Search Results - EGA European Genome-Phenome Archive

Cell line data (RNAseq, ATACseq, ChIPseq)

Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

Dataset EGAD00001005493

Transcriptomic response of miRNAs of monocytes to bacterial and viral stimuli assessed by RNA-seq in Africans and Europeans

Leveraging the miRNA transcriptome of 977 samples, the study aims to define the levels of miRNA and isomiR diversity across individuals and populations, explore the genetic sources of miRNA expression variability and miRNA-environment interactions, evaluate the effects of immune challenges upon miRNA and isomiR expression dynamics, and quantify the relative impact of transcription and miRNA-mediated degradation on gene expression variability.

Study EGAS00001004192

Single-cell RNA-seq of peripheral blood mononuclear cells in classic Hodgkin lymphoma

Abstract: Classic Hodgkin lymphoma (cHL) is a largely MHC class I-negative tumor with recurrent 9p24.1/ PD-L1/ PD-L2 copy gains and the highest reported response rates to PD-1 blockade. We utilized scRNA sequencing to characterize the peripheral immune response to PD-1 blockade and more broadly define non-CD8+ dependent mechanisms of immune evasion in cHL. Peripheral blood mononuclear cells were obtained from 20 patients with relapsed/refractory (R/R) cHL treated with PD-1 blockade (nivolumab) on the CheckMate 205 clinical trial (paired samples from cycle 1 day 1 [C1D1] and cycle 4 day 1 [C4D1]), 11 patients with newly diagnosed, previously untreated cHL and 13 healthy donors.

Dataset EGAD00001011360

A Single-Cell and Spatial Atlas of Early Human Olfactory Development

The human nasal region is a complex structure derived from neural crest and placodal lineages, but its development remains poorly understood due to limited fetal tissue access and its intricate architecture. To address this, we created a single-nucleus and spatial transcriptomic atlas of the human fetal nasal region using tissue from 10 fetuses between 7 and 12 post-conceptional weeks. Single-nucleus RNA sequencing (snRNA-seq) revealed 34 distinct cell types, including epithelial, cartilaginous, immune, neuronal, glial, muscular, and vascular cells. By integrating snRNA-seq with multiplexed error-robust fluorescence in situ hybridization (MERFISH), we tracked dynamic changes in cell composition and gene expression over time in the olfactory epithelium (OE) and surrounding nasal regions. We identified novel markers of olfactory sensory neuron development and key pathways regulating epithelial patterning and OE morphogenesis. Notably, we observed early molecular signatures consistent with the "one neuron-one receptor" model, with spatially organized expression of 171 olfactory receptor genes. Together, this study presents the first integrated molecular and spatial framework of early human nasal development. It offers an unprecedented molecular blueprint of olfactory system formation and serves as a foundational resource for embryologists and developmental biologists studying sensory neurogenesis, epithelial patterning, and congenital disorders.

Dataset EGAD50000001712

Genomic Analysis of Head and Neck Cancers

These aggregate studies focus on specimens from head and neck squamous cell carcinoma (HNSCC) patients who were treated with standard of care or window of opportunity clinical trial approaches. Specimens were interrogated with exome and RNA-Seq analysis. Patient derived xenografts (PDXs) represent a robust platform for performing co-clinical trial approaches. In the first study we generated a large panel of PDXs and compared genomic profiles between the primary tumor and matched PDX with the patients blood serving as a source of somatic variants. In the second study, we performed a window of opportunity clinical trial in oral cavity squamous cell carcinoma patients using the MEK inhibitor trametinib. In addition, PDX models were generated from these specimens also and analyzed as in the first study. Finally, the third approach used pembrolizumab, an anti-PD1 blocking antibody, in a window of opportunity setting in HNSCC patients. For the latter two studies genomic matched sample analysis was performed to define response and resistance mechanisms. Together, these genomic data will inform several therapeutic approaches for HNSCC patients.

Study phs001623

Characterization of Immune Evasion in Merkel Cell Carcinoma

Merkel cell carcinoma (MCC) is a rare, neuroendocrine skin carcinoma that is caused by the Merkel cell polyomavirus (MCPyV) in 80% of cases and by ultraviolet (UV) damage in 20% of cases. MCC should theoretically elicit a strong cytotoxic T cell response due to the high neoantigen and viral antigen burden in MCPyV- and MCPyV+ MCC, respectively. However, MCC often escapes immune recognition and is associated with very poor prognosis at advanced stages. To systemically identify mechanisms of immune evasion in MCC, we established 11 robust MCC lines from either primary tumors or patient-derived xenografts (7 MCPyV+ and 4 MCPyV-). We then characterized these tumors and cell lines by whole exome sequencing (WES), RNA-sequencing, scRNA-sequencing, ATAC-seq, and whole genome bisulfite sequencing (WGBS). We also studied MCC transcriptional subtypes, utilizing bulk and scRNA-sequencing datasets of patient-derived tumors and cell lines to investigate profiles of neuroendocrine gene expression. The genes linked below define either a neuroendocrine or a non-neuroendocrine phenotype presence within MCC tumors.

