A Kaplan-Meier survival analysis of HGSOC patients with <i>PAK4</i> amplification.

<p>HGSOC patients (<i>n</i> = 32) with <i>PAK4</i> amplification have a significantly shorter survival time (<i>P</i> = 0.004) than patients without <i>PAK4</i> amplification (<i>n</i> = 283).</p

Differentially expressed genes concordant between two data sets containing low-malignant-potential (LMP) and high-grade serous carcinoma (HGSOC) samples.

<p>(A) Heatmap of 23 genes differentially expressed between LMP and HGSOC tumors in two independent GEO expression profiles, GSE17308 (9) and GSE9891 (12), organized by median fold change. (B) The “cellular movement, cancer, and cellular development” network is enriched for genes differentially expressed between LMP and HGSOC, as determined by pathway analysis. In both panels, red represents overexpression and green represents underexpression in HGSOC. Genes highlighted in orange are well-known ovarian cancer genes that have been used as biomarkers and targets for drug design.</p

A Systems Biology Comparison of Ovarian Cancers Implicates Putative Somatic Driver Mutations through Protein-Protein Interaction Models

<div><p>Ovarian carcinomas can be aggressive with a high mortality rate (e.g., high-grade serous ovarian carcinomas, or HGSOCs), or indolent with much better long-term outcomes (e.g., low-malignant-potential, or LMP, serous ovarian carcinomas). By comparing LMP and HGSOC tumors, we can gain insight into the mechanisms underlying malignant progression in ovarian cancer. However, previous studies of the two subtypes have been focused on gene expression analysis. Here, we applied a systems biology approach, integrating gene expression profiles derived from two independent data sets containing both LMP and HGSOC tumors with protein-protein interaction data. Genes and related networks implicated by both data sets involved both known and novel disease mechanisms and highlighted the different roles of <i>BRCA1</i> and <i>CREBBP</i> in the two tumor types. In addition, the incorporation of somatic mutation data revealed that amplification of <i>PAK4</i> is associated with poor survival in patients with HGSOC. Thus, perturbations in protein interaction networks demonstrate differential trafficking of network information between malignant and benign ovarian cancers. The novel network-based molecular signatures identified here may be used to identify new targets for intervention and to improve the treatment of invasive ovarian cancer as well as early diagnosis.</p></div

Mutations in genes that significantly differed between low-malignant-potential (LMP) and high-grade serous carcinoma (HGSOC) samples in two data sets, GSE17308 (13) and GSE9891 (16), using gene expression, network, or hub protein analyses.

<p>(A) At least 5% (16/316) of Cancer Genome Atlas HGSOC samples contained one or more mutant versions of 17 genes identified from differential expression, network, or hub protein analyses. (B) The majority of genetic alterations in <i>WWOX</i>, <i>PTEN</i>, and <i>CREBBP</i> in HGSOC samples were homozygous deletions. (C) Amplifications in <i>PAK4</i> and <i>RGS19</i> tended to be mutually exclusive, although this association was not statistically significant (<i>P</i> <0.07). (D) Amplifications in <i>PAK4</i> and <i>RYR1</i> frequently co-occurred (<i>P</i> <0.001).</p

Representative subnetworks that discriminate between low-malignant-potential (LMP) and high-grade serous carcinoma (HGSOC) samples.

<p>(A-I) Subnetworks include genes such as <i>TP53</i>, <i>BRCA1</i>, and <i>MYC</i>, which are mutated in ovarian carcinomas although their expression level is not significantly altered (<i>white nodes</i>). Red nodes indicate overexpression of genes in HGSOC subnetworks, and green nodes indicate underexpression. Abbreviations: cell cycle (CC), cell growth (CG), cell proliferation (CP), cell differentiation (CD), DNA damage (DD), DNA repair (DDR), DNA replication (DRN), regulation of kinase activity (RKA), receptor protein tyrosine kinase signaling pathway (RTKs), positive regulation of metabolic process (PRM), response to drug (RD), response to stress (RS).</p

Cumulative distribution functions of RP scores for different functional classes

These include bidirectional promoters (red, green, blue), non-bidirectional promoters (purple) and unbounded promoters (light blue, pink, light green). Other functional elements are coding regions (aqua), tail-to-tail regions (yellow) and enhancers (maroon). The nonfunctional elements are represented by ancestral repeats (black).<p><b>Copyright information:</b></p><p>Taken from "Prediction-based approaches to characterize bidirectional promoters in the mammalian genome"</p><p>http://www.biomedcentral.com/1471-2164/9/S1/S2</p><p>BMC Genomics 2008;9(Suppl 1):S2-S2.</p><p>Published online 20 Mar 2008</p><p>PMCID:PMC2386062.</p><p></p

An overarching network connecting hub proteins differentially involved in low-malignant-potential (LMP) and high-grade serous carcinoma (HGSOC) samples.

<p>Nodes and edges illustrate the network diagrams of GEO data sets (A) GSE17308 and (B) GSE9891. Each functional complex is represented by a different color. (C) There are 34 hubs that overlap between the two data sets. (D) Additional gene products, highlighted in purple, have the largest number of connections to the 34 concordant hubs, interconnecting all of the hubs except for six orphans.</p

Reproducibility rates for various methods of identifying genes differentially expressed between low-malignant-potential (LMP) and high-grade serous carcinoma (HGSOC) samples in two data sets, GSE17308 (9) and GSE9891 (12).

<p>Genes were selected by: the <i>P</i>-values from t-tests (<i>solid red line</i>); the <i>P</i>-values from Wilcoxon rank-sum tests (<i>dotted red line</i>); mean fold change (FC; <i>solid blue line</i>); median FC (<i>dotted blue line</i>); and random selection (<i>dotted grey line</i>). Reproducibility was defined as the percentage of differentially expressed genes from one data set’s list also included in the other data set’s list.</p

The correlation coefficients of expression levels of <i>BRCA1</i> and interaction partners in low-malignant-potential (LMP) and high-grade serous carcinoma (HGSOC) data sets.

<p>The correlation coefficients of expression levels of <i>BRCA1</i> and interaction partners in low-malignant-potential (LMP) and high-grade serous carcinoma (HGSOC) data sets.</p

RP score cumulative distribution functions for bidirectional promoters in human and mouse

Bidirectional promoters identified from Known Genes (KG), mRNA, and ESTs all yield similar scores in both human and mouse genomes. RP scores were calculated based on genome assemblies hg17 (human) and mm8 (mouse).<p><b>Copyright information:</b></p><p>Taken from "Prediction-based approaches to characterize bidirectional promoters in the mammalian genome"</p><p>http://www.biomedcentral.com/1471-2164/9/S1/S2</p><p>BMC Genomics 2008;9(Suppl 1):S2-S2.</p><p>Published online 20 Mar 2008</p><p>PMCID:PMC2386062.</p><p></p