Joke Reumers

Gain of function of mutant p53 by coaggregation with multiple tumor suppressors

Many p53 missense mutations possess dominant-negative activity and oncogenic gain of function. We report that for structurally destabilized p53 mutants, these effects result from mutant-induced coaggregation of wild-type p53 and its paralogs p63 and p73, thereby also inducing a heat-shock response. Aggregation of mutant p53 resulted from self-assembly of a conserved aggregation-nucleating sequence within the hydrophobic core of the DNA-binding domain, which becomes exposed after mutation. Suppressing the aggregation propensity of this sequence by mutagenesis abrogated gain of function and restored activity of wild-type p53 and its paralogs. In the p53 germline mutation database, tumors carrying aggregation-prone p53 mutations have a significantly lower frequency of wild-type allele loss as compared to tumors harboring nonaggregating mutations, suggesting a difference in clonal selection of aggregating mutants. Overall, our study reveals a novel disease mechanism for mutant p53 gain of function and suggests that, at least in some respects, cancer could be considered an aggregation-associated disease.

PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes

We have developed a web tool, PupaSuite, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect, specifically oriented to help in the design of large-scale genotyping projects. PupaSuite uses a collection of data on SNPs from heterogeneous sources and a large number of pre-calculated predictions to offer a flexible and intuitive interface for selecting an optimal set of SNPs. It improves the functionality of PupaSNP and PupasView programs and implements new facilities such as the analysis of users data to derive haplotypes with functional information. A new estimator of putative effect of polymorphisms has been included that uses evolutionary information. Also SNPeffect database predictions have been included. The PupaSuite web interface is accessible through and through .

VEGF pathway genetic variants as biomarkers of treatment outcome with bevacizumab: an analysis of data from the AViTA and AVOREN randomised trials

BACKGROUND No biomarkers that could guide patient selection for treatment with the anti-VEGF monoclonal antibody bevacizumab have been identified. We assessed whether genetic variants in the VEGF pathway could act as biomarkers for bevacizumab treatment outcome. METHODS We investigated DNA from white patients from two phase 3 randomised studies. In AViTA, patients with metastatic pancreatic adenocarcinoma were randomly assigned to receive gemcitabine and erlotinib plus either bevacizumab or placebo. In AVOREN, patients with metastatic renal-cell carcinoma were randomly assigned to receive interferon alfa-2a plus either bevacizumab or placebo. We assessed the correlation of 138 SNPs in the VEGF pathway with progression-free survival and overall survival in a subpopulation of patients from AViTA. Significant findings were confirmed in a subpopulation of patients from AVOREN and functionally studied at the molecular level. FINDINGS We investigated DNA of 154 patients from AViTA, of whom 77 received bevacizumab, and 110 patients from AVOREN, of whom 59 received bevacizumab. Only rs9582036, a SNP in VEGF receptor 1 (VEGFR1 or FLT1), was significantly associated with overall survival in the bevacizumab group of AViTA after correction for multiplicity (per-allele hazard ratio [HR] 2·1, 95% CI 1·45-3·06, p=0·00014). This SNP was also associated with progression-free survival (per-allele HR 1·89, 1·31-2·71, p=0·00081) in bevacizumab-treated patients from AViTA. AC and CC carriers of this SNP exhibited HRs for overall survival of 2·0 (1·19-3·36; p=0·0091) and 4·72 (2·08-10·68; p=0·0002) relative to AA carriers. No effects were seen in placebo-treated patients and a significant genotype by treatment interaction (p=0·041) was recorded, indicating that the VEGFR1 locus containing this SNP serves as a predictive marker for bevacizumab treatment outcome in AViTA. Fine-mapping experiments of this locus identified rs7993418, a synonymous SNP affecting tyrosine 1213 in the VEGFR1 tyrosine-kinase domain, as the functional variant underlying the association. This SNP causes a shift in codon usage, leading to increased VEGFR1 expression and downstream VEGFR1 signalling. This VEGFR1 locus correlated significantly with progression-free survival (HR 1·81, 1·08-3·05; p=0·033) but not overall survival (HR 0·91, 0·45-1·82, p=0·78) in the bevacizumab group in AVOREN. INTERPRETATION A locus in VEGFR1 correlates with increased VEGFR1 expression and poor outcome of bevacizumab treatment. Prospective assessment is underway to validate the predictive value of this novel biomarker. FUNDING F Hoffmann-La Roche.

