4772 results for "*oma"

in 35.72 milliseconds.

• Targeted panel sequencing of two patient-derived melanoma cell lines

  Targeted panel sequencing was conducted on patient-derived cell lines: Mel-DCC-11 (the parental line, sensitive to the BRAF inhibitor) and Mel-DCC-11-R (resistant to the BRAF inhibitor). The parental cell line was generated from disseminated cancer cells (DCCs) obtained from a lymph node sample of a melanoma patient. The resistant cell line was generated from the parental one through exposure to Vemurafenib. Normal peripheral blood lymphocytes from the same patient served as the control for comparison. Sequencing on NovaSeq6000. Fastq files.

  Dataset EGAD50000001745

• WES dataset of a TIL-ACT metastatic melanoma cohort

  Whole-exome sequencing (WES) data from 13 patients with metastatic melanoma in a TIL-ACT cohort, generated to characterize tumor genomics and neoantigen landscapes relevant to adoptive T cell therapy.

  Dataset EGAD50000001731

• Health Information National Trends Survey-SEER (HINTS-SEER)

  HINTS-SEER is a cross-sectional survey that sampled cancer survivors from three different SEER cancer registries. Sampling frames of survivors from each registry were stratified by time since diagnosis and race/ethnicity, with non-malignant tumors and non-melanoma skin cancers excluded. Respondents who consented completed a self-administered questionnaire sent through the mail and resulted in a total sample of 1,234 respondents. The goal of HINTS-SEER was to better understand the communication needs and practices, information preferences, risk behaviors and cancer knowledge of cancer survivors using a modified version of the Health Information National Trends Survey (HINTS) specifically designed for cancers survivors. Demographic information on the survivors showed that over 60% of the sample was 10 or more years since diagnosis with the most common cancers being male reproductive (24.6%), female breast (23%) and melanoma (9.6%) and gastrointestinal (8.6%). De-identified data is available in SAS, SPSS, and STATA formats, as part of a data package that also includes a history document, methodology report, data analysis recommendations, and a codebook.

  Study phs004065

• Methylproteome profiling of Diffuse Midline Glioma

  Study EGAS00001007342

• Total proteome and phosphoproteome profiling of Diffuse Midline Glioma

  Study EGAS00001007341

• Analysis of Large Cell Neuroendocrine Carcinoma Expressing HNF4alpha Using WGS

  Lung LCNEC (Large Cell Neuroendocrine Carcinoma) has a poor prognosis, and no effective treatment has yet been established. We have found that the gastrointestinal marker HNF4alpha is specifically expressed in some LCNEC cases. By performing Whole Genome Sequencing (WGS) on samples from 10 LCNEC patients, we aim to identify changes characteristic of LCNEC expressing HNF4alpha and explore new classifications and treatment options for LCNEC.

  Study JGAS000732

• Genetic mutation profiling of lymphomas arising in the uterine cervix and vagina

  Follicle center lymphoma (FCL) of the lower female genital tract (LFGT) is a rare lymphoma, with fewer than 20 cases reported to date. Since the genetic features of FCL of the LFGT have not been well characterized, we aimed to identify genetic alterations in this tumor through whole-exome sequencing or targeted gene panel analysis. Genomic DNA was extracted from a frozen tissue sample obtained from a surgically resected uterine cervical tumor. Whole-exome sequencing was performed using the Illumina NovaSeq X Plus platform. Library preparation was conducted with the SureSelect Human All Exon V6 kit, and sequencing was carried out with 150 bp paired-end reads.

  Study JGAS000823

• Spatial Transcriptomic Analysis (Xenium in situ) of Large Cell Neuroendocrine Carcinoma

  Lung LCNEC (Large Cell Neuroendocrine Carcinoma) has a poor prognosis, and no effective treatment has yet been established. We have discovered that LCNEC exhibits highly heterogeneous distribution of proteins such as neuroendocrine markers and YAP1 within the tumor. We hypothesize that this heterogeneity may be responsible for the variability in chemotherapy effectiveness and treatment resistance among LCNEC patients. Therefore, by using Xenium to analyze gene expression in greater detail along with tumor morphology, we aim to identify new characteristics of LCNEC and explore potential treatment strategies.

