Inherited cancer predisposing mutations in patients with therapy-related myeloid neoplasms.

Some patients with therapy-related myeloid neoplasms (t-MN) may have unsuspected inherited cancer predisposition syndrome (CPS). We propose a set of clinical criteria to identify t-MN patients with high risk of CPS (HR-CPS). Among 225 t-MN patients with an antecedent non-myeloid malignancy, our clinical criteria identified 52 (23%) HR-CPS patients. Germline whole-exome sequencing identified pathogenic or likely pathogenic variants in 10 of 27 HR-CPS patients compared to 0 of 9 low-risk CPS patients (37% vs. 0%, p = 0.04). These simple clinical criteria identify t-MN patients most likely to benefit from genetic testing for inherited CPS.

Serial changes in liquid biopsy-derived variant allele frequency predict immune checkpoint inhibitor responsiveness in the pan-cancer setting.

Major immunotherapy challenges include a limited number of predictive biomarkers and the unusual imaging features post-therapy, such as pseudo-progression, which denote immune infiltrate-mediated tumor enlargement. Such phenomena confound clinical decision-making, since the cancer may eventually regress, and the patient should stay on treatment. We prospectively evaluated serial, blood-derived cell-free DNA (cfDNA) (baseline and 2-3 weeks post-immune checkpoint inhibitors [ICIs]) for variant allele frequency (VAF) and blood tumor mutation burden (bTMB) changes (next-generation sequencing) (N = 84 evaluable patients, diverse cancers). Low vs. high cfDNA-derived average adjusted ΔVAF (calculated by a machine-learning model) was an independent predictor of higher clinical benefit rate (stable disease ≥6 months/complete/partial response) (69.2% vs. 22.5%), and longer median progression-free (10.1 vs. 2.25 months) and overall survival (not reached vs. 6.1 months) (all P < .001, multivariate). bTMB changes did not correlate with outcomes. Therefore, early dynamic changes in cfDNA-derived VAF were a powerful predictor of pan-cancer immunotherapy outcomes.

Validation of a prostate cancer polygenic risk score.

BACKGROUND: Genome-wide association studies have identified over 100 single-nucleotide polymorphisms (SNPs) associated with prostate cancer (PrCa), and polygenic risk scores (PRS) based on their combined genotypes have been developed for risk stratification. We aimed to assess the contribution of PRS to PrCa risk in a large multisite study. METHODS: The sample included 1972 PrCa cases and 1919 unaffected controls. Next-generation sequencing was used to assess pathogenic variants in 14 PrCa-susceptibility genes and 72 validated PrCa-associated SNPs. We constructed a population-standardized PRS and tested its association with PrCa using logistic regression adjusted for age and family history of PrCa. RESULTS: The mean age of PrCa cases at diagnosis and age of controls at testing/last clinic visit was 59.5 ± 7.2 and 57.2 ± 13.0 years, respectively. Among 1740 cases with pathology data, 57.4% had Gleason score ≤ 6, while 42.6% had Gleason score ≥ 8. In addition, 39.6% cases and 20.1% controls had a family history of PrCa. The PRS was significantly higher in cases than controls (mean ± SD: 1.42 ± 1.11 vs 1.02 ± 0.76; P < .0001). Compared with men in the 1st quartile of age-adjusted PRS, those in the 2nd, 3rd, and 4th quartile were 1.58 (95% confidence interval [CI]: 1.31-1.90), 2.36 (95% CI: 1.96-2.84), and 3.98 (95% CI: 3.29-4.82) times as likely to have PrCa (all P < .0001). Adjustment for family history yielded similar results. PRS predictive performance was consistent with prior literature (area under the receiver operating curve = 0.64; 95% CI: 0.62-0.66). CONCLUSIONS: These data suggest that a 72-SNP PRS is predictive of PrCa, supporting its potential use in clinical risk assessment.

Splicing profile by capture RNA-seq identifies pathogenic germline variants in tumor suppressor genes.

