An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma

Saturation genome editing maps the functional spectrum of pathogenic VHL alleles

To maximize the impact of precision medicine approaches, it is critical to identify genetic variants underlying disease and to accurately quantify their functional effects. A gene exemplifying the challenge of variant interpretation is the von Hippel-Lindautumor suppressor (VHL). VHL encodes an E3 ubiquitin ligase that regulates the cellular response to hypoxia. Germline pathogenic variants in VHL predispose patients to tumors including clear cell renal cell carcinoma (ccRCC) and pheochromocytoma, and somatic VHL mutations are frequently observed in sporadic renal cancer. Here we optimize and apply saturation genome editing to assay nearly all possible single-nucleotide variants (SNVs) across VHL's coding sequence. To delineate mechanisms, we quantify mRNA dosage effects and compare functional effects in isogenic cell lines. Function scores for 2,268 VHL SNVs identify a core set of pathogenic alleles driving ccRCC with perfect accuracy, inform differential risk across tumor types and reveal new mechanisms by which variants impact function. These results have immediate utility for classifying VHL variants encountered clinically and illustrate how precise functional measurements can resolve pleiotropic and dosage-dependent genotype-phenotype relationships across complete genes.

Characterizing and predicting ccRCC-causing missense mutations in Von Hippel-Lindau disease

BACKGROUND

Mutations within the Von Hippel-Lindau (VHL) tumor suppressor gene are known to cause VHL disease, which is characterized by the formation of cysts and tumors in multiple organs of the body, particularly clear cell renal cell carcinoma (ccRCC). A major challenge in clinical practice is determining tumor risk from a given mutation in the VHL gene. Previous efforts have been hindered by limited available clinical data and technological constraints.

METHODS

To overcome this, we initially manually curated the largest set of clinically validated VHL mutations to date, enabling a robust assessment of existing predictive tools on an independent test set. Additionally, we comprehensively characterized the effects of mutations within VHL using in silico biophysical tools describing changes in protein stability, dynamics and affinity to binding partners to provide insights into the structure-phenotype relationship. These descriptive properties were used as molecular features for the construction of a machine learning model, designed to predict the risk of ccRCC development as a result of a VHL missense mutation.

RESULTS

Analysis of our model showed an accuracy of 0.81 in the identification of ccRCC-causing missense mutations, and a Matthew's Correlation Coefficient of 0.44 on a non-redundant blind test, a significant improvement in comparison to the previous available approaches.

CONCLUSION

This work highlights the power of using protein 3D structure to fully explore the range of molecular and functional consequences of genomic variants. We believe this optimized model will better enable its clinical implementation and assist guiding patient risk stratification and management.

VHL mosaicism: the added value of multi-tissue analysis

Von Hippel-Lindau disease (VHL) is an autosomal dominant, inherited syndrome with variants in the VHL gene causing predisposition to multi-organ benign and malignant neoplasms. A germline VHL variant is identified in 95-100% of individuals with a clinical diagnosis of VHL. Here, we present the case of an individual with a clinical diagnosis of VHL disease where peripheral blood DNA analysis did not detect a VHL variant. Sequencing of four tumor tissues (ccRCC, pheochromocytoma, lung via sputum, liver) revealed a VHL c.593 T > C (p.Leu198Pro) variant at varying allele fractions (range: 10-55%) in all tissues. Re-examination of the peripheral blood sequencing data identified this variant at 6% allele fraction. Tumor analysis revealed characteristic cytomorphological, immunohistochemical reactivity for alpha-inhibin, and CAIX, and reduced pVHL reactivity supported VHL-related pseudohypoxia. This report of a rare case of VHL mosaicism highlights the value of tissue testing in VHL variant negative cases.

Systematic evaluation of computational tools to predict the effects of mutations on protein stability in the absence of experimental structures

Changes in protein sequence can have dramatic effects on how proteins fold, their stability and dynamics. Over the last 20 years, pioneering methods have been developed to try to estimate the effects of missense mutations on protein stability, leveraging growing availability of protein 3D structures. These, however, have been developed and validated using experimentally derived structures and biophysical measurements. A large proportion of protein structures remain to be experimentally elucidated and, while many studies have based their conclusions on predictions made using homology models, there has been no systematic evaluation of the reliability of these tools in the absence of experimental structural data. We have, therefore, systematically investigated the performance and robustness of ten widely used structural methods when presented with homology models built using templates at a range of sequence identity levels (from 15% to 95%) and contrasted performance with sequence-based tools, as a baseline. We found there is indeed performance deterioration on homology models built using templates with sequence identity below 40%, where sequence-based tools might become preferable. This was most marked for mutations in solvent exposed residues and stabilizing mutations. As structure prediction tools improve, the reliability of these predictors is expected to follow, however we strongly suggest that these factors should be taken into consideration when interpreting results from structure-based predictors of mutation effects on protein stability.

