3775 results for "*oma"

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• Distribution of ctDNA levels in plasma of early-stage non-small cell lung cancer patients measured using personalised ctDNA analysis

  Blood-based assays have shown increasing ability to detect circulating tumour DNA (ctDNA) in patients with early-stage cancer. However, detection of ctDNA in patients with non-small cell lung cancer (NSCLC) has continued to prove challenging. We performed retrospective analysis to quantify ctDNA levels in a cohort of 100 patients with early-stage NSCLC prior to treatment with curative intent. Where tumour tissue was available for whole exome sequencing, mutations identified were used to define patient-specific sequencing assays. For those 90 patients, plasma cell-free DNA was sequenced to high depth across capture panels targeting a median of 328 mutations specific to each patient. Data was analysed using Integration of Variant Reads (INVAR), detecting ctDNA in 66.7% of patients, including 52.7% (29 of 55) patients with stage I disease and >88% detection for patients with stage II and III disease (16/18 and 15/17). ctDNA was detected in plasma at fractional concentrations as low as 9.1x10-6, and in patients with tumour volumes as low as 0.23 cm3. A 36-gene sequencing panel (InVisionFirst-LungTM) was used to analyse plasma DNA in 27 samples including the 10 cases without tumour exome data, and detected ctDNA in 59% of samples tested (16 of 27). Across the entire cohort, detection rates were higher in squamous cell carcinoma patients compared to adenocarcinoma patients (81% vs. 59%). Detection of ctDNA prior to treatment was associated with significantly shorter time free from relapse, across all patients and in patient subgroups, with Hazard Ratios ranging from 2.25 to >11. Our analysis indicates that for patients with stage I NSCLC, the median ctDNA fraction in plasma is approx. 12 parts per million (0.0012%). This indicates the limits of detection that would be required for ctDNA-based liquid biopsies to detect ctDNA in the majority of patients with early-stage NSCLC.

  Dataset EGAD00001006230

• Whole-genome sequencing of a thyroid carcinoma harboring a ETV6-NTRK3 fusion and a NTRK3 G623R mutation (HIPO-021)

  Dataset EGAD00001006243

• Phenotypic characterisation of LRRN4CL over-expression

  This study aims to use RNAseq to identify differentially expressed transcripts in human melanoma cells that over-express the cell surface protein, LRRN4CL, relative to empty-vector control cells, to provide mechanistic insight into how LRRN4CL over-expression confers enhanced pulmonary metastatic colonisation abilities.

  Dataset EGAD00001006249

• NABUCCO cohort 1 (NCT03387761) - Neo-Adjuvant Bladder Urothelial Carcinoma COmbination-immunotherapy

  NABUCCO cohort 1 sequencing data. The dataset includes: * Whole exome DNAseq pre-treatment on tumor samples (n=24) matched with blood samples (n=24) * RNAseq pre-treatment on tumor samples (n=18) * RNAseq post-treatment on tumor samples (n=18). Not all pre-treatment samples are linked with pre-treatment samples * High coverage Whole exome DNAseq on pre-treatment tumor samples (n=3) matched with post-treatment metastasized lymph nodes isolated with laser microdissection (n=3) * All samples are labelled with the response phenotype (Complete Responder or Non-Complete Responder)

  Dataset EGAD00001006250

• multi regional whole exome sequencing of gastric adenocarcinoma

  Multiregional whole-exome sequencing was done using 48 tumor samples (range: 4-10 tumor samples/patient) from 9 patients with adenocarcinomas of the stomach and gastroesophageal junction (GC)

  Dataset EGAD00001006251

• Convergent somatic mutations in effectors of insulin signalling in chronic liver disease

