4821 results for "*oma"

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• Sanger sequencing analysis data using cfRNA from plasma samples in 6 cases, 10 samples, all from sarcoma.

  We examined the levels of cfRNA in the blood of patients with malignant bone and soft tissue tumours harbouring specific fusion genes, to explore the relationship between fusion gene expression in the blood and therapeutic response and disease status, and to validate the clinical utility of liquid biopsy.

  Study JGAS000787

• Vaccine-Expanded Plasmablast-like B Cells Are Associated with Response to Dendritic Cell Therapy in Metastatic Melanoma

  Dendritic cells (DCs), either monocyte-derived (moDCs) or naturally circulating, have been employed in cancer treatment across both metastatic and adjuvant settings. DC vaccines (DC Vax) are capable of inducing tumor-specific immune responses, yet clinical outcomes have thus far fallen short of expectations. Here, we performed a multi-omics analysis of the apheresis product, including CD14⁺ monocytes, and the final DCVax formulation. Among all the components analyzed, the most striking finding was the unexpected presence of CD19⁺ B cells within the DC Vax formulation, which distinguished Responders from Non-Responders to moDC vaccination in metastatic melanoma. The abundance of B cells in DC Vax correlated with their peripheral frequency; however, within the vaccine, these cells acquired a CD20lowCD27hiCD38hi plasmablast-like phenotype, distinct from their autologous circulating B-cell precursors. Notably, a parallel observation was made in Responders, whose pre-treatment lesions were enriched in B cells organized as Tertiary Lymphoid Structures. These results underscore the importance of B cells in both baseline immunity and DCVax formulation, hinting at unexplored mechanisms by which they may influence vaccine effectiveness.

  Study EGAS50000001177

• RNA-Seq of primary pediatric kidney tumor controls for the soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008709

• RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008467

• WGS soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008466

• Detection of brain cancer using genome-wide cell-free DNA fragmentomes

  Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer detection. In this study, we analyzed genome-wide cell-free (cfDNA) fragmentomes, including fragmentation profiles and repeat landscapes, from the plasma of individuals with (n=148) and without (n=357) brain cancer. Machine learning analyses of cfDNA fragmentome features detected brain cancer across all grade gliomas (AUC=0.90, 95% CI: 0.87-0.93) and these results were validated in an independent prospectively collected cohort. cfDNA fragmentome changes in patients with gliomas represented a combination of fragmentation profiles from glioma cells and altered white blood cell populations in the circulation. These analyses reveal the properties of cfDNA in patients with brain cancer and open new avenues for noninvasive detection of these individuals.

  Study EGAS50000000986

• GOSH_Paediatric_Tumour_23P108_WSSS_WGS_Managed_Access

  We have a case of two siblings (twins) who were born with nodular blue rashes over their body. The first twin had a large periorbital subcutaneous mass which was diagnosed as infantile undifferentiated sarcoma. This baby was too systematically unwell for chemotherapy and died at 12 days of age. The second sibling received two cycles of emergency chemotherapy however died due to disease progression and secondary haemorrhage at 2 months of age. Post-mortem normal and tumour samples have been taken. In addition to placental tissue and parental germline DNA, the goal will be to investigate intra-uterine transfer of sarcoma and the phylogenetic relationship of tumours in both twins.

  Study EGAS00001007536

• Neuroblastoma Smart-Seq2 Single Nuclei Sequencing Data

  Heterogeneity of tumors, including the presence of resistant clones, represents a great challenge for high-risk neuroblastoma (NB). Currently, there are no treatments that address cancer heterogeneity. Classification of bulk tumors and corresponding predictions are poor and too general. Understanding heterogeneity will provide critical insight for the development of targeted therapeutic strategies. In this study, we collected 10 human neuroblastoma tumor samples and performed whole-transcriptome profiling at single-nucleus resolution using SMART-Seq2 technology. This approach enables comprehensive characterization of transcriptional diversity within individual tumors, allowing us to identify distinct cellular subpopulations.

  Study EGAS50000001103

• Human Neuroblastoma

  This dataset comprises single-nucleus transcriptomic profiles from 10 human neuroblastoma samples. Nuclei were isolated and processed using the SMART-Seq2 protocol to enable full-length, high-resolution RNA sequencing at the single-nucleus level. cDNA libraries were generated and sequenced on the Illumina HiSeq 2500 platform. The resulting raw sequencing data are provided as .fastq files for downstream analysis.

