Localization of GPI-80, a beta2-integrin-associated glycosylphosphatidyl-inositol anchored protein, on strongly CD14-positive human monocytes

Human Plasma Transcriptome Implicates Dysregulated S100A12 Expression: A Strong, Early-Stage Prognostic Factor in ST-Segment Elevated Myocardial Infarction: Bioinformatics Analysis and Experimental Verification

The ability of blood transcriptome analysis to identify dysregulated pathways and outcome-related genes following myocardial infarction remains unknown. Two gene expression datasets (GSE60993 and GSE61144) were downloaded from Gene Expression Omnibus (GEO) Datasets to identify altered plasma transcriptomes in patients with ST-segment elevated myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention. GEO2R, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes annotations, protein–protein interaction analysis, etc., were adopted to determine functional roles and regulatory networks of differentially expressed genes (DEGs). Dysregulated expressomes were verified at transcriptional and translational levels by analyzing the GSE49925 dataset and our own samples, respectively. A total of 91 DEGs were identified in the discovery phase, consisting of 15 downregulated genes and 76 upregulated genes. Two hub modules consisting of 12 hub genes were identified. In the verification phase, six of the 12 hub genes exhibited the same variation patterns at the transcriptional level in the GSE49925 dataset. Among them, S100A12 was shown to have the best discriminative performance for predicting in-hospital mortality and to be the only independent predictor of death during follow-up. Validation of 223 samples from our center showed that S100A12 protein level in plasma was significantly lower among patients who survived to discharge, but it was not an independent predictor of survival to discharge or recurrent major adverse cardiovascular events after discharge. In conclusion, the dysregulated expression of plasma S100A12 at the transcriptional level is a robust early prognostic factor in patients with STEMI, while the discrimination power of the protein level in plasma needs to be further verified by large-scale, prospective, international, multicenter studies.

Healthy myeloid-derived suppressor cells express the surface ectoenzyme Vanin-2 (VNN2)

Study of human monocytic Myeloid-Derived Suppressor cells Mo-MDSC (CD14⁺ HLA-DR^neg/low) has been hampered by the lack of positive cell-surface markers. In order to identify positive markers for Mo-MDSC, we performed microarray analysis comparing Mo-MDSC cells from healthy subjects versus CD14⁺ HLA-DR^high monocytes. We have identified the surface ectoenzyme Vanin-2(VNN2) protein as a novel biomarker highly-enriched in healthy subjects Mo-MDSC. Indeed, healthy subjects Mo-MDSC cells expressed 68 % VNN2, whereas only 9% VNN2 expression was observed on CD14⁺ HLA-DR^high cells (n = 4 p < 0.01). The top 10 percent positive VNN2 monocytes expressed CD33 and CD11b while being negative for HLA-DR, CD3, CD15, CD19 and CD56, consistent with a Mo-MDSC phenotype. CD14⁺VNN2^high monocytes were able to inhibit CD8 T cell proliferation comparably to traditional Mo-MDSC at 51 % and 48 % respectively. However, VNN2 expression on CD14⁺ monocytes from glioma patients was inversely correlated to their grade. CD14⁺VNN2^high monocytes thus appear to mark a monocytic population similar to Mo-MDSC only in healthy subjects, which may be useful for tumor diagnoses.

Identification and validation of key genes mediating intracranial aneurysm rupture by weighted correlation network analysis

Background

Rupture of intracranial aneurysm (IA) is the leading cause of subarachnoid hemorrhage. However, there are few pharmacological therapies available for the prevention of IA rupture. Therefore, exploring the molecular mechanisms which underlie IA rupture and identifying the potential molecular targets for preventing the rupture of IA is of vital importance.

Methods

We used the Gene Expression Omnibus (GEO) datasets GSE13353, GSE15629, and GSE54083 in our study. The 3 datasets were merged and normalized. Differentially expressed gene (DEG) screening and weighted correlation network analysis (WGCNA) were conducted. The co-expression patterns between ruptured IA samples and unruptured IA samples were compared. Then, the DEGs were mapped into the whole co-expression network of ruptured IA samples, and a DEG co-expression network was generated. Molecular Complex Detection (MCODE) (http://baderlab.org/Software/MCODE) was used to identify key genes based on the DEG co-expression network. Finally, key genes were validated using another GEO dataset (GSE122897), and their potential diagnostic values were shown using receiver operating characteristic (ROC) analysis.

