Swiss Institute of Bioinformatics
Recent publications
People living with human immunodeficiency virus (PLWH) have significantly increased risk for cardiovascular disease in part due to inflammation and immune dysregulation. Clonal hematopoiesis of indeterminate potential (CHIP), the age-related acquisition and expansion of hematopoietic stem cells due to leukemogenic driver mutations, increases risk for both hematologic malignancy and coronary artery disease (CAD). Since increased inflammation is hypothesized to be both a cause and consequence of CHIP, we hypothesized that PLWH have a greater prevalence of CHIP. We searched for CHIP in multi-ethnic cases from the Swiss HIV Cohort Study (SHCS, n = 600) and controls from the Atherosclerosis Risk in the Communities study (ARIC, n = 8111) from blood DNA-derived exome sequences. We observed that HIV is associated with a twofold increase in CHIP prevalence, both in the whole study population and in a subset of 230 cases and 1002 matched controls selected by propensity matching to control for demographic imbalances (SHCS 7%, ARIC 3%, p = 0.005). We also observed that ASXL1 is the most commonly mutated CHIP-associated gene in PLWH. Our results suggest that CHIP may contribute to the excess cardiovascular risk observed in PLWH.
Background Non-invasive liquid biopsies could complement current pathological nomograms for risk stratification of prostate cancer patients. Development and testing of potential liquid biopsy markers is time, resource, and cost-intensive. For most protein targets, no antibodies or ELISAs for efficient clinical cohort pre-evaluation are currently available. We reasoned that mass spectrometry-based prescreening would enable the cost-effective and rational preselection of candidates for subsequent clinical-grade ELISA development. Methods Using Mass Spectrometry-GUided Immunoassay DEvelopment (MS-GUIDE), we screened 48 literature-derived biomarker candidates for their potential utility in risk stratification scoring of prostate cancer patients. Parallel reaction monitoring was used to evaluate these 48 potential protein markers in a highly multiplexed fashion in a medium-sized patient cohort of 78 patients with ground-truth prostatectomy and clinical follow-up information. Clinical-grade ELISAs were then developed for two of these candidate proteins and used for significance testing in a larger, independent patient cohort of 263 patients. Results Machine learning-based analysis of the parallel reaction monitoring data of the liquid biopsies prequalified fibronectin and vitronectin as candidate biomarkers. We evaluated their predictive value for prostate cancer biochemical recurrence scoring in an independent validation cohort of 263 prostate cancer patients using clinical-grade ELISAs. The results of our prostate cancer risk stratification test were statistically significantly 10% better than results of the current gold standards PSA alone, PSA plus prostatectomy biopsy Gleason score, or the National Comprehensive Cancer Network score in prediction of recurrence. Conclusion Using MS-GUIDE we identified fibronectin and vitronectin as candidate biomarkers for prostate cancer risk stratification.
Cryptorchidism occurs frequently in children with cystic fibrosis. Among boys with cryptorchidism and abrogated mini-puberty, the development of the epididymis and the vas deferens is frequently impaired. This finding suggests that a common cause underlies the abnormal development of Ad spermatogonia and the epididymis. The cystic fibrosis transmembrane conductance regulator (CFTR) is an ATP-binding cassette transporter protein that acts as a chloride channel. The CFTR gene has been associated with spermatogenesis and male fertility. In boys with cryptorchidism, prepubertal hypogonadotropic hypogonadism induces suboptimal expression of the ankyrin-like protein gene, ASZ1 , the P-element induced wimpy testis-like gene, PIWIL, and CFTR . The abrogated expression of these gene leads to transposon reactivation, and ultimately, infertility. Curative gonadotropin-releasing hormone agonist (GnRHa) treatment stimulates the expression of CFTR and PIWIL3 , which play important roles in the development of Ad spermatogonia and fertility. Furthermore, GnRHa stimulates the expression of the epididymal androgen-sensitive genes, CRISP1, WFDC8, SPINK13 , and PAX2 , which thereby promotes epididymal development. This review focuses on molecular evidence that favors a role for CFTR in cryptorchidism-induced infertility. Based on information available in the literature, we interpreted our RNA-Seq expression data obtained from samples before and after randomized GnRHa treatment in boys with bilateral cryptorchidism. We propose that, in boys with cryptorchidism, CFTR expression is controlled by luteinizing hormone and testosterone. Moreover, CFTR regulates the activities of genes that are important for fertility and Wolffian duct differentiation.
