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Background: The KRAS gene is mutated in about 40% of colorectal cancer (CRC) cases, which has been clinically validated as a predictive mutational marker of intrinsic resistance to anti-EGFR inhibitor (EGFRi) therapy. Since nearly 60% of patients with a wild type KRAS fail to respond to EGFRi combination therapies, there is a need to develop more reliable molecular signatures to better predict response. Here we address the challenge of adapting a gene expression signature predictive of RAS pathway activation, created using fresh frozen (FF) tissues, for use with more widely available formalin fixed paraffin-embedded (FFPE) tissues. Methods: In this study, we evaluated the translation of an 18-gene RAS pathway signature score from FF to FFPE in 54 CRC cases, using a head-to-head comparison of five technology platforms. FFPE-based technologies included the Affymetrix GeneChip (Affy), NanoString nCounter™ (NanoS), Illumina whole genome RNASeq (RNA-Acc), Illumina targeted RNASeq (t-RNA), and Illumina stranded Total RNA-rRNA-depletion (rRNA). Results: Using Affy_FF as the "gold" standard, initial analysis of the 18-gene RAS scores on all 54 samples shows varying pairwise Spearman correlations, with (1) Affy_FFPE (r = 0.233, p = 0.090); (2) NanoS_FFPE (r = 0.608, p < 0.0001); (3) RNA-Acc_FFPE (r = 0.175, p = 0.21); (4) t-RNA_FFPE (r = −0.237, p = 0.085); (5) and t-RNA (r = −0.012, p = 0.93). These results suggest that only NanoString has successful FF to FFPE translation. The subsequent removal of identified "problematic" samples (n = 15) and genes (n = 2) further improves the correlations of Affy_FF with three of the five technologies: Affy_FFPE (r = 0.672, p < 0.0001); NanoS_FFPE (r = 0.738, p < 0.0001); and RNA-Acc_FFPE (r = 0.483, p = 0.002). Conclusions: Of the five technology platforms tested, NanoString technology provides a more faithful translation of the RAS pathway gene expression signature from FF to FFPE than the Affymetrix GeneChip and multiple RNASeq technologies. Moreover, NanoString was the most forgiving technology in the analysis of samples with presumably poor RNA quality. Using this approach, the RAS signature score may now be reasonably applied to FFPE clinical samples. [ABSTRACT FROM AUTHOR]

Background: A comprehensive network-based understanding of molecular pathways abnormally altered in glioblastoma multiforme (GBM) is essential for developing effective therapeutic approaches for this deadly disease. Methodology/Principal Findings: Applying a next generation sequencing technology, massively parallel signature sequencing (MPSS), we identified a total of 4535 genes that are differentially expressed between normal brain and GBM tissue. The expression changes of three up-regulated genes, CHI3L1, CHI3L2, and FOXM1, and two down-regulated genes, neurogranin and L1CAM, were confirmed by quantitative PCR. Pathway analysis revealed that TGF- β pathway related genes were significantly up-regulated in GBM tumor samples. An integrative pathway analysis of the TGF β signaling network identified two alternative TGF- β signaling pathways mediated by SOX4 (sex determining region Y-box 4) and TGFBI (Transforming growth factor beta induced). Quantitative RT-PCR and immunohistochemistry staining demonstrated that SOX4 and TGFBI expression is elevated in GBM tissues compared with normal brain tissues at both the RNA and protein levels. In vitro functional studies confirmed that TGFBI and SOX4 expression is increased by TGF- β stimulation and decreased by a specific inhibitor of TGF- β receptor 1 kinase. Conclusions/Significance: Our MPSS database for GBM and normal brain tissues provides a useful resource for the scientific community. The identification of non-SMAD mediated TGF- β signaling pathways acting through SOX4 and TGFBI (GENE ID:7045) in GBM indicates that these alternative pathways should be considered, in addition to the canonical SMAD mediated pathway, in the development of new therapeutic strategies targeting TGF- β signaling in GBM. Finally, the construction of an extended TGF- β signaling network with overlaid gene expression changes between GBM and normal brain extends our understanding of the biology of GBM. [ABSTRACT FROM AUTHOR]

The identification, purification and characterization of cancer stem cells (CSCs) holds tremendous promise for improving the treatment of cancer. Mounting evidence is demonstrating that only certain tumour cells (i.e. the CSCs) can give rise to tumours when injected and that these purified cell populations generate heterogeneous tumours. While the cell of origin is still not determined definitively, specific molecular markers for populations containing these CSCs have been found for leukaemia, brain cancer and breast cancer, among others. Systems approaches, particularly molecular profiling, have proven to be of great utility for cancer diagnosis and characterization. These approaches also hold significant promise for identifying distinctive properties of the CSCs, and progress is already being made. [ABSTRACT FROM AUTHOR]

The DNA-binding domain of Drosophila c-Myb protein has been studied using different spectroscopic probes, namely CD, fluorescence, acrylamide quenching and NMR, to determione the structure of some of its sub-domains and their relative stabilities in aqueous solutions. While CD and fluorescence spectroscopy showed that the protein had completely lost its tertiary and secondary structures in approximately 3 M urea, solvent accessibility of the tryptophan residues was still partial, as determined by acrylamide quenching. This suggested the presence of significant amounts of residual structure which persisted until the urea concentration was raised to approximately 6.0 M. Thermal-denaturation experiments also indicated the presence of an intermediate in the unfolding pathway. The experimental data could be fitted assuming a minimum of three states in both modes of denaturation. The thermodynamic parameters for the apparent three-state transition have been determined. From the protein stability curve, we have determined that Drosophila melanogaster Myb R123 has maximal stability at 16°C and pH 7.0. [ABSTRACT FROM AUTHOR]

Presents a letter to the editor about the analysis of the gene-dense major histocompatibility complex class III region and its comparison to mouse.

Prior work using lymphoblast DNA prepared from 192 subjects from the Iowa Adoption Studies (IAS) demonstrated that decreased MAOA promoter methylation was associated with lifetime symptom count for nicotine dependence (ND) and provided suggestive evidence that the amount of methylation is genotype dependent. In the current investigation, we replicate and extend these prior findings in three ways using another 289 IAS subjects and the same methodologies. First, we show that methylation is dependent on current smoking status. Second, we introduce a factor analytic approach to DNA methylation, highlighting three distinct regions of the promoter that may function in somewhat different ways for males and females. Third, we directly compare the methylation signatures in DNA prepared from whole blood and lymphoblasts from a subset of these subjects and provide suggestive evidence favoring the use of lymphoblast DNA. We conclude that smoking reliably decreases MAOA methylation, but exact characterization of effects on level of methylation depend on genotype, smoking history, current smoking status, gender, and region of the promoter-associated CpG Island examined., ((c) 2009 Wiley-Liss, Inc.)

The National Institutes of Health Mammalian Gene Collection (MGC) Program is a multiinstitutional effort to identify and sequence a cDNA clone containing a complete ORF for each human and mouse gene. ESTs were generated from libraries enriched for full-length cDNAs and analyzed to identify candidate full-ORF clones, which then were sequenced to high accuracy. The MGC has currently sequenced and verified the full ORF for a nonredundant set of >9,000 human and >6,000 mouse genes. Candidate full-ORF clones for an additional 7,800 human and 3,500 mouse genes also have been identified. All MGC sequences and clones are available without restriction through public databases and clone distribution networks (see http:mgc.nci.nih.gov).