PCA is a heterogeneous disease and many molecular methods have been used in the search to determine the mechanism of the development of the disease, and to find new diagnostic and prognostic markers (Hughes et al., 2005
; Quinn et al., 2005
). Our study has demonstrated new genetic networks and biological pathways in both up- and down-regulated gene expression levels. It should be kept in mind that there are certain limits to in silico analysis. Since there are many different genegene interactions resulting from various cellular/experimental conditions, the edges denoted in the network may not represent the actual causal relationship between genes. Moreover, the probe collection on a chip, which necessarily relies on the coverage and the accuracy of both genomic sequences and clone libraries, presents a serious constraint on its detection power (Liu et al., 2007
). Furthermore, confounding factors such as low-abundance potential biomarkers could interfere with several groups of high-abundance proteins in human plasma in which a dynamic concentration range of protein component exists (Cho et al., 2005
Analysis using IPA software revealed 738 up-regulated genes in the progression to PCA. These were 466 network eligible genes and 423 Functions-Pathways eligible genes. Often individual genes were found in multiple categories of functions related to cancer development including cell-to-cell signaling and interaction, cell signaling, cell death, cellular growth and proliferation, andcellular movement.
One important gene network was identified around the IL-1β gene (). This gene has been reported to be a potent modulator of cellular differentiation and a suitable target for anticancer drug design in PCA (Albrecht et al., 2004
). A group of chemokines (CCL20, CCL3, CXCL3, CXCL6, CCL14) were up-regulated around IL-1β. Chemokines and their ligands are considered to have a significant role in tumor angiogenesis and cancer metastasis. CCL3, CXCL3, and CXCL6 were reported before in PCA (Akashi et al., 2006
; Engl et al., 2006
). In particular, CXCL3 were found to be highly up-regulated in our study. Other chemokines (MIP-3, MIP-4, MIP-1A, BCA-1, CC-1, MCP-1, TAFA-5, IP-9, CXCR4) were not identified on this network, but they were up- regulated in our study. The CXCR4 gene was reported as up-regulated in leukemia and PCA before (Savli et al., 2002
; Engl et al., 2006
; Ao et al., 2007
). Akashi et al. showed that the expression of androgen receptor (AR) down-regulates the migratory responses of human PCA cells via chemokine and its receptor systems (Akashi et al., 2006
). AR is an important molecule in the development of a normal prostate and PCA progress (George, 2003
). Amplification of the AR gene has been described in more than 30% of tumors to prior to therapy (Nelson et al., 1999
). Thus, it was reasonable to suppose that chemo-kines and their ligands were highly important in the progression to PCA. Here we present a group of chemokine up-regulation in the most significant gene work of our study.
The SELE gene was a highly up-regulated member of the network around the IL-1β gene. Bhaskar et al. (2003
) found up-regulated SELE levels in another microarray study on PCA. The role of this gene has been described in metastatic prostate tumor cells as well (Dimitroff et al., 2004
). Other adhesion molecules (Selectin P, desmolin, Endothelin1, Endothelin RecA, vimentin, PECAM-1, etc.) were not identified on this network, but they were up-regulated in our study as well.
Three serum amyloid protein coding genes (SAA, SAA1, SAA2) were highly up-regulated in the network around the IL-1β gene. Alterations in the expression of serum amyloid proteins have been linked to many tumors such as osteosarcoma (Kovacevic et al., 2008
), lung cancer (Dai et al., 2007
), renal cell carcinoma (Engwegen et al., 2007
), gastric cancer (Chan et al., 2007
), and choriocarcinoma (Kovacevic et al., 2007). Serum amyloid protein coding genes are not specific markers for any particular type of tumor. We recommend these genes for monitoring disease activity and response to therapy in patients with PCA.
One network was identified around the insulinlike growth factor 1 (IGF-1) gene (). This gene has been linked to PCA before (Abate-Shen and Shen, 2000
). Other growth factors (IGFB7, GHBP, URG, and PDF) were not identified on this network, but they were up-regulated in our study.
Another network was identified around the NFKB gene (). The angiotensin II receptor type 1 gene was highly up-regulated. This gene could also be a good target for the therapy of prostate cancer (Uemura et al., 2006
). Further studies are required to establish the role this gene plays in PCA.
Our study has also demonstrated up-regulated apoptosis related genes (FAS, BIC, PACAP, BFL1) and up-regulated oncogene partners (PET-1, LAF-4, HSP2123-like). FAS is the most conspicuous gene among them. Up-regulated FAS levels were reported in PCA previously (Iacopino et al., 2006
). Well-known oncogenes such as Ras (Konishi, 1992
), or apoptosis related genes such as BCL2 (McDonnell, 1992
) were found in PCA progress previously, but we did not confirm them in this study.
