en News - BIOINFORMATICS BARCELONA News Mon, 17 Jun 2019 10:23:05 +0000 Mon, 17 Jun 2019 10:23:05 +0000 Houdini 2 (http://houdini.antaviana.cat/) http://www.bioinformaticsbarcelona.eu/news A webserver to study the protein networks perturbed in diseases

Researchers from the UPF, IMIM and UVIC have developed the website GUILDify to study the molecular environment of the proteins involved in diseases. The website is a promising tool to study the molecular mechanisms underlying a disease, to understand the relationships between two diseases and to propose potential drugs for their treatment.

The website GUILDify has been developed at the Structural Bioinformatics Group of GRIB (IMIM-UPF) led by Prof. Baldo Oliva with the objective to study the protein interactions involved in a disease. When accessing the website, the user finds an input box to introduce any disease name and the species of the interactome (human, mouse, rat...). After introducing the disease, GUILDify provides the user with a list of proteins whose corresponding genes are likely to be mutated when the disease occurs. The gene mutations are obtained from DisGeNET, a database of genes associated to human diseases. GUILDify uses these proteins as seeds for an algorithm that searches for the proteins in the interactome that are more connected to them. In the end, the user obtains the protein interactions that are more likely to cause the disease and a list of the biological functions affected.

Quim Aguirre, PhD student at the Structural Bioinformatics Group (SBI) of GRIB, behind this project, tells us all about it in an article on the El·lipse website.

 

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Mon, 17 Jun 2019 10:23:05 +0000 http://www.bioinformaticsbarcelona.eu/news//news/139/a-webserver-to-study-the-protein-networks-perturbed-in-diseases http://www.bioinformaticsbarcelona.eu/news/139 0
Computational method increases design efficiency of protein-based drugs

Researchers from the Institute of Biotechnology and Biomedicine (IBB), in collaboration with scientists from the University of Warsaw recently presented an important update to their AGGRESCAN 3D computational method, focused on facilitating and reducing the cost of developing new generation protein-based drugs, diminishing their propensity to form aggregates and keeping them stable and active for a longer period of time.

Protein aggregation is a common phenomenon found in a wide range of pathologies, from Parkinson's and Alzheimer's diseases to some cancers and type 2 diabetes. A growing molecular knowledge of this phenomenon has yielded the development of different algorithms capable of identifying and predicting the regions with a greater tendency to aggregate. Among the first was AGGRESCAN, developed by the same researchers of the IBB, which took into account the propensity of the linear sequence, but not the 3D structure acquired by globular proteins. Four years ago, this same team of researchers expressed the idea of conducting predictions on these protein structures by implementing the AGGRESCAN 3D (A3D) server. This server offered a higher precision than those based on linear sequencing to predict the aggregation properties of globular proteins. It also provided new features, such as the possibility of easily modelling pathogenic mutations, or a dynamic mode, which allowed modelling the flexibility of small proteins to find potentially hidden regions.

The latest update was presented as a web server freely accessible to the academic world, in addition to a desktop version compatible with Windows, MacOS and Linux. The new algorithm surpasses all previous limitations and substantially broadens computational costs to allow modelling the flexibility of molecules of biomedical interest. It also includes different tools such as an automatic generation of mutations to facilitate redesigns of proteins as antibodies to make them stable and at the same time more soluble, and an improved user interface with which to view the data directly on the website.

"With this update, the A3D becomes one of the most complete aggregation predictors. The fact that one same place offers you the chance to make protein aggregation predictions, model their flexibility, study options for a smart redesign and verify how different factors can affect them, represents a giant step forward with regard to other similar servers", affirms Salvador Ventura, researcher at the IBB and the Department of Biochemistry and Molecular Biology, as well as creator of the A3D. "Among other things, all of this will allow us to improve the production of protein-based drugs, reducing the costs of development, production, storage and distribution".

