Explore the vast range of titles available.

Background Establishment of telomere maintenance mechanisms is a universal step in tumor development to achieve replicative immortality. These processes leave molecular footprints in cancer genomes in the form of altered telomere content and aberrations in telomere composition. To retrieve these telomere characteristics from high-throughput sequencing data the available computational approaches need to be extended and optimized to fully exploit the information provided by large scale cancer genome data sets. Results We here present TelomereHunter, a software for the detailed characterization of telomere maintenance mechanism footprints in the genome. The tool is implemented for the analysis of large cancer genome cohorts and provides a variety of diagnostic diagrams as well as machine-readable output for subsequent analysis. A novel key feature is the extraction of singleton telomere variant repeats, which improves the identification and subclassification of the alternative lengthening of telomeres phenotype. We find that whole genome sequencing-derived telomere content estimates strongly correlate with telomere qPCR measurements (r = 0.94). For the first time, we determine the correlation of in silico telomere content quantification from whole genome sequencing and whole genome bisulfite sequencing data derived from the same tumor sample (r = 0.78). An analogous comparison of whole exome sequencing data and whole genome sequencing data measured slightly lower correlation (r = 0.79). However, this is considerably improved by normalization with matched controls (r = 0.91). Conclusions TelomereHunter provides new functionality for the analysis of the footprints of telomere maintenance mechanisms in cancer genomes. Besides whole genome sequencing, whole exome sequencing and whole genome bisulfite sequencing are suited for in silico telomere content quantification, especially if matched control samples are available. The software runs under a GPL license and is available at https://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html .

With the number of prognostic and predictive genetic markers in neuro-oncology steadily growing, the need for comprehensive molecular analysis of neuropathology samples has vastly increased. We therefore developed a customized enrichment/hybrid-capture-based next-generation sequencing (NGS) gene panel comprising the entire coding and selected intronic and promoter regions of 130 genes recurrently altered in brain tumors, allowing for the detection of single nucleotide variations, fusions, and copy number aberrations. Optimization of probe design, library generation and sequencing conditions on 150 samples resulted in a 5-workday routine workflow from the formalin-fixed paraffin-embedded sample to neuropathological report. This protocol was applied to 79 retrospective cases with established molecular aberrations for validation and 71 prospective cases for discovery of potential therapeutic targets. Concordance of NGS compared to established, single biomarker methods was 98.0 %, with discrepancies resulting from one case where a TERT promoter mutation was not called by NGS and three ATRX mutations not being detected by Sanger sequencing. Importantly, in samples with low tumor cell content, NGS was able to identify mutant alleles that were not detectable by traditional methods. Information derived from NGS data identified potential targets for experimental therapy in 37/47 (79 %) glioblastomas, 9/10 (90 %) pilocytic astrocytomas, and 5/14 (36 %) medulloblastomas in the prospective target discovery cohort. In conclusion, we present the settings for high-throughput, adaptive next-generation sequencing in routine neuropathology diagnostics. Such an approach will likely become highly valuable in the near future for treatment decision making, as more therapeutic targets emerge and genetic information enters the classification of brain tumors.

Bringing together cancer genomes from different projects increases power and allows the investigation of pan-cancer, molecular mechanisms. However, working with whole genomes sequenced over several years in different sequencing centres requires a framework to compare the quality of these sequences. We used the Pan-Cancer Analysis of Whole Genomes cohort as a test case to construct such a framework. This cohort contains whole cancer genomes of 2832 donors from 18 sequencing centres. We developed a non-redundant set of five quality control (QC) measurements to establish a star rating system. These QC measures reflect known differences in sequencing protocol and provide a guide to downstream analyses and allow for exclusion of samples of poor quality. We have found that this is an effective framework of quality measures. The implementation of the framework is available at: https://dockstore.org/containers/quay.io/jwerner_dkfz/pancanqc:1.2.2 . Working with cancer genomes from multiple projects can increase investigative power, but quality of sequences can vary. Here, the authors present a framework for comparing whole genome sequencing quality to help researchers guide downstream analyses and exclude poor quality samples.

