UniGene clusters were positioned onto chromosomes. A total of 43 and 55 clusters of differentially expressed genes were observed in squamous cell carcinoma and adenocarcinoma, respectively. The number of genes in each cluster ranged from 18 to 78 in squamous cell carcinomas and from 20 to 165 in adenocarcinomas. The size of these clusters varied from 1.8 Mb to 65.5 Mb in squamous cell carcinomas and from 1.6 Mb to 98.1 Mb in adenocarcinomas. Overall, the clusters with genes over-represented in tumors had an average of 3–4-fold increase in gene expression compared with the normal control. In contrast, clusters of genes with reduced expression had about 50–65% of the gene expression level compared with the normal. Examination of clusters identified in squamous cell lung cancer suggested that 9 of 15 clusters with overexpressed genes and 13 of 28 clusters with underexpressed genes were concordant with previously reported cytogenetic, comparative genomic hybridization or loss of heterozygosity studies. Therefore, at least a portion of the gene clusters identified via the transcriptome map most likely represented the transcriptional or genetic alterations occurred in the tumors. Integrating chromosomal mapping information with gene expression profiles may help reveal novel molecular changes associated with human lung cancer.

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