4859 results for "*oma"

in 36.72 milliseconds.

• Phased melanoma whole genomes

  We have sequenced whole genomes of 10 melanoma samples (1 cell line; A375 and 9 patient derived short term cultures). Libraries were prepared with 10X linked reads technology in order to obtain phase information and subsequently sequenced on Illumina NovaSeq6000.

  Dataset EGAD00001005773

• Sequencing data for oesophageal / related samples - Kazachenka et al (DNA)

  Data supporting: "The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes" WGS for 452 samples

  Dataset EGAD00001011095

• Genome and transcriptome sequence data from an uveal melanoma patient

  Genome and transcriptome sequence data from an uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005824

• RNA of peripheral blood for pancreatic cancer and chronic pancreatitis

  Samples of nucleated cells found in peripheral blood from over 300 patients suffering from resectable pancreatic ductal adenocarcinoma, non-resectable pancreatic cancer, chronic pancreatitis, or none of these. Please cite this article when using data: Al-Fatlawi, A.; Malekian, N.; García, S.; Henschel, A.; Kim, I.; Dahl, A.; Jahnke, B.; Bailey, P.; Bolz, S.N.; Poetsch, A.R.; Mahler, S.; Grützmann, R.; Pilarsky, C.; Schroeder, M. Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants. Cancers 2021, 13, 2654. https://doi.org/10.3390/cancers13112654

  Dataset EGAD00001006915

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of unknown primary (upper GI?) patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of unknown primary (upper GI?) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005837

• Pre-neoplastic liver colonization by 11p15.5 altered mosaic cells in young children with hepatoblastoma

  Additional datasets linked to EGAS00001006692

  Dataset EGAD00001011097

• Genome and transcriptome sequence data from a colon adenocarcinoma patient

  Genome and transcriptome sequence data from a colon adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005911

• pancreatic ductal adenocarcinoma exomes in study: Pro-immunogenic Impact of MEK inhibition combined with an anti-CD40 immunostimulatory antibody

  This dataset contains 3 pairs of exomes, germline (from whole blood) and patient-derived xenograft (PDX), from human pancreatic durctal adenocarcinoma patients. The data is referred to in the publication: "Pro-immunogenic impact of MEK inhibition synergizes with agonist anti-CD40 immunostimulatory antibodies in tumor therapy" (Nature Communications, 2020) Abstract: Cancer types with lower mutational load and a non-permissive tumor microenvironment are intrinsically resistant to immune checkpoint blockade. While the combination of cytostatic drugs and immunostimulatory antibodies constitutes an attractive concept for overcoming this refractoriness, suppression of immune cell function by cytostatic drugs may limit therapeutic efficacy. Here we show that targeted inhibition of mitogen-activated protein kinase (MAPK) kinase (MEK) does not impair dendritic cell-mediated T-cell priming and activation. Accordingly, combining MEK inhibitors (MEKi) with agonist antibodies (Abs) targeting the immunostimulatory CD40 receptor resulted in potent synergistic anti-tumor efficacy. Detailed analysis of the mechanism of action of MEKi GDC-0623 by means of flow cytometric analysis of the tumor immune infiltrate and whole tumor transcriptomics showed that, in addition to its cytostatic impact on tumor cells, this drug exerts multiple pro-immunogenic effects, including the suppression of M2-type macrophages, myeloid derived suppressor cells and CD4+ T-regulatory cells. In addition, MEKi was found to induce tumor-cell intrinsic interferon signaling, which contributed to antigen presentation by tumor cells. Finally, the tumoridical impact of MEKi involves the activation of multiple pro-inflammatory pathways involved in immune cell effector function in the tumor microenvironment. Our data therefore indicate that the combination of MEK inhibition with agonist anti-CD40 Ab is a promising therapeutic concept, especially for the treatment of mutant Kras-driven tumors such as pancreatic ductal adenocarcinoma.

