Target Discovery and Validation Reviews and Protocols

Molecular Profiling of Breast Cancer 105
but not mutant BRCA1, was able to inhibit estradiol-induced activation of
extracellular signal-regulated kinase as well as the synthesis of cyclins D1 and
B1, the activity of cyclin-dependent kinases Cdk4 and CDK1, and G 1 /S and
G 2 /M cell cycle progression (57).
Differences in mutation frequencies of cancer genes, such as those described
here, highlight the important roles for these genes and associated pathways in
determining the gene expression patterns of the various tumors. Such data allow
us to unveil previously unknown genes that may be involved in tumorigenesis.
Similar variation in expression of a set of genes across a set of samples indicates
similar means of regulation and function; hence, it provides a powerful
way of identifying novel biologically important genes that could be used as
markers and targets for therapy. One such example is ras-related and estrogenregulated
growth inhibitor (RERG) that was identified by its coexpression with
the ER (58). RERG overexpression inhibits growth of tumor cells, and its high
expression is correlated with a favorable prognosis for patients.
5.1.2. Effects of TP53 Mutations on Global Gene Expression
The profound differences (clinical and molecular) among the tumor subtypes
most likely reflect different alterations in molecular pathways within the tumor
cells. TP53 plays an important role in directing cellular responses to genotoxic
damage and regulates the activation of downstream genes that are involved in
apoptosis, cell cycle arrest, and DNA repair (59–61). Previous studies have
shown that mutations in the TP53 gene predict poor prognosis and are associated
with poor response to systemic therapy (62–64). Even though TP53 itself
is not differentially expressed at a detectable level across tumors, it is likely that
TP53 plays a significant role in shaping the gene expression patterns in the various
tumor subtypes. The coding region of the TP53 gene (exons 2–11) was
screened for mutations in all but eight tumor samples (not including benign
tumors or normal breast tissue samples) by using temporal temperature gel
electrophoresis (65). The frequencies of TP53 mutations among the different
subclasses was significantly different (p < 0.001). Luminal subtype A contained
only 16% mutated tumors, whereas the luminal B, ERBB2+, and basal-like subclasses
had 71, 86, and 75% TP53-mutated tumors, respectively (Fig. 5). The
finding of TP53 mutations in tumors that simultaneously expressed the ERBB2
gene at high levels supports previous observations of an interdependent role for
TP53 and ERBB2 (20,66).
To more directly investigate the effect of TP53 mutations on the expression patterns
in these tumors, we searched for genes whose expression was consistently
different between TP53-mutated and TP53-wild type tumors (two-class significance
analysis of microarrays [SAM]); [11]). A list of 158 genes significantly
correlated with TP53 status was selected that showed a median false discovery