Identifying Genotype-Phenotype Correlations via Integrative Mutation Analysis

Mutations in protein-coding regions can lead to large biological changes and are associated with genetic conditions, including cancers and Mendelian diseases, as well as drug resistance. Although whole genome and exome sequencing help to elucidate potential genotype-phenotype correlations, there is a large gap between the identification of new variants and deciphering their molecular consequences. A comprehensive understanding of these mechanistic consequences is crucial to better understand and treat diseases in a more personalized and effective way. This is particularly relevant considering estimates that over 80% of mutations associated with a disease are incorrectly assumed to be causative. A thorough analysis of potential effects of mutations is required to correctly identify the molecular mechanisms of disease and enable the distinction between disease-causing and non-disease-causing variation within a gene. Here we present an overview of our integrative mutation analysis platform, which focuses on refining the current genotype-phenotype correlation methods by using the wealth of protein structural information.

SKEMPI 2.0: an updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation

Motivation

Understanding the relationship between the sequence, structure, binding energy, binding kinetics and binding thermodynamics of protein–protein interactions is crucial to understanding cellular signaling, the assembly and regulation of molecular complexes, the mechanisms through which mutations lead to disease, and protein engineering.

Results

We present SKEMPI 2.0, a major update to our database of binding free energy changes upon mutation for structurally resolved protein–protein interactions. This version now contains manually curated binding data for 7085 mutations, an increase of 133%, including changes in kinetics for 1844 mutations, enthalpy and entropy changes for 443 mutations, and 440 mutations, which abolish detectable binding.

Availability and implementation

The database is available as supplementary data and at https://life.bsc.es/pid/skempi2/.

Supplementary information

Supplementary data are available at Bioinformatics online.

von Hippel-Lindau mutants in renal cell carcinoma are regulated by increased expression of RSUME

Renal cell carcinoma (RCC) is the major cause of death among patients with von Hippel-Lindau (VHL) disease. Resistance to therapies targeting tumor angiogenesis opens the question about the underlying mechanisms. Previously we have described that RWDD3 or RSUME (RWD domain-containing protein SUMO Enhancer) sumoylates and binds VHL protein and negatively regulates HIF degradation, leading to xenograft RCC tumor growth in mice. In this study, we performed a bioinformatics analysis in a ccRCC dataset showing an association of RSUME levels with VHL mutations and tumor progression, and we demonstrate the molecular mechanism by which RSUME regulates the pathologic angiogenic phenotype of VHL missense mutations. We report that VHL mutants fail to downregulate RSUME protein levels accounting for the increased RSUME expression found in RCC tumors. Furthermore, we prove that targeting RSUME in RCC cell line clones carrying missense VHL mutants results in decreased early tumor angiogenesis. The mechanism we describe is that RSUME sumoylates VHL mutants and beyond its sumoylation capacity, interacts with Type 2 VHL mutants, reduces HIF-2α-VHL mutants binding, and negatively regulates the assembly of the Type 2 VHL, Elongins and Cullins (ECV) complex. Altogether these results show RSUME involvement in VHL mutants deregulation that leads to the angiogenic phenotype of RCC tumors.

Single-cell genetic analysis validates cytopathological identification of circulating cancer cells in patients with clear cell renal cell carcinoma

CONTEXT

Circulating Rare Cells (CRC) are non-haematological cells circulating in blood. They include Circulating Cancer Cells (CCC) and cells with uncertain malignant features (CRC-UMF) according to cytomorphology. Clear cell renal cell carcinomas frequently bear a mutated Von Hippel-Lindau (VHL) gene.

AIM

To match blind genetic analysis of CRC and tumor samples with CRC cytopathological diagnosis.

RESULTS

29/30 patients harboured CRC (20 harboured CCC, 29 CRC-UMF) and 25/29 patients carried VHL mutations in their tumour. 205 single CRC (64 CCC, 141 CRC-UMF) provided genetic data. 57/57 CCC and 104/125 CRC-UMF from the 25 patients with VHL-mutated tumor carried the same VHL mutation detected in the tumor. Seven CCC and 16 CRC-UMF did not carry VHL mutations but were found in patients with wild-type VHL tumor tissue.