Germline variants in tumor suppressor genes (TSGs) can result in RNA mis-splicing and predisposition to cancer. However, identification of variants that impact splicing remains a challenge, contributing to a substantial proportion of patients with suspected hereditary cancer syndromes remaining without a molecular diagnosis. To address this, we used capture RNA-sequencing (RNA-seq) to generate a splicing profile of 18 TSGs (APC, ATM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, MLH1, MSH2, MSH6, MUTYH, NF1, PALB2, PMS2, PTEN, RAD51C, RAD51D, and TP53) in 345 whole-blood samples from healthy donors. We subsequently demonstrated that this approach can detect mis-splicing by comparing splicing profiles from the control dataset to profiles generated from whole blood of individuals previously identified with pathogenic germline splicing variants in these genes. To assess the utility of our TSG splicing profile to prospectively identify pathogenic splicing variants, we performed concurrent capture DNA and RNA-seq in a cohort of 1000 patients with suspected hereditary cancer syndromes. This approach improved the diagnostic yield in this cohort, resulting in a 9.1% relative increase in the detection of pathogenic variants, demonstrating the utility of performing simultaneous DNA and RNA genetic testing in a clinical context.

Tumour characteristics provide evidence for germline mismatch repair missense variant pathogenicity.

BACKGROUND: Pathogenic variants in mismatch repair (MMR) genes (MLH1, MSH2, MSH6 and PMS2) increase risk for Lynch syndrome and related cancers. We quantified tumour characteristics to assess variant pathogenicity for germline MMR genes. METHODS: Among 4740 patients with cancer with microsatellite instability (MSI) and immunohistochemical (IHC) results, we tested MMR pathogenic variant association with MSI/IHC status, and estimated likelihood ratios which we used to compute a tumour characteristic likelihood ratio (TCLR) for each variant. Predictive performance of TCLR in combination with in silico predictors, and a multifactorial variant prediction (MVP) model that included allele frequency, co-occurrence, co-segregation, and clinical and family history information was assessed. RESULTS: Compared with non-carriers, carriers of germline pathogenic/likely pathogenic (P/LP) variants were more likely to have abnormal MSI/IHC status (p<0.0001). Among 150 classified missense variants, 73.3% were accurately predicted with TCLR alone. Models leveraging in silico scores as prior probabilities accurately classified >76.7% variants. Adding TCLR as quantitative evidence in an MVP model (MVP +TCLR Pred) increased the proportion of accurately classified variants from 88.0% (MVP alone) to 98.0% and generated optimal performance statistics among all models tested. Importantly, MVP +TCLR Pred resulted in the high yield of predicted classifications for missense variants of unknown significance (VUS); among 193 VUS, 62.7% were predicted as P/PL or benign/likely benign (B/LB) when assessed according to American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines. CONCLUSION: Our study demonstrates that when used separately or in conjunction with other evidence, tumour characteristics provide evidence for germline MMR missense variant assessment, which may have important implications for genetic testing and clinical management.

REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification.

Many in silico predictors of genetic variant pathogenicity have been previously developed, but there is currently no standard application of these algorithms for variant assessment. Using 4,094 ClinVar-curated missense variants in clinically actionable genes, we evaluated the accuracy and yield of benign and deleterious evidence in 5 in silico meta-predictors, as well as agreement of SIFT and PolyPhen2, and report the derived thresholds for the best performing predictor(s). REVEL and BayesDel outperformed all other meta-predictors (CADD, MetaSVM, Eigen), with higher positive predictive value, comparable negative predictive value, higher yield, and greater overall prediction performance. Agreement of SIFT and PolyPhen2 resulted in slightly higher yield but lower overall prediction performance than REVEL or BayesDel. Our results support the use of gene-level rather than generalized thresholds, when gene-level thresholds can be estimated. Our results also support the use of 2-sided thresholds, which allow for uncertainty, rather than a single, binary cut-point for assigning benign and deleterious evidence. The gene-level 2-sided thresholds we derived for REVEL or BayesDel can be used to assess in silico evidence for missense variants in accordance with current classification guidelines.

