3659 results for "RNA AND sequencing OR transcriptome"

in 22.90 milliseconds.

• RNA sequencing of in vitro generated suppressive myeloid cells using parental and Sialidase expressing A549 cancer cell lines

  Study EGAS00001007618

• Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  Study EGAS00001008050

• Single-Cell RNA-Sequencing Analysis of Responses to Pembrolizumab in Sezary Syndrome

  This phase 2 single arm clinical trial assessed the efficacy of pembrolizumab in patients with previously treated mycosis fungoides or Sezary syndrome. Pembrolizumab was found to have a 38% overall response rate, and a 27% overall response rate in subjects with Sezary syndrome. We performed single-cell RNA-sequencing on samples collected before the first treatment and after 3 weeks of pembrolizumab treatment. Sequencing was performed on cryopreserved peripheral blood T-lymphocytes isolated from 6 trial participants, including 3 patients who responded to pembrolizumab treatment and 3 patients who did not respond. A total of 118,961 peripheral blood T-cells are included in this data set.

  Study phs002933

• Dataset for hepatopancreaticobiliary_malignancy-RNA

  Rare cancer sequencing data of 119 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008863

• The Adhesion GPCR ADGRL2 Engages Galpha13 to Enable Epidermal Differentiation

  We sought to determine the role of ADGRL2 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. ADGRL2, working through GNA13, was found to promote epidermal differentiation through the ADGRL2 intracellular loop 3 (ICL3) loop, using the methods of RNA-seq and Perturb-seq.

  Study phs004223

• IKZF5 RNAseq samples for platelets, neutrophils, monocytes and CD4+ T-cells.

  To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing (WGS) 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 (TF)-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 (EM) 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 (DEGs) 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.

  Dataset EGAD00001005107

• A Phase Ib/II Study of Regorafenib and Paclitaxel in Beyond First-line Advanced Esophagogastric Carcinoma (REPEAT)

  Regorafenib showed promising results in gastric cancer. We aimed to assess the tolerability of regorafenib and paclitaxel in advanced esophagogastric cancer (EGC) patients refractory to first-line treatment and explore potential biomarkers.. We performed enzyme-linked immunosorbent assay measurements of galectin-1, RNA sequencing, and shallow wholegenome sequencing of metastatic tumor biopsies for biomarker analyses.

  Study EGAS00001006054

• Genomic and transcriptomic profiling of signalling networks in follicular lymphoma

  This dataset is composed of sequencing data from 16 patients diagnosed with follicular lymphoma, who developed transformed disease and for whom representative frozen tumor biopsy samples were available. For 14 patients there is paired material from both disease stages. DNA and RNA libraries were constructed and captured with a kinome bait library (Agilent Technologies), before sequencing on an Illumina platform.

  Study EGAS00001002175

• The genomic landscape of Burkitt Lymphoma

  As part of the ICGC, the ICGC MMML-Seq project performed whole genome sequencing and RNA sequencing of Burkitt Lymphomas . Burkitt lymphomas are the most common B-cell lymphomas in childhood. Analyses were performed in concordance with the guidelines of the ICGC. The results define the genomic landscape of structural variants, somatic single nucleotide variants and mutational signatures in these lymphomas.

  Study EGAS00001002198

• RNA Editing Exome

  Exome sequencing data for tumor and matched normal samples of the EGAS00001000495 project.

  Dataset EGAD00001000626

• HCA_Adrenal_Foetal_WSSS_RNA_SB

  The Human Cell Atlas initiative is an ambitious global research effort which aims to describe every cell in the human body across all developmental stages to generate a reference map to accelerate progress in science and medicine particularly relating to human development and disease. The initiative is led by investigators based at the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard and funding support from the Wellcome and NIH. This specific project will assess human development. We aim to interrogate the cellular composition and molecular regulators underpinning development and maturation through single cell RNA-sequencing/spatial transcriptomics and computational algorithms to predict cellular developmental trajectories and cell-cell interactions. We will subsequent validate these findings in situ using allied imaging technologies e.g. immunohistochemistry and RNAscope and in vitro culture of human intestinal organoids (HIOs). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001004089

• Developing Allelic Imbalance Analysis from Single-Nucleus RNA-Seq Data

  Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that, because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq) and introns are under lower purifying selection, and are thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. Overall, we provide an end-to-end experimental and computational approach for future studies.