  Dataset EGAD00001005938

• Genome and transcriptome sequence data from a non-small cell lung carcinoma patient

  Genome and transcriptome sequence data from a non-small cell lung carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004596

• Single cell sequencing of a post-PD-1 inhibitor metastatic melanoma mass

  Three technical replicates of FACS-sorted T cells (CD45+CD3+) and one replicate of FACS-sorted tumor cells (MCSP+) were loaded to a targeted 10,000 cells per lane on the 10X Genomics Chromium Controler with the single cell 5’ Immune Repertoire and Gene Expression profiling kit. In total, we loaded ~30,000 individual tumor infiltrating lymphocytes (TILs) and ~10,000 melanoma cells on the 10X platform (10X Genomics, CA, USA). Reverse transcription, TCR enrichment, and library preparations were performed according to the 10X Genomics 5’ V(D)J protocol revision C. Transcriptome libraries were pooled and sequenced on the Illumina NovaSeq 6000 S2 flow cell with 26 R1, 8 i7, and 91 R2 cycles respectively. The TCR libraries were pooled and sequenced on the Illumina MiSeq V2 150 cycles paired-end. Single cell transcriptomic and TCR data was processed with the 10X Genomics Cell Ranger Pipeline version 2.2.0 with the software-provided GRCh38 reference transcriptomes. After quality control, there was RNAseq profile data available from 6267 immune and 4303 melanoma cells. Downstream processing and visualization was encompassed through Seurat and tSNE plots.

  Dataset EGAD00001006013

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-025

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Dataset EGAD00001006029

• WGS data of neuroblastoma patients

  30 samples of 15 individuals with neuroblastoma tumor, whole genome sequencing

  Dataset EGAD00001006956

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003051

• Melanoma C32 ENU resistance to Combination Therapy

  This study involves mutagenizing C32, a melanoma cell line, with ENU to identify those mutations which engender resistance to a targeted treatment.

  Dataset EGAD00001002234

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002537

• Genome and transcriptome sequence data from a Ewing sarcoma patient

  Genome and transcriptome sequence data from a Ewing sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005894

• Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma (colorectal cancer) patient

  Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma (colorectal cancer) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002567

• Genome and transcriptome sequence data from an oligodendroglioma patient

  Genome and transcriptome sequence data from an oligodendroglioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002539

• Oesophageal adenocarcinoma WGS from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains whole genome sequencing (WGS) generated from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). WGS data were generated with the aim to assess previously reported (e.g. tumour mutational burden) and novel predictive genomic markers for immunochemotherapy treatment in this setting. Using these data, mutation and copy number profiles were generated for the LUD2015-005 study, which were assessed for correlation with patient outcomes from this trial.

  Dataset EGAD00001009400

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002546

• CRUK Accelerator: oesophageal adenocarcinoma whole exome and RNA-seq raw sequencing data

  Whole exome and RNASeq raw sequencing data for a cohort of 7 male patients with oesophageal adenocarcinoma. Median age at diagnosis was 68. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001008489

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482

• Genome and transcriptome sequence data from a ductal carcinoma of left breast patient

  Genome and transcriptome sequence data from a ductal carcinoma of left breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002574

• SF11964 scRNA-Seq Low Grade Glioma IDHR132H mutant Male

  Single cell RNA-Seq Low Grade Astrocytoma IDHR132H mutant. Male, 64. Single Cell RNA seq from primary astrocytoma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005396

• Single-cell RNA sequencing of anti-LAG3+anti-PD1 treated melanoma patients

  Single-cell RNA sequencing of 18 peripheral blood samples from six melanoma patients. The raw data is available as fastq files.

  Dataset EGAD00001009807

• WTS data of patients diagnosed with angiosarcoma

  Whole-transcriptome sequencing (WTS) of 6 tumor-normal and 6 tumor-only samples from patients diagnosed with angiosarcoma. Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on HiSeq 2500 and HiSeq 3000 (Illumina) with 2x101 bp and 2x151 bp read length, respectively.

