Gene expression analysis of embryonic stem cells expressing VE-cadherin (CD144) during endothelial differentiation

Background: Endothelial differentiation occurs during normal vascular development in the developing embryo. This process is recapitulated in the adult when endothelial progenitor cells are generated in the bone marrow and can contribute to vascular repair or angiogenesis at sites of vascular injury or ischemia. The molecular mechanisms of endothelial differentiation remain incompletely understood. Novel approaches are needed to identify the factors that regulate endothelial differentiation. Methods: Mouse embryonic stem (ES) cells were used to further define the molecular mechanisms of endothelial differentiation. By flow cytometry a population of VEGF-R2 positive cells was identified as early as 2.5 days after differentiation of ES cells, and a subset of VEGF-R2+ cells, that were CD41 positive at 3.5 days. A separate population of VEGF-R2+ stem cells expressing the endothelial-specific marker CD144 (VE-cadherin) was also identified at this same time point. Channels lined by VE-cadherin positive cells developed within the embryoid bodies (EBs) formed by differentiating ES cells. VE-cadherin and CD41 expressing cells differentiate in close proximity to each other within the EBs, supporting the concept of a common origin for cells of hematopoietic and endothelial lineages. Results: Microarray analysis of \u3e45,000 transcripts was performed on RNA obtained from cells expressing VEGF-R2+, CD41+, and CD144+ and VEGF-R2-, CD41-, and CD144-. All microarray experiments were performed in duplicate using RNA obtained from independent experiments, for each subset of cells. Expression profiling confirmed the role of several genes involved in hematopoiesis, and identified several putative genes involved in endothelial differentiation. Conclusion: The isolation of CD144+ cells during ES cell differentiation from embryoid bodies provides an excellent model system and method for identifying genes that are expressed during endothelial differentiation and that are distinct from hematopoiesis

Bioinformatic identification and characterization of human endothelial cell-restricted genes

<p>Abstract</p> <p>Background</p> <p>In this study, we used a systematic bioinformatics analysis approach to elucidate genes that exhibit an endothelial cell (EC) restricted expression pattern, and began to define their regulation, tissue distribution, and potential biological role.</p> <p>Results</p> <p>Using a high throughput microarray platform, a primary set of 1,191 transcripts that are enriched in different primary ECs compared to non-ECs was identified (LCB >3, FDR <2%). Further refinement of this initial subset of transcripts, using published data, yielded 152 transcripts (representing 109 genes) with different degrees of EC-specificity. Several interesting patterns emerged among these genes: some were expressed in all ECs and several were restricted to microvascular ECs. Pathway analysis and gene ontology demonstrated that several of the identified genes are known to be involved in vasculature development, angiogenesis, and endothelial function (P < 0.01). These genes are enriched in cardiovascular diseases, hemorrhage and ischemia gene sets (P < 0.001). Most of the identified genes are ubiquitously expressed in many different tissues. Analysis of the proximal promoter revealed the enrichment of conserved binding sites for 26 different transcription factors and analysis of the untranslated regions suggests that a subset of the EC-restricted genes are targets of 15 microRNAs. While many of the identified genes are known for their regulatory role in ECs, we have also identified several novel EC-restricted genes, the function of which have yet to be fully defined.</p> <p>Conclusion</p> <p>The study provides an initial catalogue of EC-restricted genes most of which are ubiquitously expressed in different endothelial cells.</p

Cdc42-Dependent Transfer of mir301 from Breast Cancer-Derived Extracellular Vesicles Regulates the Matrix Modulating Ability of Astrocytes at the Blood–Brain Barrier

Breast cancer brain metastasis is a major clinical challenge and is associated with a dismal prognosis. Understanding the mechanisms underlying the early stages of brain metastasis can provide opportunities to develop efficient diagnostics and therapeutics for this significant clinical challenge. We have previously reported that breast cancer-derived extracellular vesicles (EVs) breach the blood–brain barrier (BBB) via transcytosis and can promote brain metastasis. Here, we elucidate the functional consequences of EV transport across the BBB. We demonstrate that brain metastasis-promoting EVs can be internalized by astrocytes and modulate the behavior of these cells to promote extracellular matrix remodeling in vivo. We have identified protein and miRNA signatures in these EVs that can lead to the interaction of EVs with astrocytes and, as such, have the potential to serve as targets for development of diagnostics and therapeutics for early detection and therapeutic intervention in breast cancer brain metastasis

Serum Protein Signatures Using Aptamer-Based Proteomics for Minimal Change Disease and Membranous Nephropathy

