@article {Yang1610, author = {Yongliang Yang and Pavel Pospisil and Lakshmanan Iyer and S. James Adelstein and Amin Kassis}, title = {Systematic microarray data mining approach useful for identifying cancer imaging targets}, volume = {50}, number = {supplement 2}, pages = {1610--1610}, year = {2009}, publisher = {Society of Nuclear Medicine}, abstract = {1610 Objectives The identification of molecular targets that can be used to develop molecular imaging agents is essential for the accurate diagnosis of human cancer and other disease. Proteins that are overexpressed extracellularly on the cell surface or are membrane-bound are particularly attractive. Methods In the publically accessible cancer genomic microarray Oncomine platform, genes overexpressed in six solid human cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate) cut-off implemented. The identified genes were imported to the Ingenuity Pathway Analysis (IPA) program and enlarged by functional-related entities and biomolecular interaction networks. All genes encoding putative cell-surface or membrane-bound proteins were then filtered, ranked, and prioritized according to the normalized absolute Student t values. Results Between 72 and 398 genes encoding putative cell-surface or membrane-bound proteins were retrieved for the six tumor types. For prostate cancer, for example, 374 entities were retrieved. By manually consulting the identified entities at gene-disease knowledgebase GeneCards and protein-disease knowledgebase iHOP (information hyperlinked over proteins) database, we retrieved several proteins that are already being investigated as radioimaging targets, thereby confirming the effectiveness of our mining strategy. Conclusions The systematic and biologist-friendly approach described is very useful in the discovery of radioimaging targets and for advancing our understanding of the underlying biological mechanisms of human disease.}, issn = {0161-5505}, URL = {https://jnm.snmjournals.org/content/50/supplement_2/1610}, eprint = {https://jnm.snmjournals.org/content}, journal = {Journal of Nuclear Medicine} }