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• WHOLE GENOME SEQUENCING FOR THE CHARACTERIZATION OF CLEAR CELL RENAL CELL CARCINOMA IN VHL PATIENT

  To characterize clear cell Renal Cell Carcinoma (ccRCC), we set up a comprehensive multi-omics pilot study on a VHL-ccRCC-patient. Whole Genome Sequencing (WGS) was applied on six ccRCCs, four cysts and one blood DNA sample as germinal control. Raw-data were analyzed with GENomics-DRAGEN platform. We will upload WGS-Data for 11 samples (6 ccRCCs, 4 Cysts, 1 blood).

  Dataset EGAD50000000425

• Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer using Cell-Free DNA Fragmentomics

  The circulating tumor DNA (ctDNA) mutation-based approach shows limited performance in minimal residual disease (MRD) detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, A total of 87 NSCLC patients, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for high-throughput sequencing.

  Dataset EGAD00001010300

• Single-Cell Transcriptomic Characterisation of Patient-Derived Glioblastoma Cell Lines for Co-culture Modelling (Parse Evercode WT v3)

  Patient-derived glioblastoma (GBM) cell lines provide a tractable system to model tumour biology and enable functional studies. Here, we generate single-cell transcriptomic profiles of patient-derived GBM cell lines using Parse Evercode WT v3, including both standard and GFP-labelled variants. These datasets establish a transcriptional reference for subsequent co-culture experiments with patient-derived GBM organoids, enabling the study of cell–cell interactions and tumour microenvironment dynamics.

  Dataset EGAD00001016126

• Additional RNA-seq, ChIP-seq, and ATAC-seq files for PCGP SJERG

  This dataset contains RNA-seq, ATAC-seq, and ChIP-seq samples from the SJERG cohort. We applied ChIP-Seq for Dux4 on two B-cell ALL cell-lines(REH, Nalm6) along with INPUT. ATAC-Seq on two B-cell ALL cell-lines(REH, Nalm6) and xenograft of a B-cell ALL patient(ERG000016).

  Dataset EGAD00001002654

• Combination Therapies for Personalised Cancer Medicine in drug resistant EGFR mutant lung cancer (2019-06-10)

  This study involves mutagenizing a range of different cell lines with ENU to identify those mutations which engender resistance to targeted treatment. . This dataset contains all the data available for this study on 2019-06-10.

  Dataset EGAD00001005080

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas_LCM (2020-01-15)

  Samples prepared by LCM - 5 cases for pilot study. Bulk DNA not available. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005789

• Fine-mapping clustered GWAS hits enhances the identification of disease risk and protective genetic variants

  This dataset contains: 1) Raw FASTQ and BAM files for short reads. Here, DNA libraries were prepared using Nextera Rapid Capture Custom Enrichment kit (Illumina) and paired-end sequenced on a HiSeq2500 (Illumina). 2) Raw FASTQ and BAM files for long reads. Here, DNA libraries were prepared using 1D DNA ligation Sequencing Kit (SQK-LSK109, Oxford Nanopore) and single-end sequenced on a MinION device (Oxford Nanopore).

  Dataset EGAD00001006916

• Temporal Evolution Reveals Bifurcated Lineages in Aggressive Neuroendocrine Small Cell Prostate Cancer Trans-Differentiation

  Trans-differentiation from adenocarcinoma to small cell neuroendocrine (SCN) cancer is an adverse consequence of treatment escape in various cancers, including prostate, lung, and bladder cancers (Balanis and Sheu et al., PMID 31287989). Expression of dominant negative p53 (TP53DN), myrAkt1, RB1-shRNA, c-Myc, and Bcl2(PARCB forward transformation) using human naïve prostate basal epithelial cells recapitulated both transcriptional and histological characteristics of small cell neuroendocrine prostate cancer (NEPC) (Park et al., PMID 30287662). To study the temporal transcriptional landscape during this trans-differentiation process, we conducted a time course study using a PARCB model by integrating multi-omics sequencing, including bulk RNA-sequencing and ATAC-sequencing on samples taken at different time point, as well as single cell RNA sequencing on serial xenograft tumors. We found a common SCN pathway that resulted in two distinct end states defined by mutually exclusive expression of ASCL1 and ASCL2. Further investigation using CUT&RUN sequencing identified TFAP4 as a potential epigenetic regulator of both proteins. Our study reveals temporal and transcriptional changes from prostate adenocarcinoma to NEPC trans-differentiation.

