4736 results for "*oma"

in 52.41 milliseconds.

• Human tumor bulk RNA-seq

  We profiled 7 patient neuroblastoma-FOXR2 tumor samples by bulk RNA-seq. The raw fastqs are provided.

  Dataset EGAD00001010901

• Genome and transcriptome sequence data from a myoepithelioma patient

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

  Dataset EGAD00001010938

• 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 EGAD00001010940

• 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 EGAD00001010939

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

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

  Dataset EGAD00001010941

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

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

  Dataset EGAD00001010942

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

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

  Dataset EGAD00001010954

• 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 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 unknown - likely pancreatobiliary / intrahepatic cholangiocarcinoma in liver patient

  Genome and transcriptome sequence data from a unknown - likely pancreatobiliary / intrahepatic cholangiocarcinoma in liver patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010989

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

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

  Dataset EGAD00001011021

• Genome and transcriptome sequence data from a thymoma patient

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

  Dataset EGAD00001011039

• 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 EGAD00001011040

• Sequencing data for oesophageal / related samples - Kazachenka et al (RNA)

  Data supporting: "The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes" RNAseq for 279 samples

  Dataset EGAD00001011076

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Dataset EGAD00001011079

• Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

  In this study we performed whole genome sequencing on matched tumor-normal CD138+ bone marrow mononuclear cells from 60 patients with newly diagnosed multiple myeloma treated with daratumumab, carfilzomib, lenalidomide, and dexamethasone (NCT03290950-MANHATTAN trial). In addition, we performed 5’-single-cell RNA-sequencing (10X Genomics) coupled with V(D)J sequencing and capture of the surface protein markers (TotalSeq-C, Biolegend) of the CD138- bone marrow mononuclear cells to interrogate the composition of the immune microenvironment at baseline and after eight cycles of induction therapy in 22 patients with newly diagnosed multiple myeloma. Samples were multiplexed using hashtag oligo.

  Dataset EGAD00001011132

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

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

  Dataset EGAD00001015290

• WXS Normal Samples Javelin head and neck 100

  We performed Whole Exome (WXS) and RNASeq sequencing on samples obtained from the phase 3 randomized, double-blinded, placebo-controlled study in patients with locally advanced squamous cell carcinoma of the head and neck JAVELIN Head and Neck 100 (NCT02952586). There are 471 WXS Tumor samples and 346 RNASeq tumor samples. All tumor samples have matching normal samples.

  Dataset EGAD00001011321

• Single-cell RNA-sequencing of H3-K27M diffuse midline glioma.

  Fastq files are deposited for single-cell transcriptomes of patient H3-K27M diffuse midline gliomas, generated using the SMART-seq2 method.

  Dataset EGAD00001011339

• Machine Learning Guided Signal Enrichment for Plasma Tumor-burden Monitoring Dataset

  Includes 4 Datasets: 1. 35 Control Plasma WGS samples sequenced on NovaSeq V1.0 Chemistry at the New York Genome Center. Denoted by CTRL-2XX naming scheme. 2. Plasma WGS from 17 patients with Small Cell Lung Cancer. Samples extracted at either Pretreatment or Postoperative at weeks 2 or 3. Denoted by SCLC-XX naming scheme. 3. Plasma WGS from a synthetic mixing study of a high-burden melanoma plasma sample with plasma bag, at estimated tumor concentrations of 10e-3, 10e-4, 10e-5, and 10e-6 for 2 replicates. Denoted by SM-repX naming scheme. 4. Assorted Plasma, Tumor, and Normal WGS from patients with NSCLC expressing high-burden for use in model training. Denoted by NSCLC-2XX naming scheme.

  Dataset EGAD00001011352

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 1)

  Whole genome sequencing data of 6 high-grade serous carcinoma (HGSC) patients (11 samples) sequenced with MGISEQ-2000

  Dataset EGAD00001011353

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

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

  Dataset EGAD00001002983

• Complex structural variation patterns in pediatric solid tumors WGS

  Paired tumor-normal whole genome sequencing data from primary tumors of patients diagnosed with neuroblastoma, Ewing sarcoma, Wilms tumor, hepatoblastoma and rhabdomyosarcoma

  Dataset EGAD00001011378

• WES data for study of the microenviroment of angioimmunoblastic T-cell lymphoma

  Exome sequencing data for study of the microenviroment of angioimmunoblastic T-cell lymphoma

  Dataset EGAD00001011581

• Characterisation of the genetic landscape of cutaneous leiomyoma and leiomyosarcoma - Leiomyosarcoma WES

