16758 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

• snRNAseq prostate cancer

  single-nucleus RNA seq characterization of human fresh frozen prostate cancer samples and non-malignant controls for the same patients. Biopsies were sectioned in 100 micron thick sections, adjacent to those used for spatial transcriptomics.

  Dataset EGAD50000001633

• pediatric AML genomic sequences

  This dataset contains whole sequencing data from 30 patients with pediatric AML. For each patient, there is one dataset derived from tumor cells and one dataset derived from a matched non-malignant control.

  Dataset EGAD50000001572

• 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

• RNA-Seq dataset for malignant pleural and peritoneal mesothelioma

  This dataset contains RNA sequencing data of pleural and peritoneal mesothelioma. The number of samples is 18. Sequencing was performed on Illumina NovaSeq 6000 and Illumina NovaSeqXPlus. The sequencing was always paired.

  Dataset EGAD50000001342

• ChIP-seq peaks of H3K27ac

  ChIP-seq peaks of H3K27ac. The dataset includes FASTQ files, BAM files, and analyses of the ChIP-seq peaks of H3K27ac determined using MACS2

  Dataset EGAD00001008964

• ATRT whole exome sequencing

  ATRT whole exome sequencing

  Dataset EGAD00001004576

• 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