  Study phs003749

• Proteogenomic Landscape of Squamous Cell Lung Cancer

  To provide a detailed analysis on how genomic and transcriptomic alterations related to proteome level changes in squamous cell lung cancer (SCC), we performed an integrated analysis incorporating DNA copy number, somatic mutations, expression RNA-sequencing, and expression proteomics in 108 SCC nested within clinical outcome, tumor pathology, and other clinically relevant data.

  Study phs001781

• BRCA Mutation Status Shapes the Microenvironment of Pancreatic Adenocarcinoma

  This study was established in order to address how the stromal landscape is influenced by BRCA-mutated and BRCA Wild-type (WT) pancreatic ductal adenocarcinoma (PDAC). A primary cohort of 12 PDAC patients (7 BRCA-WT and 5 germline BRCA-mut) was analyzed by laser-capture microdissection, RNA-sequencing and multiplexed immunofluorescence.

  Study phs002994

• DAC for study: "Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer."

  This is Data Access Committee will oversee data sharing for sequence data in the EGA study: "Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer." This dataset includes 116 bam files from whole exome sequencing on the Illumina HiSeq2500, 102 fastq files from RNA sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor/normal DNA samples and tumor RNA samples from 72 individuals with non-small cell lung cancer treated with pembrolizumab and SBRT or pembrolizumab alone on the NCT02492568 trial.

  Dac EGAC50000000202

• Ex vivo modeling of precision immuno-oncology responses in lung cancer

  Single-cell RNA-sequencing (scRNA-seq) data from paired lung cancer organoids and immune cells. The experiment was performed using the Single Cell 5' solution of 10X Genomics. The dataset includes 15 samples from 4 multiplexed experiments. The multiplexing was performed using the Feature Barcoding technology of 10X Genomics.

  Study EGAS50000000593

• Black Representation in Genomic Research Whole Blood eQTL Study

  This dataset contains whole genome sequencing (WGS) results, as well as mRNA-seq of RNA extracted from a venous blood sample, from 23andMe research participants of African ancestry. This dataset facilitates the study of gene expression, genetic variation and the genetic architecture of gene expression in individuals of African ancestry.

  Study phs002969

• Integrated Somatic and Germline Molecular Properties Dictating Biological and Clinical Phenotypes in Cancer

  We performed single-nuclei matched RNA- and ATAC-sequencing of frozen biopsies from normal adjacent tissue, primary and metastatic esophageal adenocarcinoma specimens. The data was then further stratified into a tumor microenvironment and malignant compartment and was computationally analyzed to reveal cancer cell subtypes and programs driving malignancy.

  Study phs003438

• Oncogenic gene fusions in primary colon cancers

  This study represents RNA-sequencing data from 278 primary colon cancers obtained from fresh-frozen tumor sections. The project goal was to identify novel oncogenic gene fusions in these data. In addition, we studied the detected gene fusions at the molecular level and defined their effects on downstream pathways.

  Study EGAS00001002197

• Comparison of fresh and slow-frozen cancer samples for different applications

  Surplus tissues from multiple solid human cancers directly slow-frozen after resection can subsequently be used for different types of methods including the establishment of 2D, 3D, and ex vivo cultures as well as single cell RNA sequencing (scRNAseq) with similar results when compared to freshly analyzed material.

  Study EGAS00001005891

• Natural Killer Cell Plasticity During IL-15-driven Homeostatic Proliferation

  Here we performed single-cell RNA sequencing to address repertoire stability and subset plasticity during IL-15 driven homeostatic proliferation. Sorted NK cell subsets representing discrete stages of NK cell differentiation are compared with the corresponding subsets after proliferation and further sorted into two subsets depending on the rate of proliferation.

