Microarray Expression Data Identify <i>DCC</i> as a Candidate Gene for Early Meningioma Progression

<div><p>Meningiomas are the most common primary brain tumors bearing in a minority of cases an aggressive phenotype. Although meningiomas are stratified according to their histology and clinical behavior, the underlying molecular genetics predicting aggressiveness are not thoroughly understood. We performed whole transcript expression profiling in 10 grade I and four grade II meningiomas, three of which invaded the brain. Microarray expression analysis identified deleted in colorectal cancer (<i>DCC</i>) as a differentially expressed gene (DEG) enabling us to cluster meningiomas into <i>DCC</i> low expression (3 grade I and 3 grade II tumors), <i>DCC</i> medium expression (2 grade I and 1 grade II tumors), and <i>DCC</i> high expression (5 grade I tumors) groups. Comparison between the <i>DCC</i> low expression and <i>DCC</i> high expression groups resulted in 416 DEGs (<i>p</i>-value < 0.05; fold change > 2). The most significantly downregulated genes in the <i>DCC</i> low expression group comprised <i>DCC</i>, phosphodiesterase 1C (<i>PDE1C</i>), calmodulin-dependent 70kDa olfactomedin 2 (<i>OLFM2</i>), glutathione S-transferase mu 5 (<i>GSTM5</i>), phosphotyrosine interaction domain containing 1 (<i>PID1</i>), sema domain, transmembrane domain (TM) and cytoplasmic domain, (semaphorin) 6D (<i>SEMA6D</i>), and indolethylamine N-methyltransferase (<i>INMT</i>). The most significantly upregulated genes comprised chromosome 5 open reading frame 63 (<i>C5orf63</i>), homeodomain interacting protein kinase 2 (<i>HIPK2</i>), and basic helix-loop-helix family, member e40 (<i>BHLHE40</i>). Biofunctional analysis identified as predicted top upstream regulators beta-estradiol, TGFB1, Tgf beta complex, LY294002, and dexamethasone and as predicted top regulator effectors NFkB, PIK3R1, and CREBBP. The microarray expression data served also for a comparison between meningiomas from female and male patients and for a comparison between brain invasive and non-invasive meningiomas resulting in a number of significant DEGs and related biofunctions. In conclusion, based on its expression levels, <i>DCC</i> may constitute a valid biomarker to identify those benign meningiomas at risk for progression.</p></div

The predicted top regulator effects network with a consistency score of 8.489 in the <i>DCC</i> low <i>vs</i>. <i>DCC</i> high expression comparison.

<p>Upstream regulators NFkB, PIK3R1, and CREBBP target a number of DEGs including <i>MMP2</i>, <i>SERPINE2</i>, <i>DOK5</i>, <i>SLC2A5</i>, <i>FST</i>, <i>TGM2</i>, <i>NR4A3</i>, <i>TGFB3</i>, <i>BCL2</i>, <i>NCAM1</i>, <i>TLR2</i>, <i>AR</i>, <i>CTGF</i>, <i>VEGFA</i>, <i>CYR61</i>, <i>VCAM1</i>, and <i>GDF15</i>. Connected downstream functions are entitled adhesion of leukemia cell lines, differentiation of cells, sprouting (including cell morphological characteristics), cell viability, and cell movement of phagocytes.</p

Unsupervised hierarchical cluster analysis of 416 genes that were differentially expressed (<i>p</i>-value < 0.05; fold change > 2.0) between the three <i>DCC</i> expression groups.

<p>BN samples are included in cluster analysis. A number of genes is represented by more than one transcript. Meningiomas are clustering into two main branches, one of which contains the <i>DCC</i> low expression samples and a <i>DCC</i> medium expression sample that was a brain invasive case. Color scheme bar indicates comparably higher and lower expression values in red and blue color, respectively. Color scheme for samples: yellow, <i>DCC</i> low expression; green, <i>DCC</i> medium expression; orange, <i>DCC</i> high expression; BN samples, red.</p

The predicted top upstream regulators in the comparison group female <i>vs</i>. male meningioma patients are tacrolimus, glutathione, ITPR, (E)-2,3',4,5'-tetramethoxystilbene, and SLC39A4 with a <i>p</i>-value of overlap of 1.16E-03, 1.55E-03, 2.02E-03, 2.02E-03, and 2.02E-03, respectively.

<p>Target genes are <i>APOD</i>, <i>KLRC4-KLRK1</i>/<i>KLRK1</i>, <i>MYH10</i>, <i>TNC</i>, <i>SLC7A11</i>, <i>CYP1B1</i>, and <i>NELL1</i>. Upregulated and downregulated genes in red and blue color, respectively. Asterisk indicates a gene that is represented in the dataset by more than one transcript.</p

The predicted top regulator effects network with a consistency score of 13.0 in the brain invasive <i>vs</i>. non-invasive meningioma dataset.

