Construction of a polycystic ovarian syndrome (PCOS) pathway based on the interactions of PCOS-related proteins retrieved from bibliomic data

Abstract

Polycystic ovary syndrome (PCOS) is a complex but frequently occurring endocrine abnormality. PCOS has become one of the leading causes of oligo-ovulatory infertility among premenopausal women. The definition of PCOS remains unclear because of the heterogeneity of this abnormality, but it is associated with insulin resistance, hyperandrogenism, obesity and dyslipidaemia. The main purpose of this study was to identify possible candidate genes involved in PCOS. Several genomic approaches, including linkage analysis and microarray analysis, have been used to look for candidate PCOS genes. To obtain a clearer view of the mechanism of PCOS, we have compiled data from microarray analyses. An extensive literature search identified seven published microarray analyses that utilized PCOS samples. These were published between the year of 2003 and 2007 and included analyses of ovary tissues as well as whole ovaries and theca cells. Although somewhat different methods were used, all the studies employed cDNA microarrays to compare the gene expression patterns of PCOS patients with those of healthy controls. These analyses identified more than a thousand genes whose expression was altered in PCOS patients. Most of the genes were found to be involved in gene and protein expression, cell signaling and metabolism. We have classified all of the 1081 identified genes as coding for either known or unknown proteins. Cytoscape 2.6.1 was used to build a network of protein and then to analyze it. This protein network consists of 504 protein nodes and 1408 interactions among those proteins. One hypothetical protein in the PCOS network was postulated to be involved in the cell cycle. BiNGO was used to identify the three main ontologies in the protein network: molecular functions, biological processes and cellular components. This gene ontology analysis identified a number of ontologies and genes likely to be involved in the complex mechanism of PCOS. These include the insulin receptor signaling pathway, steroid biosynthesis, and the regulation of gonadotropin secretion among others.

Figure 1

The hypothetical PCOS pathway assembled by BioNetBuilder 2.0 in Cytoscape 2.6.1. From the 1081 input genes, only 504 protein nodes and 1408 interactions among those proteins were assembled. Protein-protein interactions identified by the HPRD database (712) are represented in red. Interactions identified by the KEGG database (561) are represented in blue. Interactions from the MINT database (68) are represented in yellow. Interactions from the BIND database (67) are represented in green.

Figure 2

Protein-protein interactions of the hypothetical protein. The HPRD database identified an interaction between the hypothetical protein and cyclin B1. Cyclin B1 interacts with 9 other proteins including geminin, the tumor suppressor protein p53, and cyclin-dependent kinase 6 among others.

Figure 3

Molecular function map. Map of molecular functions associated with PCOS. Darker nodes refer to the significant ontologies of the dataset. The size is proportional to the number of genes that participate in that molecular function.

Figure 4

Protein binding node. The protein binding node is connected to 12 other nodes. The protein binding node is the most significant node because it encompasses 331 genes. Of the 468 genes in the PCOS molecular function network, 339 (72.4%) are involved in protein binding and are thereby linked to other protein nodes such as the transcription factors (34 genes), identical proteins (37 genes), protein dimerization (35 genes), receptors (50 genes), protein complexes (13 genes), cyclins (2 genes), enzymes (24 genes), growth factors (13 genes), follistatins (3 genes), and insulin receptor substrates (3 genes).