12307 results for "cancer rna-seq"

in 27.55 milliseconds.

• Single cell RNA sequencing of CD19 CAR T-cell infusion products

  We performed single cell RNA sequencing of remnants from CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma. Libraries were prepared using 10X 5’ GEX chemistry and sequenced on an Illumina HiSeq 4000 to obtain >50,000 reads per cell.

  Study EGAS00001004576

• Total RNA sequencing from the TNT trial (NCT00532727)

  Primary tumours from 186 TNT participants (13 matched recurrences) were profiled using total RNA-sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective-response-rate (ORR) and progression-free-survival (PFS) and performed conditional inference forest clustering to integrate multi-modal data.

  Study EGAS00001007398

• Oxford Nanopore RNA sequencing for HLA typing

  A targeted RNA-based method for typing of 12 classical HLA genes using Oxford Nanopore sequencing. In the method, were enriched HLA genes from cDNA of 50 individuals using gene-specific reverse primers. The library molecules were then barcoded, pooled into 2 separate gene pools, and sequenced on MinION R9.4 SpotON flow cells.

  Study EGAS00001004918

• Single-cell 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 single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell 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 single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Genetic Effects on miRNA Expression During Mid-Gestation Neocortical Development

  In this study we aimed to find common genetic variants that influence miRNA expression during mid-gestation neocortical development. Small RNA-sequencing from 212 fetal cortical tissue samples between 14 and 21 weeks gestation were used to profile miRNA expression. Combined with donor genotypes, we were able to find miRNA-eQTLs during neocortical development. The dataset provided here includes 212 Small RNA-sequencing files in FASTQ format from cortical wall samples. Also provided here are 212 donor genotypes in PLINK format (hg19).

  Study phs003106

• Single Suture Craniosynostosis: Gene and Pathway Discovery

  Craniosynostosis is the premature fusion of one or more of the calvarial sutures. In this work, we used genomics and network modeling to reveal genetic and developmental pathways which, when disrupted, result in premature calvarial fusion. Calvarial bone explants were obtained from children undergoing surgery for single suture craniosynostosis. Primary osteoblast cell lines were established from calvarial explants and used as an RNA source.  The data available includes subject sex, affected suture, RNA sequence variants and counts.

  Study phs002684

• RNAseq of MCL cell lines

  This study provides bulk RNA sequencing data from Mino and Jeko-1 mantle cell lymphoma (MCL) cell lines treated with CDK9 inhibitors, including the novel compound YX0798. CDK9 is a key regulator of RNA polymerase II–mediated transcription, and its inhibition disrupts transcriptional programs critical for tumor survival. The dataset captures transcriptomic changes associated with CDK9 inhibition, including downregulation of oncogenic drivers such as MYC and MCL-1. These data support mechanistic studies of transcriptional reprogramming and therapeutic vulnerability in aggressive MCL.

  Study EGAS50000001089

• Transcriptome sequencing of fibroblast-dependent alveolar organoids derived from patient-specific iPS cells with SFTPC^Y104H variant and their gene-corrected (monoallelic wild type SFTPC) ones.

  A disease-specific iPS cell line derived from a pulmonary fibrosis patient with SFTPC^Y104H and its gene-corrected (monoallelic wild type SFTPC) one were established. Then lung progenitor cells were differentiated from each cell line and co-cultured with human fetal lung fibroblasts to generate alveolar organoids, respectively. Alveolar epithelial cells and fibroblasts were isolated by fluorescence-activated cell sorting and each RNA was extracted. We performed transcriptome analysis of those samples by RNA-sequencing.

  Study JGAS000617

• Convergent evolution drives therapy resistance in DNA repair-deficient mCRPC

  These are FASTQ files obtained from RNA-sequencing and DNA-sequencing of tumor biopsies obtained from metastatic castration-resistant prostate tumors. Patients were treated with multiple lines of therapy with samples obtained at the time of rapid autopsy following the CASCADE protocol. Multiple biopsies were obtained from each patient under guidance of pathology. DNA were analyzed by high-depth whole genome, exome, and targeted sequencing. RNA were analyzed using a Nugen amplification protocol as described in Quigley Cell 2018.

  Study EGAS00001007147

• Transcriptomic analysis of human hematopoietic populations sorted from umbilical cord blood.

