3772 results for "*oma"

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• Genome and transcriptome sequence data from a metastatic thymic carcinoma patient

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

  Dataset EGAD00001004678

• Genome and transcriptome sequence data from a metastatic breast carcinoma patient

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

  Dataset EGAD00001004688

• Genome and transcriptome sequence data from a metastatic leiomyosarcoma patient

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

  Dataset EGAD00001004639

• 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 EGAD00001004642

• Genome and transcriptome sequence data from a metastatic lung adenocarcinoma patient

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

  Dataset EGAD00001004644

• Genome and transcriptome sequence data from a locally advanced oropharyngeal carcinoma patient

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

  Dataset EGAD00001004655

• Genome and transcriptome sequence data from a metastatic ampullar carcinoma patient

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

  Dataset EGAD00001004657

• Genome and transcriptome sequence data from a metastatic osteosarcoma patient

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

  Dataset EGAD00001004658

• Genome and transcriptome sequence data from a metastatic clear cell carcinoma of the ovary patient

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

  Dataset EGAD00001004661

• Genome and transcriptome sequence data from a metastatic leiomyosarcoma of pancreas patient

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

  Dataset EGAD00001004662

• Genome and transcriptome sequence data from a uterine sarcoma patient

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

  Dataset EGAD00001002538

• 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 EGAD00001002585

• Genome and transcriptome sequence data from a rectosigmoid adenocarcinoma (colorectal cancer) patient

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

  Dataset EGAD00001002567

• Genome and transcriptome sequence data from a leiomyosarcoma patient

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

  Dataset EGAD00001002570

• Genome and transcriptome sequence data from a right breast carcinoma patient

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

  Dataset EGAD00001002580

• Genome and transcriptome sequence data from a metastatic myxofibrosarcoma patient

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

  Dataset EGAD00001002581

• Genome and transcriptome sequence data from an osteogenic sarcoma patient

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

  Dataset EGAD00001002562

• Genome and transcriptome sequence data from an adenomacarcinoma of vulva patient

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

  Dataset EGAD00001002590

• Genome and transcriptome sequence data from a squamous cell carcinoma of anus patient

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

  Dataset EGAD00001002628

• 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 EGAD00001002642

• Genome and transcriptome sequence data from a small cell/neuroendocrine carcinoma of the lung patient

  Genome and transcriptome sequence data from a small cell/neuroendocrine carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002617

• Genome and transcriptome sequence data from a myxoid liposarcoma patient

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

  Dataset EGAD00001002620

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

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

  Dataset EGAD00001002623

• Genome and transcriptome sequence data from a Ewing sarcoma patient

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

  Dataset EGAD00001002625

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

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

  Dataset EGAD00001005836

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of unknown primary (upper GI?) patient

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

  Dataset EGAD00001005837

• Genome and transcriptome sequence data from a carcinoma primary unknown origin patient

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

  Dataset EGAD00001005840

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

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

  Dataset EGAD00001005849

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the lung patient

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

  Dataset EGAD00001005850

• Genome and transcriptome sequence data from an endometrioid ovary carcinoma patient

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

  Dataset EGAD00001005859

• Genome and transcriptome sequence data from a transformed diffuse large B cell lymphoma patient

  Genome and transcriptome sequence data from a transformed diffuse large B cell lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005869

• Genome and transcriptome sequence data from a chordoma patient

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

  Dataset EGAD00001005871

• Genome and transcriptome sequence data from a breast carcinoma patient

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

  Dataset EGAD00001005888

• Genome and transcriptome sequence data from a thyroid hurthle cell carcinoma patient

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

  Dataset EGAD00001005891

• Genome and transcriptome sequence data from a metastatic gallbladder adenocarcinoma patient

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

  Dataset EGAD00001005903

• Raw data for "Spatial and temporal transcriptomics of medulloblastoma with chromothripsis identifies multiple genetic clones that resist to treatment and lead to relapse"

  FASTQ files from Illumina sequencing of 10x Visium experiments.

  Dataset EGAD00001010260

• WES of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007301

• Multi-omic analysis of the tumor microenvironment shows clinical correlations in Ph1 study of atezolizumab +/- SoC in MM

