4772 results for "*oma"

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• 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

• Genome and transcriptome sequence data from a left cavernous sinus invasive skull meningioma patient

  Genome and transcriptome sequence data from a left cavernous sinus invasive skull meningioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003662

• 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 EGAD00001004639

• Small cell carcinoma of the ovary, hypercalcemic type, displays frequent inactivating germline and somatic mutations in SMARCA4

  Small cell carcinoma of the ovary of hypercalcemic type (SCCOHT) is an extremely rare, aggressive cancer affecting children and young women. We identified germline and somatic inactivating mutations in the SWI/SNF chromatin-remodeling gene SMARCA4 in 75% (9/12) of SCCOHT patients in addition to SMARCA4 protein loss in 82% (14/17) of SCCOHT tumors, but in only 0.4% (2/485) of other primary ovarian tumors. These data implicate SMARCA4 in SCCOHT oncogenesis.

  Dataset EGAD00001000850

• Molecular and phenotypic data for patients enrolled in the IMmotion150 trial

  Tumor transcriptome and whole exome sequencing data (matched tumor/normal for somatic mutation calling) along with key phenotypic information are provided for patients enrolled in the phase 2 IMmotion150 trial, assessing efficacy of atezolizumab monotherapy or combination of atezolizumab and bevacizumab versus standard of care (sunitinib) in 1L renal cell carcinoma. This data set accompanies the respective Nature Medicine publication (PMID: 29867230).

  Dataset EGAD00001004183

• 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

• 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 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 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 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 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 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

• 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

• 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

• 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

• 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

• RNA sequencing of myxofibrosarcoma

  RNA sequencing (fastq files) of 29 samples of myxofibrosarcoma

  Dataset EGAD00001004102

• Genome and transcriptome sequence data from a retroperitoneal mucinous cystic adenocarcinoma patient

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

  Dataset EGAD00001003626

• 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 EGAD00001003733

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

  Genome-wide profiling of DNA methylation levels by RRBS in 150 glioblastoma tumor samples. Patients were selected to represent the general population of glioblastoma patients based on Austrian Brain Tumor Registry. These DNA methylation profiles were created for the validation of the glioblastoma progression study (GBMatch) and consist of 106 profiles from FFPE samples and 44 profiles from fresh-frozen samples. For the 44 fresh-frozen samples also WGS data (43 genomes) and RNA-seq data (37 transcriptomes) have been produced for validation purposes.

  Dataset EGAD00001004074

• WGS profiling of pediatric osteosarcoma

  Primary pediatric osteosarcoma samples were collected and profiled using WGS. When possible, germline and tumor samples were collected. For some patients, multiple tumor tissues were collected and sequenced. Some of the samples were used to derive PDTX models, which were also profiled with WGS. Paired end sequencing was performed on Illumina HiSeq instruments and FASTQ files reported.

  Dataset EGAD00001004537

• NKI-AvL OpACIN DNA-seq of stage III melanoma patients

  The dataset “NKI-AvL OpACIN DNA-seq of stage III melanoma patients" includes 2 x 18 normal and 2 x 18 tumor FASTQ files from paired-end whole exome sequencing on Illumina HiSeq2500 for 18 stage III melanoma patients.

  Dataset EGAD00001004217

• 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 EGAD00001004605

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

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

  Dataset EGAD00001004616

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

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

  Dataset EGAD00001004627

• 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 EGAD00001004632

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

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

  Dataset EGAD00001004619

• RNAseq of patients with Ewings sarcoma

  Cancer is driven my mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

  Dataset EGAD00001000444

• Genome and transcriptome sequence data from a follicular lymphoma patient

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

  Dataset EGAD00001004611

• Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

  Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

  Dataset EGAD00001000807

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

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

  Dataset EGAD00001004633

• Genome and transcriptome sequence data from a double-hit lymphoma patient

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

  Dataset EGAD00001004624

• Genome and transcriptome sequence data from a metastatic clear cell carcinoma of gynecological origin patient

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

  Dataset EGAD00001004637

• 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 EGAD00001004649

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

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

  Dataset EGAD00001004668

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Dataset EGAD00001001356

• 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 EGAD00001004680

• 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

• RNAseq - Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma

  We propose to biopsy 20 consented BRAF mutant melanoma patients at Addenbrooke's Hospital pre-treatment with vemurafenib and also upon the development of resistant disease, with the aim of using exome sequence and SNP6 data to identify novel sequence variants and copy number alterations that can be used to validate observed resistance mechanisms in our cell line models and also to use these models to inform as to likely candidate small molecule inhibitors to overcome resistance and that could be tested in the clinical trial setting.

