1,354,384 research outputs found
Lysine-specific modifications of p53: a matter of life and death?
No full textPost-translational modifications provide a fine-tuned control of protein function(s) in the cell. The well-known tumour suppressor p53 is subject to many post-translational modifications, which alter its activity, localization and stability, thus ultimately modulating its response to various forms of genotoxic stress. In this review, we focus on the role of recently discovered lysine-specific modifications of p53, methylation and acetylation in particular, and their effects on p53 activity in damaged cells. We also discuss a possibility of mutual influence of covalent modifications in the p53 and histone proteins located in the vicinity of p53 binding sites in chromatin and propose important ramifications stemming from this hypothesis
Google search data for psychological scientists: a tutorial and best practices
No full textGoogle searches have been described as the most important dataset on the human psyche ever assembled. Google search data—accessible through a tool called Google Trends—can provide new insights on topics as varied as stereotypes and prejudices, political attitudes, religious identity and belief, personality, motivations, psychological well-being, mental health, and culture. Google Trends can generate highly customized datasets: Users can compare the popularity of search terms across most of the world, or access longitudinal data as far back as 2004, and they can do so with high geographical and temporal granularity. Notwithstanding these opportunities, Google Trends has significant limitations. Without appropriate caution, users can easily rely on data that are not meaningful or draw mistaken conclusions. We provide a comprehensive overview and tutorial, covering (a) opportunities of Google Trends for psychological scientists; (b) how Google Trends scores are calculated, how reliable they are, and why some queries might yield low-quality data; (c) instructions with accompanying R code for creating custom datasets beyond what Google Trends provides by default; (d) example analyses for studies that could be done using Google Trends data; (e) an overview of common pitfalls; and (f) recommendations for safeguarding data quality and their interpretation
DNA damage-induced ubiquitylation of proteasome controls its proteolytic activity
No full textStability of proteins is largely controlled by post-translational covalent modifications. Among those, ubiquitylation plays a central role as it marks the proteins for proteasome-dependent degradation. Proteolytic activities of proteasomes are critical for execution of various cellular processes, including DNA damage signaling and repair. However, very little is known about the regulation of proteasomal activity in cells during genotoxic stress. Here we investigated post-translational modifications of the 20S proteasomal subunits upon DNA damage induced by doxorubicin. Using mass-spectrometry, we found novel sites of phosphorylation and ubiquitylation in multiple proteasome subunits upon doxorubicin treatment. Ectopic co-expression of proteasome subunits and tagged ubiquitin confirmed the presence of ubiquitylated forms of PSMA5, PSMA1, PSMA3 and PSMB5 in cells. Moreover, we demonstrated that ubiquitylation in vitro inhibited chymotrypsin-like and caspase-like activities of proteasomes. In vivo, doxorubicin increased the activity of proteasomes, paralleling with attenuation of the overall level of proteasome ubiquitylation. Collectively, our results suggest a novel mechanism whereby the proteolytic activities of proteasomes are dynamically regulated by ubiquitylation upon DNA damage
PPISURV: a novel bioinformatics tool for uncovering the hidden role of specific genes in cancer survival outcome
No full textMultiple clinical studies have correlated gene expression with survival outcome in cancer on a genome-wide scale. However, in many cases, no obvious correlation between expression of well-known tumour-related genes (that is, p53, p73 and p21) and survival rates of patients has been observed. This can be mainly explained by the complex molecular mechanisms involved in cancer, which mask the clinical relevance of a gene with multiple functions if only gene expression status is considered. As we demonstrate here, in many such cases, the expression of the gene interaction partners (gene 'interactome') correlates significantly with cancer survival and is indicative of the role of that gene in cancer. On the basis of this principle, we have implemented a free online datamining tool (http://www.bioprofiling.de/PPISURV). PPISURV automatically correlates expression of an input gene interactome with survival rates on >40 publicly available clinical expression data sets covering various tumours involving about 8000 patients in total. To derive the query gene interactome, PPISURV employs several public databases including protein-protein interactions, regulatory and signalling pathways and protein post-translational modifications
MIRUMIR: an online tool to test microRNAs as biomarkers to predict survival in cancer using multiple clinical data sets
No full textThe microRNA and p53 families join forces against cancer
No full textThe product of the TP53 gene, p53, is one of the most recognised and extensively studied molecules that protects multicellular organisms from cancer. The well-deserved fame of p53 stems from the nature of its function – to coordinate an appropriate cellular response to various forms of genotoxic stress through cell cycle arrest, senescence and/or apoptosis. Given the importance of this role, it is not, perhaps, surprising that p53 was found to be inactive in more than half of human cancers. It should be noted that p53 does not work alone but cooperates with two ancestral proteins of the same family, p63 and p73. Aiming to broaden our understanding of the function of the p53 family of proteins in cancer, the mini-symposium held in the University of Leicester provided an opportunity for scientists and clinicians to exchange knowledge and expertise and to establish new collaborations. The main focus of this event was on the recently emerged link between the p53 family members and microRNA during cancer development
sj-docx-1-spp-10.1177_19485506211060724 – Supplemental material for Weight Location Moderates Weight-Based Self-Devaluation and Perceived Social Devaluation in Women
No full textSupplemental material, sj-docx-1-spp-10.1177_19485506211060724 for Weight Location Moderates Weight-Based Self-Devaluation and Perceived Social Devaluation in Women by Michael Barlev, Ahra Ko, Jaimie A. Krems and Steven L. Neuberg in Social Psychological and Personality Science</p
The 26S proteasome is a multifaceted target for anti-cancer therapies
No full textProteasomes play a critical role in the fate of proteins that are involved in major cellular processes, including signal transduction, gene expression, cell cycle, replication, differentiation, immune response, cellular response to stress, etc. In contrast to non-specific degradation by lysosomes, proteasomes are highly selective and destroy only the proteins that are covalently labelled with small proteins, called ubiquitins. Importantly, many diseases, including neurodegenerative diseases and cancers, are intimately connected to the activity of proteasomes making them an important pharmacological target. Currently, the vast majority of inhibitors are aimed at blunting the proteolytic activities of proteasomes. However, recent achievements in solving structures of proteasomes at very high resolution provided opportunities to design new classes of small molecules that target other physiologically-important enzymatic activities of proteasomes, including the de-ubiquitinating one. This review attempts to catalog the information available to date about novel classes of proteasome inhibitors that may have important pharmacological ramifications
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Current Genome Editing Tools in Gene Therapy: New Approaches to Treat Cancer
No full textGene therapy suggests a promising approach to treat genetic diseases by applying genes as pharmaceuticals. Cancer is a complex disease, which strongly depends on a particular genetic make-up and hence can be treated with gene therapy. From about 2,000 clinical trials carried out so far, more than 60% were cancer targeted. Development of precise and effective gene therapy approaches is intimately connected with achievements in the molecular biology techniques. The field of gene therapy was recently revolutionized by the introduction of "programmable" nucleases, including ZFNs, TALENs, and CRISPR, which target specific genomic loci with high efficacy and precision. Furthermore, when combined with DNA transposons for the delivery purposes into cells, these programmable nucleases represent a promising alternative to the conventional viral-mediated gene delivery. In addition to "programmable" nucleases, a new class of TALE-and CRISPR-based "artificial transcription effectors" has been developed to mediate precise regulation of specific genes. In sum, these new molecular tools may be used in a wide plethora of gene therapy strategies. This review highlights the current status of novel genome editing tools and discusses their suitability and perspectives in respect to cancer gene therapy studies
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