Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences.
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ABSTRACT:
SUBMITTER: Kumar S
PROVIDER: S-EPMC7210002 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
Publications
Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences.
Kumar Sushant S Warrell Jonathan J Li Shantao S McGillivray Patrick D PD Meyerson William W Salichos Leonidas L Harmanci Arif A Martinez-Fundichely Alexander A Chan Calvin W Y CWY Nielsen Morten Muhlig MM Lochovsky Lucas L Zhang Yan Y Li Xiaotong X Lou Shaoke S Pedersen Jakob Skou JS Herrmann Carl C Getz Gad G Khurana Ekta E Gerstein Mark B MB
Cell 20200220 5
The dichotomous model of "drivers" and "passengers" in cancer posits that only a few mutations in a tumor strongly affect its progression, with the remaining ones being inconsequential. Here, we leveraged the comprehensive variant dataset from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project to demonstrate that-in addition to the dichotomy of high- and low-impact variants-there is a third group of medium-impact putative passengers. Moreover, we also found that molecular impact ...[more]
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Project description:Cancer progression is driven by the accumulation of a small number of genetic alterations. However, these few driver alterations reside in a cancer genome alongside tens of thousands of additional mutations termed passengers. Passengers are widely believed to have no role in cancer, yet many passengers fall within protein-coding genes and other functional elements that can have potentially deleterious effects on cancer cells. Here we investigate the potential of moderately deleterious passengers to accumulate and alter the course of neoplastic progression. Our approach combines evolutionary simulations of cancer progression with an analysis of cancer sequencing data. From simulations, we find that passengers accumulate and largely evade natural selection during progression. Although individually weak, the collective burden of passengers alters the course of progression, leading to several oncological phenomena that are hard to explain with a traditional driver-centric view. We then tested the predictions of our model using cancer genomics data and confirmed that many passengers are likely damaging and have largely evaded negative selection. Finally, we use our model to explore cancer treatments that exploit the load of passengers by either (i) increasing the mutation rate or (ii) exacerbating their deleterious effects. Though both approaches lead to cancer regression, the latter is a more effective therapy. Our results suggest a unique framework for understanding cancer progression as a balance of driver and passenger mutations.
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Project description:Variant interpretation remains a central challenge for precision medicine. Missense variants are particularly difficult to understand as they change only a single amino acid in a protein sequence yet can have large and varied effects on protein activity. Numerous tools have been developed to identify missense variants with putative disease consequences from protein sequence and structure. However, biological function arises through higher order interactions among proteins and molecules within cells. We therefore sought to capture information about the potential of missense mutations to perturb protein interaction networks by integrating protein structure and interaction data. We developed 16 network-based annotations for missense mutations that provide orthogonal information to features classically used to prioritize variants. We then evaluated them in the context of a proven machine-learning framework for variant effect prediction across multiple benchmark datasets to demonstrate their potential to improve variant classification. Interestingly, network features resulted in larger performance gains for classifying somatic mutations than for germline variants, possibly due to different constraints on what mutations are tolerated at the cellular versus organismal level. Our results suggest that modeling variant potential to perturb context-specific interactome networks is a fruitful strategy to advance in silico variant effect prediction.
| S-EPMC8873243 | biostudies-literature
Project description:BackgroundIn somatic cancer genomes, delineating genuine driver mutations against a background of multiple passenger events is a challenging task. The difficulty of determining function from sequence data and the low frequency of mutations are increasingly hindering the search for novel, less common cancer drivers. The accumulation of extensive amounts of data on somatic point and copy number alterations necessitates the development of systematic methods for driver mutation analysis.ResultsWe introduce a framework for detecting driver mutations via functional network analysis, which is applied to individual genomes and does not require pooling multiple samples. It probabilistically evaluates 1) functional network links between different mutations in the same genome and 2) links between individual mutations and known cancer pathways. In addition, it can employ correlations of mutation patterns in pairs of genes. The method was used to analyze genomic alterations in two TCGA datasets, one for glioblastoma multiforme and another for ovarian carcinoma, which were generated using different approaches to mutation profiling. The proportions of drivers among the reported de novo point mutations in these cancers were estimated to be 57.8% and 16.8%, respectively. The both sets also included extended chromosomal regions with synchronous duplications or losses of multiple genes. We identified putative copy number driver events within many such segments. Finally, we summarized seemingly disparate mutations and discovered a functional network of collagen modifications in the glioblastoma. In order to select the most efficient network for use with this method, we used a novel, ROC curve-based procedure for benchmarking different network versions by their ability to recover pathway membership.ConclusionsThe results of our network-based procedure were in good agreement with published gold standard sets of cancer genes and were shown to complement and expand frequency-based driver analyses. On the other hand, three sequence-based methods applied to the same data yielded poor agreement with each other and with our results. We review the difference in driver proportions discovered by different sequencing approaches and discuss the functional roles of novel driver mutations. The software used in this work and the global network of functional couplings are publicly available at http://research.scilifelab.se/andrej_alexeyenko/downloads.html.
