16452 results for "sec+and+unspecified+malignant+neoplasm"

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• Whole exome sequencing of pediatric soft tissue sarcoma PDX models

  Childhood cancer remains one of the leading causes of death in pediatric patients in Europe. Pediatric sarcomas, comprising soft tissue sarcomas and malignant bone tumors, are a heterogenous group of malignancies, with more than 50 subtypes (WHO classification). Due to low case numbers, studying pediatric sarcomas requires accurate and reliable preclinical models. Here, we established 18 soft tissues sarcoma PDX models, including Ewing Sarcoma, Rhabdmyosarcoma and Osteosarcoma. We characterized these models by Whole Exome Sequencing and assessd the response to a wide range of drugs.

  Study EGAS50000000048

• Mesothelioma Genomics Study - WGS tumour/normal pairs

  Malignant mesothelioma (MM) is an incurable and aggressive tumour that occurs principally in the pleura as a consequence of inhaling asbestos fibres. There are >15,000 cases per annum worldwide, the incidence is increasing and Australia has one of the world's highest incidence rates. Surgery, chemotherapy and radiotherapy (or their combinations) all feature in the clinical management but do not impact significantly on overall survival. This study uses whole genome sequencing (WGS) with the aim of identifying mesothelioma-related genomic alterations and potentially identifying novel treatment strategies.

  Study EGAS00001002299

• MSK SPECTRUM - SPatiotemporal Evolution of Cancer Traced Using Multimodalities

  MSK SPECTRUM is a multi-modal, interdisciplinary prospective study of spatiotemporal determinants of high-grade serous ovarian cancer (HGSOC) evolution, treatment and response. Accounting for ~80% of ovarian cancers, HGSOC is the most lethal gynecological malignancy and is a cancer of major unmet clinical need. Challenges in disease management relate to several unresolved questions about disease biology and diagnostic modalities. Prospective longitudinal collection of tissues and blood from laparoscopic biopsies and debulking surgeries enable multi-modal molecular measurements. The program brings together formidable expertise at Memorial Sloan Kettering Cancer Center (MSKCC) across the disciplines of high-resolution genomics and computer science, radiology and radiomics, surgery, tissue banking and sample preparation, medical oncology, immuno-oncology and high-resolution tissue profiling to generate a comprehensive and integrative dataset that will allow us to address the following major aims: i) characterize malignant and immune diversity at diagnosis, ii) survey the co-evolution of malignant cells and the immune response, and iii) stratify patients on standard-of-care and investigational compounds based on their genomic and transcriptomic signatures and changes to relevant genes (TP53, CCNE1, BRCA1/2, CDK12). The goal is to create a framework to utilize integrated multi-modal data as a route to advanced diagnostics and to ultimately establish a proof-of-concept for integrated diagnostics.

  Study phs002857

• 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

• ATAC-seq in colon normal mucosa

  ATAC-seq

  Dataset EGAD00001007690

• GATCI whole genome sequencing fastqs

  Raw whole genome sequencing data (fastq) for the GATCI project

  Dataset EGAD00001005926

• Acquired Cross-Resistance in Small Cell Lung Cancer Patient-Derived Xenografts

  Here we present whole genome sequencing and RNA sequencing of patient-derived xenograft (PDX) models of small cell lung cancer (SCLC). These models were derived at a variety of clinical time points from either biopsy/resection samples, malignant effusions, or circulating tumor cells (CTCs), and grown in the subcutaneous flank of NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl /SzJ) mice. The first analysis published with these data was to determine the genomic and transcriptomic features of PDX models derived after relapse that demonstrated in vivo resistance to multiple chemotherapy regimens (cross-resistance).

  Study phs003486

• DAC Dr. PORTEU – Gustave Roussy

  Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways Data Access Committee Members (Name, Email, Job Title): Principal Investigator PORTEU Françoise (FRANCOISE.PORTEU@gustaveroussy.fr) Head of Bioinformatics platform DELOGER Marc (Marc.DELOGER@gustaveroussy.fr) Data Protection Officer BECHET Clara (Clara.BECHET@gustaveroussy.fr)

  Dac EGAC50000000252

• Balanced Ependymoma

  We propose to definitively characterise the somatic genetics of a number of pediatric malignant tumours including ependymoma, high grade glioma and central nervous system primitive neurectodermal tumours through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Dataset EGAD00001000350

