4821 results for "*oma"

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• NHLBI TOPMed: African American Sarcoidosis Genetics Resource

  This study aims to comprehensively interrogate the genomes of African American sarcoidosis families. Sarcoidosis is characterized by a hyperimmune response resulting in granuloma formation in multiple organs. It affects African Americans (AAs) more frequently and more severely than whites. While previous linkage, admixture, candidate gene and genome-wide association (GWA) studies show statistically compelling effects, causal variants are still unknown and much of sarcoidosis heritability is yet to be explained. This "missing" heritability likely includes effects of both common (minor allele frequency (MAF)>5%) and rare variants (MAF

  Study phs001207

• Somatic L1 retrotransposition mapping in high-grade serous ovarian carcinoma using LDI-PCR/Nanopore-sequencing (part 2)

  Somatic L1 retrotransposition was mapped in high-grade serous carcinoma (HGSC) tumors using LDI-PCR/Nanopore-seq method. This method identifies somatic L1 insertions originating from two active L1 loci at chr22q12.1 and chrXp22.2. Multiple tumors from the same patient were utilised to understand L1-mediated intrapatient heterogeneity. Long-read data generated by LDI-Nanopore sequencing was aligned to the reference genome (GRCh38). This dataset contains the remaining file of this study.

  Dataset EGAD50000001757

• Convergent evolution towards CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

  Monoclonal antibodies directed against CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients will still experience disease relapse. Despite their ubiquity, little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape, whereby tumor cells alter expression of cell surface immunotherapy targets, has been proposed as a potential avenue, and has been seen with other immunotherapies in MM. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 72 patients at relapse with naivety to anti-CD38 antibodies, and 52 patients collected at relapse following anti-CD38 antibodies, we report biallelic inactivation of CD38 as a recurrent mechanism of resistance in 6% of patients, often via convergent evolution where distinct subclones are advantaged towards the same selective endpoint within the same patient. Monoallelic loss of the CD38 locus was seen in another 14% post-CD38-directed therapy. Three of the cases with biallelic events on CD38 presented with missense mutations and retained CD38 expression. Functional work demonstrated that two of these mutations decreased binding affinity and antibody-dependent cellular cytotoxicity of commercial antibodies Daratumumab and Isatuximab. However, the third mutation (R140G) provided relative resistance only towards one commercial product. Given that patients are often rechallenged with CD38 antibodies following disease progression, these data support the need for next generation sequencing to guide treatment selection.

  Study EGAS50000000709

• Single cell atlas of relapsed/refractory large B-cell lymphoma

  Relapsed/refractory large B-cell lymphomas (rrLBCL) are clinically and biologically diverse lymphoid malignancies with intricate microenvironments that play a key role in disease development. In this study, we used single-nucleus multiome profiling along with bulk DNA and RNA sequencing on 120 tumor and control biopsies to comprehensively characterize the various cell types and subsets found in rrLBCL tumors.

  Study EGAS50000001293

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  This study introduces MorphoITH, a framework for deconvolving intra-tumor heterogeneity (ITH) in clear cell renal cell carcinoma (ccRCC) based on tissue morphology from histopathological slides. The study tested MorphoITH's ability to capture different aspects of morphology and to reflect genetic ITH. The data deposited here is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. This dataset consists of whole exome sequencing of tumor from multiple sites and adjacent normal samples which were collected from two patients treated in affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital.

  Study EGAS50000001064

• Extrachromosomal DNA-driven oncogene dosage heterogeneity determines therapy response in neuroblastoma

  Characterization of ecDNA copy number-dependent plasticity of neuroblastoma patient-derived xenograft models. Data corresponds to single-cell G&T sequencing from an untreated neuroblastoma PDX and single-cell multiome ATAC + gene expression sequencing of a SHH medulloblastoma tumor.

  Study EGAS50000001040

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - RNA validation cohort

  This reposiroty contains bulk RNA data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere.

  Study EGAS50000001212

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - WGS validation cohort

  This reposiroty contains bulk WGS data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere.

  Study EGAS50000001211

• DAC for "Drug Development against Tumor Microtube Networks in Glioblastoma"

  This is the DAC for the study "Drug Development against Tumor Microtube Networks in Glioblastoma" of Dirk C. Hoffmann, Dirk.Hoffmann@dkfz.de and Frank Winkler, Frank.Winkler@med.uni-heidelberg.de