  Dataset EGAD00001005367

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• Myeloid-specific KDM6B inhibition sensitizes Glioblastoma to PD1 blockade

  This data set include FASTQ files for five experiments: Human scRNA-Seq data (6 samples), Human Visium spatial transcriptomic data (3 samples), Mouse scRNA-seq data (4 samples), Mouse scATAC-seq data (2 samples), Mouse ChIP-seq data (8 samples). For the mouse scATAC-seq data (2 samples), there are originally three FASTQ files, R1, R2 and R3 files. The R1 and R2 FASTQ files were merged into one larger file ("R1R2") per sample for submission as paired-end sequencing setting to follow the EGA guidelines. They can be split into individual R1 and R2 files in order to be processed by Cell Ranger software. The files with IC1 suffix are CHIP-seq Input control for anti-KDM6B antibody pull down experiments and the files with IC2 suffix are CHIP-seq Input control for anti-H3K27ME3 antibody pull down experiments in murine model.

  Dataset EGAD00001010073

• Chordoma Extension Study

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001238

• Chordoma Extension (known cancer genes)

  Extension analysis to pursue candidate genes of interest in chordoma

  Dataset EGAD00001001239

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the GE junction patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the GE junction patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002595

• Genome and transcriptome sequence data from a porocarcinoma patient

  Genome and transcriptome sequence data from a porocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002596

• Genome and transcriptome sequence data from a multiple myeloma patient

  Genome and transcriptome sequence data from a multiple myeloma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008947

• Longitudinal Single-Cell Profiling in Refractory Mantle Cell Lymphoma

  we performed sequential scRNA-seq of 21 specimens (discovery cohort) collected at baseline, during treatment, and/or at disease remission/progression from 3 ibrutinib-responsive (R) patients (Pt-V, C and D) and 2 non-responsive (NR) patients (Pt-B and E). In addition, the PBMC samples from two healthy donors (N1 and N2) were included as the normal controls.

  Dataset EGAD00001006994

• Melanoma Germlines subset for BAP1

  These samples comprise both melanoma cases and controls sequenced for a selection of loci linked to disease susceptibility. These bams are a subset of the sequencing restricted specifically to the GRCh37 coding areas of the BAP1 gene.

  Dataset EGAD00001002743

• Genomic characterization (through whole-exome sequencing) of bone marrow clonal plasma cells before and after VRD treatment from multiple myeloma patients.

  WES data from clonal pahtologic bone marrow plasma cells of multiple myeloma patients. From each patient there are three samples, pathologyc bone marrow plasma cells at diagnosis, pathologyc bone marrow plasma cells after VRD treatment and T lymphocytes as germline control. There are 14 patients in total

  Dataset EGAD00001006302

• SF10619

  SF10619 snATAC Oligodendroglioma (WHO gr. 2).Tumor Location: Parietal. Age: 52. Sex: Male

  Dataset EGAD00001006316

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - chemo_cohort

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - chemo_cohort

  Dataset EGAD00001002241

• PDX RNA

  RNAseq from PDX tumours under treatment with dpbs or eribulin. Sarcomatous or mixed sarcoma/carcinoma. 6 PDX tumours each with 2 treatments gave 12 pairs of fastq files.

  Dataset EGAD00001009658

• Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient

  Genome and transcriptome sequence data from an adenocarcinoma of primary unknown cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002577

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. This dataset contains all the data available for this study on 2021-09-27.

  Dataset EGAD00001006083

• Genome and transcriptome sequence data from a metastatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003077

• Dataset for glioblastoma panel sequencing

  This dataset contains panel sequencing data of 228 samples from patients with glioblastoma. Sequencing has been performed on Illumina NovaSeq 6000 and NextSeq 500. The sequencing was always paired.

