4982 results for "*oma"

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• WGS data for medulloblastoma samples (SJMB)

  WGS data of medulloblastoma tumor/control pairs.

  Dataset EGAD00001003126

• WGS data for medulloblastoma samples (ICGC)

  WGS data of medulloblastoma tumor/control pairs.

  Dataset EGAD00001003127

• Exome sequencing data for medulloblastoma samples

  Exome sequencing data for medulloblastoma tumor/control pairs

  Dataset EGAD00001003128

• Methylation of Ewing sarcoma tumors - RRBS (ICGC)

  RRBS data of 86 Ewing patients (French). Illumina HiSeq 2000/2500 (Fastq files available). Sheffield et al. Nat Med. 2017 Jan 30

  Dataset EGAD00001003133

• The spatial organization of intratumor heterogeneity and evolutionary trajectories of metastasis in hepatocellular carcinoma

  A dataset consisting of Multi-regional Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS) data for 54 samples from 9 patients with hepatocellular carcinoma. The dataset includes 45 tumor samples and 9 normal blood samples. Selected somatic variants were validated by Sequenom. Patients covered are: Patient 1, Patient 2, Patient 3, Patient 4, Patient 5, Patient 6, Patient 7, Patient 8, Patient 9 and Patient 10.

  Dataset EGAD00001003138

• RNA-sequencing of six Pilocytic astrocytoma tumors

  Total stranded TruSeq RNA sequencing by Illumina of six tumor samples from six cases of pediatric Pilocytic astrocytoma. The data is published in the following paper: Tomic TT, Olausson J, Wilzen A, Sabel M, Truve K, Sjogren H, Dosa S, Tisell M, Lannering B, Enlund F, Martinsson T, Aman P, Abel F. A new GTF2I-BRAF fusion mediating MAPK pathway activation in pilocytic astrocytoma. PLoS One. 2017 Apr 27;12(4):e0175638.

  Dataset EGAD00001003143

• Whole genome sequencing on HiSeq platform of tumour-normal sample pairs from 183 melanoma cases

  Aligned, merged and deduplicated BAM files from HiSeq whole genome sequencing of 366 samples: matched tumour-normal pairs from 183 melanoma cases comprising 48 primary melanomas, 15 cell lines, and 120 metastases. Sequencing was performed on the Illumina HiSeq 2000 and Xten platforms at Australian and Korean sequencing centres. Data was aligned to the human genome (GRCh37) using BWA-MEM.

  Dataset EGAD00001003388

• Whole-genome sequencing (WGS) data of Gastric adenocarcinoma and adjacent normal tissues

  High-coverage WGS sequencing of DNA samples from 51pairs GCs was performed on the Illumina HiSeq X Ten System.

  Dataset EGAD00001003392

• Epigenetic profiles of neuroblastoma PDXs

  This dataset contains bam files for ChIP-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft). It includes the bam files for the H3K27ac mark as well as the bam files of the corresponding input DNA for each sample.

  Dataset EGAD00001003394

• Transcriptomic profiles of neuroblastoma PDXs and primary tumors

  This dataset contains bam files for RNA-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft) and 3 pairs of neuroblastoma tumors at diagnosis and at relapse.

  Dataset EGAD00001003393

• RNAseq dataset of 34 samples (6 normals, 7 stroma-enriched, 21 malignant cells-enriched) from patients with resected pancreatic ductal carcinoma.

  RNAseq dataset of 34 samples (6 normals, 7 stroma-enriched, 21 malignant cells-enriched) from patients with resected pancreatic ductal carcinoma.

  Dataset EGAD00001003399

• Whole-genome sequencing (WGS) data of Gastric adenocarcinoma and adjacent normal tissues

  High-coverage WGS sequencing of DNA samples from 23pairs GCs was performed on the Illumina HiSeq X Ten System.