Comprehensive Paired Tumor/Germline Testing for Lynch Syndrome: Bringing Resolution to the Diagnostic Process.

PURPOSE: The current diagnostic testing algorithm for Lynch syndrome (LS) is complex and often involves multiple follow-up germline and somatic tests. We aimed to describe the results of paired tumor/germline testing performed on a large cohort of patients with colorectal cancer (CRC) and endometrial cancer (EC) to better determine the utility of this novel testing methodology. MATERIALS AND METHODS: We retrospectively reviewed a consecutive series of patients with CRC and EC undergoing paired tumor/germline analysis of the LS genes at a clinical diagnostic laboratory (N = 702). Microsatellite instability, MLH1 promoter hypermethylation, and germline testing of additional genes were performed if ordered. Patients were assigned to one of five groups on the basis of prior tumor screening and germline testing outcomes. Results for each group are described. RESULTS: Overall results were informative regarding an LS diagnosis for 76.1% and 60.8% of patients with mismatch-repair-deficient (MMRd) CRC and EC without and with prior germline testing, respectively. LS germline mutations were identified in 24.8% of patients in the group without prior germline testing, and interestingly, in 9.5% of patients with previous germline testing; four of these were discordant with prior tumor screening. Upon excluding patients with MLH1 promoter hypermethylation and germline mutations, biallelic somatic inactivation was seen in approximately 50% of patients with MMRd tumors across groups. CONCLUSION: Paired testing identified a cause for MMRd tumors in 76% and 61% of patients without and with prior LS germline testing, respectively. Findings support inclusion of tumor sequencing as well as comprehensive LS germline testing in the LS testing algorithm. Paired testing offers a complete, convenient evaluation for LS with high diagnostic resolution.

Association of Breast and Ovarian Cancers With Predisposition Genes Identified by Large-Scale Sequencing.

Importance: Since the discovery of BRCA1 and BRCA2, multiple high- and moderate-penetrance genes have been reported as risk factors for hereditary breast cancer, ovarian cancer, or both; however, it is unclear whether these findings represent the complete genetic landscape of these cancers. Systematic investigation of the genetic contributions to breast and ovarian cancers is needed to confirm these findings and explore potentially new associations. Objective: To confirm reported and identify additional predisposition genes for breast or ovarian cancer. Design, Setting, and Participants: In this sample of 11 416 patients with clinical features of breast cancer, ovarian cancer, or both who were referred for genetic testing from 1200 hospitals and clinics across the United States and of 3988 controls who were referred for genetic testing for noncancer conditions between 2014 and 2015, whole-exome sequencing was conducted and gene-phenotype associations were examined. Case-control analyses using the Genome Aggregation Database as a set of reference controls were also conducted. Main Outcomes and Measures: Breast cancer risk associated with pathogenic variants among 625 cancer predisposition genes; association of identified predisposition breast or ovarian cancer genes with the breast cancer subtypes invasive ductal, invasive lobular, hormone receptor-positive, hormone receptor-negative, and male, and with early-onset disease. Results: Of 9639 patients with breast cancer, 3960 (41.1%) were early-onset cases (≤45 years at diagnosis) and 123 (1.3%) were male, with men having an older age at diagnosis than women (mean [SD] age, 61.8 [12.8] vs 48.6 [11.4] years). Of 2051 women with ovarian cancer, 445 (21.7%) received a diagnosis at 45 years or younger. Enrichment of pathogenic variants were identified in 4 non-BRCA genes associated with breast cancer risk: ATM (odds ratio [OR], 2.97; 95% CI, 1.67-5.68), CHEK2 (OR, 2.19; 95% CI, 1.40-3.56), PALB2 (OR, 5.53; 95% CI, 2.24-17.65), and MSH6 (OR, 2.59; 95% CI, 1.35-5.44). Increased risk for ovarian cancer was associated with 4 genes: MSH6 (OR, 4.16; 95% CI, 1.95-9.47), RAD51C (OR, not estimable; false-discovery rate-corrected P = .004), TP53 (OR, 18.50; 95% CI, 2.56-808.10), and ATM (OR, 2.85; 95% CI, 1.30-6.32). Neither the MRN complex genes nor CDKN2A was associated with increased breast or ovarian cancer risk. The findings also do not support previously reported breast cancer associations with the ovarian cancer susceptibility genes BRIP1, RAD51C, and RAD51D, or mismatch repair genes MSH2 and PMS2. Conclusions and Relevance: The results of this large-scale exome sequencing of patients and controls shed light on both well-established and controversial non-BRCA predisposition gene associations with breast or ovarian cancer reported to date and may implicate additional breast or ovarian cancer susceptibility gene candidates involved in DNA repair and genomic maintenance.