  Multiple myeloma (MM) remains incurable, and treatment of relapsed/refractory (R/R) disease is challenging. There is an unmet need for more targeted therapies in this setting; deep cellular and molecular phenotyping of the tumor and microenvironment in MM could help guide such therapies. This phase 1b study (NCT02431208) evaluated the safety and efficacy of the anti-programmed death-ligand 1 monoclonal antibody atezolizumab (Atezo) alone or in combination with the standard of care (SoC) treatments lenalidomide (Len) or pomalidomide (Pom) and/or daratumumab (Dara) in patients with R/R MM. Study endpoints included incidence of adverse events (AEs) and overall response rate (ORR). A novel unsupervised integrative multi-omic analysis was performed using RNA sequencing, mass cytometry immunophenotyping, and proteomic profiling of baseline and on-treatment bone marrow samples from patients receiving Atezo monotherapy or Atezo+Dara. A similarity network fusion (SNF) algorithm was applied to preprocessed data. Eighty-five patients were enrolled. Treatment-emergent deaths occurred in 2 patients; both deaths were considered unrelated to study treatment. ORRs ranged from 11.1% (Atezo+Len cohorts, n=18) to 83.3% (Atezo+Dara+Pom cohort, n=6). High-dimensional multi-omic profiling of the tumor microenvironment and integrative SNF analysis revealed novel correlations between cellular and molecular features of the tumor and immune microenvironment, patient selection criteria, and clinical outcome. Atezo monotherapy and SoC combinations were safe in this patient population and demonstrated some evidence of clinical efficacy. Integrative analysis of high dimensional genomics and immune data identified novel clinical correlations that may inform patient selection criteria and outcome assessment in future immunotherapy studies for myeloma.

  Study EGAS00001007286

• Single cell and plasma RNA sequencing

  Single cell and plasma RNA sequencing for RNA liquid biopsy for hepatocellular carcinoma

  Study EGAS00001005194

• Prognostic markers of DNA methylation and NGS sequencing in progressive glioblastoma from the EORTC-26101 trial

  These dataset contains NGS data from 380 samples from the EORTC-26101 clinical trial for patients with progressive glioblastoma.

  Study EGAS00001007421

• Molecular characterization of Barrett’s esophagus at single cell resolution

  Backgrounds & Aims: Patient with Barrett’s esophagus (BE) have an increased risk to develop esophageal adenocarcinoma and are under periodical endoscopic surveillance for malignant transformation. Pathologists distinguish between different BE stages to identify high-risk patients, but this process remains difficult as stage-specific markers are still missing. We established BE organoid cultures, applied single cell sequencing approaches to identify differences in gene expression and genomic alterations, and validated candidate genes for their predictive value on histological sections. Methods: We collected 43 epithelial biopsies from 21 patients, established organoids for the clonal expansion of matching healthy and diseased tissue from two patients to identify genomic alterations by whole genome sequencing (WGS). We performed single cell DNA-sequencing (scDNAseq) to analyse DNA alterations within biopsies from 8 patients and single cell RNA-sequencing (scRNAseq) to identify gene expression differences between BE stages from 19 patients. Candidate marker genes were then validated by RNA in situ hybridization experiments on histological resection specimen. Results: Most BE biopsies were chromosomal stable (CS) and their single base substitution (SBS) signatures were indistinguishable from the healthy control tissues. Dysplastic BE cells contained areas of chromosomal instabilities (CIN), which differed by the presence of the SBS17 signatures from biopsy-matching CS cells or patient-matching healthy control cells. Such CIN areas affected efficient clustering of the scRNAseq data. We identified two sets of marker genes (SLC5A5, PSCA, LIPF and ANPEP, CEACAM6, REG4), which distinguish columnar BE epithelium from non-dysplastic/dysplastic stages. CLDN2 allowed the distinction between dysplastic and more advanced stages as its expression level increased and spread in dysplastic BE glands. Conclusions: Molecular characterization of BE samples identified a correlation between the presence of CIN and COSMIC signature 17, and we report seven marker genes that help in distinguishing different BE stages.

  Study EGAS00001005221

• Integrative Profiling of T790M Negative EGFR Mutated NSCLC Reveals Pervasive Lineage Transition and Therapeutic Opportunities

  We performed whole exome and transcriptome analysis of 59 first- and second-generation EGFR TKI resistant metastatic EGFR mutated patients to characterize and compare molecular alterations mediating resistance in T790M positive and negative disease. Transcriptomic analysis revealed ubiquitous loss of adenocarcinoma lineage gene expression in T790M negative tumors, orthogonally validated using multiplex immunohistochemistry. There was enrichment of genomic features such as TP53 alterations, 3q chromosomal amplifications, whole genome doubling and non-aging mutational signatures in T790M negative tumors. Almost half of resistant tumors were further classified as Immunehot, with clinical outcomes conditional on immune cell infiltration state and T790M status. Finally, using a Bayesian statistical approach, we explored how T790M negative and positive disease might be predicted using comprehensive genomic and transcriptomic profiles of treatment-naïve patients.

  Study EGAS00001005389

• Epithelioid haemangioendothelioma (EHE) case series from the Stafford Fox Rare Cancer Program

  Nine EHE cases with comprehensive histologic and molecular profiling from the Walter and Eliza Hall Institute of Medical Research Stafford Fox Rare Cancer Program were collated via nation-wide referral to the Australian Rare Cancer Portal. Molecular analysis of RNA, DNA or both was possible in seven of nine cases. Survival was highly variable and unrelated to molecular profile. DNA sequences for two cases are deposited here.

