13393 results for ""pdc"+"heritage+language"+census+study"

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• Genome and transcriptome sequence data from a hemangioma patient

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

  Dataset EGAD00001005900

• Genome and transcriptome sequence data from a pancreatic cancer patient

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

  Dataset EGAD00001005902

• Somatic mutations and single cell transcriptomes reveal the root of malignant rhabdoid tumours

  Like many childhood cancers, malignant rhabdoid tumours (MRT) are thought to arise from aberrant foetal development. Although MRT predominantly exhibit a mesenchymal phenotype, it has been suggested that the foetal root of MRT lies in neural crest development. Here, we combine phylogenetic analyses of MRT, single cell mRNA assays, and functional experiments in patient-derived MRT organoids, to define the embryological origin of MRT and explore therapeutic avenues that may drive MRT differentiation. Phylogenetic analyses from the distribution of somatic mutations revealed that MRT were related to neural crest-derived, but not to mesodermal tissues, providing direct evidence of the neural crest origin of MRT in humans. In MRT organoids, reversal of the principal driver event underpinning MRT, SMARCB1 loss, induced differentiation along mesenchymal pathways. Together, these findings placed MRT cells on a developmental trajectory of neural crest to mesenchyme conversion, and defined the transcriptional changes underpinning MRT differentiation. Searching perturbation databases for agents that mimic these mRNA changes, we identified HDAC and mTOR inhibition as potential differentiation agents. Treatment of MRT organoids with this drug combination induced proliferation arrest with transcriptional changes akin to SMARCB1 re-expression. Our study defines the embryological root of MRT and proposes a differentiation treatment for this often fatal childhood cancer.

  Dataset EGAD00001006296

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• Genome sequence data from a metastatic rectal carcinoma patient

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

  Dataset EGAD00001010972

• Genome and transcriptome sequence data from a rectal adenocarcinoma patient

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

  Dataset EGAD00001010981

• Genome and transcriptome sequence data from a cerebellar glioma patient

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

  Dataset EGAD00001010982

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001010984

• Genome sequence data from a metastatic paraganglioma patient

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

  Dataset EGAD00001010985

• 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 EGAD00001010987

• Genome and transcriptome sequence data from a prostate adenocarcinoma patient

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

  Dataset EGAD00001010988

• Genome and transcriptome sequence data from a colorectal cancer patient

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

  Dataset EGAD00001010991

• Genome and transcriptome sequence data from a primary unknown patient

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

  Dataset EGAD00001010995

• Genome and transcriptome sequence data from a hepatic cholangiocarcinoma patient

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

  Dataset EGAD00001010997

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001010998

• Genome and transcriptome sequence data from a melanoma patient

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

  Dataset EGAD00001011000

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

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

  Dataset EGAD00001011001

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

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

  Dataset EGAD00001011004

• Genome and transcriptome sequence data from a colorectal adenocarcinoma patient

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

  Dataset EGAD00001011008

• Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient

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

  Dataset EGAD00001011012

• Genome and transcriptome sequence data from a metastatic melanoma patient

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

  Dataset EGAD00001011018

• 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

• CcRCC_metabolic_heterogeneity

  Heterogeneity is a hallmark of clear cell renal cell carcinoma (ccRCC). In this study, hyperpolarized [1-13C]pyruvate MRI (HP-13C-MRI) was used to probe metabolic heterogeneity non-invasively in 6 ccRCC patients from which 58 tumor and healthy tissues biopsies were acquired postoperatively. MRI parameters were correlated with 146 metabolite concentrations and the expression of 2523 metabolic genes across 34 metabolic pathways. Using metabologram projections and pathway consensus scoring, several metabolic pathways were correlated with the metabolic MRI, including glycolysis, pentose phosphate pathway, and the TCA cycle. A simple thresholding approach applied to the imaging metrics was sufficient to provide meaningful metabolic pathway information. We also show that tissue metabolic heterogeneity increases in regions with higher pyruvate-to-lactate conversion on imaging. These results provide validation of the biological relevance of HP-13C-MRI and support the possibility of its clinical use to improve disease characterization, stratification, targeting of biopsies, and providing novel methods to monitor treatment response.

  Dataset EGAD00001015780

• Genomic evolution and natural history of myeloproliferative neoplasms on therapy - triple-negative-ET

  Philadelphia-negative myeloproliferative neoplasms are chronic blood neoplasms. Treatments control blood counts but disease can progress to myelofibrosis or acute myeloid leukaemia. We performed longitudinal whole-genome and targeted sequencing in 30 patients, integrating clonal dynamics with 7,986 blood counts and clinical histories. Distinct evolutionary patterns distinguished stable from progressive disease, with leukaemic transformation arising via TP53 loss, stepwise driver mutation acquisition within complex clones, or emergence of independent leukaemic clones. In contrast, stable disease showed long-term clonal equilibrium without new drivers. Phylogenetic analysis using 203 whole-genomes of haematopoietic colonies revealed age-appropriate polyclonal haematopoiesis in triple-negative essential thrombocythaemia and germline predisposition to thrombocytosis, supporting non-neoplastic origins. Therapy-associated mutagenesis was observed, including C>G mutations following azacitidine and characteristic T>A/T>G after hydroxycarbamide exposure in blood cells, although not in skin where UV damage predominated. These findings demonstrate progression is genomically encoded years in advance and support serial monitoring and further study of treatment-related mutagenesis.

  Dataset EGAD00001016066

• Genomic evolution and natural history of myeloproliferative neoplasms on therapy - MPN_bulk

  Philadelphia-negative myeloproliferative neoplasms are chronic blood neoplasms. Treatments control blood counts but disease can progress to myelofibrosis or acute myeloid leukaemia. We performed longitudinal whole-genome and targeted sequencing in 30 patients, integrating clonal dynamics with 7,986 blood counts and clinical histories. Distinct evolutionary patterns distinguished stable from progressive disease, with leukaemic transformation arising via TP53 loss, stepwise driver mutation acquisition within complex clones, or emergence of independent leukaemic clones. In contrast, stable disease showed long-term clonal equilibrium without new drivers. Phylogenetic analysis using 203 whole-genomes of haematopoietic colonies revealed age-appropriate polyclonal haematopoiesis in triple-negative essential thrombocythaemia and germline predisposition to thrombocytosis, supporting non-neoplastic origins. Therapy-associated mutagenesis was observed, including C>G mutations following azacitidine and characteristic T>A/T>G after hydroxycarbamide exposure in blood cells, although not in skin where UV damage predominated. These findings demonstrate progression is genomically encoded years in advance and support serial monitoring and further study of treatment-related mutagenesis.

  Dataset EGAD00001016067