  Dataset EGAD00001015505

• Dataset for melanoma-EXON

  Rare cancer sequencing data of 76 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008890

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

  Genome and transcriptome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004898

• Dataset for melanoma-WHOLE_GENOME

  Rare cancer sequencing data of 22 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008889

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005907

• 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

• Whole genome sequencing data of lung adenocarcinomas

  This dataset includes the whole-genome sequencing data from a study entitled "Tracing Oncogene Rearrangements in the Mutational History of Lung Adenocarcinoma". Whole-genome sequencing libraries were generated by PCR-free methods, and sequencing run was made in HiSeq X Ten machines. PCR duplicates-marked, indel-realigned, and base-recalibrarted BAM files are provided in our dataset.

  Dataset EGAD00001004793

• Genome and transcriptome sequence data from a pancreatic acinar cell adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic acinar cell adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008934

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008933

• Molecular Characterization for Nasopharyngeal Carcinoma (NPC)

  Total RNA was isolated from 50 formalin-fixed paraffin-embedded nasopharyngeal cancer (NPC) specimens using the RecoverAll Total Nucleic Acid Isolation kit (Ambion). Tumor RNA libraries were prepared with 200ng RNA using the Illumina TruSeq Stranded Total RNA kit with Ribo-Zero Gold, and sequenced with >80 million 100 bp paired-end reads.

  Dataset EGAD00001009047

• Congenital mesoblastic nephroma and infantile fibrosarcoma

  The genetic basis of many rare childhood cancers remains unknown. These include a spectrum of infant soft tissue tumors without canonical gene fusions, encompassing congenital mesoblastic nephroma (CMN) of the kidney and infantile fibrosarcoma (IFS). Here, we integrated whole genome and transcriptome sequencing and identified diagnostic markers and novel therapeutic strategies.

  Dataset EGAD00001003884

• Leeds Paired Primary and Recurrent GBM RNAseq

  Whole transcriptome, strand-directional RNAseq data for paired primary dn recurrent samples from patients with glioblastoma

  Dataset EGAD00001005224

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004931

• DKFZ-St.Jude Medulloblastoma - 218 CEF control exomes

  218 control exomes, CEF cohort, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006659

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004932

• Exome sequencing of matching primary tumor and venous tumor thrombus (VTT) renal cell carcinoma (RCC) samples

  We performed multiregion whole exome sequencing of a total of 37 samples from five consecutive patients (normal tissue, n=5; primary tumors, n=16; tumor thrombi, n=16) to >35-fold target coverage. Matching primary tumor and venous tumor thrombus samples were analyzed. Four patients had a clear cell RCC, one patient had a poorly differentiated type II papillary RCC (RCC-VTT-04). The latter patient had a friable thrombus, the others were of solid consistency.

  Dataset EGAD00001004887

• Molecular determinants of outcomes in relapsed mantle cell lymphoma treated with ibrutinib or temsirolimus in the MCL3001 (RAY) trial

  234 BAM files containing capture data of MCL tumours and constitutive DNA

  Dataset EGAD00001008975

• Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

  Exome Sequencing and RNA Sequencing Data for PDX Samples

  Dataset EGAD00001005734

• Sporadic and endemic Burkitt lymphoma have frequent FOXO1 mutations but distinct hotspots in the AKT recognition motif

  Sample set of 74 whole-exome sequencing samples from sporadic Burkitt lymphoma patients from the UK. 33 of these samples have matched constitutional data, giving a total number of 107 samples

  Dataset EGAD00001005105

• WGS of cell-free DNA derived from plasma of patients with pediatric sarcoma and healthy controls, and lcWGS/RRBS of matched tumor tissue

