Forging Links between Human Mental Retardation–Associated CNVs and Mouse Gene Knockout Models

Rare copy number variants (CNVs) are frequently associated with common neurological disorders such as mental retardation (MR; learning disability), autism, and schizophrenia. CNV screening in clinical practice is limited because pathological CNVs cannot be distinguished routinely from benign CNVs, and because genes underlying patients' phenotypes remain largely unknown. Here, we present a novel, statistically robust approach that forges links between 148 MR–associated CNVs and phenotypes from ∼5,000 mouse gene knockout experiments. These CNVs were found to be significantly enriched in two classes of genes, those whose mouse orthologues, when disrupted, result in either abnormal axon or dopaminergic neuron morphologies. Additional enrichments highlighted correspondences between relevant mouse phenotypes and secondary presentations such as brain abnormality, cleft palate, and seizures. The strength of these phenotype enrichments (>100% increases) greatly exceeded molecular annotations (<30% increases) and allowed the identification of 78 genes that may contribute to MR and associated phenotypes. This study is the first to demonstrate how the power of mouse knockout data can be systematically exploited to better understand genetically heterogeneous neurological disorders

Mobster: Accurate detection of mobile element insertions in next generation sequencing data

Mobile elements are major drivers in changing genomic architecture and can cause disease. The detection of mobile elements is hindered due to the low mappability of their highly repetitive sequences. We have developed an algorithm, called Mobster, to detect non-reference mobile element insertions in next generation sequencing data from both whole genome and whole exome studies. Mobster uses discordant read pairs and clipped reads in combination with consensus sequences of known active mobile elements. Mobster has a low false discovery rate and high recall rate for both L1 and Alu elements. Mobster is available at http://sourceforge.net/projects/mobster. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0488-x) contains supplementary material, which is available to authorized users

LRFN5 locus structure is associated with autism and influenced by the sex of the individual and locus conversions

LRFN5 is a regulator of synaptic development and the only gene in a 5.4 Mb mammalian-specific conserved topologically associating domain (TAD); the LRFN5 locus. An association between locus structural changes and developmental delay (DD) and/or autism was suggested by several cases in DECIPHER and own records. More significantly, we found that maternal inheritance of a specific LRFN5 locus haplotype segregated with an identical type of autism in distantly related males. This autism-susceptibility haplotype had a specific TAD pattern. We also found a male/female quantitative difference in the amount histone-3-lysine-9-associated chromatin around the LRFN5 gene itself (p < 0.01), possibly related to the male-restricted autism susceptibility. To better understand locus behavior, the prevalence of a 60 kb deletion polymorphism was investigated. Surprisingly, in three cohorts of individuals with DD (n = 8757), the number of deletion heterozygotes was 20%–26% lower than expected from Hardy–Weinberg equilibrium. This suggests allelic interaction, also because the conversions from heterozygosity to wild-type or deletion homozygosity were of equal magnitudes. Remarkably, in a control group of medical students (n = 1416), such conversions were three times more common (p = 0.00001), suggesting a regulatory role of this allelic interaction. Taken together, LRFN5 regulation appears unusually complex, and LRFN5 dysregulation could be an epigenetic cause of autism.publishedVersio

Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

Over the past 10 years, institutional and national molecular tumor boards have been implemented for relapsed or refractory pediatric cancer to prioritize targeted drugs for individualized treatment based on actionable oncogenic lesions, including the Dutch iTHER platform. Hematological malignancies form a minority in precision medicine studies. Here, we report on 56 iTHER leukemia/lymphoma patients for which we considered cell surface markers and oncogenic aberrations as actionable events, supplemented with ex vivo drug sensitivity for six patients. Prior to iTHER registration, 34% of the patients had received allogeneic hematopoietic cell transplantation (HCT) and 18% CAR-T therapy. For 51 patients (91%), a sample with sufficient tumor percentage (≥20%) required for comprehensive diagnostic testing was obtained. Up to 10 oncogenic actionable events were prioritized in 49/51 patients, and immunotherapy targets were identified in all profiled patients. Targeted treatment(s) based on the iTHER advice was given to 24 of 51 patients (47%), including immunotherapy in 17 patients, a targeted drug matching an oncogenic aberration in 12 patients, and a drug based on ex vivo drug sensitivity in one patient, resulting in objective responses and a bridge to HCT in the majority of the patients. In conclusion, comprehensive profiling of relapsed/refractory hematological malignancies showed multiple oncogenic and immunotherapy targets for a precision medicine approach, which requires multidisciplinary expertise to prioritize the best treatment options for this rare, heavily pretreated pediatric population

Recommendations for reporting results of diagnostic genetic testing (biochemical, cytogenetic and molecular genetic)

Genetic test results can have considerable importance for patients, their parents and more remote family members. Clinical therapy and surveillance, reproductive decisions and genetic diagnostics in family members, including prenatal diagnosis, are based on these results. The genetic test report should therefore provide a clear, concise, accurate, fully interpretative and authoritative answer to the clinical question. The need for harmonizing reporting practice of genetic tests has been recognised by the External Quality Assessment (EQA), providers and laboratories. The ESHG Genetic Services Quality Committee has produced reporting guidelines for the genetic disciplines (biochemical, cytogenetic and molecular genetic). These guidelines give assistance on report content, including the interpretation of results. Selected examples of genetic test reports for all three disciplines are provided in an annexe.</p

Genome-wide Copy Number Profiling on High-density Bacterial Artificial Chromosomes, Single-nucleotide Polymorphisms, and Oligonucleotide Microarrays: A Platform Comparison based on Statistical Power Analysis

