Microarrays for cancer diagnosis and classification

Abstract

Microarray analysis has yet to be widely accepted for diagnosis and classification of human cancers, despite the exponential increase in microarray studies reported in the literature. Among several methods available, a few refined approaches have evolved for the analysis of microarray data for cancer diagnosis. These include class comparison, class prediction and class discovery. Using as examples some of the major experimental contributions recently provided in the field of both hematological and solid tumors, we discuss the steps required to utilize microarray data to obtain general and reliable gene profiles that could be universally used in clinical laboratories. As we show, microarray technology is not only a new tool for the clinical lab but it can also improve the accuracy of the classical diagnostic techniques by suggesting novel tumor-specific markers. We then highlight the importance of publicly available microarray data and the development of their integrated analysis that may fulfill the promise that this new technology holds for cancer diagnosis and classification.