Bioinformatics Algorithms: Techniques and Applications

ONCOMINE: A RESOURCE FOR META-ANALYSIS 345
FIGURE 15.2 A profile search for “prostate” yields analyses ranked by the percentage of
most significantly dysregulated genes. Each analysis listed contains direct links to heat maps
and lists of genes that are up, down, or differentially regulated.
listed contains study information and the classes of samples that are being compared.
In order to identify potential biomarkers specific for metastatic prostate cancer, we
can filter our list to display cancer versus cancer comparisons. The question we pose
is, which genes are activated in metastatic prostate carcinoma? The analysis begins
with the selection of independent studies where the appropriate sample comparisons
were made to identify genes significantly dysregulated in metastatic prostate cancer
as compared to nonmetastatic prostate cancer.
Within individual profiles listed, the differentially expressed genes are represented
in a heat map (Fig. 15.3). Here, higher level of expression can be noted in the 25
metastatic prostate carcinoma samples relative to the 64 prostate carcinoma samples
in the Yu Study. The most significantly overexpressed gene EIF1X, a eukaryotic transcription
factor, is listed at the top of the heat map reflecting specific over expression
in metastatic prostate adenocarcinoma in this study. This finding alone often drives
additional investigation of genes observed to be overexpressed based on a chosen
significance level. The approach of meta-analysis within Oncomine, takes advantage
of the large population of studies where genes are measured by multiple, heterogeneous
reporters, and microarray platforms within different research organizations to
provide robust validation and focus efforts on the most promising targets.
The next step in meta-analysis is to select the studies to include those genes where
significant differential expression is observed. The top five analyses having the most
differentially expressed genes are selected for inclusion in meta-analysis. Additional
filters can be applied to limit the analysis to a particular functional category such as
“cell cycle” (Fig. 15.4).