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• Advanced molecular neuropathology to increase diagnostic accuracy in pediatric neurooncology

  To assess their utility in routine neuropathology, we prospectively integrated DNA methylation-based CNS tumor classification and targeted gene panel sequencing of tumor and constitutional DNA with blinded neuropathological reference diagnostics for a population-based cohort of > 1,200 newly-diagnosed pediatric patients.

  Study EGAS00001006680

• Sequencing data on patients with Sezary Syndrome

  This dataset consists of sequencing data on 15 patients with Sezary syndrome. On 12 of these patients, we have exome sequencing data while on 10 patients, we have RNA sequencing data. In total for seven patients, we have both exome as well as RNA sequencing data. We looked for gene mutations and fusion events in these patients to identify genes that could be involved in the pathogenesis of the disease.

  Dataset EGAD00001001998

• Chromatin accessability in cytokine induced immune cell states (2019-03-11)

  We isolated T cells and monocotyes from healthy platelet donors and cultured them in resting and stimulated conditions with addition of a range of cytokines. We performed ATAC sequencing to assess the chromatin accessability in different cytokines treated cells. These cellular profiles were used to map risk variants to the cytokine-induced cell states relevant for autoimmune diseases. . This dataset contains all the data available for this study on 2019-03-11.

  Dataset EGAD00001004831

• Chromatin accessability in cytokine induced immune cell states (2019-03-19)

  We isolated T cells and monocotyes from healthy platelet donors and cultured them in resting and stimulated conditions with addition of a range of cytokines. We performed K27Ac ChM sequencing to assess the chromatin activity in different cytokines treated cells. These cellular profiles were used to map risk variants to the cytokine-induced cell states relevant for autoimmune diseases. . This dataset contains all the data available for this study on 2019-03-19.

  Dataset EGAD00001004852

• ChIPseq data

  ChIPseq data for H3K4me1 and H3K9me3 in HT29; H3K4me1, H3K27me3, H3K9me3, H3K36me3 in LoVo.

  Dataset EGAD00001003258

• Biallelic loss of function PAX4 variants are a Novel Cause of Transient Neonatal Diabetes

  The identification of genes in which loss of function (LoF) variants cause neonatal diabetes mellitus (NDM) can provide unique insights into the development and function of human pancreatic beta cells. We describe the identification of biallelic PAX4 LoF variants in 2 unrelated individuals with transient NDM: one due to a homozygous p.(Arg126*) PAX4 stop gain variant and a second due to a homozygous c.-352_104del 2.65kb deletion affecting the first 4 exons and promoter of the PAX4 Matched Annotation from NCBI and EMBL-EBI select transcript. We confirmed reduced transcript expression due to nonsense mediated decay for the e p.(Arg126*) variant in CRISPR-edited iPSC-derived pancreatic endoderm cells. Analysis of PAX4 binding through integration of CUT&RUN and RNA-sequencing in PAX4 depleted endocrine cells identified genes directly regulated by PAX4 involved in both pancreatic islet development and glucose-sensitive insulin secretion. The remitting and relapsing diabetes in both probands demonstrates that in contrast to mice PAX4 is not essential for the development of pancreatic beta-cells and supports differences in the requirements of functional beta-cell mass across the life-course.

  Study EGAS50000000857

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• Cisplatin increases sensitivity to FGFR inhibition in patient-derived xenograft models of lung squamous cell carcinoma

  Lung squamous cell carcinoma (SqCC) is a molecularly complex and genomically unstable disease. No targeted therapy is currently approved for lung SqCC, although potential oncogenic drivers of SqCC have been identified, including amplification of the fibroblast growth factor receptor 1 (FGFR1). Reports from a recently completed clinical trial indicate low response rates in patients treated with FGFR tyrosine kinase inhibitors, suggesting inadequacy of FGFR1 amplification as a biomarker of response, or the need for combination treatment. We aimed to develop accurate models of lung SqCC and determine improved targeted therapies for these tumors. We show that detection of FGFR1 mRNA by RNA in situ hybridisation is a better predictor of response to FGFR inhibition than FGFR1 gene amplification using clinically relevant patient-derived xenograft (PDX) models of lung SqCC. FGFR1-overexpressing tumors were observed in all histological subtypes of non-small cell lung cancers (NSCLC) as assessed on a tissue microarray, indicating a broader range of tumors that may respond to FGFR inhibitors. In FGFR1-overexpressing PDX tumors, we observed increased differentiation and reduced proliferation following FGFR inhibition. Combination therapy with cisplatin was able to increase tumor cell death, and dramatically prolonged animal survival compared to single agent treatment. Our data suggest that FGFR tyrosine kinase inhibitors can benefit NSCLC patients with FGFR1-overexpressing tumors and provides a rationale for clinical trials combining cisplatin with FGFR inhibitors.

  Study EGAS00001002423

• single nuclei multiomics (ATAC-RNA) of KOLF2.1J human induced pluripotent stem cells-derived differentiated dopaminergic neurons

  We processed nuclei from hIPSCs differentiated optimized protocols for generating dopaminergic neurons. Cells differentiated with a first iteration were RNA and ATAC-sequenced, to understand our protocol caveats to address for optimization. Cells differentiated with a second protocol and in vivo were RNA-sequenced to validate the identities of our cells.

  Study EGAS50000001418

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  We performed the single nuclei Assay for Transposase-Accessible Chromatin with Sequencing (snATAC-Seq) to map potential regulatory genomic regions operating in individual cell populations of the human GE, using these to test for enrichment of schizophrenia common genetic variant liability and to functionally annotate non-coding variants associated with the disorder.

  Study EGAS50000000411