Analysis and Interpretation of the Impact of Missense Variants in Cancer.
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ABSTRACT:
SUBMITTER: Petrosino M
PROVIDER: S-EPMC8196604 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Objective: We aimed to improve the classification of SCN1A missense variants in patients with Dravet syndrome (DS) by combining and modifying the current variants classification criteria to minimize inconclusive test results. Methods: We established a score classification workflow based on evidence of pathogenicity to adapt the classification of DS-related SCN1A missense variants. In addition, we compiled the variants reported in the literature and our cohort and assessed the proposed pathogenic classification criteria. We combined information regarding previously established pathogenic amino acid changes, mode of inheritance, population-specific allele frequencies, localization within protein domains, and deleterious effect prediction analysis. Results: Our meta-analysis showed that 46% (506/1,101) of DS-associated SCN1A variants are missense. We applied the score classification workflow and 56.5% (286/506) of the variants had their classification changed from VUS: 17.8% (90/506) into "pathogenic" and 38.7% (196/506) as "likely pathogenic." Conclusion: Our results indicate that using multimodal analysis seems to be the best approach to interpret the pathogenic impact of SCN1A missense changes for the molecular diagnosis of patients with DS. By applying the proposed workflow, most DS related SCN1A variants had their classification improved.
| S-EPMC6455056 | biostudies-literature
Project description:BackgroundImproving the clinical interpretation of missense variants can increase the diagnostic yield of genomic testing and lead to personalised management strategies. Currently, due to the imprecision of bioinformatic tools that aim to predict variant pathogenicity, their role in clinical guidelines remains limited. There is a clear need for more accurate prediction algorithms and this study aims to improve performance by harnessing structural biology insights. The focus of this work is missense variants in a subset of genes associated with X linked disorders.MethodsWe have developed a protein-specific variant interpreter (ProSper) that combines genetic and protein structural data. This algorithm predicts missense variant pathogenicity by applying machine learning approaches to the sequence and structural characteristics of variants.ResultsProSper outperformed seven previously described tools, including meta-predictors, in correctly evaluating whether or not variants are pathogenic; this was the case for 11 of the 21 genes associated with X linked disorders that met the inclusion criteria for this study. We also determined gene-specific pathogenicity thresholds that improved the performance of VEST4, REVEL and ClinPred, the three best-performing tools out of the seven that were evaluated; this was the case in 11, 11 and 12 different genes, respectively.ConclusionProSper can form the basis of a molecule-specific prediction tool that can be implemented into diagnostic strategies. It can allow the accurate prioritisation of missense variants associated with X linked disorders, aiding precise and timely diagnosis. In addition, we demonstrate that gene-specific pathogenicity thresholds for a range of missense prioritisation tools can lead to an increase in prediction accuracy.
| S-EPMC8961765 | biostudies-literature
Project description:AimThe study aimed to develop a scalable dual-fluorescence assay in cells to enable the functional interpretation of HNF-4α missense variants identified in exome sequencing, which can be used to guide clinical diagnosis.MethodsUsing mOrange2 and GFP fluorescence proteins to track the expression of HNF-4α (HNF-4α-mOrange2) and reporter activity under the control of the HNF-1α promoter (pHNF1A-GFP), respectively, we designed a dual-fluorescence assay to evaluate the expression level, cellular localization, and transcriptional function of HNF-4α simultaneously in live cells. To assess the scalable characteristic of the assay, a small library containing five previously reported mutations and wild-type HNF-4α was constructed. Cells infected with this library were sorted into different populations through fluorescence-activated cell sorting (FACS) according to the transcription activity and expression abundance. Cloning and Sanger sequencing were used to detect the mutations of the different groups. High content screening (HCS) assay was used for the validation of individual mutants in the function and expression point of view.ResultsHNF-4α-mOrange2 exhibited nuclear localization and transactivation capability on the HNF-1α promoter as physical HNF-4α does. The expression of HNF-4α-mOrange2 shows a 6-fold induction of GFP expression compared to the control without HNF-4α-mOrange2, which was significantly abolished by the known loss-of-function mutant M373R. The different performances of wild-type and mutant M373R made them distinguishable in the FACS system, empowering the scalable capability of this assay for classifying large numbers of variants combining functional stratification and sequencing. Further application of the assay in the small library showed that three cell populations were seen grouped as Normal (same transactivation as wild type), Reducedexp_nor (reduced transactivation with normal or higher expression), and Reducedexp_low (reduced transactivation with lower expression). Subsequently, Sanger sequencing showed that wild-type HNF-4α was in the Normal group, two mutations (M373R and G79C) were enriched in the Reducedexp_nor group, and three mutations (C115S, L272P, and F83C) belonged to the Reducedexp_low group. These results were validated by further imaging data using HCS assay for individual mutation.ConclusionsOur study proposes a scalable and informative approach for the characterization of the variants in HNF-4α genes in a quantitative and high-throughput manner.