  Dataset EGAD00001003405

• Distinct genomic profile and specific targeted drug responses in adult cerebellar glioblastoma

  This dataset includes genomic information of 19 adult cerebellar glioblastomas (C-GBMs). Whole-exome sequencing data are available for 9 C-GBMs and their 8 corresponding matched blood samples, and glioma-specific targeted-DNA sequencing (GliomaSCAN) data from additional 10 C-GBMs are also available. Among them, Whole-transcriptome sequencing data were conducted for 6 C-GBM tumors.

  Dataset EGAD00001003417

• FASTQ files of total RNA-Seq data from the POPS SGA (Small for Gestational Age) samples

  All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003507

• FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

  All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003508

• BCL2 Break NegativeFollicular Lymphoma

  Whole Exome Sequencing reads consisting of BAM paired end reads from Follicular Lymphoma samples.

  Dataset EGAD00001003509

• Genome and transcriptome sequence data from a serous carcinoma of fallopian tube patient

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

  Dataset EGAD00001003001

• Genome and transcriptome sequence data from a glioblastoma multiforme patient

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

  Dataset EGAD00001003004

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

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

  Dataset EGAD00001003005

• Genome and transcriptome sequence data from a metastatic adenocarcinoma presumably of ovarian origin patient

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

  Dataset EGAD00001003008

• Genome and transcriptome sequence data from a metastatic uterine leiomyosarcoma patient

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

  Dataset EGAD00001003010

• Genome and transcriptome sequence data from a squamous cell carcinoma of the lung patient

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

  Dataset EGAD00001003011

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

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

  Dataset EGAD00001003012

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

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

  Dataset EGAD00001003016

• Genome and transcriptome sequence data from an ovarian adenocarcinoma patient

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

  Dataset EGAD00001003036

• 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

• Genome and transcriptome sequence data from a metastatic clear cell sarcoma patient

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

  Dataset EGAD00001003018

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

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

  Dataset EGAD00001003019

• Genome and transcriptome sequence data from a metastatic renal cell carcinoma patient

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

  Dataset EGAD00001003023

• Genome and transcriptome sequence data from a liposarcoma patient

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

  Dataset EGAD00001003024

• Genome and transcriptome sequence data from an endometrial adenocarcinoma patient

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

  Dataset EGAD00001003025

• Genome and transcriptome sequence data from an anaplastic myxopapillary ependymoma patient

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

  Dataset EGAD00001003027

• 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 EGAD00001003029

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

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

  Dataset EGAD00001003032

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

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

  Dataset EGAD00001003042

• Genome and transcriptome sequence data from a breast carcinoma patient

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

  Dataset EGAD00001003043

• RNASeq on HiSeq platform of 95 pancreatic adenocarcinoma cases

  BAM outputs from RSEM (https://deweylab.github.io/RSEM/) analysis of RNASeq sequencing on HiSeq platform of tumour samples from 95 pancreatic adenocarcinoma cases.

  Dataset EGAD00001003298

• Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue

  Diffuse Intrinsic Pontine Glioma (DIPG) is a fatal brain cancer that arises in the brainstem of children with no effective treatment. To understand what drives DIPGs we integrated whole-genome-sequencing with methylation, expression and copy-number profiling.

  Dataset EGAD00001003305

• Glioblastoma CRISPR Screen (2017-04-27)

  This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs. This dataset contains all the data available for this study on 2017-04-27.

  Dataset EGAD00001003308

• Multiple Myeloma Diagnosis to Relapse study samples (2017-04-27)

  The study will investigate serial samples from the same patient taken at the time of MGUS or SMM diagnosis, and later at the time of evolution towards MM. Samples will be sequenced by whole genome along with a matched normal to obtain the highest possible amount of information toinvestigate genomic changes at disease evolution. This dataset contains all the data available for this study on 2017-04-27.

  Dataset EGAD00001003309

• RNA-sequencing of SYSCOL colorectal adenoma-carcinoma samples

  RNA-sequencing alignment for SYSCOL colorectal adenoma-carcinoma samples

  Dataset EGAD00001003318

• Single-cell RNA sequencing on 5063 single T cells from six hepatocellular carcinoma patients

  T cells isolated from peripheral blood, tumors and adjacent normal tissues from six hepatocellular carcinoma patients. SmartSeq2 and Tang2009 protocol were used to amplify RNA from single T cells. High depth enables simultaneously expression profiling and TCR assembling.