  Study phs003230

• Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Study EGAS50000001313

• Oxidative DNA damage and ubiquitin proteasome system dysfunction underpins neurodegeneration in young adults with a DNA repair disorder

  Deposited here are time series bulk RNA-seq data generated from isogenic wild-type (WT), XPA and XPG gene knockouts hiPSC cells during cortical neuronal differentiation.

  Dataset EGAD50000000228

• Oxidative DNA damage and ubiquitin proteasome system dysfunction underpins neurodegeneration in young adults with a DNA repair disorder

  Deposited here are time series bulk RNA-seq data generated from XP patients and controls as well as rescued patient hiPSC cells during cortical neuronal differentiation.

  Dataset EGAD50000000230

• Sequence-based gene expression in uterine and ovarian carcinosarcomas

  Gynecologic carcinosarcomas (CS), including more generally uterine (endometrial) and less frequently ovarian localization, are histologically defined as biphasic neoplasms composed of carcinomatous (C) epithelial and sarcomatous (S) malignant components. We report a comprehensive analysis of 20 patients of macro-dissected samples of C and S components through RNA sequencing.

  Dataset EGAD00001009099

• Hi-C in endometrial healthy and tumor tissues

  Hi-C libraries have been prepared by enzymatic digestion with MboI restriction enzyme and sonication. Illumina single-indexig primers have been use to amplify ligated fragments. Hi-C experiments have been performed on 10 slices (30um thick) of fresh-frozen tissues derived from 3 healthy and 3 tumor endometrial tissues of post-menopausal patients. Raw paired-end fastq.gz files are provided.

  Dataset EGAD00001010898

• Discovery of Novel Melanoma Predisposing Mutations by Exome Sequencing

  Melanoma risk shows clear heritability, but the inherited genetic factors remain largely unknown. Rare high risk mutations in CDKN2A, CDK4, BAP1 and TERT have been described but these variants, in aggregate, account for less than 50% of the kindreds reporting a family history of melanoma. This project will seek to identify new genes which may confer melanoma susceptibility. Identifying melanoma predisposing mutations can provide new biological insights and may impact important clinical decision making regarding treatment, surveillance and preventive approaches. Hereditary melanoma patients (defined as those individuals with multiple primary melanomas and those patients with a family history of melanoma) were collected from melanoma clinics at the Massachusetts General Hospital in Boston and the A. Sygrous Hospital in Athens, Greece. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000823

• Deciphering craniopharyngioma subtypes: Single-cell analysis of tumor microenvironment and immune networks

  Craniopharyngiomas, including both adamantinomatous (ACP) and squamous papillary (PCP) types, present significant challenges in treatment due to their proximity to critical pituitary structures. In this study, we conducted a single-cell RNA analysis to examine the tumor microenvironments (TME) of ACP and PCP. Single-cell clustering revealed a wide range of cell types, which were further categorized based on gene expression patterns. For ACP, these categories included developing epithelia, calcification, and immune response, while PCP showed developing epithelia, cell cycle, and immune response as prominent categories. Subclustering analysis unveiled different types of immune cells in both ACP and PCP TMEs, with specific patterns of immune responses. Interestingly, smaller tumors were associated with particular immune cell ratios. Furthermore, we identified specific cell-to-cell interactions within the tumor cells. In conclusion, our study has led to the development of a comprehensive cell atlas, shedding light on the molecular characteristics and intricate interplay of immune cells within the TMEs of ACP and PCP.

