4909 results for "*oma"

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• RNAseq of MCL cell lines

  This study profiles the transcriptomic response of the Mino-VEN-R and Jeko-BTK-R mantle cell lymphoma (MCL) cell lines to pirtobrutinib (PBN) treatment using bulk RNA sequencing. Mino-VEN-R models drug-tolerant persister (DTP) cells that arise during exposure to non-covalent BTK inhibitors. Building on our recent findings that DTP cells undergo metabolic and phenotypic state transitions governed by TCA cycle reprogramming, this dataset aims to capture gene expression changes associated with treatment-induced plasticity. The results contribute to a broader multi-omic framework exploring mechanisms of resistance and therapeutic vulnerability in MCL.

  Study EGAS50000001087

• RNaseq of mantle cell lymphoma patient samples

  This study presents bulk RNA sequencing data from 78 clinical mantle cell lymphoma (MCL) samples. Following rigorous quality control and batch effect correction to account for sample type and redundancy, 62 samples from 59 patients were included in the final analysis. The transcriptomic profiles capture the molecular diversity across both solid and liquid tumor contexts and support investigations into the phenotypic plasticity and metabolic states of drug-tolerant persister (DTP) cells.

  Study EGAS50000001086

• Transcriptomic analysis of B-cell acute lymphoblastic leukaemia (B-ALL) patients treated on the ALL09 clinical trial

  This study provides comprehensive transcriptomic analysis of adolescent and young adult (AYA) patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL09 clinical trial (ACTRN12618001734257). The ALL09 clinical trial is a Phase II single arm study to assess whether substitution of blinatumomab for conventional multi-agent chemotherapy in phase 2 induction leads to improved minimal residual disease negativity rates when compared to the historical AYA ALL trial cohort. Patients treated on this trial were aged 15-40 years, demonstrated morphological diagnosis of CD19 positive B-lineage acute lymphoblastic leukaemia (B-ALL), and were negative for Philadelphia chromosome-positive disease. Transcriptomic sequencing was performed as a correlative study to determine assess patients’ genomic subtypes and enable comparison of clinical outcome in blinatumomab treated patients.

  Study EGAS50000001109

• Survival and safety of laser interstitial thermal therapy and adjuvant pembrolizumab in recurrent high-grade astrocytoma: a Phase 1/randomized Phase 2b trial

  This dataset is the immune profiling of the trial patients. Cryopreserved PBMCs obtained from the patients at different time points were processed to single-cell transcriptomic or TCR libraries using 10x next GEM single Cell 5' v2 kit. We also performed whole exome sequencing (WES) of the tumor to identify the mutation burden. The WES data was generated by sequencing company Novogene. There are total of 69 of single cell libraires, 69 of single cell TCR libraries, and 13 of tumor WES data being generated from 18 trial patients recruited at University of Florida.

  Dataset EGAD50000001639

• WHOLE GENOME SEQUENCING OF CLEAR CELL RENAL CELL CARCINOMA IN VHL PATIENT

  This submission contains Whole Genome Sequencing data of six ccRCCs, four cysts and one blood DNA sample of a VHL patient.

  Study EGAS50000000295

• Phenotypic characterization and prognostic impact of CD103+ tissue-resident memory T cells in diffuse large B cell lymphoma

  Tissue-resident memory T (TRM) cells are a population of memory T cells that stably occupy tissues and play a key role in immunosurveillance, having been linked to favorable survival outcomes in various solid tumors. While TRM cells have been identified in lymph nodes, their phenotype and prognostic significance in B-cell non-Hodgkin lymphoma (B-NHL), including diffuse large B-cell lymphoma (DLBCL), remains poorly characterized. The frequency of CD103 expressing T cells in patient samples with DLCBL was quantified by immunofluorescence (IF) staining of tissue biopsies (n=306) and flow cytometry (n=252) of cell disaggregates, and linked with clinical outcome. The phenotype of TRM cells was characterized by spectral flow cytometry (n=10 DLBCL and 2 reactive lymph node (rLN) samples) and single-cell RNA sequencing (scRNAseq) (n=12 aggressive B cell lymphomas and 4 rLN samples). An additional 51 samples from an external dataset were included to verify the single cell transcriptome findings. The flow cytometry and scRNAseq findings in DLBCL were extrapolated to additional B-NHL entities. Through analysis of these datasets we were able to characterize CD103+ TRM-like cells in DLBCL and other B-NHL entities and identified them to represent a prognostically favorable population with an activated/cytotoxic T cell phenotype.