  Cutaneous leiomyoma (cLM) and leiomyosarcoma (cLMS) are rare benign and malignant soft tissue neoplasms showing smooth muscle differentiation, respectively, that arise from mesenchymal cells in the dermis and subcutis. Through whole exome sequencing of cLM and cLMS cases, we observed distinct differences between the somatic mutational profile of these tumour types. FH was identified as a driver gene in cLM with genetic alterations of FH occurring via somatic point mutation, somatic copy number loss, biallelic inactivation and germline point mutations. TP53 and RB1 were identified as driver genes in the cLMS cohort, with genetic alterations of TP53 occurring via somatic and germline point mutations, copy number loss and biallelic inactivation. Using RNA-sequencing, we identified recurrent gene fusions, including CRTC1/3-MAML2 in cLMS and a novel MYLK-MAP3K2 fusion. Analysis of the cell types present in the tumour microenvironment revealed a significantly increased presence of macrophages and decreased presence of myeloid dendritic cells in the cLMS cohort relative to the cLM cohort. Additionally, we identified common driver genes between cLMS and LMS from other sites. Thus, we provide the first in-depth profile of the genetic landscape of cLM and cLMS.

  Dataset EGAD00001014789

• Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset EGAD00001015373

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015379

• RNAseq in pleural mesothelioma primary cell lines

  Pleural mesothelioma (PM) requires new treatments. Drug repurposing offers a potential approach to finding effective therapies. This study aimed to explore new therapeutic options for PM using RNA sequencing. RNA sequencing was performed on 58 patient-derived PM cell lines. Drug screening of over 1300 compounds was conducted on 11 lines, with further testing of selected drugs on 48 lines. Top candidates were validated in 3D culture and mouse models.

  Dataset EGAD00001015408

• WES in pleural mesothelioma primary cell lines

  We performed exome sequencing on the largest cohort of patient-derived pleural mesothelioma (PM) cell lines (n=58) to explore their molecular heterogeneity. The analysis recapitulated key features of PM tumors and uncovered novel mutations specific to this cohort. These findings provide insight into the genetic landscape of PM, supporting the identification of potential therapeutic targets and advancing the understanding of its molecular diversity.

  Dataset EGAD00001015409

• Vulval Squamous Cell Carcinoma Spatial Transcriptomics

  This dataset contains raw paired-end fastq files from 10x Genomics Visium spatial transcriptomics platform of four early-stage VSCC cases (PMID: 39787746)

  Dataset EGAD00001015461

• The earliest stages of neoplastic transformation in Familial Adenomatous Polyposis

  The succession of somatic genetic events associated with the conversion of a normal colorectal epithelial cell into a colorectal carcinoma constitutes a paradigmatic model of cancer development. Familial Adenomatous Polyposis (FAP) is caused by constitutional inactivating mutations in APC, the central gatekeeper gene of colorectal cancer, and is associated with a substantially increased lifetime-risk of colorectal cancer. To investigate the earliest stages of neoplastic change due to APC inactivation, we microdissected and individually whole genome sequenced 279 histologically normal and abnormal colorectal crypts from 15 individuals with FAP. Histologically normal crypts generally exhibited similar mutation burdens and mutational signatures to normal crypts from wild-type individuals of the same age, with 1/110 carrying a somatic inactivating APC mutation. By contrast, 9/18 aberrant crypt foci carried somatic APC mutations and exhibited modestly increased burdens of some mutational signatures found in normal crypts. 12/13 diminutive adenomatous polyps (less than 5mm diameter) showed somatic APC mutations and carried substantially increased mutation loads of most mutational signatures present in normal crypts. Phylogenetic trees of crypts from aberrant crypt foci and adenomatous polyps revealed that some had acquired their initiating somatic APC mutations decades previously during the first few years of life. The results catalogue the changes in somatic mutation rates, mutational processes and “driver” mutations in cancer genes during the earliest stages of colorectal neoplastic transformation initiated by APC inactivation and highlight the long periods of clonal evolution required for a cancer to develop.

  Dataset EGAD00001015471

• Bulk RNA Seq in FAP Adenoma

  Bulk RNASeq data of Duodenal organoids, sorted ILC3 and duodenal tissue

  Dataset EGAD00001015488

• The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

  Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

  Dataset EGAD00001015503

• GBM-Space: Joint Transcriptome and Chromatin Accessibility Profiling of Glioblastoma (10x Genomics - Multiome)

  GBM-Space: Joint Transcriptome and Chromatin Accessibility Profiling of Glioblastoma (10x Genomics - Multiome)

  Dataset EGAD00001015526

• GBM-Space: Spatial Transcriptomic Profiling of Glioblastoma (10x Genomics - Visium)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. The datasets in this study include sequencing data from Visium spatial transcriptomic (10x Genomics) profiling of these tumours.

  Dataset EGAD00001015527

• Segmental Cherry Angioma case

  Cherry angiomas are common benign blood vessel growths on the skin. In this study we characterise mutational profile of a cherry angioma and adjacent skin biopsied from a patient with multiple lesions with segmental presentation.

  Dataset EGAD00001015641