  This dataset contains: i) 241 deep (median 12x) whole-genome sequencing profiles of 95 patients with Ewing sarcoma, 31 patients with other pediatric sarcomas, and 22 additional profiles from healthy controls. Sequencing was performed on a NovaSeq 6000 instrument using the NovaSeq S4 2x100 bp configuration. In addition, pilot experiments for 18 cfDNA samples were performed using Illumina HiSeq 2000/2500 machines (2x75 bp configuration). Data is provided as .fastq.gz files (2 files, .R1 and .R2, per sample). i) Low coverage whole-genome-sequencing on 43 tumor biopsy samples from patients with Ewing sarcoma with matched cfDNA samples. The samples were sequenced using a NovaSeq 6000 instrument with the NovaSeq S4 1x100 bp configuration. Data are provided as unmapped (raw) .bam files. iii) Reduced-representation bisulfite sequencing data for 38 tumor biopsy samples from patients with Ewing sarcoma with matched cfDNA samples, and 2 control samples. RRBS libraries were sequenced on Illumina HiSeq 2000/2500 machines. Data are provided as unmapped (raw) .bam files.

  Dataset EGAD00001007080

• EATL-II whole-exome sequencing profile

  Enteropathy-associated T-cell lymphoma (EATL), a rare and aggressive intestinal malignancy of intraepithelial T lymphocytes, comprises two disease variants (EATL-I and EATL-II) differing in clinical characteristics and pathological features. Here we report findings derived from whole exome sequencing of 15 EATL-II tumor-normal tissue pairs.

  Dataset EGAD00001002220

• Genome and transcriptome sequence data from an osteosarcoma patient

  Genome and transcriptome sequence data from an osteosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005870

• Longitudinal ctDNA in Uveal Melanoma

  This dataset contains data from 11 uveal melanoma patients. Plasma samples were collected at baseline, 2-weeks, 3-, 6-, and 12-months post treatment (surgery/radiation). Samples underwent targeted panel, shallow whole genome, and cfMeDIP sequencing. A total of 46 plasma samples, 7 tumours, 11 buffy coats, and 10 healthy controls are included.

  Dataset EGAD00001008998

• Genomic Analysis of Medullary Thyroid Carcinoma

  Sequence data from two medullary thyroid carcinoma patients: WGS datasets generated from tumors and matched normal tissues and RNA-Seq from tumors are included.

  Dataset EGAD00001001618

• Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

  Exome sequencing was performed on n=28 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. WES was performed on EAC biopsies at 120X average coverage, with autologous PBMCs used as germline controls at 80X average coverage. Libraries were prepared from 30 ng of input DNA using the SureSelect QXT Human All Exon V7 kit (Agilent Technologies) and sequenced on the NextSeq 550 (Illumina), 2x150 bp. BCL files were demultiplexed to FastQ files using bcl2fastq2 software (Illumina). Three paired end sequencing batches were analyzed independently (Batch1: samples 8, 10, 11, 12, 15, 17, 18; Batch2: samples 20, 24, 25, 26, 27, 29, 30, 31, 33, 34 ; Batch3: samples 35, 37, 39, 40, 41, 43, 45, 48, 54, 55, 57). RNA sequencing was performed on n=26 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. RNAseq libraries were prepared on 50 ng of total RNA (with RNA integrity index RIN >=7) with the TruSeq Stranded mRNA library preparation kit (Illumina) in accordance with low-throughput protocol. After PCR enrichment (15 cycles) and purification of adapter-ligated fragments, the concentration and length of DNA fragments were measured using D1000 Screen Tape System (Agilent), obtaining a median insert size of 311 nucleotides. Then, RNAseq libraries were sequenced using the Illumina NovaSeq platform, 1x100 bp, obtaining on average 100 million single reads per sample.

  Dataset EGAD00001010876

• Polyomavirus-positive Merkel cell carcinoma derived from a trichoblastoma suggests an epithelial origin of Merkel cell carcinoma

  Tricholastoma (TB): Exome Merkel cell carcinoma (MCC): Genome and Exome Healthy tissue (HT): Exome

  Dataset EGAD00001005223

• Genome and transcriptome sequence data from a metastatic choroidal melanoma patient

  Genome and transcriptome sequence data from a metastatic choroidal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005828

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005849

• Mixing Sample Low Grade Glioma Gender Male, Age , 34,44

  Mixed Sample of scRNA-Seq primary low grade glioma. Genders: Male, Age: 34, 44.

