Kingsley, Christopher

Abstract Many cancer researchers are currently generating heterogeneous genomic data sets containing mRNA expression, array based comparative genomic hybridization (aCGH), and other information from multiple patients. In the near future, data sets will likely include proteomics, methylomics, and high throughput sequencing data. Analytical tools that integrate these different data types to prioritize genes for further study have lagged, however. With this in mind, we have implemented a standalone software application that integrates CGH and mRNA expression profiling data. This application implements several different methods to generate ranked lists of genes and genomic regions based on breakpoint frequency, aberration frequency, and the impact of copy number changes on mRNA expression. The software is Java GUI based, with abstracted object models that can be extended as new genomic data types and annotations become available. We used this application to analyze aCGH datasets generated from 22 primary pancreatic tumor xenografts and mRNA expression datasets from 16 of the 22 samples. Genes which were located near a putative breakpoint and whose expression levels were high in a majority of the xenografts samples were considered putative targets. Preliminary IHC analysis of pancreas primary tumor tissue microarrays confirms one of these putative targets, Chemokine (CXC motif) Ligand 5 (CXCL5). By allowing cancer researchers to correlate genomic aberrations with expression data, we believe that this application will generate more meaningful targets for further biomarker identification and/or drug target discovery. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A30.

Abstract Malignant gliomas are the most common primary brain tumors. Despite intensive clinical investigation and significant technical advances in surgical and radiation treatment, the impact on clinical outcome for patients with malignant gliomas is disappointing. We have previously shown that tumor necrosis factor–like weak inducer of apoptosis (TWEAK), a member of the tumor necrosis factor superfamily, can stimulate glioma cell survival via binding to the Fn14 receptor, activation of the NF-κB pathway, and upregulation of BCL-XL gene expression. Here, we show that TWEAK treatment of glioma cells leads to phosphorylation of Akt and BAD. TWEAK stimulation results in the phosphorylation of both Akt1 and Akt2. However, small interfering RNA (siRNA)–mediated depletion of either Akt1 or Akt2 showed that BAD serine 136 phosphorylation is dependent specifically on Akt2 function. Depletion of Akt2 expression by siRNA also abrogates TWEAK-stimulated glioma cell survival, whereas no effect on glioma cell survival was observed after siRNA-mediated depletion of Akt1 expression. Surprisingly, although siRNA-mediated depletion of BAD in glioma cells abrogates cytotoxic- and chemotherapy-induced apoptosis, TWEAK still displays a strong protective effect, suggesting that BAD serine 136 phosphorylation plays a minor role in TWEAK-Akt2–induced glioma cell survival. We also report here that AKT2 gene expression levels increased with glioma grade and inversely correlate with patient survival. Additionally, immunohistochemical analysis showed that Akt2 expression positively correlates with Fn14 expression in glioblastoma multiforme specimens. We hypothesize that the TWEAK-Fn14 signaling axis functions, in part, to enhance glioblastoma cell survival by activation of the Akt2 serine/threonine protein kinase. (Mol Cancer Res 2009;7(11):1871–81)