Use of cDNA Microarrays to Assess DNA Gene Expression Patterns in Cancer

TLDR: This chapter will provide an overview of the current status of cDNA microarray technology and discuss its potential applications to problems in cancer biology.

Abstract: It is no longer controversial to state that genomic alterations are of fundamental importance in carcinogenesis. However, it remains difficult to determine the spectrum of genomic changes in any given tumor and even more difficult to determine the impact of these changes on gene expression. As a result of progress in the Human Genome Project, significant advances have been made which offer the potential to solve this problem. These techniques utilize human genome maps, cloned resources, and sequence data in conjunction with fluorescence based technologies to enable the genome wide analysis of tumor cells. One such technique, cDNA microarray hybridization1,2, has the potential to provide large scale analysis of gene expression. This novel system for massively parallel cDNA hybridization is based upon robotic printing of DNAs on glass slides and simultaneous two-color fluorescence hybridization. For studies of gene expression, it is possible to utilize the vast resource of arrayed cDNA clones which have been developed as part of the Expressed Sequence Tag (EST) project to produce microarrays containing tens of thousands of genes3–6. When fluorescent probes generated by reverse transcription of tumor cell mRNA are hybridized to the array, the level of expression of every array element is simultaneously determined with respect to a reference probe labeled in a second color. Although the processing of such large quantities of data is challenging in itself, microarray technology will provide a far more detailed picture of gene expression than has previously been possible. The availability of this information has ramifications which will affect virtually all areas of cancer biology. This chapter will provide an overview of the current status of cDNA microarray technology and discuss its potential applications to problems in cancer biology.