• Modeling Malignant Progression in Glioma

  Gliomas are the most common primary brain tumor in humans. Low-grade gliomas (WHO grade II) invariably progress to high-grade gliomas (WHO grade III or IV). Although malignant progression may take many years, the survival rate after transformation to a high-grade glioma is poor, often only 12-15 months. In this data set, we have identified low-grade gliomas that have progressed to high-grade gliomas or high-grade gliomas that have progressed from low-grade gliomas. Some cases are matched pairs (meaning we have both the original low-grade tumor and the subsequent high-grade tumor). The samples deposited have been analyzed with bulk-RNA sequencing. They are also de-identified but are clinically annotated. When available, genetic information including IDH mutation status, 1p/19q deletion and histological subtype are also included.

  Study phs002607

• Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

  Malignant rhabdoid tumor (MRT) is one of the most aggressive childhood cancers for which no effective treatment options are available. Reprogramming of cellular metabolism is an important hallmark of cancer, with various metabolism-based drugs being approved cancer treatment. In this study, we use patient derived tumor organoids (tumoroids) to map the metabolic landscape of several pediatric cancers. Combining gene expression analyses and metabolite profiling using mass spectrometry, we find nucleotide biosynthesis to be a particular vulnerability of MRT. Treatment of MRT tumoroids with de novo nucleotide synthesis inhibitors lowers nucleotide levels in MRT tumoroids and induces apoptosis. Lastly, we demonstrate invivo efficacy of methotrexate in an MRT PDX mouse model. Our study revealsnucleotide biosynthesis as an MRT-specific metabolic vulnerability, which can ultimately lead to better treatment options for children suffering from this lethal pediatric malignancy.

  Study EGAS00001007877

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

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

  Dataset EGAD00001005387

• Sequencing data for oesophageal and related samples - Katz-Summercorn, Jammula et al (RNA)

  Data supporting: “Multi-omic cross-sectional cohort study of pre-malignant Barrett’s esophagus reveals structural variation and retrotransposon activity occur early in cancer evolution.” Katz-Summercorn, Jammula et al. RNAseq (BAM files)

  Dataset EGAD00001006353

• cytogenetically visibile inversions

  Pacbio Hifi whole genome sequencing data from six individuals carrying cytogenetically visible inversions. The HiFi data was produced on the PacBio Revio machine, using 1 flowcell per sample. The resulting data was aligned to hg19 using minimap2, and converted into bam using samtools.

  Dataset EGAD50000000635

• Targeted capture sequencing from High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  Targeted capture sequencing for 366 newly added samples in High-grade B-cell lymphoma, not otherwise specified: an LLMPP study and 29 samples from a previously uploaded dataset.

  Dataset EGAD50000001364

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

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

  Dataset EGAD00001005105

• Sequencing data for oesophageal / related samples - Foley, Shorthouse et al (RNA)

  Data supporting: "SMAD4 and KCNQ3 Alterations are Associated with Lymph Node Metastases in Oesophageal Adenocarcinoma" RNAseq (FASTQ files) 6 samples

  Dataset EGAD00001011065

• Methylation data

  To ellucidate methylation activity in mRCC, methylation data was generated as part of the EuroTarget study

  Dataset EGAD50000002295

• RNA-seq

  RNA-seq data

  Dataset EGAD00001008959

• PacBio medulloblastoma datasets

  PacBio data from 5 medulloblastoma tumor-normal pairs. The data consists of BAM files aligned using NGMLR

  Dataset EGAD00001010852

• TGL49_HBC sWGS

  Shallow whole genome sequencing of plasma samples from healthy control patients.

  Dataset EGAD00001010000

• McGill EMC Release 4 for assay "H3K27ac"

  McGill EMC Release 4 for assay "H3K27ac"

  Dataset EGAD00001001298

• McGill EMC Release 4 for assay "H3K9me3"

  McGill EMC Release 4 for assay "H3K9me3"

  Dataset EGAD00001001299

• McGill EMC Release 4 for assay "H3K4me1"

  McGill EMC Release 4 for assay "H3K4me1"

  Dataset EGAD00001001296

• McGill EMC Release 4 for assay "H3K36me3"

  McGill EMC Release 4 for assay "H3K36me3"

  Dataset EGAD00001001295