| S-EPMC4262241 | biostudies-literature
Project description:PRODH maps to 22q11 in the region deleted in the velocardiofacial syndrome/DiGeorge syndrome (VCFS/DGS) and encodes proline oxidase (POX), a mitochondrial inner-membrane enzyme that catalyzes the first step in the proline degradation pathway. At least 16 PRODH missense mutations have been identified in studies of type I hyperprolinemia (HPI) and schizophrenia, 10 of which are present at polymorphic frequencies. The functional consequences of these missense mutations have been inferred by evolutionary conservation, but none have been tested directly. Here, we report the effects of these mutations on POX activity. We find that four alleles (R185Q, L289M, A455S, and A472T) result in mild (<30%), six (Q19P, A167V, R185W, D426N, V427M, and R431H) in moderate (30%-70%), and five (P406L, L441P, R453C, T466M, and Q521E) in severe (>70%) reduction in POX activity, whereas one (Q521R) increases POX activity. The POX encoded by one severe allele (T466M) shows in vitro responsiveness to high cofactor (flavin adenine dinucleotide) concentrations. Although there is limited information on plasma proline levels in individuals of known PRODH genotype, extant data suggest that severe hyperprolinemia (>800 microM) occurs in individuals with large deletions and/or PRODH missense mutations with the most-severe effect on function (L441P and R453C), whereas modest hyperprolinemia (300-500 microM) is associated with PRODH alleles with a moderate reduction in activity. Interestingly, three of the four alleles associated with or found in schizophrenia (V427M, L441P, and R453C) resulted in severe reduction of POX activity and hyperprolinemia. These observations plus the high degree of polymorphism at the PRODH locus are consistent with the hypothesis that reduction in POX function is a risk factor for schizophrenia.
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Project description:Smad4 is an essential signal transducer of the transforming growth factor beta (TGF-beta) signalling pathway and has been identified as a tumour suppressor, being mutated in approx. 50% of pancreatic cancers and approx. 15% of colorectal cancers. Two missense mutations in the C-terminal domain of Smad4, D351H (Asp351-->His) and D537Y (Asp537-->Tyr), have been described recently in the human colorectal cancer cell lines CACO-2 and SW948 respectively [Woodford-Richens, Rowan, Gorman, Halford, Bicknell, Wasan, Roylance, Bodmer and Tomlinson (2001) Proc. Natl. Acad. Sci. U.S.A. 98, 9719-9723]. Previous work in vitro suggested that only Asp-351 was required for interaction with Smad2 [Wu, Fairman, Penry and Shi (2001) J. Biol. Chem. 276, 20688-20694]. In the present study, we investigate the functional consequences of these point mutations in vivo. We demonstrate that neither of these colorectal cancer cells undergo growth arrest in response to TGF-beta, which can be explained, at least in part, by their inability to up-regulate cyclin-dependent kinase inhibitors p21 (CIP1 ) or p15 ( INK4b) after TGF-beta stimulation. Although the point-mutated Smad4s are expressed at normal levels in these colorectal cancer cells, they cannot interact with either TGF-beta-induced phosphorylated Smad2 or Smad3. As a result, these Smad4 mutants do not accumulate in the nucleus after TGF-beta stimulation, are not recruited to DNA by relevant Smad-binding transcription factors and cannot generate transcriptionally active DNA-bound complexes. Therefore both these colorectal tumour cells completely lack functional Smad4 activity owing to the missense mutations. Given the location of these mutations in the three-dimensional structure of the Smad4 C-terminal domain, the results also give us significant insights into Smad complex formation.
| S-EPMC1224058 | biostudies-other
Project description:The objective of this work was to investigate the role of acidic residues within the exposed middle segment of the central helix of cTnC in (1) cTnC-cTnI interactions, (2) Ca(2+) binding and exchange with the regulatory N-domain of cTnC in increasingly complex biochemical systems, and (3) ability of the cTn complex to regulate actomyosin ATPase. In order to achieve this objective, we introduced the D87A/D88A and E94A/E95A/E96A mutations into the central helix of cTnC. The D87A/D88A and E94A/E95A/E96A mutations decreased affinity of cTnC for the regulatory region of cTnI. The Ca(2+) sensitivity of the regulatory N-domain of isolated cTnC was decreased by the D87A/D88A, but not E94A/E95A/E96A mutation. However, both the D87A/D88A and E94A/E95A/E96A mutations desensitized the cTn complex and reconstituted thin filaments to Ca(2+). Decreases in the Ca(2+) sensitivity of the cTn complex and reconstituted thin filaments were, at least in part, due to faster rates of Ca(2+) dissociation. In addition, the D87A/D88A and E94A/E95A/E96A mutations desensitized actomyosin ATPase to Ca(2+), and decreased maximal actomyosin ATPase activity. Thus, our results indicate that conserved acidic residues within the exposed middle segment of the central helix of cTnC are important for the proper regulatory function of the cTn complex.
| S-EPMC4026335 | biostudies-literature
Project description:Current statistical models for assessing hotspot significance do not properly account for variation in site-specific mutability, thereby yielding many false-positives. We thus (i) detail a Log-normal-Poisson (LNP) background model that accounts for this variability in a manner consistent with models of mutagenesis; (ii) use it to show that passenger hotspots arise from all common mutational processes; and (iii) apply it to a ?10,000-patient cohort to nominate driver hotspots with far fewer false-positives compared with conventional methods. Overall, we show that many cancer hotspot mutations recurring at the same genomic site across multiple tumors are actually passenger events, recurring at inherently mutable genomic sites under no positive selection.
