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• Robust methylation-based classification of brain tumours using nanopore sequencing

  Background: DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro-oncology. However, current implementations using hybridization microarrays are time-consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows to discriminate a wide spectrum of primary brain tumours. Results: Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on N=382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of N = 56 cases, we find that a minimum set of 1,000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as confidence measure for interpretation in a clinical context and empirically determined a platform-specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut-off to an independent validation series (N = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100 % specificity. Cross-lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), median time to results was 21.1 hours. Conclusions: In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumours. Platform-specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.

  Study EGAS00001006540

• Whole Exome Sequencing data of six chRCC tumors corresponding to three patients

  Mammalian target of rapamycin (mTOR) is a central regulator of mammalian metabolism and physiology. Aberrant hyperactivation of the mTOR pathway promotes tumor growth and metastasis, and can also promote tumor resistance to chemotherapy and cancer drugs; this makes mTOR an attractive cancer therapeutic target. mTOR inhibitors have been approved to treat cancer; however, the mechanisms underlying drug sensitivity remain poorly understood. Here, whole exome sequencing of three chromophobe renal cell carcinoma (chRCC) patients with exceptional mTOR inhibitor sensitivity revealed that all three patients shared somatic mutations in the deubiquitinase USP9X. The clonal characteristics of the mutations, which were amassed by studying multiple patients’ primary and metastatic samples from various years, together with the low USP9X mutation rate in unselected chRCC series, reinforced a causal link between USP9X and mTOR inhibitor sensitivity. Rapamycin treatment of USP9X-depleted HeLa and renal cancer 786-O cells, along with the pharmacological inhibition of USP9X, confirmed that this protein plays a role in patients’ sensitivity to mTOR inhibition. USP9X was not found to exert a direct effect on mTORC1, but subsequent ubiquitylome analyses identified p62 as a direct USP9X target. Increased p62 ubiquitination and the augmented rapamycin effect upon bortezomib treatment, together with the results of p62 and LC3 immunofluorescence assays, suggested that dysregulated autophagy in USP9X-depleted cells can have a synergistic effect with mTOR inhibitors. In summary, we show that USP9X constitutes a potential novel marker of sensitivity to mTOR inhibitors in chRCC patients, and represents a clinical strategy for increasing the sensitivity to these drugs.

  Study EGAS00001007104

• Clonal fitness inferred from timeseries modeling of single cell cancer genomes

  Progress in defining genomic fitness landscapes in cancer by copy number alterations (CNA) has been impeded by lack of single cell and timeseries sampling. We generated 42,000 single cell whole genomes (scWGS) from breast epithelium and primary triple negative breast cancer (TNBC) patient-derived xenografts (PDX) collected during multi-year time series. Using a Wright-Fisher population genetics model, we inferred reproducible CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy, with accurate forecasting of experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDX resulted in cisplatin resistant clones that had shown low fitness in the untreated setting. By contrast high fitness clones from treatment naive controls were eradicated reflecting an inversion of the fitness landscape. Upon drug release selective pressure dynamics were reversed indicating a fitness cost of treatment resistance. Taken together, our findings reveal clonal fitness dynamics linked to CNA and therapeutic resistance in polyclonal tumours.

  Study EGAS00001004448

• DNA methylation in rhabdomyosarcoma PDX and PDX-derived primary cells

  Conditions to maintain primary tumor cells in culture are largely unknown for most tumor entities including rhabdomyosarcoma. In this collaborative study with Dr. Beat Schäfer's laboratory, we performed DNA methylation profiles of rhabdomyosarcoma patient-derived xenograft (PDX) and their matching PDX-derived primary cells (PPC), where the PPCs were developed and maintained under optimized culture conditions. We further compared DNA methylation profiles between these PDXs and PPCs. Exome sequencing and copy number analysis between these rhabdomyosarcoma PDXs and PPXs were also carried out. These analyses may help us to evaluate a feasibility of in vitro profiling of primary rhabdomyosarcoma cells from a genomic perspective.

  Study phs002051

• Mechanisms of Chemotherapy Resistance in T-ALL

  The goals of this study are to unravel the molecular mechanisms underlying leukemic transformation and chemotherapy resistance in T-cell acute lymphoblastic leukemia (T-ALL). Towards this end, a cohort of T-ALL lymphoblast specimens was collected at the time of initial T-ALL diagnosis (prior to the start of therapy) from children enrolled on contemporary clinical trials, Children's Oncology Group study AALL0434 and Dana-Farber Cancer Institute 05-001. Samples were analyzed using targeted exon sequencing and RNA sequencing analysis. Results of these analyses form the basis of studies that have been submitted for publication, and will be linked to this entry once published.

