DNA microarrays for assessing ovarian cancer gene expression Izhak Haviv a , Ian G. Campbell b,c, * a Signal Transduction Laboratory, Peter MacCallum Cancer Institute, St. Andrews Place, East Melbourne, Vic. 3002 Australia b VBCRC Cancer Genetics Laboratory, Peter MacCallum Cancer Institute, St. Andrews Place, East Melbourne, Vic. 3002 Australia c Gynecological Cancer Research Centre, Royal Women’s Hospital, Carlton, Vic. 3053 Australia Abstract Although DNA microarray analysis is presented as a revolution in gene expression studies, it is in fact based on the classic technique of Southern DNA hybridisation where a labelled DNA probe is hybridised to single stranded DNA that is bound to a solid support matrix. The truly revolutionary aspect of microarray analysis lies in the fact that, within a given cell population, the expression of tens of thousands of genes, and ultimately the entire genome, can be assayed simultaneously. This capability, when coupled with powerful data analysis software, allows researchers to rapidly compare gene expression between two cell populations. In the cancer field, this enables researchers to compare gene expression between normal and malignant cells and to identify genes that are differentially regulated during cancer development. Microarray data can also be used to categorize tumours on the basis of their molecular profile, which may provide important biological, diagnostic and prognostic information. As little as 5 years ago identifying even a few differentially expressed genes may have taken several years and cost tens of thousands of dollars. Today microarrays can identify ten times the number of candidate genes in just a few months and at a tenth of the cost. Even so, microarray analysis is still in its infancy and the technology is advancing rapidly. There is little doubt that microarrays will revolutionize our ability to quantify the complex changes that occur in gene expression during cancer development. The greatest challenge that lies ahead is how to translate this knowledge into clinically useful diagnostic and therapeutic tools. In this review, we describe the technical aspects of DNA microarray analysis and some of the current and future applications of this technology for analysing gene expression in ovarian cancer. # 2002 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Microarray; Gene expression; Ovarian cancer 1. Ovarian cancer Ovarian cancer is the fifth most common cancer in Australian women, and the second most common cause of cancer death. There has been little change in ovarian cancer incidence in the last five decades, and unfortu- nately, there are a number of significant barriers to improvement in its treatment. Ovarian cancer is not a single disease and is classified on the basis of the cell type of origin. This review will focus on the ovarian cancers that arise from the ovarian surface epithelium, which represent about 90% of ovarian malignancies. The epithelial cancers consist of several major sub-types based on their histological appearance and include serous, mucinous, endometrioid and clear cell types. The difference between these histological types is not trivial and there is good evidence to suggest that they develop via distinct molecular pathways (Obata et al., 1998; Wright et al., 1999). Furthermore, ovarian tumours, which appear to be of similar histology, stage and grade, may differ dramatically in response to treatment suggesting an even greater molecular com- plexity. Insight into the different molecular pathogenesis pathways that give rise to these diverse tumours may lead to treatments that are better tailored for the specific tumour type. 2. Principles of microarray analysis 2.1. Gene expression predicts cell behaviour Each cell type in the body has a different repertoire of genes that are transcribed. In addition, cells respond to different circumstances (such as medical therapies) by * Corresponding author. Tel.:  /61-3-96561803; fax:  /61-3- 96561411. E-mail address: i.campbell@pmci.unimelb.edu.au (I.G. Campbell). Molecular and Cellular Endocrinology 191 (2002) 121  /126 www.elsevier.com/locate/mce 0303-7207/02/$ - see front matter # 2002 Elsevier Science Ireland Ltd. All rights reserved. PII:S0303-7207(02)00063-1