Human Anti-Human WIP (Phospho S488) monoclonal Antibody, clone SFB648 [APC]

We tried to identify molecular markers in peripheral blood to predict high risk of aneurysm rupture. Extraction of the total population of peripheral blood mononuclear cell (PBMC) from total blood volume, total RNA extraction from PBMC and Agilent One Color Gene-expression Oligo-Microarray were performed on peripheral venous blood samples from 45 patients with ruptured, unruptured cerebral aneurysms and control group (15). Mean foreground/ background signal intensities and A (log2(R*G)/2) values were calculated for each spot. Genes with absolute fold change (FC) >= +/- 1.5 and p-value < 0.05 were considered differentially expressed in the 3 groups (Student T-test). Genes coding for MMPs were strongly underexpressed in ruptured aneurysms group, suggesting a possible role in aneurysms development more than their rupture. Genes coding for adhesine proteins of the extracellular matrix (ICAM1) and cytoskeleton (WIPF1,TUBA4A) were underexpressed in ruptured aneurysms. Genes coding proteins involved in the regulation of apoptotic processes may be important in aneurysm development and rupture, resulting into an increased rate of remodeling processes in the arterial wall. Fas coding gene, SUM01, ZFAT, BCL2, CCR5 genes were all over-represented in unruptured aneurysms. The coexisting over-representation of pro-apoptotic genes and the underexpression of cytoskeleton and extracellular matrix genes confirms that aneurysms development and evolution are part of a degenerative process of the arterial wall not involved in aneurysms rupture. MMPs may be involved in repairing chronic damages to the arterial walls and preventing SAH. Unexpectedly, Heat Shock Proteins (HSP90AA1, HSPA1A, HSPB1), G and RAS proteins, generally activated by stress situations were under-represented in aneurysmal walls. Further PCR and Western Blotting studies are needed to confirm such findings and to identify diagnostic and prognostic markers in order to define screening protocols for intracranial aneurysms.

The heterogeneity in head and neck squamous cell carcinoma (HNSCC) has made reliable stratification extremely challenging. Behavioral risk factors such as smoking and alcohol consumption contribute to this heterogeneity. To help elucidate potential mechanisms of progression in HNSCC, we focused on elucidating patterns of gene interactions associated with tumor progression. We performed de-novo gene co-expression network inference utilizing 229 patient samples from The Cancer Genome Atlas (TCGA) previously annotated by Bornstein et al. (2016). Differential network analysis allowed us to contrast progressor and non-progressor cohorts. Beyond standard differential expression (DE) analysis, this approach evaluates changes in gene expression variance (differential variability DV) and changes in covariance, which we denote as differential wiring (DVV). The set of affected genes was overlaid onto the co-expression network, identifying 12 modules significantly enriched in DE, DV, and/or DW genes. Additionally, we identified modules correlated with behavioral measures such as alcohol consumption and smoking status. In the module enriched for differentially wired genes, we identified network hubs including IL1 ORA, DOK2, APBB1I UBASH3A, SASH3, CELF2, TRAF3IP3, GIMAP6, IVIY01E NCKAP1L, WAS, FERMT3, SLA, SELPLG, TNFRSF1B. WIPF1, AMICA1. PTPN22; the network centrality and progression specificity of these genes suggest a potential role in tumor evolution mechanisms related to inflammation and microenvironment. The identification of this network-based gene signature could be further developed to guide progression stratification, highlighting how network approaches may help improve clinical research end points and ultimately aid in clinical utility.