  Dataset EGAD00001003337

• Radiotherapy induced Sarcoma exome (2017-05-17)

  Whole exome library making will be performed on genomic DNA derived from radiotherapy induced sarcoma samples and matched normal DNA from the same patients. Next Generation sequencing will be performed on the resulting libraries and mapped to build 37 of the human reference genome to facilitate the identification of mutations This dataset contains all the data available for this study on 2017-05-17.

  Dataset EGAD00001003339

• Whole Genome Sequencing of Mutifocal HCC tisue

  The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy.

  Dataset EGAD00001003348

• ChIP-Seq on multiple myeloma and plasma cell leukaemia cell lines

  ChIP-seq data (H3K4Me1, H3K4Me3, H3K27Ac histone modifications) in experimental triplicates on multiple myeloma cell line KMS11 and plasma cell leukaemia cell lines L363 and JJN3. ChIP reactions were performed on a Diagenode SX-8G IP-Star Compact using Diagenode automated Ideal Kit. ChIP libraries were generated using HTP Illumina library preparation kit, and sequenced using Illumina HiSeq 2000 with 100 bp single-ended reads. ChIP-seq files are in BED format.

  Dataset EGAD00001003349

• RNASeq on HiSeq platform of 56 samples from 46 melanoma cases

  BAM outputs from STAR (https://github.com/alexdobin/STAR) analysis of RNASeq sequencing on HiSeq platform of 56 tumour samples from 46 melanoma cases. Gene model = Ensembl version 70

  Dataset EGAD00001003353

• Identification of molecule relationship between intravenous leiomyomatosis and uterus myoma

  Up to now, there are two hypothesis about the pathogenesis of the relationship of intravenous leiomyomatosis and uterine myoma. One theory suggests that the IVL comes from the smooth muscle cell in the vessel wall.The other theory indicates that the IVL derives from the uterine myometrium. However, limited to the technology, few studies have been deeply explore the underlying relation. In this study, we employ the RNA sequencing to explore the molecule relationship between IVL and uterus myoma. In order to identify the molecule relationship between IVl and uterine myoma we conducted transcriptome sequencing and bioinformaitc analysis

  Dataset EGAD00001003356

• Whole exome sequencing on HiSeq platform of tumour-normal sample pairs from 53 melanoma cases

  Aligned, merged and deduplicated BAM files from HiSeq whole exome sequencing of 106 samples: matched tumour-normal pairs from 53 melanoma patients.

  Dataset EGAD00001003357

• DNA methylation (RRBS) data for the glioblastoma progression study (GBMatch).

  Genome-wide profiling of DNA methylation levels by RRBS in 349 samples, derived from 112 glioblastoma (IDH wildtype) patients, 13 IDH muated brain tumor patients, and 5 normal brain controls. For each patient samples from at least two and up to six tumor resections are available. For 6 patients multiple regions of each tumor were sampled.

  Dataset EGAD00001003427

• Whole-genome sequencing (WGS) data of Gastric adenocarcinoma and adjacent normal tissues

  High-coverage WGS sequencing of DNA samples from 45pairs GCs was performed on the Illumina HiSeq X Ten System.

  Dataset EGAD00001003431

• FASTQ files of total RNA-Seq data of POPS control samples

  Placental biopsies (n = 64 female placentas, n = 67 male placentas) were selected from healthy pregnancies from the POPs cohort. These patients had no evidence of hypertension at booking and during pregnancy, did not experience pre-eclampsia, Hemolysis, Elevated Liver enzymes, and Low Platelets (HELLP) syndrome, gestational diabetes, or diabetes mellitus type I or type II and other obstetric complications. They delivered live babies with a birth weight percentile in the normal range (20-80th percentile), with no evidence of slowing in fetal growth trajectory. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003457

• 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

• Genome and transcriptome sequence data from an adrenocortical carcinoma patient