  Dac EGAC50000000326

• Drug Development against Tumor Microtube Networks in Glioblastoma

  Glioblastomas are aggressive brain tumors that resist current therapies by hijacking neurodevelopmental programs to invade the brain and form resilient multicellular networks. Tumor Microtubes (TMs), neurite-like processes extended by cancer cells, drive this pathobiology, but TM-inhibiting drugs are lacking. Here we developed a comprehensive, combined in vitro and in vivo drug screening approach, including novel AI-based analysis tools of TM parameters. Two Protein Kinase C (PKC) activators, TPPB and PMA, exhibited robust inhibition of TM formation in cell-based assays. Since unconnected glioblastoma cells exhibit increased sensitivity to cytotoxic therapy in vivo, brain tumor-bearing mice received TPPB, the most consistent TM-inhibiting compound, in combination with radiotherapy. Long-term intravital 2-photon microscopy confirmed anti-TM and anti-tumor effects of the co-treatment. Mechanistically, TPPB treatment inhibited several key molecular and functional components of TM-related glioblastoma cell network communication and decreased the expression of TTYH1, a key driver of invasive TMs. By establishing a novel screening pipeline for anti-TM drug development, our study identifies a druggable TM master regulator pathway and a small molecule with robust anti-TM effects. It provides a proof-of-principle that disrupting TMs and disconnecting tumor networks is a pharmacologically feasible strategy to make therapies against glioblastoma more effective.

  Study EGAS50000000477

• Dataset for RNA sequencing glioblastoma data

  This dataset contains RNA sequencing data of 36 glioblastoma samples. Sequencing was performed on Illumina NovaSeq 6000 using TruSeq Stranded RNA Kit. The sequencing was always paired.

  Dataset EGAD50000000688

• Multimodal antigenic escape to GPRC5D-targeted T-cell engagers in multiple myeloma

  We analyzed the genome of plasma cells collected from bone marrow samples or plasmocytoma from patients prior to (when available) and progression on anti-GPRC5D T cell engagers.

  Study EGAS50000001148

• WGS dataset for Multimodal antigenic escape to GPRC5D-targeted T-cell engagers in multiple myeloma

  We analyzed the genome of plasma cells collected from bone marrow samples or plasmocytoma from patients prior to (when available) and progression on anti-GPRC5D T cell engagers. Dataset includes tumor and matched normal WGS data aligned to GRCh38.p14 in bam format, as well as tumor small variant and CNV calls.

  Dataset EGAD50000001643

• Longitudinal analysis of bone marrow heterogeneity reveals the co-evolution of malignant B cells and their T-cell niche supporting follicular lymphoma persistence

  Follicular Lymphoma (FL) is an indolent lymphoid malignancy characterized by cycles of remission and relapse, reflecting the inability of current therapies to fully eradicate tumor cells. Our hypothesis is that rare cancer precursor/persister cells (CPCs) evade treatment by homing to a protective tumor microenvironment, particularly within the bone marrow (BM), and/or by adopting specific cellular states, and form a rare reservoir of residual cells seeding lymphoma recurrence. To adress this, we collected paired BM samples at diagnosis and one year post-therapy from a clinical trial (FLIRT trial, NCT02303119) and applied multi-modal single-cell analysis to dissect the transcriptomics determinants of rare drug-tolerant persister cells and their surrounding T-cell niche.

  Study EGAS50000001295

• Single cell multi modal dataset of bone marrow samples from follicular lymphoma patients at diagnosis et one year post treatment

  This dataset contains transcriptome, BCR, TCR and HTO data at the single cell level from follicular lymphoma bone marrow samples at diagnosis (n=19) and one year post rituximab therapy (n=16).

  Dataset EGAD50000001843

• Human glioblastoma single cell DAC (Linnarsson)

  DAC for human glioblastoma single cell sequencing samples

  Dac EGAC50000000575

• an integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

  Study EGAS00001000509

• Disease recurrence after pathologic response (Recurrence DNAseq)

  In this study we aim to gain insight into the mechanisms of immune evasion after initial pathologic response to neoadjuvant immune checkpoint inhibition in macroscopic stage III melanoma by pooling data of the neoadjuvant OpACIN, OpACIN-neo and PRADO trials(EGAD00001012116, EGAS00001004832, EGAD00001006730, EGAS50000000268). Therefore we analyzed in-depth paired baseline(n=10) and recurrent tumor samples of the lymph nodes(n=10) and brain metastasis (n=2) through Whole Exome Sequencing (WES) analyses. Additionally we incorporated transcriptome sequencing data from 22 patients (21 paired-end samples and one single end sample)

  Study EGAS50000000488

• ChIP-seq data in MSC_Pat and EWIma1 (FLI1 & H3K27ac)