  Chronic liver disease is associated with metabolic dysregulation, liver failure and hepatocellular carcinoma. We analysed somatic mutations from 1202 genomes across 32 liver samples, including normal controls, alcohol-related and non-alcoholic fatty liver disease. Five of 27 patients with liver disease carried hotspot driver mutations in FOXO1, the major transcription factor downstream of insulin signalling. FOXO1 mutations were independently acquired by up to 5 distinct clones within the same patient’s sample, and impaired insulin-mediated nuclear export of FOXO1. GPAM, which produces storage triacylglycerol from dietary calories, also had significant excess of mutations, similarly exhibiting convergent evolution within biopsies. Telomeres were shorter in diseased than normal liver, with attrition more pronounced in larger clones. Multiple independent acquisitions of drivers within one small liver sample imply that such mutations could affect hundreds of grams of tissue across the whole organ, potentially contributing to systemic metabolic dysfunction.

  Dataset EGAD00001006255

• RNAseq BAM files

  RNAseq BAM files for Coding and non-coding mantle cell lymphoma driver mutations

  Dataset EGAD00001006268

• Melanoma exome profiling

  This dataset includes whole exome profiling of 65 early-passage metastatic melanoma cell lines. The data are provided as BAM files for tumor and normal samples.

  Dataset EGAD00001006271

• Melanoma microRNA profiling

  This dataset includes microRNA profiling of 61 early-passage metastatic melanoma cell lines. The data are provided as single-end small RNA seq fastq files.

  Dataset EGAD00001006269

• Melanoma transcriptome profiling

  This dataset includes transcriptome profiling of 68 early-passage metastatic melanoma cell lines. The data are provided as paired-end RNA seq fastq files.

  Dataset EGAD00001006270

• Raw microarray gene expression data from NPC samples_Cohort 1

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Dataset EGAD00001006273

• Raw microarray gene expression data from NPC samples_Cohort 2

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Dataset EGAD00001006272

• Processed microarray gene expression data from NPC samples_Cohort 2

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Dataset EGAD00001006274

• Processed microarray gene expression data from NPC samples_Cohort 1

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Dataset EGAD00001006275

• Single cell transcriptomes of of primary tumors and normal endometrial derived organoids treated with DBZ

  Endometrial carcinoma, the most common gynecologic cancer, develops from endometrial epithelium which is composed of secretory and ciliated cells. Pathologic classification is unreliable and there is a need for prognostic tools. We used single cell sequencing to study organoid model systems derived from normal endometrial endometrium to discover novel markers specific for endometrial ciliated or secretory cells. We performed single cell sequencing on endometrial and ovarian tumours, and on organoids both treated with DBZ and normal and found both secretory-like and ciliated-like tumour cells.

  Dataset EGAD00001006280

• MGMT genomic rearrangements contribute to chemotherapy resistance in gliomas

  Temozolomide (TMZ) is an oral alkylating agent used for the treatment of glioblastoma and is now becoming a chemotherapeutic option in patients diagnosed with high-risk low-grade gliomas. The O-6-methylguanine-DNA methyltransferase (MGMT) is responsible for the direct repair of the main TMZ-induced toxic DNA adduct, the O6-Methylguanine lesion. MGMT promoter hypermethylation is currently the only known biomarker for TMZ response in glioblastoma patients. Here we show that a subset of recurrent gliomas carry MGMT genomic rearrangements that lead to MGMT overexpression, independently from changes in its promoter methylation. By leveraging the CRISPR/Cas9 technology we generated some of these MGMT rearrangements in glioma cells and demonstrated that they lead to TMZ resistance both in vitro and in vivo. Lastly we showed that such fusions can be detected in tumor-derived exosomes and could potentially represent an early detection marker of tumor recurrence in a subset of patients treated with TMZ.

  Dataset EGAD00001006281

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

  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 EGAD00001006282

• 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

• Epigenetic subtypes of neuroblastoma - ChIPseq

  In the absence of recurrent gene mutations, evidence accumulates that epigenetic deregulation plays a prominent role in neuroblastoma biology. Here we provide genome wide H3K27ac profiles in 60 primary neuroblastoma samples.