  Dataset EGAD00001006018

• 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

• Single nuclei RNA-sequencing of glioblastoma tumors

  Single nuclei RNA-sequencing of snap frozen glioblastoma tumor tissue with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome with intron using CellRanger.

  Dataset EGAD00001006802

• WGS seq data (56 tumor/control pairs) for study EGAS00001001394

  Part of WGS seq data of Maligant Lymphoma study (ICGC)

  Dataset EGAD00001001673

• Single cell RNA-sequencing of glioblastoma tumours

  Single cell RNA-sequencing of fresh glioblastoma tumor biopsies with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome using CellRanger.

  Dataset EGAD00001006803

• Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002981

• Deep multi-region WGS of lung cancer tumours

  Deep WGS (germline and 2-5 tumour regions) was performed on 20 patients: 13 lung adenocarcinoma, 5 squamous cell carcinoma, 2 small-cell lung cancers. A total of 68 BAM files are provided, where tumours were sequenced to 60x or 150x depth.

  Dataset EGAD00001005287

• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  These data were used in the following publication: Andradas, C.; Byrne, J.; Kuchibhotla, M.; Ancliffe, M.; Jones, A.C.; Carline, B.; Hii, H.; Truong, A.; Storer, L.C.D.; Ritzmann, T.A.; et al. Assessment of Cannabidiol and delta9-Tetrahydrocannabiol in Mouse Models of Medulloblastoma and Ependymoma. Cancers 2021, 13, 330. https://doi.org/10.3390/cancers13020330 There are 4 paired-end RNA-seq samples from paediatric brain cancer cell lines.

  Dataset EGAD00001006923

• Identification of drug resistance genes in melanoma by small RNAs expression analysis

  We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001003245

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005836

• Conserved interferon-gamma signaling and decreased immune exclusion programs in responses to immune checkpoint blockade therapy_CM38-DNA

  We analyzed baseline and on-therapy tumor biopsies from 101 patients with advanced melanoma treated with nivolumab (anti-PD-1) alone or combined with ipilimumab (anti-CTLA-4). Analysis of whole transcriptome data showed that T cell infiltration and interferon-gamma signaling signatures corresponded most highly with clinical response to therapy, with a reciprocal decrease in cell cycle and WNT signaling pathways in responding biopsies. Clinical outcome differences were likely not due to differential melanoma cell responses to interferon-gamma, as 57 human melanoma cell lines exposed in vitro to this cytokine showed a conserved interferon-gamma transcriptome response unless they had mutations that precluded signaling from the interferon-gamma receptor. Therefore, the magnitude of the antitumor T cell response and the corresponding downstream interferon-gamma signaling are the main drivers of clinical response or resistance to immune checkpoint blockade therapy.

  Dataset EGAD00001006284

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• Whole genome sequencing of osteosarcoma from patients seen at UT MD Anderson Cancer Center.

  Whole genome sequencing of 35 osteosarcoma patients (primary, relapsed, and metastatic) with matched normals. Tumors were sequenced at target 60X and matched normals at target 30X.

  Dataset EGAD00001005389

• Analysis of resistance to PLX4032 (2019-08-21)

  We have collected material from a patient who had BrafV600E mutant melanoma that was treated with PLX4032. We have germline DNA from the patient and DNA and RNA from distinct lesions before and after treatment with PLX4032. We would like to exome sequence these samples to gain a snap shot of the mechanisms of resistance that are operative. . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005278

• SF12017 scRNA-Seq Primary astrocytoma IDH mutant Male

  Single cell Primary astrocytoma G2. IDH mutant, ATRX negative. Male, 44. Single Cell RNA seq from primary astrocytoma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005395

• Mantle cell lymphoma exomes and genomes for finding driver mutations

  Tumor and normal exomes for 51 MCL patients and tumor and normal genomes for 34 MCL patients.