  Study EGAS50000000943

• A renal cell carcinoma tumorgraft platform to advance precision medicine

  Study EGAS00001005516

• Lymphoma_primary_patient_drug_perturbed_RNASeq_samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET-762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dac EGAC50000000578

• RNAseq of Thymic epithelial tumors and paired normals

  Between November 2010 and May 2014, 20 cases—17 thymomas and 3 thymic carcinomas (including 2 squamous and 1 neuroendocrine carcinoma)—were newly sequenced from surgically removed TETs at Seoul National University Hospital, with written informed consent. Tumors and normal tissues were carefully separated and immediately preserved in liquid nitrogen after resection. DNA and RNA were extracted from the tumors, adjacent normal tissues, and/or blood samples. Libraries for RNA-seq were prepared using the TruSeq Stranded mRNA LT Sample Prep Kit following standard Illumina protocols.

  Dataset EGAD50000001158

• WES of thymic epithelial tumors and paired normals

  Between November 2010 and May 2014, 20 cases—17 thymomas and 3 thymic carcinomas (including 2 squamous and 1 neuroendocrine carcinoma)—were newly sequenced from surgically removed TETs at Seoul National University Hospital, with written informed consent. Tumors and normal tissues were carefully separated and immediately preserved in liquid nitrogen after resection. DNA and RNA were extracted from the tumors, adjacent normal tissues, and/or blood samples. Libraries for WES were prepared using the SureSelect XT (Human All Exon + UTR v5) Library Prep Kit following standard Illumina protocols.

  Dataset EGAD50000001159

• A single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  Nodal B-cell non-Hodgkin lymphomas (B-NHL) are a clinically diverse set of cancers thought to originate from distinct stages of B-cell maturation. To characterize intratumor heterogeneity across B-NHL entities, we performed CITE-Seq (cellular indexing of transcriptomes and epitopes) on 51 lymph node samples including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL, n = 11) tumors, in addition to non-malignant reactive lymph nodes (rLN, n = 8). We also performed 5 prime scRNA-seq with immune receptor profiling for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL, and 2 MZL).

  Study EGAS50000000342

• Spatial gene expression analysis of the tumor cells and their microenvironments at the pioneering-round of the metastasis.

  To analysis the metastatic process of invasive ductal carcinoma of the breast, we performed in situ gene expression analyses of the primary tumor, metastatic lympho node, and tumor-draining lympho node. To characterize the tumor, we also conducted multiomics analyses of normal breast tissue derived from the same patient.

  Study JGAS000804

• A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies

  Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with our atlas of pineal gland development to retrace cellular origins. Integrative computational analyses maps pineoblastoma origins to transient cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncovers a tumor-associated photoreceptor signature common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.

  Study EGAS50000001457

• Variant calling for IMMU-SCCHN1 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with confirmed locally recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN) who receive first-line treatment with immune checkpoint inhibitors (ICI) or ICI combined with chemotherapy. This dataset contains whole exome sequencing data from tumor and matching germline samples processed with the Vegan pipeline. It includes SNP and CNV calling.

  Dataset EGAD50000002205

• Transcriptomics for IMMU-SCCHN1 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with confirmed locally recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN) who receive first-line treatment with immune checkpoint inhibitors (ICI) or ICI combined with chemotherapy. This dataset contains transcriptomics data processed with the STAR pipeline. Two sequencing kits were employed: Roche KAPA for high-quality RNA samples and Takara SMART-Seq Stranded for samples with limited RNA quantities.

  Dataset EGAD50000002206

• Common origin and somatic mutation patterns of composite lymphomas and leukemias

  When two lymphomas occur concurrently or sequentially in a patient, it is a major question whether they derive from the same lymphocyte or hematopoietic precursor cell or developed independently. We studied four composite classic Hodgkin lymphomas (HL) and other mature B-cell lymphomas, and two composite mature B- and T-cell neoplasias by whole exome sequencing (WES) and analyzed shared somatic mutations in the lymphomas of these clonally related composite lymphomas, indicating their derivation from a common, pre-malignant precursor. Most identified mutations were restricted to one or the other of these lymphomas, likely explaining how distinct lymphomas developed from a common ancestral B cell. In the two B-cell/T-cell lymphoma cases, and a composite clonally unrelated HL/chronic lymphocytic leukemia, the lymphoma partners did not share any somatic mutations. In three cases, we identified potentially oncogenic variants also in cells serving as constitutional controls.