  Dataset EGAD00001006285

• Epigenetic subtypes of neuroblastoma - RNAseq

  In the absence of recurrent gene mutations, evidence accumulates that epigenetic deregulation plays a prominent role in neuroblastoma biology. Here we provide RNAseq profiles in 71 primary and relapse neuroblastoma samples.

  Dataset EGAD00001006286

• Survival Benefit and Genetic Profile of Pemetrexed as Initial Chemotherapy in Selected Chinese Patients with Advanced Lung Adenocarcinoma

  NGS data of 12 patients enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017.

  Dataset EGAD00001006287

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Dataset EGAD00001006293

• Therapeutic vulnerabilities in the DNA damage response for the treatment of ATRX mutant neuroblastoma

  Whole genome sequencing data of isogenic ATRX/TP53 knockout clones of the neuroblastoma cell line SK-N-SH

  Dataset EGAD00001006294

• 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

• The Transcriptional Landscape of SHH Medulloblastoma

  To further understand the biology of Sonic hedgehog medulloblastoma and its molecular subtypes, we studied 250 human Shh-MB using strand-specific RNA sequencing. We identified novel alterations within the cAMP dependent pathway and found that 18% of tumors have genetic events that directly target the abundance and/or stability of MYCN. We also discovered an extensive network of fusions in focally amplified regions, and several loss-of-function fusions in tumor suppressor genes PTCH, SUFU and NCOR1. Molecular convergence on a core of specific genes by nucleotide variants, copy number aberrations, and gene fusions highlights key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma.

  Dataset EGAD00001006305

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma_CM67-RNASeq

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006306

• Clinical Outcomes by Tumor Mutational Burden and Inflammatory Gene Expression With Combined Nivolumab and Ipilimumab or Monotherapy in Advanced Melanoma - CM066-WES

  Purpose Exploratory analyses of CheckMate 066 and 067 trials were conducted to investigate associations of tumor mutational burden (TMB), a 4-gene inflammatory gene expression signature, and BRAF mutation status with tumor response, progression-free survival (PFS), and overall survival (OS) in patients with advanced melanoma. Patients and Methods Patients with known programmed death ligand 1 (PD-L1) expression and BRAF mutation status received nivolumab (NIVO) or dacarbazine in CheckMate 066 and either NIVO, ipilimumab (IPI), or NIVO+IPI in CheckMate 067. Whole exome sequencing and RNA sequencing were used to determine TMB and inflammatory gene expression signature scores, respectively. These biomarkers were evaluated in terms of their association with PFS and OS. Results In the NIVO, NIVO+IPI, and IPI arms of CheckMate 067, longer survival was associated with high (> median) versus low (≤ median) TMB with hazard ratios (HRs) (95% confidence interval [CI]) for PFS of 0.45 (0.30–0.65), 0.55 (0.38–0.81), and 0.60 (0.43–0.82), and for OS of 0.46 (0.30–0.71), 0.53 (0.34–0.82), and 0.52 (0.36–0.74), respectively. For NIVO-treated patients, these results were confirmed in CheckMate 066. A survival benefit was observed with high TMB and absence of BRAF mutation. Survival was associated with high versus low inflammatory signature scores with HRs (95% CI) for PFS of 0.56 (0.34–0.94), 0.40 (0.23–0.72), and 0.43 (0.27–0.70), and for OS of 0.37 (0.20–0.66), 0.38 (0.19–0.74), and 0.46 (0.27–0.79), in the NIVO, NIVO+IPI, and IPI arms, respectively. Weak correlations were observed between PD-L1, TMB, and the inflammatory signature. Conclusions Combined assessment of TMB, inflammatory gene expression signature, and BRAF mutation status may be predictive for response to immunotherapy in advanced melanoma.

  Dataset EGAD00001006309

• SF11940

  SF11940 snATAC Sequencing.Anaplastic Astrocytoma, IDH-mutant. Tumor location: Left Frontal. Age: 29. Sex: Male .