SNPeffect: a database mapping molecular phenotypic effects of human non-synonymous coding SNPs

Single nucleotide polymorphisms (SNPs) are an increasingly important tool for genetic and biomedical research. However, the accumulated sequence information on allelic variation is not matched by an understanding of the effect of SNPs on the functional attributes or ‘molecular phenotype’ of a protein. Towards this aim we developed SNPeffect, an online resource of human non-synonymous coding SNPs (nsSNPs) mapping phenotypic effects of allelic variation in human genes. SNPeffect contains 31 659 nsSNPs from 12 480 human proteins. The current release of SNPeffect incorporates data on protein stability, integrity of functional sites, protein phosphorylation and glycosylation, subcellular localization, protein turnover rates, protein aggregation, amyloidosis and chaperone interaction. The SNP entries are accessible through both a search and browse interface and are linked to most major biological databases. The data can be displayed as detailed descriptions of individual SNPs or as an overview of all SNPs for a given protein. SNPeffect will be regularly updated and can be accessed at http://snpeffect.vib.be/.

Genome dynamics of the human embryonic kidney 293 lineage in response to cell biology manipulations

The HEK293 human cell lineage is widely used in cell biology and biotechnology. Here we use whole-genome resequencing of six 293 cell lines to study the dynamics of this aneuploid genome in response to the manipulations used to generate common 293 cell derivatives, such as transformation and stable clone generation (293T); suspension growth adaptation (293S); and cytotoxic lectin selection (293SG). Remarkably, we observe that copy number alteration detection could identify the genomic region that enabled cell survival under selective conditions (i.c. ricin selection). Furthermore, we present methods to detect human/vector genome breakpoints and a user-friendly visualization tool for the 293 genome data. We also establish that the genome structure composition is in steady state for most of these cell lines when standard cell culturing conditions are used. This resource enables novel and more informed studies with 293 cells, and we will distribute the sequenced cell lines to this effect.

Genetic variability in the mitochondrial serine protease HTRA2 contributes to risk for Parkinson disease.

In one genetic study, the high temperature requirement A2 (HTRA2) mitochondrial protein has been associated with increased risk for sporadic Parkinson disease (PD). One missense mutation, p.Gly399Ser, in its C‐terminal PDZ domain (from the initial letters of the postsynaptic density 95, PSD‐95; discs large; and zonula occludens‐1, ZO‐1 proteins [Kennedy, 1995 ]) resulted in defective protease activation, and induced mitochondrial dysfunction when overexpressed in stably transfected cells. Here we examined the contribution of genetic variability in HTRA2 to PD risk in an extended series of 266 Belgian PD patients and 273 control individuals. Mutation analysis identified a novel p.Arg404Trp mutation within the PDZ domain predicted to freeze HTRA2 in an inactive form. Moreover, we identified six patient‐specific variants in 5′ and 3′ regulatory regions that might affect HTRA2 expression as supported by data of luciferase reporter gene analyses. Our study confirms a role of the HTRA2 mitochondrial protein in PD susceptibility through mutations in its functional PDZ domain. In addition, it extends the HTRA2 mutation spectrum to functional variants possibly affecting transcriptional activity. The latter underpins a previously unrecognized role for altered HTRA2 expression as a risk factor relevant to parkinsonian neurodegeneration. Hum Mutat 29(6), 832–840, 2008.

Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: a combined case-control study.

IntroductionSeveral common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium.MethodsWe evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects.ResultsThese analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar.ConclusionsThe relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.