  We isolated by fluorescence-activated cell sorting highly purified populations (long term hematopoietic stem cells (LT-HSCs), short term hematopoietic stem cells (ST-HSCs), multipotent progenitors (MPPs), common myeloid progenitor (CMPs), granulocyte and monocyte progenitors (GMPs), multilymphoid progenitors (MLPs), Myeloid-erythorid Progenitor (MEP), Granulocytes, Monocytes, B cells, T cells, Dendritic cells, Natural Killer cells and Erythrocyte Progenitors from 3 to 4 cord blood pools. We extracted RNA from 5K cells of each population and performed RNA-sequencing.

  Study EGAS00001004968

• Drug screen in iPSC-Neurons identifies nucleoside analogs as inhibitors of (G4C2)n expression in C9orf72 ALS/FTD

  To investigate the mode of action and potential side-effects we analyzed differential gene expression in Postmitotic C9orf72 iPSC-Neurons by RNAseq. The cells were treated in a 2 dose regime at 10 µm in 0.1 % DMSO for 9 days. Compound treated iPSC-Neurons were washed with PBS, frozen on dry ice and stored at -80°C until RNA isolation. The RNA was isolated using miRNA Mini Kit (Qiagen) using 700 μl of Qiazol. A total of 250 ng of RNA per sample was processed for mRNA library preparation as per the manufacturer’s instructions for Illumina® Stranded mRNA Prep Ligation to be used with the IDT® for Illumina® RNA UD Indexes Set B and sequenced using NextSeq 500/550 High Output Kit v2.5 (Illumina) on NextSeq 550 (Illumina). The data was processed and analyzed using CLC genomics workbench (Version 21.0.3, Qiagen)

  Dataset EGAD00001008674

• A Randomized Trial of Combined PD-L1 and CTLA-4 Inhibition with Targeted Low-Dose or Hypofractionated Radiation for Patients with Metastatic Colorectal Cancer

  Brief SummaryThis randomized phase II trial studies the side effects of durvalumab and tremelimumab to see how well they work with or without high or low-dose radiation therapy in treating patients with colorectal (CRC) or non-small cell lung cancer (NSCLC) that has spread to other parts of the body (metastatic). Immunotherapy with durvalumab and tremelimumab may induce changes in body's immune system and may interfere with the ability of tumor cells to grow and spread. Radiation therapy uses high energy x-rays to kill tumor cells and shrink tumors. Giving durvalumab and tremelimumab with radiation therapy may work better in treating patients with colorectal or non-small cell lung cancer.Detailed DescriptionPRIMARY OBJECTIVES:I. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 (durvalumab) and tremelimumab alone or with high or low-dose radiation in non-small cell lung cancer (NSCLC). (NSCLC Cohort) II. To compare the overall response (excluding the irradiated lesion[s]) between combined checkpoint blockade with MEDI4736 and tremelimumab alone or combined checkpoint blockade with low or high dose radiation. (NSCLC Cohort) III. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 and tremelimumab with high or low-dose radiation. (Colorectal Cohort) IV. To determine the overall response rate (excluding the irradiated lesion[s]) with combined checkpoint blockade with MEDI4736 and tremelimumab with either low or high dose radiation. (Colorectal Cohort)SECONDARY OBJECTIVES:I. To estimate median progression-free survival and overall survival. (NSCLC Cohort) II. To determine local control within the irradiated field(s) and abscopal response rates. (NSCLC Cohort) III. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells and overall response. (NSCLC Cohort) IV. To explore changes in PD-L1 expression, circulating T-cell populations, T-cell infiltration, ribonucleic acid (RNA) expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (NSCLC Cohort) V. To estimate median progression-free survival and overall survival. (Colorectal Cohort) VI. To determine local control within the irradiated field and abscopal response rates. (Colorectal Cohort) VII. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+ CD8+ T-cells and overall response. (Colorectal Cohort) VIII. To evaluate changes between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells induced by targeted low or high dose radiation. (Colorectal Cohort) IX. To explore changes in circulating T-cell populations, T-cell infiltration, RNA expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (Colorectal Cohort)OUTLINE: Patients are assigned to 1 of 2 cohorts. NOTE: This Study is only for Cohort 2. Please see phs003295 for Cohort 1COHORT 1: Patients with NSCLC are randomized to 1 of 3 arms.ARM A: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.ARM C: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses.COHORT 2: Patients with CRC are randomized to 1 of 2 arms.ARM A: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.After completion of study treatment, patients are followed for up to 12 weeks.Official TitleA Phase 2 Study of MEDI4736 (Durvalumab) and Tremelimumab Alone or in Combination With High or Low-Dose Radiation in Metastatic Colorectal and NSCLC Conditions Metastatic Colorectal CarcinomaMetastatic Lung Non-Small Cell CarcinomaStage IV Colorectal Cancer AJCC v7Stage IV Lung Non-Small Cell Cancer AJCC v7Stage IVA Colorectal Cancer AJCC v7Stage IVB Colorectal Cancer AJCC v7 Intervention/Treatment Biological: DurvalumabRadiation: Radiation TherapyBiological: Tremelimumab Other Study ID Numbers NCI-2016-01325NCI-2016-01325 ( Registry Identifier ) (REGISTRY: CTRP (Clinical Trial Reporting Program))17-71910021 ( Other Identifier ) (OTHER: Dana-Farber - Harvard Cancer Center LAO)10021 ( Other Identifier ) (OTHER: CTEP) Molecular Technologies/AssaysIHCmIFOlinkCyTOFRNAseqWES