Characterization of gene expression in pancreatic islets and its alteration in type 2 diabetes (T2D) are vital in understanding islet function and T2D pathogenesis. We leveraged RNA sequencing and genome-wide genotyping in islets from 188 donors to create the Islet Gene View (IGW) platform to make this information easily accessible to the scientific community. Expression data were related to islet phenotypes, diabetes status, other islet-expressed genes, islet hormone-encoding genes and for expression in insulin target tissues. The IGW web application produces output graphs for a particular gene of interest. In IGW, 284 differentially expressed genes (DEGs) were identified in T2D donor islets compared with controls. Forty percent of DEGs showed cell-type enrichment and a large proportion significantly co-expressed with islet hormone-encoding genes; glucagon ( GCG , 56%), amylin ( IAPP , 52%), insulin ( INS , 44%), and somatostatin ( SST , 24%). Inhibition of two DEGs, UNC5D and SERPINE2 , impaired glucose-stimulated insulin secretion and impacted cell survival in a human β-cell model. The exploratory use of IGW could help designing more comprehensive functional follow-up studies and serve to identify therapeutic targets in T2D.
Cancer evolution is driven by the concerted action of multiple molecular alterations, which emerge and are selected during tumor progression. An alteration is selected when it provides an advantage to the tumor cell. However, the advantage provided by a specific alteration depends on the tumor lineage, cell epigenetic state, and presence of additional alterations. In this case, we say that an evolutionary dependency exists between an alteration and what influences its selection. Epistatic interactions between altered genes lead to evolutionary dependencies (EDs), by favoring or vetoing specific combinations of events. Large-scale cancer genomics studies have discovered examples of such dependencies, and showed that they influence tumor progression, disease phenotypes, and therapeutic response. In the past decade, several algorithmic approaches have been proposed to infer EDs from large-scale genomics datasets. These methods adopt diverse strategies to address common challenges and shed new light on cancer evolutionary trajectories. Here, we review these efforts starting from a simple conceptualization of the problem, presenting the tackled and still unmet needs in the field, and discussing the implications of EDs in cancer biology and precision oncology.
The spread of antibiotic resistance genes on plasmids is a threat to human and animal health. Phylogenies of bacteria and their plasmids contain clues regarding the frequency of plasmid transfer events, as well as the co-evolution of plasmids and their hosts. However, whole genome sequencing data from diverse ecological or clinical bacterial samples are rarely used to study plasmid phylogenies and resistance gene transfer. This is partially due to the difficulty of extracting plasmids from short-read sequencing data. Here, we use both short- and long-read sequencing data of 24 clinical extended-spectrum β -lactamase (ESBL)-producing Escherichia coli to estimate chromosomal and plasmid phylogenies. We compare the impact of different sequencing and assembly methodologies on these phylogenies and on the inference of horizontal gene transfer. We find that chromosomal phylogenies can be estimated robustly with all methods, whereas plasmid phylogenies have more variable topology and branch lengths across the methods used. Specifically, hybrid methods that use long reads to resolve short-read assemblies (HybridSPAdes and Unicycler) perform better than those that started from long reads during assembly graph generation (Canu). By contrast, the inference of plasmid and antibiotic resistance gene transfer using a parsimony-based criterion is mostly robust to the choice of sequencing and assembly method. This article is part of a discussion meeting issue ‘Genomic population structures of microbial pathogens’.
DNA variants that modulate life span provide insight into determinants of health, disease, and aging. Through analyses in the UM-HET3 mice of the Interventions Testing Program (ITP), we detected a sex-independent quantitative trait locus (QTL) on chromosome 12 and identified sex-specific QTLs, some of which we detected only in older mice. Similar relations between life history and longevity were uncovered in mice and humans, underscoring the importance of early access to nutrients and early growth. We identified common age- and sex-specific genetic effects on gene expression that we integrated with model organism and human data to create a hypothesis-building interactive resource of prioritized longevity and body weight genes. Finally, we validated Hipk1, Ddost, Hspg2, Fgd6, and Pdk1 as conserved longevity genes using Caenorhabditis elegans life-span experiments.
