Because these capabilities are under genetic control, the history of a metastasis is characterized by complex gene-expression patterns, which cDNA microarrays are well suited to track. Single-stranded DNA, attached to a chip, hybridizes to cDNAs generated from a cell's RNA. By monitoring hybridization, researchers can simultaneously examine the expression levels of thousands of genes.
Scientists increasingly apply microarrays to cancer diagnosis and prognosis.1 Dozens of studies have correlated gene-expression profiles with the clinical outcomes of various cancers. But relatively few microarray-based publications focus on metastasis.
Several factors underlie the paucity of papers. Since surgeons overwhelmingly excise primary tumors, metastatic specimens are scarce. When available, specimens are hard to separate from their nonmalignant milieu, and many are altered by prior radiation and chemotherapy treatments. Moreover, metastasis and microarrays are, conceptually speaking, an odd couple: Metastasis is a lengthy process generally thought to originate in a single primary-tumor cell; microarrays, in contrast, ...