Introduction: Minimal change disease (MCD) and membranous nephropathy (MN) are glomerular diseases (glomerulonephritis [GN]) that present with the nephrotic syndrome. Although circulating PLA2R antibodies have been validated as a biomarker for MN, the diagnosis of MCD and PLA2R-negative MN still relies on the results of kidney biopsy or empirical corticosteroids in children. We aimed to identify serum protein biomarker signatures associated with MCD and MN pathogenesis using aptamer-based proteomics. Methods: Quantitative SOMAscan proteomics was applied to the serum of adult patients with MCD (n = 15) and MN(n = 37) and healthy controls (n = 20). Associations between the 1305proteins detected with SOMAscan were assessed using multiple statistical tests, expression pattern analysis, and systems biology analysis. Results: A total of 208 and 244 proteins were identified that differentiated MCD and MN, respectively, with high statistical significance from the healthy controls (Benjamin-Hochberg [BH] P \u3c 0.0001). There were 157 proteins that discriminated MN from MCD (BH P \u3c 0.05). In MCD, 65 proteins were differentially expressed as compared with MN and healthy controls. When compared with MCD and healthy controls, 44 discriminatory proteins were specifically linked to MN. Systems biology analysis of these signatures identified cell death and inflammation as key pathways differentiating MN from MCD and healthy controls. Dysregulation of fatty acid metabolism pathways was confirmed in both MN and MCD as compared with the healthy subjects. Conclusion: SOMAscan represents a promising proteomic platform for biomarker development in GN. Validation of a greater number of discovery biomarkers in larger patient cohorts is needed before these data can be translated for clinical care

Genomic Counter-Stress Changes Induced by the Relaxation Response

Background: Mind-body practices that elicit the relaxation response (RR) have been used worldwide for millennia to prevent and treat disease. The RR is characterized by decreased oxygen consumption, increased exhaled nitric oxide, and reduced psychological distress. It is believed to be the counterpart of the stress response that exhibits a distinct pattern of physiology and transcriptional profile. We hypothesized that RR elicitation results in characteristic gene expression changes that can be used to measure physiological responses elicited by the RR in an unbiased fashion. Methods/Principal Findings: We assessed whole blood transcriptional profiles in 19 healthy, long-term practitioners of daily RR practice (group M), 19 healthy controls (group $N_1$), and 20 $N_1$ individuals who completed 8 weeks of RR training (group $N_2$). 2209 genes were differentially expressed in group M relative to group $N_1$ (p<0.05) and 1561 genes in group $N_2$ compared to group $N_1$ (p<0.05). Importantly, 433 (p<$10_{−10}$) of 2209 and 1561 differentially expressed genes were shared among long-term (M) and short-term practitioners ($N_2$). Gene ontology and gene set enrichment analyses revealed significant alterations in cellular metabolism, oxidative phosphorylation, generation of reactive oxygen species and response to oxidative stress in long-term and short-term practitioners of daily RR practice that may counteract cellular damage related to chronic psychological stress. A significant number of genes and pathways were confirmed in an independent validation set containing 5 $N_1$ controls, 5 $N_2$ short-term and 6 M long-term practitioners. Conclusions/Significance: This study provides the first compelling evidence that the RR elicits specific gene expression changes in short-term and long-term practitioners. Our results suggest consistent and constitutive changes in gene expression resulting from RR may relate to long term physiological effects. Our study may stimulate new investigations into applying transcriptional profiling for accurately measuring RR and stress related responses in multiple disease settings

Correction: Genomic Counter-Stress Changes Induced by the Relaxation Response

The Competing Interests statement is incorrect. The correct Competing Interests statement is: The following authors hold or have held positions at the Benson-Henry Institute for Mind Body Medicine at Massachusetts General Hospital, which is paid by patients and their insurers for running the SMART-3RP and related relaxation/mindfulness clinical programs, markets related products such as books, DVDs, CDs and the like, and holds a patent pending (PCT/ US2012/049539 filed August 3, 2012) entitled Quantitative Genomics of the Relaxation Response : JAD, ALW, HB

Analysis of Multiple Sarcoma Expression Datasets: Implications for Classification, Oncogenic Pathway Activation and Chemotherapy Resistance

Background: Diagnosis of soft tissue sarcomas (STS) is challenging. Many remain unclassified (not-otherwise-specified, NOS) or grouped in controversial categories such as malignant fibrous histiocytoma (MFH), with unclear therapeutic value. We analyzed several independent microarray datasets, to identify a predictor, use it to classify unclassifiable sarcomas, and assess oncogenic pathway activation and chemotherapy response. Methodology/Principal Findings: We analyzed 5 independent datasets (325 tumor arrays). We developed and validated a predictor, which was used to reclassify MFH and NOS sarcomas. The molecular “match” between MFH and their predicted subtypes was assessed using genome-wide hierarchical clustering and Subclass-Mapping. Findings were validated in 15 paraffin samples profiled on the DASL platform. Bayesian models of oncogenic pathway activation and chemotherapy response were applied to individual STS samples. A 170-gene predictor was developed and independently validated (80-85% accuracy in all datasets). Most MFH and NOS tumors were reclassified as leiomyosarcomas, liposarcomas and fibrosarcomas. “Molecular match” between MFH and their predicted STS subtypes was confirmed both within and across datasets. This classification revealed previously unrecognized tissue differentiation lines (adipocyte, fibroblastic, smooth-muscle) and was reproduced in paraffin specimens. Different sarcoma subtypes demonstrated distinct oncogenic pathway activation patterns, and reclassified MFH tumors shared oncogenic pathway activation patterns with their predicted subtypes. These patterns were associated with predicted resistance to chemotherapeutic agents commonly used in sarcomas. Conclusions/Significance: STS profiling can aid in diagnosis through a predictor tracking distinct tissue differentiation in unclassified tumors, and in therapeutic management via oncogenic pathway activation and chemotherapy response assessment