Results

In our study, 49 DEGs were screened while 8 and 6 gene modules were detected based on ruptured IA samples and unruptured IA samples, respectively. Pathways associated with inflammation and immune response were clustered in the salmon module of ruptured IA samples. The DEG co-expression network with 35 nodes and 168 edges was generated, and 14 key genes were identified based on this DEG co-expression network. The gene with the highest degree in the key gene cluster was CXCR4. All key genes were validated using GSE122897, and they all showed the potential diagnostic value in predicting IA rupture.

Conclusions

Using a weighted gene co-expression network approach, we identified 8 and 6 modules for ruptured IA and unruptured IA, respectively. After that, we identified the hub genes for each module and key genes based on the DEG co-expression network. All these key genes were validated by another GEO dataset and might serve as potential targets for pharmacological therapies and diagnostic markers in predicting IA rupture. Further studies are needed to elucidate the detailed molecular mechanisms and biological functions of these key genes which underlie the rupture of IA.

Regulation of coenzyme A levels by degradation: the 'Ins and Outs'

Coenzyme A (CoA) is the predominant acyl carrier in mammalian cells and a cofactor that plays a key role in energy and lipid metabolism. CoA and its thioesters (acyl-CoAs) regulate a multitude of metabolic processes at different levels: as substrates, allosteric modulators, and via post-translational modification of histones and other non-histone proteins. Evidence is emerging that synthesis and degradation of CoA are regulated in a manner that enables metabolic flexibility in different subcellular compartments. Degradation of CoA occurs through distinct intra- and extracellular pathways that rely on the activity of specific hydrolases. The pantetheinase enzymes specifically hydrolyze pantetheine to cysteamine and pantothenate, the last step in the extracellular degradation pathway for CoA. This reaction releases pantothenate in the bloodstream, making this CoA precursor available for cellular uptake and de novo CoA synthesis. Intracellular degradation of CoA depends on specific mitochondrial and peroxisomal Nudix hydrolases. These enzymes are also active against a subset of acyl-CoAs and play a key role in the regulation of subcellular (acyl-)CoA pools and CoA-dependent metabolic reactions. The evidence currently available indicates that the extracellular and intracellular (acyl-)CoA degradation pathways are regulated in a coordinated and opposite manner by the nutritional state and maximize the changes in the total intracellular CoA levels that support the metabolic switch between fed and fasted states in organs like the liver. The objective of this review is to update the contribution of these pathways to the regulation of metabolism, physiology and pathology and to highlight the many questions that remain open.

The ratio of HLA-DR and VNN2+ expression on CD14+ myeloid derived suppressor cells can distinguish glioblastoma from radiation necrosis patients

Glioblastoma (GBM) is the most aggressive and lethal type of brain cancer with a median survival of less than two years even following aggressive treatment (Stupp et al., N Engl J Med 352:987-996, 2005). Among the many challenges in treating patients with this devastating disease is the ability to differentiate Magnetic Resonance Imaging (MRI) images that appear following radiation therapy, often termed "radiation necrosis" from true GBM recurrence. Radiation necrosis (RN) and GBM are very difficult to distinguish and currently only a brain biopsy can conclusively differentiate these pathologies. In the present study, we introduce a differential diagnostic approach using a newly identified Myeloid-Derived Suppressor Cell (MDSC) biomarker, vascular non-inflammatory molecule 2 (VNN2⁺), in combination with expression of traditional HLA-DR on peripheral blood CD14⁺ monocytes isolated from GBM and/or RN patients. We performed proof-of-principle experiments confirming the sensitivity and specificity of this approach based upon the combined expression levels of HLA-DR and VNN2 among CD14⁺ Mo-MDSC, which we called the DR-Vanin Index or DVI. The DVI was able to distinguish GBM from RN patients with a high degree of certainty (n = 18 and n = 6 respectively; p = 0.0004). This novel, quick and inexpensive blood-based liquid biopsy could potentially replace invasive brain biopsies in differentiating GBM from RN patients using a minimally-invasive technique.

The pattern of GPI-80 expression is a useful marker for unusual myeloid maturation in peripheral blood

