4821 results for "*oma"

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• Multi-modal spatial characterization of tumor-immune microenvironments identifies targetable inflammatory niches in diffuse large B-cell lymphoma

  This dataset includes NGS data of large B-cell lymphoma, including bulk RNAseq data of 71 biopsies and germline WES data of 70 biopsies.

  Dataset EGAD50000001641

• Methylation Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  3 sets of matched patient-derived-organoids (PDOs),  -neurospheres (PDNs), and parent glioblastoma tissue (9 samples total) underwent methylation array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Illumina EPIC v2.0 array. Data is provided as raw red and green .idat files.

  Dataset EGAD00010002745

• SNP Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  4 sets of matched patient-derived-organoids (PDOs),  -neurospheres (PDNs), and parent glioblastoma tissue (12 samples total) underwent SNP array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Global Screening Array v2.0 array. Data is provided as raw red and green .idat files.

  Dataset EGAD00010002744

• Studying Glioblastoma in a Human Organoid Tumor Transplantation Model

  This study comprises two complementary investigations that leverage innovative human model systems and cutting-edge molecular profiling to dissect glioblastoma (GBM) heterogeneity and tumor-microenvironment interactions. The first study uses a novel Human Organoid Tumor Transplantation (HOTT) model, in which freshly dissociated GBM tumor cells from five patients were transplanted into human embryonic stem cell-derived cortical organoids. This system enables the interrogation of tumor and microenvironment interactions in a human-specific, developmentally relevant context. Using single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq), the authors profiled over 216,000 cells, analyzing tumor heterogeneity across multiple media conditions. Ligand-receptor analysis (CellChat), immunofluorescence, and RNAScope were used to validate findings. The study revealed that the HOTT model faithfully recapitulates primary GBM cell types and microenvironmental components, and uncovered a novel bidirectional signaling axis mediated by PTPRZ1 that influences both tumor migration and cell fate in a context-dependent manner. PTPRZ1 is identified to be important for intercellular communication between tumor and microenvironmental cells, while PDGFRB, NOTCH3, HOPX, FAM107A, CLDN5, RGS5, FOXC1, SOX18 are key markers of the neurovascular progenitor that we identify to be a multipotent, restricted progenitor in GBM. Related datasets include the inclusion of immune cells in the HOTT system, termed “iHOTT”. The second study focuses on identifying and characterizing a rare but functionally potent neurovascular progenitor (NVP) population within GBM tumors. By generating a meta-atlas from seven publicly available GBM scRNA-seq datasets, the authors identified a unique tumor-derived cell population co-expressing neural progenitor and vascular markers. This population was validated in situ and in vivo through immunostaining and lineage tracing via DNA barcoding in the HOTT system. Functional knockdown of NVPs in a murine GBM model resulted in reduced cycling cells, altered tumor composition, and increased survival. Clonal analysis showed NVPs have dual potency to give rise to both neuronal and vascular-like tumor cells, contributing significantly to tumor cell diversity. Molecular technologies used across the studies include: Single-cell and single-nucleus RNA sequencing DNA barcoding and clonal lineage tracing (CellTag) Population information: Tumor samples were obtained directly from multiple GBM patients (all IDH1 wild-type, adult), including core and peripheral tumor regions. Human cortical organoids derived from human embryonic stem cells (hESCs) served as the microenvironment in the HOTT model. Principal findings include: HOTT recapitulates the heterogeneity and cell type fidelity of GBM, while enabling the study of tumor–microenvironment signaling. PTPRZ1 has opposing roles in tumor and microenvironment, influencing GBM cell migration and fate via non-catalytic mechanisms. A novel GBM neurovascular progenitor population (NVP) was identified, validated, and shown to contribute clonally to distinct tumor cell types. Elimination of NVPs in vivo reduces tumor aggressiveness and improves survival. Data to be available through dbGaP: Raw and processed single-cell and single-nucleus RNA-seq data (HOTT model and NVP studies) CellTag barcode-labeled scRNA-seq clonal lineage data Associated metadata including patient of origin, experimental condition, and sample annotations.

