3735 results for "*oma"

in 59.69 milliseconds.

• Genome and transcriptome sequence data from a metastatic spindle cell sarcoma patient

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

  Dataset EGAD00001003644

• Genome and transcriptome sequence data from an anaplastic ependymoma patient

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

  Dataset EGAD00001003645

• Genome and transcriptome sequence data from an ependymoma patient

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

  Dataset EGAD00001003659

• Genome and transcriptome sequence data from an advanced adenocarcinoma of lung patient

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

  Dataset EGAD00001003661

• Genome and transcriptome sequence data from a left cavernous sinus invasive skull meningioma patient

  Genome and transcriptome sequence data from a left cavernous sinus invasive skull meningioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003662

• Genome and transcriptome sequence data from a metastatic rhabdomyosarcoma patient

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

  Dataset EGAD00001003668

• Genome and transcriptome sequence data from a metastatic mucinous adenocarcinoma of the rectum patient

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

  Dataset EGAD00001003669

• 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 EGAD00001003675

• 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 EGAD00001003695

• Genome and transcriptome sequence data from a metastatic meningioma patient

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

  Dataset EGAD00001003697

• Genome and transcriptome sequence data from a high grade serous carcinoma of the fallopian tube/ovary/peritoneum patient

  Genome and transcriptome sequence data from a high grade serous carcinoma of the fallopian tube/ovary/peritoneum patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003702

• Genome and transcriptome sequence data from a melanoma of the right buccal mucosa patient

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

  Dataset EGAD00001003716

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

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

  Dataset EGAD00001003723

• 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 EGAD00001003730

• Genome and transcriptome sequence data from a metastatic uterine leiomyosarcoma patient

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

  Dataset EGAD00001003733

• Genome and transcriptome sequence data from a spindle cell carcinoma of the left parotid patient

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

  Dataset EGAD00001003734

• 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 EGAD00001003735

• 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 EGAD00001003714

• Genome and transcriptome sequence data from a pleomorphic xanthoastrocytoma patient

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

  Dataset EGAD00001003744

• Genome and transcriptome sequence data from a non-small cell adenocarcinoma patient

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

  Dataset EGAD00001004600

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

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

  Dataset EGAD00001004603

• Genome and transcriptome sequence data from a double-hit lymphoma patient

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

  Dataset EGAD00001004624

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectosigmoid patient

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

  Dataset EGAD00001004627

• 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 EGAD00001004629

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

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

  Dataset EGAD00001004608

• Genome and transcriptome sequence data from a follicular lymphoma patient

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

  Dataset EGAD00001004611

• 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 EGAD00001004612

• Genome and transcriptome sequence data from a metastatic uveal melanoma patient

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

  Dataset EGAD00001004667

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the esophagus patient

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

  Dataset EGAD00001004668

• Genome and transcriptome sequence data from a metastatic spindle cell sarcoma patient

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

  Dataset EGAD00001004670

• Genome and transcriptome sequence data from a peripheral T-cell lymphoma patient

  Genome and transcriptome sequence data from a peripheral T-cell lymphoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004696

• Genome and transcriptome sequence data from a adenocarcinoma of the liver patient

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

  Dataset EGAD00001004706

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

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

  Dataset EGAD00001004708

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

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

  Dataset EGAD00001004677

• 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

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

  From all paediatric brain tumours, medulloblastomas with chromothripsis, a form of genome instability leading to massive genome rearrangements, are particularly aggressive. To dissect the complex biology underlying the aggressiveness of chromothriptic medulloblastomas, we applied spatial transcriptomics to i) chromothriptic and non-chromothriptic medulloblastomas from the same molecular subgroup (n=13) and ii) patient-derived xenografts from chromothriptic medulloblastoma, from the minimal residual disease stage to regrown tumours (n=11). Chromothriptic medulloblastomas showed higher spatial intra-tumour heterogeneity, proliferation and stemness, but lower immune infiltration and differentiation, as compared with non-chromothriptic medulloblastomas. Spatial mapping of genetic clones identified phenotypic features such as degree of differentiation, proliferation and immune infiltration enriched in specific clones. Cells from multiple genetic clones resisted treatment and gave rise to relapse in patient-derived xenografts of chromothriptic medulloblastoma. We identified a potential role of tumour microtubes in treatment resistance in chromothriptic medulloblastoma.

