Multigene panels provide a powerful tool for analyzing several genes simultaneously. We evaluated the frequency of pathogenic variants (PV) in customized predefined panels according to clinical ...suspicion by phenotype and compared it to the yield obtained in the analysis of our clinical research gene panel. We also investigated mutational yield of opportunistic testing of BRCA1/2 and mismatch repair (MMR) genes in all patients. A total of 1,205 unrelated probands with clinical suspicion of hereditary cancer were screened for germline mutations using panel testing. Overall, 1,048 females and 157 males were analyzed, mean age at cancer diagnosis was 48; 883 had hereditary breast/ovarian cancer‐suspicion, 205 hereditary nonpolyposis colorectal cancer (HNPCC)‐suspicion, 73 adenomatous‐polyposis‐suspicion and 44 with other/multiple clinical criteria. At least one PV was found in 150 probands (12%) analyzed by our customized phenotype‐driven panel. Tumoral MMR deficiency predicted for the presence of germline MMR gene mutations in patients with HNPCC‐suspicion (46/136 vs. 0/56 in patients with and without MMR deficiency, respectively). Opportunistic testing additionally identified five MSH6, one BRCA1 and one BRCA2 carriers (0.6%). The analysis of the extended 24‐gene panel provided 25 additional PVs (2%), including in 4 out of 51 individuals harboring MMR‐proficient colorectal tumors (2 CHEK2 and 2 ATM). Phenotype‐based panels provide a notable rate of PVs with clinical actionability. Opportunistic testing of MMR and BRCA genes leads to a significant straightforward identification of MSH6, BRCA1 and BRCA2 mutation carriers, and endorses the model of opportunistic testing of genes with clinical utility within a standard genetic counseling framework.
What's new?
Multigene panels offer a powerful tool for analyzing several cancer‐related genes with a single test. But which genes are actually useful in guiding medical decisions in the clinic? In this study, the authors analyzed several customized, phenotype‐driven diagnostic gene panels. These yielded a notable rate of pathogenic variants with clear clinical actionability. The study also found that opportunistic testing of MMR and BRCA genes leads to a significant, straightforward identification of MSH6, BRCA1 and BRCA2 mutation carriers. This approach could be applied within a standard genetic counseling framework.
Fatigue is common in breast-cancer survivors. Our study assessed fatigue longitudinally in breast cancer patients receiving adjuvant radiotherapy (RT) and aimed to identify risk factors associated ...with long-term fatigue and underlying fatigue trajectories. Fatigue was measured in a prospective multicenter cohort (REQUITE) using the Multidimensional Fatigue Inventory (MFI-20) and analyzed using mixed models. Multivariable logistic models identified factors associated with fatigue dimensions at 2 years post-RT and latent class growth analysis identified individual fatigue trajectories. A total of 1443, 1302, 1203 and 1098 patients completed the MFI-20 at baseline, end of RT, after 1 and 2 years. Overall, levels of fatigue significantly increased from baseline to end of RT for all fatigue dimensions (P < .05) and returned to baseline levels after 2 years. A quarter of patients were assigned to latent trajectory high (23.7%) and moderate (24.8%) fatigue classes, while 46.3% and 5.2% to the low and decreasing fatigue classes, respectively. Factors associated with multiple fatigue dimensions at 2 years include age, BMI, global health status, insomnia, pain, dyspnea and depression. Fatigue present at baseline was consistently associated with all five MFI-20 fatigue dimensions (OR
= 3.81, P < .001). From latent trajectory analysis, patients with a combination of factors such as pain, insomnia, depression, younger age and endocrine therapy had a particularly high risk of developing early and persistent high fatigue years after treatment. Our results confirmed the multidimensional nature of fatigue and will help clinicians identify breast cancer patients at higher risk of having persistent/late fatigue so that tailored interventions can be delivered.
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.
What's new?
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.
Poly(ADP‐ribose) polymerase (PARP) inhibitors (PARPi) are effective in cancers with defective homologous recombination DNA repair (HRR), including BRCA1/2‐related cancers. A test to identify ...additional HRR‐deficient tumors will help to extend their use in new indications. We evaluated the activity of the PARPi olaparib in patient‐derived tumor xenografts (PDXs) from breast cancer (BC) patients and investigated mechanisms of sensitivity through exome sequencing, BRCA1 promoter methylation analysis, and immunostaining of HRR proteins, including RAD51 nuclear foci. In an independent BC PDX panel, the predictive capacity of the RAD51 score and the homologous recombination deficiency (HRD) score were compared. To examine the clinical feasibility of the RAD51 assay, we scored archival breast tumor samples, including PALB2‐related hereditary cancers. The RAD51 score was highly discriminative of PARPi sensitivity versus PARPi resistance in BC PDXs and outperformed the genomic test. In clinical samples, all PALB2‐related tumors were classified as HRR‐deficient by the RAD51 score. The functional biomarker RAD51 enables the identification of PARPi‐sensitive BC and broadens the population who may benefit from this therapy beyond BRCA1/2‐related cancers.
Synopsis
Sensitive and highly specific biomarkers usable in archived formalin fixed parafin embedded (FFPE) tumour samples are needed to extend the use of PARP inhibitors beyond BRCA1/2‐related cancers. The RAD51 score may satisfy this clinical unmet need.
The RAD51 score shows complete discriminative capacity in predicting PARP inhibitor response.