Protein aggregation, a key element in biomedicine and biotechnology

Protein aggregation has gone from being an ignored area of protein chemistry to becoming a key element within the biomedicine and biotechnology fields. "A bad protein folding and subsequent aggregation is behind a growing number of human disorders and one of the most important impediments to designing and manufacturing proteins for therapeutic applications. These therapies, which imply the use of monoclonal antibodies, growth factors and enzyme substitutions, have already demonstrated high precision of molecular targeting, and therefore the need to study them more in depth becomes even more transcendent", Salvador Ventura concludes.

 

Articles: 
Aleksander Kuriata, Valentín Iglesias, Jordi Pujols, Mateusz Kurcinski, Sebastian Kmiecik and Salvador Ventura. Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility  Nucleic Acids Research, gkz321, doi.org/10.1093/nar/gkz321
https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkz321/5485072 

Aleksander Kuriata, Valentín Iglesias, Salvador Ventura and Sebastian Kmiecik. Aggrescan3D standalone package for structure-based prediction of protein aggregation propertiesBioinformatics. 2019 pii: btz143. doi: 10.1093/bioinformatics/btz143.
https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btz143/5368526?redirectedFrom=fulltext

To learn more about how AGGRESCAN3D works please visit the following website: http://biocomp.chem.uw.edu.pl/A3D2/

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Tue, 28 May 2019 07:43:23 +0000 http://www.bioinformaticsbarcelona.eu/news//news/137/computational-method-increases-design-efficiency-of-protein-based-drugs http://www.bioinformaticsbarcelona.eu/news/137 0
First stable simulations of DNA crystals

A research team has presented the first stable simulations of DNA crystals, according to a study published in the journal Chem -part of the publisher Cell- and led by Modesto Orozco, Professor from the Department of Biochemistry and Molecular Biomedicine of the Faculty of Biology of the UB, and head of a research group of the Institute for Research in Biomedicine (IRB Barcelona) and the platform Bioinformatics Barcelona (BIB).

The new study shows the most detailed description so far about the properties of crystal systems with DNA at an atomic scale. This scientific milestone enables explaining the importance of chemical additives which are experimentally used to reach suitable crystallization conditions to get stable crystals in the laboratories.

According to Pablo D. Dans, postdoctoral researcher at IRB Barcelona, "the first to benefit from the study is the community of computational physicists and the chemists and biophysicists, who now have a clear protocol and reference to get stable simulations of DNA crystals".

According to Professor Modesto Orozco, head of the Molecular Modelling and Bioinformatics laboratory of IRB Barcelona, "in the long run, the simulation of several crystals obtained in under different experimental conditions should allow us to predict the effect of a certain chemical additive, and guide crystallographers in their experiments, reducing the costs and the time to get the crystals". 
 


Further information
 

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Thu, 30 May 2019 09:01:19 +0000 http://www.bioinformaticsbarcelona.eu/news//news/135/first-stable-simulations-of-dna-crystals http://www.bioinformaticsbarcelona.eu/news/135 0
Researchers discover the action mechanism of an antitumor drug to treat glioblastoma Glioblastoma is a type of brain tumor with no cure, usually associated with mutations in the epidermal growth factor receptor (EGFR). The main EGFR mutation found in this tumor -known as EGFRvlll- is treated with the antibody mAb806, a drug developed by the Ludwig Institute for Cancer Research (United States) about twenty years ago, although its action mechanism was unknown. Now, a new study published in the journal Proceedings of the National Academy of Science (PNAS) reveals for the first time -the action mechanism of this antibody on the mutated EGFR receptor.

 

The results of the study, which open new pathways for the treatment of cancer, suggest the antibody mAb806 could be used in many tumours in which EGFR has mutated and not only in a specific mutation -like researchers believed so far. The study counts on the participation of experts from the University of Barcelona, the Institute for Research in Biomedicine (IRB Barcelona), Stockholm University (Sweden), and the University of California (United States), among other institutions.