Selection protocols such as SELEX, where molecules are selected over multiple rounds for their ability to bind to a target of interest, are popular methods for obtaining binders for diagnostic and therapeutic purposes. We show that Restricted Boltzmann Machines (RBMs), an unsupervised two-layer neural network architecture, can successfully be trained on sequence ensembles from single rounds of SELEX experiments for thrombin aptamers. RBMs assign scores to sequences that can be directly related to their fitnesses estimated through experimental enrichment ratios. Hence, RBMs trained from sequence data at a given round can be used to predict the effects of selection at later rounds. Moreover, the parameters of the trained RBMs are interpretable and identify functional features contributing most to sequence fitness. To exploit the generative capabilities of RBMs, we introduce two different training protocols: one taking into account sequence counts, capable of identifying the few best binders, and another based on unique sequences only, generating more diverse binders. We then use RBMs model to generate novel aptamers with putative disruptive mutations or good binding properties, and validate the generated sequences with gel shift assay experiments. Finally, we compare the RBM’s performance with different supervised learning approaches that include random forests and several deep neural network architectures.
Rhizobia fix nitrogen within root nodules of host plants where nitrogenase expression is strictly controlled by its key regulator NifA. We recently discovered that in nodules infected by the beta-rhizobial strain Paraburkholderia phymatum STM815, NifA controls expression of two bacterial auxin synthesis genes. Both the iaaM and iaaH transcripts, as well as the metabolites indole-acetamide (IAM) and indole-3-acetic acid (IAA) showed increased abundance in nodules occupied by a nifA mutant compared to wild-type nodules. Here, we document the structural changes that a P. phymatum nifA mutant induces in common bean ( Phaseolus vulgaris ) nodules, eventually leading to hypernodulation. To investigate the role of the P. phymatum iaaMH genes during symbiosis, we monitored their expression in presence and absence of NifA over different stages of the symbiosis. The iaaMH genes were found to be under negative control of NifA in all symbiotic stages. While a P. phymatum iaaMH mutant produced the same number of nodules and nitrogenase activity as the wild-type strain, the nifA mutant produced more nodules than the wild-type that clustered into regularly-patterned root zones. Mutation of the iaaMH genes in a nifA mutant background reduced the presence of these nodule clusters on the root. We further show that the P. phymatum iaaMH genes are located in a region of the symbiotic plasmid with a significantly lower GC content and exhibit high similarity to two genes of the IAM pathway often used by bacterial phytopathogens to deploy IAA as a virulence factor. Overall, our data suggest that the increased abundance of rhizobial auxin in the non-fixing nifA mutant strain enables greater root infection rates and a role for bacterial auxin production in the control of early stage symbiotic interactions.
Genetic variations affect behavior and cause disease but understanding how these variants drive complex traits is still an open question. A common approach is to link the genetic variants to intermediate molecular phenotypes such as the transcriptome using RNA-sequencing (RNA-seq). Paradoxically, these variants between the samples are usually ignored at the beginning of RNA-seq analyses of many model organisms. This can skew the transcriptome estimates that are used later for downstream analyses, such as expression quantitative trait locus (eQTL) detection. Here, we assessed the impact of reference-based analysis on the transcriptome and eQTLs in a widely-used mouse genetic population: the BXD panel of recombinant inbred lines. We highlight existing reference bias in the transcriptome data analysis and propose practical solutions which combine available genetic variants, genotypes, and genome reference sequence. The use of custom BXD line references improved downstream analysis compared to classical genome reference. These insights would likely benefit genetic studies with a transcriptomic component and demonstrate that genome references need to be reassessed and improved.