  Study EGAS00001003946

• Transcriptomic signatures of CD4+ T cells from visceral leishmaniasis (VL) patients

  Bulk RNA-sequencing was performed on CD4+ T cells isolated from the blood of visceral leishmaniasis patients (n = 12) and endemic controls (EC; n = 12). CD4+ T cells were obtained by magnetic-activated cell sorting (MACS). Alterations in the transcripts of T helper (Th) cells during infection were identified.

  Study EGAS00001004152

• Smart-seq3 scRNA-seq of cells from primary (OV2295) and metastatic (OV2295R2) high-grade serous ovarian cancer cell-line

  In this project, single cells extracted from two high-grade serous ovarian cancer cell-lines, one primary (OV2295) and one metastatic (OV2295R2), where split into two 384 well plates and libraries were prepared using Smart-seq3 single cell RNA sequencing (Hagemann-Jensen et al, 2020).

  Study EGAS00001006868

• Systematic comparative analysis of single-nucleotide variants detection methods from single-cell RNA sequencing data

  Systematic interrogation of single nucleotide variations (SNVs) is one of the most promising approaches to delineate the cellular heterogeneity and phylogenetic relationships at the single cell level. While SNV detection from abundant single cell RNA sequencing (scRNA-seq) data is applicable and cost-effective in identifying expressed variants, inferring sub-clones, and deciphering genotype-phenotype linkages, there is a lack of computational methods specifically developed for SNV calling in scRNA-seq. Although variant callers for bulk RNA-seq have been sporadically used in scRNA-seq, the performances of different tools have not been assessed. Here, we performed a systematic comparison of seven tools including SAMtools, the GATK pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, using both simulation and scRNA-seq datasets, and identified multiple elements influencing their performance. Our study provided the first benchmarking to evaluate the performances of different SNV detection tools for scRNA-seq data.

  Study EGAS00001003883

• Notch Signaling and Efficacy PD-1/PD-L1 Blockade in Relapsed Small Cell Lung Cancer

  Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine (NE) cancer that accounts for approximately 15% of all lung cancer, with an annual incidence of more than 34,000 in the United States alone. SCLC is characterized by loss of function of p53 and RB and high tumor mutational burden, which suggests that these tumors could be immunogenic and respond to immune checkpoint blockade (ICB). However, the benefit from ICB in an unselected SCLC population is modest. In this study, we evaluated the genomic features associated with clinical outcomes in relapsed SCLC to gain insight into the underlying mechanisms of ICB response. Exome, RNA and TCR sequencing data from a prospective clinical trial of relapsed SCLC treated with durvalumab and olaparib and RNA-sequencing data for second cohort of relapsed SCLC cohort treated with nivolumab are included.   

  Study phs002176

• Transfer Learning Associates CAFs with EMT and Inflammation in Tumor Cells in Human Tumors and Organoid Co-Culture in Pancreatic Ductal Adenocarcinoma

  This study examined the transcriptional changes induced by cancer associated fibroblasts (CAFs) in pancreatic ductal adenocarcinoma patient-derived tumor organoids. We hypothesized that cancer associated fibroblasts impacted tumor cell transcription to promote tumorigenic behavior. Using patient-matched cells from 3 patients, we compared the transcriptional profiles of patient-derived organoids in monoculture to patient-derived organoids co-cultured with CAFs. Similarly, we looked at the transcriptional changes in matched patient-derived cancer associated fibroblasts grown in monoculture or co-cultured with patient-derived organoids. With a focus on intercellular crosstalk, we identified crosstalk between cancer associated fibroblasts and patient-derived organoids through VEGFA and NRP1. This was identified by bulk RNA sequencing and examined dynamically in organoid-CAF co-culture. This dbGaP deposit is the bulk RNA sequencing data for these 3 patients.