Detection of structural variation using target captured next-generation sequencing data for genetic diagnostic testing.

PURPOSE: Structural variation (SV) is associated with inherited diseases. Next-generation sequencing (NGS) is an efficient method for SV detection because of its high-throughput, low cost, and base-pair resolution. However, due to lack of standard NGS protocols and a limited number of clinical samples with pathogenic SVs, comprehensive standards for SV detection, interpretation, and reporting are to be established. METHODS: We performed SV assessment on 60,000 clinical samples tested with hereditary cancer NGS panels spanning 48 genes. To evaluate NGS results, NGS and orthogonal methods were used separately in a blinded fashion for SV detection in all samples. RESULTS: A total of 1,037 SVs in coding sequence (CDS) or untranslated regions (UTRs) and 30,847 SVs in introns were detected and validated. Across all variant types, NGS shows 100% sensitivity and 99.9% specificity. Overall, 64% of CDS/UTR SVs were classified as pathogenic/likely pathogenic, and five deletions/duplications were reclassified as pathogenic using breakpoint information from NGS. CONCLUSION: The SVs presented here can be used as a valuable resource for clinical research and diagnostics. The data illustrate NGS as a powerful tool for SV detection. Application of NGS and confirmation technologies in genetic testing ensures delivering accurate and reliable results for diagnosis and patient care.

A Bayesian framework for efficient and accurate variant prediction.

There is a growing need to develop variant prediction tools capable of assessing a wide spectrum of evidence. We present a Bayesian framework that involves aggregating pathogenicity data across multiple in silico scores on a gene-by-gene basis and multiple evidence statistics in both quantitative and qualitative forms, and performs 5-tiered variant classification based on the resulting probability credible interval. When evaluated in 1,161 missense variants, our gene-specific in silico model-based meta-predictor yielded an area under the curve (AUC) of 96.0% and outperformed all other in silico predictors. Multifactorial model analysis incorporating all available evidence yielded 99.7% AUC, with 22.8% predicted as variants of uncertain significance (VUS). Use of only 3 auto-computed evidence statistics yielded 98.6% AUC with 56.0% predicted as VUS, which represented sufficient accuracy to rapidly assign a significant portion of VUS to clinically meaningful classifications. Collectively, our findings support the use of this framework to conduct large-scale variant prioritization using in silico predictors followed by variant prediction and classification with a high degree of predictive accuracy.

Quantitative Analysis of BRCA1 and BRCA2 Germline Splicing Variants Using a Novel RNA-Massively Parallel Sequencing Assay.

