4821 results for "*oma"

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• Single cell atlas of large B-cell lymphoma

  Large B-cell lymphomas (LBCL) are clinically and biologically heterogeneous lymphoid malignancies, shaped by complex tumor and microenvironments that play a critical role in disease progression. There has been no direct and comprehensive single-cell characterization of tumor microenvironment in LBCL that simultaneously captures lymphoid, myeloid, and stromal populations across a sufficiently large cohort to reveal reproducible and biologically meaningful patterns. Here, we performed single-nucleus multiome profiling, coupled with bulk DNA and RNA sequencing, on 232 tumor and control biopsies to comprehensively map cell subpopulations of LBCL. Through this integrative approach, we identified Lymphoma Microenvironment Archetype Profiles (LymphoMAPs)—distinct, reproducible patterns defined by the co-occurrence of functionally specialized cell subsets. We further characterized the cell-cell communication pathways that shape these transcriptional phenotypes within archetypes. Importantly, we discovered associations between specific LymphoMAPs and clinical and molecular features of LBCL, including response to CD19 CAR T-cell therapy. Our study provides a valuable resource of lymphoid, myeloid, and non-hematopoietic cell states in LBCL and offers a framework for understanding how the abundance and functional state of cells within the tumor microenvironment may drive inter-patient variability in therapeutic outcome.

  Study EGAS50000001022

• Single cell atlas of large B-cell lymphoma

  The dataset comprises multi-omics profiles from 232 biopsies, including 217 from patients with large B-cell lymphoma (114 newly diagnosed and 103 relapsed/refractory) and 15 benign control samples. Specifically: single-nucleus RNA sequencing (snRNA-seq) was performed on all 232 biopsies; single-nucleus ATAC sequencing was conducted on 96 biopsies; bulk RNA sequencing was generated for 208 biopsies; whole-exome sequencing (WES) was performed on 174 tumor biopsies with 118 matched germline samples; Low-pass whole-genome sequencing (lpWGS) was performed on 174 tumor biopsies with 41 matched germline samples. All raw data files are provided in FASTQ format.

  Dataset EGAD50000001491

• Methylation profiling of CDS and ES tumor samples

  Methylation profiling of 9 CDS and ES tumor samples, using the approach described in "Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  Dataset EGAD00010002760

• DKFZ-HIPO DACO for "Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target"

  Dac EGAC00001003559

• Single cell RNA-seq of two rare cases of human glioblastoma at multiple sampling points

  Glioblastoma is characterized by large cellular diversity whose complexity and organizing principles are only starting to be uncovered. Both neurodevelopment-like and mesenchymal-like cell states have been described in glioblastoma but the nature of the mesenchymal-like cell states remains unresolved. Here, we performed deep single-cell RNA sequencing of two rare glioblastoma cases where tissue could be sampled from tumor core to macroscopically normal cortex with the aim of understanding these tumor cell states.

  Study EGAS50000001030

• Human glioblastoma single cell RNA-seq from two patient, sampled at different positions within as well as outside tumor

  We performed deep single-cell RNA sequencing of two rare glioblastoma cases where tissue could be sampled from tumor core to macroscopically normal cortex. We processed two to three replicates per sample with the 10X Genomics V3.1 kits. Deep sequencing was performed to about 100,000 reads per cell on the Illumina NovaSeq 6000 platform, resulting in a total of 37 BAM files.

  Dataset EGAD50000001500

• Whole Exome Sequencing Data of 34 indolent primary renal B-Cell lymphoma cases

  Here, 34 iNHL samples were sequenced using whole exome sequencing to describe the mutational landscape of indolent primary renal B-Cell lymphomas. Mutational profiles were compared to other Marginal Zone Lymphomas.

  Dataset EGAD50000001136

• Whole exome sequencing of Human High-Grade-B-Cell-Lymphomas, classified according to IGH status

  HGBCL-DH-BCL2(-BCL6) lymphoma cases, classified according to IGH status in IGH+ or IGH-undetectable

  Dataset EGAD50000001527

• Whole genome sequencing of metachronous FL-High-Grade-B-Cell-Lymphomas, classified according to IGH status

  FL-HGBCL-DH-BCL2(-BCL6) metachronous lymphoma pairs, classified according to IGH status in IGH+ or IGH-undetectable

  Dataset EGAD50000001528

• Diagnostic Genomic Analysis is Prognostic in AYA ALL Patients Treated on a MRD-Stratified Paediatric Protocol

  Background: Over the last decade, next generation sequencing has enabled classification of multiple new recurrent genomic drivers of acute lymphoblastic leukemia (ALL). We provide a comprehensive genomic survey of adolescent and young adult (AYA) patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL06 study. ALL06 clinical trial described the efficacy and tolerability of AYA ALL patients aged 15-39 years treated on a single minimal residual disease (MRD)-stratified platform. In this study we have taken the ALL06 cohort and retrospectively performed comprehensive genomic analyses assessing response of AYA patients with various genomic subtypes treated with a paediatric approach. Methods: Genomic risk classification of B- and T-ALL patients (n=57) enrolled to the study was based on mRNA-Sequencing, MLPA, immunophenotyping and cytogenetics. Results: Using this approach, 36/40 (90%) B- and 13/17 (76.5%) T-ALL patients were classified according to genomic risk. We have linked outcome data with each patient’s genomic risk and found a strong correlation between adverse genomic risk and MRD at the end of consolidation, translating to inferior overall and relapse free survival. Patients with adverse risk genomics who achieved negative MRD status had improved responses compared to those with persistent MRD. Patients with standard risk genomics had excellent responses regardless of their MRD status. Conclusion: Our data argue strongly for incorporation of a genomic risk classification into future ALL treatment paradigms at the time of diagnosis.

  Study EGAS50000000752