VHLdb: A database of von Hippel-Lindau protein interactors and mutations

Tabaro, Francesco; Minervini, Giovanni; Sundus, Faiza; Quaglia, Federica; Leonardi, Emanuela; Piovesan, Damiano; Tosatto, Silvio C. E.

doi:10.1038/srep31128

Cited by 41 publications

(71 citation statements)

References 60 publications

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“…Interface B forms the HIF-1α binding-site (7), while interface C participates in the cullin2 interaction (26). A further interface is defined by an accessory N-terminal tail (surface D) present only in the pVHL30 isoform (23). As the recently developed VHLdb database (23) collects pVHL interactors and mutations, here we present an analysis of this data to shed light on pVHL functions.…”

Section: Resultsmentioning

confidence: 99%

“…pVHL is also known to harbor at least three different binding surfaces (22) which are thought to be involved in multiple protein-protein interactions. While hundreds of different pVHL protein-protein associations are described (23), whether and how these HIF-independent pVHL contribute to VHL tumorigenesis is largely unknown. Here, we present our efforts in deciphering pVHL function.…”

Section: Introductionmentioning

confidence: 99%

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Genotype-Phenotype Relations of the von Hippel-Lindau Tumor Suppressor Inferred from a Large-Scale Analysis of Disease Mutations and Interactors

Minervini

Quaglia

Tabaro

et al. 2018

Preprint

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Familiar cancers represent a privileged point of view for studying the complex cellular events inducing tumor transformation. Von Hippel-Lindau syndrome, a familiar predisposition to develop cancer is a clear example. Here, we present our efforts to decipher the role of von Hippel-Lindau tumor suppressor protein (pVHL) in cancer insurgence. We collected high quality information about both pVHL mutations and interactors to investigate the association between patient phenotypes, mutated protein surface and impaired interactions. Our data suggest that different phenotypes correlate with localized perturbations of the pVHL structure, with specific cell functions associated to different protein surfaces. We propose five different pVHL interfaces to be selectively involved in modulating proteins regulating gene expression, protein homeostasis as well as to address extracellular matrix (ECM) and ciliogenesis associated functions. These data were used to drive molecular docking of pVHL with its interactors and guide Petri net simulations of the most promising alterations. We predict that disruption of pVHL association with certain interactors can trigger tumor transformation, inducing metabolism imbalance and ECM remodeling. Collectively taken, our findings provide novel insights into VHL-associated tumorigenesis. This highly integrated in silico approach may help elucidate novel treatment paradigms for VHL disease. Author summaryCancer is generally caused by a series of mutations accumulating over time in a healthy tissue, which becomes re-programmed to proliferate at the expense of the hosting organism. This process is difficult to follow and understand as events in a multitude of different genes can lead to similar outcomes without apparent cause. The von Hippel-Lindau (VHL) tumor suppressor is one of the few genes harboring a familiar cancer syndrome, i.e. VHL mutations are known to cause a predictable series of events leading cancer in the kidneys and a few selected other tissues. This article describes a large-scale analysis to relate known VHL mutations to specific cancer pathways by looking at the molecular interactions.Different cancer types appear to be caused by mutations changing the surface of specific parts of the VHL protein. By looking at the VHL interactors involved, it is therefore possible to identify other candidate genes for mutations leading to very similar cancer types.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genotype-Phenotype Relations of the von Hippel-Lindau Tumor Suppressor Inferred from a Large-Scale Analysis of Disease Mutations and Interactors

Minervini

Quaglia

Tabaro

et al. 2018

Preprint

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“…To address this, we sought to develop a VHL‐specific database which would serve as a platform to comprehensively catalog clinical and genetic information in a standardized format. While databases such as VHLdb and CIViC (Clinical Interpretations of Variants in Cancer) have been created to house VHL‐related genetic information and associated manifestations, they do not contain detailed data on all VHL manifestations which may be of interest for an individual investigator. Additionally, Takayanagi et al published a database specific to the VHL patient population in Japan, however, this database was limited to the use of epidemiological surveys and was restricted in its scalability .…”