  Dataset EGAD00001001050

• Chondromyxoid fibroma

  Chondromxoid fibroma is a benign tumour of bone with unknown underlying pathogenesis. To determine pathognomic genomic event in chondromyxoid fibroma whole genome sequencing will be undertaken to reconstruct rearrangements and find underlying mutations.

  Dataset EGAD00001001063

• Characterization of individual foci of multicentric/multifocal breast cancer using targeted next generation sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the ?quadrants? of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients? survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Dataset EGAD00001000624

• Transcriptome and Exome from longitudinal samples of human glioblastoma (newly added after 2015)

  We expanded our previous collection of longitudinal GBM patients (EGAS00001001041) by recruiting 21 additional patients. Tumor specimens were subjected to whole-exome sequencing (16 of 21 cases, with the matched normal/blood) and transcriptome sequencing (16 of 21 cases).

  Dataset EGAD00001002143

• Genomics of enteropathy-associated T cell lymphoma (EATL)

  Whole exome sequencing of enteropathy-associated T cell lymphoma (EATL) tumors and paired normals, as well as RNA-sequencing of EATL tumors: including (1) 69 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples, (2) 36 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL paired normal samples, and (3) 32 RNAseq, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples.

  Dataset EGAD00001003284

• Clear cell renal cell carcinoma (HIPO-045)

  Exome from EGAS00001001861

  Dataset EGAD00001002166

• Genome and transcriptome sequence data from an osterosarcoma patient

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

  Dataset EGAD00001003685

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

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

  Dataset EGAD00001003693

• Whole exome sequencing dataset in follicular lymphoma without evidence of transformation

  Whole exome sequencing data of 5 patients diagnosed with FL that had undergone several relapse episodes without evidence of transformation

  Dataset EGAD00001001301

• Small cell carcinoma of the ovary, hypercalcemic type, displays frequent inactivating germline and somatic mutations in SMARCA4

  Small cell carcinoma of the ovary of hypercalcemic type (SCCOHT) is an extremely rare, aggressive cancer affecting children and young women. We identified germline and somatic inactivating mutations in the SWI/SNF chromatin-remodeling gene SMARCA4 in 75% (9/12) of SCCOHT patients in addition to SMARCA4 protein loss in 82% (14/17) of SCCOHT tumors, but in only 0.4% (2/485) of other primary ovarian tumors. These data implicate SMARCA4 in SCCOHT oncogenesis.

  Dataset EGAD00001000794

• 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

• TCR- and BCR-sequencing data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Each tumor sample was cut into three pieces, yielding two end-pieces for cryovials and a middle portion placed in 10% buffered formalin. End pieces were homogenized manually and with a paddle blender (Stomacher). All paraffin-embedded blocks, including formalin-fixed tumor samples and molecular-fixed fallopian tubes, were sectioned and stained with hematoxylin and eosin prior to expert histopathological review to confirm the presence of high grade serous carcinoma. Homogenized end pieces were then flash frozen, and RNA was extracted using the miRNeasy Mini kit. Nanodrop was used to assess quality (260/280) and quantity. Total RNA samples were also QC checked using the Caliper HT RNA HiSens assay. Samples ranging from 60-255ng RNA were re-arrayed into a 96-well plate. 5'-RACE PCR was carried out as described in "The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer" (Zhang et al.). Briefly, this involved first round and nested PCR with TRB (TCR beta chain) and IGH (immunoglobulin heavy chain) gene-specific primers. The indexed libraries were sequenced on the Illumina HiSeq platform with paired-end 250bp reads using v2 chemistry reagents.

  Dataset EGAD00001003985

• BLUEPRINT September 2016, ATAC-seq Mantle Cell Lymphoma from venous blood, on Genome GRCh38

  ATAC-seq data for 5 sample(s) Mantle Cell Lymphoma from venous blood, on Genome GRCh38. 5 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002918

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

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

  Dataset EGAD00001003669

• 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 EGAD00001003673

• Whole-exome sequencing of 20 samples of actinic keratosis (10s) and cutaneous squamous cell carcinoma (10s)

  Whole-exome sequencing of 20 samples of actinic keratosis (10) and cutaneous squamous cell carcinoma (10) was performed to investigate a potential relationship between DNA methylation-based subtypes and genetic mutation patterns. 7 samples were shown to belong to the stem cell-like subclass (4 AK and 2 SCC), 12 - to the keratinocyte-like subtype (6 AK and 6 SCC) and one SCC sample is unclassified (was not included in the methylation analysis). Exome regions were captured using Agilent Low Input Exome-Seq Human v5 kit and sequenced on Illumina Hiseq4000 with paired-end 100-nucleotide reads.