  Study EGAS00001007474

• Clear cell sarcoma sequencing data

  This study shares DNA and RNA sequencing data from Clear cell sarcoma patients

  Study EGAS00001006072

• Study of the microenvironment of angioimmunoblastic T-cell lymphoma

  Study EGAS00001006401

• Single-cell profiling of co-cultures of GSCCs and macrophages

  Glioblastoma (GBM) remains the most malignant primary brain tumor, with a median survival rarely exceeding 2 years. Tumor heterogeneity and an immunosuppressive microenvironment are key factors contributing to the poor response rates of current therapeutic approaches. GBM-associated macrophages (GAMs) often exhibit immunosuppressive features that promote tumor progression. However, their dynamic interactions with GBM tumor cells remain poorly understood. Here, we used patient-derived GBM stem cell cultures and combined single-cell RNA sequencing of GAM-GBM co-cultures and real-time in vivo monitoring of GAM-GBM interactions in orthotopic zebrafish xenograft models to provide insight into the cellular, molecular, and spatial heterogeneity. Our analyses revealed substantial heterogeneity across GBM patients in GBM-induced GAM polarization and the ability to attract and activate GAMs – features that correlated with patient survival. Differential gene expression analysis, immunohistochemistry on original tumor samples, and knock-out experiments in zebrafish subsequently identified LGALS1 as a primary regulator of immunosuppression. Overall, our work highlights that GAM-GBM interactions can be studied in a clinically relevant way using co-cultures and avatar models, while offering new opportunities to identify promising immune-modulating targets.

  Study EGAS00001007482

• Subclonal somatic copy number alterations emerge and dominate in recurrent osteosarcoma

  Multiple large-scale genomic profiling efforts have been undertaken in osteosarcoma to define the genomic drivers of tumorigenesis, therapeutic response, and disease recurrence. The spatial and temporal intratumor heterogeneity could also play a role in promoting tumor growth and treatment resistance. Here, we conducted longitudinal whole-genome sequencing of 37 tumor samples from eight patients with osteosarcoma that relapsed or became refractory to initial therapy. We found that the chemoresistant population in recurrent osteosarcoma is subclonal at diagnosis, emerges at the time of primary resection due to selective pressure from neoadjuvant chemotherapy, and is characterized by unique oncogenic amplifications.

  Study EGAS00001007486

• Oncoprint GSCCs

  Glioblastoma (GBM) remains the most malignant primary brain tumor, with a median survival rarely exceeding 2 years. Tumor heterogeneity and an immunosuppressive microenvironment are key factors contributing to the poor response rates of current therapeutic approaches. GBM-associated macrophages (GAMs) often exhibit immunosuppressive features that promote tumor progression. However, their dynamic interactions with GBM tumor cells remain poorly understood. Here, we used patient-derived GBM stem cell cultures and combined single-cell RNA sequencing of GAM-GBM co-cultures and real-time in vivo monitoring of GAM-GBM interactions in orthotopic zebrafish xenograft models to provide insight into the cellular, molecular, and spatial heterogeneity. Our analyses revealed substantial heterogeneity across GBM patients in GBM-induced GAM polarization and the ability to attract and activate GAMs – features that correlated with patient survival. Differential gene expression analysis, immunohistochemistry on original tumor samples, and knock-out experiments in zebrafish subsequently identified LGALS1 as a primary regulator of immunosuppression. Overall, our work highlights that GAM-GBM interactions can be studied in a clinically relevant way using co-cultures and avatar models, while offering new opportunities to identify promising immune-modulating targets.

  Study EGAS00001007481

• Single-cell characterization of anti-LAG3+anti-PD1 treatment in melanoma patients

  Study EGAS00001005580

• Whole genome sequencing of tumour and normal paired samples of diffuse intrinsic pontine gliomas

  Diffuse intrinsic pontine glioma (DIPG) have a universally dismal prognosis (median 9-12 months), with neither chemotherapeutic nor targeted agents showing any substantial survival benefit in clinical trials in children with these tumours. DIPG are highly infiltrative malignant glial neoplasms of the ventral pons, which due to their location within the brain, make them unsuitable for surgical resection and consequently have a universally dismal clinical outcome. Recent high-throughput sequencing approaches have revealed a striking prevalence of K27M mutations in the genes encoding the histone variants H3.3 (H3F3A) or H3.1 (HIST1H3B) in the childhood brain tumour DIPG. This K-to-M substitution confers a trans-dominant ablation of global H3K27 trimethylation, which likely profoundly alters gene expression through de-repression of polycomb repressive complex 2 (PRC2) target genes. Despite these advances in our understanding of the distinct biology of these tumours, approaches for specific novel therapeutic interventions are not clear, and little has been reported of the secondary mutations accompanying these changes. We carried out whole genome sequencing on a series of 20 tumour normal pairs of pre-treatment biopsy samples of DIPG, for which the patients underwent a safe stereotactic procedure, and whole exome sequencing on a further six tumour normal pairs obtained at autopsy.

  Study EGAS00001000572