Cancer Genetics and Epigenetics 2016, Vol.4, No.2, 1-9
7
Table 1 The result of Cox proportional hazards regression
Gene ID
P value
Regression coefficient
2
0.443
0.069
16
0.003
0.429
20
0.747
0.036
24
0.855
-0.008
25
0.098
0.345
28
0.806
-0.008
26
0.162
0.046
38
0.809
-0.036
41
0.343
0.068
72
0.505
-0.027
105
0.382
0.019
107
0.284
-0.042
130
0.852
0.004
132
0.034
0.373
134
0.397
-0.048
135
0.013
-0.155
136
0.429
-0.053
141
0.861
-0.024
222
0.492
0.030
223
0.524
-0.115
265
0.983
0.001
123
0.281
0.098
293
0.836
0.032
SAM algorithm was used to screen differentially expressed genes between breast tumors and normal samples and
5880 genes were found, including 1715 upregulated and 4165 down-regulated. By GO functional enrichment
analysis we found that these genes were mainly enriched in cell adhesion, biological adhesion, cell-cell signaling,
behavior, regulation of system process, ion transport and many other biological processes. In addition, KEGG
pathway enrichment analysis found that they are significantly enriched in neuroactive ligand-receptor interaction,
cytokine - cytokine receptor interaction, retinol metabolism, drug metabolism, complement and coagulation
cascades, metabolism of xenobiotics by cytochrome P450, steroid hormone biosynthesis and ECM-receptor
interaction. By integrating gene interaction information from these pathways a KEGG pathway network was built
and then the hub nodes of the network were extracted, 32 candidate genes were obtained.
The expression level of 23 genes were obtained from gene expression profiles, by Cox proportional hazards
regression analysis, adjusted for age and stage, 3 genes were found had a significant effect on survival (p < 0.05)
including AARS, ADK, ADORA2A. Wherein, AARS, alanyl-tRNA synthetase was responsible for protein
synthesis and cell viability in a variety of processes involved in tumor genesis. It has been shown to play an
important role in the development of breast cancer; it can modify individual susceptibility of Chinese patients and
was associated with risk of breast cancer
. This confirms the reliability of our results. However,
association between the other two genes with breast cancer risk has not yet been studied; they may be new
prognostic factors or risk genes of breast cancer, so the further analysis and experimental verification of them is
necessary.
Furthermore, these three genes were introduced into multivariate analysis to calculate a risk score for each sample.
According to the value of risk score sample was divided into a high risk group and a low risk group. Survival
analysis was conducted between these two groups and we found that the two groups are different significantly in
outcome. This indicates our subject can divide TCGA breast cancer patients into different prognostic groups; the
method can also be used on other patient data to guide breast cancer treatment.
