Estimating sample-specific regulatory networks

Biological systems are driven by intricate interactions among the complex array of molecules that comprise the cell. Many methods have been developed to reconstruct network models of those interactions. These methods often draw on large numbers of samples with measured gene expression profiles to infer connections between genes (or gene products). The result is an aggregate network model representing a single estimate for the likelihood of each interaction, or "edge," in the network. While informative, aggregate models fail to capture the heterogeneity that is represented in any population. Here we propose a method to reverse engineer sample-specific networks from aggregate network models. We demonstrate the accuracy and applicability of our approach in several data sets, including simulated data, microarray expression data from synchronized yeast cells, and RNA-seq data collected from human lymphoblastoid cell lines. We show that these sample-specific networks can be used to study changes in network topology across time and to characterize shifts in gene regulation that may not be apparent in expression data. We believe the ability to generate sample-specific networks will greatly facilitate the application of network methods to the increasingly large, complex, and heterogeneous multi-omic data sets that are currently being generated, and ultimately support the emerging field of precision network medicine

Niederländischer Umweltplan: Die Erfolge staatlicher Förderung

Die Niederlande streben mit ihrem Umwelt-Unternehmens-Plan konkrete Umweltziele an. Dazu gehören auch Veränderungen, die in enger Zusammenarbeit mit der Industrie durchgeführt werden müssen. Die bisherigen Ergebnisse zeigen, daß eine Stärkung des Umweltmanagements in den Unternehmen durch eine sinnvolle Zusammenarbeit mit den Behörden ergänzt werden muß

A systems biology approach to study high-grade osteosarcoma

High-grade osteosarcoma is a primary bone tumor with complex genetic alterations, for which targeted therapy is lacking. The aim of this thesis was to use high-throughput molecular data analysis of high-grade osteosarcoma specimens and model systems, in order to learn more on osteosarcomagenesis and to find possible ways to inhibit this process. By analyzing different microarray data types using a systems biology approach, genomic instability was identified as an important driver of osteosarcomagenesis. A protective role of macrophages against metastasis of osteosarcoma was detected. In addition, the IR/IGF1R and PI3K/Akt signaling pathways were discovered as potential targets for treatment. This thesis provides the first steps in unraveling the genomic and transcriptomic landscape of high-grade osteosarcoma, and provides a biological rationale for certain new options for adjuvant treatment of this highly genomica lly unstable tumor.Nederlandse Kankerbestrijding KWFUBL - phd migration 201

Kinome and mRNA expression profiling of high-grade osteosarcoma cell lines implies Akt signaling as possible target for therapy

Background: High-grade osteosarcoma is a primary malignant bone tumor mostly occurring in adolescents and young adults, with a second peak at middle age. Overall survival is approximately 60%, and has not significantly increased since the introduction of neoadjuvant chemotherapy in the 1970s. The genomic profile of high-grade osteosarcoma is complex and heterogeneous. Integration of different types of genome-wide data may be advantageous in extracting relevant information from the large number of aberrations detected in this tumor. Methods: We analyzed genome-wide gene expression data of osteosarcoma cell lines and integrated these data with a kinome screen. Data were analyzed in statistical language R, using LIMMA for detection of differential expression/phosphorylation. We subsequently used Ingenuity Pathways Analysis to determine deregulated pathways in both data types. Results: Gene set enrichment indicated that pathways important in genomic stability are highly deregulated in these tumors, with many genes showing upregulation, which could be used as a prognostic marker, and with kinases phosphorylating peptides in these pathways. Akt and AMPK signaling were identified as active and inactive, respectively. As these pathways have an opposite role on mTORC1 signaling, we set out to inhibit Akt kinases with the allosteric Akt inhibitor MK-2206. This resulted in inhibition of proliferation of osteosarcoma cell lines U-2 OS and HOS, but not of 143B, which harbors a KRAS oncogenic transformation. Conclusions: We identified both overexpression and hyperphosphorylation in pathways playing a role in genomic stability. Kinome profiling identified active Akt signaling, which could inhibit proliferation in 2/3 osteosarcoma cell lines. Inhibition of PI3K/Akt/mTORC1 signaling may be effective in osteosarcoma, but further studies are required to determine whether this pathway is active in a substantial subgroup of this heterogeneous tumor

