DisCanVis: Visualizing integrated structural and functional annotations to better understand the effect of cancer mutations located within disordered proteins

Intrinsically disordered proteins (IDPs) play important roles in a wide range of biological processes and have been associated with various diseases, including cancer. In the last few years, cancer genome projects have systematically collected genetic variations underlying multiple cancer types. In parallel, the number and different types of disordered proteins characterized by experimental methods have also significantly increased. Nevertheless, the role of IDPs in various types of cancer is still not well understood. In this work, we present DisCanVis, a novel visualization tool for cancer mutations with a special focus on IDPs. In order to aid the interpretation of observed mutations, genome level information is combined with information about the structural and functional properties of proteins. The web server enables users to inspect individual proteins, collect examples with existing annotations of protein disorder and associated function or to discover currently uncharacterized examples with likely disease relevance. Through a REST API interface and precompiled tables the analysis can be extended to a group of proteins

Az emlőrák szisztémás kezelése: szakmai útmutatás

The article presents the practice guideline of systemic treatment of breast cancer and recommendations of the 3rd Hungarian Breast Cancer Consensus Conference. It reflects the recent international guidelines (ESMO, NCCN, ABC2, St Gallen's) irrespectively of the current financial opportunities. Here we follow the early - locally advanced - locally relapsed - metastatic breast cancer line for didactic considerations and we discuss the different subgroups of breast cancer based on hormone receptor and HER2 receptor status. Diagnosis and treatment options of rare clinical entities are summarised at the end of the paper

The interaction between LC8 and LCA5 reveals a novel oligomerization function of LC8 in the ciliary-centrosome system

Dynein light chain LC8 is a small dimeric hub protein that recognizes its partners through short linear motifs and is commonly assumed to drive their dimerization. It has more than 100 known binding partners involved in a wide range of cellular processes. Recent large-scale interaction studies suggested that LC8 could also play a role in the ciliary/centrosome system. However, the cellular function of LC8 in this system remains elusive. In this work, we characterized the interaction of LC8 with the centrosomal protein lebercilin (LCA5), which is associated with a specific form of ciliopathy. We showed that LCA5 binds LC8 through two linear motifs. In contrast to the commonly accepted model, LCA5 forms dimers through extensive coiled coil formation in a LC8-independent manner. However, LC8 enhances the oligomerization ability of LCA5 that requires a finely balanced interplay of coiled coil segments and both binding motifs. Based on our results, we propose that LC8 acts as an oligomerization engine that is responsible for the higher order oligomer formation of LCA5. As LCA5 shares several common features with other centrosomal proteins, the presented LC8 driven oligomerization could be widespread among centrosomal proteins, highlighting an important novel cellular function of LC8

DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation

The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure.Fil: Quaglia, Federica. Università di Padova; Italia. Consiglio Nazionale delle Ricerche; ItaliaFil: Mészáros, Bálint. European Molecular Biology Laboratory; AlemaniaFil: Salladini, Edoardo. Università di Padova; ItaliaFil: Hatos, András. Università di Padova; ItaliaFil: Pancsa, Rita. Research Centre for Natural Sciences; HungríaFil: Chemes, Lucia Beatriz. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Pajkos, Mátyás. Eötvös Loránd University; HungríaFil: Lazar, Tamas. Vlaams Instituut voor Biotechnology; Hungría. Vrije Unviversiteit Brussel; BélgicaFil: Peña Díaz, Samuel. Universitat Autònoma de Barcelona; EspañaFil: Santos, Jaime. Universitat Autònoma de Barcelona; EspañaFil: Ács, Veronika. Research Centre for Natural Sciences; HungríaFil: Farahi, Nazanin. Vlaams Instituut voor Biotechnology; Bélgica. Vrije Unviversiteit Brussel; BélgicaFil: Fichó, Erzsébet. Research Centre for Natural Sciences; HungríaFil: Aspromonte, Maria Cristina. Università di Padova; Italia. Città della Speranza Pediatric Research Institute; ItaliaFil: Bassot, Claudio. Stockholms Universitet; SueciaFil: Chasapi, Anastasia. Centre for Research & Technology Hellas; GreciaFil: Davey, Norman E.. Chester Beatty Laboratories; Reino UnidoFil: Davidović, Radoslav. University of Belgrade; SerbiaFil: Laszlo Holland, Alicia Verónica. European Molecular Biology Laboratory; Alemania. Research Centre for Natural Sciences; HungríaFil: Elofsson, Arne. Stockholms Universitet; SueciaFil: Erdős, Gábor. Eötvös Loránd University; HungríaFil: Gaudet, Pascale. Swiss Institute of Bioinformatics; SuizaFil: Giglio, Michelle. University of Maryland School of Medicine; Estados UnidosFil: Glavina, Juliana. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Iserte, Javier Alonso. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Iglesias, Valentín. Universitat Autònoma de Barcelona; EspañaFil: Kálmán, Zsófia. Pázmány Péter Catholic University; HungríaFil: Lambrughi, Matteo. Danish Cancer Society Research Center; DinamarcaFil: Leonardi, Emanuela. Università di Padova; Italia. Pediatric Research Institute Città della Speranza; ItaliaFil: Rodriguez Sawicki, Luciana. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Critical assessment of protein intrinsic disorder prediction

Abstract: Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude

Az emlőrák szisztémás kezelése: szakmai útmutatás

The article presents the practice guideline of systemic treatment of breast cancer and recommendations of the 3rd Hungarian Breast Cancer Consensus Conference. It reflects the recent international guidelines (ESMO, NCCN, ABC2, St Gallen's) irrespectively of the current financial opportunities. Here we follow the early - locally advanced - locally relapsed - metastatic breast cancer line for didactic considerations and we discuss the different subgroups of breast cancer based on hormone receptor and HER2 receptor status. Diagnosis and treatment options of rare clinical entities are summarised at the end of the paper