  Study phs003563

• P4HA1 Mediates Hypoxia-Induced Invasion in Human Pancreatic Cancer Organoids

  Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy defined by extensive invasion into the local tumor microenvironment and systemic metastasis. PDAC develops in a hypoxic microenvironment and adapts to survive under low oxygen conditions, including the activation of processes that may enhance the ability of cancer cells to invade locally or metastasize. Here we employ bulk RNA-sequencing of eight patient-derived organoid (PDO) cultures grown in hypoxia and normoxia to identify differentially expressed genes. PDOs were grown in Matrigel, transferred into collagen domes, then incubated in hypoxia or normoxia. Invasive organoids were individually collected from collagen domes grown in hypoxia and normoxia separately and processed for RNA-sequencing analysis. Using this dataset, prolyl 4-hydroxylase subunit alpha (P4HA1) was identified as a potential regulator of PDAC invasion in hypoxia. This dataset exists as a reference for gene expression of invasive organoids in hypoxia and normoxia.

  Study phs003961

• Functional Genomic Landscape of Acute Myeloid Leukemia

  The implementation of targeted therapies for acute myeloid leukemia has been challenged by complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. The initial findings from the Beat AML program were from a cohort of 672 tumor specimens collected from 562 patients. Additional patients have been added in subsequent versions. We assessed these specimens using whole exome sequencing, RNA-sequencing, and ex vivo drug sensitivity analyses. Our data reveal novel mutational events not previously detected in AML. We show association of drug response with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA-sequencing also revealed gene expression signatures, which predict a role of specific gene networks in drug response. Collectively, this report offers a dataset, accessible by the Beat AML data viewer (www.vizome.org), that can be leveraged to address clinical, genomic, transcriptomic, and functional inquiries into the biology of AML.

  Study phs001657

• Reproducibility of 10x Genomics single cell RNA sequencing method in the immune cell environment

  Study EGAS00001005905

• MILK-Omics: Systems Biology of Human Milk and Its Links to Maternal and Infant Health

  The primary objective of the project is to generate a systems-level view of human milk in the context of healthy mothers and their term infants. The study uses biospecimens and clinical data from the Mothers and Infants LinKed for Healthy Growth Study (MILk Study), a prospective observational cohort of approximately 500 exclusively breastfeeding women and their infants who are followed to 6 months of age. The project focuses on mature milk samples collected at 1 month postpartum and infant gut microbiome samples collected at 1 and 6 months of age. Specific Aim 1 is to identify maternal genetic and clinical factors that shape human milk gene expression. Using bulk and single-cell RNA sequencing of the milk cell pellet and genotypes from maternal DNA, we will identify novel genetic determinants of the milk transcriptome and assess potential modification of these genetic associations by gestational weight gain, diet, and other clinical factors. Specific Aim 2 is to describe key features of the normative human milk biosystem and their interactions with one another. Specifically, machine learning techniques will be used to characterize interaction networks and correlational structures among the following features of human milk: transcriptomics, microbiomes, oligosaccharides, metabolomics, lipidomics, and milk macronutrient composition. Specific Aim 3 is to establish how the milk biosystem is related to variation in infant gut microbiomes and health. dbGaP will house the maternal genotype and milk transcriptomics data.The infant microbiome sequence data are associated with BioProject PRJNA1019702.

  Study phs003408

• DNA hypermethylation and differential gene expression associated with Klinefelter syndrome