  Dataset EGAD00001003765

• Genome and transcriptome sequence data from a lung adenocarcinoma patient

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

  Dataset EGAD00001004699

• DLBCL Validation (FFPE) Cohort

  miRNA-seq Cohort of 140 Formalin Fixed Paraffin Embedded Diffuse Large B-cell Lymphoma Patient Samples

  Dataset EGAD00001001073

• Genomic Analysis of Hurthel Cell (Oncocytic) Thyroid Carcinoma

  This dataset includes 2 pairs of tumour/normal whole genome sequence data as well as MEN1 gene targeted sequencing of an additional 87 specimens.

  Dataset EGAD00001001085

• Myeloma Targeted Follow-up Study

  Targeted sequencing follow-up of genomic lesions in multiple myeloma.

  Dataset EGAD00001001215

• Identification of drug resistance genes in melanoma

  Our aim is to analyze the genome of human melanoma cell lines and short term culture from human melanoma samples in order to identify genes that confer drug resistance to clinically relevant targeted therapies. We will perform whole-exome sequencing, copy number variation analysis and methylome analysis in a collection of human melanoma cell lines and short term culture that will be then screened for drug sensitivity/resistance through a library of clinically relevant drugs and drug combinations. By the combined analysis of the genomic lesion and the drug sensitivity/resistance profile of different cell lines, we will look for genes whose mutation is associated to the sensitivity or resistance to a specific drug in different samples.

  Dataset EGAD00001001124

• Mechanism and targeted therapy of Vemurafenib-Resistant Hairy-Cell Leukemia

  The discovery of the BRAF V600E mutation in almost all cases of hairy-cell leukemia has led to the widespread adoption of the BRAF inhibitor vemurafenib for treatment of chemotherapy-resistant cases. Impressive responses are reported; however, acquired resistance is common. Whilst diverse mechanisms of vemurafenib resistance have been elucidated in melanoma, the basis of resistance in HCL is unclear. Here we apply whole genome and deep targeted sequencing to investigate resistance mechanisms and potential therapeutic strategies in a patient with aquired resistance to vemurafenib.

  Dataset EGAD00001003923

• Sebaceous carcinoma tumor/normal exome sequencing and transcriptome sequencing. Transcriptome sequencing of

  Sebaceous carcinomas (SeC) are cutaneous malignancies that, in rare cases, metastasize and prove fatal. Here we report whole exome sequencing on 32 SeC, revealing distinct mutational classes that explain both cancer ontogeny and clinical course. A UV-damage signature predominated 10/32 samples, while 9 were instead defined by microsatellite instability (MSI) mutations. UV-damage SeC exhibited poorly differentiated, infiltrative histopathologycompared to MSI signature SeC (p = 0.003), features previously associated with dissemination. Strikingly, UV-damage SeC transcriptomes and anatomic distributionclosely resembling those of cutaneous squamous cell carcinomas (SCC), implicating sun-exposed keratinocytes as a cell of origin. Like SCC, this UV-damage subclass harbors a high somatic mutation burden with >50 mutations/Mb, predicting immunotherapeutic response. In contrast, ocular SeC acquire far fewer mutations without a dominant signature, but show frequent truncating mutations in the ZNF750 epidermal differentiation regulator. Our data exemplify how different mutational processes convergently drive histopathologically related but clinically distinct cancers.

  Dataset EGAD00001004016

• POT1 splice site mutant analysis

  We are interested in the contribution mutations in the Shelterin complex protein POT1 may have to the development of melanoma. We have identified a patient who carries a splice site mutation in POT1 and as part of our analysis of this gene we aim to sequence the transcriptome of this patient to see how this mutation influences splicing. RNA has been obtained from lymphocytes collected from the patient.