  Study JGAS000733

• cfDNA methylation profiling on longitudinally collected blood plasma of patients with esophageal adenocarcinoma

  cell-free Reduced Representation Bisulfite Sequencing (cfRRBS) data from blood plasma and FFPE tissue samples from patients with esophageal adenocarcinoma, and blood plasma of healthy donors.

  Dataset EGAD50000000734

• Dynamics of checkpoint receptors in γδ T cell subsets are associated with clinical responses during anti-PD-1 immunotherapies

  scRNA-seq data from circulating gamma delta T cells derived from healthy donors and patients with stage IV melanoma that either responded or did not respond to anti-PD-1 monotherapy or anti-PD-1 and anti-CTLA-4 combination therapy. This dataset includes paired samples from these patients before and 3 months after the start of immunotherapy.

  Dataset EGAD50000001812

• Spatial transcriptomics analysis of triple negative breast cancers

  While triple negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigated TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We performed an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures led to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identified nine TNBC ecotypes, further validated in external datasets. Several ecotypes were associated with disease outcome and characterized by potentially actionable features. In this work, we provideThis is the largest TNBC series providing a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy. All the processed data needed to replicate the results from the publication (counts, images, clinical data, etc) are available on Zenodo: https://zenodo.org/records/14204217

  Study EGAS50000000475

• Visium CytAssist Spatial Gene Expression analysis for glioblastoma

  The glioblastoma spatial transcriptomics dataset was generated from 4 FFPE fixed adult glioblastoma samples, using the 10x Genomics Visium platform, producing raw FASTQ files, spatial feature matrices (.h5, .mtx, .tsv), and paired histology images (.tif). Spot-level transcript counts were aligned to tissue architecture and processed in Seurat, with results stored as .rds objects. Data visualization was performed using SpatialFeaturePlot, and quantitative analyses were supported by custom Matlab scripts. The dataset provides both raw and processed files, offering reproducible spatially resolved transcriptomic profiles of glioblastoma tissue sections

  Dataset EGAD50000001767

• DAC policy The Kids Research Institute Australia

  DAC policy related to the study: Visium CytAssist Spatial Gene Expression analysis for FFPE glioblastoma samples. Committee: Emily Fletcher emily.fletcher@thekids.org.au Anya Jones anya.jones@thekids.org.au Emma Stone emma.stone@thekids.org.au

  Dac EGAC50000000734

• 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

• Single Cell Multiome ATAC + Gene Expression sequencing

  The SHH medulloblastoma tumor 7316-178 was received through the Childhood Brain Tumor Network (CBTN). From the patient tumor, disassociated cryopreserved cells stored in 10% DMSO/FBS were used. At least 50 mg of tissue (1 M cells) was used for both samples. Disassociated cells were prepared for Single Cell Multiome ATAC + Gene Expression sequencing (10× Genomics) according to the manufacturer’s instructions. Sequencing was performed on an Illumina NovaSeq S4 200 to a depth of at least 250 M reads for snATAC-seq and 200 M reads for snRNA-seq.

  Dataset EGAD50000001515

• WES of tumor samples from patients with renal medullary carcinoma (RMC)

  The dataset, in .bam file format, consists of whole exome sequencing (WES) data of tumors from patients (n=24) with Renal Medullary Carcinoma (RMC), generated using Illumina NovaSeq 6000 sequencing technology. DNA was extracted from FFPE solid tumor samples using the AllPrep DNA FFPE Kit (Qiagen, CA). Libraries from FFPE tissue were prepared with the SureSelect XT HS2 DNA Kit (Agilent, CA) for exome capture. The All Exon V7 exome probe set (Agilent, CA) was used for hybridization and capture of DNA.

  Dataset EGAD50000001822

• Shallow dataset

  Associated with Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL) Study. shallow Whole Genome Sequencing (sWGS) of 63 samples. sWGS was done to analyze copy number aberration.