| S-EPMC8883583 | biostudies-literature
Project description:Background: With the advent of next-generation sequencing in genetic testing, predicting the pathogenicity of missense variants represents a major challenge potentially leading to misdiagnoses in the clinical setting. In neurofibromatosis type 1 (NF1), where clinical criteria for diagnosis may not be fully present until late infancy, correct assessment of variant pathogenicity is fundamental for appropriate patients' management. Methods: Here, we analyzed three different computational methods, VEST3, REVEL and ClinPred, and after extracting predictions scores for 1585 NF1 missense variants listed in ClinVar, evaluated their performances and the score distribution throughout the neurofibromin protein. Results: For all the three methods, no significant differences were present between the scores of "likely benign", "benign", and "likely pathogenic", "pathogenic" variants that were consequently collapsed into a single category. The cutoff values for pathogenicity were significantly different for the three methods and among benign and pathogenic variants for all methods. After training five different models with a subset of benign and pathogenic variants, we could reclassify variants in three sharply separated categories. Conclusions: The recently developed metapredictors, which integrate information from multiple components, after gene-specific fine-tuning, could represent useful tools for variant interpretation, particularly in genetic diseases where a clinical diagnosis can be difficult.
| S-EPMC7037781 | biostudies-literature
Project description:Missense DNA variants have variable effects upon protein function. Consequently, interpreting their pathogenicity is challenging, especially when they are associated with disease variability. To determine the degree to which functional assays inform interpretation, we analyzed 48 CFTR missense variants associated with variable expressivity of cystic fibrosis (CF). We assessed function in a native isogenic context by evaluating CFTR mutants that were stably expressed in the genome of a human airway cell line devoid of endogenous CFTR expression. 21 of 29 variants associated with full expressivity of the CF phenotype generated <10% wild-type CFTR (WT-CFTR) function, a conservative threshold for the development of life-limiting CF lung disease, and five variants had moderately decreased function (10% to ∼25% WT-CFTR). The remaining three variants in this group unexpectedly had >25% WT-CFTR function; two were higher than 75% WT-CFTR. As expected, 14 of 19 variants associated with partial expressivity of CF had >25% WT-CFTR function; however, four had minimal to no effect on CFTR function (>75% WT-CFTR). Thus, 6 of 48 (13%) missense variants believed to be disease causing did not alter CFTR function. Functional studies substantially refined pathogenicity assignment with expert annotation and criteria from the American College of Medical Genetics and Genomics and Association for Molecular Pathology. However, four algorithms (CADD, REVEL, SIFT, and PolyPhen-2) could not differentiate between variants that caused severe, moderate, or minimal reduction in function. In the setting of variable expressivity, these results indicate that functional assays are essential for accurate interpretation of missense variants and that current prediction tools should be used with caution.
| S-EPMC5992123 | biostudies-literature
Project description:Clinical genetic testing readily detects germline genetic variants. Yet, the rarity of individual variants limits the evidence available for variant classification, leading to many variants of uncertain significance (VUS). VUS cannot guide clinical decisions, complicating counseling and management. In hereditary breast cancer gene PALB2, approximately 50% of clinically identified germline variants are VUS and approximately 90% of VUS are missense. Truncating PALB2 variants have homologous recombination (HR) defects and rely on error-prone nonhomologous end-joining for DNA damage repair (DDR). Recent reports show that some missense PALB2 variants may also be damaging, but most functional studies have lacked benchmarking controls required for sufficient predictive power for clinical use. Here, variant-level DDR capacity in hereditary breast cancer genes was assessed using the Traffic Light Reporter (TLR) to quantify cellular HR/nonhomologous end-joining with fluorescent markers. First, using BRCA2 missense variants of known significance as benchmarks, the TLR distinguished between normal/abnormal HR function. The TLR was then validated for PALB2 and used to test 37 PALB2 variants. Based on the TLR's ability to correctly classify PALB2 validation controls, these functional data where applied in subsequent germline variant interpretations at a moderate level of evidence toward a pathogenic interpretation (PS3_moderate) for 8 variants with abnormal DDR, or a supporting level of evidence toward a benign interpretation (BS3_supporting) for 13 variants with normal DDR.