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

  Dataset EGAD00001003053

• Genome and transcriptome sequence data from a small bowel carcinoma patient

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

  Dataset EGAD00001003055

• Genome and transcriptome sequence data from a solitary fibrous tumors (sarcoma) patient

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

  Dataset EGAD00001003056

• Genome and transcriptome sequence data from a liposarcoma patient

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

  Dataset EGAD00001003060

• Genome and transcriptome sequence data from an adenocarcinoma of the distal esophagus patient

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

  Dataset EGAD00001003061

• Genome and transcriptome sequence data from an extraosseous osteosarcoma patient

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

  Dataset EGAD00001003062

• Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the palate patient

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

  Dataset EGAD00001003065

• Genome and transcriptome sequence data from an appendiceal adenocarcinoma patient

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

  Dataset EGAD00001003066

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

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

  Dataset EGAD00001003067

• Genome and transcriptome sequence data from a pleural mesothelioma patient

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

  Dataset EGAD00001003071

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

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

  Dataset EGAD00001003073

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

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

  Dataset EGAD00001003076

• 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

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

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

  Dataset EGAD00001003086

• Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient

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

  Dataset EGAD00001003090

• Genome and transcriptome sequence data from a clear cell carcinoma of ovary patient

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

  Dataset EGAD00001003091

• A new subgroup of hepatocellular adenomas with sonic hedgehog pathway activation

  Using sequencing and gene expression analyses, we identified a subgroup of HCA characterized by fusion of the INHBE and GLI1 genes and activation of sonic hedgehog pathway. Molecular subtypes of HCAs associated with different patients’ risk factors for HCA, disease progression, and pathology features of tumors. This classification system might be used to select treatment strategies for patients with HCA. Related Publication: Molecular Classification of Hepatocellular Adenoma Associates With Risk Factors, Bleeding, and Malignant Transformation Nault, Jean-CharlesLaurent, Christophe et al. Gastroenterology , Volume 152 , Issue 4 , 880 - 894.e6 http://dx.doi.org/10.1053/j.gastro.2016.11.042

  Dataset EGAD00001003092

• Leiomyosarcoma Cancer Transcriptome Sequencing

  RNA-Seq data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 75bp paired-end protocol to a minimum mean reads of 50 million.

  Dataset EGAD00001003192

• Constit Genome Sequencing

  WGS blood data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 67 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 30x.

  Dataset EGAD00001003190

• Leiomyosarcoma Cancer Genome Sequencing

  WGS cancer data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 50x.

  Dataset EGAD00001003191

• HiSeqXTen sequencing of tumour-normal sample pairs from three mesothelioma patients

  Aligned, merged and deduplicated BAM files from HiSeqXTen sequencing of six samples: matched tumour-normal pairs from three melanoma patients.

  Dataset EGAD00001003222

• Sequencing files for "Transcriptional Mechanisms of Resistance to Anti-PD-1 Therapy"

  Files from whole exome sequencing of 26 tumors and two matched normals from one melanoma patient. The 26 tumors include the untreated primary, cutaneous metastases and distant metastases to internal organs.

  Dataset EGAD00001003200

• Precursor lesions, clonal architecture and relapse in Wilms nephroblastoma

  Targeted resequencing at high depth (21 genes, 9 chromosomal regions): at least 4 FFPE samples per case and matched germline DNA: * 100 cases with detailed outcome data, including 15 cases with tumour relapse (515 samples) * 40 cases with matched pre-chemotherapy biopsies (240 samples) * 50 nephrogenic rests matched to above cases (50 samples) We expect a proportion (possibly 10%) of cases to be mutationally silent on the above studies, and propose to subsequently carry out integrated whole-genome, methylome and transcriptome studies on matched frozen tissue from these cases

  Dataset EGAD00001003217

• High-grade meningioma sequencing data

  Whole genome, whole exome, and custom panel sequencing of high-grade meningioma cohort

  Dataset EGAD00001003220

• BGISeq-500 sequencing of tumour-normal sample pairs from three mesothelioma patients

  Aligned, merged and deduplicated BAM files from BGISeq-500 sequencing of six samples: matched tumour-normal pairs from three melanoma patients.

