12300 results for "cancer rna-seq"

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• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0019_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0019_001 for Triple negative breast cancer patient-derived xenograft SA604X7XB02089

  Dataset EGAD00001011253

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0020_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0020_002 for Triple negative breast cancer patient-derived xenograft SA604X8XB02164

  Dataset EGAD00001011254

• 10x Single Cell Gene Expression Library TENX063

  10x Single Cell Gene Expression library TENX063 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011268

• To profile the landscape of sebaceous tumours_WES

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract DNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted DNA will be used for exome sequencing. Please note that the dataset was last revised on October 16, 2025.

  Dataset EGAD00001015367

• Whole genome sequencing of tumor samples from advanced pre-treated NSCLC patients recruited in a phase I/II single-arm trial utilising CVA21, an oncolytic coxsackie virus, in combination with pembrolizumab.

  This dataset contains paired tumor and matched normal whole-genome sequencing (WGS) data from longitudinally collected samples of patients enrolled in an Australian clinical study involving multiple cancer types. For each patient, one or more tumor biopsies were obtained at different treatment time points (Scr, Day 0, Day 15, Day 22, Day 33), and matched normal samples were collected either from blood or non-tumor tissue.

  Dataset EGAD00001015682

• DNA Double Strand Breaks in KMT2A-Rearranged AML patients

  DNA breakage at specific rearrangement-participating genes, which are more sensitive to a range of environmental and chemotherapeutic agents than other regions of the human genome, contributes to the generation of leukemia-causing rearrangements, and can be used as a predictor of susceptibility to cancer caused by gene rearrangements. As a direct proof-of-principle regarding the feasibility of employing fragile site breakage to identify and monitor high-risk populations to allow personalized treatments, genome-wide DNA break mapping/sequencing was used to determine whether preferential DNA breaks are generated at the major breakpoint regions of KMT2A in AML remission patients with previously diagnosed KMT2A rearrangement. We are submitting break mapping data from three patients with KMT2A rearrangements and three non-fusion patients, with and without etoposide treatments.

  Study phs002804

• Genomic sequencing of Pediatric Rhabdomyosarcoma

  Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood accounting for approximately 350 newly diagnosed cases yearly in the United States. With the development of multimodal chemotherapy regimens, relapse-free survival rates have improved to 70-80% in patients with localized disease albeit with significant toxicity. Unfortunately, despite aggressive treatment, patients with metastatic or recurrent disease continue to suffer from high mortality. Further characterization of the genetic events underlying this tumor type is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. In a collaborative effort between the National Cancer Institute, the Children's Oncology Group, and the Broad Institute, we use a combination of whole-genome and whole-exome sequencing to characterize the landscape of somatic alterations in 147 tumor/normal pairs.

  Study phs000720

• Genome Sequencing of Hepatocellular Carcinoma at The Human Genome Sequencing Center of Baylor College of Medicine (HGSC-BCM)

  Hepatocellular carcinoma (HCC) accounts for 85-90% of primary liver cancers. We have focused on three major HCC etiologies:hepatitis C virus (HCV), hepatitis B virus (HBV), and nonviral causes. The onset and progression of cancer is driven by extensive rearrangement and mutation of the genome. We combined our capability to capture and enrich exome DNA with the next generation sequencing capacity to allow us to detect and characterize the somatic mutation profile of patients with HCC. Patient samples were collected by the Liver Center, Division of Abdominal Transplantation in the Baylor College of Medicine Department of Surgery. Sequencing of HCC is one of the NHGRI Center Initiated Projects in progress in the Human Genome Sequencing Center at Baylor College of Medicine.

  Study phs000509

• Health Professionals Follow-Up Study

  Health Professionals Follow-up Study (HPFS) is a prospective cohort study of men designed to evaluate hypotheses about men’s health related to diet and lifestyle to the incidence of serious illnesses, such as cancer, heart disease, and other vascular diseases. It consisted of 51,529 U.S. male health professionals who were 40-75 years old at baseline in 1986 and completed a mailed six-page baseline questionnaire. Information on age, height and weight, ancestry, medications, disease history, physical activity, lifestyle factors, and diet were gathered, with follow-up questionnaires sent biennially to update information and record health outcomes with every four years to update their diet. This datafile includes responses to the 2016 questionnaire, which is available at: https://cdn1.sph.harvard.edu/wp-content/uploads/sites/2471/2017/09/16L.pdf

  Study phs002460

• Establishment and Genomic Validation of Novel Patient-Derived Xenograft Models for Drug Discovery in Gastrointestinal Stromal Tumor

  This dataset contains targeted next-generation sequencing data generated with the Illumina TruSight Oncology 500 (TSO500) assay from six gastrointestinal stromal tumors (GIST) and matched patient-derived xenograft (PDX) models established at Fox Chase Cancer Center (Philadelphia, PA). GIST are most commonly driven by activating mutations in KIT or PDGFRA, and this study focused on KIT-mutant tumors. All PDXs were derived from metastatic patient tumors previously treated with one or more tyrosine kinase inhibitors (TKIs). PDXs were maintained through series of passages and represents in vivo models of differential TKI sensitivity. The dataset represents a detailed comparison of mutational profiles between primary tumors and corresponding PDXs across passages, enabling studies of genomic stability, resistance mechanisms, and the evaluation of novel therapeutic strategies in GIST.

  Study phs004185