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• Cerebral organoid model reveals excessive proliferation of human caudal late interneuron progenitors in Tuberous Sclerosis Complex

  Although the intricate and prolonged development of the human brain critically distinguishes it from other mammals, our current understanding of neurodevelopmental diseases is largely based on work using animal models. Recent studies revealed that neural progenitors in the human brain are profoundly different from those found in rodent animal models. Moreover, post-mortem studies revealed extensive migration of interneurons into the late-gestational and post-natal human prefrontal cortex that does not occur in rodents. Here, we use cerebral organoids to show that overproduction of mid-gestational human interneurons causes Tuberous Sclerosis Complex (TSC), a severe neuro-developmental disorder associated with mutations in TSC1 and TSC2. We identify a previously uncharacterized population of caudal late interneuron progenitors, the CLIP-cells. In organoids derived from patients carrying heterozygous TSC2 mutations, dysregulation of mTOR signaling leads to CLIP-cell over-proliferation and formation of cortical tubers and subependymal tumors. Surprisingly, second-hit events resulting from copy-neutral loss-of-heterozygosity (cnLOH) are not causative for but occur during the progression of tumor lesions. Instead, EGFR signaling is required for tumor proliferation, opening up a promising approach to treat TSC lesions. Our study demonstrates that the analysis of developmental disorders in organoid models can lead to fundamental insights into human brain development and neuropsychiatric disorders.

  Study EGAS00001004586

• Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

  Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

  Study EGAS00001004289

• ICGC Benchmarking Exercise

  The main objective of this benchmark is the comparison of the full sequencing pipeline of different ICGC partners, including procedures, methods and performance of library preparation and whole-genome deep-sequencing. A secondary objective will be a follow-up comparison of data analysis pipelines for identification of germline and somatic variants subsequent to the results of the ICGC Somatic Variant Calling Pipeline Benchmark.

  Dataset EGAD00001000625

• BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples (DLBCL-panel)

  This dataset contains BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples for cases 2, 3, 4 and 13. The sequencing panel used is a DLBCL-oriented panel containing 136 genes, described in Mozas P. et al., Hematol Oncol 2023.

  Dataset EGAD50000000802

• Asan Medical Center Data Access Committee

  This DAC is responsible for reviewing and approving data access requests to protect the sensitive information of patients. The dataset includes RNA-seq data from CRLM patients treated with FOLFOX, bevacizumab, and atezolizumab, and supports research in gene expression analysis and therapeutic response. Data access requests require an approved ethical research plan, limited to projects related to cancer biology and therapy development.

  Dac EGAC50000000439

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• Methylation Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  3 sets of matched patient-derived-organoids (PDOs),  -neurospheres (PDNs), and parent glioblastoma tissue (9 samples total) underwent methylation array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Illumina EPIC v2.0 array. Data is provided as raw red and green .idat files.

  Dataset EGAD00010002745

• MissionBio single cell DNA and protein seq for 2 samples

  This dataset contains MissionBio Targeted single-cell DNA and Protein sequencing data from a primary sample and a patient-derived xenograft (PDX) model, which is used to investigate the clonal evolution in the FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001793

• bulk RNA-Seq samples of CRC patients

  The dataset contains samples of 30 CRC patients (3 samples for each patient, tumor and 2 normal adjacent tissue sites, 90 samples in total). Dataset is composed by fastq file (paired end) type from bulk RNA-Seq.

  Dataset EGAD00001009635

• Human Hi-C

  This dataset contains 2 human tumor-derived cell lines and 1 human tumor Hi-C samples. The raw fastq files and the processed .hic file is provided for each sample.

  Dataset EGAD00001009050