Cancer Genetics and Epigenetics 2015, Vol.3, No.12, 1-7
2
SD is the variance of arrays, AVE is the average of
sites. Average gene expression level of multiple arrays
on the same gene is defined as the gene expression
level of gene. Then DEGs are identified by package
“samr” with FDR<=0.05(Tusher et al., 2001; Li and
Tibshirani, 2013). The FDR is calculated based on
Benjamini & Hochberg. At last we distinguish the
DEGs into up-regulated genes and down-regulated
genes (Wu et al., 2014; Zhang et al., 2015).
1.3 Hierarchical clustering analysis
Bidirectional hierarchical clustering analysis is a
computational method that is always used to explore
the relationship of samples. We use Genepattern
(
ttern/) and calculate Euclidean distance to explore
whether the similar samples exist strong relationship.
We use DEGs to make the bidirectional hierarchical
clustering analysis and exhibit the result through
Genepattern(Varley et al., 2013).
1.4 Functional enrichment analysis
In order to identify the function of DEGs, we use
DAVID (
crf .gov/) to explore
whether DEGs are enriched in Gene Ontology (GO)
and Kyoto Encyclopedia of Genes and Genomes
(KEGG) with the FDR 0.05(2008; Okuda et al.,
2008).
1.5 The construction of protein-protein interaction
network
The protein-protein interaction network (PPIN) not
only shows the relationship among different factors,
but also show the function of these factors. In order to
identify the function of DEGs, PPI sub-network is
built by published PPI network. There are a lot of
databases storing the interactions of genes, including
the Biomolecular Interaction Network Database (BIND),
the Biological General Repository for Interaction Data
sets (BioGRID), the Database of Interacting Proteins
(DIP), the Human Protein Reference Database (HPRD),
IntAct, the Molecular IN Teraction database (MINT),
the mammalian PPI database of the Munich
Information Center on Protein Sequences (MIPS),
PDZBase (a PPI database for PDZ-domains) and
Reactome. The background network includes 80,980
edges and 13,361 nodes. We regard red nodes as
up-regulated genes, yellow nodes as down-regulated
genes and grey nodes as other nodes(Isserlin et al.,
2011; Stark et al., 2011; Salwinski et al., 2004; Peri et
al., 2003; Aranda et al., 2010; Licata et al., 2012;
Pagel et al., 2005; Beuming et al., 2005; Yu et al.,
2012; Canturk et al., 2014; Wang et al., 2014).
2 Result
s
2.1 The identification of differentially expressed genes
Four tumor samples and three normal samples are
used to compare in this study. After preprocessing,
12625 arrays are obtained. Then we calculate the
average of arrays and obtain 8305 genes for the
further analysis. Then we use the package “samr” to
calculate the DEGs and obtain 86 DEGs with the FDR
less than 0.05. We distinguish DEGs into 35 up-regulated
genes and 51 down-regulated genes.
2.2 The hierarchical clustering analysis
To measure the similarity of samples, we use
hierarchical clustering analysis to identify the
relationship of tumor samples and norma l
samples (Figure 1). Four tumor samples are clustered
together and three normal samples are clustered
together. The result shows DEGs can distinguish the
tumor samples and normal samples significantly. This
means the pattern in tumor samples or normal samples
exists the similarity and the robustness. This result
provides a possibility for our further analysis.
2.3 The enrichment analysis of DEGs
It is very easy to identify the potential functions and
kegg pathways which DEGs are enriched in by
DAVID (Figure 2). Firstly, we analyze the Biological
Process (BP) which DEGs are enriched in. We find
that DEGs are enriched in 33 GO terms. The GO
terms are mainly involved in response to hormone
stimulus, regulation of hormone levels, response to
endogenous stimulus, male gonad development gonad
development, development of primary male sexual
characteristics and so on. The GO terms show the
relationship between prolactinoma and hormone.
Prolactinoma can influence the sexual development of
male and female and result in maldevelopment.
Next, we analyze Kyoto Encyclopedia of Genes and
Genomes (KEGG) annotation and DEGs are enriched
in 2 KEGG pathways (Table 1). We recognize that
DEGs are mainly enriched in Neuroactive ligand
-receptor interaction and Pathogenic Escherichia coli
infection. Neuroactive ligand-receptor interaction
is potentially correlated with nervous system. The
