Actin nucleation by WH2 domains at the autophagosome

Autophagy is a catabolic process whereby cytosolic components and organelles are degraded to recycle key cellular materials. It is a constitutive process required for proper tissue homoeostasis but can be rapidly regulated by a variety of stimuli (for example, nutrient starvation and chemotherapeutic agents). JMY is a DNA damage-responsive p53 cofactor and actin nucleator important for cell survival and motility. Here we show that JMY regulates autophagy through its actin nucleation activity. JMY contains an LC3-interacting region, which is necessary to target JMY to the autophagosome where it enhances the autophagy maturation process. In autophagosomes, the integrity of the WH2 domains allows JMY to promote actin nucleation, which is required for efficient autophagosome formation. Thus our results establish a direct role for actin nucleation mediated by WH2 domain proteins that reside at the autophagosome

Regulation of actin nucleation and autophagosome formation

Autophagy is a process of self-eating, whereby cytosolic constituents are enclosed by a double-membrane vesicle before delivery to the lysosome for degradation. This is an important process which allows for recycling of nutrients and cellular components and thus plays a critical role in normal cellular homeostasis as well as cell survival during stresses such as starvation or hypoxia. A large number of proteins regulate various stages of autophagy in a complex and still incompletely understood series of events. In this review, we will discuss recent studies which provide a growing body of evidence that actin dynamics and proteins that influence actin nucleation play an important role in the regulation of autophagosome formation and maturation

Functional interplay between E2F7 and ribosomal rRNA gene transcription regulates protein synthesis

A prerequisite for protein synthesis is the transcription of ribosomal rRNA genes by RNA polymerase I (Pol I), which controls ribosome biogenesis. UBF (upstream binding factor) is one of the main Pol I transcription factors located in the nucleolus that activates rRNA gene transcription. E2F7 is an atypical E2F family member that acts as a transcriptional repressor of E2F target genes, and thereby contributes to cell cycle arrest. Here, we describe an unexpected role for E2F7 in regulating rRNA gene transcription. We have found that E2F7 localises to the perinucleolar region, and further that E2F7 is able to exert repressive effects on Pol I transcription. At the mechanistic level, this is achieved in part by E2F7 hindering UBF recruitment to the rRNA gene promoter region, and thereby reducing rRNA gene transcription, which in turn compromises global protein synthesis. Our results expand the target gene repertoire influenced by E2F7 to include Pol I-regulated genes, and more generally suggest a mechanism mediated by effects on Pol I transcription where E2F7 links cell cycle arrest with protein synthesis

E2F1 Regulates Cellular Growth by mTORC1 Signaling

During cell proliferation, growth must occur to maintain homeostatic cell size. Here we show that E2F1 is capable of inducing growth by regulating mTORC1 activity. The activation of cell growth and mTORC1 by E2F1 is dependent on both E2F1's ability to bind DNA and to regulate gene transcription, demonstrating that a gene induction expression program is required in this process. Unlike E2F1, E2F3 is unable to activate mTORC1, suggesting that growth activity could be restricted to individual E2F members. The effect of E2F1 on the activation of mTORC1 does not depend on Akt. Furthermore, over-expression of TSC2 does not interfere with the effect of E2F1, indicating that the E2F1-induced signal pathway can compensate for the inhibitory effect of TSC2 on Rheb. Immunolocalization studies demonstrate that E2F1 induces the translocation of mTORC1 to the late endosome vesicles, in a mechanism dependent of leucine. E2F1 and leucine, or insulin, together affect the activation of S6K stronger than alone suggesting that they are complementary in activating the signal pathway. From these studies, E2F1 emerges as a key protein that integrates cell division and growth, both of which are essential for cell proliferation

The Interplay between NF-kappaB and E2F1 Coordinately Regulates Inflammation and Metabolism in Human Cardiac Cells

Pyruvate dehydrogenase kinase 4 (PDK4) inhibition by nuclear factor-κB (NF-κB) is related to a shift towards increased glycolysis during cardiac pathological processes such as cardiac hypertrophy and heart failure. The transcription factors estrogen-related receptor-α (ERRα) and peroxisome proliferator-activated receptor (PPAR) regulate PDK4 expression through the potent transcriptional coactivator PPARγ coactivator-1α (PGC-1α). NF-κB activation in AC16 cardiac cells inhibit ERRα and PPARβ/δ transcriptional activity, resulting in reduced PGC-1α and PDK4 expression, and an enhanced glucose oxidation rate. However, addition of the NF-κB inhibitor parthenolide to these cells prevents the downregulation of PDK4 expression but not ERRα and PPARβ/δ DNA binding activity, thus suggesting that additional transcription factors are regulating PDK4. Interestingly, a recent study has demonstrated that the transcription factor E2F1, which is crucial for cell cycle control, may regulate PDK4 expression. Given that NF-κB may antagonize the transcriptional activity of E2F1 in cardiac myocytes, we sought to study whether inflammatory processes driven by NF-κB can downregulate PDK4 expression in human cardiac AC16 cells through E2F1 inhibition. Protein coimmunoprecipitation indicated that PDK4 downregulation entailed enhanced physical interaction between the p65 subunit of NF-κB and E2F1. Chromatin immunoprecipitation analyses demonstrated that p65 translocation into the nucleus prevented the recruitment of E2F1 to the PDK4 promoter and its subsequent E2F1-dependent gene transcription. Interestingly, the NF-κB inhibitor parthenolide prevented the inhibition of E2F1, while E2F1 overexpression reduced interleukin expression in stimulated cardiac cells. Based on these findings, we propose that NF-κB acts as a molecular switch that regulates E2F1-dependent PDK4 gene transcription

