Potential for pancreatic maturation of differentiating human embryonic stem cells is sensitive to the specific pathway of definitive endoderm commitment

This study provides a detailed experimental and mathematical analysis of the impact of the initial pathway of definitive endoderm (DE) induction on later stages of pancreatic maturation. Human embryonic stem cells (hESCs) were induced to insulin-producing cells following a directed-differentiation approach. DE was induced following four alternative pathway modulations. DE derivatives obtained from these alternate pathways were subjected to pancreatic progenitor (PP) induction and maturation and analyzed at each stage. Results indicate that late stage maturation is influenced by the initial pathway of DE commitment. Detailed quantitative analysis revealed WNT3A and FGF2 induced DE cells showed highest expression of insulin, are closely aligned in gene expression patterning and have a closer resemblance to pancreatic organogenesis. Conversely, BMP4 at DE induction gave most divergent differentiation dynamics with lowest insulin upregulation, but highest glucagon upregulation. Additionally, we have concluded that early analysis of PP markers is indicative of its potential for pancreatic maturation. © 2014 Jaramillo et al

Anomalous Features of EMT during Keratinocyte Transformation

During the evolution of epithelial cancers, cells often lose their characteristic features and acquire a mesenchymal phenotype, in a process known as epithelial-mesenchymal transition (EMT). In the present study we followed early stages of keratinocyte transformation by HPV16, and observed diverse cellular changes, associated with EMT. We compared primary keratinocytes with early and late passages of HF1 cells, a cell line of HPV16-transformed keratinocytes. We have previously shown that during the progression from the normal cells to early HF1 cells, immortalization is acquired, while in the progression to late HF1, cells become anchorage independent. We show here that during the transition from the normal state to late HF1 cells, there is a progressive reduction in cytokeratin expression, desmosome formation, adherens junctions and focal adhesions, ultimately leading to poorly adhesive phenotype, which is associated with anchorage-independence. Surprisingly, unlike “conventional EMT”, these changes are associated with reduced Rac1-dependent cell migration. We monitored reduced Rac1-dependent migration also in the cervical cancer cell line SiHa. Therefore we can conclude that up to the stage of tumor formation migratory activity is eliminated

Immunohistochemical assessment of Pax8 expression during pancreatic islet development and in human neuroendocrine tumors

The paired box transcription factor Pax8 is critical for development of the eye, thyroid gland as well as the urinary and reproductive organs. In adult, Pax8 overexpression is associated with kidney, ovarian and thyroid tumors and has emerged as a specific marker for these cancers. Recently, Pax8 expression was also reported in human pancreatic islets and in neuroendocrine tumors, identifying Pax8 as a novel member of the Pax family expressed in the pancreas. Herein, we sought to provide a comprehensive analysis of Pax8 expression during pancreogenesis and in adult islets. Immunohistochemical analysis using the most employed Pax8 polyclonal antibody revealed strong nuclear staining in the developing mouse pancreas and in mature human and mouse islets. Astonishingly, Pax8 mRNA in mouse islets was undetectable while human islets exhibited low levels. These discrepancies raised the possibility of antibody cross-reactivity. This premise was confirmed by demonstrating that the polyclonal Pax8 antibody also recognized the islet-enriched Pax6 protein both by Western blotting and immunohistochemistry. Thus, in islets polyclonal Pax8 staining corresponds mainly to Pax6. In order to circumvent this caveat, a novel Pax8 monoclonal antibody was used to re-evaluate whether Pax8 was indeed expressed in islets. Surprisingly, Pax8 was not detected in neither the developing pancreas or in mature islets. Reappraisal of pancreatic neuroendocrine tumors using this Pax8 monoclonal antibody exhibited no immunostaining as compared to the Pax8 polyclonal antibody. In conclusion, Pax8 is not expressed in the pancreas and cast doubts on the value of Pax8 as a pancreatic neuroendocrine tumor marker

Clusters of Conserved Beta Cell Marker Genes for Assessment of Beta Cell Phenotype

The aim of this study was to establish a gene expression blueprint of pancreatic beta cells conserved from rodents to humans and to evaluate its applicability to assess shifts in the beta cell differentiated state. Genome-wide mRNA expression profiles of isolated beta cells were compared to those of a large panel of other tissue and cell types, and transcripts with beta cell-abundant and -selective expression were identified. Iteration of this analysis in mouse, rat and human tissues generated a panel of conserved beta cell biomarkers. This panel was then used to compare isolated versus laser capture microdissected beta cells, monitor adaptations of the beta cell phenotype to fasting, and retrieve possible conserved transcriptional regulators.Journal ArticleSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Predicting Pancreas Cell Fate Decisions and Reprogramming with a Hierarchical Multi-Attractor Model

Cell fate reprogramming, such as the generation of insulin-producing β cells from other pancreas cells, can be achieved by external modulation of key transcription factors. However, the known gene regulatory interactions that form a complex network with multiple feedback loops make it increasingly difficult to design the cell reprogramming scheme because the linear regulatory pathways as schemes of causal influences upon cell lineages are inadequate for predicting the effect of transcriptional perturbation. However, sufficient information on regulatory networks is usually not available for detailed formal models. Here we demonstrate that by using the qualitatively described regulatory interactions as the basis for a coarse-grained dynamical ODE (ordinary differential equation) based model, it is possible to recapitulate the observed attractors of the exocrine and β, δ, α endocrine cells and to predict which gene perturbation can result in desired lineage reprogramming. Our model indicates that the constraints imposed by the incompletely elucidated regulatory network architecture suffice to build a predictive model for making informed decisions in choosing the set of transcription factors that need to be modulated for fate reprogramming