Clinical genetic testing for hereditary breast and ovarian cancer (HBOC) is becoming widespread. However, the interpretation of variants of unknown significance (VUS) in HBOC genes, such as the clinically actionable genes BRCA1 and BRCA2, remain a challenge. Among the variants that are frequently classified as VUS are those with unclear effects on splicing. In order to address this issue we developed a high-throughput RNA-massively parallel sequencing assay-CloneSeq-capable to perform quantitative and qualitative analysis of transcripts in cell lines and HBOC patients. This assay is based on cloning of RT-PCR products followed by massive parallel sequencing of the cloned transcripts. To validate this assay we compared it to the RNA splicing assays recommended by members of the ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) consortium. This comparison was performed using well-characterized lymphoblastoid cell lines (LCLs) generated from carriers of the BRCA1 or BRCA2 germline variants that have been previously described to be associated with splicing defects. CloneSeq was able to replicate the ENIGMA results, in addition to providing quantitative characterization of BRCA1 and BRCA2 germline splicing alterations in a high-throughput fashion. Furthermore, CloneSeq was used to analyze blood samples obtained from carriers of BRCA1 or BRCA2 germline sequence variants, including the novel uncharacterized alteration BRCA1 c.5152+5G>T, which was identified in a HBOC family. CloneSeq provided a high-resolution picture of all the transcripts induced by BRCA1 c.5152+5G>T, indicating it results in significant levels of exon skipping. This analysis proved to be important for the classification of BRCA1 c.5152+5G>T as a clinically actionable likely pathogenic variant. Reclassifications such as these are fundamental in order to offer preventive measures, targeted treatment, and pre-symptomatic screening to the correct individuals.

TumorNext-Lynch-MMR: a comprehensive next generation sequencing assay for the detection of germline and somatic mutations in genes associated with mismatch repair deficiency and Lynch syndrome.

The current algorithm for Lynch syndrome diagnosis is highly complex with multiple steps which can result in an extended time to diagnosis while depleting precious tumor specimens. Here we describe the analytical validation of a custom probe-based NGS tumor panel, TumorNext-Lynch-MMR, which generates a comprehensive genetic profile of both germline and somatic mutations that can accelerate and streamline the time to diagnosis and preserve specimen. TumorNext-Lynch-MMR can detect single nucleotide variants, small insertions and deletions in 39 genes that are frequently mutated in Lynch syndrome and colorectal cancer. Moreover, the panel provides microsatellite instability status and detects loss of heterozygosity in the five Lynch genes; MSH2, MSH6, MLH1, PMS2 and EPCAM. Clinical cases are described that highlight the assays ability to differentiate between somatic and germline mutations, precisely classify variants and resolve discordant cases.

Correction: Candidate-gene criteria for clinical reporting: diagnostic exome sequencing identifies altered candidate genes among 8% of patients with undiagnosed diseases.

In the published version of this paper, some of the columns in the last three rows of Table 3 were mistakenly transposed. The corrected table appears below. In col. 6 of the row for DNMT3A, "S3" was published in the original article. However, in the revised table for the corrigendum, it has been corrected to "S1". In col. 6 of the row for SON, "S3" was published in the original article. However, in the revised table for the corrigendum, it has been corrected to "S2".

Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels.

BACKGROUND: With the expanded availability of next generation sequencing (NGS)-based clinical genetic tests, clinicians seeking to test patients with Mendelian diseases must weigh the superior coverage of targeted gene panels with the greater number of genes included in whole exome sequencing (WES) when considering their first-tier testing approach. Here, we use an in silico analysis to predict the analytic sensitivity of WES using pathogenic variants identified on targeted NGS panels as a reference. METHODS: Corresponding nucleotide positions for 1533 different alterations classified as pathogenic or likely pathogenic identified on targeted NGS multi-gene panel tests in our laboratory were interrogated in data from 100 randomly-selected clinical WES samples to quantify the sequence coverage at each position. Pathogenic variants represented 91 genes implicated in hereditary cancer, X-linked intellectual disability, primary ciliary dyskinesia, Marfan syndrome/aortic aneurysms, cardiomyopathies and arrhythmias. RESULTS: When assessing coverage among 100 individual WES samples for each pathogenic variant (153,300 individual assessments), 99.7% (n = 152,798) would likely have been detected on WES. All pathogenic variants had at least some coverage on exome sequencing, with a total of 97.3% (n = 1491) detectable across all 100 individuals. For the remaining 42 pathogenic variants, the number of WES samples with adequate coverage ranged from 35 to 99. Factors such as location in GC-rich, repetitive, or homologous regions likely explain why some of these alterations were not detected across all samples. To validate study findings, a similar analysis was performed against coverage data from 60,706 exomes available through the Exome Aggregation Consortium (ExAC). Results from this validation confirmed that 98.6% (91,743,296/93,062,298) of pathogenic variants demonstrated adequate depth for detection. CONCLUSIONS: Results from this in silico analysis suggest that exome sequencing may achieve a diagnostic yield similar to panel-based testing for Mendelian diseases.

