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    ABSTRACT: High throughput technologies enable researchers to measure expression levels on a genomic scale. However, the correct and efficient biological interpretation of such voluminous data remains a challenging problem. Many tools have been developed for the analysis of GO terms that are over- or under-represented in a list of differentially expressed genes. However, a previously unexplored aspect is the identification of changes in the way various biological processes interact in a given condition with respect to a reference. Here we present a novel approach that aims at identifying such interactions between biological processes that are significantly different in a given phenotype with respect to normal. The proposed technique uses vector-space representation, SVD-based dimensionality reduction, differential weighting, and bootstrapping to asses the significance of the interactions under the multiple and complex dependencies expected between the biological processes. We illustrate our approach on two real datasets involving breast and lung cancer. More than 88% of the interactions found by our approach were deemed to be correct by an extensive manual review of literature. An interesting subset of such interactions is discussed in detail and shown to have the potential to open new avenues for research in lung and breast cancer.
    IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM 04/2012; · 2.25 Impact Factor
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    ABSTRACT: Staufen1 (STAU1)-mediated mRNA decay (SMD) is an mRNA degradation process in mammalian cells that is mediated by the binding of STAU1 to a STAU1-binding site (SBS) within the 3'-untranslated region (3'-UTR) of target mRNAs. During SMD, STAU1, a double-stranded (ds) RNA-binding protein, recognizes dsRNA structures formed either by intramolecular base pairing of 3'-UTR sequences or by intermolecular base pairing of 3'-UTR sequences with a long-noncoding RNA (lncRNA) via partially complementary Alu elements. Recently, STAU2, a paralog of STAU1, has also been reported to mediate SMD. Both STAU1 and STAU2 interact directly with the ATP-dependent RNA helicase UPF1, a key SMD factor, enhancing its helicase activity to promote effective SMD. Moreover, STAU1 and STAU2 form homodimeric and heterodimeric interactions via domain-swapping. Because both SMD and the mechanistically related nonsense-mediated mRNA decay (NMD) employ UPF1; SMD and NMD are competitive pathways. Competition contributes to cellular differentiation processes, such as myogenesis and adipogenesis, placing SMD at the heart of various physiologically important mechanisms. WIREs RNA 2013. doi: 10.1002/wrna.1168 For further resources related to this article, please visit the WIREs website.
    WIREs RNA 05/2013; · 4.19 Impact Factor
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    ABSTRACT: Epithelial ovarian cancer (EOC) is one of the most lethal gynecological cancers; the majority of EOC is the serous histotype and diagnosed at advanced stage. IL6 is the cytokine that has been found most frequently associated with carcinogenesis and progression of serous EOCs. IL6 is a growth-promoting and anti-apoptotic factor, and high plasma levels of IL6 in advanced stage EOCs correlate with poor prognosis. The objective of the present study was to identify IL6 co-regulated genes and gene network/s in EOCs. We applied bioinformatics tools on 7 publicly available data sets containing the gene expression profiles of 1262 EOC samples. By Pearson's correlation analysis we identified, in EOCs, an IL6-correlated gene signature containing 40 genes mainly associated with proliferation. 33 of 40 genes were also significantly correlated in low malignant potential (LMP) EOCs, while 7 genes, named C5AR1, FPR1, G0S2, IL8, KLF2, MMP19, and THBD were IL6-correlated only in advanced stage EOCs. Among the 40-gene signature EGFR ligand HBEGF, genes of the EGR family members and genes encoding for negative feedback regulators of growth factor signaling were included. The results obtained by Gene Set Enrichment and Ingenuity Pathway Analyses enabled the identification, respectively, of gene sets associated with 'early growth factor response' for the 40-gene signature, and a biological network related to 'thrombosis and cardiovascular disease' for the 7-gene signature. In agreement with these results, selected genes from the identified signatures were validated in vitro by real time RT-PCR in serous EOC cell lines upon stimulation with EGF. Serous EOCs, independently of their aggressiveness, co-regulate IL6 expression together with that of genes associated to growth factor signaling, arguing for the hypothesis that common mechanism/s driven by EGFR ligands characterize both advanced-stage and LMP EOCs. Only advanced-stage EOCs appeared to be characterized by a scenario that involves genes which are so far associated with thrombosis and cardiovascular disease, thus suggesting that this pathway is implicated in the growth and/or spread of more aggressive tumors. We have discovered novel activated signaling pathways that drive the expression of IL6 and of co-regulated genes and are possibly involved in the pathobiology of EOCs.
    BMC Genomics 07/2013; 14(1):508. · 4.40 Impact Factor

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