Section: Introductionmentioning

confidence: 99%

Comprehensive characterization of a Canadian cohort of von Hippel‐Lindau disease patients

et al. 2019

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Von Hippel‐Lindau disease (VHL) is a heritable condition caused by pathogenic variants in VHL and is characterized by benign and malignant lesions in the central nervous system (CNS) and abdominal viscera. Due to its variable expressivity, existing efforts to collate VHL patient data do not adequately capture all VHL manifestations. We developed a comprehensive and standardized VHL database in the web‐based application, REDCap, that thoroughly captures all VHL manifestation data. As an initial trial, information from 86 VHL patients from the University Health Network/Hospital for Sick Children was populated into the database. Analysis of this cohort showed missense variants occurring with the greatest frequency, with all variants localizing to the α‐ or β‐domains of VHL. The most prevalent manifestations were central nervous system (CNS), renal, and retinal neoplasms, which were associated with frameshift variants and large deletions. We observed greater age‐related penetrance for CNS hemangioblastomas with truncating variants compared to missense, while the reverse was true for pheochromocytomas. We demonstrate the utility of a comprehensive VHL database, which supports the standardized collection of clinical and genetic data specific to this patient population. Importantly, we expect that its web‐based design will facilitate broader international collaboration and lead to a better understanding of VHL.

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“…PH also plays a crucial role in signaling, in particular in the oxygen sensing pathways, including angiogenesis (9) and tumor cell proliferation (10,11). An example is HIF1α, the main target of the von Hippel-Lindau (pVHL) E3 ubiquitin ligase complex (12). In normoxia, the prolyl hydroxylase domain-containing enzymes (PHDs) hydroxylate HIF1α, promoting its degradation through pVHL binding (13).…”

Section: Introductionmentioning

confidence: 99%

Assessing predictors for new post translational modification sites: a case study on hydroxylation

Piovesan

Hatos

Minervini

et al. 2020

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Post-translational modification (PTM) sites have become popular for predictor development. However, with the exception of phosphorylation and a handful of other examples, PTMs suffer from a limited number of available training examples and their sparsity in protein sequences. Here, proline hydroxylation is taken as an example to compare different methods and evaluate their performance on new experimentally determined sites. As a proxy for an effective experimental design, predictors require both high specificity and sensitivity. However, the self-reported performance is often not indicative of prediction quality and detection of new sites is not guaranteed. We have benchmarked seven published hydroxylation site predictors on two newly constructed independent datasets. The self-reported performance widely overestimates the real accuracy measured on independent datasets. No predictor performs better than random on new examples, indicating the refined models are not sufficiently general to detect new sites. The number of false positives is high and precision low, in particular for non-collagen proteins whose motifs are not conserved. In short, existing predictors for hydroxylation sites do not appear to generalize to new data. Caution is advised when dealing with PTM predictors in the absence of independent evaluations, in particular for unique specific sites such as those involved in signalling. Author SummaryMachine learning methods are extensively used by biologists to design and interpret experiments. Predictors which take the only sequence as input are of particular interest due to the large amount of sequence data available and self-reported performance is often very high. In this work, we evaluated post-translational modification (PTM) predictors for hydroxylation sites and found that they perform no better than random, in strong contrast to performances reported in the original publications. PTMs are chemical amino acids alterations providing the cell with conditional mechanisms to fine tune protein function, thereby regulating complex biological processes such as signalling and cell cycle. Hydroxylation sites are a good PTM test case due to the availability of a range of predictors and an abundance of newly experimentally detected modification sites. Poor performances in our results highlight the overlooked problem of predicting PTMs when best practices are not followed and training data are likely incomplete. Experimentalists should be careful when using PTM predictors blindly and more independent assessments are needed to separate the wheat from the chaff in the field.

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VHLdb: A database of von Hippel-Lindau protein interactors and mutations

Cited by 41 publications

References 60 publications

Genotype-Phenotype Relations of the von Hippel-Lindau Tumor Suppressor Inferred from a Large-Scale Analysis of Disease Mutations and Interactors

Genotype-Phenotype Relations of the von Hippel-Lindau Tumor Suppressor Inferred from a Large-Scale Analysis of Disease Mutations and Interactors

Comprehensive characterization of a Canadian cohort of von Hippel‐Lindau disease patients

Assessing predictors for new post translational modification sites: a case study on hydroxylation

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