Unraveling a tumor type-specific regulatory core underlying E2F1-mediated epithelial-mesenchymal transition to predict receptor protein signatures

Cancer is a disease of subverted regulatory pathways. In this paper, we reconstruct the regulatory network around E2F, a family of transcription factors whose deregulation has been associated to cancer progression, chemoresistance, invasiveness, and metastasis. We integrate gene expression profiles of cancer cell lines from two E2F1-driven highly aggressive bladder and breast tumors, and use network analysis methods to identify the tumor type-specific core of the network. By combining logic-based network modeling, in vitro experimentation, and gene expression profiles from patient cohorts displaying tumor aggressiveness, we identify and experimentally validate distinctive, tumor type-specific signatures of receptor proteins associated to epithelial-mesenchymal transition in bladder and breast cancer. Our integrative network-based methodology, exemplified in the case of E2F1-induced aggressive tumors, has the potential to support the design of cohort- as well as tumor type-specific treatments and ultimately, to fight metastasis and therapy resistance

Conceptual and Measurement Issues in Assessing Democratic Backsliding

During the past decade, analyses drawing on several democracy measures have shown a global trend of democratic retrenchment. While these democracy measures use radically different methodologies, most partially or fully rely on subjective judgments to produce estimates of the level of democracy within states. Such projects continuously grapple with balancing conceptual coverage with the potential for bias (Munck and Verkuilen 2002; Przeworski et al. 2000). Little and Meng (L&M) (2023) reintroduce this debate, arguing that “objective” measures of democracy show little evidence of recent global democratic backsliding.1 By extension, they posit that time-varying expert bias drives the appearance of democratic retrenchment in measures that incorporate expert judgments. In this article, we engage with (1) broader debates on democracy measurement and democratic backsliding, and (2) L&M’s specific data and conclusions

Die Übersetzung des „Oxford Elbow Score“ (OES) in die deutsche Version der „Oxford Ellenbogen Bewertung“ (OEB)

Hintergrund: In Deutschland gibt es in der physiotherapeutischen Praxis bisher lediglich 2 Fragebögen, die ellenbogenspezifische Beschwerden aus der Patientenperspektive erfassen und einen therapeutischen Erfolg messen. Ziel: Das Ziel dieser Studie war daher die Übersetzung des englischen „Oxford Elbow Score“ (OES) ins Deutsche. Methode: Der OES wurde anhand von 2 Leitlinien zur kulturellen Adaption ins Deutsche übersetzt. Es wurden 2 unabhängige Vorwärtsübersetzungen erstellt und miteinander verglichen. Anschließend erfolgten 2 unabhängige Rückwärtsübersetzungen, gefolgt von einem Review. Der daraus resultierende Fragebogen wurde in 2 Testphasen mit jeweils 5 Probanden qualitativ auf seine Verständlichkeit und kulturelle Stimmigkeit überprüft. Ergebnisse: Der OES wurde in die deutsche Version der „Oxford Ellenbogen Bewertung“ (OEB) übersetzt und adaptiert. Nach der 1. Pilotphase wurden kleinere Änderungen am Fragebogen vorgenommen. Die Überprüfung in der 2. Testphase machte weitere Änderungen überflüssig. Schlussfolgerung: Eine autorisierte Version des OES konnte erfolgreich ins Deutsche übersetzt werden. Deren Gütekriterien werden in einer nachfolgenden Studie untersucht

Replication Data for: "What Makes Experts Reliable? Expert reliability and the estimation of latent traits."

This file contains replication data for the article "What makes experts reliable? Expert reliability and the estimation of latent traits.

A Systems-Based Key Innovation-Driven Approach Infers Co-option of Jaw Developmental Programs During Cancer Progression.

