Combined population dynamics and entropy modelling supports patient stratification in chronic myeloid leukemia

Modelling the parameters of multistep carcinogenesis is key for a better understanding of cancer progression, biomarker identification and the design of individualized therapies. Using chronic myeloid leukemia (CML) as a paradigm for hierarchical disease evolution we show that combined population dynamic modelling and CML patient biopsy genomic analysis enables patient stratification at unprecedented resolution. Linking CD34+ similarity as a disease progression marker to patientderived gene expression entropy separated established CML progression stages and uncovered additional heterogeneity within disease stages. Importantly, our patient data informed model enables quantitative approximation of individual patients’ disease history within chronic phase (CP) and significantly separates “early” from “late” CP. Our findings provide a novel rationale for personalized and genome-informed disease progression risk assessment that is independent and complementary to conventional measures of CML disease burden and prognosis

Using ontology engineering for understanding needs and allocating resources in web-based industrial virtual collaboration systems

In many interactions in cross-industrial and inter-industrial collaboration, analysis and understanding of relative specialist and non-specialist language is one of the most pressing challenges when trying to build multi-party, multi-disciplinary collaboration system. Hence, identifying the scope of the language used and then understanding the relationships between the language entities are key problems. In computer science, ontologies are used to provide a common vocabulary for a domain of interest together with descriptions of the meaning of terms and relationships between them, like in an encyclopedia. These, however, often lack the fuzziness required for human orientated systems. This paper uses an engineering sector business collaboration system (www.wmccm.co.uk) as a case study to illustrate the issues. The purpose of this paper is to introduce a novel ontology engineering methodology, which generates structurally enriched cross domain ontologies economically, quickly and reliably. A semantic relationship analysis of the Google Search Engine Index was devised and evaluated. Using Semantic analysis seems to generate a viable list of subject terms. A social network analysis of the semantically derived terms was conducted to generate a decision support network with rich relationships between terms. The derived ontology was quicker to generate, provided richer internal relationships and relied far less on expert contribution. More importantly, it improved the collaboration matching capability of WMCCM

Dissecting interferon-induced transcriptional programs in human peripheral blood cells

Interferons are key modulators of the immune system, and are central to the control of many diseases. The response of immune cells to stimuli in complex populations is the product of direct and indirect effects, and of homotypic and heterotypic cell interactions. Dissecting the global transcriptional profiles of immune cell populations may provide insights into this regulatory interplay. The host transcriptional response may also be useful in discriminating between disease states, and in understanding pathophysiology. The transcriptional programs of cell populations in health therefore provide a paradigm for deconvoluting disease-associated gene expression profiles.We used human cDNA microarrays to (1) compare the gene expression programs in human peripheral blood mononuclear cells (PBMCs) elicited by 6 major mediators of the immune response: interferons alpha, beta, omega and gamma, IL12 and TNFalpha; and (2) characterize the transcriptional responses of purified immune cell populations (CD4+ and CD8+ T cells, B cells, NK cells and monocytes) to IFNgamma stimulation. We defined a highly stereotyped response to type I interferons, while responses to IFNgamma and IL12 were largely restricted to a subset of type I interferon-inducible genes. TNFalpha stimulation resulted in a distinct pattern of gene expression. Cell type-specific transcriptional programs were identified, highlighting the pronounced response of monocytes to IFNgamma, and emergent properties associated with IFN-mediated activation of mixed cell populations. This information provides a detailed view of cellular activation by immune mediators, and contributes an interpretive framework for the definition of host immune responses in a variety of disease settings

Increased Expression of Cell-Cell Signaling Genes by Stimulated Mononuclear Leukocytes in Patients with Previous Atherothrombotic Stroke A Whole Genome Expression Profile Study

Background/Aims: Inflammation plays an important role in atherosclerosis and stroke. Acute infections are recognized as trigger factors for ischemic stroke. Methods: In this whole genome expression profile study of 15 patients and 15 control subjects, we tested the hypothesis that patients with a history of atherothrombotic stroke show enhanced transcription of inflammatory genes in circulating leukocytes. RNA from unstimulated or lipopolysaccharide (LPS)-stimulated peripheral blood mononuclear cells (PBMCs) was analyzed with Affymetrix U133A GeneChips using a pooling design. Expression of single genes and functional groups of genes was analyzed by global statistical tests. Results: A total of 10,197 probe sets showed positive calls. After correction for multiple testing no single probe set revealed significant differences either without or with LPS stimulation. However, significant global expression differences were found upon LPS stimulation for the group of genes that are involved in cell-cell signaling. Conclusion: LPS stimulation of PBMCs, a condition mimicking bacterial infection, induces differential expression of a group of cell-cell signaling genes in patients with previous atherothrombotic stroke. This finding can be caused by genetic differences between both groups, but acquired risk factors, medication and technical factors may also have contributed to the result. Copyright (C) 2009 S. Karger AG, Base