Study phs002260

Altered Interactions between Circulating and Tissue-Resident CD8 T Cells with the Colonic Mucosa Define Checkpoint Inhibitor Colitis

Therapeutic immune checkpoint blockade has revolutionized oncology, but treatments are limited by immune-related adverse events, including checkpoint inhibitor colitis (irColitis). To define molecular drivers of irColitis, we profiled ~300,000 cells from the colonic mucosa and blood of 29 patients and controls. Patients with irColitis showed expanded mucosal Tregs (regulatory T cells), CD8 tissue-resident memory T cells expressing CXCL13 and Th17 gene programs, and recirculating ITGB2 CD8 T cells. Cytotoxic CD4 T cells, recirculating CD8 T cells, and endothelial cells expressing hypoxia gene programs were further expanded in colitis associated with anti-PD-1/CTLA-4 compared to in the presence of anti-PD-1 therapy. Luminal epithelial cells in irColitis patients expressed PCSK9, PD-L1, and interferon-induced signatures associated with apoptosis, increased cell turnover, and malabsorption.Raw data files from both colon and PBMCs from irColitis patients and controls have been provided to dbGaP. Count matrices derived from raw RNA-Seq data will be available through GEO accession GSE206301.

Study phs003418

Multi-Omic Profiling of Glioma Patient Tumors and Patient-Derived Model Systems

We have created a resource of transcriptomic (RNAseq), genomic (whole-exome seq), and lipidomic (untargeted shotgun) profiling data from over 175 molecularly diverse glioma tumors and derivative models in orthotopic mouse xenografts and gliomasphere cultures from over 110 unique patient tumor lines. Provided in this dataset are matched bulk RNA and whole-exome paired-end sequencing data from resected gliomas and derived model systems performed on Illumina HiSeq and NovaSeq sequencing instruments. This comprehensive dataset powers multiple studies aiming to derive molecular signatures of intertumoral heterogeneity and perturbation responses in glioma. Through integrative multi-omic analyses in Minami, et al., 2023, PMID: 37236196, we identified that CDKN2A deletion remodels the GBM lipidome and consequently primes CDKN2A-deleted tumors for ferroptosis. Lipidomics data related to this study are publicly available here. In another study, we used a combination of molecular profiling and functional profiling of apoptotic potential to stratify patients into groups with differential vulnerability to the current standard-of-care in gliomas, and in combination with drugs targeting intrinsic apoptosis, largely informed but not limited to TP53 mutation status.

Study phs003286

Immuno-genomic Profiling of Biopsy Specimens Predicts Neoadjuvant Chemotherapy Response in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers and is primarily treated with platinum-based neoadjuvant chemotherapy (NAC). Some ESCCs respond well to NAC. However, biomarkers to predict NAC sensitivity and their response mechanism in ESCC remain unclear. We introduce a model by machine learning and validated its potential to predict the NAC response in ESCC. To create this model, we performed whole genome sequencing and RNA-seq analysis on totally 141 ESCC biopsy specimens before NAC treatment and analyzed their immuno-genomic features and association with NAC response. Neutrophils infiltration could play an important role in ESCC response to NAC. We also demonstrated that specific copy number alterations and copy number signatures in the ESCC genome were significantly associated with NAC response. The interactions between the tumor genome and immune features of ESCC are likely to be a new indicator of therapeutic capability and a new therapeutic target for ESCC, and machine learning prediction for NAC response is useful.

Study JGAS000535

Myasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma

Myasthenia gravis (MG) is a neurological disease caused by autoantibodies against neuromuscular-associated proteins. While MG is frequently developed in thymoma patients, the etiologic factors for MG are not well understood. Here, by constructing a comprehensive atlas of thymoma using bulk and single-cell RNA-seq, we identified ectopic expression of neuromuscular molecules in MG-associated thymoma (MG-thymoma). These molecules were originated from a distinct subpopulation of medullary thymic epithelial cells (mTECs), which we named neuromuscular mTECs (nmTECs). MG-thymoma also exhibited microenvironments dedicated to autoantibody production, including ectopic germinal center formation, T follicular helper cell accumulation, and type 2 conventional dendritic cell migration. Cell-cell interaction analysis also predicted the interaction between nmTECs and T/B cells via CXCL12-CXCR4. The enrichment of nmTECs presenting neuromuscular molecules within MG-thymoma was further confirmed by immunohistochemically and by cellular composition estimation from MG-thymoma transcriptome. Altogether, this study suggests that nmTECs play a significant role in MG pathogenesis via ectopic expression of neuromuscular molecules.

Study JGAS000482

Single-cell analysis of airway samples identifies immune cell activation correlating with COVID-19 disease severity

To investigate the immune response and mechanisms associated with severe COVID-19, we performed single-cell RNA-seq on nasopharyngeal and bronchial samples from 19 clinically well-characterized patients with moderate or critical disease and from 5 healthy controls. We identified airway epithelial cell types and states vulnerable to SARS-CoV-2 infection. In COVID-19 patients, epithelial cells showed an average threefold increase in expression of the SARS-CoV-2 entry receptor ACE2, which correlated with interferon signals by immune cells. Compared with moderate cases, critical cases exhibited stronger interactions between epithelial and immune cells, as indicated by ligand–receptor expression profiles, and activated immune cells , including inflammatory macrophages expressing CCL2, CCL3, CCL20, CXCL1, CXCL3, CXCL10, IL8, IL1B and TNF . The transcriptional differences in critical cases compared with moderate cases likely contribute to clinical observations of heightened inflammatory tissue damage, lung injury and respiratory failure. Our data suggest that pharmacologic inhibition of the CCR1 and/or CCR5 pathways may suppress immune hyperactivation in critical COVID-19.

Study EGAS00001004481

Exploring the Microbiome-Gut-Brain Axis with Respect to Psychoneurological Symptoms for Children with Solid Tumors

The human body hosts tens of trillions of microbes, a number 10 times greater than the number of human body cells. The collection of these human-associated microbes and their genomes is called the “human microbiome”. More than 90% of these microbes live in the gastrointestinal (GI) tract, representing 500 species on average. With the development of high-throughput sequencing technology and bioinformatics tools (e.g., 16S ribosomal RNA or 16S rRNA sequencing and shotgun metagenomics analysis), recent progress has been made to elaborate the critical role that the gut microbiome plays in human health and disease. A significant disruption (dysbiosis) of the composition and function of the gut microbiome is associated with carcinogenesis, chemotherapeutic metabolism, and treatment-related symptom toxicities. The current state of science on the gut microbiome in cancer has only recently started in animal models and adults, and has not been well investigated in children diagnosed and treated for cancer, nor with respect to associations with cancer treatment-related toxicities. This proposed study will explore the hypothesis that dysbiosis of the gut microbiome is associated with cancer treatment-related GI and psychoneurological symptoms. We will collect both stool samples (for the gut microbiome) and patient-reported outcomes across chemotherapy.

Study phs002960

Comprehensive molecular portrait reveals genetic diversity and distinct molecular subtypes of small intestinal neuroendocrine tumors

This study aims to characterize neuroendocrine tumors of the small intestine (siNETs) from genomic, transcriptomic, epigenomic, and clinical perspectives. Involving 122 patients and 219 samples, we generated whole-genome sequencing data, RNA sequencing data, genotyping arrays, and methylation arrays to conduct an integrative analysis of this rare tumor type. Our findings identify distinct molecular subtypes that correlate with siNET clinical features.

Study EGAS50000000642

Whole exome and RNA sequencing data from urothelial bladder cancer patients treated with anti-PD-(L)1

We have generated and analyzed genomic data from a cohort of metastatic urothelial carcinoma patients treated with ICI such as anti-PD-(L)1 monoclonal antibodies. The dataset contains whole exome sequencing data of 27 whole blood samples and 27 FFPE tumor samples. Further, it includes RNA sequencing data from 21 tumor samples. Following the RECIST criteria, 10 patients were classified as non-responders to the treatment, and 17 were responders. The dataset also contains a merged vcf file containing somatic mutations called by Strelka2 and Mutect2 following the gatk best practice pipeline.

Dataset EGAD00001010324

Single-cell RNA sequencing on 11,138 single T cells from 12 colon and rectal cancer (CRC) patients

Deep single-cell RNA sequencing data for 11,138 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive CRC patients. The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any academic research institutions complying with the laws and bioethic regulation policies of China will be approved.

Dataset EGAD00001003910

11936 results for "cancer rna-seq"

in 13.39 milliseconds.