| S-EPMC8491091 | biostudies-literature
Project description:The PAX6 gene encodes a highly-conserved transcription factor involved in eye development. Heterozygous loss-of-function variants in PAX6 can cause a range of ophthalmic disorders including aniridia. A key molecular diagnostic challenge is that many PAX6 missense changes are presently classified as variants of uncertain significance. While computational tools can be used to assess the effect of genetic alterations, the accuracy of their predictions varies. Here, we evaluated and optimised the performance of computational prediction tools in relation to PAX6 missense variants. Through inspection of publicly available resources (including HGMD, ClinVar, LOVD and gnomAD), we identified 241 PAX6 missense variants that were used for model training and evaluation. The performance of ten commonly used computational tools was assessed and a threshold optimization approach was utilized to determine optimal cut-off values. Validation studies were subsequently undertaken using PAX6 variants from a local database. AlphaMissense, SIFT4G and REVEL emerged as the best-performing predictors; the optimized thresholds of these tools were 0.967, 0.025, and 0.772, respectively. Combining the prediction from these top-three tools resulted in lower performance compared to using AlphaMissense alone. Tailoring the use of computational tools by employing optimized thresholds specific to PAX6 can enhance algorithmic performance. Our findings have implications for PAX6 variant interpretation in clinical settings.
| S-EPMC11292026 | biostudies-literature
Project description:Exome sequencing in diabetes presents a diagnostic challenge because depending on frequency, functional impact, and genomic and environmental contexts, HNF1A variants can cause maturity-onset diabetes of the young (MODY), increase type 2 diabetes risk, or be benign. A correct diagnosis matters as it informs on treatment, progression, and family risk. We describe a multi-dimensional functional dataset of 73 HNF1A missense variants identified in exomes of 12,940 individuals. Our aim was to develop an analytical framework for stratifying variants along the HNF1A phenotypic continuum to facilitate diagnostic interpretation. HNF1A variant function was determined by four different molecular assays. Structure of the multi-dimensional dataset was explored using principal component analysis, k-means, and hierarchical clustering. Weights for tissue-specific isoform expression and functional domain were integrated. Functionally annotated variant subgroups were used to re-evaluate genetic diagnoses in national MODY diagnostic registries. HNF1A variants demonstrated a range of behaviors across the assays. The structure of the multi-parametric data was shaped primarily by transactivation. Using unsupervised learning methods, we obtained high-resolution functional clusters of the variants that separated known causal MODY variants from benign and type 2 diabetes risk variants and led to reclassification of 4% and 9% of HNF1A variants identified in the UK and Norway MODY diagnostic registries, respectively. Our proof-of-principle analyses facilitated informative stratification of HNF1A variants along the continuum, allowing improved evaluation of clinical significance, management, and precision medicine in diabetes clinics. Transcriptional activity appears a superior readout supporting pursuit of transactivation-centric experimental designs for high-throughput functional screens.
| S-EPMC7536579 | biostudies-literature
Project description:1 Novel Missense Variants in Patients with Primary Immunodeficiency and Immune dysregulation
| PRJEB46587 | ENA
Project description:BackgroundPathogenic missense variants in the dystrophin (DMD) gene are rarely reported in dystrophinopathies. Most DMD missense variants are of uncertain significance and their pathogenicity interpretation remains complicated. We aimed to investigate whether DMD missense variants would cause aberrant splicing and re-interpret their pathogenicity based on mRNA and protein studies.MethodsNine unrelated patients who had an elevated serum creatine kinase level with or without muscle weakness were enrolled. They underwent a detailed clinical, imaging, and pathological assessment. Routine genetic testing and muscle-derived mRNA and protein studies of dystrophin and sarcoglycan genes were performed in them.ResultsThree of the 9 patients presented with a Duchenne muscular dystrophy (DMD) phenotype and the remaining 6 patients had a suspected diagnosis of Becker muscular dystrophy (BMD) or sarcoglycanopathy based on their clinical and pathological characteristics. Routine genetic testing detected only 9 predicted DMD missense variants in them, of which 6 were novel and interpreted as uncertain significance. Muscle-derived mRNA studies of sarcoglycan genes didn't reveal any aberrant transcripts in them. Dystrophin mRNA studies confirmed that 3 predicted DMD missense variants (c.2380G > C, c.4977C > G, and c.5444A > G) were in fact splicing and frameshift variants due to aberrant splicing. The 9 DMD variants were re-interpreted as pathogenic or likely pathogenic based on mRNA and protein studies. Therefore, 3 patients with DMD splicing variants and 6 patients with confirmed DMD missense variants were diagnosed with DMD and BMD, respectively.ConclusionOur study highlights the importance of muscle biopsy and aberrant splicing for clinical and genetic interpretation of uncertain DMD missense variants.
| S-EPMC10941385 | biostudies-literature