High-sensitivity array analysis of gene expression for the early detection of disseminated breast tumor cells in peripheral blood.

Early detection is an effective means of reducing cancer mortality. Here, we describe a highly sensitive high-throughput screen that can identify panels of markers for the early detection of solid tumor cells disseminated in peripheral blood. The method is a two-step combination of differential display and high-sensitivity cDNA arrays. In a primary screen, differential display identified 170 candidate marker genes differentially expressed between breast tumor cells and normal breast epithelial cells. In a secondary screen, high-sensitivity arrays assessed expression levels of these genes in 48 blood samples, 22 from healthy volunteers and 26 from breast cancer patients. Cluster analysis identified a group of 12 genes that were elevated in the blood of cancer patients. Permutation analysis of individual genes defined five core genes (P < or = 0.05, permax test). As a group, the 12 genes generally distinguished accurately between healthy volunteers and patients with breast cancer. Mean expression levels of the 12 genes were elevated in 77% (10 of 13) untreated invasive cancer patients, whereas cluster analysis correctly classified volunteers and patients (P = 0.0022, Fisher's exact test). Quantitative real-time PCR confirmed array results and indicated that the sensitivity of the assay (1:2 x 10(8) transcripts) was sufficient to detect disseminated solid tumor cells in blood. Expression-based blood assays developed with the screening approach described here have the potential to detect and classify solid tumor cells originating from virtually any primary site in the body.

Linking gene expression patterns to therapeutic groups in breast cancer.

A major objective of current cancer research is to develop a detailed molecular characterization of tumor cells and tissues that is linked to clinical information. Toward this end, we have identified approximately one-quarter of all genes that were aberrantly expressed in a breast cancer cell line using differential display. The cancer cells lost the expression of many genes involved in cell adhesion, communication, and maintenance of cell shape, while they gained the expression of many synthetic and metabolic enzymes important for cell proliferation. High-density, membrane-based hybridization arrays were used to study mRNA expression patterns of these genes in cultured cells and archived tumor tissue. Cluster analysis was then used to identify groups of genes, the expression patterns of which correlated with clinical information. Two clusters of genes, represented by p53 and maspin, had expression patterns that strongly associated with estrogen receptor status. A third cluster that included HSP-90 tended to be associated with clinical tumor stage, whereas a forth cluster that included keratin 14 tended to be associated with tumor size. Expression levels of these clinically relevant gene clusters allowed breast tumors to be grouped into distinct categories. Gene expression fingerprints that include these four gene clusters have the potential to improve prognostic accuracy and therapeutic outcomes for breast cancer patients.