Candidate-gene criteria for clinical reporting: diagnostic exome sequencing identifies altered candidate genes among 8% of patients with undiagnosed diseases.

PURPOSE: Diagnostic exome sequencing (DES) is now a commonly ordered test for individuals with undiagnosed genetic disorders. In addition to providing a diagnosis for characterized diseases, exome sequencing has the capacity to uncover novel candidate genes for disease. METHODS: Family-based DES included analysis of both characterized and novel genetic etiologies. To evaluate candidate genes for disease in the clinical setting, we developed a systematic, rule-based classification schema. RESULTS: Testing identified a candidate gene among 7.7% (72/934) of patients referred for DES; 37 (4.0%) and 35 (3.7%) of the genes received evidence scores of "candidate" and "suspected candidate," respectively. A total of 71 independent candidate genes were reported among the 72 patients, and 38% (27/71) were subsequently corroborated in the peer-reviewed literature. This rate of corroboration increased to 51.9% (27/52) among patients whose gene was reported at least 12 months previously. CONCLUSIONS: Herein, we provide transparent, comprehensive, and standardized scoring criteria for the clinical reporting of candidate genes. These results demonstrate that DES is an integral tool for genetic diagnosis, especially for elucidating the molecular basis for both characterized and novel candidate genetic etiologies. Gene discoveries also advance the understanding of normal human biology and more common diseases.Genet Med 19 2, 224-235.

Sanger Confirmation Is Required to Achieve Optimal Sensitivity and Specificity in Next-Generation Sequencing Panel Testing.

Next-generation sequencing (NGS) has rapidly replaced Sanger sequencing as the method of choice for diagnostic gene-panel testing. For hereditary-cancer testing, the technical sensitivity and specificity of the assay are paramount as clinicians use results to make important clinical management and treatment decisions. There is significant debate within the diagnostics community regarding the necessity of confirming NGS variant calls by Sanger sequencing, considering that numerous laboratories report having 100% specificity from the NGS data alone. Here we report our results from 20,000 hereditary-cancer NGS panels spanning 47 genes, in which all 7845 nonpolymorphic variants were Sanger- sequenced. Of these, 98.7% were concordant between NGS and Sanger sequencing and 1.3% were identified as NGS false-positives, located mainly in complex genomic regions (A/T-rich regions, G/C-rich regions, homopolymer stretches, and pseudogene regions). Simulating a false-positive rate of zero by adjusting the variant-calling quality-score thresholds decreased the sensitivity of the assay from 100% to 97.8%, resulting in the missed detection of 176 Sanger-confirmed variants, the majority in complex genomic regions (n = 114) and mosaic mutations (n = 7). The data illustrate the importance of setting quality thresholds for panel testing only after thousands of samples have been processed and the necessity of Sanger confirmation of NGS variants to maintain the highest possible sensitivity.

A recurrent mutation in KCNA2 as a novel cause of hereditary spastic paraplegia and ataxia.

The hereditary spastic paraplegias (HSPs) are heterogeneous neurodegenerative disorders with over 50 known causative genes. We identified a recurrent mutation in KCNA2 (c.881G>A, p.R294H), encoding the voltage-gated K(+) -channel, KV 1.2, in two unrelated families with HSP, intellectual disability (ID), and ataxia. Follow-up analysis of > 2,000 patients with various neurological phenotypes identified a de novo p.R294H mutation in a proband with ataxia and ID. Two-electrode voltage-clamp recordings of Xenopus laevis oocytes expressing mutant KV 1.2 channels showed loss of function with a dominant-negative effect. Our findings highlight the phenotypic spectrum of a recurrent KCNA2 mutation, implicating ion channel dysfunction as a novel HSP disease mechanism. Ann Neurol 2016.