  Dataset EGAD50000001596

• miRNA-seq of paired Follicular Lymphoma (FL) patient samples before and after high-grade transformation to DLBCL (FL vs. tFL) from FFPE tissues

  The aim of this study was to analyze transcriptional changes in paired samples of follicular lymphoma (FL) and its histological transformation (tFL). Transformation of FL is an adverse event in the course of the disease and is associated with poor outcome. Several genetic aberrations have been linked to tFL pathogenesis, but gene expression changes and microenvironmental interactions have not been well characterized. We performed miRNA profiling of FL and paired tFL samples transformed to DLBCL (n=10 pairs). For miRNA profiling, we utilized libraries prepared using RNA isolated from archival FFPE tissues.

  Study EGAS50000000942

• RNA-seq from B-ALL patients treated on the ALLG ALL09 study

  Dataset contains RNA-sequencing data (fastq files) from 46 patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL09 study (ACTRN12618001734257). All patients were diagnosed with CD19 positive B-cell acute lymphoblastic leukaemia and were negative for Philadelphia chromosome positive disease. Patient samples (bone marrow or peripheral blood) were taken at diagnosis. mRNA was extracted from lymphoblasts and underwent paired-end sequencing using either the illumina NextSeq (75 bp PE) or MGI DNABSEQ-G400 (100bp PE) platforms. Transcriptomic data was used for identification of genomic drivers of acute lymphoblastic leukaemia (ALL).

  Dataset EGAD50000001603

• MOSAIC Window Mesothelioma Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 Mesothelioma patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001706

• MD Anderson Cancer Center HGSOC LRS Data Access Comittee

  Oxford Nanopore long-read sequencing was performed on six paired tumor-normal samples from patients with high-grade serous ovarian carcinoma. Reads were mapped to the GRCh38 reference genome, incorporating base modification information.

  Dac EGAC50000000597

• Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

  Study EGAS00001007404

• Involvement of the FGF8/FGF Receptor Signaling Pathway in the Maintenance and Progression of Fusion-Positive Rhabdomyosarcoma

  In our previous work, we used a myoblast model of fusion-positive rhabdomyosarcoma (FP-RMS) to demonstrate that FGF8, a target of the PAX3-FOXO1 (P3F) transcription factor, is essential for tumorigenicity driven by P3F. When aberrantly expressed, FGF8 can also sustain tumorigenicity in recurrent tumors that are independent of P3F. In this study, we report that FGF8, along with its receptors FGFR1 and FGFR4, is often highly expressed in FP-RMS tumors. We found that high levels of FGF8 expression in FP-RMS cells correlate with increased sensitivity to an FGFR4 inhibitor and a pan-FGFR inhibitor. Conversely, downregulating FGF8 led to a loss of sensitivity to these inhibitors. Interestingly, when FGF8 was upregulated in myoblasts, it resulted in decreased FGFR4 expression and sensitized the cells to an FGFR1 inhibitor and a pan-FGFR inhibitor. The downregulation of FGFR4 expression mediated by FGF8 could be reversed by inhibiting FGFR1, MEK, or ERK, thereby defining a signaling pathway through which FGF8 exerts its regulatory effects. Additionally, we discovered that high FGF8 expression in P3F-independent recurrent tumors is due to a rearrangement of viral long terminal repeat (LTR) sequences into the 3' untranslated region (UTR) of FGF8, leading to increased stability of FGF8 mRNA. These findings indicate that FGF8 plays an oncogenic role in FP-RMS through FGFR4 and may also exert oncogenic effects in P3F-independent relapses via FGFR1. Our study highlights the functional significance of FGF8 in FP-RMS and supports the rationale for preclinical investigations of FGFR inhibitors in treating this type of cancer.