  Study JGAS000722

• Single Cell Transcriptional Analysis of Human Adenoids Identifies Molecular Features of Airway Microfold Cells

  We aimed to characterize the cellular composition and molecular features of the human adenoid, a mucosa-associated lymphoid tissue located in the upper airway, with a focus on epithelial populations involved in immune surveillance. To this end, we performed single-nucleus RNA sequencing (snRNA-seq) on adenoid tissue obtained from 6 human donors (age 2 – 14; 3 males and 3 females) undergoing routine adenoidectomy. The donor cohort includes clinically annotated samples with no known immunodeficiency or chronic airway disease.Our analysis uncovered distinct epithelial populations, including transcriptionally defined immature and mature microfold (M) cells, and a previously unrecognized interferon-stimulated epithelial population enriched for antiviral response genes, which we term WISP cells (Waldeyer's ring Interferon-Stimulated Population). We validated key transcriptomic findings through multiplex immunofluorescence microscopy in independent donor tissues, confirming the spatial localization of WISP and M cells and their predicted interactions with specific immune subsets.

  Study phs004103

• scRNAseq for patients with immunodeficiency and HCs

  The NFAT family of transcription factors plays central roles in adaptive immunity in murine models, however, their contribution to human immune homeostasis remains poorly defined. In a multigenerational pedigree, we identified three patients carrying germline biallelic missense variants in NFATC1, presenting with recurrent infections, hypogammaglobulinemia and decreased antibody responses. The compound heterozygous NFATC1 variants identified in the patients caused decreased stability and reduced binding of DNA and interacting proteins. We observed defects in early activation and proliferation of T and B cells from these patients, amenable to reconstitution upon genetic rescue. Following stimulation, T-cell activation and proliferation were impaired, reaching that of healthy controls with delay indicative of an adaptive capacity of the cells. Assessment of the metabolic capacity of patient T cells, revealed that NFATc1-dysfunction rendered T cells unable to engage in glycolysis following stimulation, although oxidative metabolic processes were intact. We hypothesized that NFATc1-mutant T cells could compensate for the energy deficit due to defective glycolysis by enhanced lipid metabolism as an adaptation, leading to a delayed, but not lost activation responses. Indeed, we observed increased 13C-labelled palmitate incorporation into citrate indicating higher fatty acid oxidation and we demonstrated that metformin and rosiglitazone improved patient T-cell effector functions. Collectively, enabled by our molecular dissection of NFATC1 mutations and extending the role of NFATc1 in human immunity beyond receptor signaling, and reveal evidence of metabolic plasticity in the context of impaired glycolysis observed in patient T cells to remedy delayed effector responses.

  Study EGAS00001007271

• Peripheral T cell lymphoma (PTCL) Shallow Whole Genome Sequencing

  Shallow Whole Genome Sequencing (sWGS) of 148 FFPE DNA samples from peripheral T cell lymphoma (PTCL) samples. Assoicated with the "Molecular biomarkers for stratification peripheral T cell lymphoma" study.

  Dataset EGAD50000001146

• Whole exome sequencing of two BPDCN patients for tracing clonal evolution

  Whole exome sequencing data was mapped to GRCh38 using bwa-mem2 as implemented in the nfcore sarek workflow.

  Dataset EGAD50000000309

• banfora_20150706_autosomes

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 355 individuals from the VAC050 trial performed in Banfora, Burkina Faso - autosomes.

  Dataset EGAD00010002581

• Hypoxia acts as an environmental cue for the human TRM differentiation program

  Dataset consists of 19 bam files from RNA sequencing experiments batch1 and batch2.

  Dataset EGAD00001007692

• Long-read sequencing for cell-free DNA analysis (human pacbio)

  8 pregnant women at the 3rd trimesters, 4 hepatitis B carriers, and 4 patients with hepatocellular carcinoma

  Dataset EGAD00001009427

• NKI-AvL CRC-OVC RNA-seq

  The dataset “NKI-AvL CRC-OVC RNA-seq" includes 4 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004341

• Expression profiling of pediatric brain tumors Embryonal Tumor with Multilayered Rosettes (ETMR)

  RNA was prepared using the IlluminaTruSeq RNA sample preparation kit for poly-adenylated mRNA with an average of 97.64 million reads per sample respectively

  Dataset EGAD00001004803

• FASTQ Files for Human LV H3K27ac ChIP-seq

  This dataset contains 70 human LV H3K27ac ChIP-seq paired-end FASTQ files. The sequencing was performed using Illumina Hiseq 4000.