  Dataset EGAD00001003221

• Poly A transcriptom sequencing of mutifocal hepatocellular carcinoma

  Poly A transcriptome sequence of mutifocal hepatocelular carcinoma

  Dataset EGAD00001003231

• Genetic profiling of mucosal melanoma

  Primary mucosal melanomas (MMs) arise from melanocytes located in mucosal membranes lining the respiratory, gastrointestinal and urogenital tracts. MMs frequently present late and have a poor prognosis; the 5-year survival rate is only 14%. MM makes up only ~1.4% of all melanomas and it is this rarity that makes knowledge of the genetic changes that contribute to its pathogenesis limited to a small number of exome/genome studies and other targeted studies. Thus to investigate the somatic alterations and mutation spectra in MM genomes, we have extracted genomic DNA from formalin-fixed, paraffin-embedded (FFPE) human MMs, and subjected them to whole exome sequencing. Given the propensity of MM to metastasize, we will also be sequencing metastatic MM lesions; primary and metastatic lesions from the same individual represent an excellent opportunity to identify potential drivers of metastasis in MM. Finally we will sequence 'normal' DNA from the same individual, where possible, to exclude germline variations.

  Dataset EGAD00001003237

• Spatial heterogeneity of follicular lymphoma

  Follicular lymphoma (FL) is an incurable B cell malignancy characterized by advanced stage disease and a heterogeneous clinical course. Recent genomic studies have focused on profiling “single” FL biopsies over several time-points, however, multi-site sampling in solid cancers has demonstrated profound spatial intra-tumor heterogeneity (ITH) with implications for precision medicine based initiatives. This study examined the extent of spatial heterogeneity in FL by whole exome sequencing 22 synchronously removed spatially separated biopsies from 9 patients. We observed significant differences in the extent of ITH across cases, with two distinct patterns of high and low spatial heterogeneity emerging. Site-specific alterations in genes with biological, prognostic or therapeutic relevance included, TNFRSF14, PIK3CD, TNFAIP3, PTEN, EP300 and XBP1. In depth characterization of these variants using deep-sequencing techniques confirmed their discordant nature, suggesting on-going genetic diversification driving evolution after widespread tumor dissemination. There was evidence of tumors comprising multiple competing subclones, with distinct clusters of mutations demonstrating differential expansions within spatially-separated sites. For cases where spatial tumors were examined at two time-points (FL and transformation to diffuse large B cell lymphoma (DLBCL)), the degree of heterogeneity increased with transformation. Collectively, our results demonstrate that spatial ITH is prevalent in FL. The existence of site-specific aberrations suggests that a single biopsy may not be sufficient in all patients to capture the full genomic complexity present and these spatial variations need to be considered in biomarker-led clinical studies.

  Dataset EGAD00001003553

• The genomic landscape of cutaneous squamous cell carcinoma based on 40 paired normal and tumour whole-exome sequencing samples

  40 paired normal and tumour whole-exome sequencing samples was used to investigate the genomic landscape of cutaneous squamous cell carcinoma

  Dataset EGAD00001003555

• Whole exome sequencing of SU- DIPG-XIII from different sites

  Whole exome sequencing of diffuse intrinsic pontine glioma (DIPG) cells isolated from the pons and from a sub-ventricular zone site of spread within the frontal lobe from the same individual (SU- DIPG-XIII)

  Dataset EGAD00001003563

• Clonal evolution study of Intrahepatic cholangiocarcinoma: 69 PDPCs and 6 tissues.

  Clonal evolution study of Intrahepatic cholangiocarcinoma: 69 PDPCs and 6 tissues.

