Differential expression of the tumor suppressor A-kinase anchor protein 12 in human diffuse and pilocytic astrocytomas is regulated by promoter methylation

Role of A-Kinase Anchoring Protein 12 in the Central Nervous System

A-kinase anchoring protein (AKAP) 12 is a scaffolding protein that anchors various signaling proteins to the plasma membrane. These signaling proteins include protein kinase A, protein kinase C, protein phosphatase 2B, Src-family kinases, cyclins, and calmodulin, which regulate their respective signaling pathways. AKAP12 expression is observed in the neurons, astrocytes, endothelial cells, pericytes, and oligodendrocytes of the central nervous system (CNS). Its physiological roles include promoting the development of the blood-brain barrier, maintaining white-matter homeostasis, and even regulating complex cognitive functions such as long-term memory formation. Under pathological conditions, dysregulation of AKAP12 expression levels may be involved in the pathology of neurological diseases such as ischemic brain injury and Alzheimer's disease. This minireview aimed to summarize the current literature on the role of AKAP12 in the CNS.

Investigating Glioblastoma Multiforme Sub-Proteomes: A Computational Study of CUSA Fluid Proteomic Data

Based on our previous proteomic study on Cavitating Ultrasound Aspirator (CUSA) fluid pools of Newly Diagnosed (ND) and Recurrent (R) glioblastomas (GBMs) of tumor core and periphery, as defined by 5-aminolevulinc acid (5-ALA) metabolite fluorescence, this work aims to apply a bioinformatic approach to investigate specifically into three sub-proteomes, i.e., Not Detected in Brain (NB), Cancer Related (CR) and Extracellular Vesicles (EVs) proteins following selected database classification. The study of these yet unexplored specific datasets aims to understand the high infiltration capability and relapse rate that characterizes this aggressive brain cancer. Out of the 587 proteins highly confidently identified in GBM CUSA pools, 53 proteins were classified as NB. Their gene ontology (GO) analysis showed the over-representation of blood coagulation and plasminogen activating cascade pathways, possibly compatible with Blood Brain Barrier damage in tumor disease and surgery bleeding. However, the NB group also included non-blood proteins and, specifically, histones correlated with oncogenesis. Concerning CR proteins, 159 proteins were found in the characterized GBM proteome. Their GO analysis highlighted the over-representation of many pathways, primarily glycolysis. Interestingly, while CR proteins were identified in ND-GBM exclusively in the tumor zones (fluorescence positive core and periphery zones) as predictable, conversely, in R-GBM they were unexpectedly characterized prevalently in the healthy zone (fluorescence negative tumor periphery). Relative to EVs protein classification, 60 proteins were found. EVs are over-released in tumor disease and are important in the transport of biological macromolecules. Furthermore, the presence of EVs in numerous body fluids makes them a possible low-invasive source of brain tumor biomarkers to be investigated. These results give new hints on the molecular features of GBM in trying to understand its aggressive behavior and open to more in-depth investigations to disclose potential disease biomarkers.

Gene expression changes in cervical squamous cancers following neoadjuvant interventional chemoembolization

BACKGROUND

The efficacy of therapy for cervical cancer is related to the alteration of multiple molecular events and signaling networks during treatment. The aim of this study was to evaluate gene expression alterations in advanced cervical cancers before- and after-trans-uterine arterial chemoembolization- (TUACE).

METHODS

Gene expression patterns in three squamous cell cervical cancers before- and after-TUACE were determined using microarray technique. Changes in AKAP12 and CA9 genes following TUACE were validated by quantitative real-time PCR.

RESULTS

Unsupervised cluster analysis revealed that the after-TUACE samples clustered together, which were separated from the before-TUACE samples. Using a 2-fold threshold, we identified 1131 differentially expressed genes that clearly discriminate after-TUACE tumors from before-TUACE tumors, including 209 up-regulated genes and 922 down-regulated genes. Pathway analysis suggests these genes represent diverse functional categories. Results from real-time PCR confirmed the expression changes detected by microarray.