  Study EGAS00001007128

• 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

• Single-cell multi-omic profiling of glioblastoma-associated myeloid cells

  Study EGAS00001004871

• 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

• ENCORAFENIB COMBINED WITH BINIMETINIB FOR BRAFV600E-MUTATED RELAPSED/REFRACTORY MULTIPLE MYELOMA: THE PHASE II GMMG-BIRMA TRIAL (Hipo_K08K)

  Activating BRAF mutations are rare events in multiple myeloma but have been shown to be promising therapeutic targets in small case studies. This multicenter phase II trial assessed the efficacy and safety of the BRAF/MEK inhibitors, encorafenib and binimetinib, in patients with relapsed/refractory multiple myeloma (RRMM) carrying an activating BRAFV600E mutation. Twelve RRMM patients with a median of five prior lines of therapy were enrolled. The study met its primary endpoint with 10 patients achieving at least a partial response according to IMWG criteria (overall response rate 83.3%). Responses occurred rapidly within the first cycle and deepened over time. The median progression-free survival (PFS) was 5.6 months and overall survival was 55% at 24 months. Genomic profiling revealed RAS mutations and structural variants involving the BRAF locus to be drivers of resistance to BRAF/MEK inhibition in RRMM. This trial demonstrates the value of translationally driven clinical trials in selected patient populations.

  Study EGAS00001005973

• 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

• Comparison of EGF and PDGF driven glioblastomas.

  Glioblastoma multiforme (GBM) is the most common and aggressive type of primary brain tumor. Epidermal growth-factor (EGF) and platelet-derived growth-factor (PDGF) receptors are frequently amplified and/or possess gain-of-function mutations in these tumors. Despite years of research into tyrosine-kinase inhibitors, clinical trials have shown disappointing efficacy. One of the underlying reasons is intra-tumor heterogeneity. To assess the effect of intra-tumor heterogeneity on gene expression, we derived a general approach to map single-cell expression profiles to sequentially-acquired mutations identified from exome sequencing. Using 288 single cells, we constructed high-resolution phylogenies of EGF-driven and PDGF-driven GBMs, modeling transcriptional kinetics during tumor evolution. A deletion in a PDGF-receptor domain involved in dimerization correlated to an up-regulation of the PI3K/AKT pathway in a proneural GBM, and ectopic expression of this mutant PDGFRA in vitro enhanced proliferation and invasiveness. Descending the phylogenetic tree of the PDGFR-driven tumor corresponded to a progressive induction of an oligodendrocyte progenitor-like cell type that expresses growth and angiogenic factors. In contrast, phylogenetic analysis of an EGFR-amplified tumor showed a gradual up-regulation of pro-invasive genes.

  Study EGAS00001001900

• 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

• Unraveling the genetics of transformed splenic marginal zone lymphoma

  Study EGAS00001006389

• Spatial and temporal genomic evolution in glioblastoma

  Tumor heterogeneity is a challenging barrier to successful targeted therapy in glioblastoma. Identifying the mechanisms that drive cancer cells as they genetically evolve and adapt in response to treatment is a vital goal of modern cancer research. Analysis of sequencing data provides a method for uncovering the mechanisms sustaining tumor heterogeneity and driving evolution. Here, we analyzed genomic profiles of GBM biopsies taken from pre- and post-treatment GBMs (with matched germline controls), to understand 1) the intratumoral clonal compositions of primary GBM and 2) how GBM responds to therapeutic intervention. Our results provide a molecular portrait of GBM recurrence.

  Study EGAS00001001033

• Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA-sequencing the pros and cons

  RNA sequencing data of a collection of 6 pediatric ependymoma cases

  Study EGAS00001006535

• DNA methylation and somatic mutations converge on cell cycle and define similar evolutionary histories in brain tumors

  The evolutionary history of tumor cell populations can be reconstructed from patterns of genetic alterations. In contrast to the stability of genetic events, epigenetic states are reversible and sensitive to the microenvironment, prompting the question whether epigenetics can be similarly used to discover tumor phylogeny. We examined the spatial and temporal dynamics of DNA methylation in a cohort of low-grade gliomas and their patient-matched recurrences. Genes upregulated through promoter hypomethylation during malignant progression to high-grade glioblastoma were enriched in cell cycle function, evolving in parallel with genetic alterations that deregulate the G1/S cell cycle checkpoint. Moreover, phyloepigenetic relationships robustly recapitulated phylogenetic patterns inferred from somatic mutations. These findings highlight widespread co-dependency of genetic and epigenetic events throughout brain tumor evolution.

  Study EGAS00001001255

• Single cell RNA sequencing of bone marrow mononuclear cells

  Bone marrow aspirates were obtained from patients with relapsed/refractory large B cell lymphoma (rrLBCL), mononuclear cells isolated by ficoll density-gradient centrifugation, and loaded onto a 10X Chromium for single cell RNA-sequencing using 5’ chemistry without prior cryopreservation. Healthy donor bone marrow mononuclear cells were obtained from healthy allogeneic stem cell transplant donors and analyzed following viable cryopreservation.