  Dataset EGAD00001006311

• SF10679

  SF10679 snATAC Seq. Oligodendroglioma, Anaplastic (WHO gr. 3). Tumor Location: Frontal Age: 43. Sex: Male.

  Dataset EGAD00001006312

• SF11310

  SF11310 Oligodendroglioma, IDH-mutant.Tumor Location: Frontal. Age:22. Sex: Female

  Dataset EGAD00001006313

• SF12374

  SF12374 snATAC Oligodendroglioma. Tumor Location: Right frontal. Age: 33. Sex: Male.

  Dataset EGAD00001006315

• SF10619

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

  Dataset EGAD00001006316

• SF4007

  SF4007 snATAC Seq. Oligodendroglioma (WHO gr. 2) Tumor Location: Left frontotemporal. Age:33. Sex: Female.

  Dataset EGAD00001006317

• SF10207

  SF10207 snATAC Seq. Oligodendroglioma, Anaplastic (WHO gr. 3). Tumor Location:Frontal. Age:43. Sex: Male

  Dataset EGAD00001006319

• SF4454

  Astrocytoma (WHO gr. 2)

  Dataset EGAD00001006318

• Single-cell Full Transcriptome RNA sequencing

  Single cell full transcriptome sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006325

• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327

• RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  RNA-Seq samples from the BELOB clinical trial study to find transcriptome associations with response to Bevacizumab and CCNU in glioblastoma patients

  Dataset EGAD00001006329

• Analysis of the Patient derived cells that model the intratumoral heterogeneity of hypermutated IDH1 mutant glioma

  Dataset contains paired-end Whole Exome sequencing data from 2 glioma patients (1 oligodendroglioma and 1 astrocytoma) , derived cultured cells, and derived murine xenografts.

  Dataset EGAD00001006340

• Additional Neuroblastoma whole genome sequencing data (Part 2)

  Additional Neuroblastoma whole genome sequencing data

  Dataset EGAD00001006344

• Whole Exome Sequences IberianRoma

  Dataset with 81 whole exome sequences from Iberian Roma samples.

  Dataset EGAD00001006357

• Genome-wide data Iberian Roma

  VCF file with genome-wide data for 62 Iberian Roma samples.

  Dataset EGAD00001006358

• 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

• RRBS profiling for a cohort including 88 precancer specimens from 62 resected lung nodules from 39 patients including atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (ADC) and 39 matched normal lung tissues.

  To study the evolution of DNA methylation at genome level and methylation intra-tumor heterogeneity (ITH) during early lung carcinogenesis, we performed multiregional reduced representation bisulfite sequencing (RRBS) of 127 resected lung samples from 39 patients using single end library Hiseq3000.

  Dataset EGAD00001006367

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• Medulloblastoma whole and focused exome sequencing (n=13 patients, n=37 samples)

  Whole exome sequencing: 24 samples matched tumor-normal and one matched CSF. Focused exome sequencing: 17 samples matched tumor-normal-2 time point CSF.

  Dataset EGAD00001006387

• Whole exome sequencing of endometriod ovarian cancer tumours

  Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

  Dataset EGAD00001006389

• EPC (eccrine porocarcinoma) WES samples

  Whole-exome sequencing (WES) in a well-characterized sample of 14 matched EP tumour/healthy surrounding tissue samples. The sequencing was done with paired EXOME sequencing on Illumina HiSeq 4000 using Agilent SureSelect XT HS + Human All Exon V7.

  Dataset EGAD00001006395

• Oncoscan SNP arrays for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 82 Oncoscan SNP tumor initial samples, zipped Affymetrix CEL file types, Oncoscan CNV FFPE Assay Kit, Thermo Fisher Scientific GeneChipTM Scanner 3000 7G

  Dataset EGAD00010001978

• ChIP-Seq files for RMS.

  ChIP-Seq files accompanying the paper titled "Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses".

  Dataset EGAD00001006398