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

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• Genome and transcriptome sequence data from a malignant rhabdoid tumour tumor patient

  Genome and transcriptome sequence data from a malignant rhabdoid tumour patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015310

• Genome and transcriptome sequence data from a malignant rhabdoid tumor tumor patient

  Genome and transcriptome sequence data from a malignant rhabdoid tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015323

• Mapping Genotypes to Chromatin Accessibility Profiles in Single Cells

  In somatic tissue differentiation, chromatin accessibility changes govern priming and precursor commitment towards cellular fates1–3. Therefore, somatic mutations likely alter chromatin accessibility patterns, as they disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wild-type cells. To chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed Genotyping of Targeted loci with single-cell Chromatin Accessibility (GoT-ChA). This high-throughput platform links genotypes to chromatin accessibility at single-cell resolution, across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from myeloproliferative neoplasm (MPN) patients with JAK2V617F-mutated hematopoiesis.

  Study EGAS50000000164

• Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype

  Comprehensive analysis of the malignant cells present in the skin lesions of Mycosis fungoides, the most common subtype of cutaneous T-cell lymphoma, is complicated by the fact that malignant from reactive T cells are challenging to distinguish with certainty. To this end, combined single-cell RNA and TCR sequencing allows unambiguous identification of MF cells, thereby revealing a marked heterogeneity between and within patients with unexpected functional phenotypes. It should be further noted, that mRNA expression of established CTCL protein markers in single-cell transcriptomics to identify MF cells should be used with caution; however, our study uncovered an exciting gene expression pattern that serves as a beacon separating malignant from reactive T cells.

  Study EGAS50000000226

• Genomic and Transcriptomic Profiling of Patients with Malignant Pleural and Peritoneal Mesothelioma: The NCI Cohort

  Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. Better understanding of mesothelioma genomics and transcriptomics could advance novel therapies. We performed whole-exome sequencing (WXS) of germline and tumors of 122 patients, and RNA-sequencing (RNA-Seq) of tumor samples of 100 patients with pleural, peritoneal, and tunica-vaginalis mesothelioma.The biospecimens used in this study were collected as a part of the Mesothelioma Natural History Protocol (https://clinicaltrials.gov/ct2/show/NCT01950572), wherein, samples were collected from subjects with malignant mesothelioma as listed in the eligibility criteria below and written consent from each participant was obtained before sample acquisition.

  Study phs002207

• Genome and transcriptome sequence data from a malignant granular cell tumor tumor patient

  Genome and transcriptome sequence data from a malignant granular cell tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015275

• DNA polymerase and mismatch repair exert distinct microsatellite instability signatures in normal and malignant human cells

  Whole genome sequencing data used in the manuscript: DNA polymerase and mismatch repair exert distinct microsatellite instability signatures in normal and malignant human cells.

  Dataset EGAD00001006593

• Genomics Define Malignant Transformation in Myeloma Precursor Conditions

  Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

  Dataset EGAD00001015768

• Dynamics of Tumor Heterogeneity from Primary to Metastatic Dissemination in Prostate Cancer

  PRO-SPeCT: PROstate cancer heterogeneity deconvolution through Single cell Profiling of Chromatin accessibility and Transcriptomic output Identifying drivers of cancer progression to guide treatment selection is hindered by limited abilities to understand tumor heterogeneity’s impact on evolution. Here, we delineated the phenotypic variability across ~300,000 prostate tumor cells collected from multiple loci in primary and matched locoregional metastases. We found inter-patient heterogeneity to be confined to malignant populations. While malignant cell populations exhibit intra-locus heterogeneity, they maintain inter-loci phenotypic similarity within a patient’s prostate gland. In addition, the intra-locus heterogeneity between malignant cell populations is paired with a common clonal architecture. Lastly, we show that malignant cell populations disseminating to locoregional lymph nodes mirror the clonal architecture and phenotypic heterogeneity observed across primary tumor loci while showcasing cell state transition toward inflammatory phenotypes. These findings provide insights into distinct measures of tumor heterogeneity, revealing diverse evolutionary paths across patients converging to common phenotypic adaptations in early prostate cancer progression.

  Study EGAS50000000524

• sWGS of CTCL patients

  Paired end shallow whole genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fraction and ploidy sorted malignant CD3+/Vb+ T-cells and corresponding CD19+ non-malignant B-cells

  Dataset EGAD00001006901