Moreover, the scientific team proved that, even if EGFR has not mutated yet, it can be treated to make it sensitive to the protocol with the antibody mAb806. "These findings provide the rational basis to conduct anti-EGFR therapies combined with antibodies and kinase inhibitors, instead of blind testing them, as it has happened so far", notes Modesto Orozco, professor at the Department of Biochemistry and Molecular Biology at the Faculty of Chemistry of the UB, head of the Molecular Modelling and Bioinformatics Lab at IRB Barcelona and member of the Bioinformatics Barcelona platform (BIB).

 

Further information

 

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Thu, 23 May 2019 09:19:11 +0000 http://www.bioinformaticsbarcelona.eu/news//news/133/researchers-discover-the-action-mechanism-of-an-antitumor-drug-to-treat-glioblastoma http://www.bioinformaticsbarcelona.eu/news/133 0
Ready, set, go for crossing the barrier!

Genes contain all the information needed for the functioning of cells, tissues, and organs in our body. Gene expression, meaning when and how are the genes being read and executed, is thoroughly regulated like an assembly line with several things happening one after another.

Researchers at the Centre for Genomic Regulation (CRG) in collaboration with the Structural Bioinformatics group of GRIB (IMIM-UPF) led by Baldo Oliva and the Department of Molecular Epigenetics, Helmholtz Center Munich, Germany, have discovered a new step in this line, which controls the expression of some genes with an important role in cancer. "We observed that breast cancer cells need a particular modification to express a set of genes required for cellular proliferation and tumour progression," explains the CRG - Beatriu de Pinós postdoctoral researcher Priyanka Sharma, first author of the paper. "This modification allows the enzyme RNA polymerase II to overcome a pausing barrier and to continue to transcribe these genes," adds Sharma.

Cancer cells are willing to quickly proliferate so, genes involved in cell division and proliferation are really active and usually highly expressed. Such a precise and meticulous machinery involves many different molecules to properly function. In this case, when all the machinery to express proliferation genes is ready, it still has to wait for a particular modification to go. As in race when runners are asked to be ready, set and go. Here, the polymerase is also ready and set but still needs a final modification to cross the barrier for transcription and go.

Deciphering every single step and all actors involved in this process is an important achievement in terms of fundamental science. We are now able to better understand how an intricate mechanism of gene regulation actually works and this might be a new target for clinical researchers to study novel therapies for certain types of cancer," states Miguel Beato, CRG group leader and principal investigator in this work.

The work, which has been published in Molecular Cell, describes a novel modification of in the Carboxyl terminal domain of RNA Polymerase II, namely the de-imination of an arginine, by the enzyme PADI2, which allows the polymerase to transcribe genes relevant for cancer cell growth. "Most chemo-therapies are oriented at blocking the activity of enzymes, but we know that PADI2 participates in many different processes involving the nervous system, immune response and inflammation, among others. Thus, inhibiting PADI2 would have multiple side effects. Our results make it possible to target just the particular action of PADI2 on RNA polymerase needed for tumour progression without globally blocking the enzyme," explains Beato.

Reference article: Priyanka Sharma et al. "Arginine citrullination at the c-terminal domain controls RNA polymerase II transcription" Molecular Cell (2018) DOI: 10.1016/j.molcel.2018.10.01.

For further information and media requests, please, contact: Laia Cendrós, press officer, Centre for Genomic Regulation (CRG) - Tel. +34 93 316 0237. For press releases in spanish and catalan click here.

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Mon, 28 Jan 2019 13:00:20 +0000 http://www.bioinformaticsbarcelona.eu/news//news/125/ready-set-go-for-crossing-the-barrier http://www.bioinformaticsbarcelona.eu/news/125 0
First year of the european project eTRANSAFE: read the keynote from Prof. Ferran Sanz, Project Coordinator

The eTRANSAFE (Enhancing TRANslational SAFEty Assessment through Integrative Knowledge Management) project aims at enhancing the efficiency of translational safety assessment during the drug discovery and development process by means of the development of an integrative data infrastructure and innovative computational methods and tools. This infrastructure will be underpinned by legacy data sharing, the use of data standards, such as the SEND format for preclinical studies, and the implementation of a modular computational architecture.

eTRANSAFE started its journey in September 2017 and during the first year, we have set the foundations for the development of widely accepted guidelines on safe legacy data sharing, and we have been working in the extension of the preclinical database released in the previous IMI eTOX project, in terms of incorporation of individual animal data in SEND format together with structural and pharmacological information. In addition, identification of useful data available in the public domain, its integration with the data contributed from the EFPIA partners and the identification of potential challenges by means of prototypes and use cases have been the first steps to move forward the development of the eTRANSAFE Knowledge Hub.

