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OBJECTIVE--Obesity-associated insulin resistance is characterized by a state of chronic, low-grade inflammation that is associated with the accumulation of M1 proinflammatory macrophages in adipose tissue. Although different evidence explains the mechanisms linking the expansion of adipose tissue and adipose tissue macrophage (ATM) polarization, in the current study we investigated the concept of lipid-induced toxicity as the pathogenic link that could explain the trigger of this response. RESEARCH DESIGN AND METHODS--We addressed this question using isolated ATMs and adipocytes from genetic and diet-induced murine models of obesity. Through transcriptomic and lipidomic analysis, we created a model integrating transcript and lipid species networks simultaneously occurring in adipocytes and ATMs and their reversibility by thiazolidinedione treatment. RESULTS--We show that polarization of ATMs is associated with lipid accumulation and the consequent formation of foam cell-like cells in adipose tissue. Our study reveals that early stages of adipose tissue expansion are characterized by M2-polarized ATMs and that progressive lipid accumulation within ATMs heralds the M1 polarization, a macrophage phenotype associated with severe obesity and insulin resistance. Furthermore, rosiglitazone treatment, which promotes redistribution of lipids toward adipocytes and extends the M2 ATM polarization state, prevents the lipid alterations associated with M1 ATM polarization. CONCLUSIONS--Our data indicate that the M1 ATM polarization in obesity might be a macrophage-specific manifestation of a more general lipotoxic pathogenic mechanism. This indicates that strategies to optimize fat deposition and repartitioning toward adipocytes might improve insulin sensitivity by preventing ATM lipotoxicity and M1 polarization., Obesity-associated insulin resistance is characterized by a state of low-grade inflammation (1) that affects adipocyte function (2) and is associated with macrophage infiltration of adipose tissue (3). Additional evidence exists [...]

Hematopoietic stem cells derived from pluripotent stem cells could be used as an alternative to bone marrow transplants. Deriving these has been a long‐term goal for researchers. However, the success of these efforts has been limited with the cells produced able to engraft in the bone marrow of recipient animals only in very low numbers. There is evidence that defects in the migratory and homing capacity of the cells are due to mis‐regulation of miRNA expression and are responsible for their failure to engraft. We compared the miRNA expression profile of hematopoietic progenitors derived from pluripotent stem cells to those derived from bone marrow and found that numerous miRNAs are too highly expressed in hematopoietic progenitors derived from pluripotent stem cells, and that most of these are inhibitors of epithelial‐mesenchymal transition or metastasis (including miR‐200b, miR‐200c, miR‐205, miR‐148a, and miR‐424). We hypothesize that the high expression of these factors, which promote an adherent phenotype, may be causing the defect in hematopoietic differentiation. However, inhibiting these miRNAs, individually or in multiplex, was insufficient to improve hematopoietic differentiation in vitro, suggesting that other miRNAs and/or genes may be involved in this process. StemCells2018;36:55–64 Schematic shows how epithelial‐mesenchymal transition‐suppressing miRNAs may be inhibiting hematopoietic stem cell emergence from pluripotent stem cell‐derived hemogenic endothelium.

Human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) are defined as pluripotent in view of their self‐renewal ability and potential to differentiate to cells of all three germ layers. Recent studies have indicated that microRNAs (miRNAs) play an important role in the maintenance of pluripotency and cell cycle regulation. We used a microarray based approach to identify miRNAs that were enriched in hESCs when compared to differentiated cells and at the same time showed significant expression changes between different phases of cell cycle. We identified 34 candidate miRNAs and performed functional studies on one of these, miR‐1305, which showed the highest expression change during cell cycle transition. Overexpression of miR‐1305 induced differentiation of pluripotent stem cells, increased cell apoptosis and sped up G1/S transition, while its downregulation facilitated the maintenance of pluripotency and increased cell survival. Using target prediction software and luciferase based reporter assays we identified POLR3Gas a downstream target by which miR‐1305 regulates the fine balance between maintenance of pluripotency and onset of differentiation. Overexpression of POLR3Grescued pluripotent stem cell differentiation induced by miR‐1305 overexpression. In contrast, knock‐down of POLR3Gexpression abolished the miR‐1305‐knockdown mediated enhancement of pluripotency, thus validating its role as miR‐1305 target in human pluripotent stem cells. Together our data point to an important role for miR‐1305 as a novel regulator of pluripotency, cell survival and cell cycle and uncovers new mechanisms and networks by which these processes are intertwined in human pluripotent stem cells. StemCells2016;34:2306–2317

