MBASED: allele-specific expression detection in cancer tissues and cell lines

Allele-specific gene expression, ASE, is an important aspect of gene regulation. We developed a novel method MBASED, meta-analysis based allele-specific expression detection for ASE detection using RNA-seq data that aggregates information across multiple single nucleotide variation loci to obtain a gene-level measure of ASE, even when prior phasing information is unavailable. MBASED is capable of one-sample and two-sample analyses and performs well in simulations. We applied MBASED to a panel of cancer cell lines and paired tumor-normal tissue samples, and observed extensive ASE in cancer, but not normal, samples, mainly driven by genomic copy number alterations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0405-3) contains supplementary material, which is available to authorized users

p21-activated kinase 1: PAK'ed with potential

The p21-activated kinases (PAKs) are central players in growth factor signaling networks and morphogenetic processes that control proliferation, cell polarity, invasion and actin cytoskeleton organization. This raises the possibility that interfering with PAK activity may produce significant anti-tumor activity. In this perspective, we summarize recent data concerning the contribution of the PAK family member, PAK1, in growth factor signaling and tumorigenesis. We further discuss mechanisms by which inhibition of PAK1 can arrest tumor growth and promote cell apoptosis, and the types of cancers in which PAK1 inhibition may hold promise

High-resolution analysis of copy number alterations and associated expression changes in ovarian tumors

<p>Abstract</p> <p>Background</p> <p>DNA copy number alterations are frequently observed in ovarian cancer, but it remains a challenge to identify the most relevant alterations and the specific causal genes in those regions.</p> <p>Methods</p> <p>We obtained high-resolution 500K SNP array data for 52 ovarian tumors and identified the most statistically significant minimal genomic regions with the most prevalent and highest-level copy number alterations (recurrent CNAs). Within a region of recurrent CNA, comparison of expression levels in tumors with a given CNA to tumors lacking that CNA and to whole normal ovary samples was used to select genes with CNA-specific expression patterns. A public expression array data set of laser capture micro-dissected (LCM) non-malignant fallopian tube epithelia and LCM ovarian serous adenocarcinoma was used to evaluate the effect of cell-type mixture biases.</p> <p>Results</p> <p>Fourteen recurrent deletions were detected on chromosomes 4, 6, 9, 12, 13, 15, 16, 17, 18, 22 and most prevalently on X and 8. Copy number and expression data suggest several apoptosis mediators as candidate drivers of the 8p deletions. Sixteen recurrent gains were identified on chromosomes 1, 2, 3, 5, 8, 10, 12, 15, 17, 19, and 20, with the most prevalent gains localized to 8q and 3q. Within the 8q amplicon, <it>PVT1</it>, but not <it>MYC</it>, was strongly over-expressed relative to tumors lacking this CNA and showed over-expression relative to normal ovary. Likewise, the cell polarity regulators <it>PRKCI </it>and <it>ECT2 </it>were identified as putative drivers of two distinct amplicons on 3q. Co-occurrence analyses suggested potential synergistic or antagonistic relationships between recurrent CNAs. Genes within regions of recurrent CNA showed an enrichment of Cancer Census genes, particularly when filtered for CNA-specific expression.</p> <p>Conclusion</p> <p>These analyses provide detailed views of ovarian cancer genomic changes and highlight the benefits of using multiple reference sample types for the evaluation of CNA-specific expression changes.</p

Small molecule inhibition of group I p21-activated kinases in breast cancer induces apoptosis and potentiates the activity of microtubule stabilizing agents

IntroductionBreast cancer, the most common cause of cancer-related deaths worldwide among women, is a molecularly and clinically heterogeneous disease. Extensive genetic and epigenetic profiling of breast tumors has recently revealed novel putative driver genes, including p21-activated kinase (PAK)1. PAK1 is a serine/threonine kinase downstream of small GTP-binding proteins, Rac1 and Cdc42, and is an integral component of growth factor signaling networks and cellular functions fundamental to tumorigenesis.MethodsPAK1 dysregulation (copy number gain, mRNA and protein expression) was evaluated in two cohorts of breast cancer tissues (n = 980 and 1,108). A novel small molecule inhibitor, FRAX1036, and RNA interference were used to examine PAK1 loss of function and combination with docetaxel in vitro. Mechanism of action for the therapeutic combination, both cellular and molecular, was assessed via time-lapse microscopy and immunoblotting.ResultsWe demonstrate that focal genomic amplification and overexpression of PAK1 are associated with poor clinical outcome in the luminal subtype of breast cancer (P = 1.29 × 10−4 and P = 0.015, respectively). Given the role for PAK1 in regulating cytoskeletal organization, we hypothesized that combination of PAK1 inhibition with taxane treatment could be combined to further interfere with microtubule dynamics and cell survival. Consistent with this, administration of docetaxel with either a novel small molecule inhibitor of group I PAKs, FRAX1036, or PAK1 small interfering RNA oligonucleotides dramatically altered signaling to cytoskeletal-associated proteins, such as stathmin, and induced microtubule disorganization and cellular apoptosis. Live-cell imaging revealed that the duration of mitotic arrest mediated by docetaxel was significantly reduced in the presence of FRAX1036, and this was associated with increased kinetics of apoptosis.ConclusionsTaken together, these findings further support PAK1 as a potential target in breast cancer and suggest combination with taxanes as a viable strategy to increase anti-tumor efficacy

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Computational inference of transcriptional regulatory networks from expression profiling and transcription factor binding site identification

We have developed a computational method for transcriptional regulatory network inference, CARRIE (Computational Ascertainment of Regu latory Relationships Inferred from Expression), which combines microarray and promoter sequence analysis. CARRIE uses sources of data to identify the transcription factors (TFs) that regulate gene expression changes in response to a stimulus and generates testable hypotheses about the regulatory network connecting these TFs to the genes they regulate. The promoter analysis component of CARRIE, ROVER (Relative OVER-abundance of cis-elements), is highly accurate at detecting the TFs that regulate the response to a stimulus. ROVER also predicts which genes are regulated by each of these TFs. CARRIE uses these transcriptional interactions to infer a regulatory network. To demonstrate our method, we applied CARRIE to six sets of publicly available DNA microarray experiments on Saccharomyces cerevisiae. The predicted networks were validated with comparisons to literature sources, experimental TF binding data, and gene ontology biological process information

CARRIE web service: automated transcriptional regulatory network inference and interactive analysis

We present an intuitive and interactive web service for CARRIE (Computational Ascertainment of Regulatory Relationships Inferred from Expression). CARRIE is a computational method that analyzes microarray and promoter sequence data to infer a transcriptional regulatory network from the response to a specific stimulus. This service displays an interactive graph of the inferred network and provides easy access to the evidence for the involvement of each gene in the network. We provide functionality to include network data in KEGG XML (KGML) format in this graph. Our service also provides Gene Ontology annotation to aid the user in forming hypotheses about the role of each gene in the cellular response. The CARRIE web service is freely available at http://zlab.bu.edu/CARRIE-web