Recently, comparative genomic hybridization onto bacterial artificial chromosome (BAC) arrays (array-based comparative genomic hybridization) has proved to be successful for the detection of submicroscopic DNA copy-number variations in health and disease. Technological improvements to achieve a higher resolution have resulted in the generation of additional microarray platforms encompassing larger numbers of shorter DNA targets (oligonucleotides). Here, we present a novel method to estimate the ability of a microarray to detect genomic copy-number variations of different sizes and types (i.e. deletions or duplications). We applied our method, which is based on statistical power analysis, to four widely used high-density genomic microarray platforms. By doing so, we found that the high-density oligonucleotide platforms are superior to the BAC platform for the genome-wide detection of copy-number variations smaller than 1 Mb. The capacity to reliably detect single copy-number variations below 100 kb, however, appeared to be limited for all platforms tested. In addition, our analysis revealed an unexpected platform-dependent difference in sensitivity to detect a single copy-number loss and a single copy-number gain. These analyses provide a first objective insight into the true capacities and limitations of different genomic microarrays to detect and define DNA copy-number variations

Systematic discovery of gene fusions in pediatric cancer by integrating RNA-seq and WGS

Background: Gene fusions are important cancer drivers in pediatric cancer and their accurate detection is essential for diagnosis and treatment. Clinical decision-making requires high confidence and precision of detection. Recent developments show RNA sequencing (RNA-seq) is promising for genome-wide detection of fusion products but hindered by many false positives that require extensive manual curation and impede discovery of pathogenic fusions. Methods: We developed Fusion-sq to overcome existing disadvantages of detecting gene fusions. Fusion-sq integrates and “fuses” evidence from RNA-seq and whole genome sequencing (WGS) using intron–exon gene structure to identify tumor-specific protein coding gene fusions. Fusion-sq was then applied to the data generated from a pediatric pan-cancer cohort of 128 patients by WGS and RNA sequencing. Results: In a pediatric pan-cancer cohort of 128 patients, we identified 155 high confidence tumor-specific gene fusions and their underlying structural variants (SVs). This includes all clinically relevant fusions known to be present in this cohort (30 patients). Fusion-sq distinguishes healthy-occurring from tumor-specific fusions and resolves fusions in amplified regions and copy number unstable genomes. A high gene fusion burden is associated with copy number instability. We identified 27 potentially pathogenic fusions involving oncogenes or tumor-suppressor genes characterized by underlying SVs, in some cases leading to expression changes indicative of activating or disruptive effects. Conclusions: Our results indicate how clinically relevant and potentially pathogenic gene fusions can be identified and their functional effects investigated by combining WGS and RNA-seq. Integrating RNA fusion predictions with underlying SVs advances fusion detection beyond extensive manual filtering. Taken together, we developed a method for identifying candidate gene fusions that is suitable for precision oncology applications. Our method provides multi-omics evidence for assessing the pathogenicity of tumor-specific gene fusions for future clinical decision making

Improved Gene Fusion Detection in Childhood Cancer Diagnostics Using RNA Sequencing

PURPOSE: Gene fusions play a significant role in cancer etiology, making their detection crucial for accurate diagnosis, prognosis, and determining therapeutic targets. Current diagnostic methods largely focus on either targeted or low-resolution genome-wide techniques, which may be unable to capture rare events or both fusion partners. We investigate if RNA sequencing can overcome current limitations with traditional diagnostic techniques to identify gene fusion events. METHODS: We first performed RNA sequencing on a validation cohort of 24 samples with a known gene fusion event, after which a prospective pan-pediatric cancer cohort (n = 244) was tested by RNA sequencing in parallel to existing diagnostic procedures. This cohort included hematologic malignancies, tumors of the CNS, solid tumors, and suspected neoplastic samples. All samples were processed in the routine diagnostic workflow and analyzed for gene fusions using standard-of-care methods and RNA sequencing. RESULTS: We identified a clinically relevant gene fusion in 83 of 244 cases in the prospective cohort. Sixty fusions were detected by both routine diagnostic techniques and RNA sequencing, and one fusion was detected only in routine diagnostics, but an additional 24 fusions were detected solely by RNA sequencing. RNA sequencing, therefore, increased the diagnostic yield by 38%-39%. In addition, RNA sequencing identified both gene partners involved in the gene fusion, in contrast to most routine techniques. For two patients, the newly identified fusion by RNA sequencing resulted in treatment with targeted agents. CONCLUSION: We show that RNA sequencing is sufficiently robust for gene fusion detection in routine diagnostics of childhood cancers and can make a difference in treatment decisions

Mesenchymal tumor organoid models recapitulate rhabdomyosarcoma subtypes

Rhabdomyosarcomas (RMS) are mesenchyme-derived tumors and the most common childhood soft tissue sarcomas. Treatment is intense, with a nevertheless poor prognosis for high-risk patients. Discovery of new therapies would benefit from additional preclinical models. Here, we describe the generation of a collection of 19 pediatric RMS tumor organoid (tumoroid) models (success rate of 41%) comprising all major subtypes. For aggressive tumors, tumoroid models can often be established within 4-8 weeks, indicating the feasibility of personalized drug screening. Molecular, genetic, and histological characterization show that the models closely resemble the original tumors, with genetic stability over extended culture periods of up to 6 months. Importantly, drug screening reflects established sensitivities and the models can be modified by CRISPR/Cas9 with TP53 knockout in an embryonal RMS model resulting in replicative stress drug sensitivity. Tumors of mesenchymal origin can therefore be used to generate organoid models, relevant for a variety of preclinical and clinical research questions