Advances in large-scale technologies in proteomics, such as yeast two-hybrid screening and mass spectrometry, have made it possible to generate large Protein Interaction Networks (PINs). Recent methods for identifying dense sub-graphs in such networks have been based solely on graph theoretic properties. Therefore, there is a need for an approach that will allow us to combine domain-specific knowledge with topological properties to generate functionally relevant sub-graphs from large networks. This article describes two alternative network measures for analysis of PINs, which combine functional information with topological properties of the networks. These measures, called weighted clustering coefficient and weighted average nearest-neighbors degree, use weights representing the strengths of interactions between the proteins, calculated according to their semantic similarity, which is based on the Gene Ontology terms of the proteins. We perform a global analysis of the yeast PIN by systematically comparing the weighted measures with their topological counterparts. To show the usefulness of the weighted measures, we develop an algorithm for identification of functional modules, called SWEMODE (Semantic WEights for MODule Elucidation), that identifies dense sub-graphs containing functionally similar proteins. The proposed method is based on the ranking of nodes, i.e., proteins, according to their weighted neighborhood cohesiveness. The highest ranked nodes are considered as seeds for candidate modules. The algorithm then iterates through the neighborhood of each seed protein, to identify densely connected proteins with high functional similarity, according to the chosen parameters. Using a yeast two-hybrid data set of experimentally determined protein-protein interactions, we demonstrate that SWEMODE is able to identify dense clusters containing proteins that are functionally similar. Many of the identified modules correspond to known complexes or subunits of these complexes.

BackgroundMicroRNAs (miRNAs) constitute a class of small non-coding RNAs that post-transcriptionally regulate genes involved in several key biological processes and thus are involved in various diseases, including cancer. In this study we aimed to identify a miRNA expression signature that could be used to separate between normal and malignant prostate tissues.ResultsNine miRNAs were found to be differentially expressed (p <0.00001). With the exception of two samples, this expression signature could be used to separate between the normal and malignant tissues. A cross-validation procedure confirmed the generality of this expression signature. We also identified 16 miRNAs that possibly could be used as a complement to current methods for grading of prostate tumor tissues.ConclusionsWe found an expression signature based on nine differentially expressed miRNAs that with high accuracy (85%) could classify the normal and malignant prostate tissues in patients from the Swedish Watchful Waiting cohort. The results show that there are significant differences in miRNA expression between normal and malignant prostate tissue, indicating that these small RNA molecules might be important in the biogenesis of prostate cancer and potentially useful for clinical diagnosis of the disease.

Abbreviations:miRNA microRNA qPCR quantitative PCR Research articleNovelty and impact of the paperWe pinpoint to the importance of testing for optimal control genes in miRNA expression studies as we found that the stability of endogenous controls included in the arrays really behave distinctly different. The evaluation and comparison of two applications that is used in stability tests generated practically the same results. AbstractWhen performing qPCR analysis, there is a need for correction of technical variation between experiments. This correction is most commonly performed by using endogenous control genes, which are stably expressed across samples, as reference genes for normal expression in a specific tissue. In microRNA (miRNA) studies, two types of control genes are commonly used and these are small nuclear RNAs and small nucleolar RNAs. In this study, six different endogenous control genes for miRNA studies were investigated in a prostate tissue material from the Swedish WatchfulWaiting cohort. The stability of the controls was investigated using two different software applications, NormFinder and BestKeeper. The results denote RNU24 as the most suitable endogenous control gene for miRNA studies in prostate tissue materials.

BackgroundOverexpression of the human epidermal growth factor receptor (HER) 2 is associated with poor prognosis and shortened survival in breast cancer patients. HER2 is a potent activator of several signaling pathways that support cell survival, proliferation and metabolism. In HER2-positive breast cancer there are most likely unexplored proteins that act directly or indirectly downstream of well established pathways and take part in tumor development and treatment response.MethodsIn order to identify novel copy number variations (CNVs) in HER2-positive breast cancer whole-genome single nucleotide polymorphism (SNP) arrays were used. A PCR-based loss of heterozygosis (LOH) assay was conducted to verify presence of deletion in HER2-positive breast cancer cases but also in HER2 negative breast cancers, cervical cancers and lung cancers. Screening for mutations was performed using single-strand conformation polymorphism (SSCP) followed by PCR sequencing. Protein expression was evaluated with immunohistochemistry (IHC).ResultsA common deletion at chromosome Xq24 was found in 80% of the cases. This locus harbors the gene solute carrier (SLC) family 25A member 43 (SLC25A43) encoding for a mitochondrial transport protein. The LOH assay revealed presence of SLC25A43 deletion in HER2-positive (48%), HER2-negative (9%), cervical (42%) and lung (67%) cancers. HER2-positive tumors with negative or low SLC25A43 protein expression had significantly lower S-phase fraction compared to tumors with medium or high expression (P = 0.024).ConclusionsWe have found deletion in the SLC25A43 gene to be a common event in HER2-positive breast cancer as well as in other cancers. In addition, the SLC25A43 protein expression was shown to be related to S-phase fraction in HER2-positive breast cancer. Our results indicate a possible role of SLC25A43 in HER2-positive breast cancer and support the hypothesis of altered mitochondrial function in cancer.

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