  Study phs003294

• Durvalumab Plus Tremelimumab Alone or in Combination with Low-Dose or Hypofractionated Radiotherapy in Metastatic Non-Small-Cell Lung Cancer Refractory to Previous PD(L)-1 Therapy: an Open-Label, Multicentre, Randomised, Phase 2 Trial

  Brief SummaryThis randomized phase II trial studies the side effects of durvalumab and tremelimumab and to see how well they work with or without high or low-dose radiation therapy in treating patients with colorectal or non-small cell lung cancer that has spread to other parts of the body (metastatic). Immunotherapy with durvalumab and tremelimumab, may induce changes in body's immune system and may interfere with the ability of tumor cells to grow and spread. Radiation therapy uses high energy x-rays to kill tumor cells and shrink tumors. Giving durvalumab and tremelimumab with radiation therapy may work better in treating patients with colorectal or non-small cell lung cancer.Detailed DescriptionPRIMARY OBJECTIVES:I. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 (durvalumab) and tremelimumab alone or with high or low-dose radiation in non-small cell lung cancer (NSCLC). (NSCLC Cohort) II. To compare the overall response (excluding the irradiated lesion[s]) between combined checkpoint blockade with MEDI4736 and tremelimumab alone or combined checkpoint blockade with low or high dose radiation. (NSCLC Cohort) III. To assess safety and tolerability of combined checkpoint blockade with MEDI4736 and tremelimumab with high or low-dose radiation. (Colorectal Cohort) IV. To determine the overall response rate (excluding the irradiated lesion[s]) with combined checkpoint blockade with MEDI4736 and tremelimumab with either low or high dose radiation. (Colorectal Cohort)SECONDARY OBJECTIVES:I. To estimate median progression-free survival and overall survival. (NSCLC Cohort) II. To determine local control within the irradiated field(s) and abscopal response rates. (NSCLC Cohort) III. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells and overall response. (NSCLC Cohort) IV. To explore changes in PD-L1 expression, circulating T-cell populations, T-cell infiltration, ribonucleic acid (RNA) expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (NSCLC Cohort) V. To estimate median progression-free survival and overall survival. (Colorectal Cohort) VI. To determine local control within the irradiated field and abscopal response rates. (Colorectal Cohort) VII. To evaluate associations between PD-L1 expression as well as levels of infiltrating CD3+ CD8+ T-cells and overall response. (Colorectal Cohort) VIII. To evaluate changes between PD-L1 expression as well as levels of infiltrating CD3+, CD8+ T-cells induced by targeted low or high dose radiation. (Colorectal Cohort) IX. To explore changes in circulating T-cell populations, T-cell infiltration, RNA expression, spatial relationship of immune markers, and mutational burden as a result of low or high dose radiation. (Colorectal Cohort)OUTLINE: Patients are assigned to 1 of 2 cohorts. NOTE: This Study is only for Cohort 1. Please see phs003294 for Cohort 2COHORT 1: Patients with NSCLC are randomized to 1 of 3 arms.ARM A: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab and durvalumab and as in Arm C. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.ARM C: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses.COHORT 2: Patients with CRC are randomized to 1 of 2 arms.ARM A: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive high dose radiation therapy once per day (QD) over 10 days for up to 3 fractions.ARM B: Patients receive tremelimumab intravenously (IV) and durvalumab IV over 60 minutes every 4 weeks for up to 16 weeks in the absence of disease progression or unacceptable toxicity. Patients then receive durvalumab IV over 60 minutes 4 weeks after last combination dose for up to 9 additional doses. Beginning at week 2, patients receive low dose radiation therapy every 6 hours twice per day (BID) on weeks 2, 6, 10 and 14.After completion of study treatment, patients are followed for up to 12 weeks.Official TitleA Phase 2 Study of MEDI4736 (Durvalumab) and Tremelimumab Alone or in Combination With High or Low-Dose Radiation in Metastatic Colorectal and NSCLC Conditions Metastatic Colorectal CarcinomaMetastatic Lung Non-Small Cell CarcinomaStage IV Colorectal Cancer AJCC v7Stage IV Lung Non-Small Cell Cancer AJCC v7Stage IVA Colorectal Cancer AJCC v7Stage IVB Colorectal Cancer AJCC v7 Intervention/Treatment Biological: DurvalumabRadiation: Radiation TherapyBiological: Tremelimumab Other Study ID Numbers NCI-2016-01325NCI-2016-01325 ( Registry Identifier ) (REGISTRY: CTRP (Clinical Trial Reporting Program))17-71910021 ( Other Identifier ) (OTHER: Dana-Farber - Harvard Cancer Center LAO)10021 ( Other Identifier ) (OTHER: CTEP) Molecular Technologies / AssaysCyTOFIHCmIFOlinkRNAseqWES

