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

Abstract

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.

The pVHL neglected functions, a tale of hypoxia-dependent and -independent regulations in cancer

“…Kidney-specific pVHL inactivation causes the development of kidney cysts in a mouse model [ 28 ], while reintroduction of a wild-type gene interrupts malignant progression [ 29 ]. Nevertheless, pVHL somatic inactivation is calculated to affect about 75% of sporadic clear cell renal cell carcinomas (ccRCC) [ 30 , 31 ], while a number of studies suggests a role for pVHL in the regulation of the cellular tumour antigen p53 (p53) [ 32 – 34 ].…”

von Hippel-Lindau Disease: an Update

“…The prototypic VHL disease type 2A (p.Tyr98His) and type 2B (p.Arg167Trp/p.Arg167GLn) mutations (see Table 2) disrupt respectively the HIF-1α/β-domain and the elongin C/α-domain binding sites. In a recent study, Minervini et al [51] used computational modelling to propose that five different interfaces of pVHL can be delineated and, using published data from 360 VHL mutations and 59 proposed pVHL interactors, they attempted to correlate the phenotypic effects of VHL missense variants with their effect on the various interactors. These findings will provide a framework for functional studies aimed at determining the molecular basis for the complex genotype-phenotype correlations observed in VHL disease and VHL-related polycythaemia disorders.…”

Large scale analyses of genotype-phenotype relationships of glycine decarboxylase mutations and neurological disease severity

“…CUPSAT uses protein structure to make fast and accurate ΔΔG predictions from 494 environment-specific atomic and torsion angle potentials. The high speed of CUPSAT predictions 495 lends itself to analyses of diseases associated with a large number of missense mutations [43]. 496…”