Macrophages inhibit human osteosarcoma cell growth after activation with the bacterial cell wall derivative liposomal muramyl tripeptide in combination with interferon-γ

Drug Delivery Technolog

Mesenchymal stromal cells of osteosarcoma patients do not show evidence of neoplastic changes during long-term culture

Background: In vitro expanded mesenchymal stromal cells (MSCs) are increasingly used as experimental cellular therapy. However, there have been concerns regarding the safety of their use, particularly with regard to possible oncogenic transformation. MSCs are the hypothesized precursor cells of high-grade osteosarcoma, a tumor with often complex karyotypes occurring mainly in adolescents and young adults.Methods: To determine if MSCs from osteosarcoma patients could be predisposed to malignant transformation we cultured MSCs of nine osteosarcoma patients and five healthy donors for an average of 649 days (range 601679 days). Also, we compared MSCs derived from osteosarcoma patients at diagnosis and from healthy donors using genome wide gene expression profiling.Results: Upon increasing passage, increasing frequencies of binucleate cells were detected, but no increase in proliferation suggestive of malignant transformation occurred in MSCs from either patients or donors. Hematopoietic cell specific Lyn substrate 1 (HLCS1) was differentially expressed (fold change 0.25, P value 0.0005) between MSCs of osteosarcoma patients (n = 14) and healthy donors (n = 9).Conclusions: This study shows that although HCLS1 expression was downregulated in MSCs of osteosarcoma patients and binucleate cells were present in both patient and donor derived MSCs, there was no evidence of neoplastic changes to occur during long-term culture

Sustained proliferation in cancer: mechanisms and novel therapeutic targets

Proliferation is an important part of cancer development and progression. This is manifest by altered expression and/or activity of cell cycle related proteins. Constitutive activation of many signal transduction pathways also stimulates cell growth. Early steps in tumor development are associated with a fibrogenic response and the development of a hypoxic environment which favors the survival and proliferation of cancer stem cells. Part of the survival strategy of cancer stem cells may manifested by alterations in cell metabolism. Once tumors appear, growth and metastasis may be supported by overproduction of appropriate hormones (in hormonally dependent cancers), by promoting angiogenesis, by undergoing epithelial to mesenchymal transition, by triggering autophagy, and by taking cues from surrounding stromal cells. A number of natural compounds (e.g., curcumin, resveratrol, indole-3-carbinol, brassinin, sulforaphane, epigallocatechin-3-gallate, genistein, ellagitannins, lycopene and quercetin) have been found to inhibit one or more pathways that contribute to proliferation (e.g., hypoxia inducible factor 1, nuclear factor kappa B, phosphoinositide 3 kinase/Akt, insulin-like growth factor receptor 1, Wnt, cell cycle associated proteins, as well as androgen and estrogen receptor signaling). These data, in combination with bioinformatics analyses, will be very important for identifying signaling pathways and molecular targets that may provide early diagnostic markers and/or critical targets for the development of new drugs or drug combinations that block tumor formation and progression

Ergänzungen zur iberischen Pseudoscorpioniden-Fauna

Die systematischen Aufsammlungen, die Prof. Dr. H. Franz in den letzten Jahren in weiten Teilen der iberischen Halbinsel durchführte, schliessen weitgehend die Lücken, die bisher noch zwischen den explorierten Gebieten klafften. Sie ergänzen und berichtigen daher unsere bisherigen, von mir letztmals 1955 (Eos, XXXI, pp. 87-122) zusammengefassten Kenntnisse in taxonomischer und faunistischer Hinsicht und runden das Faunenbild auch tiergeographisch zu erfreulicher Vollständigkeit ab. Die Ausbeuten enthielten wiederum 8 neue Arten beziehungsweise Unterarten. Drei weitere Arten waren für Spanien neu. In den cantabrischen Gebirgen tritt nunmehr die Gattung Microcreagris als charakteristisches Faunenelement noch stärker hervor.— Im folgenden werden die seither gemachten Funde angeführt.Peer reviewe