MicroRNA (miRNAs) are short noncoding RNA molecules involved in many cellular processes and shown to play a key role in somatic cell induced reprogramming. We performed an array based screening to identify candidates that are differentially expressed between dermal skin fibroblasts (DFs) and induced pluripotent stem cells (iPSCs). We focused our investigations on miR‐145 and showed that this candidate is highly expressed in DFs relative to iPSCs and significantly downregulated during reprogramming process. Inhibition of miR‐145 in DFs led to the induction of “cellular plasticity” demonstrated by: (a) alteration of cell morphology associated with downregulation of mesenchymal and upregulation of epithelial markers; (b) upregulation of pluripotency‐associated genes including SOX2, KLF4, C‐MYC; (c) downregulation of miRNA let‐7b known to inhibit reprogramming; and (iv) increased efficiency of reprogramming to iPSCs in the presence of reprogramming factors. Together, our results indicate a direct functional link between miR‐145 and molecular pathways underlying reprogramming of somatic cells to iPSCs. StemCells2016;34:246–251

Background:Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient’s organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators.Methods:A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma.Results:New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies.Conclusion:The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma.

Identification of gene expression-based breast cancer subtypes is considered a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene-expression changes occurring in breast cancer. So far, these epigenetic contributions to sporadic breast cancer subtypes have not been well characterized, and only a limited understanding exists of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and to deliver specific epigenotypes associated with particular breast cancer subtypes. By using a microarray approach, we analyzed DNA methylation in regulatory regions of 806 cancer-related genes in 28 breast cancer paired samples. We subsequently performed substantial technical and biologic validation by pyrosequencing, investigating the top qualifying 19 CpG regions in independent cohorts encompassing 47 basal-like, 44 ERBB2+ overexpressing, 48 luminal A, and 48 luminal B paired breast cancer/adjacent tissues. With the all-subset selection method, we identified the most subtype-predictive methylation profiles in multivariable logistic regression analysis. The approach efficiently recognized 15 individual CpG loci differentially methylated in breast cancer tumor subtypes. We further identified novel subtype-specific epigenotypes that clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors. Our results provide evidence that well-defined DNA methylation profiles enable breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.

INTRODUCTION: B cell chronic lymphocytic leukemia (B-CLL) is a lymphoproliferative disorder with a variable clinical course. Patients (pts) with unmutated (unmut) IgVH gene show a shorter progression free survival and overall survival than the patients with IgVH mutated (mut). To understand the differences between molecular subgroups of B-CLL we have studied transcriptomic and proteomic profiles on samples from 40 B-CLL pts (Binet stage A). MATERIAL AND METHODS: 100 µg of total PBMC proteins were used for IEF followed by 2D electrophoresis. Image analysis of scanned gels was used to identify statistically differentially expressed proteins. Image acquisition and analysis were performed using the Ludesi software (http://www.ludesi.com). Selected spots were subjected to automatic digestion and the proteins were identified by MALDI-TOF (Voyager DE-Pro, Applied Biosystems) peptide mass fingerprint using the Protein Prospector software. To confirm the initial results, sequencing of selected peptide ions was carried out by collision-induced dissociation (CID) with a nESI-QTRAP mass spectrometer from Applied Biosystems. Eight proteins were validated by Western Blot. Total RNA from B cells was used to analyze the expression profile by hybridization with Whole Human Genome U133 Plus 2.0 Array from Affymetrix. Normalization, differential gene expression and functional annotations were analyzed using the GEPAS suite (http://www.gepas.org). qPCR using TaqMan primers/probes was used for validation of the microarray data RESULTS: When we compared IgVH mut vs unmut transcriptomic and proteomic profiles, we found more than 600 differentially expressed genes and 12 proteins ( fdr <0.05 adjusted for multiple test contrast and p<0.05, Mann-Whitney’s test, for gene and proteins, respectively). In tables 1 and 2 we show some of the most differentially expressed gene/proteins in each group of pts. Validation of results from microarrays and proteomic data using qPCR and Western blot are in progress. We obtained positive correlation between transcriptomic and proteomic profiles, (corr=0.21, p=0.04, Pearson’s correation test) suggesting that common features are found using both approximations. CONCLUSION: We found a number of interesting gene/proteins that could be able to differentiate molecular subgroups of B-CLL pts. The study of these proteins and genes may lead to better understand the different clinical behaviour of IgVH mut and unmut B-CLL forms, but validation with a larger group of pts is still necessary. Table 1: Genes differentially expressed IgVH mut IgVH unmut Genes annotated using their gene symbol BCL11A MGC9913 DUSP22 RGS4 PDLIM5 CRY1 RDH13 GGT2 PHF15 DMD SVH TUBB6 ADAM29 LPL ITPKB ITGA9 RBKS BCL7A NFATC1 MYEOV RIN3 PPP1R9A Table 2: Proteins differentially expressed IgVH mut IgVH unmut Proteins were annotated according to their gene symbol VIM ERP29 COTL1 CCT2 S100A9 PSMB10 HSPD1