  The molecular basis for the phenotypic traits and morbidity in Klinefelter syndrome (KS) are not clarified. As DNA methylation affect gene expression and thereby play a role in disease susceptibility, we performed genome-wide DNA methylation profiling of leucocytes from peripheral blood samples from 67 KS patients, 67 male controls and 33 female controls, in addition to genome-wide RNA-sequencing profiling in a subset of 9 KS patients, 9 control males and 13 female controls. Characterization of the methylome as well as the transcriptome of both coding and non-coding genes identified a unique epigenetic and genetic landscape of both autosomal chromosomes as well as the X chromosome in KS. A subset of genes show significant correlation between methylation values and expression values. Gene set enrichment analysis of differentially methylated positions yielded terms associated with well-known comorbidities seen in KS. In addition, differentially expressed genes revealed enrichment for genes involved in the immune system, wnt-signaling pathway and neuron development. Based on our data we point towards many new candidate genes (AKAP17A, AMOT, APOB, DACT1, DDX58, DOCK7, EIF2S3, FIGNL1, G3BP1, HENMT1, HERC5, IFI44, IFI44L, IFIT1, IFIT3, ISG15, KANK1, LGALS1, NSD1, PEX10, PLSCR1, RSAD2, SHROOM2, SLC25A6, SPEG, SPON2, TXLNG), which may be implicated in the phenotype and further point towards non-coding genes (RP13-216E22.4, RP13-36G14.4, G087825, G088512), which may be involved in X chromosome inactivation in KS and in the regulation of escape genes.

  Study EGAS00001002797

• Uncovering RNA Signatures of C9orf72-Linked ALS and Related Disorders

  Substantial clinical and pathological variability has been reported in patients carrying an expanded repeat in C9orf72, who are generally diagnosed with amyotrophic lateral sclerosis (ALS) and/or frontotemporal dementia (FTD). Emerging evidence suggests that C9orf72 expression, RNA foci, and dipeptide-repeat proteins contribute to C9orf72-related diseases; however, the majority of the clinicopathological variability remains unexplained. We hypothesize that RNA sequencing (RNA-Seq) might reveal individual genes or groups of highly correlated genes (modules) that could account for this variability, which may help to identify much-needed druggable targets and/or biomarkers. Our preliminary studies performed in the frontal cortex, where we compared C9orf72 expansion carriers to (disease) controls, demonstrated that the top differentially expressed gene was C9orf72 itself. We also noticed that differentially expressed genes were enriched for the endocytosis pathway, which is consistent with the reported function of the C9orf72 protein in vesicle trafficking. Furthermore, we detected a module enriched for vesicular pathways, and additionally, we discovered an association with survival after onset for several promising candidates involved in vesicular transport. To find new therapeutic targets and biomarkers, here we have completed RNA-Seq on an increased number of samples to examine another relevant region: the cerebellum. As such, we performed RNA-Seq on a well-characterized cohort of C9orf72 expansion carriers, patients without this expansion, and control subjects without neurological diseases. We used multivariable linear regression models for gene-level analysis, weighted correlation network analysis for module-level analysis, and leafcutter for splicing analysis. Using the cerebellar RNA-Seq data, we found a large number (>6,000) of differentially expressed genes, with a notable increase in expression of homeobox genes in C9orf72 expansion carriers, as well as many gene modules that were associated with C9orf72 expansion status. Additionally, using leafcutter, we detected over 1,000 differential splicing events and an increase in the number of cryptic splicing events in C9orf72 expansion carriers.

  Study phs003065

• 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

• Comprehensive molecular profiling of pulmonary pleomorphic carcinoma

  Information regarding the molecular features of pulmonary pleomorphic carcinoma (PPC) is insufficient. Here, we performed next-generation sequencing to determine the genomic and transcriptomic profiles of PPC. Whole exome sequencing (WES) of fresh-frozen tissue samples and target-capture sequencing of formalin-fixed-paraffin-embedded (FFPE) samples were performed. Fresh-frozen tissue samples and FFPE samples were subjected to WES and target-capture sequencing as normal control, respectively. Fresh-frozen tissue samples and 56 FFPE samples were subjected to RNA-seq.

  Study JGAS000297

• DDX50 Cooperates With STAU1 to Effect Stabilization of Pro-Differentiation RNAs

  This study was undertaken to determine the role of DDX50 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. DDX50, which was associated with STAU1, was found to promote epidermal differentiation and transcript stability using the methods of RNA-seq, CLIP-seq and DMS-MaP-seq.

