128 research outputs found
Network analyses in systems biology: new strategies for dealing with biological complexity
The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from the investigation of organizational properties of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological complexity
Identification of critical paralog groups with indispensable roles in the regulation of signaling flow
Extensive cross-talk between signaling pathways is required to integrate the myriad of extracellular signal combinations at the cellular level. Gene duplication events may lead to the emergence of novel functions, leaving groups of similar genes - termed paralogs - in the genome. To distinguish critical paralog groups (CPGs) from other paralogs in human signaling networks, we developed a signaling network-based method using cross-talk annotation and tissue-specific signaling flow analysis. 75 CPGs were found with higher degree, betweenness centrality, closeness, and ‘bowtieness’ when compared to other paralogs or other proteins in the signaling network. CPGs had higher diversity in all these measures, with more varied biological functions and more specific post-transcriptional regulation than non-critical paralog groups (non-CPG). Using TGF-beta, Notch and MAPK pathways as examples, SMAD2/3, NOTCH1/2/3 and MEK3/6-p38 CPGs were found to regulate the signaling flow of their respective pathways. Additionally, CPGs showed a higher mutation rate in both inherited diseases and cancer, and were enriched in drug targets. In conclusion, the results revealed two distinct types of paralog groups in the signaling network: CPGs and non-CPGs. Thus highlighting the importance of CPGs as compared to non-CPGs in drug discovery and disease pathogenesis
EGF functionalized polymer-coated gold nanoparticles promote EGF photostability and EGFR internalization for photothermal therapy
The application of functionalized nanocarriers on photothermal therapy for cancer ablation has wide interest. The success of this application depends on the therapeutic efficiency and biocompatibility of the system, but also on the stability and biorecognition of the conjugated protein. This study aims at investigating the hypothesis that EGF functionalized polymer -coated gold nanoparticles promote EGF photostability and EGFR internalization, making these conjugated particles suitable for photothermal therapy. The conjugated gold nanoparticles (100-200 nm) showed a plasmon absorption band located within the near infrared range (650-900 nm), optimal for photothermal therapy applications. The effects of temperature, of polymer-coated gold nanoparticles and of UVB light (295nm) on the fluorescence properties of EGF have been investigated with steady-state and time-resolved fluorescence spectroscopy. The fluorescence properties of EGF, including the formation of Trp and Tyr photoproducts, is modulated by temperature and by the intensity of the excitation light. The presence of polymeric-coated gold nanoparticles reduced or even avoided the formation of Trp and Tyr photoproducts when EGF is exposed to UVB light, protecting this way the structure and function of EGF. Cytotoxicity studies of conjugated nanoparticles carried out in normal-like human keratinocytes showed small, concentration dependent decreases in cell viability (0-25%). Moreover, conjugated nanoparticles could activate and induce the internalization of overexpressed Epidermal Growth Factor Receptor in human lung carcinoma cells. In conclusion, the gold nanoparticles conjugated with Epidermal Growth Factor and coated with biopolymers developed in this work, show a potential application for near infrared photothermal therapy, which may efficiently destroy solid tumours, reducing the damage of the healthy tissue.Support was provided by: Fundacao para a Ciencia e Tecnologia (FCT) for the financial support under the project reference PTDC/BBB-BMC/0611/2012 [https://www.fct.pt/apoios/projectos)]. The work at CBMA was supported by the strategic programme UID/BIA/04050/2013 (POCI-01-0145-FEDER-007569) funded by national funds through the FCT I.P. and by the ERDF through the COMPETE2020 - Programa Operacional Competitividade e Internacionalizacao (POCI) [https://www.fct.pt/apoios/projectos]; European Commission through the project H2020-644242-SAPHELY (https://saphely.eu/project.php) and the project H2020-634013-2-PHOCNOSIS [http://cordis.europa.eu/project/rcn/193268_en.html].The authors would like to thank Fundacao para a Ciencia e Tecnologia (FCT) for the financial support under the project reference PTDC/BBB-BMC/0611/2012. The work at CBMA was supported by the strategic programme UID/BIA/04050/2013 (POCI-01-0145-FEDER-007569) funded by national funds through the FCT I.P. and by the ERDF through the COMPETE2020 - Programa Operacional Competitividade e Internacionalizacao (POCI). The authors acknowledge the funding from the European Commission through the project H2020-644242-SAPHELY and the project H2020-634013-2-PHOCNOSIS. Finally, the authors would also like to thank the master student Joao Lopes from Universidade Lusofona (Portugal) for the help with in vitro cytotoxic assays. Isabel Correia acknowledges FCT for Investigator FCT contract.info:eu-repo/semantics/publishedVersio
Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies
Even targeted chemotherapies against solid cancers show a moderate success increasing the need to novel targeting strategies. To address this problem, we designed a systems-level approach investigating the neighbourhood of mutated or differentially expressed cancer-related proteins in four major solid cancers (colon, breast, liver and lung). Using signalling and protein–protein interaction network resources integrated with mutational and expression datasets, we analysed the properties of the direct and indirect interactors (first and second neighbours) of cancer-related proteins, not found previously related to the given cancer type. We found that first neighbours have at least as high degree, betweenness centrality and clustering coefficient as cancer-related proteins themselves, indicating a previously unknown central network position. We identified a complementary strategy for mutated and differentially expressed proteins, where the affect of differentially expressed proteins having smaller network centrality is compensated with high centrality first neighbours. These first neighbours can be considered as key, so far hidden, components in cancer rewiring, with similar importance as mutated proteins. These observations strikingly suggest targeting first neighbours as a novel strategy for disrupting cancer-specific networks. Remarkably, our survey revealed 223 marketed drugs already targeting first neighbour proteins but applied mostly outside oncology, providing a potential list for drug repurposing against solid cancers. For the very central first neighbours, whose direct targeting would cause several side effects, we suggest a cancer-mimicking strategy by targeting their interactors (second neighbours of cancer-related proteins, having a central protein affecting position, similarly to the cancer-related proteins). Hence, we propose to include first neighbours to network medicine based approaches for (but not limited to) anticancer therapies
Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome
Prioritizing biological pathways by recognizing context in time-series gene expression data
Knowledge-fused differential dependency network models for detecting significant rewiring in biological networks
Comparison Between Folic Acid and gH625 Peptide-Based Functionalization of Fe3O4 Magnetic Nanoparticles for Enhanced Cell Internalization
Denoising perturbation signatures reveal an actionable AKT-signaling gene module underlying a poor clinical outcome in endocrine-treated ER+ breast cancer
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