  Dataset EGAD00001004945

• ChIP-seq for GOF p53

  This dataset includes ChIP-seq data from two cell lines (HKCI-11 (GOFp53) and MIHA(WT p53)). All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001005449

• Whole Genome Sequencing of Normal Singaporean Volunteers

  Whole-genome sequencing (WGS) data for 546 Singaporean volunteers used to estimate WGS-LTL in the study. Samples were sequenced using Illumina Hiseq X to a mean coverage of 30X.

  Dataset EGAD00001005480

• long RNA data

  long RNA data for 27 CLL samples (8 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005968

• Sequencing files for 7 melanoma patients

  Files from whole exome sequencing of matched normals and multiple tumors from 7 melanoma patients. The tumors include primary tumors and distant metastases.

  Dataset EGAD00001006410

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• Whole exome and RNA sequencing of organoid samples derived from TRACERx patients

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘hot’) and non-evading (‘cold’) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008092

• Single-cell RNA sequencing of SI-NET

  Small intestinal neuroendocrine tumors (SI-NETs) arise from hormone-producing cells in the gut, yet the molecular changes driving malignant transformation remain poorly understood. Bulk tissue-based analyses make it challenging to distinguish signals derived from normal cells from those of normal hormone-producing cells. In this study, we analyzed SI-NETs at single-cell resolution and directly compared tumor cells with their corresponding normal hormone-producing counterparts using single-cell RNA sequencing. Tissue samples were obtained from two patients undergoing tumor resection surgery. Cells from corresponding normal intestinal mucosa and SI-NET tumors were isolated using specific markers and analyzed for direct comparison.

  Study EGAS50000001584

• The dataset for Detection and characterization of lung cancer using cell-free DNA fragmentomes

  The dataset for Detection and characterization of lung cancer using cell-free DNA fragmentomes includes 872 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD00001007796

• Transcriptomic changes in placenta associated with anesthesia, delivery mode and maternal diabetes

  Samples were from 34 mothers, 6 with gestational diabetes, 14 with type 1 diabetes and 14 without diabetes history with either vaginal (N=17) or cesarean section (n=17) delivery, comprising primary planned section (N=9) or secondary emergency section (N=8). Anesthesia methods during delivery included spinal (N=11), epidural (N=11), or local anesthesia (N=6), with unknown anesthesia information for six cases. Samples from each other were from the Villous and the Decidua part of the Placenta

  Dataset EGAD50000000701

• Raw sequencing data - Intra-tumor heterogeneity and clonal evolution patterns towards platinum-resistant high-grade serous ovarian cancer

  This dataset includes 69 sampels of whole-exome sequencing data of high-grade serous ovarian carcinoma (HGSOC). We included patients with advanced (International Federation of Gynecology and bstetrics [FIGO] stage IIIeIV) HGSOC for which biopsies were obtained during debulking surgery, the first at initial diagnosis and the second at disease relapse. Where possible, matched normal DNA from each participating patient was obtained from a whole-blood sample. Written informed consent was obtained from all patients and approved by the local ethics committee.

  Dataset EGAD00001001381

• Prevalence of transthyretin amyloidosis in patients with heart failure and no left ventricular hypertrophy

  The study prospectively enrolled patients admitted for HF with LV ejection fraction (LVEF) ≥ 50% and LV wall thickness <12 mm. TTR cardiac amyloidosis was diagnosed according to accepted criteria, which include positive cardiac 99-Tc-DPD scintigraphy in the absence of monoclonal protein expansion in blood. In a cohort of patients with HFpEF without LVH, the prevalence of TTR cardiac amyloidosis was 5%. Transthyretin gene sequencing was performed in positive patients.

