Spectrum and prevalence of genetic predisposition in medulloblastoma: a retrospective genetic study and prospective validation in a clinical trial cohort.

BACKGROUND: Medulloblastoma is associated with rare hereditary cancer predisposition syndromes; however, consensus medulloblastoma predisposition genes have not been defined and screening guidelines for genetic counselling and testing for paediatric patients are not available. We aimed to assess and define these genes to provide evidence for future screening guidelines. METHODS: In this international, multicentre study, we analysed patients with medulloblastoma from retrospective cohorts (International Cancer Genome Consortium [ICGC] PedBrain, Medulloblastoma Advanced Genomics International Consortium [MAGIC], and the CEFALO series) and from prospective cohorts from four clinical studies (SJMB03, SJMB12, SJYC07, and I-HIT-MED). Whole-genome sequences and exome sequences from blood and tumour samples were analysed for rare damaging germline mutations in cancer predisposition genes. DNA methylation profiling was done to determine consensus molecular subgroups: WNT (MBWNT), SHH (MBSHH), group 3 (MBGroup3), and group 4 (MBGroup4). Medulloblastoma predisposition genes were predicted on the basis of rare variant burden tests against controls without a cancer diagnosis from the Exome Aggregation Consortium (ExAC). Previously defined somatic mutational signatures were used to further classify medulloblastoma genomes into two groups, a clock-like group (signatures 1 and 5) and a homologous recombination repair deficiency-like group (signatures 3 and 8), and chromothripsis was investigated using previously established criteria. Progression-free survival and overall survival were modelled for patients with a genetic predisposition to medulloblastoma. FINDINGS: We included a total of 1022 patients with medulloblastoma from the retrospective cohorts (n=673) and the four prospective studies (n=349), from whom blood samples (n=1022) and tumour samples (n=800) were analysed for germline mutations in 110 cancer predisposition genes. In our rare variant burden analysis, we compared these against 53 105 sequenced controls from ExAC and identified APC, BRCA2, PALB2, PTCH1, SUFU, and TP53 as consensus medulloblastoma predisposition genes according to our rare variant burden analysis and estimated that germline mutations accounted for 6% of medulloblastoma diagnoses in the retrospective cohort. The prevalence of genetic predispositions differed between molecular subgroups in the retrospective cohort and was highest for patients in the MBSHH subgroup (20% in the retrospective cohort). These estimates were replicated in the prospective clinical cohort (germline mutations accounted for 5% of medulloblastoma diagnoses, with the highest prevalence [14%] in the MBSHH subgroup). Patients with germline APC mutations developed MBWNT and accounted for most (five [71%] of seven) cases of MBWNT that had no somatic CTNNB1 exon 3 mutations. Patients with germline mutations in SUFU and PTCH1 mostly developed infant MBSHH. Germline TP53 mutations presented only in childhood patients in the MBSHH subgroup and explained more than half (eight [57%] of 14) of all chromothripsis events in this subgroup. Germline mutations in PALB2 and BRCA2 were observed across the MBSHH, MBGroup3, and MBGroup4 molecular subgroups and were associated with mutational signatures typical of homologous recombination repair deficiency. In patients with a genetic predisposition to medulloblastoma, 5-year progression-free survival was 52% (95% CI 40-69) and 5-year overall survival was 65% (95% CI 52-81); these survival estimates differed significantly across patients with germline mutations in different medulloblastoma predisposition genes. INTERPRETATION: Genetic counselling and testing should be used as a standard-of-care procedure in patients with MBWNT and MBSHH because these patients have the highest prevalence of damaging germline mutations in known cancer predisposition genes. We propose criteria for routine genetic screening for patients with medulloblastoma based on clinical and molecular tumour characteristics. FUNDING: German Cancer Aid; German Federal Ministry of Education and Research; German Childhood Cancer Foundation (Deutsche Kinderkrebsstiftung); European Research Council; National Institutes of Health; Canadian Institutes for Health Research; German Cancer Research Center; St Jude Comprehensive Cancer Center; American Lebanese Syrian Associated Charities; Swiss National Science Foundation; European Molecular Biology Organization; Cancer Research UK; Hertie Foundation; Alexander and Margaret Stewart Trust; V Foundation for Cancer Research; Sontag Foundation; Musicians Against Childhood Cancer; BC Cancer Foundation; Swedish Council for Health, Working Life and Welfare; Swedish Research Council; Swedish Cancer Society; the Swedish Radiation Protection Authority; Danish Strategic Research Council; Swiss Federal Office of Public Health; Swiss Research Foundation on Mobile Communication; Masaryk University; Ministry of Health of the Czech Republic; Research Council of Norway; Genome Canada; Genome BC; Terry Fox Research Institute; Ontario Institute for Cancer Research; Pediatric Oncology Group of Ontario; The Family of Kathleen Lorette and the Clark H Smith Brain Tumour Centre; Montreal Children's Hospital Foundation; The Hospital for Sick Children: Sonia and Arthur Labatt Brain Tumour Research Centre, Chief of Research Fund, Cancer Genetics Program, Garron Family Cancer Centre, MDT's Garron Family Endowment; BC Childhood Cancer Parents Association; Cure Search Foundation; Pediatric Brain Tumor Foundation; Brainchild; and the Government of Ontario