  Study phs003295

• Genomic Analysis of Low Grade B-Cell Lymphoma

  We included tumors from 64 newly diagnosed or untreated Low Grade B-Cell Lymphoma (LGBCL) patients, consisting of SMZL (n = 48), NMZL (n = 6), EMZL (n = 2), LPL (n = 5), and B-NOS (n = 3) in this study. Samples were selected from cases consented to the Molecular Epidemiology Resource (MER) of the University of Iowa and Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). RNA or DNA were extracted from 64 frozen LGBCLs tumors (with available matched germline DNA for N=61. For RNA sequencing, library preparation was done using the Illumina TruSeq RNA Exome Kit and sequenced with 100 nucleotide paired-end reads using the HiSeq 4000. For WES, library preparation was done using the Agilent SureSelect XT kit and sequenced with 100 nucleotide paired-end reads using the Illumina HiSeq 4000.

  Study phs002552

• ScRNA-seq of kidney organoids expressing different APOL1 variants and treated with IFN-γ

  This dataset includes scRNA-seq fastq files and Seurat counts and metadata for 3 samples of hiPSC-derived kidney organoid cells cultured in vitro in presence of IFN-γ. Samples were obtained from kidney organoids with APOL1 G1G1 variant, APOL1 G2G2 variant and an isogenic control.

  Dataset EGAD50000001743

• Effect of ETS2 modulation on chromatin accessibility and enhancer activity in primary human macrophages

  3 datasets included: - H3K27ac ChIP in ETS2-edited and unedited TPP macrophages from 3 biological replicates - H3K27ac ChIP in ETS2-overexpressing and control M0 (resting) macrophages from 3 biological replicates - ATAC-seq (deep sequencing) in ETS2-edited and unedited TPP macrophages from 3 biological replicates

  Dataset EGAD50000000154

• Oxford Human Islet ATAC-seq data of 18 human pancreatic islet preparations

  18 human pancreatic islet preparations derived from 17 donors were processed for ATAC-seq. The data was generated on an Illumina Hiseq 2500 sequencing machine to generate 50bp paired end read data. The resulting fastq.gz and mapped bam files were deposited.

  Dataset EGAD00001003947

• MethylCap-seq based DNA methylation profiles of 65 glioblastoma and 5 non-tumoral tissues

  Data represent genome-wide DNA methylation profiles obtained by MethylCap-seq (Diagenode’s MethylCap-kit based purification followed by Illumina GAIIx sequencing), for 70 brain tissue samples, including 65 glioblastoma samples and 5 non-tumoral tissues (obtained from epilepsy surgery).