CONCLUSIONS

Gene expression signature significantly changes during TUACE therapy of cervical cancer. Theses alterations provide useful information for the development of novel treatment strategies for cervical cancers on the molecular level.

Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas

The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets for the treatment of PAs. The DNA methylation profile and gene expression profile were downloaded from the Gene Expression Omnibus database. Following screening of the differentially expressed genes (DEGs) and differentially methylated regions (DMRs), respectively, integrated analysis of the DEGs and DMRs was performed to detect their correlation. Subsequently, the WGCNA algorithm was applied to identify the significant modules and construct the co-expression network associated with PAs. Furthermore, Gene Ontology enrichment analysis of the associated genes was performed using the Database for Annotation, Visualization and Integrated Discovery. A total number of 2,259 DEGs and 235 DMRs were screened out. Integrated analysis revealed that 30 DEGs were DMRs with prominent negative correlation (cor=−0.82; P=0.02). Based on the DEGs, the gene co-expression network was constructed, and nine network modules associated with PAs were identified. The functional analysis results showed that genes relevant to PAs were closely associated with cell differentiation modulation. The screened PA-associated genes were significantly different at the expression and methylation levels. These genes may be used as reliable candidate target genes for the treatment of PAs.

Elevated AKAP12 in paclitaxel-resistant serous ovarian cancer cells is prognostic and predictive of poor survival in patients

A majority of high-grade (HG) serous ovarian cancer (SOC) patients develop resistant disease despite high initial response rates to platinum/paclitaxel-based chemotherapy. We identified shed/secreted proteins in preclinical models of paclitaxel-resistant human HGSOC models and correlated these candidate proteins with patient outcomes using public data from HGSOC patients. Proteomic analyses of a HGSOC cell line secretome was compared to those from a syngeneic paclitaxel-resistant variant and from a line established from an intrinsically chemorefractory HGSOC patient. Associations between the identified candidate proteins and patient outcome were assessed in a discovery cohort of 545 patients and two validation cohorts totaling 795 independent SOC patients. Among the 81 differentially abundant proteins identified (q < 0.05) from paclitaxel-sensitive vs -resistant HGSOC cell secretomes, AKAP12 was verified to be elevated in all models of paclitaxel-resistant HGSOC. Furthermore, elevated AKAP12 transcript expression was associated with worse progression-free and overall survival. Associations with outcome were observed in three independent cohorts and remained significant after adjusted multivariate modeling. We further provide evidence to support that differential gene methylation status is associated with elevated expression of AKAP12 in taxol-resistant ovarian cancer cells and ovarian cancer patient subsets. Elevated expression and shedding/secretion of AKAP12 is characteristic of paclitaxel-resistant HGSOC cells, and elevated AKAP12 transcript expression is a poor prognostic and predictive marker for progression-free and overall survival in SOC patients.

Prognostic biomarkers for HNSCC using quantitative real-time PCR and microarray analysis: β-tubulin isotypes and the p53 interactome

In 2014, more than 40,000 people in the United States will be diagnosed with head and neck squamous cell cancer (HNSCC) and nearly 8400 people will die of the disease (www.cancer.org/acs/groups). Little is known regarding molecular targets that might lead to better therapies and improved outcomes for these patients. The incorporation of taxanes into the standard cisplatin/5-fluouracil initial chemotherapy for HNSCC has been associated with improved response rate and survival. Taxanes target the β-subunit of the tubulin heterodimers, the major protein in microtubules, and halt cell division at G2/M phase. Both laboratory and clinical research suggest a link between β-tubulin expression and cancer patient survival, indicating that patterns of expression for β-tubulin isotypes along with activity of tumor suppressors such as p53 or micro-RNAs could be useful prognostic biomarkers and could suggest therapeutic targets. © 2014 Wiley Periodicals, Inc.