Myeloid-derived suppressor cells (MDSCs) have a wide spectrum of immunosuppressive activity; control of these cells is a new target for improving clinical outcomes in cancer patients. MDSCs originate from unusual differentiation of neutrophils or monocytes induced by inflammatory cytokines, including granulocyte-colony stimulating factor (G-CSF) and granulocyte-macrophage (GM)-CSF. However, MDSCs are difficult to detect in neutrophil or monocyte populations because they are not uniform cells, resembling both neutrophils and monocytes; thus, they exist in a heterogeneous population. In this study, we investigated GPI-80, a known regulator of Mac-1 (CD11b/CD18) and associated closely with neutrophil maturation, to clarify this unusual differentiation. First, we demonstrated that the mean fluorescence intensity (MFI) of GPI-80 and coefficient of variation (CV) of GPI-80 were increased by treatment with G-CSF and GM-CSF, respectively, using a human promyelocytic leukaemia (HL60) cell differentiation model. To confirm the value of GPI-80 as a marker of unusual differentiation, we measured GPI-80 expression and MDSC functions using peripheral blood cells from metastatic renal cell carcinoma patients. The GPI-80 CV was augmented significantly in the CD16^hi neutrophil cell population, and GPI-80 MFI was increased significantly in the CD33^hi monocyte cell population. Furthermore, the GPI-80 CV in the CD16^hi population was correlated inversely with the proliferative ability of T cells and the GPI-80 MFI of the CD33^hi population was correlated with reactive oxygen species production. These results led us to propose that the pattern of GPI-80 expression in these populations is a simple and useful marker for unusual differentiation, which is related to MDSC functions.

Enhanced hepatotoxicity by acetaminophen in Vanin-1 knockout mice is associated with deficient proliferative and immune responses

BACKGROUND AND AIMS

Pretreatment with clofibrate, a peroxisome proliferator-activated receptor alpha (PPARa) agonist, protects mice from acetaminophen (APAP) injury. Protection is not due to alterations in APAP metabolism and is dependent on PPARa expression. Gene array analysis revealed that mice receiving clofibrate have enhanced hepatic Vanin-1 (Vnn1) gene expression, a response that is also PPARa dependent.

METHODS

We examined the role of Vnn1 by comparing the responses of Vnn1 knockout and wild-type mice following APAP hepatotoxicity. APAP metabolism, hepatotoxicity, and compensatory hepatocyte proliferation and immune responses were assessed.

RESULTS

Vnn1 knockout mice are more susceptible to APAP hepatotoxicity despite no differences in hepatic glutathione content, gene expression of APAP metabolizing enzymes, or hepatic capacity to bioactivate or detoxify APAP ex vivo. Together, these data strongly suggest that the susceptibility of Vnn1 knockout mice is not due to differences in APAP metabolism. Immunochemistry revealed a lack of proliferating cell nuclear antigen-positive hepatocytes and F4/80-positive macrophages in and around areas of centrilobular necrosis in APAP-treated Vnn1 knockouts. Hepatic gene induction of pro-inflammatory cytokines was either significantly reduced or completely blunted in these mice. This was correlated with a reduction in early recruitment of cells positive for granulocyte differentiation antigen 1 or integrin alpha M. Heightened toxicity was also observed in CCl4 and ConA hepatitis models in the absence of Vnn1.

CONCLUSIONS

These results indicate that mice lacking Vnn1 have deficiencies in compensatory repair and immune responses following toxic APAP exposure and that these mechanisms may contribute to the enhanced hepatotoxicity seen.

Using cell fate attractors to uncover transcriptional regulation of HL60 neutrophil differentiation

BACKGROUND

The process of cellular differentiation is governed by complex dynamical biomolecular networks consisting of a multitude of genes and their products acting in concert to determine a particular cell fate. Thus, a systems level view is necessary for understanding how a cell coordinates this process and for developing effective therapeutic strategies to treat diseases, such as cancer, in which differentiation plays a significant role. Theoretical considerations and recent experimental evidence support the view that cell fates are high dimensional attractor states of the underlying molecular networks. The temporal behavior of the network states progressing toward different cell fate attractors has the potential to elucidate the underlying molecular mechanisms governing differentiation.

RESULTS

Using the HL60 multipotent promyelocytic leukemia cell line, we performed experiments that ultimately led to two different cell fate attractors by two treatments of varying dosage and duration of the differentiation agent all-trans-retinoic acid (ATRA). The dosage and duration combinations of the two treatments were chosen by means of flow cytometric measurements of CD11b, a well-known early differentiation marker, such that they generated two intermediate populations that were poised at the apparently same stage of differentiation. However, the population of one treatment proceeded toward the terminally differentiated neutrophil attractor while that of the other treatment reverted back toward the undifferentiated promyelocytic attractor. We monitored the gene expression changes in the two populations after their respective treatments over a period of five days and identified a set of genes that diverged in their expression, a subset of which promotes neutrophil differentiation while the other represses cell cycle progression. By employing promoter based transcription factor binding site analysis, we found enrichment in the set of divergent genes, of transcription factors functionally linked to tumor progression, cell cycle, and development.

CONCLUSION

Since many of the transcription factors identified by this approach are also known to be implicated in hematopoietic differentiation and leukemia, this study points to the utility of incorporating a dynamical systems level view into a computational analysis framework for elucidating transcriptional mechanisms regulating differentiation.