  Dataset EGAD00001001399

• BLUEPRINT release January 2015, Bisulfite-Seq for Multiple myeloma

  Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001152

• BLUEPRINT release January 2015, Bisulfite-Seq for Acute myeloid leukemia

  Bisulfite-Seq data for 1 Acute myeloid leukemia sample(s). 18 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001162

• BLUEPRINT release January 2015, Bisulfite-Seq for Acute promyelocytic leukemia

  Bisulfite-Seq data for 3 Acute promyelocytic leukemia sample(s). 24 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001167

• miRNA seq data of 13 cases

  miRNA seq data of 13 cases (MMML)

  Dataset EGAD00001001632

• BLUEPRINT release August 2014, Bisulfite-Seq for Multiple myeloma

  Bisulfite-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000934

• ETMR ATACSeq

  ATACSeq library amplification was performed on 5 ETMR tumour samples using the NEBnext High Fidelity 2xPCR Master Mix (New England Biolabs, Cat#M0541S) according to the manufacturer’s protocol. ATAC-seq libraries were sequenced using single-end 50 bp reads on the Illumina HiSeq 2000 platform. ATAC-seq peaks analysed was conducted as published previously(Torchia et al. 2016).

  Dataset EGAD00001004805

• smMIP-seq of 18 FFPE prostate samples (normal and tumour pairs) to identify mutations

  smMIP-Seq was performed on radical prostatectomy formalin-fixed paraffin-embedded sample pairs (n = 18). Library prep was done by capture of targeted sequences with single molecule (unique molecular index) tagged molecular inversion probes (MIP) and sequenced as 75bp paired end on Illumina NextSeq 500. Sequences were aligned to the human genome (hg38) using BWA.

  Dataset EGAD00001006109

• Extramammary Paget Disease

  37 surgical samples were interrogated by WXS, and 50 formalin-fixed, paraffin-embedded samples were interrogated by target-seq. Agilent SureSelect XT kit and SureSelect Human Exon V6 were used to generate exome libraries. Agilent SureSelect XT low input kit and custom capture panel designed on SureDesign were used to generate target-seq libraries. All libraries were sequenced on Illumina HiSeq 2500 platform.

  Dataset EGAD00001006449

• smRNA-seq of human post-mortem brain data from the frontal lobe (goettingen part)

  This dataset contains smRNA-seq data from human post-mortem brain tissue of the frontal lobe of patients with FTD and healthy controls. These samples depict the data generated at the DZNE Göttingen and should be used together with the data generated at the DZNE Tübingen.

  Dataset EGAD00001006845

• CHROMATIN ACTIVATION PROFILING OF STEREOTYPED CHRONIC LYMPHOCYTIC LEUKEMIAS

  We used chromatin-immunoprecipitation followed by sequencing (ChIP-Seq) with an antibody for the H3K27ac (a bona fide histone mark for regulatory element activation) in sorted CLL cells from 15 CLL, including cases from stereotyped subsets #1, #2, #4, and #8. The samples were sequenced by Illumina HiSeq 2500.

  Dataset EGAD00001009082

• Single-cell ATAC-seq of matched pediatric AML tumors

  Single-cell ATAC-seq of pediatric AML tumours from patients enrolled in the clinical trial AAML1031. Obtained using the 10X Chromium NextGEM Single Cell ATAC Reagent Kit, v1.1. A total of 64 samples were obtained from biopsies at diagnosis, remission and relapse from 25 patients.

  Dataset EGAD00001011194

• Parallel Genomic Alterations of Antigen and Payload Targets Mediate Polyclonal Acquired Clinical Resistance to the Antibody Drug Conjugate Sacituzumab Govitecan

