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Identifying Potential Tumor Markers and Antigens by Database Mining and Rapid Expression Screening
Author(s) -
William Loging,
Anita Lal,
IMei Siu,
Tania L. Loney,
Carol J. Wikstrand,
Marco A. Marra,
Christa Prange,
Darell D. Bigner,
Robert L. Strausberg,
Gregory J. Riggins
Publication year - 2000
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.138000
Subject(s) - biology , gene , serial analysis of gene expression , antigen , gene expression profiling , database , gene expression , cancer , sage , computational biology , genetics , computer science , physics , nuclear physics
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.

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