  Study phs003766

• Single-Cell Sequencing of Genomic DNA, RNA, and ADT in CRISPR-Edited Cells

  CRAFTseq data containing multi-modal single-cell genomic DNA amplicon, cDNA and surface-protein from various primary cell types and cell lines, including human CD4 T cells, Jurkat cells, HH cells, Daudi cells and HEK293T cells. Cells were edited with CRISPR HDR or base editing. Also contains bulk RNA-seq data for edited human primary CD4 T cells and Daudi cells.

  Study phs004042

• Genetic and Epigenetic Screens in Primary Human T Cells Link Candidate Causal Autoimmune Variants to T Cell Networks

  We aimed to define the target genes and pathways in which autoimmune disease-associated genetic variants operate. We performed single cell-CRISPR-interference screens in primary human T cells and bulk RNA-seq on T cells containing CRISPRi and single gRNAs to assess how T cell regulatory regions containing autoimmune-associated genetic variants affect nearby gene expression and cellular programs.

  Study phs004072

• Solve-RD data - RNA Sequencing, ipatimup-oliveira_group samples

  Dataset EGAD00001012115

• 3' mRNA- sequencing bams

  This project stores bam files from 3'RNA-seq from oesophageal adenocarcinoma at different timepoints during neoadjuvant treatment (prior, during, post treatment), which were used to analyse evolutionary and phenotype dynamics in oesophageal adenocarcinoma. Samples were collected within the clinical MEMORI trial.

  Study EGAS50000000242

• Spatial atlas of human atherosclerosis highlights role of the microvasculature in disease

  Atherosclerosis is a pervasive contributor to ischemic heart disease and stroke. Despite the advance of lipid lowering-therapies and antihypertensive agents, the residual risk of an atherosclerotic event remains high and developing therapeutic strategies has proven challenging. This is due to the complexity of atherosclerosis with a spatial interplay of multiple cell types within the vascular wall. Here we generate an integrative high-resolution map of human atherosclerotic plaques combining single-cell RNA-seq from multiple studies and spatial transcriptomics data from 12 human specimens, with different stages of atherosclerosis. We show cell-type and atherosclerosis-specific expression changes and spatially constrained alterations in cell-cell communication. We highlight the possible recruitment of lymphocytes via ACKR1 endothelial cells of the vasa vasorum, the migration of vascular smooth muscle cells towards the lumen by transforming into fibromyocytes, and cell-cell communication in the plaque region, indicating an intricate cellular interplay within the adventitia and the subendothelial space in human atherosclerosis.

  Study EGAS50000000660

• Spatial Transcriptomics Uncovers Tumor Microenvironment-Based Subtypes in Invasive Lobular Carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer (BC); however, little is known about its tumor microenvironment (TME). Here, we investigated the spatial architecture of 43 hormone-receptor-positive, HER2-negative (HR+/HER2-) primary ILC samples, using spatial transcriptomics and detailed morphological annotation. By integrating morphology, spatial, and single-cell data, we mapped TME-related cell types, exploring their proximity to tumor cells and their enrichment in specific compartments. Clustering of spatial transcriptomics spots revealed significant inter- and intra-tumor heterogeneity, identifying pathways and cell types linked with disease outcomes. Morphological and gene expression data were finally integrated with a multimodal approach, leading to the identification of 4 new ILC subtypes based on TME heterogeneity. By using derived, specific gene expression signatures, these subtypes were identified and validated in external bulk RNA-seq/microarray datasets (SCAN-B and METABRIC), where differences in prognosis emerged.

  Study EGAS50000001001

• Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution

  Ischemia reperfusion is an unavoidable step of organ transplantation. Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from six human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single cell RNA sequencing. Donor and recipient origin of cells from the reperfusion timepoint were deconvolved. Gene expression profiles were (1) compared between each donor cell type between timepoints and (2) compared between donor and recipient cells. Inflammatory responses from donor lung macrophages were found after reperfusion with upregulation of multiple cytokines and chemokines, especially IL-1 and IL-1. Significant inflammatory responses were found in alveolar epithelial cells (featured by CXCL8) and lung endothelial cells (featured by IL-6 upregulation). Different inflammatory responses were noted between donor and recipient monocytes and CD8+ T cells. The inflammatory signals and differences between donor and recipient cells observed provide insight into the cellular and molecular mechanisms of ischemia reperfusion induced lung injury. Further investigations may lead to the development of novel targeted therapeutics.