  Sacituzumab Govitecan (SG), a novel antibody drug conjugate (ADC) incorporating the anti-TROP2 antibody hRS7 conjugated to a topoisomerase-1 inhibitor (SN-38) payload, is the first ADC to be approved for advanced triple negative breast cancer (TNBC). However, mechanisms governing therapeutic resistance to SG are not known. We sought to identify mechanisms of de novo and acquired resistance to SG through unbiased whole-exome sequencing (WES) and RNA sequencing analysis of pre-treatment and multi-site post-progression (autopsy) tumor specimens. We examined three metastatic TNBC cases exhibiting (1) de novo progression, (2) stable disease, and (3) a deep response followed by progression, then mapped the temporal and spatial genomic evolution of acquired resistance in the responding patient. We then conducted additional pre-clinical experiments to validate the observed resistance mechanisms. TROP2 RNA and gene copy number were associated with de novo resistance, as case (1) was found to have absent TROP2 expression in all specimens, case (2) expressed TROP2, while case (3) exhibited both expression and focal genomic amplification of the TACSTD2/TROP2 locus. The genomic phylogeny tree inferred from case (3) post-progression specimens revealed one branch harboring an acquired canonical E418K resistance mutation in TOP1 (encoding topoisomerase 1) and a subsequent sub-clonal TOP1 inactivating frameshift mutation, while a distinct branch exhibited acquisition of a novel T256R missense mutation in TACSTD2 (encoding TROP2). Both the TOP1- and TACSTD2-mutant clones seeded multiple distinct metastatic sites. Through reconstitution experiments in TROP2 negative cells we found that TROP2 T256R is a stable protein with defective cell membrane localization and reduced cell surface binding by RS7 compared to wild-type TROP2. Collectively, these findings underscore TROP2 as a determinant of initial response to SG, and they reveal parallel and mutually exclusive polyclonal molecular mechanisms of acquired resistance involving the direct antibody target and drug payload target in distinct metastatic subclones of a single patient. While further research is needed to extend these novel findings, this study highlights the specificity of SG and illustrates how identifying such mechanisms will inform rational therapeutic strategies to overcome ADC resistance.  

  Study phs002555

• Epigenetic analysis of clear cell renal cell carcinoma using ChIP-seq

  To investigate the epigenetic landscape of clear cell renal cell carcinoma (ccRCC), we performed ChIP-seq data for the CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, and HIF1A marks in the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as the HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and narrowPeak formats. Data were processed using the nf-core chipseq pipeline.

  Dataset EGAD50000001886

• 5 scRNA-seq with TCR Enrichment of Tumour-Involved Lymph Nodes, Malignant Seromas and Patient-Derived Xenografts from 18 T-Cell Lymphoma Patients

  This raw data contains 5' scRNA-seq with TCR enrichment data from 18 individual patients analysing cells taken from tumour-involved lymph nodes (LN), malignant seromas and patient-derived xenografts (PDX) including systemic/nodal ALK+ ALCL (n=3 PDX), BIA-ALCL (n=2 seromas), PTCL-NOS (n=5 nodal tumours), nodal T follicular helper lymphoma - angioimmunoblastic type (nTFHL-AI) (n=1), nTFHL, not otherwise specified (nTFHL, NOS, n=1), TLBL (n=5) and 1 case of Sezary Syndrome (SS, cutaneous tumour). Droplet-based 5’ scRNA-seq with TCR enrichment (10x Chromium platform) was performed for all live cells, or the viable CD45+CD3- and CD45+CD3+ fractions following cell sorting by flow cytometry.

  Dataset EGAD00001015703

• ChIP-seq on Hodgkin lymphoma DAC

  Dac EGAC00001001007

• Henssen Lab Neuroblastoma Circle-seq Data

  Dac EGAC00001001803

• Henssen Lab Neuroblastoma Circle-seq Data

  Dac EGAC00001001804

• Human Inflammatory Skin Disease scRNA-seq

  Dac EGAC00001002309

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia

  For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases were acquired by using the ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) tools for the RNA sequencing data.

  Study EGAS50000001803

• A capture methyl-seq protocol with improved efficiency and cost-effectiveness using pre-pooling and enzymatic conversion

  The opportunities for sequencing-based methylome analysis of clinical samples are increasing. To reduce its cost and the amount of genomic DNA required for library preparation, we aimed to establish a capture methyl-seq protocol, which adopts pre-pooling of multiple libraries before hybridization capture and TET2/APOBEC-mediated conversion of unmethylated cytosine to thymine. We compared a publicly available dataset generated by the standard Agilent protocol of SureSelect XT Human Methyl-Seq Kit and our dataset obtained by our modified protocol, EMCap, that adopted sample pre-pooling and enzymatic conversion. We confirmed that the quality of DNA methylation data was comparable between the two datasets. As our protocol, EMCap, is more cost-effective and reduces the amount of input genomic DNA, it would serve as a better choice for clinical methylome sequencing.