<p>Effector molecules IFNG, IL1B, and TNF target a number of DEGs including <i>OCLN</i>, <i>FLT1</i>, <i>CYBB</i>, <i>MCAM</i>, <i>RGS1</i>, <i>ITGA4</i>, <i>SPP1</i>, <i>FCGR1A</i>, <i>FCGR2A</i>, <i>TLR2</i>, <i>THBS1</i>, <i>C3</i>, <i>SELPLG</i>, and <i>FCGR3A</i>/<i>FCGR3B</i>. Connected downstream functions are entitled, cell movement of myeloid cells, adhesion of blood cells, engulfment of cells, response of phagocytes, response of myeloid cells, binding of professional phagocytic cells, and recruitment of cells. Upregulated and downregulated genes in red and blue color, respectively. Asterisk indicates a gene that is represented in the dataset by more than one transcript.</p

PCA scatter plot as a dimensional measure for the similarity of the expression profiles of samples (colored dots).

<p>Ellipsoids represent the 95% confidence interval and are a measure for the distance of relationships between samples of a group. Green, <i>DCC</i> low expression; purple, <i>DCC</i> medium expression; blue, <i>DCC</i> low expression; red, normal brain samples (BN).</p

Prospective multicentre study in intensive care units in five cities from the Kingdom of Saudi Arabia: Impact of the International Nosocomial Infection Control Consortium (INICC) multidimensional approach on rates of central line-associated bloodstream infection

OBJECTIVE: To analyse the impact of the International Nosocomial Infection Control Consortium (INICC) Multidimensional Approach (IMA) and INICC Surveillance Online System (ISOS) on central line-associated bloodstream infection (CLABSI) rates in five intensive care units (ICUs) from October 2013 to September 2015. DESIGN: Prospective, before-after surveillance study of 3769 patients hospitalised in four adult ICUs and one paediatric ICU in five hospitals in five cities. During baseline, we performed outcome and process surveillance of CLABSI applying CDC/NHSN definitions. During intervention, we implemented IMA and ISOS, which included: (1) a bundle of infection prevention practice interventions; (2) education; (3) outcome surveillance; (4) process surveillance; (5) feedback on CLABSI rates and consequences; and (6) performance feedback of process surveillance. Bivariate and multivariate regression analyses were performed. RESULTS: During baseline, 4468 central line (CL) days and 31 CLABSIs were recorded, accounting for 6.9 CLABSIs per 1000 CL-days. During intervention, 12,027 CL-days and 37 CLABSIs were recorded, accounting for 3.1 CLABSIs per 1000 CL-days. The CLABSI rate was reduced by 56% (incidence-density rate, 0.44; 95% confidence interval, 0.28–0.72; P = 0.001). CONCLUSIONS: Implementing IMA through ISOS was associated with a significant reduction in the CLABSI rate in the ICUs of Saudi Arabia

Impact of the International Nosocomial Infection Control Consortium (INICC)’s multidimensional approach on rates of ventilator-associated pneumonia in intensive care units in 22 hospitals of 14 cities of the Kingdom of Saudi Arabia

To analyze the impact of the International Nosocomial Infection Control Consortium (INICC) Multidimensional Approach (IMA) and use of INICC Surveillance Online System (ISOS) on ventilator-associated pneumonia (VAP) rates in Saudi Arabia from September 2013 to February 2017. A multicenter, prospective, before–after surveillance study on 14,961 patients in 37 intensive care units (ICUs) of 22 hospitals. During baseline, we performed outcome surveillance of VAP applying the definitions of the CDC/NHSN. During intervention, we implemented the IMA and the ISOS, which included: (1) a bundle of infection prevention practice interventions, (2) education, (3) outcome surveillance, (4) process surveillance, (5) feedback on VAP rates and consequences and (6) performance feedback of process surveillance. Bivariate and multivariate regression analyses were performed using generalized linear mixed models to estimate the effect of intervention. The baseline rate of 7.84 VAPs per 1000 mechanical-ventilator (MV)-days―with 20,927 MV-days and 164 VAPs―, was reduced to 4.74 VAPs per 1000 MV-days―with 118,929 MV-days and 771 VAPs―, accounting for a 39% rate reduction (IDR 0.61; 95% CI 0.5–0.7; P 0.001). Implementing the IMA was associated with significant reductions in VAP rates in ICUs of Saudi Arabia