Identifying Potential Tumor Markers and Antigens by Database Mining and Rapid Expression Screening

Abstract

Genes expressed specifically in malignant tissue may have potential as therapeutic targets but have been difficult to locate for most cancers. The information hidden within certain public databases can reveal RNA transcripts specifically expressed in transformed tissue. To be useful, database information must be verified and a more complete pattern of tissue expression must be demonstrated. We tested database mining plus rapid screening by fluorescent-PCR expression comparison (F-PEC) as an approach to locate candidate brain tumor antigens. Cancer Genome Anatomy Project (CGAP) data was mined for genes highly expressed in glioblastoma multiforme. From 13 mined genes, seven showed potential as possible tumor markers or antigens as determined by further expression profiling. Now that large-scale expression information is readily available for many of the commonly occurring cancers, other candidate tumor markers or antigens could be located and evaluated with this approach.[The expression data described in this paper have been submitted to the NCBI SAGEmap database under library name SAGE_Duke_GBM_H1110, SAGE_pooled_GBM, SAGE_BB542_whitematter, and SAGE_normal_pool(6th).]