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001172

• RNA-seq data in hMPC, MSC_Pat and EWIma

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001173

• Delineating pediatric brain tumor progression using single-nuclei sequencing

  Pediatric brain cancers are the most common solid tumors in children with varying survival rates depending on molecular features of cancer cells and associated microenvironment. Several studies have used single-cell RNA sequencing to define transcriptional programs active in cancer cells and highlighted supportive roles of non-cancerous cells embedded in these tumors. Although application of single-cell RNA sequencing technology has expanded our understanding of intratumoral heterogeneity and underlying transcriptional mechanisms in brain tumors at diagnosis, mechanisms of disease remains elusive. Therefore, the purpose of this proposal is to characterize cellular and transcriptional states of malignant and non-malignant compartments at primary diagnosis and at relapse. In this study, we performed single-nuclei sequencing of 42 patient samples taken at various disease stages (initial diagnosis, progressive disease, and relapsed disease) from 20 patients with low-grade glioma or Atypical Teratoid Rhabdoid Tumor (ATRT). Bulk whole genome and RNA-seq data for these samples are available from the Children’s Brain Tumor Network and the Gabriella Miller Kids First Data Resource Center. Findings from our study will help define the mechanistic shifts of tumor and non-cancerous cells over course of disease progression. Collectively with the single-cell Pediatric Cancer Atlas funded, this project lays the foundation of an important data set focused on lethal relapsed cancers that can continue to be expanded to identify cancer-intrinsic and extrinsic microenvironmental factors supporting recurrence of pediatric brain tumors.

  Study EGAS50000001288

• De novo modeling of chromoplectic Ewing sarcoma tumors from patient-derived mesenchymal stem cells

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic (RNA-seq) and epigenetic (ChIP-seq) hallmarks of EwS.

  Dataset EGAD50000001673

• Multiomic Landscape of Multiple Myeloma Precursor and Relapsed Disease

  Multiple myeloma (MM) is a treatable, though incurable, plasma cell malignancy. The molecular mechanisms driving disease onset and the emergence of drug resistance remain elusive. To better characterize the mutational, transcriptional, and epigenetic alterations that accompany MM disease evolution, we accessed molecular data from MM patients treated at Moffitt Cancer Center, with bone marrow biopsies collected between 2011 and 2023.We performed scMultiome (single-cell, paired RNA/ATAC-Seq, 10x Genomics) on 18 CD138+-selected bone marrow aspirate samples, including: 2 healthy donors, 3 patients with monoclonal gammopathy of undetermined significance (MGUS), 4 with smoldering myeloma (SMM), 3 with newly diagnosed MM (NDMM), 1 with early relapse MM (ERMM, 1 to 3 lines of therapy), and 5 with late relapse MM (LRMM, 4 or more lines of therapy). Our dataset includes a sequential sample: a patient with a premalignant condition ("scMultiome_SMM_4") that progressed to active myeloma ("scMultiome_NDMM_3"). These data allow for the assessment of transcriptional and epigenetic dysregulation at the cellular level. Our findings illustrate the dynamic epigenetic and transcriptional landscapes that accompany MM disease progression.We also conducted CUT&Tag analysis on 4 NDMM and 4 LRMM samples to map histone modifications, specifically H3K27ac, to investigate their role in transcriptional reprogramming observed in advanced stages of MM. This analysis revealed sample heterogeneity in terms of super-enhancer-regulated genes associated with active transcription.This cohort also includes samples from the clinical trial NCT04151667, “Daratumumab-Based Response-Adaptive Therapy for Older Adults With Newly Diagnosed Multiple Myeloma.” We performed scRNAseq (single-cell RNA sequencing, 10x Genomics) on 30 CD138+-selected bone marrow aspirate samples and 31 pre-sort samples featuring bone marrow mononuclear cells of various cell types from 5 healthy donors and 11 patients with newly diagnosed MM (NDMM). Our dataset includes sequential samples for all 11 NDMM patients, both prior to induction therapy (denoted by ‘a') with Daratumumab and Dexamethasone, and at cycle 2 day 22 (C2D22, i.e., 60 days after induction therapy start, denoted by ‘b'). For three NDMM patients, we also have samples at relapse (denoted by ‘c'). These data allow for the assessment of transcriptional dysregulation at the single-cell level in both the tumor and immune-tumor microenvironment, associated with Daratumumab treatment in NDMM patients.In addition to the molecular data, demographic, and phenotypic information for all samples is provided.

  Study phs003892

• RNA sequencing data from glioblastoma primary cell lines treated with indisulam

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The splicing-modulating drug indisulam was investigated for its potential to induce aberrant transcriptomes, potentially increasing ncTSAs, subsequently predicted by NovumRNA. Four glioblastoma primary cell lines were derived from patient Cavitron Ultrasonic Aspirator (CUSA) material, cultured as neurospheres, and treated with indisulam or vehicle control. RNA was extracted at 6 and 16 hours post-treatment and sequenced using the NovaSeq platform. The resulting RNA-seq data was analyzed with NovumRNA, using healthy brain GTEx samples as controls, to identify and validate ncTSAs induced by indisulam treatment. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000680

• Single-cell G&T sequencing - Transcriptomic data

  Single-cell G&T seq from an untreated PDX mouse with neuroblastoma (MYCN amplified).

  Dataset EGAD50000001514