Canonical pathway analysis revealed that "acute phase response" was the most significant signaling pathway modulated by the up-regulated genes in PCA (See Supplementary Figure 1
). Dysregulation of IL-6-type cytokine signaling was reported to contribute to PCA previously (Heinrich et al., 2003
). The genes that we found up-regulated were using the IL1 type cytokine signaling on an extracellular level. Then, interactions were determined among p38 MAPK and c-fos in the nucleus, but it is not easy to determine the pathway that really participated in prostate tumorigenesis since many other pathway members were not detected.
Another significant signaling pathway is hepatic fibrosis/hepatic stellate cell activation (See Supplementary Figure 3
). Changes in prostate-specific antigen levels among cirrhotic patients have been reported before (Kubota et al., 1999
; Akdogan et al., 2002
) but further research is needed to establish whether these genes are new molecular markers or not.
The actin cytoskeleton pathway was highly significant. This pathway has been reported many times in PCA before (Moore et al., 2000
; Papakonstanti et al., 2003
; Wells et al., 2005
; Marelli et al., 2006
). Genes belonging to the coagulation pathway were found to be distinctly up-regulated (See Supplementary Figure 2
). Patients with PCA may have life-threatening coagulation complications due to their disease. The pathophysiology of disseminated intravascular coagulopathy in patients with prostate cancer is not completely understood. Investigators reported coagulation disorders as early or late signs in PCA (Bern, 2005
; Navarro et al., 2006
; Duran and Tannock, 2007
; Shirai and Chaudhary, 2007
). We found highly up-regulated F8, F5, F9, VWF, and F3 gene accumulation around ca-dependent and ca-phospholipid dependent regions of the coagulation pathway. These regions could be the subject of studies to understand the pathophysiology and plan further therapeutic interventions.
Analysis using IPA software revealed that 515 mapped down-regulated genes were detected in the progression to PCA. These were 363 network eligible genes and 342 Functions-Pathways eligible genes. Often individual genes were found in multiple categories of functions related to cell-tocell signaling and interaction, cell signaling, immune response, cancer, cellular growth and proliferation, nucleic acid metabolism, cellular assembly and organization, and connective tissue development and function.
One important down-regulated carcinogenic gene network was identified around the NFKB gene (). We observed some down-regulated genes, ADRA2C, FABP4, and FABP5, which were not reported in cancer progress before. Moreover, five genes belonging to MHC were strictly downregulated in this network (H2-Q10, HLA-A, HLA-C, HLA-F, and HLA-G). Tamura et al. (2007
) observed down-regulation of HLA-A antigen in microarray analysis of hormone-refractory prostate cancer. We report the down-regulation of four genes (H2-Q10, HLA-C, HLA-F, and HLA-G) here for the first time.
Canonical pathway analysis revealed that "antigen presentation" was an important pathway modulated by the down-regulated genes in PCA. Our findings on MHC genes were related to down-regulation of MHC I-α and MHC II-β class genes (See Supplementary Figure 4
Axonal guidance signaling was the most significant down-regulated canonical pathway (See Supplementary Figure 5
). The FGFR3 gene showed the highest value of under-expression. Fibroblast growth factors (FGFs) and their receptors (FGFRs) have a critical function for the development and homeostasis of the human prostate. Imbalance in expression of these factors is associated with malignancy. We found three members of this family (FGFR3, PIK3C2B, and RAC1) to be downregulated. RAC1 and FGFR3 were evaluated in previous studies (Kwabi-Addo et al., 2001
; Gowardhan et al., 2005
; Chaffer et al., 2007
; Wu et al., 2007
), but here we report PIK3C2B gene down-regulation and its relationship to PCA for the first time.Two important gene members of this pathway were down-regulated. K-RAS is not only an oncogene, but also a known target in differentiation therapy of PCA (Benbrahim-Tallaa et al., 2005
). ERBB2 overexpression is important in PCA and our finding is in concordance with previous observations (Liu et al., 2001
; Calvo et al., 2003
; Ullén et al., 2005
). Taken together, two well-known genes, FOS and IL1B, were up-regulated as members of the same pathway as well. Axonal guidance signaling in the progress of PCA needs further investigation.
There are different valuable bioinformatic approaches in the literature to analyze prostate cancer progression. Tomlins et al. (2007
) profiled prostate cancer progression from benign epithelium to metastatic disease. They identified expression signatures, and analyzed these signatures in the context of a compendium of molecular concepts. Their strategy allowed them to make several insights into disease progression. In the present study we analyzed over one thousand altered genes regarding functions and communications using the IPA tool and detected new relationships.
Our data provide not only new networks between the genes for understanding the biologic properties of PCA but also useful common pathway maps for future understanding of disease and construction of new therapeutic targets. Further combined genomic and proteomic studies are necessary to find out more details of the hierarchy and regulation on DNA-RNA-protein levels.