Introduction: In recent years several molecular prognostic factors have been identified in Chronic Lymphocytic Leukemia B (B-CLL). These include mutations in the variable region of the immunoglobulin genes (IgVH), somatic mutations in the BCL6 gene (Leukemia (2004) 18, 743–746) and the expression level of CD38 and ZAP70. However its biological significance is not clear. In order to identify novel molecular markers with prognostic and therapeutic value we have analyzed the proteomic and genomic profile of 40 B-CLL patients (Binet stage A). Material and methods: 100 μg of total PBMC proteins were used for IEF followed by 2D electrophoresis. Image analysis of scanned gels was used to identify statistically significant differentially expressed proteins. Image acquisition and analysis were performed using the Image Master Platinum software. Selected spots were subjected to automatic digestion and the proteins were identified by MALDI-TOF (Voyager DE-Pro, Applied Biosystems) peptide mass fingerprint using the Protein Prospector software. To confirm the initial identification amino acid sequencing of selected peptide ions was carried out by collision-induced dissociation (CID) with a nESI-QTRAP mass spectrometer from Applied Biosystems. 100 ng of total RNA was used to analyze the expression profile by cDNA microarrays (Whole Human Genome U133 Plus 2.0 Array from Affymetrix). Differential gene expression has been analyzed using the corresponding module (pomelo) from the GEPAS web tools (http://www.gepas.org). Results and Discussion: We found 126 proteins and 25 genes exhibiting differential expression (p<0.05, Student t-test, FDR-adjusted for multiple testing contrasts). We found 34 proteins and 18 genes with different expression according to the mutational status of IgVH. We also classified patients according to mutations in the BCL6 gene, which we previously showed clinical relevance (Leukemia (2004) 18, 743–746), and found 36 proteins and 2 genes with differential expression. Next, we compared samples attending to the mutational status of both genes, results are summarized in the following table: Compared groups attending to the mutational status of IgVH and BCL6 genes targets IgVH wt/BCL6 wt IgVH mut/BCL6 mut 16 proteins / 10 genes IgVH mut/BCL6 wt 28 proteins / 9 genes Of particular interest is the comparision between BCL6 status in IgVH mutated patients where we found 27 proteins with differential expression but no difference in the gene expression profile. This result suggest that the bad prognostic associated to BCL6 mutation may be due solely to postransductional modification of proteins. CD38 and ZAP70 expression level have also been associated with bad clinical prognosis, however, we found no significant difference in the gene expression profile according to CD38 or ZAP70 expression level. We are currently assessing a wider number of patients in order to obtain stronger conclusions. The study of these proteins and genes may lead to a better understanding of the different clinical behaviour of these B-CLL forms.