Cancer genomics has revealed many genes and core molecular processes that contribute to human malignancies, but the genetic and molecular bases of many rare cancers remains unclear. Genetic predisposition accounts for 5 to 10% of cancer diagnoses in children 1 , 2 , and genetic events that cooperate with known somatic driver events are poorly understood. Pathogenic germline variants in established cancer predisposition genes have been recently identified in 5% of patients with the malignant brain tumour medulloblastoma 3 . Here, by analysing all protein-coding genes, we identify and replicate rare germline loss-of-function variants across ELP1 in 14% of paediatric patients with the medulloblastoma subgroup Sonic Hedgehog (MB SHH ) . ELP1 was the most common medulloblastoma predisposition gene and increased the prevalence of genetic predisposition to 40% among paediatric patients with MB SHH . Parent–offspring and pedigree analyses identified two families with a history of paediatric medulloblastoma. ELP1 -associated medulloblastomas were restricted to the molecular SHHα subtype 4 and characterized by universal biallelic inactivation of ELP1 owing to somatic loss of chromosome arm 9q. Most ELP1 -associated medulloblastomas also exhibited somatic alterations in PTCH1 , which suggests that germline ELP1 loss-of-function variants predispose individuals to tumour development in combination with constitutive activation of SHH signalling. ELP1 is the largest subunit of the evolutionarily conserved Elongator complex, which catalyses translational elongation through tRNA modifications at the wobble (U 34 ) position 5 , 6 . Tumours from patients with ELP1 -associated MB SHH were characterized by a destabilized Elongator complex, loss of Elongator-dependent tRNA modifications, codon-dependent translational reprogramming, and induction of the unfolded protein response, consistent with loss of protein homeostasis due to Elongator deficiency in model systems 7 – 9 . Thus, genetic predisposition to proteome instability may be a determinant in the pathogenesis of paediatric brain cancers. These results support investigation of the role of protein homeostasis in other cancer types and potential for therapeutic interference. Germline mutations in the Elongator complex gene ELP1 predispose individuals to the development of childhood medulloblastoma.

Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and ‘enhancer hijacking’ events that activate PRDM6 . Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma. Genomic analysis of 491 medulloblastoma samples, including methylation profiling of 1,256 cases, effectively assigns candidate drivers to most tumours across all molecular subgroups. Genomic landscapes of medulloblastomas Medulloblastomas are highly malignant brain tumours that develop during childhood. Paul Northcott and colleagues analysed the whole-genome sequences of 491 medulloblastomas in order to characterize the genomic landscape across tumours and identify new drivers and mutational signatures. Their integrative genomic analyses, including methylation profiling of 1,256 medulloblastomas, identifies subgroup-specific driver mutations and suggests additional tumour subtypes. The authors assign driver mutations to a high proportion of the less well characterized Group 3 and Group 4, which together contribute to more than 60% of all medulloblastomas.

The large diversity of central nervous system (CNS) tumor types in children and adolescents results in disparate patient outcomes and renders accurate diagnosis challenging. In this study, we prospectively integrated DNA methylation profiling and targeted gene panel sequencing with blinded neuropathological reference diagnostics for a population-based cohort of more than 1,200 newly diagnosed pediatric patients with CNS tumors, to assess their utility in routine neuropathology. We show that the multi-omic integration increased diagnostic accuracy in a substantial proportion of patients through annotation to a refining DNA methylation class (50%), detection of diagnostic or therapeutically relevant genetic alterations (47%) or identification of cancer predisposition syndromes (10%). Discrepant results by neuropathological WHO-based and DNA methylation-based classification (30%) were enriched in histological high-grade gliomas, implicating relevance for current clinical patient management in 5% of all patients. Follow-up (median 2.5 years) suggests improved survival for patients with histological high-grade gliomas displaying lower-grade molecular profiles. These results provide preliminary evidence of the utility of integrating multi-omics in neuropathology for pediatric neuro-oncology. The integration of DNA methylation profiling and targeted sequencing with neuropathology improves the diagnostic accuracy of central nervous system tumors in a population-based cohort of more than 1,200 newly diagnosed pediatric patients.