Reference-based comparison of adaptive immune receptor repertoires

B- and T-cell receptor (immune) repertoires can represent an individual’s immune history. While current repertoire analysis methods aim to discriminate between health and disease states, they are typically based on only a limited number of parameters (e.g., clonal diversity, germline usage). Here, we introduce immuneREF: a quantitative multi-dimensional measure of adaptive immune repertoire (and transcriptome) similarity that allows interpretation of immune repertoire variation by relying on both repertoire features and cross-referencing of simulated and experimental datasets. immuneREF is implemented in an R package and was validated based on detection sensitivity of immune repertoires with known similarities and dissimilarities. To quantify immune repertoire similarity landscapes across health and disease, we applied immuneREF to >2400 datasets from individuals with varying immune states (healthy, [autoimmune] disease and infection [Covid-19], immune cell population). Importantly we discovered, in contrast to the current paradigm, that blood-derived immune repertoires of healthy and diseased individuals are highly similar for certain immune states, suggesting that repertoire changes to immune perturbations are less pronounced than previously thought. In conclusion, immuneREF implements population-wide analysis of immune repertoire similarity and thus enables the study of the adaptive immune response across health and disease states.Support was provided from The Helmsley Charitable Trust (#2019PG-T1D011, to VG), UiO WorldLeading Research Community (to VG), UiO:LifeSciences Convergence Environment Immunolingo (to VG and GKS), EU Horizon 2020 iReceptorplus (#825821) (to VG), a Research Council of Norway FRIPRO project (#300740, to VG), a Research Council of Norway IKTPLUSS project (#311341, to VG and GKS), a Norwegian Cancer Society grant (#215817, to VG), and Stiftelsen Kristian Gerhard Jebsen (K.G. Jebsen Coeliac Disease Research Centre) (to GKS), Swiss National Science Foundation (Project 31003A to S.T.R), the Norwegian Research Council, Helse Sør-Øst, and the University of Oslo through the Centre for Molecular Medicine Norway (#187615 to MLK).N

Rescuing historical weather observations improves quantification of severe windstorm risks

Billions of historical climatological observations remain unavailable to science as they exist only on paper, stored in numerous archives around the world. The conversion of these data from paper to digital could transform our understanding of historical climate variations, including extreme weather events. Here we demonstrate how the rescue of such paper observations has improved our understanding of a severe windstorm that occurred in February 1903 and its significant impacts. By assimilating newly rescued atmospheric pressure observations, the storm is now credibly represented in an improved reanalysis of the event. In some locations this storm produced stronger winds than any event during the modern period (1950–2015) and it is in the top-4 storms for strongest winds anywhere over land in England and Wales. As a result, estimates of risk from severe storms, based on modern period data, may need to be revised. Examining the atmospheric structure of the storm suggests that it is a classic Shapiro–Keyser-type cyclone with “sting-jet” precursors and associated extreme winds at locations and times of known significant damage. Comparison with both independent observations and qualitative information, such as photographs and written accounts, provides additional evidence of the credibility of the atmospheric reconstruction, including sub-daily rainfall variations. Simulations of the storm surge resulting from this storm show a large coastal surge of around 2.5 m, comparing favourably with newly rescued tide gauge observations and adding to our confidence in the reconstruction. Combining historical rescued weather observations with modern reanalysis techniques has allowed us to plausibly reconstruct a severe windstorm and associated storm surge from more than 100 years ago, establishing an invaluable end-to-end tool to improve assessments of risks from extreme weather.</p