  Dataset EGAD00001006159

• Genome and transcriptome sequence data from a chordoma patient

  Genome and transcriptome sequence data from a chordoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003040

• Exome sequences of AL amyloidosis (ALA), multiple myeloma (MM) and ALA+MM hematological malignancies

  DNA was isolated from aberrant plasma cells (aPCs) and peripheral blood of 12 ALA, 10 ALA+MM and 29 MM individuals. DNA from aPCs was amplified using REPLI-g Mini Kit (Qiagen). Totally, we analyzed 51 patients, 102 samples. One batch of exome libraries (paired tumor-normal samples from 12 ALA, 10 ALA+MM and 6 MM) was prepared using SureSelect Human All Exon V5 Kit (Agilent Technologies) and sequenced on Illumina HiSeq 4000 platform, 100 cycles. Second batch (23 MM samples; IDs ARK01-ARK26) was prepared using SureSelect Human All Exon V5 + IGH, IGK, IGL, MYC (Agilent Technologies) library preparation kit and sequenced on Illumina HiSeq 2000 platform in paired-end settings, 75 cycles. The reads were mapped using BWA-MEM on human genome GRCh38 without alternate loci.

  Dataset EGAD00001006047

• Paired-end RNA-seq analysis of the Hypermutation and Malignant Progression in Low-grade Glioma Patients

  44 DNA samples were derived from the tumors of the low grade glioma patients and sequenced using Illumina RNAseq paired-end technology. Dataset contains 44 BAM files aligned to hg19 using Tophat 2.

  Dataset EGAD00001005387

• WES from two human osteosarcoma with two samples each from the corresponding cell line

  WES from two human osteosarcoma with two samples each from the corresponding cell line, BAM files

  Dataset EGAD00001005370

• Exome sequencing of primary and relapse neuroblastoma

  In this dataset, 16 trios- primary tumor, relapse and corresponding normals- for patients with neuroblastoma are provided. For one patient, more than one relapse was available for the analyses.

  Dataset EGAD00001001607

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002891

• Genome and transcriptome sequence data from a multifocal hepatocellular carcinoma patient

  Genome and transcriptome sequence data from a multifocal hepatocellular carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002644

• Comprehensive single cell study of lung adenocarcinoma from early to metastatic stages

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001005054

• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  38 PPTCs were sequenced using RNASeq to identify oncogenic variants in driver-unknown tumors and to explore gene expression patterns. RNA libraries were quantified by qPCR using the Kapa Library Quantification Illumina/ABI Prism Kit protocol (KAPA Biosystems). Libraries were pooled in equimolar quantities and paired-end sequenced on 2 lanes of a High Throughput Run Mode flowcell with the V4 sequencing chemistry on an Illumina HiSeq 2500 platform following Illumina’s recommended protocol to generate paired-end reads of 126-bases in length.

  Dataset EGAD00001007499

• Pediatric Papillary Thyroid Carcinoma Whole Exome Sequencing

  Exome libraries from 47 blood and tissue samples were prepared using Agilent SureSelect Human Exome Library Preparation V5 kit and the Agilent Bravo Automation System fExome libraries were pooled and sequenced with the TruSeq SBS sequencing chemistry using a V4 high throughput flowcell on a HiSeq 2500 platform following Illumina’s recommended protocol. Approximately 6-8 gigabases of raw paired end data of 126-bases were generated per exome library.

  Dataset EGAD00001007502

• Genomic characterisation of MGUS

  The hematological malignancy multiple myeloma (MM), also called Kahler's disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Dataset EGAD00001006363

• SF11644 scRNA-Seq primary GBM

  SF11644 Primary GBM Gender Male age 57. Single Cell RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005393

• SF11956 scRNA-Seq GBM IDHR132H Wildtype Male

  SF11956 IDHR132H WT GBM. Male, 63. Single Cell RNA seq from high grade glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005392