Cancer acquires metastatic potential and evolves via co-opting gene regulatory networks (GRN) of embryonic development and tissue homeostasis. Such GRNs are encoded in the genome and frequently conserved among species. Considering that all metazoa have evolved from a common ancestor via major macroevolutionary events which shaped those GRNs and increased morphogenetic complexity, we sought to examine whether there are any key innovations that may be consistently and deterministically linked with metastatic potential across the metazoa clades. To address tumor evolution relative to organismal evolution, we revisited and retrospectively juxtaposed seminal laboratory and field cancer studies across taxa that lie on the evolutionary lineage from cnidaria to humans. We subsequently applied bioinformatics to integrate species-specific cancer phenotypes, multiomics data from up to 42 human cancer types, developmental phenotypes of knockout mice, and molecular phylogenetics. We found that the phenotypic manifestations of metastasis appear to coincide with agnatha-to-gnathostome transition. Genes indispensable for jaw development, a key innovation of gnathostomes, undergo mutations or methylation alterations, are aberrantly transcribed during tumor progression and are causatively associated with invasion and metastasis. There is a preference for deregulation of gnathostome-specific versus pre-gnathostome genes occupying hubs of the jaw development network. According to these data, we propose our systems-based model as an in silico tool the prediction of likely tumor evolutionary trajectories and therapeutic targets for metastasis prevention, on the rationale that the same genes which are essential for key innovations that catalyzed vertebrate evolution, such as jaws, are also important for tumor evolution

Introducing the Historical Varieties of Democracy Dataset: Political Institutions in the Long 19th Century

The Historical Varieties of Democracy Dataset (Historical V-Dem) is a new dataset containing about 260 indicators, both factual and evaluative, describing various aspects of political regimes and state institutions. The dataset covers 91 polities globally – including most large, sovereign states, as well as some semi-sovereign entities and large colonies – from 1789 to 1920 for many cases. The majority of the indicators are also included in the Varieties of Democracy dataset, which covers the period from 1900 to the present – and together these two datasets cover the bulk of “modern history”. Historical V-Dem also includes several new indicators, covering features that are pertinent for 19th century polities. We describe the data, the process of coding, and the different strategies employed in Historical V-Dem to cope with issues of reliability and validity and ensure inter-temporal- and cross-country comparability. To illustrate the potential uses of the dataset we provide a descriptive account of patterns of democratization in the “long 19th century.” Finally, we perform an empirical investigation of how inter-state war relates to subsequent democratization.We gratefully acknowledge coding efforts and other research assistance provided by Solveig Bjørkholt, Ben Chatterton, Vlad Ciobanu, Lee Cojocaru, Vilde Lunnan Djuve, Kristian Frederiksen, Sune Orloff Hellegaard, Bernardo Isola, Sindre Haugen, Haakon Haugevik Jernsletten, Claudia Maier, Swaantje Marten, Selemon Negash, Moa Olin, Konstantinos Skenteri, and Katharina Sibbers; help with constructing vignettes by Amanda Haraldsson, Kersti Hazell and Alexander Kuhn; assistance with implementing the measurement model by Joshua Krusell and Johannes von Römer; and help with creating expert surveys, managing the data, coordinating, discussing and resolving conceptual and technical issues, etc., by numerous people at the V-Dem Institute in Gothenburg, including Frida Andersson, Staffan I. Lindberg, Valeriya Mechkova, Moa Olin, Josefine Pernes, Laura Saxer, and Natalia Stepanova. We also thank our country experts and numerous scholars (who are too many to mention), both inside and outside the wider V-Dem team, for inputs at various stages in the process. Finally, we acknowledge funding from various larger and smaller grants for the data collection for Historical V-Dem (see V-Dem Organization and Management document for details). The two largest sources of funding were Swedish Research Council Grant 421-2014-1283, PI: Jan Teorell, Department of Political Science, Lund University and Norwegian Research Council Grant pnr 240505, PI: Carl Henrik Knutsen, Department of Political Science, University of Oslo. Another main funding source was Innovationsfonden Grant 4110-00002B, PI: Svend-Erik Skaaning, Department of Political Science, Aarhus University. Further, the V-Dem data collection was supported by Riksbankens Jubileumsfond, Grant M13-0559:1, PI: Staffan I. Lindberg, V-Dem Institute, University of Gothenburg, Sweden; by Knut and Alice Wallenberg Foundation to Wallenberg Academy Fellow Staffan I. Lindberg, Grant 2013.0166, V-Dem Institute, University of Gothenburg, Sweden; as well as by internal grants from the Vice-Chancellor’s office, the Dean of the College of Social Sciences, and the Department of Political Science at University of Gothenburg. We performed simulations and other computational tasks using resources provided by the Notre Dame Center for Research Computing (CRC) through the High Performance Computing section and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre in Sweden, SNIC 2017/1-407 and 2017/1-68. We specifically acknowledge the assistance of In-Saeng Suh at CRC and Johan Raber at SNIC in facilitating our use of their respective systems

