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Background: TaqMan low density array (LDA) is promising for high throughput screening in functional genomics by simultaneously measuring mRNA expression of multiple genes. However, the reproducibility and reliability remain to be explored., Methods: We applied LDA to detect mRNA expression of 95 gastrointestinal differentiation associated genes in 27 colorectal cancers with individual-matched normal mucosa. Conventional Q-PCR assay was done to detect 18 differentially expressed genes in additional 22 colorectal cancers., Results: A total of 97.2% (11,520/11,844) gene samples were successfully amplified by LDA. There was a perfect agreement between intra-LDA assays in all gene samples (CCC=0.952, p<0.0001). Seventy-nine genes showed perfect or substantial agreement between intra-LDA tests (CCC>0.713). Genes with low Ct values (<30 cycles) had more genes showing perfect agreement, less showing moderate agreement, and lower DeltaCt variances between intra-plate assays than that with high Ct values (>30 cycles) (p<0.01). All 18 genes showed the same directional changes in colorectal cancers versus normal mucosa by both SYBR Green and LDA approaches., Conclusions: LDA is a roughly robust method for gene quantification in colorectal cancer, but its reproducibility decreased in low copy genes. Hence, we strongly recommend caution when analyzing LDA results of those low copy genes.

The Epstein-Barr virus (EBV) induces B-cell proliferation with high efficiency through expression of latent proteins and microRNAs. This process takes place in vivo soon after infection, presumably to expand the virus reservoir, but can also induce pathologies, e.g. an infectious mononucleosis (IM) syndrome after primary infection or a B-cell lymphoproliferation in immunosuppressed individuals. In this paper, we investigated the growth characteristics of EBV-infected B-cells isolated from transplant recipients or patients with IM. We found that these cells grew and withstood apoptosis at highly variable rates, suggesting that the expansion rate of the infected B-cells widely varies between individuals, thereby influencing the size of the B-cell reservoir and the ability to form tumors in infected individuals. All viruses investigated were type 1 and genetically close to western strains. EBV-infected B-cells expressed the transforming EBV latent genes and microRNAs (miRNAs) at variable levels. We found that the B-cell growth rates positively correlated with the BHRF1 miRNA levels. Comparative studies showed that infected B-cells derived from transplant recipients with iEBVL on average expressed higher levels of EBV miR-BHRF1 miRNAs and grew more rapidly than B-cells from IM patients, suggesting infection by more transforming viruses. Altogether, these findings suggest that EBV infection has a highly variable impact on the B-cell compartment that probably reflects the genetic diversity of both the virus and the host. It also demonstrates the unexpected finding that B-cells from different individuals can grow at different speed under the influence of the same virus infection. [ABSTRACT FROM AUTHOR]

Introduction: Inflammatory breast cancer (IBC) is the most lethal form of breast cancers with a 5-year survival rate of only 40 %. Despite its lethality, IBC remains poorly understood which has greatly limited its therapeutic management. We thus decided to utilize an integrative functional genomic strategy to identify the Achilles' heel of IBC cells.Methods: We have pioneered the development of genetic tools as well as experimental and analytical strategies to perform RNAi-based loss-of-function studies at a genome-wide level. Importantly, we and others have demonstrated that these functional screens are able to identify essential functions linked to certain cancer phenotypes. Thus, we decided to use this approach to identify IBC specific sensitivities.Results: We identified and validated HDAC6 as a functionally necessary gene to maintain IBC cell viability, while being non-essential for other breast cancer subtypes. Importantly, small molecule inhibitors for HDAC6 already exist and are in clinical trials for other tumor types. We thus demonstrated that Ricolinostat (ACY1215), a leading HDAC6 inhibitor, efficiently controls IBC cell proliferation both in vitro and in vivo. Critically, functional HDAC6 dependency is not associated with genomic alterations at its locus and thus represents a non-oncogene addiction. Despite HDAC6 not being overexpressed, we found that its activity is significantly higher in IBC compared to non-IBC cells, suggesting a possible rationale supporting the observed dependency.Conclusion: Our finding that IBC cells are sensitive to HDAC6 inhibition provides a foundation to rapidly develop novel, efficient, and well-tolerated targeted therapy strategies for IBC patients. [ABSTRACT FROM AUTHOR]