  Study phs004009

• Sleep Heart Health Study (SHHS-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Related StudiesParent cohort phenotype data can be accessed through ARIC-BioLINCC, Framingham-BioLINCC, and CHS-BioLINCC. Objectives To determine the cardiovascular and other consequences of sleep-disordered breathing and to test whether sleep-disordered breathing is associated with an increased risk of coronary heart disease, stroke, all-cause mortality and hypertension by examining subjects from well-characterized and established epidemiologic cohorts. Background Obstructive sleep apnea syndrome (OSA) is a potentially debilitating condition characterized by repetitive episodes of apnea while asleep, nocturnal oxygen desaturation, excessive daytime sleepiness, and loud disruptive snoring. Epidemiologic data from middle-aged adults indicate that OSA is common, with prevalence rates of 4% in men and 2% in women. Prior studies implicated OSA as a risk factor for the development of hypertension, ischemic heart disease, congestive heart failure, stroke and consequently premature death. Questions arose as to whether an increased propensity for cardiovascular and cerebrovascular diseases was limited to only those with frank OSA or whether more subtle forms of sleep-disordered breathing (SDB) would also confer elevated risk. Further evidence was also needed to clarify whether, SDB, including OSA, is an independent risk factor for the development of cardiovascular or cerebrovascular disease. Known cardiovascular and cerebrovascular disease risk factors such as obesity and smoking are commonly present in those with SDB; therefore, apparent associations between SDB and cardiovascular and cerebrovascular diseases may have resulted from the effects of these concomitant risk factors. Moreover, there was no understanding as to whether such factors as race, age, gender, and prevalent cardiovascular or cerebrovascular disease might interact with SDB to alter future cardiovascular and cerebrovascular disease risk. Mechanisms underlying any propensity to develop cardiovascular or cerebrovascular disease with SDB had not been firmly established (Quan, et al., 1997, PMID: 9493915). Participants Participants in SHHS were recruited from nine existing NHLBI epidemiological studies in which data on cardiovascular risk factors had been collected previously. The “parent” cohorts included: Two sites of the Atherosclerosis Risk in Communities Study (ARIC) Three sites of the Cardiovascular Health Study (CHS) The Framingham Offspring Cohort The Strong Heart Study (SHS) sites in South Dakota, Oklahoma, and Arizona The New York Hypertension Cohorts The Tucson Epidemiologic Study of Airways Obstructive Diseases and the Health and Environment Study From these parent cohorts, a sample of participants who met the inclusion criteria (age 40 years or older; no history of treatment of sleep apnea; no tracheostomy; no current home oxygen therapy) was invited to participate in the baseline examination of the SHHS, which included an initial polysomnogram (SHHS-1). Several cohorts over-sampled snorers in order to increase the study-wide prevalence of sleep-disordered breathing. In all, 6441 individuals were enrolled between November 1, 1995 and January 31, 1998. During exam cycle 3 (January 2001-June 2003), a second polysomnogram (SHHS-2) was obtained in 3295 of the participants. Due to sovereignty issues, Strong Heart Study participants are not included in the shared SHHS data. Data from a total of 5839 participants (1920 ARIC, 1249 CHS, 997 Framingham Offspring and OMNI 1, and 1673 from other studies), consenting to share data are available. Design The Sleep Heart Health Study added in-home polysomnography to the data collected in each of the parent studies at a baseline SHHS exam and a follow-up approximately 4 years later. Using the Compumedics PS polysomnograph, sleep studies were obtained in an unattended setting, usually in the homes of the participants, by trained and certified technicians. The recording montage consisted of: C3/A2 and C4/A1 EEGs, sampled at 125 Hz right and left electrooculograms (EOGs), sampled at 50 Hz a bipolar submental electromyogram (EMG), sampled at 125 Hz thoracic and abdominal excursions (THOR and ABDO), recorded by inductive plethysmography bands and sampled at 10 Hz "airflow" detected by a nasal-oral thermocouple (Protec, Woodinville, WA), sampled at 10 Hz finger-tip pulse oximetry (Nonin, Minneapolis, MN) sampled at 1 Hz ECG from a bipolar lead, sampled at 125 Hz for most SHHS-1 studies and 250 Hz for SHHS-2 studies Heart rate (PR) derived from the ECG and sampled at 1 Hz body position (using a mercury gauge sensor) ambient light (on/off, by a light sensor secured to the recording garment)This montage provides data on the occurrence of sleep-disordered breathing, sleep stages, heart rate, oximetry and on arousals. Each participant in the parent studies was also asked to complete the Sleep Habits Questionnaire which covers usual sleep pattern, snoring, and sleepiness.

  Study phs003637

• Rituximab-treated lymphoma patients show correlated deficiency in serological and T cell Spike-specific response after SARS-CoV-2 vaccination: insights from the CORSA Study.

  This study is part of the CORSA trial (NCT04345315), a prospective multicentric research project conducted by the Istituto Romagnolo per lo Studio dei Tumori “Dino Amadori” to investigate the immunologic response to mRNA SARS-CoV-2 vaccines in patients with hematologic malignancies (HM) and healthy individuals as controls (HC). The data in this repository refer to two subcohorts: 7 healthy controls and 10 lymphoma patients, randomly selected. Whole blood samples were collected to characterize T cell receptor (TCR) repertoire specificity against SARS-CoV-2 proteins before and after two BNT162b2 vaccination cycles, at baseline (before vaccination), 50 days after the first dose (V1), and 6 months after the first dose (V3). All participants were vaccinated under the Italian national campaign and provided informed consent following the Declaration of Helsinki. We investigated SARS-CoV-2-specific T cell responses through TCR repertoire profiling and examined correlations between serological and cellular responses in both patient and control groups. Using Next-Generation Sequencing (NGS) to characterize the CDR3 sequences of TCR β-chains from peripheral blood, we assessed clonal expansion (depth) and diversification (breadth) of SARS-CoV-2-specific T cell clonotypes over time, aiming to understand how cancer and its treatment influence vaccine-induced immunity in immunocompromised individuals.