In the past months, an internal group, which gathers representatives from all workpackages, has been intensively working on the development of a preliminary prototype solution that allows searching for compounds, annotation of those compounds with pre-clinical and clinical data and visualisation of that data. This has proven to be a useful exercise to provide the project a means to better explore how data will need to be integrated and accessed from the Final Knowledge Hub. This work will be further developed.

The Project is pleased of the progress achieved and will continue advancing towards the final objective of supporting and improving the drug discovery and development.

The eTRANSAFE consortium is a private and public partnership of 8 academic institutions, 6 SMEs and 12 pharmaceutical companies, and is coordinated by the Fundació Institut Mar d'Investigacions Mèdiques (IMIM) and led by the pharmaceutical company Novartis. Universitat Pompeu Fabra is partner of the Consortium. 

Click here to read more about the eTRANSAFE project.

Click here to subscribe to the eTRANSAFE Newsletter to be up to date on the progress of the Project activities.

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Mon, 28 Jan 2019 13:00:03 +0000 http://www.bioinformaticsbarcelona.eu/news//news/123/first-year-of-the-european-project-etransafe-read-the-keynote-from-prof-ferran-sanz-project-coordinator http://www.bioinformaticsbarcelona.eu/news/123 0
The depths of the ocean and gut flora unravel the mystery of microbial genes

Understanding the functions of genes in bacteria that form part of the human microbiome-the collection of microbes found inside our bodies-is important because these genes might explain mechanisms of bacterial infection or cohabitation in the host, antibiotic resistance, or the many effects-positive and negative-that the microbiome has on human health.

Surprisingly, the functions of a huge number of microbial genes are still unknown. This knowledge gap can be thought of as "genomic dark matter" in microbes, and neither computational biology nor current lab techniques have been able address this gap.

This challenge has now been tackled through an international collaboration between the Institute for Research in Biomedicine (IRB Barcelona) and two other interdisciplinary research centres, namely the IJS in Ljubljana (Slovenia) and RBI in Zagreb (Croatia). The findings have been published recently in Microbiome, the international journal of reference in microbiome research. The study was led by Fran Supek, computational biologist and leader of the Genome Data Science lab at IRB Barcelona, and first-authored by Vedrana Vidulin, a computer scientist affiliated to the centres in Slovenia and Croatia.

Intelligent prediction method

The researchers have developed a new computational method able to examine thousands of metagenomes simultaneously and identify the evolutionary signal that can predict the function of many microbial genes. This method, which analyses "big data" from human microbiomes (e.g. from the intestine or skin) and other metagenomes (e.g. from the soil or ocean) is based on a special kind of machine learning algorithm: it can create "decision trees" to predict hundreds of different functions at once, finding links between genes and at the same time predicting what they do in the microbial cell.

"This makes the algorithm very good at not getting confused by the noise in the metagenomic data, meaning that it is accurate and can confidently propose a biological role for a large number of genes with unknown functions. Intriguingly, it also proposes many additional functions for genes that already have some known role," says Supek.

The most important finding to emerge from this research is that the analysis of human microbiomes and other metagenomic data, such as those of the soil and ocean, allows researchers to assign hundreds of gene functions that have evaded current computational genomics approaches until now. "In other words, metagenomes allow scientists to see what ordinary genomes don't," explains the Croatian researcher, who was recently awarded a grant from the European Research Council (ERC).

