The transcription factor PU.1 plays a pivotal role in normal myeloid differentiation. PU.1 ؊/؊ mice exhibit a complete block in myeloid differentiation. Heterozygous PU.1 mutations were reported in some patients with acute myeloid leukemia (AML), but not in AML with translocation t(8;21), which gives rise to the fusion gene AML1-ETO.

IntroductionHematopoiesis is the regulated development of distinct cellular lineages from a common precursor, the hematopoietic stem cell. Fundamental changes in gene expression result in each cell type expressing a characteristic complement of genes necessary for its function. This is achieved through the action of transcriptional regulators with general and restricted expression patterns in the hematopoietic system. 1 The ets domain transcription factor PU.1 is preferentially expressed in myeloid and B cells. 2,3 Inactivation of the PU.1 gene in mice causes defects in the development of multiple hematopoietic lineages, including B and T lymphocytes, monocytes, and granulocytes. 4,5 PU.1 regulates the expression of almost all characterized myeloid genes, including growth factor receptors. In particular, it directs the monocyte-specific expression of the macrophage colony-stimulating factor receptor. 6,7 PU.1 probably plays an important role at several stages in the differentiation process, and there is evidence that it is active at an early stage, mediating commitment of multipotential progenitor cells to the myeloid lineage. 8 CCAAT/enhancer-binding protein alpha (C/EBP␣) was initially identified in liver and adipose tissue, where it was found to be important for terminal differentiation. 9-14 C/EBP␣ expression is prominent in immature myeloid cells. 15-17 C/EBP␣-null mice lack the entire granulocyte lineage but develop normal monocytes. 18 Recently, we identified dominant-negative mutations of C/EBP␣ in acute myeloid leukemia 19 and a down-regulation of C/EBP␣ expression by the leukemic fusion protein AML1/ETO, 20 suggesting an important role of C/EBP␣ in leukemogenesis. Ectopic expression of C/EBP␣ in U937 monocyte leukemia cells induces granulocytic differentiation over a 2-week period and inhibits monocyte differentiation. 16 These hematopoietic progenitors require PU.1 to initiate monocyte differentiation and C/EBP␣ to initiate granulopoiesis. PU.1 has been shown to interact with a C/EBP family member, C/EBP␦. 21 However, the interaction of these transcription factors in differentiating to a specific lineage is still unclear.We propose here that the granulocyte factor C/EBP␣ interacts with the myeloid master regulator PU.1 and inactivates PU.1. c-Jun belongs to the b-ZIP group of DNA-binding proteins and is a component of AP-1 transcription complexes. 22 c-Jun has been shown to be a coactivator of PU.1, resulting in increased macrophage-colony-stimulating factor (M-CSF) receptor expression, and it is involved in the development of the monocyte lineage. 23 Here we show that C/EBP␣ blocks PU.1 function by displacing c-Jun, the coactivator of PU.1. Furthermore, C/EBP␣ specifies the fate of myeloid progenitor cells to the granulocyte lineage by inactivating PU.1 through protein-protein interactions. Materials and methods Cell lines and cell cultureFibroblast F9 and 293T cells were cultured in Dulbecco Modified Eagle Medium (PAN Biotech GmbH, Karlsruhe, Germany) containing 10% fetal bovine serum (FBS; Gibco BR...

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Accumulating evidence from epidemiological studies suggests that higher γ-glutamyl transferase (GGT) levels in the blood are associated with the incident of cardiovascular disease (CVD), including atherosclerosis, and have prognostic importance. However, to the best of our knowledge, the association of the GGT level with premature coronary artery disease (CAD) in an Asian Indian population has not been evaluated. In the present study, 240 (120 unaffected and 120 CAD affected) young subjects (males, ≤45 years and females, ≤50 years) were selected. The markers assayed were GGT, high-sensitivity C-reactive protein, lipids, secretory phospholipase A2, neopterin, myeloperoxidase, interleukin-6, cystatin-C, tumor necrosis factor-like weak inducer of apoptosis and lipoprotein (a). The plasma GGT levels in these subjects showed a positive correlation with quantitative variables, such as waist circumference, triglycerides, neopterin levels and cross-sectional correlation with qualitative variable smoking. The findings suggest that the subjects in the highest tertile of GGT had a 2.1-fold [odds ratio (OR), 2.104; 95% confidence interval (CI), 1.063–4.165; P=0.033] higher risk of developing premature CAD in comparison with the reference tertile. Furthermore, a 1 U/l increase of GGT (on a log scale) increased the OR by 5.2-fold (OR, 5.208; 95% CI, 1.018–24.624; P=0.048) and 7.4-fold (OR, 7.492; 95% CI, 1.221–45.979; P=0.030) on addition of associated risk factors. In conclusion, the elevated plasma GGT levels potentially indicate increased oxidative stress and the risk of developing premature CAD. Therefore, these findings could be potentially used in the risk stratification of premature CAD following further evaluation.