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Project description:Metachromatic leukodystrophy is a lysosomal storage disorder caused by the deficiency of arylsulphatase A. We describe the functional consequences of three mis-sense mutations in the arylsulphatase A gene (Asp-335-Val, Arg-370-Trp and Arg-370-Gln), affecting an apparent intramolecular Asp-335 to Arg-370 salt bridge, and interpret the effects and clinical consequences on the basis of the three-dimensional structure of arylsulphatase A. Asp-335-Val and Arg-370-Trp substitutions each cause a complete loss of enzyme activity and are associated with the most severe form of the human disease, whereas the Arg-370-Gln-substituted enzyme retains some residual activity, being found in a patient suffering from the milder juvenile form of the disease. Detailed analysis reveals that formation of the apparent salt bridge depends critically on the presence of aspartic acid and arginine residues at positions 335 and 370, respectively. Substitution by various other amino acids, including glutamic acid and lysine, affects enzyme function severely. Biosynthesis and immunoprecipitation studies indicate that the Asp-335-Val substitution affects folding of arylsulphatase A more severely than either the Arg-370-Trp or Arg-370-Gln substitutions. In vitro mutagenesis data show that clinical severity correlates with the space occupied by residue 370. The combination with structural data suggests that the bulky tryptophan residue broadens the cleft held together by the apparent salt bridge, whereas the smaller glutamine residue still allows the cleft to close, yielding a less severely affected enzyme. The position of residue 370 in the three-dimensional structure of the enzyme provides a plausible explanation for the differing severities in loss of enzyme function caused by the mutations and thus the clinical phenotype.
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Project description:PurposeBestrophin-1 gene (BEST1) mutations are responsible for a broad spectrum of human retinal phenotypes, jointly called bestrophinopathies. Canine multifocal retinopathy (cmr), caused by mutations in the dog gene ortholog, shares numerous phenotypic features with human BEST1-associated disorders. The purpose of this study was the assessment of molecular consequences and pathogenic outcomes of the cmr1 (C(73)T/R(25)X) premature termination and the cmr2 (G(482)A/G(161)D) missense mutation of the canine model compared with the C(87)G/Y(29)X mutation observed in human patients.MethodsDogs carrying the BEST1 mutation were introduced into a breeding colony and used to produce either carrier or affected offspring. Eyes were collected immediately after euthanatization at the disease-relevant ages and were harvested for expression studies. In parallel, an in vitro cell culture model system was developed and compared with in vivoResultsResultsThe results demonstrate that cmr1 and human C(87)G-mutated transcripts bypass the nonsense-mediated mRNA decay machinery, suggesting the AUG proximity effect as an underlying transcriptional mechanism. The truncated protein, however, is not detectable in either species. The in vitro model accurately recapitulates transcriptional and translational expression events observed in vivo and, thus, implies loss of bestrophin-1 function in cmr1-dogs and Y(29)X-affected patients. Immunofluorescence microscopy of cmr2 mutant showed mislocalization of the protein.ConclusionsMolecular evaluation of cmr mutations in vivo and in vitro constitutes the next step toward elucidating genotype-phenotype interactions concerning human bestrophinopathies and emphasizes the importance of the canine models for studying the complexity of the BEST1 disease mechanism.
| S-EPMC3175949 | biostudies-literature
Project description:Determining the cancer type and molecular subtype has important clinical implications. The primary site is however unknown for some malignancies discovered in the metastatic stage. Moreover liquid biopsies may be used to screen for tumoral DNA, which upon detection needs to be assigned to a site-of-origin. Classifiers based on genomic features are a promising approach to prioritize the tumor anatomical site, type and subtype. We examined the predictive ability of causal (driver) somatic mutations in this task, comparing it against global patterns of non-selected (passenger) mutations, including features based on regional mutation density (RMD). In the task of distinguishing 18 cancer types, the driver mutations-mutated oncogenes or tumor suppressors, pathways and hotspots-classified 36% of the patients to the correct cancer type. In contrast, the features based on passenger mutations did so at 92% accuracy, with similar contribution from the RMD and the trinucleotide mutation spectra. The RMD and the spectra covered distinct sets of patients with predictions. In particular, introducing the RMD features into a combined classification model increased the fraction of diagnosed patients by 50 percentage points (at 20% FDR). Furthermore, RMD was able to discriminate molecular subtypes and/or anatomical site of six major cancers. The advantage of passenger mutations was upheld under high rates of false negative mutation calls and with exome sequencing, even though overall accuracy decreased. We suggest whole genome sequencing is valuable for classifying tumors because it captures global patterns emanating from mutational processes, which are informative of the underlying tumor biology.
| S-EPMC6483366 | biostudies-literature