  Study EGAS00001006836

• Integrated genomic characterization of IDH1 mutant Glioma malignant progression

  Gliomas represent approximately 30% of all central nervous system tumors, and 80% of malignant brain tumors. To understand the molecular mechanisms underlying the malignant progression of low-grade Isocitrate Dehydrogenase 1 (IDH1) mutant gliomas, we studied paired tumor samples from 41 patients, comparing higher-grade, progressed samples to their lower-grade counterparts. Integrated genomic analyses, including whole-exome sequencing, copy number, gene expression and DNA methylation profiling, demonstrated non-linear clonal expansion of the original tumors and identified oncogenic pathways driving progression. These include activation of the MYC and RTK-RAS-PI3K pathways, up-regulation of the FOXM1- and E2F2-mediated cell cycle transition genes, as well as epigenetic silencing of developmental transcriptional factors bound by Polycomb repressive complex 2 in human embryonic stem cells. Our results not only provide mechanistic insight into the genetic and epigenetic mechanisms driving glioma progression but also identify inhibition of the bromodomain and extra-terminal (BET) family as a potential therapeutic approach.

  Study EGAS00001001588

• Molecular evolution of classic Hodgkin lymphoma revealed through whole genome sequencing of Hodgkin and Reed Sternberg cells

  Here we leveraged whole genome structural variant copy number analysis to report the first whole genome sequencing landscape of HRS cells and reconstruct the chronology and likely etiology of pathogenic events prior to the clinical diagnosis of cHL.

  Study EGAS00001006884

• Genomic profiling of localized (lFL) and systemic follicular lymphoma (sFL) reveals novel insights into FL pathogenesis

  At diagnosis, the majority of FL presents with symptomatic disease in advanced/systemic stages of FL (sFL). In contrast only around 10 to 15% of cFL are diagnosed in localized stages (lFL). The biological knowledge is mainly based on data derived from global sFL analysis and only small cohorts of lFL were characterized intensively so far. It is well-known that the hallmark BCL2 translocation is less frequently observed in lFL. Furthermore, lFL differs from sFL concerning their gene expression and their N-glycosylation profiles. In consequence, comprehensive global analysis with CNA profiling and whole exome sequencing was performed in a large cohort of lFL. Additionally, the mutational profile as well as the CNA landscape of lFL and sFL, as well as for BCL2 translocation-positive and -negative was compared.

  Study EGAS00001006927

• VRK3 depletion in Pontine Diffuse Midline Glioma (DMG)-K27 altered cells

  Study EGAS00001007047

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_squamous_cell_carcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002725

• Study of complex rearrangements and mutational signatures in neuroblastoma heterogeneous risk groups.

  Neuroblastoma is a pediatric solid tumor characterized by strong clinical heterogeneity. Although certain complex genomic alterations, such as extrachromosomal DNA amplifications (ecDNA), are associated with adverse outcome and have been recurrently detected in neuroblastomas, the mutational processes involved in their generation remain largely unclear. By examining the topography of complex rearrangements along with mutational signatures derived from all variant classes, we identify previously unrecognized co-occurring mutational footprints, which we termed mutational scenarios. We demonstrate that clinical neuroblastoma heterogeneity is linked to differences in the processes driving these mutational scenarios. Whereas high-risk MYCN-amplified neuroblastoma genomes were characterized by signs of replication slippage and stress, homologous recombination-associated signatures defined high-risk non-MYCN-amplified patients. Non-high-risk neuroblastomas, on the other hand, were marked by footprints of chromosome missegregation and TOP1 mutational activity. This analysis provides a systematic perspective on the repertoire of mutational patterns that contribute to clinical neuroblastoma heterogeneity.

  Study EGAS00001006983

• Neuroblastoma heterogeneity

  Neuroblastoma is a pediatric solid tumor characterized by strong clinical heterogeneity. Although certain complex genomic alterations, such as extrachromosomal DNA amplifications (ecDNA), are associated with adverse outcomes and have been recurrently detected in neuroblastomas, the mutational processes involved in their generation remain largely unclear. By examining the topography of complex rearrangements along with mutational signatures derived from all variant classes, we identify previously unrecognized co-occurring mutational footprints, which we termed mutational scenarios. We demonstrate that clinical neuroblastoma heterogeneity is linked to differences in the processes driving these mutational scenarios. Whereas high-risk MYCN-amplified neuroblastoma genomes were characterized by signs of replication slippage and stress, homologous recombination-associated signatures defined high-risk non-MYCN-amplified patients. Non-high-risk neuroblastomas, on the other hand, were marked by footprints of chromosome missegregation and TOP1 mutational activity. This analysis provides a systematic perspective on the repertoire of mutational patterns that contribute to clinical neuroblastoma heterogeneity.

  Study EGAS00001007016