Diversity is key

The scientists have found that different types of environments can predict different types of gene functions. For example, metagenomes from the ocean can be used to predict the genes used by bacteria for photosynthesis. But as the researchers point out, this could not have been discovered from the bacteria in the human gut. In contrast, the gut microbiome has been very useful for predicting key genes involved in the mechanisms underlying the development of disease and in the metabolism of alcohol and the biosynthesis of certain amino acids-predictions that would have been more difficult to make using microbiomes from the environment.

The authors conclude that, through machine learning, a large and diverse set of environments allows us to learn about many different gene functions in microbes. "Computational methods like this one are shedding light on the "dark matter" within microbial genomes ­­-- the enormous number of genes in bacteria and in archaea whose functions are a mystery," says Supek.

The thousands of computational predictions generated will need to be validated in experiments. Once validated, they may lead to the discovery of new genes that explain how bacteria shape the ecosystems around us and indeed the ecosystem within us-the human microbiome.

This study has been funded through the European FP7 'Future and Emerging Technologies' Programme and an ERC Starting Grant.

Reference article:

The evolutionary signal in metagenome phyletic profiles predicts many gene functions

Vedrana Vidulin, Tomislav Šmuc, Sašo Džeroski and Fran Supek

Microbiome (2018) 6:129 Doi: https://doi.org/10.1186/s40168-018-0506-4

 

VIDEO MEET OUR SCIENTISTS. Fran Supek: "Solving the riddle of DNA"

 

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Wed, 18 Jul 2018 08:26:59 +0000 http://www.bioinformaticsbarcelona.eu/news//news/121/the-depths-of-the-ocean-and-gut-flora-unravel-the-mystery-of-microbial-genes http://www.bioinformaticsbarcelona.eu/news/121 0
A new computational method for exploring the reuse of drugs

Researchers led by Emre Guney of the research programme on Biomedical Informatics (GRIB), a joint programme of Pompeu Fabra University (UPF) and the Hospital del Mar Medical Research Institute (IMIM), have developed a new computational method to reuse drugs that target biological pathways common to more than one disease.

Drug reuse, an efficient strategy

A significant percentage of marketed drugs are not effective in patients due to the complexity of the biological processes involved in diseases and genetic differences between people. Despite recent technological advances, the discovery of new effective treatments takes a long time and continues to be expensive. For this reason, the reuse of medicines, i.e., the use of existing drugs for other diseases, is a very interesting alternative to reduce the costs of drug development.

In order to explore this reuse, the researchers have developed a new computational method called Proximal pathway Enrichment Analysis (PxEA), which assesses whether the proteins on which the drug acts are involved only in one specific disease or share common pathways for different diseases.

"PxEA reveals that most drugs currently used for autoimmune disorders such as arthritis, psoriasis, ulcerative colitis and multiple sclerosis do not target specifically the proteins that cause the disease", says Emre Guney, a researcher with the GRIB's Integrated Biomedical Informatics group and the Structural Bioinformatics group led by  Laura I. Furlong and Baldo Oliva, respectively. "The targets of these drugs are often common immune response proteins and belong to the inflammation-related pathways that are involved in several autoimmune diseases", he continues.

Application of the method for comorbidity

Joaquim Aguirre-Plans, first author of the study, explains "we also show that PxEA can be applied to reuse drugs that can target shared mechanisms involved in comorbid diseases (occurring simultaneously in one patient)". 

Type 2 diabetes and Alzheimer's disease are highly prevalent in an increasingly ageing society. Due to the interplay of various biological processes shared between these two diseases, they are commonly observed in the same patient, and recent efforts aim to reuse antidiabetic agents to prevent insulin resistance in Alzheimer's disease.

"As far as we know, PxEA is the first systematic method that can identify drugs targeting common pathological processes involved in two diseases, such as type 2 diabetes and Alzheimer's disease", says Emre Guney.

The study also involved researchers of the Research Centre for Molecular Medicine of the Austrian Academy of Sciences and the University of Maastricht in the Netherlands.

