ObjectiveGastric cancer is a major gastrointestinal malignancy for which targeted therapies are emerging as treatment options. This study sought to identify the most prevalent molecular targets in gastric cancer and to elucidate systematic patterns of exclusivity and co-occurrence among these targets, through comprehensive genomic analysis of a large panel of gastric cancers.DesignUsing high-resolution single nucleotide polymorphism arrays, copy number alterations were profiled in a panel of 233 gastric cancers (193 primary tumours, 40 cell lines) and 98 primary matched gastric non-malignant samples. For selected alterations, their impact on gene expression and clinical outcome were evaluated.Results22 recurrent focal alterations (13 amplifications and nine deletions) were identified. These included both known targets (FGFR2, ERBB2) and also novel genes in gastric cancer (KLF5, GATA6). Receptor tyrosine kinase (RTK)/RAS alterations were found to be frequent in gastric cancer. This study also demonstrates, for the first time, that these alterations occur in a mutually exclusive fashion, with KRAS gene amplifications highlighting a clinically relevant but previously underappreciated gastric cancer subgroup. FGFR2-amplified gastric cancers were also shown to be sensitive to dovitinib, an orally bioavailable FGFR/VEGFR targeting agent, potentially representing a subtype-specific therapy for FGFR2-amplified gastric cancers.ConclusionThe study demonstrates the existence of five distinct gastric cancer patient subgroups, defined by the signature genomic alterations FGFR2 (9% of tumours), KRAS (9%), EGFR (8%), ERBB2 (7%) and MET (4%). Collectively, these subgroups suggest that at least 37% of gastric cancer patients may be potentially treatable by RTK/RAS directed therapies.

Based on gene expression patterns, we classified gastric cancers into 3 subtypes, and validated these in an independent set of tumors. The subgroups have differences in molecular and genetic features and response to therapy; this information might be used to select specific treatment approaches for patients with gastric cancer.

Purpose: Current classification of head and neck squamous cell carcinomas (HNSCC) based on anatomic site and stage fails to capture biologic heterogeneity or adequately inform treatment.Experimental

The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD (n=40), mild cognitive impairment (MCI, n=36) and control (n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-β (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure.

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Gastrointestinal cancers are frequently associated with chronic inflammation and excessive secretion of IL-6 family cytokines, which promote tumorigenesis through persistent activation of the GP130/JAK/STAT3 pathway. Although tumor progression can be prevented by genetic ablation of Stat3 in mice, this transcription factor remains a challenging therapeutic target with a paucity of clinically approved inhibitors. Here, we uncovered parallel and excessive activation of mTOR complex 1 (mTORC1) alongside STAT3 in human intestinal-type gastric cancers (IGCs). Furthermore, in a preclinical mouse model of IGC, GP130 ligand administration simultaneously activated mTORC1/S6 kinase and STAT3 signaling. We therefore investigated whether mTORC1 activation was required for inflammation-associated gastrointestinal tumorigenesis. Strikingly, the mTORC1-specific inhibitor RAD001 potently suppressed initiation and progression of both murine IGC and colitis-associated colon cancer. The therapeutic effect of RAD001 was associated with reduced tumor vascularization and cell proliferation but occurred independently of STAT3 activity. We analyzed the mechanism of GP130-mediated mTORC1 activation in cells and mice and revealed a requirement for JAK and PI3K activity but not for GP130 tyrosine phosphorylation or STAT3. Our results suggest that GP130-dependent activation of the druggable PI3K/mTORC1 pathway is required for inflammation-associated gastrointestinal tumorigenesis. These findings advocate clinical application of PI3K/mTORC1 inhibitors for the treatment of corresponding human malignancies.

BackgroundThe accomplishment of the various genome sequencing projects resulted in accumulation of massive amount of gene sequence information. This calls for a large-scale computational method for predicting protein localization from sequence. The protein localization can provide valuable information about its molecular function, as well as the biological pathway in which it participates. The prediction of localization of a protein at subnuclear level is a challenging task. In our previous work we proposed an SVM-based system using protein sequence information for this prediction task. In this work, we assess protein similarity with Gene Ontology (GO) and then improve the performance of the system by adding a module of nearest neighbor classifier using a similarity measure derived from the GO annotation terms for protein sequences.ResultsThe performance of the new system proposed here was compared with our previous system using a set of proteins resided within 6 localizations collected from the Nuclear Protein Database (NPD). The overall MCC (accuracy) is elevated from 0.284 (50.0%) to 0.519 (66.5%) for single-localization proteins in leave-one-out cross-validation; and from 0.420 (65.2%) to 0.541 (65.2%) for an independent set of multi-localization proteins. The new system is available at .ConclusionThe prediction of protein subnuclear localizations can be largely influenced by various definitions of similarity for a pair of proteins based on different similarity measures of GO terms. Using the sum of similarity scores over the matched GO term pairs for two proteins as the similarity definition produced the best predictive outcome. Substantial improvement in predicting protein subnuclear localizations has been achieved by combining Gene Ontology with sequence information.

for virus production. Host cell lipid metabolism and plasma membrane microdomains are implicated in the biogenesis of virus envelopes. Several studies have dissected the lipid inventory of purifi ed infl uenza virions ( 9, 10 ), whereas others have demonstrated the requirements for de novo fatty acid and sphingolipid biosynthesis and unique cholesterol compositions for virus production at budding sites (11)(12)(13)(14).In addition to the importance of host cell lipid metabolism for the biogenesis of infl uenza virus envelopes, recent fi ndings suggest a major role for soluble lipid mediators in antiviral responses against infl uenza virus infection in vivo ( 15,16 ). These soluble lipid mediators originate from membrane glycerophospholipids (GPLs) via phospholipase activity, and (to some extent), are metabolized in peroxisomes. For example, ␤ -oxidation in the peroxisome is crucial for the retroconversion of DHA, the precursor of the lipid mediator protectin D1, which prevents nuclear export of infl uenza virus RNAs; protectin D1 production is directly inhibited by infl uenza virus ( 15 ). The role of peroxisomes during infl uenza virus replication is further evident by interaction between infl uenza virus nonstructural protein 1 (NS1) and multifunctional protein 2 (MFP2/HSD17B4), an antiviral protein essential for peroxisomal ␤ -oxidation ( 17 ). Therefore, the collective literature indicates an apparent role for peroxisomes as the initial sites of antiviral signaling ( 18 ). Infl uenza viruses hijack host cell machineries for efficient replication and acquire a host-derived lipid envelope during budding. Recent systems-scale studies have primarily addressed the individual roles of genes ( 1-5 ) and proteins ( 6-8 ) in this process, yet have failed to illustrate how they function together to generate macromolecular precursors Abstract