Young children with medulloblastoma have a poor overall survival compared with older children, due to use of radiation-sparing therapy in young children. Radiotherapy is omitted or reduced in these young patients to spare them from debilitating long-term side-effects. We aimed to estimate event-free survival and define the molecular characteristics associated with progression-free survival in young patients with medulloblastoma using a risk-stratified treatment strategy designed to defer, reduce, or delay radiation exposure. In this multicentre, phase 2 trial, we enrolled children younger than 3 years with newly diagnosed medulloblastoma at six centres in the USA and Australia. Children aged 3–5 years with newly diagnosed, non-metastatic medulloblastoma without any high-risk features were also eligible. Eligible patients were required to start therapy within 31 days from definitive surgery, had a Lansky performance score of at least 30, and did not receive previous radiotherapy or chemotherapy. Patients were stratified postoperatively by clinical and histological criteria into low-risk, intermediate-risk, and high-risk treatment groups. All patients received identical induction chemotherapy (methotrexate, vincristine, cisplatin, and cyclophosphamide), with high-risk patients also receiving an additional five doses of vinblastine. Induction was followed by risk-adapted consolidation therapy: low-risk patients received cyclophosphamide (1500 mg/m2 on day 1), etoposide (100 mg/m2 on days 1 and 2), and carboplatin (area under the curve 5 mg/mL per min on day 2) for two 4-week cycles; intermediate-risk patients received focal radiation therapy (54 Gy with a clinical target volume of 5 mm over 6 weeks) to the tumour bed; and high-risk patients received chemotherapy with targeted intravenous topotecan (area under the curve 120–160 ng-h/mL intravenously on days 1–5) and cyclophosphamide (600 mg/m2 intravenously on days 1–5). After consolidation, all patients received maintenance chemotherapy with cyclophosphamide, topotecan, and erlotinib. The coprimary endpoints were event-free survival and patterns of methylation profiling associated with progression-free survival. Outcome and safety analyses were per protocol (all patients who received at least one dose of induction chemotherapy); biological analyses included all patients with tissue available for methylation profiling. This trial is registered with ClinicalTrials.gov, number NCT00602667, and was closed to accrual on April 19, 2017. Between Nov 27, 2007, and April 19, 2017, we enrolled 81 patients with histologically confirmed medulloblastoma. Accrual to the low-risk group was suspended after an interim analysis on Dec 2, 2015, when the 1-year event-free survival was estimated to be below the stopping rule boundary. After a median follow-up of 5·5 years (IQR 2·7–7·3), 5-year event-free survival was 31·3% (95% CI 19·3–43·3) for the whole cohort, 55·3% (95% CI 33·3–77·3) in the low-risk cohort (n=23) versus 24·6% (3·6–45·6) in the intermediate-risk cohort (n=32; hazard ratio 2·50, 95% CI 1·19–5·27; p=0·016) and 16·7% (3·4–30·0) in the high-risk cohort (n=26; 3·55, 1·66–7·59; p=0·0011; overall p=0·0021). 5-year progression-free survival by methylation subgroup was 51·1% (95% CI 34·6–67·6) in the sonic hedgehog (SHH) subgroup (n=42), 8·3% (95% CI 0·0–24·0%) in the group 3 subgroup (n=24), and 13·3% (95% CI 0·0–37·6%) in the group 4 subgroup (n=10). Within the SHH subgroup, two distinct methylation subtypes were identified and named iSHH-I and iSHH-II. 5-year progression-free survival was 27·8% (95% CI 9·0–46·6; n=21) for iSHH-I and 75·4% (55·0–95·8; n=21) for iSHH-II. The most common adverse events were grade 3–4 febrile neutropenia (48 patients [59%]), neutropenia (21 [26%]), infection with neutropenia (20 [25%]), leucopenia (15 [19%]), vomiting (15 [19%]), and anorexia (13 [16%]). No treatment-related deaths occurred. The risk-adapted approach did not improve event-free survival in young children with medulloblastoma. However, the methylation subgroup analyses showed that the SHH subgroup had improved progression-free survival compared with the group 3 subgroup. Moreover, within the SHH subgroup, the iSHH-II subtype had improved progression-free survival in the absence of radiation, intraventricular chemotherapy, or high-dose chemotherapy compared with the iSHH-I subtype. These findings support the development of a molecularly driven, risk-adapted, treatment approach in future trials in young children with medulloblastoma. American Lebanese Syrian Associated Charities, St Jude Children's Research Hospital, NCI Cancer Center, Alexander and Margaret Stewart Trust, Sontag Foundation, and American Association for Cancer Research.

Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoral heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and group 4 subgroup medulloblastomas account for most paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified. Here we describe a series of prevalent, highly disparate genomic structural variants, restricted to groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family proto-oncogenes, GFI1 and GFI1B. Somatic structural variants juxtapose GFI1 or GFI1B coding sequences proximal to active enhancer elements, including super-enhancers, instigating oncogenic activity. Our results, supported by evidence from mouse models, identify GFI1 and GFI1B as prominent medulloblastoma oncogenes and implicate ‘enhancer hijacking’ as an efficient mechanism driving oncogene activation in a childhood cancer. Focusing on two ill-characterized subtypes of medulloblastoma (group 3 and group 4), this study identifies prevalent genomic structural variants that are restricted to these two subtypes and independently bring together coding regions of GFI1 family proto-oncogenes with active enhancer elements, leading to their mutually exclusive oncogenic activation. Oncogenesis through enhancer hijacking Medulloblastoma is a highly malignant paediatric brain tumour. Here the authors focus on two ill-characterized subtypes — group 3 and group 4 — which account for the majority of paediatric cases. They identify prevalent genomic structural variants, which are restricted to these two subtypes, and bring together coding regions of proto-oncogenes, GFI1 and GFI1B , and active enhancer elements leading to oncogene activation. This work identifies 'enhancer hijacking' as an efficient mechanism driving oncogene activation in a childhood cancer.

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy. Cancer genetics has benefited from the advent of next generation sequencing, yet a comparison of sequencing and analysis techniques is lacking. Here, the authors sequence a normal-tumour pair and perform data analysis at multiple institutes and highlight some of the pitfalls associated with the different methods.