The Connectivity Map (CMAP) project profiled human cancer cell lines exposed to a library of anticancer compounds with the goal of connecting cancer with underlying genes and potential treatments. Since the therapeutic goal of most anticancer drugs is to induce tumor-selective apoptosis, it is critical to understand the specific cell death pathways triggered by drugs. This can help to better understand the mechanism of how cancer cells respond to chemical stimulations and improve the treatment of human tumors. In this study, using CMAP microarray data from breast cancer cell line MCF7, we applied a Gaussian Bayesian network modeling approach and identified apoptosis as a major drug-induced cellular-pathway. We then focused on 13 apoptotic genes that showed significant differential expression across all drug-perturbed samples to reconstruct the apoptosis network. In our predicted subnetwork, 9 out of 15 high-confidence interactions were validated in the literature, and our inferred network captured two major cell death pathways by identifying BCL2L11 and PMAIP1 as key interacting players for the intrinsic apoptosis pathway and TAXBP1 and TNFAIP3 for the extrinsic apoptosis pathway. Our inferred apoptosis network also suggested the role of BCL2L11 and TNFAIP3 as “gateway” genes in the drug-induced intrinsic and extrinsic apoptosis pathways. [ABSTRACT FROM AUTHOR]

Summary: Glucocorticoid resistance is a major driver of therapeutic failure in T cell acute lymphoblastic leukemia (T-ALL). Here, we identify the AKT1 kinase as a major negative regulator of the NR3C1 glucocorticoid receptor protein activity driving glucocorticoid resistance in T-ALL. Mechanistically, AKT1 impairs glucocorticoid-induced gene expression by direct phosphorylation of NR3C1 at position S134 and blocking glucocorticoid-induced NR3C1 translocation to the nucleus. Moreover, we demonstrate that loss of PTEN and consequent AKT1 activation can effectively block glucocorticoid-induced apoptosis and induce resistance to glucocorticoid therapy. Conversely, pharmacologic inhibition of AKT with MK2206 effectively restores glucocorticoid-induced NR3C1 translocation to the nucleus, increases the response of T-ALL cells to glucocorticoid therapy, and effectively reverses glucocorticoid resistance in vitro and in vivo. [Copyright &y& Elsevier]

Abstract: Sequence tag count-based gene expression analysis is potent for the identification of candidate genes relevant to the cancerous phenotype. With the public availability of count-based data, the computational approaches for differentially expressed genes, which are mainly based on Binomial or beta-Binomial distribution, become practical and important in cancer biology. It remains a permanent need to select a proper statistical model for these methods. In this study, we developed a novel Bayesian algorithm-based method, Electronic Differential Gene Expression Screener (EDGES), in which a statistical model was determined by geometric averaging of 12 common housekeeping genes. EDGES identified a set of differentially expressed genes in lung, breast and colorectal cancers by using publically available Serial Analysis of Gene Expression (SAGE) and Expressed Sequence Tag (EST data). Gene expression microarray analysis and quantitative reverse transcription real-time PCR demonstrated the effectiveness of this procedure. We conclude that current normalization of calibrators provides a new insight into count-based digital subtraction in cancer research. [Copyright &y& Elsevier]

Glucocorticoids play a fundamental role in the treatment of all lymphoid tumors because of their capacity to induce apoptosis in lymphoid progenitor cells. The importance of glucocorticoid therapy in lymphoid malignancies is underscored by the strong association of glucocorticoid response with prognosis in childhood acute lymphoblastic leukemia (ALL). Thus, the identification of the molecular mechanisms contributing to glucocorticoid resistance and the development of therapeutic strategies to enhance the efficacy of glucocorticoids is of maximal relevance for the treatment of T-ALL. Glucocortioid resistance is a complex and probably molecularly heterogeneous phenotype. However, glucocorticoid-resistant leukemias show a distinct gene expression signature that probably reflects common underlying molecular mechanisms. Here we used reverse engineering of transcriptional regulatory networks and master regulator analysis to identify the AKT1 kinase as a signaling factor driving glucocorticoid resistance in T-ALL. Mechanistically, we show that AKT1 directly interacts with and phosphorylates the glucocorticoid receptor NR3C1 protein at position S134. This phosphorylation blocks glucocorticoid-induced NR3C1 translocation to the nucleus, which is strictly required for the activation of glucocorticoid-induced apoptosis. Consistently, we demonstrate that pharmacologic inhibition of AKT1 increases the response of T-ALL cells to glucocorticoid therapy and effectively reverses glucocorticoid resistance in T-ALL cell lines, primary patient samples and mouse models of glucocorticoid resistance in vitro and in vivo. Overall, these results indicate that AKT inhibition can reverse glucocorticoid resistance in human leukemia and warrant the clinical testing of AKT inhibitors and glucocorticoids in combination for the treatment of T-ALL. Finally our results demonstrate that reverse engineering of signaling networks can be exploited to identify relevant therapeutic targets for the reversal of chemotherapy resistance in human cancer. [ABSTRACT FROM AUTHOR]