Proximal genetic variants are frequently correlated, implying that the corresponding effect sizes detected by genome-wide association studies (GWAS) are also not independent. Methods already exist to account for this when aggregating effects from a single GWAS across genes or pathways. Here we present a rigorous yet fast method for detecting genes with coherent association signals for two traits, facilitating cross-GWAS analyses. To this end, we devised a new significance test for the covariance of datapoints not drawn independently but with a known inter-sample covariance structure. We show that the distribution of its test statistic is a linear combination of χ ² distributions with positive and negative coefficients. The corresponding cumulative distribution function can be efficiently calculated with Davies’ algorithm at high precision. We apply this general framework to test for dependence between SNP-wise effect sizes of two GWAS at the gene level. We extend this test to detect also gene-wise causal links. We demonstrate the utility of our method by uncovering potential shared genetic links between the severity of COVID-19 and (1) being prescribed class M05B medication (drugs affecting bone structure and mineralization), (2) rheumatoid arthritis, (3) vitamin D (25OHD), and (4) serum calcium concentrations. Our method detects a potential role played by chemokine receptor genes linked to T H 1 versus T H 2 immune response, a gene related to integrin beta-1 cell surface expression, and other genes potentially impacting the severity of COVID-19. Our approach will be useful for similar analyses involving datapoints with known auto-correlation structures.
Background Starch, a vital plant-derived polysaccharide comprised of branched glucans, is essential in nutrition and many industrial applications. Starch is often modified post-extraction to alter its structure and enhance its functionality. Targeted metabolic engineering of crops to produce valuable and versatile starches requires knowledge of the relationships between starch biosynthesis, structure, and properties, but systematic studies to obtain this knowledge are difficult to conduct in plants. Here we used Saccharomyces cerevisiae as a testbed to dissect the functions of plant starch biosynthetic enzymes and create diverse starch-like polymers. Results We explored yeast promoters and terminators to tune the expression levels of the starch-biosynthesis machinery from Arabidopsis thaliana . We systematically modulated the expression of each starch synthase (SS) together with a branching enzyme (BE) in yeast. Protein quantification by parallel reaction monitoring (targeted proteomics) revealed unexpected effects of glucan biosynthesis on protein abundances but showed that the anticipated broad range of SS/BE enzyme ratios was maintained during the biosynthetic process. The different SS/BE ratios clearly influenced glucan structure and solubility: The higher the SS/BE ratio, the longer the glucan chains and the more glucans were partitioned into the insoluble fraction. This effect was irrespective of the SS isoform, demonstrating that the elongation/branching ratio controls glucan properties separate from enzyme specificity. Conclusions Our results provide a quantitative framework for the in silico design of improved starch biosynthetic processes in plants. Our study also exemplifies a workflow for the rational tuning of a complex pathway in yeast, starting from the selection and evaluation of expression modules to multi-gene assembly and targeted protein monitoring during the biosynthetic process.
Background and aims: Immunohistochemistry for hepatitis E virus (HEV) ORF2 (capsid) protein is a powerful tool for tissue-based diagnosis of hepatitis E, particularly useful in evaluating abnormal liver values in immunocompromised patients. We here report a previously unobserved reactivity of the HEV ORF2 antibody to human cytomegalovirus (CMV) proteins and contrast the staining patterns encountered in HEV and CMV infection, respectively. Methods and results: As part of a routine diagnostic workup, the liver biopsy of an immunocompromised patient with elevated liver values was examined histologically for infection with viruses including CMV and HEV. Cytopathic changes were found, suggestive of CMV infection, which was confirmed by immunohistochemistry. Surprisingly, reactivity of a portion of CMV-infected cells with a mouse monoclonal antibody (clone 1E6) against HEV ORF2 protein was also detected. This observation prompted a screening of 22 further specimens (including liver, gastrointestinal, lung, brain and placental biopsies) with confirmed CMV infection/reactivation. Immunoreactivity of CMV-infected cells with HEV ORF2 antibody was observed in totally 18 of 23 specimens. While the HEV ORF2 antibody showed cytoplasmic, nuclear, and canalicular positivity in hepatitis E cases, positivity in CMV-infected cells was limited to the nucleus. Conclusions: The HEV ORF2 antibody (clone 1E6) shows unexpected immunoreactivity against CMV proteins. In contrast to the hepatitis E staining pattern with cytoplasmic, nuclear and occasional canalicular positivity, reactivity in CMV-infected cells is restricted to the nucleus. Awareness of this cross-reactivity and knowledge of the differences in staining patterns will prevent pathologists from misinterpreting positive HEV ORF2 immunohistochemistry in liver specimens.