CONCLUSIONS

All the CCC and 83,2% (104/125) of the CRC-UMF were found to carry the same VHL mutation identified in the corresponding tumorous tissue, validating cytopathological identification of CCC in patients with clear cell renal cell carcinoma.

METHODS

The blood of 30 patients with clear cell renal cell carcinoma was treated by ISET® for CRC isolation, cytopathology and single-cell VHL mutations analysis, performed blindly and compared to VHL mutations of corresponding tumor tissues and leukocytes.

Von Hippel-Lindau and Hereditary Pheochromocytoma/Paraganglioma Syndromes: Clinical Features, Genetics, and Surveillance Recommendations in Childhood

Von Hippel-Lindau disease (vHL) is a hereditary tumor predisposition syndrome that places affected individuals at risk for multiple tumors, which are predominantly benign and generally occur in the central nervous system or abdomen. Although the majority of tumors occur in adults, children and adolescents with the condition develop a significant proportion of vHL manifestations and are vulnerable to delayed tumor detection and their sequelae. Although multiple tumor screening paradigms are currently being utilized for patients with vHL, surveillance should be reassessed as the available relevant clinical information continues to expand. We propose a new vHL screening paradigm similar to existing approaches, with important modifications for some tumor types, placing an emphasis on risks in childhood. This includes advancement in the timing of surveillance initiation and increased frequency of screening evaluations. Another neuroendocrine-related familial condition is the rapidly expanding hereditary paraganglioma and pheochromocytoma syndrome (HPP). The tumor spectrum for patients with HPP syndrome includes paragangliomas, pheochromocytomas, renal cancer, and gastrointestinal stromal tumors. The majority of patients with HPP syndrome harbor an underlying variant in one of the SHDx genes (SDHA, SDHB, SDHC, SDHD, SDHA, and SDHAF2), although other genes also have been described (MAX and TMEM127). Annual screening for elevated plasma or urine markers along with complete blood count and biennial whole-body MRI accompanied by focal neck MRI is recommended for older children and adults with HPP syndrome to detect tumors early and to decrease morbidity and mortality from HPP-related tumors. Clin Cancer Res; 23(12); e68-e75. ©2017 AACRSee all articles in the online-only CCR Pediatric Oncology Series.

Atlas on substrate recognition subunits of CRL2 E3 ligases

The Cullin2-type ubiquitin ligases belong to the Cullin-Ring Ligase (CRL) family, which is a crucial determinant of proteasome-based degradation processes in eukaryotes. Because of the finding of von Hippel-Lindau tumor suppressor (VHL), the Cullin2-type ubiquitin ligases gain focusing in the research of many diseases, especially in tumors. These multisubunit enzymes are composed of the Ring finger protein, the Cullin2 scaffold protein, the Elongin B&C linker protein and the variant substrate recognition subunits (SRSs), among which the Cullin2 scaffold protein is the determining factor of the enzyme mechanism. Substrate recognition of Cullin2-type ubiquitin ligases depends on SRSs and results in the degradation of diseases associated substrates by intracellular signaling events. This review focuses on the diversity and the multifunctionality of SRSs in the Cullin2-type ubiquitin ligases, including VHL, LRR-1, FEM1b, PRAME and ZYG11. Recently, as more SRSs are being discovered and more aspects of substrate recognition have been illuminated, insight into the relationship between Cul2-dependent SRSs and substrates provides a new area for cancer research.

Specific Localization of Missense Mutations in the VHL Gene in Clear Cell Renal Cell Carcinoma

Missense mutations in the VHL gene during sporadic clear cell renal cell carcinoma were studied to evaluate their localization in relation to functionally important motifs of the VHL protein. Somatic mutations were identified in 124 of 307 samples. All missense mutations in the α-domain were localized in the binding site for elongin C. Substitutions in the β-domain (77%) were found in the HIF-binding site. Five missense mutations were absent in these sites, which illustrates their role in VHL protein formation or suppressor function of other protein cofactors. Mutation c.392A→T (p.N131I) was identified for the first time. Our results hold much promise to estimate the boundaries of functionally important sites in the VHL suppressor gene and contribute to the interpretation of a pathogenic role of mutations in direct DNA diagnostics.