Loss of function of the retinoid-related nuclear receptor (RORB) gene and epilepsy.

Genetic generalized epilepsy (GGE), formerly known as idiopathic generalized epilepsy, is the most common form of epilepsy and is thought to have predominant genetic etiology. GGE are clinically characterized by absence, myoclonic, or generalized tonic-clonic seizures with electroencephalographic pattern of bilateral, synchronous, and symmetrical spike-and-wave discharges. Despite their strong heritability, the genetic basis of generalized epilepsies remains largely elusive. Nevertheless, recent advances in genetic technology have led to the identification of numerous genes and genomic defects in various types of epilepsies in the past few years. In the present study, we performed whole-exome sequencing in a family with GGE consistent with the diagnosis of eyelid myoclonia with absences. We found a nonsense variant (c.196C>T/p.(Arg66*)) in RORB, which encodes the beta retinoid-related orphan nuclear receptor (RORß), in four affected family members. In addition, two de novo variants (c.218T>C/p.(Leu73Pro); c.1249_1251delACG/p.(Thr417del)) were identified in sporadic patients by trio-based exome sequencing. We also found two de novo deletions in patients with behavioral and cognitive impairment and epilepsy: a 52-kb microdeletion involving exons 5-10 of RORB and a larger 9q21-microdeletion. Furthermore, we identified a patient with intellectual disability and a balanced translocation where one breakpoint truncates RORB and refined the phenotype of a recently reported patient with RORB deletion. Our data support the role of RORB gene variants/CNVs in neurodevelopmental disorders including epilepsy, and especially in generalized epilepsies with predominant absence seizures.

Germline activating MTOR mutation arising through gonadal mosaicism in two brothers with megalencephaly and neurodevelopmental abnormalities.

BACKGROUND: In humans, Mammalian Target of Rapamycin (MTOR) encodes a 300 kDa serine/ threonine protein kinase that is ubiquitously expressed, particularly at high levels in brain. MTOR functions as an integrator of multiple cellular processes, and in so doing either directly or indirectly regulates the phosphorylation of at least 800 proteins. While somatic MTOR mutations have been recognized in tumors for many years, and more recently in hemimegalencephaly, germline MTOR mutations have rarely been described. CASE PRESENTATION: We report the successful application of family-trio Diagnostic Exome Sequencing (DES) to identify the underlying molecular etiology in two brothers with multiple neurological and developmental lesions, and for whom previous testing was non-diagnostic. The affected brothers, who were 6 and 23 years of age at the time of DES, presented symptoms including but not limited to mild Autism Spectrum Disorder (ASD), megalencephaly, gross motor skill delay, cryptorchidism and bilateral iris coloboma. Importantly, we determined that each affected brother harbored the MTOR missense alteration p.E1799K (c.5395G>A). This exact variant has been previously identified in multiple independent human somatic cancer samples and has been shown to result in increased MTOR activation. Further, recent independent reports describe two unrelated families in whom p.E1799K co-segregated with megalencephaly and intellectual disability (ID); in both cases, p.E1799K was shown to have originated due to germline mosaicism. In the case of the family reported herein, the absence of p.E1799K in genomic DNA extracted from the blood of either parent suggests that this alteration most likely arose due to gonadal mosaicism. Further, the p.E1799K variant exerts its effect by a gain-of-function (GOF), autosomal dominant mechanism. CONCLUSION: Herein, we describe the use of DES to uncover an activating MTOR missense alteration of gonadal mosaic origin that is likely to be the causative mutation in two brothers who present multiple neurological and developmental abnormalities. Our report brings the total number of families who harbor MTOR p.E1799K in association with megalencephaly and ID to three. In each case, evidence suggests that p.E1799K arose in the affected individuals due to gonadal mosaicism. Thus, MTOR p.E1799K can now be classified as a pathogenic GOF mutation that causes megalencephaly and cognitive impairment in humans.