The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing ...potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.
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The ClinGen SVI Splicing Subgroup provides recommendations for the application of existing splicing-related ACMG/AMP codes and re-purposing of other codes to capture splicing-related evidence. This study outlines a process for developing a gene-specific PVS1 decision tree and provides methodology to calibrate bioinformatic splice prediction tools.
A subset of genetic variants found through screening of patients with hereditary breast and ovarian cancer syndrome (HBOC) and Lynch syndrome impact RNA splicing. Through target enrichment of the ...transcriptome, it is possible to perform deep‐sequencing and to identify the different and even rare mRNA isoforms. A targeted RNA‐seq approach was used to analyse the naturally‐occurring splicing events for a panel of 8 breast and/or ovarian cancer susceptibility genes (BRCA1, BRCA2, RAD51C, RAD51D, PTEN, STK11, CDH1, TP53), 3 Lynch syndrome genes (MLH1, MSH2, MSH6) and the fanconi anaemia SLX4 gene, in which monoallelic mutations were found in non‐BRCA families. For BRCA1, BRCA2, RAD51C and RAD51D the results were validated by capillary electrophoresis and were compared to a non‐targeted RNA‐seq approach. We also compared splicing events from lymphoblastoid cell‐lines with those from breast and ovarian fimbriae tissues. The potential of targeted RNA‐seq to detect pathogenic changes in RNA‐splicing was validated by the inclusion of samples with previously well characterized BRCA1/2 genetic variants. In our study, we update the catalogue of normal splicing events for BRCA1/2, provide an extensive catalogue of normal RAD51C and RAD51D alternative splicing, and list splicing events found for eight other genes. Additionally, we show that our approach allowed the identification of aberrant splicing events due to the presence of BRCA1/2 genetic variants and distinguished between complete and partial splicing events. In conclusion, targeted‐RNA‐seq can be very useful to classify variants based on their putative pathogenic impact on splicing.
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Hereditary familial breast/ovarian cancer (HBOC) syndrome involves numerous pathogenic variants, including variants of uncertain clinical significance (VUS). A subset of VUS, however, is suspected to influence RNA splicing, leading to the expression of potentially pathological transcript isoforms. Here, using a targeted RNA‐seq approach, naturally occurring splice isoforms were described for BRCA1/2, RAD51C, RAD51D, and eight additional tumor‐suppressor genes that are associated with HBOC and Lynch syndrome. The targeted RNA‐seq approach also identified aberrant splicing events associated with the presence of BRCA1/2 genetic variants and successfully distinguished complete from incomplete splicing events, which is of major importance in determining pathogenicity.
Alternative splicing is an essential biological process, which increases the diversity and complexity of the human transcriptome. In our study, 304 splicing pathway-related genes were evaluated in ...tumors from breast cancer patients (TCGA dataset). A high number of alterations were detected, including mutations and copy number alterations (CNAs), although mutations were less frequently present compared with CNAs. In the four molecular subtypes, 14 common splice genes showed high level amplification in >5% of patients. Certain genes were only amplified in specific breast cancer subtypes. Most altered genes in each molecular subtype clustered to a few chromosomal regions. In the Luminal subtype, amplifications of LSM1, CLNS1A, and ILF2 showed a strong significant association with prognosis. An even more robust association with OS and RFS was observed when expression of these three genes was combined. Inhibition of LSM1, CLNS1A, and ILF2, using siRNA in MCF7 and T47D cells, showed a decrease in cell proliferation. The mRNA expression of these genes was reduced by treatment with BET inhibitors, a family of epigenetic modulators. We map the presence of splicing-related genes in breast cancer, describing three novel genes, LSM1, CLNS1A, and ILF2, that have an oncogenic role and can be modulated with BET inhibitors.
tools for splicing defect prediction have a key role to assess the impact of variants of uncertain significance. Our aim was to evaluate the performance of a set of commonly used splicing
tools ...comparing the predictions against RNA
results. This was done for natural splice sites of clinically relevant genes in hereditary breast/ovarian cancer (HBOC) and Lynch syndrome. A study divided into two stages was used to evaluate SSF-like, MaxEntScan, NNSplice, HSF, SPANR, and dbscSNV tools. A discovery dataset of 99 variants with unequivocal results of RNA
studies, located in the 10 exonic and 20 intronic nucleotides adjacent to exon-intron boundaries of
, and
, was collected from four Spanish cancer genetic laboratories. The best stand-alone predictors or combinations were validated with a set of 346 variants in the same genes with clear splicing outcomes reported in the literature. Sensitivity, specificity, accuracy, negative predictive value (NPV) and Mathews Coefficient Correlation (MCC) scores were used to measure the performance. The discovery stage showed that HSF and SSF-like were the most accurate for variants at the donor and acceptor region, respectively. The further combination analysis revealed that HSF, HSF+SSF-like or HSF+SSF-like+MES achieved a high performance for predicting the disruption of donor sites, and SSF-like or a sequential combination of MES and SSF-like for predicting disruption of acceptor sites. The performance confirmation of these last results with the validation dataset, indicated that the highest sensitivity, accuracy, and NPV (99.44%, 99.44%, and 96.88, respectively) were attained with HSF+SSF-like or HSF+SSF-like+MES for donor sites and SSF-like (92.63%, 92.65%, and 84.44, respectively) for acceptor sites. We provide recommendations for combining algorithms to conduct
splicing analysis that achieved a high performance. The high NPV obtained allows to select the variants in which the study by
RNA analysis is mandatory against those with a negligible probability of being spliceogenic. Our study also shows that the performance of each specific predictor varies depending on whether the natural splicing sites are donors or acceptors.
There is still around 50% of the familial breast cancer (BC) cases with an undefined genetic cause, here we have used next‐generation sequencing (NGS) technology to identify new BC susceptibility ...genes. This approach has led to the identification of RECQL5, a member of RECQL‐helicases family, as a new BC susceptibility candidate, which deserves further study. We have used a combination of whole exome sequencing in a family negative for mutations in BRCA1/2 throughout (BRCAX), in which we found a probably deleterious variant in RECQL5, and targeted NGS of the complete coding regions and exon‐intron boundaries of the candidate gene in 699 BC Spanish BRCAX families and 665 controls. Functional characterization and in silico inference of pathogenicity were performed to evaluate the deleterious effect of detected variants. We found at least seven deleterious or likely deleterious variants among the cases and only one in controls. These results prompt us to propose RECQL5 as a gene that would be worth to analyze in larger studies to explore its possible implication in BC susceptibility.
Germline pathogenic variants in BRCA1 confer a high risk of developing breast and ovarian cancer. The BRCA1 exon 11 (formally exon 10) is one of the largest exons and codes for the nuclear ...localization signals of the corresponding gene product. This exon can be partially or entirely skipped during pre‐mRNA splicing, leading to three major in‐frame isoforms that are detectable in most cell types and tissue, and in normal and cancer settings. However, it is unclear whether the splicing imbalance of this exon is associated with cancer risk. Here we identify a common genetic variant in intron 10, rs5820483 (NC_000017.11:g.43095106_43095108dup), which is associated with exon 11 isoform expression and alternative splicing, and with the risk of breast cancer, but not ovarian cancer, in BRCA1 pathogenic variant carriers. The identification of this genetic effect was confirmed by analogous observations in mouse cells and tissue in which a loxP sequence was inserted in the syntenic intronic region. The prediction that the rs5820483 minor allele variant would create a binding site for the splicing silencer hnRNP A1 was confirmed by pull‐down assays. Our data suggest that perturbation of BRCA1 exon 11 splicing modifies the breast cancer risk conferred by pathogenic variants of this gene.