  Dataset EGAD00001003574

• SPEN loss drives extra-follicular diffuse large B cell lymphoma with female-specific lethality and TLR pathway therapeutic vulnerabilities

  Multiome (ATAC and GEX) sequencing for one rLN sample and one DLBCL sample

  Study EGAS50000001594

• Genomic landscape of Ewing sarcoma (ICGC project)

  The Ewing sarcoma project aims to sequence 100 complete genomes of cells of patients suffering from this disease. It is an initiative of great projection, since this is the second most common bone tumor in children and teenagers. The goal of the project is to establish the catalogue of somatic mutations that may cooperate with EWS-ETS fusion in the development of the tumor. The Ewing sarcoma project aims to perform 100 whole genome sequencing of germline and tumor DNA as well as at least 50 RNA-seq from tumors. Correlations between molecular profiles and clinical features will be established. The mutated genes will be further validated in a series of 500 Ewing sarcoma cases from our Tumor Bank.

  Study EGAS00001000855

• Transcriptome sequencing of gingivo-buccal oral squamous cell carcinoma for integrative analysis: alterations in expression of genes attributable to methylation changes

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out transcriptome (n=72) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India. RNA sequencing was performed on tumor and paired adjacent normal samples from 72 OSCC-GB patients. From each patient, total RNA was extracted from tumor and normal tissue samples using AllPrep DNA/RNA Mini Kit (QIAGEN). The quality and concentration of isolated total RNA were checked using Agilent 2100 Bioanalyzer and NanoDrop 2000 (Thermo Fisher Scientific). The OD260/OD280 ratio was ≥ 2 and RNA Integrity Number (RIN) was ≥ 7.0 for all sequenced samples. Ribosomal RNA (rRNA) was removed from the RNA samples, using Ribo-Zero Magnetic Kit (Epicentre). Sequencing libraries were prepared from rRNA depleted samples using TrueSeq RNA Sample Preparation Kit (Illumina). Each triplex cDNA library pool was sequenced as 100bp paired-end on HiSeq-2000 or HiSeq-2500 (Illumina). Protocols suggested by the manufacturers were used for all assays.

  Study EGAS00001003893

• Targeting the DNA Repair Pathway in Ewing Sarcoma

  Ewing’s Sarcoma is a bone and soft tissue tumor that primarily affects adolescents and young adults. With current therapies, 70% of patients with localized disease survive but survival for metastatic and recurrent disease is poor. Whole genome sequencing of 19 Ewing’s Sarcoma tumors showed that STAG2 was mutated in 10% (2/19) of the tumors and STAG2 protein was absent in 14% (13/106) tumors by immunohistochemical staining. Previous studies have shown that glioblastoma cells lacking STAG2 are more sensitive to poly-ADP ribose polymerase (PARP) inhibitors. We found that Ewing’s Sarcoma cell lines are sensitive to PARP inhibitors irrespective of STAG2 protein expression. Ewing Sarcoma cell lines are defective in double strand DNA break repair. PARP inhibitor cytotoxicity in Ewing’s Sarcoma cells was potentiated 10-1,000 fold by DNA damaging agents (irinotecan and temozolomide). To extend these studies in vivo, we developed an orthotopic Ewing’s Sarcoma mouse model and performed pharmacokinetic and pharmacodynamic studies with three different PARP inhibitors (BMN-673, olaparib and veliparib) in clinical development for pediatric cancer. Those data were used to design preclinical phase I studies to identify tolerable drug combinations for pilot efficacy testing (preclinical phase II). Based on the results of the preclinical phase I/II data, we performed a double blind, randomized, placebo controlled preclinical phase III trial with 274 mice in 15 treatment groups. Irinotecan administered in a low-dose protracted schedule optimized for pediatric patients was an effective DNA damaging agent to combine with olaparib and BMN-673 and was better tolerated than combinations with temozolomide. Combining olaparib or BMN-673 with irinotecan and temozolomide gave complete and durable responses in over 80% of the mice.