The Marker State Space (MSS) Method for Classifying Clinical Samples

The development of accurate clinical biomarkers has been challenging in part due to the diversity between patients and diseases. One approach to account for the diversity is to use multiple markers to classify patients, based on the concept that each individual marker contributes information from its respective subclass of patients. Here we present a new strategy for developing biomarker panels that accounts for completely distinct patient subclasses. Marker State Space (MSS) defines "marker states" based on all possible patterns of high and low values among a panel of markers. Each marker state is defined as either a case state or a control state, and a sample is classified as case or control based on the state it occupies. MSS was used to define multi-marker panels that were robust in cross validation and training-set/test-set analyses and that yielded similar classification accuracy to several other classification algorithms. A three-marker panel for discriminating pancreatic cancer patients from control subjects revealed subclasses of patients based on distinct marker states. MSS provides a straightforward approach for modeling highly divergent subclasses of patients, which may be adaptable for diverse applications. © 2013 Fallon et al

Systematic identification of conserved motif modules in the human genome

<p>Abstract</p> <p>Background</p> <p>The identification of motif modules, groups of multiple motifs frequently occurring in DNA sequences, is one of the most important tasks necessary for annotating the human genome. Current approaches to identifying motif modules are often restricted to searches within promoter regions or rely on multiple genome alignments. However, the promoter regions only account for a limited number of locations where transcription factor binding sites can occur, and multiple genome alignments often cannot align binding sites with their true counterparts because of the short and degenerative nature of these transcription factor binding sites.</p> <p>Results</p> <p>To identify motif modules systematically, we developed a computational method for the entire non-coding regions around human genes that does not rely upon the use of multiple genome alignments. First, we selected orthologous DNA blocks approximately 1-kilobase in length based on discontiguous sequence similarity. Next, we scanned the conserved segments in these blocks using known motifs in the TRANSFAC database. Finally, a frequent pattern mining technique was applied to identify motif modules within these blocks. In total, with a false discovery rate cutoff of 0.05, we predicted 3,161,839 motif modules, 90.8% of which are supported by various forms of functional evidence. Compared with experimental data from 14 ChIP-seq experiments, on average, our methods predicted 69.6% of the ChIP-seq peaks with TFBSs of multiple TFs. Our findings also show that many motif modules have distance preference and order preference among the motifs, which further supports the functionality of these predictions.</p> <p>Conclusions</p> <p>Our work provides a large-scale prediction of motif modules in mammals, which will facilitate the understanding of gene regulation in a systematic way.</p

Overexpression of E2F-5 correlates with a pathological basal phenotype and a worse clinical outcome

The purpose of the present study is to identify genes that contribute to cell proliferation or differentiation of breast cancers independent of signalling through the oestrogen receptor (ER) or human epidermal growth factor receptor 2 (HER2). An oligonucleotide microarray assayed 40 tumour samples from ER(+)/HER2(−), ER(+)/HER2(+), ER(−)/HER2(+), and ER(−)/HER2(−) breast cancer tissues. Quantitative reverse transcriptase PCR detected overexpression of a cell cycle-related transcription factor, E2F-5, in ER-negative breast cancers, and fluorescence in situ hybridisation detected gene amplification of E2F-5 in 5 out of 57 (8.8%) breast cancer samples. No point mutations were found in the DNA-binding or DNA-dimerisation domain of E2F-5. Immunohistochemically, E2F-5-positive cancers correlated with a higher Ki-67 labelling index (59.5%, P=0.001) and higher histological grades (P=0.049). E2F-5-positive cancers were found more frequently in ER(−)/progesterone receptor (PgR)(−)/HER2(−) cancer samples (51.9%, P=0.0049) and in breast cancer samples exhibiting a basal phenotype (56.0%, P=0.0012). Disease-free survival in node-negative patients with E2F-5-positive cancers was shorter than for patients with E2F-5-negative cancers. In conclusion, we identify, for the first time, a population of breast cancer cells that overexpress the cell cycle-related transcription factor, E2F-5. This E2F-5-positive breast cancer subtype was associated with an ER(−)/PgR(−)/HER2(−) status, a basal phenotype, and a worse clinical outcome

Imaging biomarker roadmap for cancer studies.

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.Development of this roadmap received support from Cancer Research UK and the Engineering and Physical Sciences Research Council (grant references A/15267, A/16463, A/16464, A/16465, A/16466 and A/18097), the EORTC Cancer Research Fund, and the Innovative Medicines Initiative Joint Undertaking (grant agreement number 115151), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution