Search Results - EGA European Genome-Phenome Archive

A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer

Background Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers. Methods We combined immunohistochemistry (IHC) with RNA-sequencing and whole genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8+ T-cell infiltration of the TIME. Further, we explored transcriptional features of immune archetypes, T-cell receptor sequencing diversity, assessed the relationship between CD8+ and CD4+ abundance by IHC and deconvolution predictions, and assessed common adult biomarkers such as neoantigen load and TMB. Results A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells. Conclusions Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.

Study EGAS00001007029

RNA sequencing data of 142 samples from 142 patients with HER2+ breast cancer treated with letrozole or tamoxifen (SOLTI PAMELA trial)

PAMELA (NCT01973660) is a non-randomized, open-label, multicentric, prospective translational research study in stage I-IIIA HER2+ breast cancer designed to evaluate the ability of the PAM50 intrinsic subtypes to predict pCR in the breast (pCRB) following 18 weeks of neoadjuvant lapatinib and trastuzumab (+/- hormonal therapy if hormone receptor [HR] positive). Patients with HR+ disease received letrozole (if postmenopausal) or tamoxifen (if pre-menopausal). The primary objective was to compare the pCRB rates of the HER2-E versus the non-HER2-E subtypes in the intent-to-treat population.

Study EGAS00001006410

Stem-like peripheral helper T cells seed their effector counterpart in rheumatoid arthritis

The dynamics of helper T cells in the synovium of rheumatoid arthritis was investigated using scRNA-seq, scTCR-seq, and spatial transcriptome.

Study JGAS000774

Intraductal transplantation models of human pancreatic ductal adenocarcinoma reveal progressive transition of molecular subtypes

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal common malignancy, with little improvement in patient outcomes over the past few decades. Recently, subtypes of pancreatic cancer with different prognoses have been elaborated. However, the inability to model these subtypes has precluded mechanistic investigation of their origins. Here, we present an orthotopic xenotransplantation model of human patient-derived PDAC organoids in which organoids are grafted via direct injection into the pancreatic duct of immunocompromised (NSG) mice. Tumors that arise from these intraductally grafted organoids (IGOs) enable the distinction of the two main PDAC subtypes: intraepithelial neoplasms from this model progress in an indolent or invasive manner representing the classical or basal-like subtypes of PDAC, respectively, depending on which organoid they originate from. RNA-sequencing was used to characterize the tumors that resulted from IGO xenografts, and to compare the fast- and slow-progressing IGO tumors. Tumors generated using a traditional orthotopic xenograft model, in which organoids are injected into the parenchyma of the pancreas (i.e. orthotopically grafted organoids, or OGOs), were also sequenced for comparison with the IGO tumors. To further characterize the model, laser-capture microdissection followed by RNA-sequencing was used to compare intraductal to invasive lesions resulting from IGOs. To better understand the connection between KRAS signaling and the fast-progressing phenotype, RNA-sequencing was used to compare cultured organoids in which oncogenic KRAS (GeneID: 3845) was hyperactivated to control organoids, and to compare laser-capture microdissected lesions derived from IGOs of KRAS-hyperactivated organoids to lesions derived from control organoids. To ascertain copy number, low-coverage, whole genome DNA-sequencing was performed on organoids cultured in vitro, and on laser-capture microdissected lesions derived from IGO tumors.

Study phs002045

H3K27ac ChIP-seq in Insulinomas

H3K27ac ChIP-seq datasets in human insulinoma samples

Dataset EGAD50000000461

BLUEPRINT EpiVar ChIP-seq of Monocytes & Neutrophils

Study EGAS00001000870

Programs, Origins, and Immunomodulatory Functions of Myeloid Cells in Gliomas

Gliomas are challenging malignancies characterized by an immunosuppressive microenvironment filled with myeloid cells, whose roles in immune modulation are not fully understood. In this study, we utilized single-cell RNA sequencing (scRNA-seq) data from 85 primary human glioma tumors, related blood samples, and brain tumor organoid models. We found that nearly all glioma-associated myeloid cells express at least one of four distinct immunomodulatory activity programs. These programs include:1. Scavenger Immunosuppressive Program2. Complement Immunosuppressive Program3. Microglial Inflammatory Program4. Systemic Inflammatory ProgramAll four programs are found in both lower-grade and high-grade gliomas and are expressed across various myeloid cell types, whether derived from blood or resident origins. We validated the remarkable plasticity of myeloid cells by showing that the introduction of peripheral blood monocytes into glioma organoid models can induce the emergence of identities resembling microglia, macrophages, and dendritic cells, as well as all four immunomodulatory programs. Our study provides a valuable resource and a new framework for understanding the role of immunomodulatory myeloid cells in gliomas, laying the groundwork for developing effective immunotherapy strategies for glioma patients.

Study phs003756

Synovial Fibroblast Gene Expression in Response to Fibronectin Fragment

Osteoarthritis (OA) is a prevalent joint disease characterized by the progressive degradation of articular cartilage, hypertrophy of neighboring bone, and varying degrees of synovial inflammation. Recent research has highlighted the potential role of synovial fibroblasts in the pathogenesis of OA, particularly their inflammatory properties that disrupt cartilage homeostasis. Notably, degraded cartilage matrix components, such as fibronectin fragments (FN-f), have been identified in the synovial fluid of OA patients, suggesting that FN-f signaling influences the synovium where synovial fibroblasts reside. Despite affecting over 500 million individuals globally, our limited understanding of the underlying mechanisms of OA has significantly impeded the development of effective treatment strategies. To investigate this, we obtained deidentified surgical waste material from individuals undergoing knee replacement for OA. Synovial tissue was used to isolate synovial fibroblasts for cell culture studies. We generated bulk RNA-seq data from primary synovial fibroblasts (N=5 individuals) treated at passage 3 with either Phosphate-Buffered Saline (PBS) as control or FN-f for 18h to model the OA synovial fibroblast phenotype. We identified differentially expressed genes at an adjusted p-value of

Study phs003999

Chicago Infant Mortality Study

The Chicago Infant Mortality Study (CIMS) was a population-based, prospective, case-control study conducted in metropolitan Chicago, Cook County, Illinois, to examine the risk factors for sudden infant death syndrome (SIDS) among a primarily Black population. Eligible case infants were aged birth to one year where the cause of death was determined to be SIDS while eligible control infants were aged one month to one year who died of other sudden unexpected infant death (SUID) causes. Recruitment occurred between November 1993 and April 1996. The goal of this ancillary multiomics study was to evaluate possible genetic and epigenetic determinates of SIDS and together with metabolomic profiles, identify novel clinical diagnostic tools to enable molecular autopsies and biomarkers to proactively identify and intervene in infants at greater risk of death from SIDS. The multiomics data was generated from medical examiner autopsy specimens and includes: whole exome sequencing genotypes; RNA-seq transcriptome and methylome profiles from autopsy heart tissue; and serum metabolomics profiles. The sample size available varies with the modality of the omics assay, but the total number of unique infants included is about 400.

Study phs003790

Germline mutations in the transcription factor IKZF5 cause thrombocytopenia.

To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing data from 13,037 individuals enrolled in the NIHR BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor encoding gene IKZF5 and thrombocytopenia. We report five causal missense variants in or near IKZF5 zinc fingers (Znfs), of which two occurred de novo and three co-segregated in three pedigrees. A canonical DNA-Znf binding model predicts that three of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared to wild-type (WT) IKZF5 and electron microscopy revealed a reduced quantity of alpha granules in normally sized platelets. Proplatelet formation (PPF) was reduced in megakaryocytes (MKs) from seven cases relative to six controls. Comparison of RNA-seq data from platelets, monocytes, neutrophils and CD4 T-cells from three cases and 14 healthy controls showed 1,194 differentially expressed genes in platelets but only four DEGs in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

Study EGAS00001003736

Risk and modifying factors in Frontotemporal Dementia

Understanding the molecular mechanisms underlying frontotemporal dementia (FTD) is essential for the development of successful therapies. Here, we present Phase 1 of a multi-omics, multi-model data resource for FTD research which will allows in-depth molecular research into these mechanisms. We have integrated and analysed data from the frontal lobe of FTD patients with mutations in MAPT, GRN and C9orf72 and detected common and distinct dysregulated cellular pathways. Our results highlight that excitatory neurons are the most vulnerable neuronal cell type and that vascular aberrations are a common hallmark in FTD. Via integration of multi-omics data, we detected several transcription factors and pathways which regulate the strong neuroinflammation observed in FTD-GRN. Finally, using small RNA-seq data and verification experiments in cellular models, we identified several up-regulated miRNAs that inhibit cellular trafficking pathways in FTD and lead to microglial activation. In this work we shed light on novel mechanistic and pathophysiological hallmarks of FTD. In addition, we believe that this comprehensive, multi-omics data resource will further mechanistic FTD research by the community.

Study EGAS00001004895

RNA-Seq of 584 DLBCL Cases of Non-China Cohort from Phoenix Clinical Trial

Standard RNA-Seq datasets. Check the associated paper for more details.

Dataset EGAD00001008131

Mediator ChIP-Seq datasets in human islets

6 ChIP-Seq datasets of Mediator in human pancreatic islets from 6 donors

Dataset EGAD00001005202

Cohesin ChIP-Seq datasets in human islets

3 ChIP-Seq datasets of Cohesin in human pancreatic islets from 3 donors

Dataset EGAD00001005203

Reference epigenome Islet-derived_MSC06 h3k27me3 ChIP-Seq data generated from KEP study

Islet-derived_MSC06 h3k27me3 ChIP-Seq paired end data

Dataset EGAD00001007896

Reference epigenome Islet-derived_MSC08 h3k4me3 ChIP-Seq data generated from KEP study

Islet-derived_MSC08 h3k4me3 ChIP-Seq paired end data

Dataset EGAD00001007906

Reference epigenome Islet-derived_MSC08 h3k27me3 ChIP-Seq data generated from KEP study

Islet-derived_MSC08 h3k27me3 ChIP-Seq paired end data

Dataset EGAD00001007903

Reference epigenome Islet-derived_MSC06 h3k27ac ChIP-Seq data generated from KEP study

Islet-derived_MSC06 h3k27ac ChIP-Seq paired end data

Dataset EGAD00001007895

Reference epigenome Islet-derived_MSC06 h3k9me3 ChIP-Seq data generated from KEP study

Islet-derived_MSC06 h3k9me3 ChIP-Seq paired end data

Dataset EGAD00001007900

Reference epigenome Islet-derived_MSC06 input ChIP-Seq data generated from KEP study

Islet-derived_MSC06 input ChIP-Seq paired end data

Dataset EGAD00001007901

Reference epigenome Islet-derived_MSC06 h3k4me3 ChIP-Seq data generated from KEP study

Islet-derived_MSC06 h3k4me3 ChIP-Seq paired end data

Dataset EGAD00001007899

Reference epigenome Islet-derived_MSC08 h3k27ac ChIP-Seq data generated from KEP study

Islet-derived_MSC08 h3k27ac ChIP-Seq paired end data

Dataset EGAD00001007902

Reference epigenome Islet-derived_MSC08 h3k9me3 ChIP-Seq data generated from KEP study

Islet-derived_MSC08 h3k9me3 ChIP-Seq paired end data

Dataset EGAD00001007907

Reference epigenome Islet-derived_MSC08 input ChIP-Seq data generated from KEP study

Islet-derived_MSC08 input ChIP-Seq paired end data

Dataset EGAD00001007908

Reference epigenome Islet-derived_MSC06 h3k36me3 ChIP-Seq data generated from KEP study

Islet-derived_MSC06 h3k36me3 ChIP-Seq paired end data

Dataset EGAD00001007897

Reference epigenome Islet-derived_MSC06 h3k4me1 ChIP-Seq data generated from KEP study

Islet-derived_MSC06 h3k4me1 ChIP-Seq paired end data

Dataset EGAD00001007898

Reference epigenome Islet-derived_MSC08 h3k4me1 ChIP-Seq data generated from KEP study

Islet-derived_MSC08 h3k4me1 ChIP-Seq paired end data

Dataset EGAD00001007905

Reference epigenome Islet-derived_iPSC04 h3k36me3 ChIP-Seq data generated from KEP study

Islet-derived_iPSC04 h3k36me3 ChIP-Seq paired end data

Dataset EGAD00001007890

Reference epigenome Islet-derived_iPSC04 h3k4me3 ChIP-Seq data generated from KEP study

Islet-derived_iPSC04 h3k4me3 ChIP-Seq paired end data

Dataset EGAD00001007892

Reference epigenome Islet-derived_iPSC04 h3k9me3 ChIP-Seq data generated from KEP study

Islet-derived_iPSC04 h3k9me3 ChIP-Seq paired end data

Dataset EGAD00001007893

Reference epigenome Islet-derived_iPSC04 h3k27me3 ChIP-Seq data generated from KEP study

Islet-derived_iPSC04 h3k27me3 ChIP-Seq paired end data

Dataset EGAD00001007889

Reference epigenome Islet-derived_iPSC04 h3k27ac ChIP-Seq data generated from KEP study

Islet-derived_iPSC04 h3k27ac ChIP-Seq paired end data

Dataset EGAD00001007888

Reference epigenome Islet-derived_iPSC04 h3k4me1 ChIP-Seq data generated from KEP study

Islet-derived_iPSC04 h3k4me1 ChIP-Seq paired end data

Dataset EGAD00001007891

Reference epigenome Islet-derived_iPSC04 input ChIP-Seq data generated from KEP study

Islet-derived_iPSC04 input ChIP-Seq paired end data

Dataset EGAD00001007894

Reference epigenome Islet-derived_MSC08 h3k36me3 ChIP-Seq data generated from KEP study

Islet-derived_MSC08 h3k36me3 ChIP-Seq paired end data

Dataset EGAD00001007904

STAG1 and STAG2-ChIP-seq in RAD21-mutant adult acute myeloid leukemia

Dataset EGAD00001015361

Genomic Analysis of Prostate Tumor Heterogeneity in Metastasis

To investigate the molecular changes, mutations, and signaling pathways that characterize the initial steps of prostate cancer metastasis to the lymph nodes, we analyzed 19 discrete lymph node (LN) metastases, 97 primary tumor foci, 39 benign lymph nodes, and 10 normal adjacent prostate tissue samples from 43 patients enrolled in a clinical trial (NCT01808222) of extended lymphadenectomy and metastasis excision guided by [18F]-fluciclovine PET imaging for high risk, newly diagnosed prostate cancer conducted at Emory University. These patients fell within high or very high-risk groups (T3a, Gleason score 8-10, or PSA greater than 20 ng/ml). Of these patients, 16 had LN metastases at least 4 mm in diameter, and 20 patients had no metastases. For metastatic patients, we performed RNA and Whole Exome Sequencing (WES) on three primary tumor foci, one benign LN, and all LN metastases greater than 4mm in diameter. For non-metastatic patients, we sequenced two primary tumor foci and one benign LN. In total, RNAseq was performed on 165 tissue samples from 43 patients, and WES was performed on 137 samples from 35 patients.

Study phs003404

Immune Landscape of Cervical Lymph Nodes in Multiple Sclerosis

This study aimed to investigate the cellular compartment of deep cervical lymph nodes (dcLNs) during early MS before the influence of immunosuppressive treatments. We used ultrasound-guided FNAs followed by scRNA-seq,CITE-seq, TCR and BCR seq to characterize the immune landscape in MS patients compared to controls within the dcLNs.

Study EGAS50000000843

BLUEPRINT EpiVar ChIP-seq for naive CD4+ T-cells

Study EGAS00001000753

Region-Specific Neural Stem Cell Lineages Revealed by Single-Cell RNA-Sequences from Human Embryonic Stem Cells

During development of the human brain, multiple cell types with diverse regional identities are generated. Here we report a system to generate early human brain forebrain and mid/hindbrain cell types from human embryonic stem cells (hESCs), and infer and experimentally confirm a lineage tree for the generation of these types based on single-cell RNA-Seq analysis. We engineered SOX2Cit/+ and DCXCit/Y hESC lines to target progenitors and neurons throughout neural differentiation for single-cell transcriptomic profiling, then identified discrete cell types consisting of both rostral (cortical) and caudal (mid/hindbrain) identities. Direct comparison of the cell types were made to primary tissues using gene expression atlases and fetal human brain single-cell gene expression data, and this established that the cell types resembled early human brain cell types, including preplate cells. From the single-cell transcriptomic data a Bayesian algorithm generated a unified lineage tree, and predicted novel regulatory transcription factors. The lineage tree highlighted a prominent bifurcation between cortical and mid/hindbrain cell types, confirmed by clonal analysis experiments. We demonstrated that cell types from either branch could preferentially be generated by manipulation of the canonical Wnt/beta-catenin pathway. In summary, we present an experimentally validated lineage tree that encompasses multiple brain regions, and our work sheds light on the molecular regulation of region-specific neural lineages during human brain development.

Study phs001205

SF11964 snATAC Seq Low Grade Astrocytoma IDHR132H mutant

Single Nuclei ATAC Seq IDHR132H mutant Astrocytoma . Male, 64. Single Nuclei ATAC seq data from low grade human glioma sample. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005414

Dataset of scRNAseq from 56 CRC, treatment-naive and post-chemotherapy

The dataset includes FASTQ source files of scRNA-seq for 56 CRC patients, sequenced with Illumina 10x platform. All patients were diagnosed with colorectal cancer between 2014 and 2022 at the Gustave Roussy Institute. Cohort includes 32 samples from untreated patients and 24 samples from patients who received chemotherapy. Chemotherapy included FOLFOX or FOLFIRI as first line, in some cases in combination with anti-VEGF or anti-EGRF drugs (avastin, bevacizumab or cetuximab) as the second and third lines. The post-treatment cohort included 18 responders (partial response, stable disease and complete response) and 6 progressors (progressive disease).

Dataset EGAD50000001218

11932 results for "cancer rna-seq"

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