Reference article:

Aguirre-Plans J, Piñero J, Menche J, Sanz F, Furlong LI, Schmidt HHHW, Oliva B, Guney E. Proximal Pathway Enrichment Analysis for Targeting Comorbid Diseases via Network Endopharmacology. Pharmaceuticals. June, 2018. DOI: https://doi.org/10.3390/ph11030061

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Thu, 12 Jul 2018 08:19:47 +0000 http://www.bioinformaticsbarcelona.eu/news//news/119/a-new-computational-method-for-exploring-the-reuse-of-drugs http://www.bioinformaticsbarcelona.eu/news/119 0
Inauguration of the interuniversity Doctoral Program in Bioinformatics

The inauguration of the interuniversity doctoral program took place in the auditorium of the Faculties of Sciences and Biosciences of the Universitat Autònoma de Barcelona (UAB) on June 20, 2018.

The new interuniversity doctoral program in Bioinformatics has been promoted by the Bioinformatics Barcelona Association (BIB), and involves six universities: UAB, UPC, UdG, UdL, UOC and UVic-UCC.

The opening speech was given by the Vice-Rector for Research and Transference of UAB, Armand Sánchez, the President of the BIB association, Ana Ripoll, and the coordinator of the program, Xavier Daura, and had the presence of institutional representatives of the participating universities: Victoria Nogués, Academic Secretary of the Doctoral School, UAB; Francesc Sepulcre, Director of the Doctoral School, UPC; Robert Martí, Delegate of the Rector for International Masters, UdG; Gemma Bellí, Academic Secretary of the Doctoral School, UdL; Agatha Lapedriza, Director of the Master in Bioinformatics, UOC-UB; Josep Prieto, Director of Computer Science, Multimedia and Telecomunications, UOC and Antoni Tort, Director of the Doctoral School, UVic-UCC.

The event included the conference "Personalized Medicine as a Bioinformatic Challenge", given by Alfonso Valencia, ICREA Research Professor, Director of Life Sciences at BSC-CNS and Head of the Spanish node of the European Infrastructure for Life-Science Information, ELIXIR. Alfonso Valencia reviewed the challenges faced by bioinformatics in the developing field of precision medicine and the current state of the research in this field, and presented the strategic positioning of the BSC-CNS in this area.

The Doctorate in Bioinformatics aims to train the outstanding researchers of tomorrow in a highly strategic field. The research lines included in the program are Omics and Molecular Bioinformatics, Biomolecular Modelling and Simulation, Systems and Synthetic Biology, Data Science in Bioinformatics, and Biostatistics and Mathematical Modelling in Bioinformatics.

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Wed, 27 Jun 2018 08:44:16 +0000 http://www.bioinformaticsbarcelona.eu/news//news/117/inauguration-of-the-interuniversity-doctoral-program-in-bioinformatics http://www.bioinformaticsbarcelona.eu/news/117 0
A new therapy proves effective against brain metastasis

A study published in Nature Medicine by a team led by researchers at the Spanish National Cancer Research Centre (CNIO), with the participation of Mind the Byte, shows that the administration of silibinin in patients with brain metastasis reduces lesions without causing any adverse effects. This preliminary trial provides proof of concept that this compound could be a new effective and safe alternative to treat brain metastasis.

"We have demonstrated, taking into account all the considerations relevant to a compassionate use trial such as ours, that we can successfully treat brain metastasis", highlights Valiente, from CNIO. "This treatment could also be valid for any type of brain metastasis, regardless of the primary tumour that generated it", he added.

One of the biggest challenges in oncology is brain metastasis. It is estimated that between 10% and 40% of primary tumours generate metastasis in the brain, a situation that worsens patient prognosis considerably. Few advances have been made in terms of treatment; currently, brain metastasis is still being treated with surgery and/or radiotherapy. In recent years, some alternatives have appeared in terms of targeted therapies or immunotherapy, but the percentage of patients who might benefit from these therapies is just 20% in the best-case scenario.

The tumour microenvironment as a critical factor in metastasis

The role of the cellular context (microenvironment) in which a tumour develops is becoming increasingly important, not only with a view to understanding how cancer cells grow but also so we can know how to attack them. In the brain, an inhospitable environment for any element that is foreign to it, the role of the microenvironment is as relevant as it is unknown.