Patients with cardiovascular disease show a panel of differentially regulated serum biomarkers indicative of modulation of several pathways from disease onset to progression. Few of these biomarkers have been proposed for multimarker risk prediction methods. However, the underlying mechanism of the expression changes and modulation of the pathways is not yet addressed in entirety. Our present work focuses on understanding the regulatory mechanisms at transcriptional level by identifying the core and specific transcription factors that regulate the coronary artery disease associated pathways. Using the principles of systems biology we integrated the genomics and proteomics data with computational tools. We selected biomarkers from 7 different pathways based on their association with the disease and assayed 24 biomarkers along with gene expression studies and built network modules which are highly regulated by 5 core regulators PPARG, EGR1, ETV1, KLF7 and ESRRA. These network modules in turn comprise of biomarkers from different pathways showing that the core regulatory transcription factors may work together in differential regulation of several pathways potentially leading to the disease. This kind of analysis can enhance the elucidation of mechanisms in the disease and give better strategies of developing multimarker module based risk predictions.

Coronary artery disease (CAD) is a major cause of mortality in India, more importantly the young Indians. Combinatorial and integrative approaches to evaluate pathways and genes to gain an improved understanding and potential biomarkers for risk assessment are required. Therefore, 608 genes from the CADgene database version 2.0, classified into 12 functional classes representing the atherosclerotic disease process, were analyzed. Homology analysis of the unique list of gene ontologies (GO) from each functional class gave 8 GO terms represented in 11 and 10 functional classes. Using disease ontology analysis 80 genes belonging to 8 GO terms, using FunDO suggested that 29 of them were identified to be associated with CAD. Extended network analysis of these genes using STRING version 9.1 gave 328 nodes and 4,525 interactions of which the top 5% had a node degree of ≥75 associated with pathways including the ErbB signaling pathway with epidermal growth factor receptor (EGFR) gene as the central hub. Evaluation of EFGR protein levels in age and gender-matched 342 CAD patients vs. 342 control subjects demonstrated significant differences [controls=149.76±2.47 pg/ml and CAD patients stratified into stable angina (SA)=161.65±3.40 pg/ml and myocardial infarction (MI)=171.51±4.26 pg/ml]. Logistic regression analysis suggested that increased EGFR levels exhibit 3-fold higher risk of CAD [odds ratio (OR) 3.51, 95% confidence interval [CI] 1.96–6.28, P≤0.001], upon adjustment for hypertension, diabetes and smoking. A unit increase in EGFR levels increased the risk by 2-fold for SA (OR 2.58, 95% CI 1.25–5.33, P=0.01) and 3.8-fold for MI (OR 3.82, 95% CI 1.94–7.52, P≤0.001) following adjustment. Thus, the use of ontology mapping and network analysis in an integrative manner aids in the prioritization of biomarkers of complex disease.

The objective of the study was to gain molecular insights into the progression of atherosclerosis in Apob(tm2Sgy)Ldlr(tm1Her) mice, using transcriptome profiles. Weighted gene co network analysis (WGCNA) and time course analysis using limma were used to study disease progression from 0 to 20weeks. Five co-expression modules were identified by WGCNA using the expression values of 2153 genes. Genes associated with autophagy, endoplasmic reticulum stress, inflammation and lipid metabolism were differentially expressed at early stages of atherosclerosis. Time course analysis highlighted activation of inflammatory gene signaling at 4weeks, cell proliferation and calcification at 8weeks, amyloid like structures and oxidative stress at 14weeks and enhanced production of inflammatory cytokines at 20weeks. Our results suggest that maximum gene perturbations occur during early atherosclerosis which could be the danger signals associated with subclinical disease. Understanding these genes and associated pathways can help in improvement of diagnostic and therapeutic targets for atherosclerosis.