Experimental studies of cell growth, inheritance and their associated processes by microscopy require accurate single-cell observations of sufficient duration to reconstruct the genealogy. However, cell tracking—assigning identical cells on consecutive images to a track—is often challenging, resulting in laborious manual verification. Here, we propose fingerprints to identify problematic assignments rapidly. A fingerprint distance compares the structural information contained in the low frequencies of a Fourier transform to measure the similarity between cells in two consecutive images. We show that fingerprints are broadly applicable across cell types and image modalities, provided the image has sufficient structural information. Our tracker (TracX) uses fingerprints to reject unlikely assignments, thereby increasing tracking performance on published and newly generated long-term data sets. For Saccharomyces cerevisiae, we propose a comprehensive model for cell size control at the single-cell and population level centered on the Whi5 regulator, demonstrating how precise tracking can help uncover previously undescribed single-cell biology. TracX improves the accuracy of single-cell tracking by using a fingerprinting approach to measure the similarity between cells in two consecutive images. The approach is applicable across modalities and can enables biological discovery.
Background Giardia lamblia , a parasitic protist of the Metamonada supergroup, has evolved one of the most diverged endocytic compartment systems investigated so far. Peripheral endocytic compartments, currently known as peripheral vesicles or vacuoles (PVs), perform bulk uptake of fluid phase material which is then digested and sorted either to the cell cytosol or back to the extracellular space. Results Here, we present a quantitative morphological characterization of these organelles using volumetric electron microscopy and super-resolution microscopy (SRM). We defined a morphological classification for the heterogenous population of PVs and performed a comparative analysis of PVs and endosome-like organelles in representatives of phylogenetically related taxa, Spironucleus spp. and Tritrichomonas foetus . To investigate the as-yet insufficiently understood connection between PVs and clathrin assemblies in G. lamblia , we further performed an in-depth search for two key elements of the endocytic machinery, clathrin heavy chain (CHC) and clathrin light chain (CLC), across different lineages in Metamonada. Our data point to the loss of a bona fide CLC in the last Fornicata common ancestor (LFCA) with the emergence of a protein analogous to CLC ( Gl ACLC) in the Giardia genus. Finally, the location of clathrin in the various compartments was quantified. Conclusions Taken together, this provides the first comprehensive nanometric view of Giardia ’s endocytic system architecture and sheds light on the evolution of Gl ACLC analogues in the Fornicata supergroup and, specific to Giardia, as a possible adaptation to the formation and maintenance of stable clathrin assemblies at PVs.
Polygenic risk prediction remains an important aim of genetic association studies. Currently, the predictive power of schizophrenia polygenic risk scores (PRSs) is not large enough to allow highly accurate discrimination between cases and controls and thus is not adequate for clinical integration. Since PRSs are rarely used to reveal biological functions or to validate candidate pathways, to fill this gap, we investigated whether their predictive ability could be improved by building genome-wide (GW-PRSs) and pathway-specific PRSs, using distance- or expression quantitative trait loci (eQTLs)- based mapping between genetic variants and genes. We focused on five pathways (glutamate, oxidative stress, GABA/interneurons, neuroimmune/neuroinflammation and myelin) which belong to a critical hub of schizophrenia pathophysiology, centred on redox dysregulation/oxidative stress. Analyses were first performed in the Lausanne Treatment and Early Intervention in Psychosis Program (TIPP) study (n = 340, cases/controls: 208/132), a sample of first-episode of psychosis patients and matched controls, and then validated in an independent study, the epidemiological and longitudinal intervention program of First-Episode Psychosis in Cantabria (PAFIP) (n = 352, 224/128). Our results highlighted two main findings. First, GW-PRSs for schizophrenia were significantly associated with early psychosis status. Second, oxidative stress was the only significantly associated pathway that showed an enrichment in both the TIPP (p = 0.03) and PAFIP samples (p = 0.002), and exclusively when gene-variant linking was done using eQTLs. The results suggest that the predictive accuracy of polygenic risk scores could be improved with the inclusion of information from functional annotations, and through a focus on specific pathways, emphasizing the need to build and study functionally informed risk scores.