Nuclear expression of Rac1 in cervical premalignant lesions and cervical cancer cells

<p>Abstract</p> <p>Background</p> <p>Abnormal expression of Rho-GTPases has been reported in several human cancers. However, the expression of these proteins in cervical cancer has been poorly investigated. In this study we analyzed the expression of the GTPases Rac1, RhoA, Cdc42, and the Rho-GEFs, Tiam1 and beta-Pix, in cervical pre-malignant lesions and cervical cancer cell lines.</p> <p>Methods</p> <p>Protein expression was analyzed by immunochemistry on 102 cervical paraffin-embedded biopsies: 20 without Squamous Intraepithelial Lesions (SIL), 51 Low- grade SIL, and 31 High-grade SIL; and in cervical cancer cell lines C33A and SiHa, and non-tumorigenic HaCat cells. Nuclear localization of Rac1 in HaCat, C33A and SiHa cells was assessed by cellular fractionation and Western blotting, in the presence or not of a chemical Rac1 inhibitor (NSC23766).</p> <p>Results</p> <p>Immunoreacivity for Rac1, RhoA, Tiam1 and beta-Pix was stronger in L-SIL and H-SIL, compared to samples without SIL, and it was significantly associated with the histological diagnosis. Nuclear expression of Rac1 was observed in 52.9% L-SIL and 48.4% H-SIL, but not in samples without SIL. Rac1 was found in the nucleus of C33A and SiHa cells but not in HaCat cells. Chemical inhibition of Rac1 resulted in reduced cell proliferation in HaCat, C33A and SiHa cells.</p> <p>Conclusion</p> <p>Rac1 is expressed in the nucleus of epithelial cells in SILs and cervical cancer cell lines, and chemical inhibition of Rac1 reduces cellular proliferation. Further studies are needed to better understand the role of Rho-GTPases in cervical cancer progression.</p

Quantitative utilization of prior biological knowledge in the Bayesian network modeling of gene expression data

<p>Abstract</p> <p>Background</p> <p>Bayesian Network (BN) is a powerful approach to reconstructing genetic regulatory networks from gene expression data. However, expression data by itself suffers from high noise and lack of power. Incorporating prior biological knowledge can improve the performance. As each type of prior knowledge on its own may be incomplete or limited by quality issues, integrating multiple sources of prior knowledge to utilize their consensus is desirable.</p> <p>Results</p> <p>We introduce a new method to incorporate the quantitative information from multiple sources of prior knowledge. It first uses the Naïve Bayesian classifier to assess the likelihood of functional linkage between gene pairs based on prior knowledge. In this study we included cocitation in PubMed and schematic similarity in Gene Ontology annotation. A candidate network edge reservoir is then created in which the copy number of each edge is proportional to the estimated likelihood of linkage between the two corresponding genes. In network simulation the Markov Chain Monte Carlo sampling algorithm is adopted, and samples from this reservoir at each iteration to generate new candidate networks. We evaluated the new algorithm using both simulated and real gene expression data including that from a yeast cell cycle and a mouse pancreas development/growth study. Incorporating prior knowledge led to a ~2 fold increase in the number of known transcription regulations recovered, without significant change in false positive rate. In contrast, without the prior knowledge BN modeling is not always better than a random selection, demonstrating the necessity in network modeling to supplement the gene expression data with additional information.</p> <p>Conclusion</p> <p>our new development provides a statistical means to utilize the quantitative information in prior biological knowledge in the BN modeling of gene expression data, which significantly improves the performance.</p

Targeted Deficiency of the Transcriptional Activator Hnf1α Alters Subnuclear Positioning of Its Genomic Targets

DNA binding transcriptional activators play a central role in gene-selective regulation. In part, this is mediated by targeting local covalent modifications of histone tails. Transcriptional regulation has also been associated with the positioning of genes within the nucleus. We have now examined the role of a transcriptional activator in regulating the positioning of target genes. This was carried out with primary β-cells and hepatocytes freshly isolated from mice lacking Hnf1α, an activator encoded by the most frequently mutated gene in human monogenic diabetes (MODY3). We show that in Hnf1a−/− cells inactive endogenous Hnf1α-target genes exhibit increased trimethylated histone H3-Lys27 and reduced methylated H3-Lys4. Inactive Hnf1α-targets in Hnf1a−/− cells are also preferentially located in peripheral subnuclear domains enriched in trimethylated H3-Lys27, whereas active targets in wild-type cells are positioned in more central domains enriched in methylated H3-Lys4 and RNA polymerase II. We demonstrate that this differential positioning involves the decondensation of target chromatin, and show that it is spatially restricted rather than a reflection of non-specific changes in the nuclear organization of Hnf1a-deficient cells. This study, therefore, provides genetic evidence that a single transcriptional activator can influence the subnuclear location of its endogenous genomic targets in primary cells, and links activator-dependent changes in local chromatin structure to the spatial organization of the genome. We have also revealed a defect in subnuclear gene positioning in a model of a human transcription factor disease