A major objective of current cancer research is to develop a detailed molec
ular 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 u
sing differential display. The cancer cells lost the expression of many gen
es involved in cell adhesion, communication, and maintenance of cell shape,
while they gained the expression of many synthetic and metabolic enzymes i
mportant for cell proliferation, High-density, membrane-based hybridization
arrays were used to study mRNA expression patterns of these genes in cultu
red cells and archived tumor tissue. Cluster analysis was then used to iden
tify groups of genes, the expression patterns of which correlated with clin
ical 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 clinica
l tumor stage, whereas a forth cluster that included keratin 14 tended to b
e associated with tumor size. Expression levels of these clinically relevan
t gene clusters allowed breast tumors to be grouped into distinct categorie
s. Gene expression fingerprints that include these four gene clusters have
the potential to improve prognostic accuracy and therapeutic outcomes for b
reast cancer patients.