  Dataset EGAD00001000786

• Divergent clonal selection dominates medulloblastoma at recurrence

  Divergent clonal selection dominates medulloblastoma at recurrence

  Dataset EGAD00001000946

• Melanoma-Til Study RNAseq

  In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

  Dataset EGAD00001000325

• TERT rearrangements are frequent in neuroblastoma and identify aggressive tumors

  Whole genome sequencing detected structural rearrangements of TERT in 17/75 high stage neuroblastoma with 5 cases resulting from chromothripsis. Rearrangements were associated with increased TERT expression and targeted immediate up- and down-stream regions of TERT, placing in 7 cases a super-enhancer close to the breakpoints. TERT rearrangements (23%), ATRX deletions (11%) and MYCN amplifications (37%) identify three almost non-overlapping groups of high stage neuroblastoma, each associated with very poor prognosis. This submission contains all newly sequenced samples only.study_refcenter AMC

  Dataset EGAD00001001635

• Multiregion Whole Exome sequencing of pHGG and DIPG

  The failure to develop effective therapies for paediatric glioblastoma (pGBM) and diffuse intrinsic pontine glioma (DIPG) is in part due to their intrinsic heterogeneity. Analysis of 142 sequenced cases revealed multiple tumour subclones, spatially and temporally co-existing in a stable manner as observed by multiple sampling strategies. This dataset provides multi region sequencing of high grade gliomas and diffuse intrinsic pontine gliomas from 15 patients. DNA was extracted from FFPE sections in 2-13 regions of each tumour and sequenced with Agilent SureSelect whole exome sequencing. Germline DNA was also sequenced in 14 cases. Data was aligned to hg19 with bwa and is provided as 79 separate BAM files.

  Dataset EGAD00001004114

• Adenoma development in familial adenomatous polyposis and MUTYH‐associated polyposis: somatic landscape and driver genes

  Familial adenomatous polyposis (FAP) and MUTYH‐associated polyposis (MAP) are inherited disorders associated with multiple colorectal adenomas that lead to a very high risk of colorectal cancer. The somatic mutations that drive adenoma development in these conditions have not been investigated comprehensively. In this study we performed analysis of paired colorectal adenoma and normal tissue DNA from individuals with FAP or MAP, sequencing 14 adenoma whole exomes (eight MAP, six FAP), 55 adenoma targeted exomes (33 MAP, 22 FAP) and germline DNA from each patient.

  Dataset EGAD00001004332

• H005 WES CLL

  Whole exome sequencing from matched tumor-control samples of 121 primary lymphoma samples. Sequencing was performed on Illumina HiSeq2000. The dataset contains FASTQ files.

  Dataset EGAD00001002055

• Whole genome sequencing of adult t-cell leukemia/lymphoma

  Whole genome sequencing of single adult t-cell leukemia/lymphoma case

  Dataset EGAD00001001326

• Whole Genome Bisulfite Sequencing of Pedbrain - Medulloblastoma (20 cases)

  Whole genome bisulfite sequencing of pedbrain - medulloblastoma

  Dataset EGAD00001001891

• Mapped RNA-Seq data

  Mapped whole transcriptome RNA-Seq data from 476 human samples of early stage urothelial carcinoma.

  Dataset EGAD00001001939

• Genome and transcriptome sequence data from an adenocarcinoma of right lung patient

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

  Dataset EGAD00001001967

• Chordoma Sequencing Project RNAseq

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000653

• Genome and transcriptome sequence data from a melanoma skin cancer - squamous cell carcinoma patient

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

  Dataset EGAD00001002018

• 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 EGAD00001002046

• H005 RNA-seq CLL

  Paired-end RNA sequencing using total RNA from 136 primary lymphoma samples. Sequencing was performed on the Illumina HiSeq2000 with 300bp insert size. The dataset contains FASTQ files.

  Dataset EGAD00001002056

• Genome-wide analysis of H3K27me3 occupancy and DNA methlytion in pediatric high-grade glioma

  Genome-wide analysis of H3K27me3 occupancy and DNA methylation in K27M-mutant and H3.3-WT primary pediatric high-grade gliomas (pHGGs) as well as pediatric pHGG cell lines. The study aims to elucidate the connection between K27M-induced H3K27me3 reduction and changes in DNA methylation as well as gene expression.

  Dataset EGAD00001000677

• Leiden_melanomafamilies

  Around 10% of patients who present in melanoma clinics have a first degree relative with a previous diagnosis of melanoma. While around 3% have three or more relatives who have been diagnosed with the disease. In this project we will whole genome sequence patients from large Dutch familial melanoma pedigrees to identify mutations in genes that drive melanomagenesis. The identification of these genes will facilitate the management of familial melanoma patients and their families.