  Dataset EGAD50000001165

• DAC for "High-Resolution Spatial Transcriptomics Uncover Epidermal-Dermal Divergences in Merkel Cell Carcinoma: Spatial Context Reshapes the Gene Expression Landscape" with Jürgen C. Becker(j.becker@dkfz-heidelberg.de) and Nalini Srinivas(n.srinivas@dkfz-heidelberg.de )

  Dac EGAC00001003599

• IDH-wildtype untreated human glioblastoma samples (GB-UK cohort), published in Noorani & Haughey et al 2025.

  Extrachromosomal DNA (ecDNA) oncogene amplification is associated with treatment resistance and shorter survival in cancer. Currently, the spatial dynamics of ecDNA, and their evolutionary impact, are poorly understood. Here, we investigate the spatiotemporal evolution of ecDNA by integrating computational modeling with samples from 94 treatment-naive human IDH wild-type glioblastoma patients. Random ecDNA segregation combined with ecDNA-conferred fitness advantages induce distinct spatial ecDNA copy number patterns which depend on ecDNA oncogenic makeup. EGFR-ecDNAs often reach high copy numbers and confer strong fitness advantages. In contrast, PDGFRA-ecDNAs reach lower copy numbers and confer weaker fitness advantages. EGFR structural variants occur exclusively on ecDNA, arise from and are intermixed with wild-type EGFR-ecDNAs. Computational modeling suggests wild-type and variant EGFR-ecDNAs often accumulate before clonal expansion. Using a genetically engineered mouse model, we confirm that the accumulation of oncogenic ecDNA prior to clonal expansion under strong positive selection is observable both in vivo and in vitro in mouse neural stem cells. Intermixed wild-type and variant ecDNAs remain prevalent at diagnosis, as less fit wild-type ecDNAs hitchhike on strongly selected variant EGFR-ecDNAs. A dN/dS analysis in the Genomics England cohort further suggests positive selection of variants on EGFR-ecDNAs but not PDGFRA-ecDNAs in glioblastoma. Overall, our results suggest ecDNA oncogenic makeup determines unique evolutionary trajectories in glioblastoma. New concepts like ecDNA tumor clonality, ecDNA heteroplasmy and multi-species ecDNAs require a refined evolutionary interpretation of genomic data in a large subset of glioblastoma patients and likely other solid cancers.

  Study EGAS00001008126

• cfDNA sWGS BAM — Metastatic colorectal cancer

  Plasma cirDNA sWGS for metastatic colorectal adenocarcinoma at diagnosis prior to systemic therapy. Libraries DSP/SSP (per sample). Sequencing by IntegraGen (2022–2024). Alignment: GRCh38 with BWA-MEM; BAMs sorted/indexed; delivered as primary mapped reads only (filters/MAPQ in analysis metadata). Controlled access

  Dataset EGAD50000001879

• WES dataset

  Associated with Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL) Study. Whole Exome Sequencing (WES) of 63 samples. WES analysis done to detect mutations and copy number aberration predictive for progression from RCD to EATL.

  Dataset EGAD50000001164

• Visium Spatial transcriptomics

  This study consists of the spatial transcriptomics data generated by : Visium CytAssist Spatial Gene Expression for FFPE (10x) for steatotic liver disease-associated hepatocellular carcinoma (SLD-HCC) (n=7) and non-SLD-HCC (n=5) The goal of this data is to compare SLD-HCC vs non-SLD-HCC as well as response to immunotherapy

  Dataset EGAD50000001506

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by targeted sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by a targeted panel for somatic mutation and sCNA analysis (7 samples), subject to cell availability. Mutation analysis was performed successfully in 6/7 samples and somatic mutations were detected in all of them.

  Dataset EGAD50000001888

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001889

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by targeted sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by a targeted panel for somatic mutation and sCNA analysis (7 samples), subject to cell availability. Mutation analysis was performed successfully in 6/7 samples and somatic mutations were detected in all of them.

  Dataset EGAD50000001890

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001891