  Study EGAS50000001017

• Common origin and somatic mutation patterns of composite lymphomas and leukemias

  The dataset contains six composite lymphomas and leukemias cases (four composite B-cell lymphomas (case 1-4), and two combinations of B-cell and T-cell lymphoma (case 5+6)). Two tumor and one non-tumor (NTC) sample were sequenced from each case after library prep with NEBNext Ultra DNA Library Prep Kit, Exome capturing was done with NimbleGen SeqCap EZ Choice kit, and sequenced on a Illumina HiSeq 2000 HO and given as fastq files. WGA (Qiagen REPLI-g kit) was used for case 2 and 3. Case 1-4 were microdisected, case 5+6 were flow-sorted.

  Dataset EGAD50000001486

• DAC for lymphoma IFZ Essen

  This DAC is set in place to handle acess to data on lymphomas and immune cells submitted by scientists from the Institute of Cell Biology (Cancer Research) at the University of Duisburg-Essen in Essen, Germany.

  Dac EGAC50000000521

• Bulk RNA sequencing of 36 multi-region IPMN–PDAC tumours comprising 160 sequencing runs

  This dataset contains bulk RNA sequencing data generated from 36 multi-region tumour samples obtained from patients with intraductal papillary mucinous neoplasms (IPMN) and associated pancreatic ductal adenocarcinoma (PDAC). A total of 160 sequencing runs are included. Libraries were prepared from poly(A)-selected RNA and sequenced on an Illumina platform. The data are provided as raw sequencing files for downstream transcriptomic analyses.

  Dataset EGAD50000002215

• Single cell RNA and ATAC sequencing data from GBM patients

  Glioblastoma cells infiltrate and incorporate into the normal brain parenchyma. We conduct unbiased multimodal single-cell and spatial sequencing to capture GBM cells and the surrounding tumor microenvironment using a regional sampling strategy. For each patient, we profile the peritumoral region, tumor edge, and tumor core, providing a comprehensive characterization of the transcriptional and epigenetic landscape of GBM spatial heterogeneity, with a specific focus on infiltrative cells.

  Study EGAS50000000547

• Effects of GATA4-inhibiting compound 3i-2012 on HB-243 hepatoblastoma cells

  In order to study the effects of GATA4 inhibition, HB-243 hepatoblastoma cells were treated with GATA4-inhibiting compound 3i-2012 for 24 hours. Total RNA was extracted and sequenced.

  Study EGAS50000000999

• RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

  RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting.

  Study EGAS50000001595

• Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment

  Samples was collected at the Mayo Clinic. MM tumor samples were enriched using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). DNA from CD138+ MM cell (tumor) or peripheral blood samples (germline control) at Mayo Clinic (Rochester or Arizona) underwent WGS. For samples collected at Mayo Clinic Rochester, library preparation was completed using the NEB Ultra II (New England Biolabs, Ipswich, MA) and the Nextera Flex systems (Illumina, San Diego, CA) and sequenced at the Mayo Clinic Genome Analysis Core with an approximate depth of 30X for tumor samples and 60X for the germline control. For samples collected at Mayo Clinic Arizona, Novogene was used for WGS following random shearing of the DNA, end-repairs, A-tailed and ligated with Illumina adapters. Sequencing was performed on the Illumina Novaseq 6000 sequencer Reference Genome: GRCh38.

  Dataset EGAD50000002132

• RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

  RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting. 117 total samples were sequenced with paired reads on 10 lanes from different flowcells. They were loaded as 2400 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002278

• Whole exome sequencing data of matched pairs of primary tumour and normal frozen tissue of seven osteosarcoma patients

  This dataset contains whole exome sequencing data of matched pairs of primary tumour and normal frozen tissue of seven osteosarcoma patients. Whole exome sequencing with a minimum coverage of 100x was performed using the Illumina Novaseq6000 platform and the Agilent SureSelect Human All Exon V7 kit.

  Dataset EGAD50000002264