The RAD51 score is feasible in routine breast tumor samples without prior exposure to DNA damaging agents.
Carrying a PALB2 mutation is associated with a low RAD51score.
Sensitive and highly specific biomarkers usable in archived formalin fixed parafin embedded (FFPE) tumour samples are needed to extend the use of PARP inhibitors beyond BRCA1/2‐related cancers. The RAD51 score may satisfy this clinical unmet need.
BRCA1 and BRCA2 (BRCA1/2) genetic variants that disrupt messenger RNA splicing are commonly associated with increased risks of developing breast/ovarian cancer. The majority of splicing studies ...published to date rely on qualitative methodologies (i.e., Sanger sequencing), but it is necessary to incorporate semi‐quantitative or quantitative approaches to accurately interpret the clinical significance of spliceogenic variants. Here, we characterize the splicing impact of 31 BRCA1/2 variants using semi‐quantitative capillary electrophoresis of fluorescent amplicons (CE), Sanger sequencing and allele‐specific assays. A total of 14 variants were found to disrupt splicing. Allelic‐specific assays could be performed for BRCA1 c.302−1G>A and BRCA2 c.516+2T>A, c.1909+1G>A, c.8332–13T>G, c.8332−2A>G, c.8954−2A>T variants, showing a monoallelic contribution to full‐length transcript expression that was concordant with semi‐quantitative data. The splicing fraction of alternative and aberrant transcripts was also measured by CE, facilitating variant interpretation. Following Evidence‐based Network for the Interpretation of Germline Mutant Alleles criteria, we successfully classified eight variants as pathogenic (Class 5), five variants as likely pathogenic (Class 4), and 14 variants as benign (Class 1). We also provide splicing data for four variants classified as uncertain (Class 3), which produced a “leaky” splicing effect or introduced a missense change in the protein sequence, that will require further assessment to determine their clinical significance.
BRCA1 and BRCA2 (BRCA1/2) germline variants disrupting the DNA protective role of these genes increase the risk of hereditary breast and ovarian cancers. Correct identification of these variants then ...becomes clinically relevant, because it may increase the survival rates of the carriers. Unfortunately, we are still unable to systematically predict the impact of BRCA1/2 variants. In this article, we present a family of in silico predictors that address this problem, using a gene‐specific approach. For each protein, we have developed two tools, aimed at predicting the impact of a variant at two different levels: Functional and clinical. Testing their performance in different datasets shows that specific information compensates the small number of predictive features and the reduced training sets employed to develop our models. When applied to the variants of the BRCA1/2 (ENIGMA) challenge in the fifth Critical Assessment of Genome Interpretation (CAGI 5) we find that these methods, particularly those predicting the functional impact of variants, have a good performance, identifying the large compositional bias towards neutral variants in the CAGI sample. This performance is further improved when incorporating to our prediction protocol estimates of the impact on splicing of the target variant.
Disruptive BRCA1 and BRCA2 germline variants increase the risk of hereditary breast and ovarian cancers. We present two families of in silico predictors (multiple linear regression and neural network) designed to identify them, and the validation of these tools in the fifth Critical Assessment of Genome Interpretation‐ENIGMA challenge. Our tools generally outperform standard predictors, as shown in the heatmap: Diagonal and off‐diagonal elements correspond to successful and failed predictions, respectively.
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.
Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable ...risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly‐interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.
Variation in BRCA1 and BRCA2 can greatly increase the risk of breast, ovarian and other cancers. Growing awareness of this fact is leading to an increased rate of genetic testing, which in turn has led to the discovery of thousands of Variants of Uncertain Significance (VUS). The rate of VUS discovery has outstripped the rate of variant interpretation, which has led for a growing need for accurate, high‐throughput methods for variant analysis. In the CAG5 ENIGMA challenge, participants predicted the clinical significance of 326 variants, for which expert interpretations had been completed but not published. Six teams submitted blind predictions on these variants, with fourteen methods collectively. The best performance was achieved by the LEAP methods by Color Genomics, which successfully leveraged private data including an HGMD subscription and an internal library of genetic testing results. This emphasizes that there are still private data that could inform variant prediction. To the extent that such data can be made publicly available, science will benefit, and genetic testing patients by extension.
Many BRCA1 and BRCA2 (BRCA1/2) genetic variants have been studied at mRNA level and linked to hereditary breast and ovarian cancer due to splicing alteration. In silico tools are reliable when ...assessing variants located in consensus splice sites, but we may identify variants in complex genomic contexts for which bioinformatics is not precise enough. In this study, we characterize BRCA2 c.7976 + 5G > T variant located in intron 17 which has an atypical donor site (GC). This variant was identified in three unrelated Spanish families and we have detected exon 17 skipping as the predominant transcript occurring in carriers. We have also detected several isoforms (Δ16‐18, Δ17,18, Δ18, and ▼17q224) at different expression levels among carriers and controls. This study remarks the challenge of interpreting genetic variants when multiple alternative isoforms are present, and that caution must be taken when using in silico tools to identify potential spliceogenic variants located in GC‐AG introns.
In this study we characterize BRCA2 c.7976 + 5G > T variant located in intron 17, which has an atypical donor site (GC). The variant promotes exon 17 skipping, but several isoforms (Δ16‐18, Δ17,18, Δ18, and ▼17q224) have also been detected at different expression levels in variant carriers and controls. This study remarks the challenge of interpreting genetic variants located in regions with high levels of alternative splicing.
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