Combating mutations in genetic disease and drug resistance: understanding molecular mechanisms to guide drug design

INTRODUCTION

Mutations introduce diversity into genomes, leading to selective changes and driving evolution. These changes have contributed to the emergence of many of the current major health concerns of the 21st century, from the development of genetic diseases and cancers to the rise and spread of drug resistance. The experimental systematic testing of all mutations in a system of interest is impractical and not cost-effective, which has created interest in the development of computational tools to understand the molecular consequences of mutations to aid and guide rational experimentation. Areas covered: Here, the authors discuss the recent development of computational methods to understand the effects of coding mutations to protein function and interactions, particularly in the context of the 3D structure of the protein. Expert opinion: While significant progress has been made in terms of innovative tools to understand and quantify the different range of effects in which a mutation or a set of mutations can give rise to a phenotype, a great gap still exists when integrating these predictions and drawing causality conclusions linking variants. This often requires a detailed understanding of the system being perturbed. However, as part of the drug development process it can be used preemptively in a similar fashion to pharmacokinetics predictions, to guide development of therapeutics to help guide the design and analysis of clinical trials, patient treatment and public health policy strategies.

Management of Gene Variants of Unknown Significance: Analysis Method and Risk Assessment of the VHL Mutation p.P81S (c.241C>T)

BACKGROUND

Evaluation of the pathogenicity of a gene variant of unknown significance (VUS) is crucial for molecular diagnosis and genetic counseling, but can be challenging. This is especially so in phenotypically variable diseases, such as von Hippel-Lindau disease (vHL). vHL is caused by germline mutations in the VHL gene, which predispose to the development of multiple tumors such as central nervous system hemangioblastomas and renal cell carcinoma (RCC).

OBJECTIVE

We propose a method for the evaluation of VUS pathogenicity through our experience with the VHL missense mutation c.241C>T (p.P81S).

METHOD

1) Clinical evaluation of known variant carriers: We evaluated a family of five VHL p.P81S carriers, as well as the clinical characteristics of all the p.P81S carriers reported in the literature; 2) Evaluation of tumor tissue via genetic analysis, histology, and immunohistochemistry (IHC); 3) Assessment of the variant's impact on protein structure and function, using multiple databases, in silico algorithms, and reports of functional studies.

RESULTS

Only one family member had clinical signs of vHL with early-onset RCC. IHC analysis showed no VHL protein expressed in the tumor, consistent with biallelic VHL inactivation. The majority of in silico algorithms reported p.P81S as possibly pathogenic in relation to vHL or RCC, but there were discrepancies. Functional studies suggest that p.P81S impairs the VHL protein's function.

CONCLUSION

The VHL p.P81S mutation is most likely a low-penetrant pathogenic variant predisposing to RCC development. We suggest the above-mentioned method for VUS evaluation with use of different methods, especially a variety of in silico methods and tumor tissue analysis.

Characterization of VHL missense mutations in sporadic clear cell renal cell carcinoma: hotspots, affected binding domains, functional impact on pVHL and therapeutic relevance

BACKGROUND

The VHL protein (pVHL) is a multiadaptor protein that interacts with more than 30 different binding partners involved in many oncogenic processes. About 70 % of clear cell renal cell carcinoma (ccRCC) have VHL mutations with varying impact on pVHL function. Loss of pVHL function leads to the accumulation of Hypoxia Inducible Factor (HIF), which is targeted by current targeted treatments. In contrast to nonsense and frameshift mutations that highly likely nullify pVHL multipurpose functions, missense mutations may rather specifically influence the binding capability of pVHL to its partners. The affected pathways may offer predictive clues to therapy and response to treatment. In this study we focused on the VHL missense mutation pattern in ccRCC, and studied their potential effects on pVHL protein stability and binding partners and discussed treatment options.

METHODS

We sequenced VHL in 360 sporadic ccRCC FFPE samples and compared observed and expected frequency of missense mutations in 32 different binding domains. The prediction of the impact of those mutations on protein stability and function was assessed in silico. The response to HIF-related, anti-angiogenic treatment of 30 patients with known VHL mutation status was also investigated.

RESULTS

We identified 254 VHL mutations (68.3 % of the cases) including 89 missense mutations (35 %). Codons Ser65, Asn78, Ser80, Trp117 and Leu184 represented hotspots and missense mutations in Trp117 and Leu 184 were predicted to highly destabilize pVHL. About 40 % of VHL missense mutations were predicted to cause severe protein malfunction. The pVHL binding domains for HIF1AN, BCL2L11, HIF1/2α, RPB1, PRKCZ, aPKC-λ/ι, EEF1A1, CCT-ζ-2, and Cullin2 were preferentially affected. These binding partners are mainly acting in transcriptional regulation, apoptosis and ubiquitin ligation. There was no correlation between VHL mutation status and response to treatment.

