BackgroundFunctional and molecular integrity of cardiomyocytes (CMs) derived from induced pluripotent stem (iPS) cells is essential for their use in tissue repair, disease modelling and drug screening. In this study we compared global transcriptomes of beating clusters (BCs) microdissected from differentiating human iPS cells and embryonic stem (ES) cells.ResultsHierarchical clustering and principal component analysis revealed that iPS-BCs and ES-BCs cluster together, are similarly enriched for cardiospecific genes and differ in expression of only 1.9% of present transcripts. Similarly, sarcomeric organization, electrophysiological properties and calcium handling of iPS-CMs were indistinguishable from those of ES-CMs. Gene ontology analysis revealed that among 204 genes that were upregulated in iPS-BCs vs ES-BCs the processes related to extracellular matrix, cell adhesion and tissue development were overrepresented. Interestingly, 47 of 106 genes that were upregulated in undifferentiated iPS vs ES cells remained enriched in iPS-BCs vs ES-BCs. Most of these genes were found to be highly expressed in fibroblasts used for reprogramming and 34% overlapped with the recently reported iPS cell-enriched genes.ConclusionsThese data suggest that iPS-BCs are transcriptionally highly similar to ES-BCs. However, iPS-BCs appear to share some somatic cell signature with undifferentiated iPS cells. Thus, iPS-BCs may not be perfectly identical to ES-BCs. These minor differences in the expression profiles may occur due to differential cellular composition of iPS-BCs and ES-BCs, due to retention of some genetic profile of somatic cells in differentiated iPS cell-derivatives, or both.

Dendritic cells are able to take up exogenous Ags and present Ag-derived peptides on MHC class I molecules, a process termed cross-presentation. The mannose receptor (MR), an endocytic receptor expressed on a variety of APCs, has been demonstrated to target soluble Ags exclusively toward cross-presentation. In this study, we investigated the role of the murine nuclear receptor peroxisome proliferator-activated receptor γ (PPARγ), a ligand-activated transcription factor with immunomodulatory properties, in MR-mediated endocytosis and cross-presentation of the model Ag OVA. We could demonstrate both in vitro and in vivo that activation of PPARγ resulted in increased MR expression, which in consequence led to enhanced MR-mediated endocytosis and elevated cross-presentation of soluble OVA. Concomitantly, activation of PPARγ in dendritic cells induced up-regulation of the coinhibitory molecule B7H1, which, despite enhanced cross-presentation, caused an impaired activation of naive OVA-specific CD8+ T cells and the induction of T cell tolerance. These data provide a mechanistic basis for the immunomodulatory action of PPARγ which might open new possibilities in the development of therapeutic approaches aimed at the control of excessive immune responses, e.g., in T cell-mediated autoimmunity.

Blood-based mRNA expression profiling has already become an important issue in clinical applications. More recently , the characterization of the small RNA transcriptome offers additional avenues for diagnostic approaches. However , when applying miRNA expression profiling in routine clinical settings, the method of RNA preservation and the manner of RNA extraction as well as the reliability of the miRNA profiling procedure have to be carefully considered. Here we evaluate a recently introduced bead array-based technology as a robust method for the generation of blood-based human miRNA expression profiles. Importantly the comparison of different RNA extraction strategies resulted in dissimilar profiles depending on the RNA extraction method as well as on the underlying source. Expression profiles obtained from peripheral mononuclear cells (PBMCs) substantially differed from those of whole blood samples , whereby both sources per se yielded reproducible and reliable results. Expression profiles were also distinct when using either fresh or frozen PBMCs. Moreover RNA size fractioning resulted in discriminative miRNA expression profiles compared with total RNA based profiles. This study outlines important steps toward the establishment of a robust strategy for bloodbased miRNA profiling and provides a reliable strategy for its implementation in routine handling for diagnostic purposes.

In 1999, Golub et al. proposed for the first time microarray-based transcriptional profiling to be used as a new technology for the differential diagnosis of acute myeloid leukemias and acute lymphocytic leukemias. This very preliminary study sparked great enthusiasm beyond the leukemias. Over the last 10 years, numerous studies addressed the use of gene expression profiling of peripheral blood from patients with malignancies, infectious diseases, autoimmunity and even cardiovascular diseases. Despite this great effort, no single test has yet been established using microarray-based transcriptional profiling of peripheral blood. Here we highlight the advances in the field of blood transcriptomics during the last 10 years and also critically discuss the issues that need to be resolved before blood transcriptomics will become part of daily diagnostics in the leukemias, as well as in other diseases showing involvement of peripheral blood.

Breast cancer is a complex disease, whose heterogeneity is increasingly recognized. Despite considerable improvement in breast cancer treatment and survival, a significant proportion of patients seems to be over- or undertreated. To date, single clinicopathological parameters show limited success in predicting the likelihood of survival or response to endocrine therapy and chemotherapy. Consequently, new gene expression based prognostic and predictive tests are emerging that promise an improvement in predicting survival and therapy response. Initial evidence has emerged that this leads to allocation of fewer patients into high-risk groups allowing a reduction of chemotherapy treatment. Moreover, pattern-based approaches have also been developed to predict response to endocrine therapy or particular chemotherapy regimens. Irrespective of current pitfalls such as lack of validation and standardization, these pattern-based biomarkers will prove useful for clinical decision making in the near future, especially if more patients get access to this form of personalized medicine.