Method for the enzymatic galactosylation of monosaccharides and oligosaccharides

publication date: 1999-10-05; filing date: 1996-05-0

Neural Networks Recapitulation by Cancer Cells Promotes Disease Progression: A Novel Role of p73 Isoforms in Cancer-Neuronal Crosstalk

Mechanisms governing tumor progression differ from those of initiation. One enigmatic prometastatic process is the recapitulation of pathways of neural plasticity in aggressive stages. Cancer and neuronal cells develop reciprocal interactions via mutual production and secretion of neuronal growth factors, neurothrophins and/or axon guidance molecules in the tumor microenvironment. Understanding cancer types where this process is active, as well as the drivers, markers and underlying mechanisms, has great significance for blocking tumor progression and improving patient survival. By applying computational and systemic approaches, in combination with experimental validations, we provide compelling evidence that genes involved in neuronal development, differentiation and function are reactivated in tumors and predict poor patient outcomes across various cancers. Across cancers, they co-opt genes essential for the development of distinct anatomical parts of the nervous system, with a frequent preference for cerebral cortex and neural crest-derived enteric nerves. Additionally, we show that p73, a transcription factor with a dual role in neuronal development and cancer, simultaneously induces neurodifferentiation and stemness markers during melanoma progression. Our data yield the basis for elucidating driving forces of the nerve–tumor cell crosstalk and highlight p73 as a promising regulator of cancer neurobiology

Neural Networks Recapitulation by Cancer Cells Promotes Disease Progression: A Novel Role of p73 Isoforms in Cancer-Neuronal Crosstalk.

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MiR-205-5p and miR-342-3p cooperate in the repression of the E2F1 transcription factor in the context of anticancer chemotherapy resistance

High rates of lethal outcome in tumour metastasis are associated with the acquisition of invasiveness and chemoresistance. Several clinical studies indicate that E2F1 overexpression across high-grade tumours culminates in unfavourable prognosis and chemoresistance in patients. Thus, fine-tuning the expression of E2F1 could be a promising approach for treating patients showing chemoresistance. Methods: We integrated bioinformatics, structural and kinetic modelling, and experiments to study cooperative regulation of E2F1 by microRNA (miRNA) pairs in the context of anticancer chemotherapy resistance. Results: We showed that an enhanced E2F1 repression efficiency can be achieved in chemoresistant tumour cells through two cooperating miRNAs. Sequence and structural information were used to identify potential miRNA pairs that can form tertiary structures with E2F1 mRNA. We then employed molecular dynamics simulations to show that among the identified triplexes, miR-205-5p and miR-342-3p can form the most stable triplex with E2F1 mRNA. A mathematical model simulating the E2F1 regulation by the cooperative miRNAs predicted enhanced E2F1 repression, a feature that was verified by in vitro experiments. Finally, we integrated this cooperative miRNA regulation into a more comprehensive network to account for E2F1-related chemoresistance in tumour cells. The network model simulations and experimental data indicate the ability of enhanced expression of both miR-205-5p and miR-342-3p to decrease tumour chemoresistance by cooperatively repressing E2F1. Conclusions: Our results suggest that pairs of cooperating miRNAs could be used as potential RNA therapeutics to reduce E2F1-related chemoresistance