  Dataset EGAD00001007787

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011192

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011193

• V(D)J and 5' Gene Expression data of bone marrow cells from patients with aplastic anemia

  Viably frozen blood MNCs from 9 cGVHD patients were sorted with BD Influx Cell sorter, to enrich for CD45+ cells. Gene and V(D)J transcript profiles were studied with 10x Genomics Chromium Single Cell Immune Profiling platform. The Chromium Single Cell 5’RNAseq run and library preparation were done using the Chromium Next GEM Single Cell Immune Profiling version 1.1 chemistry. The raw data was processed using Cell Ranger v3.1 pipelines.

  Dataset EGAD00001012117

• Whole-genome sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumoroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015707

• Single-cell RNA-sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumouroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015708

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015709

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015714

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015718

• RNASeq_EGAS00001001306

  RNASeq sequencing. Each library was sequenced using TruSeq SBS Kit v3-HS, in paired-end mode with a read length of 2 × 76 bp. We generated more than 20 million paired-end reads for each sample in a fraction of a sequencing lane on HiSeq2000 (Illumina Inc.) following the manufacturer’s protocol. Image analysis, base calling and quality scoring of the run were processed using the manufacturer’s software Real Time Analysis (RTA 1.13.48) and followed by generation of FASTQ sequence files.

  Dataset EGAD00001001443

• Small RNA-sequencing and RNA-sequencing data of tuberous sclerosis complex subependymal giant cell astrocytomas

  This data set contains small RNA-sequencing and RNA-sequencing data from subependymal giant cell astrocytomas (SEGA) resected from tuberous sclerosis complex patients. Small RNA-sequencing and RNA-sequencing were performed on the same set of SEGAs (n=19) and periventricular controls (n=8). For full details on library preparation and patients please refer to the paper "The coding and non-coding transcriptional landscape of subependymal giant cell astrocytomas." (PMID: 31834371 DOI: 10.1093/brain/awz370).

  Dataset EGAD00001005932

• Pediatric Glioblastoma with Persistent STAG2 Mutation

  This case represented the genomic findings of a pediatric glioblastoma patient who underwent multiple surgical resections and treated with standard chemoradiation, as well as a novel recombinant poliovirus vaccine therapy. The results present the preservation of a STAG2 mutated clone, besides elimination and emergence of other clones with oncogenic mutations through disease progression under different treatment modalities. Although STAG2 deficiency comprises only a small subset of gliomas, this case adds clinical evidence to existing preclinical data supporting a role for STAG2 mutations in gliomagenesis and resistance to standard therapies.

  Dataset EGAD00001006202

• A Sequential Window of Opportunity Trial of Anti-PD-L1/TGF-β trap (M7824) Alone and in Combination with TriAd Vaccine and N-803 for Resectable Head and Neck Squamous Cell Carcinoma not Associated with Human Papillomavirus Infection

  This submission includes the whole exome and bulk RNA sequencing associated with the correlative study of clinical specimens from a prospective clinical study of neoadjuvant bintrafusp alfa in patients with newly diagnosed, surgically resectable oral cavity or laryngeal squamous cell carcinoma. 

  Study phs002849

• Bulk RNA and ATACseq of 2 XLP patients and 5-6 HD

  The dataset contains five samples from P1, one pre-HSCT and four post-HSCT, one sample from P2 and 5-6 HD. RNAseq reads were processed using the LUMC BIOWDL RNAseq pipeline v5.0.0 (https://github.com/biowdl/RNA-seq). Genes with log2CPM≥1 in at least 10% of all samples were retained for downstream analysis. Differential gene expression analysis was performed using the dgeAnalysis R-Shiny application (https://github.com/LUMC/dgeAnalysis/tree/v1.4.4). ATACseq reads were processed using the LUMC BIOWDL Chipseq pipeline 1.0.0-dev (https://github.com/biowdl/ChIP-seq).

  Dataset EGAD50000002072