  Dataset EGAD00001002186

• Chordoma Sequencing Project Whole Genome

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000721

• Anaplastic Meningioma WGS-X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Dataset EGAD00001001267

• Whole-genome sequencing in 14 cases and whole-exome sequencing in 90 cases of Chinese ESCC

  Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide1. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC)2-3. Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients. Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 14 ESCC cases and whole-exome sequencing in 90 cases.

  Dataset EGAD00001001691

• Multiple Myeloma Diagnosis to Relapse study samples (2016-01-27)

  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 2016-01-27.

  Dataset EGAD00001001898

• Clonal expansion of mutated cell population in bladder urothelium

  1cm biospies of from patients undergoing bladder cystectomy will be collected. The underlying muscle and stroma will be removed and the remaining epithelia dissected into small sequential areas which will be sent for ultra-deep exome sequencing using a panel of known cancer and viral genes. Sequence analysis using similar methods to Martincorena I et al (Science 2015, 348:880) will provide an idea of the somatic mutational landscape in these patient samples. Individual patient muscle samples will also be sequenced as a reference.

  Dataset EGAD00001003250

• WGS of T-cell and NK-cell lymphoma for ICGC (NKTL-SG)

  WGS of T-cell and NK-cell lymphoma The tumor samples were sequenced with Illumina HiSeq 2500 platform and the resulting FASTq files have been uploaded.

  Dataset EGAD00001003271

• 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

• Whole genome sequencing data of normal/tumors pairs from 4 patients with uterine or ovarian carcinosarcoma.

  This dataset provides whole genome sequencing data of normal/tumors pairs from 4 patients with uterine or ovarian carcinosarcoma using the HiSeq 2000 sequencing system. It includes 10 samples (4 normals, 4 uterine tumors and 2 ovarian tumors). Through separate whole genome sequencing of carcinomatous and sarcomatoid components, we analyse and compare the genomic alterations of these components.

  Dataset EGAD00001003898

• 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

• Poly A transcriptom sequencing of mutifocal hepatocellular carcinoma

  Poly A transcriptome sequence of mutifocal hepatocelular carcinoma

  Dataset EGAD00001003231

• 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

• 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

• Genome and transcriptome sequence data from a metastatic rhabdomyosarcoma patient

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

  Dataset EGAD00001003668

• Exome sequencing data for LMS tumor and control samples

  The data set contains paired end fastq files for whole exome sequencing data for Leiomyosarcoma tumor and control samples

  Dataset EGAD00001003829

• 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

• Longitudinal sequencing of a recurrent paediatric high grade neuroepithelial tumour

  We have studied a unique case of astroblastoma arising in a 6 year-old girl, with multiple recurrences over a period of 10 years, with the pathognomonic MN1:BEND2 fusion 11 surgical samples from either fresh frozen of paraffin embedded material and 1 blood sample were subjected to Illumina short read whole exome sequencing using Agilent SureSelect whole exome v4. Data is provided as 15 BAM files aligned to hg19 with bwa.

  Dataset EGAD00001004118

• WES analysis of patients with USP8 wild-type corticotroph adenomas

  The overall goal of the Identification of recurrent mutations in Cushing’s disease project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project are to implement and establish the feasibility of WES in patients with USP8 wild-type corticotroph adenomas; to develop a framework for the understanding of the molecular mechanism of the pathogenesis of corticotroph adenoma.

  Dataset EGAD00001004136

• WES files for Newman MAP3K8 melanoma

  WES files for Newman MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004566

• Alternative splicing in Shh-MB

  We analyzed alternative splicing with Shh medulloblastoma. This dataset contains bam files of whole genome sequencing from 4 cases. Genomic DNA was isolated from both tumor and matched control specimens. We performed whole genome sequence on Illumina Hiseq.

  Dataset EGAD00001004347

• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Glioblastoma patient derived Fast/Slow cycling cancer stem cell RNA sequencing. Consists of 3 patient cell lines and 6 files

  Dataset EGAD00001004380

• RNA sequencing of undifferentiated sarcomas

  mRNA sequencing of 50 undifferentiated sarcoma tumour samples and 5 adjacent muscle tissue samples. BAM files are provided, with metadata specifying which samples are tumour/normal.

  Dataset EGAD00001004439