The mutational spectrum of the mitochondrial DNA (mtDNA) does not resemble any of the known mutational signatures of the nuclear genome and variation in mtDNA mutational spectra between different organisms is still incomprehensible. Since mitochondria are responsible for aerobic respiration, it is expected that mtDNA mutational spectrum is affected by oxidative damage. Assuming that oxidative damage increases with age, we analyse mtDNA mutagenesis of different species in regards to their generation length. Analysing, (i) dozens of thousands of somatic mtDNA mutations in samples of different ages (ii) 70053 polymorphic synonymous mtDNA substitutions reconstructed in 424 mammalian species with different generation lengths and (iii) synonymous nucleotide content of 650 complete mitochondrial genomes of mammalian species we observed that the frequency of AH > GH substitutions (H: heavy strand notation) is twice bigger in species with high versus low generation length making their mtDNA more AH poor and GH rich. Considering that AH > GH substitutions are also sensitive to the time spent single-stranded (TSSS) during asynchronous mtDNA replication we demonstrated that AH > GH substitution rate is a function of both species-specific generation length and position-specific TSSS. We propose that AH > GH is a mitochondria-specific signature of oxidative damage associated with both aging and TSSS.
The Permian–Triassic Mass Extinction (PTME), life’s most severe crisis1, has been attributed to intense global warming triggered by CO2 emissions from Large Igneous Province volcanism2–8. It remains unclear, however, why super-greenhouse conditions persisted for around five million years after the volcanic episode, when Earth system feedbacks should have returned temperatures to pre-extinction levels within a few hundred thousand years8. Here we use fossil occurrences and lithological indicators of climate to reconstruct spatio-temporal maps of plant productivity and biomass changes through the Permian–Triassic and undertake climate-biogeochemical modelling to investigate the unusual longevity and intensity of warming. Our reconstructions show that terrestrial vegetation collapse during the PTME, especially in tropical regions, resulted in an Earth system with low levels of organic carbon sequestration and chemical weathering, leading to limited drawdown of greenhouse gases. This led to a protracted period of extremely high surface temperatures, during which biotic recovery was delayed for millions of years. Our results support the idea that thresholds exist in the climate-carbon system beyond which warming may be amplified substantially.
The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, implying that genotype-phenotype landscapes with only simple sign epistasis motifs will always give rise to single-peaked fitness landscapes under such selection. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.
Background: Adult-type diffuse gliomas, CNS WHO grade 4 are the most aggressive primary brain tumors and represent a particular challenge of therapeutic intervention. Methods: In a single-center retrospective study of matched pairs of initial and post-therapeutic glioma cases with a recurrence period greater than one year, we performed whole exome sequencing combined with mRNA and microRNA expression profiling to identify processes that are altered in recurrent gliomas. Results: Mutational analysis of recurrent gliomas revealed early branching evolution in seventy-five percent of patients. High plasticity was confirmed at the mRNA and miRNA levels. SBS1 signature was reduced and SBS11 was elevated, demonstrating the effect of alkylating agent therapy on the mutational landscape. There was no evidence for secondary genomic alterations driving therapy resistance. ALK7/ACVR1C and LTBP1 were upregulated, whereas LEFTY2 was downregulated, pointing towards enhanced Tumor Growth Factor β (TGF-β) signaling in recurrent gliomas. Consistently, altered microRNA expression profiles pointed towards enhanced Nuclear Factor Kappa B and Wnt signaling that, cooperatively with TGF-β, induces epithelial to mesenchymal transition (EMT), migration and stemness. TGF-β-induced expression of pro-apoptotic proteins and repression of anti-apoptotic proteins were uncoupled in the recurrent tumor. Conclusions: Our results suggest an important role of TGF-β signaling in recurrent gliomas. This may have clinical implication, since TGF-β inhibitors have entered clinical phase studies and may potentially be used in combination therapy to interfere with chemoradiation resistance. Recurrent gliomas show high incidence of early branching evolution. High tumor plasticity is confirmed at the level of microRNA and mRNA expression profiles.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.
103 members
Markus Müller
  • Proteome Informatics Group
Antoine Daina
  • Molecular Modeling Group
Ron D Appel
  • Management
Elisabeth Gasteiger
  • Swiss-Prot Group
Emmanuel Boutet
  • Swiss-Prot
Lausanne, Switzerland