  Study JGAS000605

• Raw sequencing files from WGS and RNA-Seq

  Acute leukemias are the most common malignancies in children with an onset of the disease among 0-6 years-old. The early development of theses malignancies has been proposed as an indicator of their prenatal origin, hypothesis that has been confirmed especially in the case of acute lymphoblastic leukemia. For acute myeloid leukemia (AML), comprising an heterogenous group of different cytogenetics subtypes, this prenatal origin has also been confirmed specially for MLL-rearranged and t(8;21) subgroups. AMLs carrying t(7;12) constitute up to 30% of cases under 2-years-old, frequently being associated with a trisomy of chromosome 19 and an overexpression of MNX1 gene. An in utero origin of this specific subgroup has been suggested but not clearly confirmed. Here, we present the case of a 5-months-old AML patient with t(7;12) in which we have fully characterized a novel breakpoint occurring among ETV6 and NOM1 genes. We demonstrate the presence of this specific ETV6-NOM1 fusion in CD34+ hematopoietic stem and progenitor cells isolated from the cord blood unit from the same patient and stored at birth. Moreover, trisomy +19 present at diagnosis was not detected at birth. Together, our results demonstrate the prenatal origin of the t(7;12) in infant AML, and establish trisomy +19 as a secondary event in this leukemia.

  Study EGAS50000000186

• Whole Exome and RNA Sequencing of 22 Patient-Derived Xenografts from Estrogen Receptor-Positive Breast Cancers

  We performed RNA and whole exome sequencing on 22 patient-derived xenografts (PDX) from estrogen receptor-positive (ER+) breast cancers, in the presence and absence of estradiol (E2) supplementation. Exome coverage across more than 3,500 clinically relevant genes that previously were covered below 20X (~2.72Mb) was achieved. On average, 11.2Gb of unique sequence data were generated with 95.3% of the bases in the exome design covered to 20x read depth or greater. RNA sequencing was generated from xenograft tumors. Between 50 and 85M total reads were performed. The average strand-specificity and rRNA rate was 98% and 1.5%, respectively. Transcripts for 17,000 to 27,087 genes were detected in these samples.

  Study phs003324

• Human Embryonic Multi-tissue ChIP-seq (Manchester)

  Dac EGAC00001000999

• Ig-seq celiac disease Data Access Committee

  Dac EGAC00001001208

• HDBR exome-seq data access committee

  Dac EGAC00001002703

• Tumor reactive γδ T cells contribute to a complete response to PD-1 blockade in a Merkel cell carcinoma patient

  Single cell RNA and TCR sequencing of gamma delta T cells from two Merkel cell carcinoma patients

  Study EGAS50000000102

• RNA Dataset

  The RNA dataset includes 5 samples analyzed with the Oncomine Comprehensive Assay (OCA) panel. After library preparation, sequencing was performed on the Ion Torrent S5 System, generating FASTQ files. The analysis captures gene fusions and splice variants relevant to oncogenic processes. (idem)

  Dataset EGAD50000002502

• RNA isoform diversity, splicing variants, and switching in single cells of the Alzheimer’s disease brain

  Paired 10X 3' single-nucleus RNA sequencing with PacBio Kinnex long-read sequencing in 7 control and 8 Alzheimer's disease human frontal cortex samples.

  Dataset EGAD50000002124

• RNA-Sequencing of whole blood collected from RNU4ATAC/RNU6ATC patients and controls

  RNA-Sequencing of whole blood collected from patients with biallelic RNU4ATAC/RNU6ATAC variants, parents who carry the variants, healthy controls and type 1 diabetes controls.

  Dataset EGAD50000002242

• fibroblast transcriptome of pediatric patients with epilepsy

  RNA sequencing of fibroblasts from pediatric patients with childhood epilepsy. Fibroblast RNA was extracted at passage 3-6 using MN nucleospin, >90M 150bp paired-end reads per sample were obtained with illumina sequencing. Reads were aligned to hg38.

  Dataset EGAD50000001166

• DNA sequencing of sgRNAs in CRISPR-Cas9 screening and RNA sequencing of SF3B4-overexpressing liver organoids

  DNA sequencing of sgRNAs in CRISPR-Cas9 screening and RNA sequencing of SF3B4-overexpressing liver organoids

  Dataset EGAD50000001240