  Study EGAS00001000839

• Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma

  Diffuse large B cell lymphoma (DLBCL) is the most common hematologic malignancy and is characterized by a striking degree of heterogeneity. We enrolled a total of 1001 DLBCL patients and comprehensively defined the landscape of genetic mutations, copy number alterations and expression through whole-exome and transcriptome sequencing. We identified 150 genetic drivers of DLBCL including many novel, clinically relevant genes (e.g. SPEN, SETD1B and KLHL14). Genetic drivers were highly enriched among essential genes identified by CRISPR screening in DLBCL cell lines including those of immediate potential therapeutic relevance such as MTOR, SYK, SF3B1 and XPO1. RHOA emerged as a critical driver gene from our genetic analysis and CRISPR screen; we further delineated its functional role in vitro and in vivo models to define its role as an essential oncogene in DLBCL. Our work thus identifies the functional landscape of genetic drivers and their clinical and therapeutic relevance in DLBCL patients.

  Study EGAS00001002606

• Clinical activity and molecular correlates of response to atezolizumab alone or in combination with bevacizumab versus sunitinib in renal cell carcinoma

  We examined pre-treatment tumors from participants of the IMmotion150 trial. Biomarker analyses indicate that high angiogenesis gene expression was associated with improved PFS within the sunitinib arm, and high T-effector/IFNγ response (Teff) gene expression with longer PFS in atezolizumab + bevacizumab vs sunitinib patients. In high Teff tumors, concomitant high myeloid inflammation was associated with worse PFS in the atezolizumab monotherapy arm; adding bevacizumab to atezolizumab in this subgroup improved PFS vs atezolizumab. Molecular profiles suggest that prediction of outcomes with VEGF inhibitors and immunotherapy may be possible in mRCC, and bevacizumab may overcome myeloid inflammation-associated atezolizumab resistance.

  Study EGAS00001002928

• Delineating intratumoural heterogeneity and neoantigen-directed immune escape in Esophageal Squamous Cell Carcinoma

  Delineating intratumoural heterogeneity and neoantigen-directed immune escape in Esophageal Squamous Cell Carcinoma

  Study EGAS00001003832

• Promoter capture HiC on KMS11 (multiple myeloma)

  Promoter capture HiC on KMS11 (multiple myeloma)

  Dataset EGAD00001003597

• ICGC PedBrain DNA methylation sequencing

  DNA methylation profiling of 107 medulloblastoma and 8 control samples by high-coverage whole-genome bisulfite (WBGS) sequencing and Illumina Infinium HumanMethylation450k array.

  Study EGAS00001000561

• Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade

  We conducted integrated multi-omics evaluation of 823 tumors from advanced renal cell carcinoma (RCC) patients and identified molecular subsets associated with differential clinical outcomes to angiogenesis blockade alone or with a checkpoint inhibitor. Unsupervised transcriptomic analysis revealed six molecular subsets with distinct angiogenesis, immune, cell cycle, metabolism, and stromal programs. While sunitinib was effective in subsets with high angiogenesis, atezolizumab+bevacizumab improved clinical benefit in tumors with high T-effector and/or cell cycle transcription. Somatic mutations in PBRM1 and KDM5C associated with high angiogenesis and AMPK/Fatty acid oxidation gene expression, while CDKN2A/B and TP53 alterations were more prevalent in tumors with increased cell cycle and anabolic metabolism. Sarcomatoid tumors exhibited low prevalence of PBRM1 mutations and angiogenesis markers, frequent CDKN2A/B, BAP1 and TP53 alterations, and increased PD-L1 expression. These findings can be applied to molecularly stratify advanced RCC patients, explain improved outcomes of sarcomatoid tumors to checkpoint blockade, and develop personalized therapies.

  Study EGAS00001004353

• 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 EGAD00001003637

• Genome and transcriptome sequence data from a metastatic paraganglioma patient

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

  Dataset EGAD00001003636

• Genome and transcriptome sequence data from a solitary fibrous tumors (sarcoma) patient

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

  Dataset EGAD00001003634

• Genome and transcriptome sequence data from a radiation-induced pleomorphic sarcoma patient

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

  Dataset EGAD00001003630

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of appendiceal origin patient

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

  Dataset EGAD00001003628

• Genome and transcriptome sequence data from a salivary duct carcinoma patient

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

  Dataset EGAD00001003627

• 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 EGAD00001003603