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

A generally applicable lightweight method for calculating a value structure for tools and services in bioinformatics infrastructure projects

Mayer G, Quast C, Felden J, et al. A generally applicable lightweight method for calculating a value structure for tools and services in bioinformatics infrastructure projects. BRIEFINGS IN BIOINFORMATICS. 2019;20(4):1215-1221.Sustainable noncommercial bioinformatics infrastructures are a prerequisite to use and take advantage of the potential of big data analysis for research and economy. Consequently, funders, universities and institutes as well as users ask for a transparent value model for the tools and services offered. In this article, a generally applicable lightweight method is described by which bioinformatics infrastructure projects can estimate the value of tools and services offered without determining exactly the total costs of ownership. Five representative scenarios for value estimation from a rough estimation to a detailed breakdown of costs are presented. To account for the diversity in bioinformatics applications and services, the notion of service-specific 'service provision units' is introduced together with the factors influencing them and the main underlying assumptions for these 'value influencing factors'. Special attention is given on how to handle personnel costs and indirect costs such as electricity. Four examples are presented for the calculation of the value of tools and services provided by the German Network for Bioinformatics Infrastructure (de.NBI): one for tool usage, one for (Web-based) database analyses, one for consulting services and one for bioinformatics training events. Finally, from the discussed values, the costs of direct funding and the costs of payment of services by funded projects are calculated and compared

Time-Lapse Imaging of Neuroblastoma Cells to Determine Cell Fate upon Gene Knockdown

<div><p>Neuroblastoma is the most common extra-cranial solid tumor of early childhood. Standard therapies are not effective in case of poor prognosis and chemotherapy resistance. To improve drug therapy, it is imperative to discover new targets that play a substantial role in tumorigenesis of neuroblastoma. The mitotic machinery is an attractive target for therapeutic interventions and inhibitors can be developed to target mitotic entry, spindle apparatus, spindle activation checkpoint, and mitotic exit. We present an elaborate analysis pipeline to determine cancer specific therapeutic targets by first performing a focused gene expression analysis to select genes followed by a gene knockdown screening assay of live cells. We interrogated gene expression studies of neuroblastoma tumors and selected 240 genes relevant for tumorigenesis and cell cycle. With these genes we performed time-lapse screening of gene knockdowns in neuroblastoma cells. We classified cellular phenotypes and used the temporal context of the perturbation effect to determine the sequence of events, particularly the mitotic entry preceding cell death. Based upon this phenotype kinetics from the gene knockdown screening, we inferred dynamic gene functions in mitosis and cell proliferation. We identified six genes (<em>DLGAP5</em>, <em>DSCC1</em>, <em>SMO</em>, <em>SNRPD1</em>, <em>SSBP1</em>, and <em>UBE2C</em>) with a vital role in mitosis and these are promising therapeutic targets for neuroblastoma. Images and movies of every time point of all screened genes are available at <a href="https://ichip.bioquant.uni-heidelberg.de">https://ichip.bioquant.uni-heidelberg.de</a>.</p> </div

Time series of interphase cells during five days of screening.

<p>The population shows a periodicity of ∼35 hours representing the cell cycle duration (blue bars: interphase counts (normalized by B-Score normalization) of all screened cells for each time-frame, red curve: fitting curve).</p

Determination of candidate genes that show cell death during or after mitosis.

<p>The population response to a knockdown was computed to identify the sequence of phenotype occurrence.</p

The landscape of genomic alterations across childhood cancers

Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7-8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trial