  Study EGAS50000000490

• Pseudogene RNAseq

  RNA sequencing to validate findings of somatic pseudogenes acquired during cancer development

  Dataset EGAD00001000732

• Detection and genomic analysis of BRAF fusions in Juvenile Pilocytic Astrocytoma through the combination and integration of multi-omic data

  Juvenile Pilocytic Astrocytoma (JPAs) are highly vascular tumors and show pervasive immune infiltration, which can lead to low tumor cell purity in clinical samples. In some instances, this results in gene fusions that are difficult to detect with conventional omics approaches including RNA-Seq. To this effect, we applied RNA-Seq as well as linked-read whole-genome sequencing and in situ Hi-C as new approaches to detect and characterize low-frequency gene fusions at the genomic, transcriptomic and spatial level. Overall, we demonstrate the power of integrating multi-omic datasets to identify low frequency fusions and characterize the JPA genome at high resolution.

  Study EGAS00001006388

• Genomic-Enabled Medicine for Recurrent Glioblastoma

  In this prospective study, we performed genome-wide tumor/normal exome sequencing and tumor RNA-sequencing for recurrent glioblastoma patients. A subset of patients had both enhancing tumor and non-enhancing tissue sequenced to investigate spatial heterogeneity of this disease. Together, this information builds our understanding of the genomic underpinnings of glioblastoma, and contributes toward the knowledge base for identifying and developing more effective treatments for patients with glioblastoma.

  Study phs001460

• Mate-pair sequencing of 12q-amplified osteosarcomas

  Mate-pair sequencing of 12q-amplified osteosarcomas for the detection of structural variants. This was carried out in order to study the structure of the chromosome 12q-amplicons and whether material from other chromosomes is also intertwined and amplified in a bid to further characterise these tumours beyond CDK4 and MDM2 amplification. Mate-pair data was also used to verify gene fusions detected with RNA-seq.

  Study EGAS50000000493

• 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

• Multiomics Characterization of Low-grade Serous Ovarian Carcinoma

  Low-grade serous ovarian carcinoma (LGSOC) is a rare tumor subtype with high case fatality rates. There is a pressing need to develop effective treatments using newly available preclinical models for therapeutic discovery and drug evaluation. In this study, we use multiomics integration of whole exome sequencing, RNA sequencing, and mass spectrometry-based proteomics on fourteen LGSOC patient derived cell lines to elucidate novel biomarkers and therapeutic vulnerabilities.

  Study EGAS00001004724

• DLBCL NGS Genomic Datasets of non-China cohort from Phoenix Clinical Trial

  Study biopsies (n=773; 189 cases as China cohort and 584 cases as non-China cohort) underwent whole exome sequencing or targeted gene panel DNA sequencing and RNA sequencing, allowing the identification of somatic mutations. Tumors were assigned to DLBCL genetic subtypes as the MCD (n=110), BN2 (n=47) or N1 (n=28) using the LymphGen algorithm based on their somatically mutated genes. In younger patients (age≤60), ibrutinib plus R-CHOP was associated with a 100% event free survival (EFS) at 3-years in the MCD and N1 groups, whereas R-CHOP alone was associated with a 3-year EFS of 42.9% (p=0.01) and 50% (p=0.016) in the MCD and N1 groups, respectively. This analysis showed a benefit of ibrutinib with R-CHOP chemotherapy in particular genetic subtypes, providing mechanistic support for its survival benefit in younger patients with non-GCB DLBCL. The EGA collects RNA-Seq and NuGene targeted sequencing datasets of 584 cases for non-China cohort.

  Study EGAS00001005554

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482