The inflammatory signalling mediator TAK1 mediates lymphocyte recruitment to lipopolysaccharide-activated murine mesenchymal stem cells through interleukin-6

As a response to pro-inflammatory signals mesenchymal stem cells (MSCs) secrete agents and factors leading to lymphocyte recruitment, counteracting inflammation, and stimulating immunosuppression. On a molecular level, the signalling mediator TGF-β-activated kinase 1 (TAK1) is activated by many pro-inflammatory signals, plays a critical role in inflammation and regulates innate and adaptive immune responses as well. While the role of TAK1 as a signalling factor promoting inflammation is well documented, we also considered a role for TAK1 in anti-inflammatory actions exerted by activated MSCs. We, therefore, investigated the capacity of lipopolysaccharide (LPS)-treated murine MSCs with lentivirally modulated TAK1 expression levels to recruit lymphocytes. TAK1 downregulated by lentiviral vectors expressing TAK1 shRNA in murine MSCs interfered with the capacity of murine MSCs to chemoattract lymphocytes, indeed. Analysing a pool of 84 secreted factors we found that among 26 secreted cytokines/factors TAK1 regulated expression of one cytokine in LPS-activated murine MSCs in particular: interleukin-6 (IL-6). IL-6 in LPS-treated MSCs was responsible for lymphocyte recruitment as substantiated by neutralizing antibodies. Our studies, therefore, suggest that in LPS-treated murine MSCs the inflammatory signalling mediator TAK1 may exert anti-inflammatory properties via IL-6

Age-Specific Epigenetic Drift in Late-Onset Alzheimer's Disease

Despite an enormous research effort, most cases of late-onset Alzheimer's disease (LOAD) still remain unexplained and the current biomedical science is still a long way from the ultimate goal of revealing clear risk factors that can help in the diagnosis, prevention and treatment of the disease. Current theories about the development of LOAD hinge on the premise that Alzheimer's arises mainly from heritable causes. Yet, the complex, non-Mendelian disease etiology suggests that an epigenetic component could be involved. Using MALDI-TOF mass spectrometry in post-mortem brain samples and lymphocytes, we have performed an analysis of DNA methylation across 12 potential Alzheimer's susceptibility loci. In the LOAD brain samples we identified a notably age-specific epigenetic drift, supporting a potential role of epigenetic effects in the development of the disease. Additionally, we found that some genes that participate in amyloid-β processing (PSEN1, APOE) and methylation homeostasis (MTHFR, DNMT1) show a significant interindividual epigenetic variability, which may contribute to LOAD predisposition. The APOE gene was found to be of bimodal structure, with a hypomethylated CpG-poor promoter and a fully methylated 3′-CpG-island, that contains the sequences for the ε4-haplotype, which is the only undisputed genetic risk factor for LOAD. Aberrant epigenetic control in this CpG-island may contribute to LOAD pathology. We propose that epigenetic drift is likely to be a substantial mechanism predisposing individuals to LOAD and contributing to the course of disease

High-throughput detection of fusion genes in cancer using the Sequenom MassARRAY platform

Fusion genes have pivotal roles in the development and progression of human cancer and offer potential for rational drug design. Massively parallel sequencing has identified a panoply of in-frame expressed fusion genes, but early reports suggest that the majority of these are present at very low prevalence or are private events. Conventional methods for the identification of recurrent expressed fusion genes in large cohorts of cancers (eg fluorescence in situ hybridization (FISH) and reverse transcriptase PCR (RT-PCR)) are time consuming and prone to artifacts. Here, we describe a novel high-throughput strategy for the detection of recurrent fusion genes in cancer based on the Sequenom MassARRAY platform. Fusion genes were initially identified by massively parallel sequencing of breast cancer cell lines. For each fusion gene, two Sequenom probes were designed. Primary human breast cancers and cancer cell lines were interrogated for 10 fusion genes. Sensitivity, specificity, and predictive values of the MassARRAY method were then determined using FISH and qRT-PCR as the 'gold standard.' By combining two probes per fusion gene, the negative and positive predictive values were 100 and 71.4%, respectively. All fusion genes identified by massively parallel sequencing were accurately detected. No recurrent fusion genes were found. The MassARRAY-based approach described here may, therefore, be employed as a high-throughput screening tool for known fusion genes in human cancer. In keeping with other highly sensitive assays, further refinement of this technique is necessary to reduce the number of false-positive results. Laboratory Investigation (2011) 91, 1491-1501; doi:10.1038/labinvest.2011.110; published online 1 August 201