  Study EGAS50000001205

• T cell and Antibody Responses in Rituximab-Treated Lymphoma Patients After SARS-CoV-2 Vaccination

  This dataset contains T cell receptor (TCR) sequencing data from 51 RNA samples, each processed into three independent libraries (tot 153 FASTQ files). Sequencing was performed on an Illumina NextSeq 500 platform using the NextSeq 500/550 Mid Output Kit v2.5 (300 Cycles), generating paired-end FASTQ files with dual 10 bp barcodes and 5% PhiX as internal control. Libraries were quantified with the Qubit HS dsDNA kit and assessed for fragment size distribution using the Agilent Tapestation D1000 system before isochoric pooling to 4 nM and sequencing in two independent runs. The resulting dataset enables analysis of TCR β-chain CDR3 sequences for clonal expansion and diversity studies.

  Dataset EGAD50000001714

• Genomic landscape of poorly differentiated thyroid carcinoma

  Poorly differentiated thyroid carcinoma (PDTC) is a rare and aggressive subtype of thyroid cancer with limited molecular characterization. This study aims to define the somatic mutational landscape of PDTC using whole-genome sequencing. Paired tumour and matched normal blood samples were collected from six patients undergoing surgery. The overarching goal is to identify recurrent mutations, structural variants, and other genomic alterations associated with tumour aggressiveness and poor clinical outcomes.

  Study EGAS50000001134

• Bulk RNA sequencing data of high-grade serous ovarian cancer samples (set 7-17)

  The dataset contains RNA sequencing data of 272 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000, MGISEQ or Hiseq X Ten. The 814 samples are fresh frozen tissue samples that have been collected from different tissues and time points before and during treatment. The files provided are paired fastq files.

  Dataset EGAD50000001370

• Somatic L1 retrotransposition dynamics in high-grade serous ovarian cancer

  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 same patient were utilised to understand L1-mediated intrapatient heterogeneity.

  Study EGAS50000001198

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

  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).

  Dataset EGAD50000001707

• Hematopoietic Tet2 inactivation enhances the response to checkpoint blockade immunotherapy

  Somatic mutations inactivating TET2 are among the most common drivers of clonal hematopoiesis (CH). While TET2 inactivation is associated with monocyte-derived inflammation and improved chimeric antigen-receptor-T cell function, its impact on immunotherapy response is unknown. In murine models, hematopoietic Tet2 mutation enhanced the immune checkpoint blockade (ICB) response via the combined presence of phagocytes, CD4 and CD8 T cells. This effect was lost with myeloid- or T-cell restricted Tet2 inactivation, or in mice with 20% Tet2-mutant hematopoiesis. Mechanistically, in Tet2-mutant tumor-infiltrating leukocytes (TILs), ICB preferentially restricted cell states linked to tumor progression while inducing anti-tumor states. Tet2-mutant monocytes activated costimulatory programs, while Tet2-mutant T cells showed enhanced T cell memory signatures, alongside decreased exhaustion and regulatory phenotypes. This murine data was clinically relevant, since tumors from colorectal cancer and melanoma patients with TET2 driver mutation-CH (TET2-CH) showed enhanced immune infiltration, inflammation, and T cell activation. In melanoma patients treated with ICB, TET2-CH was associated with 6-fold greater odds of clinical benefit. Collectively, we demonstrate that hematopoietic Tet2 inactivation primes leukocytes for anti-tumor states associated with immunotherapy response and provides a potential biomarker for personalized therapy.

  Study EGAS50000001191

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

  To assess how Notch inhibition impacts chromatin accessibility and how chromatin changes relate to HNF4A and CEBPA activities, we performed Assay-for-Transposase-Accessible-Chromatin (ATAC) sequencing of LIV78 tumors, 72 hours after treatment with NOTCH2 blocking or control antibodies. Our TF activity and chromatin analyses thus lead to a model in which Notch inhibition leads to increased expression of CEBPA, thus enabling CEBPA to partner with HNF4A to jointly drive transcriptional programs and the underlying chromatin rearrangements that promote differentiation of progenitor-like tumor cells to a mature hepatocyte fate incompatible with tumor growth and maintenance.

  Study EGAS50000000516

• Human Paraganglioma

  This dataset comprises single-nucleus transcriptomic profiles from 9 human paraganglioma samples. Nuclei were isolated and processed using the SMART-Seq2 protocol to enable full-length, high-resolution RNA sequencing at the single-nucleus level. cDNA libraries were generated and sequenced on the Illumina HiSeq 2500 platform. The resulting raw sequencing data are provided as .fastq files for downstream analysis.

  Dataset EGAD50000001689