  Study phs001513

• Genomic DNA analysis for malignant mesothelioma from the patients of Japan and USA.

  Malignant mesotheliomas (MMs) are highly aggressive adult malignancies and exposure to asbestos is the major factor involved in MM pathogenesis. It is desirable for a better understanding of the molecular pathogenesis of MM will lead to more specific and effective targeted therapies. In addition it is reported that germline mutation in a specific gene (ex. BAP1) associates familial MMs, and new candidate markers to determine a subject?s predisposition to MM and for early detection need to be identified. Analysis of genomic DNA from MM tumors and reference peripheral blood from Japan and USA are ongoing to find the common genomic characters beyond race.

  Study JGAS000108

• Comparison of the performance of two commercial genome-wide association study genotyping platforms in Han Chinese Samples

  Affymetrix 6.0, Illumina OMNIExpress, and llumina Immunochip genotype data for Han Chinese population including rheumatoid arthritis cases and controls. Data is in PLINK binary format. Illumina genotype clustering was performed using Illumina’s BeadStudio software. SNPs were reclustered using the study samples, low quality subjects were removed, and a subset of clustering results were manually inspected and verified. All SNPs with GenCall scores less than 0.15 were excluded. For Affymetrix chips, clustering was performed using the program Birdseed version 2, as implemented using Affymetrix Genotyper Console v4.0, using the default quality control (QC) thresholds.

  Study EGAS00000000131

• Raw multi-omics dataset from the lungNENomics cohort of lung neuroendocrine tumours

  This study contains raw multi-omics data generated as part of the lungNENomics project, a multi-omics study aimed at deep molecular profiling of lung neuroendocrine tumours, including typical carcinoids (grade 1) and atypical carcinoids (grade 2). The study includes whole-genome sequencing (WGS), RNA sequencing (RNA-seq), and Infinium MethylationEPIC array data from samples in the lungNENomics cohort. These raw data complement the associated processed molecular data released on Zenodo (10.5281/zenodo.19366762) and the corresponding whole-slide pathology images deposited in the EBI BioImage Archive (10.6019/S-BIAD3143). See Sexton-Oates et al medrxiv 2025 (https://www.medrxiv.org/content/10.1101/2025.07.18.25331556v1) for details.

  Study EGAS00001005979

• Host genotyping data from Dutch adult bacterial meningitis patients and linked bacterial genome sequences

  Streptococcus pneumoniae is a common nasopharyngeal colonizer, but can also cause life-threatening invasive diseases such as empyema, bacteremia and meningitis. Genetic variation of host and pathogen is known to play a role in invasive pneumococcal disease, though to what extent is unknown. This study includes 1146 samples of host genotyping data (genotyped and imputed) from Illumina Omni arrays. Samples were collected from adults (>16 yrs) patients with CSF confirmed bacterial meningitis in the Netherlands between 2006 and 2015. Metadata includes patient outcome, species of bacteria, and for 467 samples a link to an ENA run with the associated bacterial genome (S. pneumoniae only).

  Study EGAS00001005993

• University of Washington Cerebrospinal Fluid Biomarker Study for Parkinson disease

  There is a clear need to develop biomarkers for Parkinson disease (PD) diagnosis and monitoring disease progression. In this study we evaluated cerebrospinal fluid (CSF) proteins, which are known to be critically involved in PD or identified in our preliminary profiling studies, aptamers, and RNAs as potential PD biomarkers. Access to subjects for this study was via the Pacific Northwest Udall Center (PANUC) and the Alzheimer's Disease Research Center (ADRC) at the University of Washington and Oregon Health and Sciences University (OHSU). Using CSF samples from 30 well-characterized patients with PD and 30 age-, sex-matched healthy controls, we prepared RNA seq libraries and performed deep sequencing of all RNA species, including small and long RNA, mRNAs, noncoding RNAs and differentially spliced transcripts. We then tried several methods for RNAseq data analysis to optimize our analysis pipeline. We identified a total of 3381 transcripts corresponding to 182 long intergenic RNAs (LincRNAs), 11 microRNAs (miRNAs), 2861 protein-coding transcripts, 200 pseudogenes and 127 antisense RNAs; some of them were differentially expressed between PD and control groups. Selected differentially expressed RNAs have been validated in the same set of CSF samples using real-time PCR (RT-PCR). Further validations in independent, larger cohorts of samples are still ongoing. Our results obtained so far suggested that CSF proteins and RNAs could be used as good indexes for PD diagnosis and disease severity/progression. This study is a part of the NIDDS-funded Parkinson's Disease Biomarkers Program (PDBP).

  Study phs000901