  Study phs003936

• Shallow Whole Genome Sequencing (sWGS) of pancreatic ductal adenocarcinoma

  Associated with CNA differences between RNA-based subtypes of PDAC. Shallow Whole Genome Sequencing (sWGS) generated 47 .bam files from 37 patients. sWGS was used for Copy number aberrations (CNA) determination.

  Dataset EGAD50000001732

• The dataset for "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma”

  The dataset for the study “ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma” includes 169 bam files from whole genome sequencing on the Illumina NovaSeq6000 platform. The samples analyzed include tumor (n=28) and normal (n=28) DNA samples, and serial plasma cfDNA (n=113) samples from 28 individuals with resectable diffuse pleural mesothelioma, treated with nivolumab or nivolumab plus ipilimumab on the NCT03918252 trial.

  Dataset EGAD50000001701

• DAC for EGA study: "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma"

  This DAC regulates access to the whole-exome sequence data for the study "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma".

  Dac EGAC50000000706

• BulkRNAseq - Notch Signaling Maintains a Progenitor-Like Subclass of Hepatocellular Carcinoma

  To identify the Notch signaling components expressed in both the human cancer cells and mouse stromal cells that typically comprise PDX tumors, we performed bulk RNA sequencing. Our results demonstrate that a JAG1-NOTCH2 signaling axis within the human cancer cell population drives the Notch dependency in the super-responder models, with NOTCH2 serving as the functionally relevant receptor.

  Study EGAS50000000515

• scRNAseq - Notch Signaling Maintains a Progenitor-Like Subclass of Hepatocellular Carcinoma

  To clarify the cellular composition and the mechanism of efficacy following JAG1/NOTCH2 inhibition, we performed single-cell sequencing of LIV78 tumors isolated from control animals or following inhibition of JAG1 or NOTCH2. The results suggest that sensitive tumors consist of heterogeneous populations of cells in distinct transcriptional states and that Notch signals emerge from ligand-receptor co-expressing cells.

  Study EGAS50000000517

• scRNAseq sequencing reads and count matrices of murine splenocytes from diffuse large B-cell lymphoma

  Single-cell RNA-seq of 91 murine splenocytes from Bcl6tg/+ and Cd70-/-; Bcl6tg/+ diffuse large B-cell lymphoma mouse models and Cd70-/- and wild-type controls.

  Dataset EGAD00001012104

• Single-cell RNA-seq of murine splenocytes from Bcl6tg/+ and Cd70-/-; Bcl6tg/+ diffuse large B-cell lymphoma mouse models and Cd70-/- and wild-type controls.

  Study EGAS00001007570

• Response to tumor-infiltrating lymphocyte adoptive therapy is associated with preexisting CD8+ T-myeloid cell networks in melanoma

  Adoptive cell therapy (ACT) using ex vivo–expanded tumor-infiltrating lymphocytes (TILs) can eliminate or shrink metastatic melanoma, but its long-term efficacy remains limited to a fraction of patients. Using longitudinal samples from 13 patients with metastatic melanoma treated with TIL-ACT in a phase 1 clinical study, we interrogated cellular states within the tumor microenvironment (TME) and their interactions. We performed bulk and single-cell RNA sequencing, whole-exome sequencing, and spatial proteomic analyses in pre- and post-ACT tumor tissues, finding that ACT responders exhibited higher basal tumor cell–intrinsic immunogenicity and mutational burden. Compared with nonresponders, CD8+ TILs exhibited increased cytotoxicity, exhaustion, and costimulation, whereas myeloid cells had increased type I interferon signaling in responders. Cell-cell interaction prediction analyses corroborated by spatial neighborhood analyses revealed that responders had rich baseline intratumoral and stromal tumor–reactive T cell networks with activated myeloid populations. Successful TIL-ACT therapy further reprogrammed the myeloid compartment and increased TIL-myeloid networks. Our systematic target discovery study identifies potential T-myeloid cell network–based biomarkers that could improve patient selection and guide the design of ACT clinical trials.

  Study EGAS50000001217

• 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