PepX: a structural database of non-redundant protein–peptide complexes

Although protein–peptide interactions are estimated to constitute up to 40% of all protein interactions, relatively little information is available for the structural details of these interactions. Peptide-mediated interactions are a prime target for drug design because they are predominantly present in signaling and regulatory networks. A reliable data set of nonredundant protein–peptide complexes is indispensable as a basis for modeling and design, but current data sets for protein–peptide interactions are often biased towards specific types of interactions or are limited to interactions with small ligands. In PepX (http://pepx.switchlab.org), we have designed an unbiased and exhaustive data set of all protein–peptide complexes available in the Protein Data Bank with peptide lengths up to 35 residues. In addition, these complexes have been clustered based on their binding interfaces rather than sequence homology, providing a set of structurally diverse protein–peptide interactions. The final data set contains 505 unique protein–peptide interface clusters from 1431 complexes. Thorough annotation of each complex with both biological and structural information facilitates searching for and browsing through individual complexes and clusters. Moreover, we provide an additional source of data for peptide design by annotating peptides with naturally occurring backbone variations using fragment clusters from the BriX database.

Joint annotation of coding and non-coding single nucleotide polymorphisms and mutations in the SNPeffect and PupaSuite databases

Single nucleotide polymorphisms (SNPs) are, together with copy number variation, the primary source of variation in the human genome. SNPs are associated with altered response to drug treatment, susceptibility to disease and other phenotypic variation. Furthermore, during genetic screens for disease-associated mutations in groups of patients and control individuals, the distinction between disease causing mutation and polymorphism is often unclear. Annotation of the functional and structural implications of single nucleotide changes thus provides valuable information to interpret and guide experiments. The SNPeffect and PupaSuite databases are now synchronized to deliver annotations for both non-coding and coding SNP, as well as annotations for the SwissProt set of human disease mutations. In addition, SNPeffect now contains predictions of Tango2: an improved aggregation detector, and Waltz: a novel predictor of amyloid-forming sequences, as well as improved predictors for regions that are recognized by the Hsp70 family of chaperones. The new PupaSuite version incorporates predictions for SNPs in silencers and miRNAs including their targets, as well as additional methods for predicting SNPs in TFBSs and splice sites. Also predictions for mouse and rat genomes have been added. In addition, a PupaSuite web service has been developed to enable data access, programmatically. The combined database holds annotations for 4 965 073 regulatory as well as 133 505 coding human SNPs and 14 935 disease mutations, and phenotypic descriptions of 43 797 human proteins and is accessible via http://snpeffect.vib.be and http://pupasuite.bioinfo.cipf.es/.

Protein sequences encode safeguards against aggregation

Functional requirements shaped proteins into globular structures. Under these structural constraints, which require both regular secondary structure and a hydrophobic core, protein aggregation is an unavoidable corollary to protein structure. However, as aggregation results in reduced fitness, natural selection will tend to eliminate strongly aggregating sequences. The analysis of distribution and variation of aggregation patterns in the human proteome using the TANGO algorithm confirms the findings of a previous study on several proteomes: the flanks of aggregation‐prone regions are enriched with charged residues and proline, the so‐called gatekeeper‐residues. Moreover, in this study, we observed a widespread redundancy in gatekeeper usage. Interestingly, aggregating regions from key proteins such as p53 or huntingtin are among the most extensive “gatekept” sequences. As a consequence, mutations that remove gatekeepers could therefore result in a strong increase in disease‐susceptibility. In a set of disease‐associated mutations from the UniProt database, we find a strong enrichment of mutations that disrupt gatekeeper motifs. Closer inspection of a number of case studies indicates clearly that removing gatekeepers may play a determining role in widely varying disorders, such as van der Woude syndrome (VWS), X‐linked Fabry disease (FD), and limb‐girdle muscular dystrophy. Hum Mutat 0, 1–7, 2009.