Scientists have been studying this aspect for years, focusing in particular on two elements. On the one hand, on a population of cells known as astrocytes, which respond to damage by entering into a reactive state and which are associated with metastasis. And on the other, on the STAT3 gene, which has already been proved to be involved with brain metastasis. As shown in this research, the activation of STAT3 is significant in a subpopulation of reactive astrocytes that are key to establishing a pro-metastatic environment.

When this gene is eliminated from the reactive astrocytes, the viability of brain metastasis is compromised. With this information on the table, Valiente's research group used a novel drug screening strategy developed by them called METPlatform. This tool is capable of analysing the relationship between hundreds of compounds and the metastatic cells found in the target organ simultaneously; in this case in the brain.

"This strategy allows us to assess experimental drugs as well as those that are already in use for other types of pathologies that might or might not be linked to cancer. We believe that by using METPlatform we can be more efficient in developing new therapeutic options, since we can study the metastatic cell growing in the organ being colonised", explained Valiente.

One of the compounds tested in this preparation was silibinin, whose anti-tumour potential had previously been established by Joaquim Bosch, Head of the Lung Cancer Unit at Catalonia's Cancer Institute (ICO) in Girona, and co-author of this study. "In 2016, we reported positive brain responses in two patients with no other treatment options who received silibinin, but we did not know how it worked. Thanks to this research, led by Valiente's group, we now understand how it acts at the level of the brain", said Bosch.

A new therapeutic concept with encouraging results

Following the good results obtained by blocking STAT3 with silibinin in mice, the authors established a cohort of 18 patients with lung cancer and brain metastasis for whom compassionate use to this drug was granted in combination with standard treatment. 75% of the patients reacted positively at the level of brain metastasis. Three patients (20%) displayed a total response, and 10 (55%) a partial response. Average survival rate was 15.5 months, whereas in the control group (composed of patients treated for this disease in the same institution during 2015-2016) it was four months.

"Our treatment mainly targets the brain environment that has been altered by metastasis. This is a new therapeutic concept", said Valiente. "We are also attacking an alteration that is only seen when there is brain metastasis, and which is necessary for its viability", he added.

Scientists led by Melchor Sanchez-Martinez, Scientific Director at Mind the Byte, were responsible for the structural studies of STAT3 protein and its binding to silibinin. Combining homology modelling, in silico mutagenesis, docking studies and molecular dynamics, they computationally explored how the interaction occurs and how this is affected by the different STAT3 mutations. This information supports in vivo results and will help further improve the design of new inhibitors.

Original article: Priego N; Zhu L; Monteiro C; Mulders M; Wasilewski D; Bindeman W; Doglio L; Martínez L; Martínez-Saez E; Ramón y Cajal S; Megías D; Hernández-Encinas E; Blanco-Aparicio C; Martínez L; Zarzuela E; Muñoz J, Fustero-Torres C, Pineiero E; Hernández-Laín A; Bertero L; Poli V; Sanchez-Martinez M; Menendez JA; Soffietti R; Bosch-Barrera J, Valiente M. STAT3 labels a subpopulation of reactive astrocytes required for brain metastasis. Nature Medicine 2018 [ePub ahead of Print]. https://doi.org/10.1038/s41591-018-0044-4.

Text adapted from CNIO's press release (link).

Image: The picture shows metastatic cells in the brain (in green. GFP) surrounded by reactive astrocytes (in white. GFAP) some of which activate STAT3 pathway (red nuclei- pSTAT3). pSTAT3+ reactive astrocytes help cancer cells to develop and grow in the brain by modulating local immunity. CNIO.

 

 

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Fri, 22 Jun 2018 09:19:47 +0000 http://www.bioinformaticsbarcelona.eu/news//news/115/a-new-therapy-proves-effective-against-brain-metastasis http://www.bioinformaticsbarcelona.eu/news/115 0