Multi-omics subtyping of hepatocellular carcinoma patients using a Bayesian network mixture model

Comprehensive molecular characterization of cancer subtypes is essential for predicting clinical outcomes and searching for personalized treatments. We present bnClustOmics, a statistical model and computational tool for multi-omics unsupervised clustering, which serves a dual purpose: Clustering patient samples based on a Bayesian network mixture model and learning the networks of omics variables representing these clusters. The discovered networks encode interactions among all omics variables and provide a molecular characterization of each patient subgroup. We conducted simulation studies that demonstrated the advantages of our approach compared to other clustering methods in the case where the generative model is a mixture of Bayesian networks. We applied bnClustOmics to a hepatocellular carcinoma (HCC) dataset comprising genome (mutation and copy number), transcriptome, proteome, and phosphoproteome data. We identified three main HCC subtypes together with molecular characteristics, some of which are associated with survival even when adjusting for the clinical stage. Cluster-specific networks shed light on the links between genotypes and molecular phenotypes of samples within their respective clusters and suggest targets for personalized treatments

Dose-dependent effects of Allopurinol on human foreskin fibroblast cell and human umbilical vein endothelial cell under hypoxia

Allopurinol, an inhibitor of xanthine oxidase, has been used in clinical trials of patients with cardiovascular and chronic kidney disease. These are two pathologies with extensive links to hypoxia and activation of the transcription factor hypoxia inducible factor (HIF) family. Here we analysed the effects of allopurinol treatment in two different cellular models, and their response to hypoxia. We explored the dose-dependent effect of allopurinol on Human Foreskin Fibroblasts (HFF) and Human Umbilical Vein Endothelial Cells (HUVEC) under hypoxia and normoxia. Under normoxia and hypoxia, high dose allopurinol reduced the accumulation of HIF-1α protein in HFF and HUVEC cells. Allopurinol had only marginal effects on HIF-1α mRNA level in both cellular systems. Interestingly, allopurinol effects over the HIF system were independent of prolyl-hydroxylase activity. Finally, allopurinol treatment reduced angiogenesis traits in HUVEC cells in an in vitro model. Taken together these results indicate that high doses of allopurinol inhibits the HIF system and pro-angiogenic traits in cells

Structural Basis for Broad Neutralization of Hepatitis C Virus Quasispecies

Monoclonal antibodies directed against hepatitis C virus (HCV) E2 protein can neutralize cell-cultured HCV and pseudoparticles expressing envelopes derived from multiple HCV subtypes. For example, based on antibody blocking experiments and alanine scanning mutagenesis, it was proposed that the AR3B monoclonal antibody recognized a discontinuous conformational epitope comprised of amino acid residues 396–424, 436–447, and 523–540 of HCV E2 envelope protein. Intriguingly, one of these segments (436–447) overlapped with hypervariable region 3 (HVR3), a domain that exhibited significant intrahost and interhost genetic diversity. To reconcile these observations, amino-acid sequence variability was examined and homology-based structural modelling of E2 based on tick-borne encephalitis virus (TBEV) E protein was performed based on 413 HCV sequences derived from 18 subjects with chronic hepatitis C. Here we report that despite a high degree of amino-acid sequence variability, the three-dimensional structure of E2 is remarkably conserved, suggesting broad recognition of structural determinants rather than specific residues. Regions 396–424 and 523–540 were largely exposed and in close spatial proximity at the surface of E2. In contrast, region 436–447, which overlaps with HVR3, was >35 Å away, and estimates of buried surface were inconsistent with HVR3 being part of the AR3B binding interface. High-throughput structural analysis of HCV quasispecies could facilitate the development of novel vaccines that target conserved structural features of HCV envelope and elicit neutralizing antibody responses that are less vulnerable to viral escape

Characterization of antigenic variants of hepatitis C virus in immune evasion

<p>Abstract</p> <p>Background</p> <p>Antigenic variation is an effective way by which viruses evade host immune defense leading to viral persistence. Little is known about the inhibitory mechanisms of viral variants on CD4 T cell functions.</p> <p>Results</p> <p>Using sythetic peptides of a HLA-DRB1*15-restricted CD4 epitope derived from the non-structural (NS) 3 protein of hepatitis C virus (HCV) and its antigenic variants and the peripheral blood mononuclear cells (PBMC) from six HLA-DRB1*15-positive patients chronically infected with HCV and 3 healthy subjects, the <it>in vitro </it>immune responses and the phenotypes of CD4⁺CD25⁺cells of chronic HCV infection were investigated. The variants resulting from single or double amino acid substitutions at the center of the core region of the Th1 peptide not only induce failed T cell activation but also simultaneously up-regulate inhibitory IL-10, CD25^-TGF-β⁺Th3 and CD4⁺IL-10⁺Tr1 cells. In contrast, other variants promote differentiation of CD25⁺TGF-β⁺Th3 suppressors that attenuate T cell proliferation.</p> <p>Conclusions</p> <p>Naturally occuring HCV antigenic mutants of a CD4 epitope can shift a protective peripheral Th1 immune response into an inhibitory Th3 and/or Tr1 response. The modulation of antigenic variants on CD4 response is efficient and extensive, and is likely critical in viral persistence in HCV infection.</p

Cancer stem cell metabolism: A potential target for cancer therapy

© 2016 The Author(s). Cancer Stem cells (CSCs) are a unipotent cell population present within the tumour cell mass. CSCs are known to be highly chemo-resistant, and in recent years, they have gained intense interest as key tumour initiating cells that may also play an integral role in tumour recurrence following chemotherapy. Cancer cells have the ability to alter their metabolism in order to fulfil bio-energetic and biosynthetic requirements. They are largely dependent on aerobic glycolysis for their energy production and also are associated with increased fatty acid synthesis and increased rates of glutamine utilisation. Emerging evidence has shown that therapeutic resistance to cancer treatment may arise due to dysregulation in glucose metabolism, fatty acid synthesis, and glutaminolysis. To propagate their lethal effects and maintain survival, tumour cells alter their metabolic requirements to ensure optimal nutrient use for their survival, evasion from host immune attack, and proliferation. It is now evident that cancer cells metabolise glutamine to grow rapidly because it provides the metabolic stimulus for required energy and precursors for synthesis of proteins, lipids, and nucleic acids. It can also regulate the activities of some of the signalling pathways that control the proliferation of cancer cells. This review describes the key metabolic pathways required by CSCs to maintain a survival advantage and highlights how a combined approach of targeting cellular metabolism in conjunction with the use of chemotherapeutic drugs may provide a promising strategy to overcome therapeutic resistance and therefore aid in cancer therapy

mTOR signaling in disease

The target of rapamycin (TOR) is a highly conserved serine/threonine kinase and a central controller of cell growth, metabolism and aging. Mammalian TOR (mTOR) is activated in response to nutrients, growth factors and cellular energy. Dysregulated mTOR signaling has been implicated in major disease. Here we review recent findings on the role of mTOR in cancer, metabolic disorders, neurological diseases, and inflammation