CONCLUSIONS

VHL missense mutations may exert mild, moderate or strong impact on pVHL stability. Besides the HIF binding domain, other pVHL binding sites seem to be non-randomly altered by missense mutations. In contrast to LOF mutations that affect all the different pathways normally controlled by pVHL, missense mutations may be rather appropriate for designing tailor-made treatment strategies for ccRCC.

Germline mutations in the VHL gene associated with 3 different renal lesions in a Chinese von Hippel-Lindau disease family

Von Hippel-Lindau (VHL) disease is a rare autosomal dominant inherited cancer syndrome that is characterized by hemangioblastomas in the central nervous system and retina, renal cell carcinoma and cysts, pancreatic tumors and cysts, and pheochromocytoma. The underlying gene in this disease is the VHL tumor suppressor gene. We characterized a family with 2 affected siblings. The brother and sister displayed VHL type 2B and type 2A features, respectively. Renal lesions in the brother exhibited 3 different phenotypes, including simple renal cysts, multilocular cystic renal cell carcinoma and clear cell renal cell carcinoma. The phenotypes of the 3 concurrent renal lesions were first reported in this study. Mutation detection of the VHL gene revealed 2 recurrent mutations, namely c.256C>T (p.P86S) and c.340 + 5G > C. The former was predicted to be deleterious and to destabilize the hydrophobic core and lead to VHL dysfunction; however, the latter was predicted to be a benign variant. Our findings provided new data for the genotype-phenotype of VHL diseases and elucidated the pathogenic mechanism with in silico analysis.

In silico functional dissection of saturation mutagenesis: Interpreting the relationship between phenotypes and changes in protein stability, interactions and activity

Despite interest in associating polymorphisms with clinical or experimental phenotypes, functional interpretation of mutation data has lagged behind generation of data from modern high-throughput techniques and the accurate prediction of the molecular impact of a mutation remains a non-trivial task. We present here an integrated knowledge-driven computational workflow designed to evaluate the effects of experimental and disease missense mutations on protein structure and interactions. We exemplify its application with analyses of saturation mutagenesis of DBR1 and Gal4 and show that the experimental phenotypes for over 80% of the mutations correlate well with predicted effects of mutations on protein stability and RNA binding affinity. We also show that analysis of mutations in VHL using our workflow provides valuable insights into the effects of mutations, and their links to the risk of developing renal carcinoma. Taken together the analyses of the three examples demonstrate that structural bioinformatics tools, when applied in a systematic, integrated way, can rapidly analyse a given system to provide a powerful approach for predicting structural and functional effects of thousands of mutations in order to reveal molecular mechanisms leading to a phenotype. Missense or non-synonymous mutations are nucleotide substitutions that alter the amino acid sequence of a protein. Their effects can range from modifying transcription, translation, processing and splicing, localization, changing stability of the protein, altering its dynamics or interactions with other proteins, nucleic acids and ligands, including small molecules and metal ions. The advent of high-throughput techniques including sequencing and saturation mutagenesis has provided large amounts of phenotypic data linked to mutations. However, one of the hurdles has been understanding and quantifying the effects of a particular mutation, and how they translate into a given phenotype. One approach to overcome this is to use robust, accurate and scalable computational methods to understand and correlate structural effects of mutations with disease.

Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants

Protein stability is the free energy difference between unfolded and folded states of a protein, which lies in the range of 5-25 kcal/mol. Experimentally, protein stability is measured with circular dichroism, differential scanning calorimetry, and fluorescence spectroscopy using thermal and denaturant denaturation methods. These experimental data have been accumulated in the form of a database, ProTherm, thermodynamic database for proteins and mutants. It also contains sequence and structure information of a protein, experimental methods and conditions, and literature information. Different features such as search, display, and sorting options and visualization tools have been incorporated in the database. ProTherm is a valuable resource for understanding/predicting the stability of proteins and it can be accessed at http://www.abren.net/protherm/ . ProTherm has been effectively used to examine the relationship among thermodynamics, structure, and function of proteins. We describe the recent progress on the development of methods for understanding/predicting protein stability, such as (1) general trends on mutational effects on stability, (2) relationship between the stability of protein mutants and amino acid properties, (3) applications of protein three-dimensional structures for predicting their stability upon point mutations, (4) prediction of protein stability upon single mutations from amino acid sequence, and (5) prediction methods for addressing double mutants. A list of online resources for predicting has also been provided.