15041 results for "cancer studies using rna-seq"

in 33.46 milliseconds.

• RNA-seq dataset of Neoantigen Peptides derived from V(D)J-recombined Immunoglobulins Drive Outgrowth of Cytolytic CD8+ T-cells

  RNA-seq dataset of Neoantigen Peptides derived from V(D)J-recombined Immunoglobulins Drive Outgrowth of Cytolytic CD8+ T-cells

  Dataset EGAD00001015647

• Bulk and RIP-seq transcriptome datasets from skin fibroblasts in PTBP1- and PTBP2-related disorders

  PTBP1- and PTBP2-related disorders are rare human conditions that cause variable neurodevelopmental phenotypes, including intellectual disability and behavioral problems such as autism spectrum disorder, anxiety, aggressiveness, and attention disorders, with or without hyperactivity. PTBP1-related disorder is also associated with skeletal dysplasia. In this study, we generated bulk RNA sequencing and RNA immunoprecipitation sequencing (RIP-seq) data from skin fibroblasts obtained from patients and healthy controls.

  Study EGAS50000001210

• The Molecular Landscape of Asian Breast Cancers Reveals Clinically Relevant Population-Specific Differences

  Molecular profiles of breast cancer have contributed to an improved understanding of the disease, enabled development of molecular prognostic signatures to guide treatment decisions and unveiled new or more accurate therapeutic options for breast cancer patients. However, the extent to which differences in genetic, environmental and lifestyle factors influence molecular profiles in different populations remains poorly characterised, as relatively few large-scale molecular studies of breast tumours in non-Caucasian populations have hitherto been reported. Here, we present the molecular profiles of 560 Asian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to the breast tumours in predominantly Caucasian women reported in TCGA and METABRIC, we show an increased prevalence of Her2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. Using gene expression and immunohistochemistry, we observed elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst Her2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil new opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

  Study EGAS00001004518

• Label-free single-cell RNA Multiplexing leveraging Genetic Variability

  SNP-based demultiplexing of single-cell RNA-seq data

  Dataset EGAD50000000928

• RNA-seq analysis of CCO+/CCO- hepatocytes in normal human liver

  RNAseq data from Passman et al 2023. Clonal CCO-deficient hepatocyte patches and nearby CCO-proficient hepatocytes were identified in morphologically normal human livers and sampled at varying distances along the PT-CV axis. Samples are characterised according to their location within the liver lobule, with "PT" denoting samples abutting the portal triad, "CV" denoting samples abutting the central hepatic vein, and "Mid" sampled acquired midway between these structures. Analysis was performed on an Illumina Nextseq using a high output kit and 100 single-end cycles.

  Dataset EGAD00001010033

• Oxford Nanopore RNA sequencing for HLA typing

  A targeted RNA-based method for typing of 12 classical HLA genes using Oxford Nanopore sequencing. In the method, were enriched HLA genes from cDNA of 50 individuals using gene-specific reverse primers. The library molecules were then barcoded, pooled into 2 separate gene pools, and sequenced on MinION R9.4 SpotON flow cells.

  Study EGAS00001004918

• DS-ALL RNA-Seq DAC

  Dac EGAC00001002866

• Melanoma RNA Seq Data commitee

  Dac EGAC00001002928

• Single cell RNA-seq aging

  Dac EGAC00001001502

• Clinical Sequencing Exploratory Research Consortium: Incorporation of Genomic Sequencing into Pediatric Cancer Care

  This project includes data derived from subjects enrolled in the BASIC3 (Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care) study. BASIC3 is a National Genome Human Research Institute (NHGRI) and National Cancer Institute-funded Clinical Sequencing Exploratory Research (CSER) consortium project that focused on prospective implementation of clinical whole exome sequencing in the pediatric oncology clinic. The primary study objective were to integrate information from CLIA-certified germline and tumor exome sequencing into the care of newly diagnosed solid tumor patients at Texas Children's Cancer Center, and to perform parallel evaluation of the impact of tumor and germline exomes on families and physicians. Blood and frozen tumor (if available) samples were collected from children undergoing surgery or biopsy of newly diagnosed solid tumors and subjected to exome sequencing in a CLIA-certified laboratory. Germline and tumor (if applicable) exome sequencing reports were generated and submitted into the electronic health record and returned to each patient/family by their primary oncologist. In addition to the clinical exome sequencing, specific (optional) consent was requested for research sequencing studies. If this consent was obtained then research studies of some of the children and parents participating in the BASIC3 study (including tumor transcriptome and whole genome sequencing of blood and/or tumor) are performed. The Clinical Sequencing Exploratory Research Consortium Cohort is utilized in the following dbGaP sub-study. To view molecular data, and derived variables collected in this sub-study, please click on the following sub-studies below or in the "Sub-study" section of this top-level study page phs001383 Clinical Sequencing Exploratory Research Consortium Cohort. phs001026 BASIC3 phs001878 GMKF BASIC3

  Study phs001683

• Whole genome and RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  Paediatric glioblastoma (pedGBM) is characterised by substantial intertumoural heterogeneity. In order to identify the genetic lesions underlying tumourigenesis, we analysed whole genomes and transcriptomes of pedGBMs and in vitro model systems by next generation sequencing. Novel fusions of the receptor tyrosine kinase MET lead us to investigate targeted therapy using MET inhibitors. This study is part of the International Cancer Genome Consortium PedBrain Tumor Project (ICGC PedBrain, http://www.pedbraintumor.org/).

  Study EGAS00001001139

• Whole-exome sequencing of human pancreatic cancers and characterization of genomic instability caused by MLH1 haploinsufficiency and complete deficiency

  Whole-exome sequencing (Exome-Seq) has been successfully applied in several recent studies. We here performed Exome-Seq of 15 pancreatic tumor-normal pairs. We captured 162,073 exons of 16,954 genes and sequenced the targeted regions to a mean coverage of 56 folds. This study identified a total of 1,517 somatic mutations and validated 934 of them by transcriptome sequencing. We detected recurrent mutations in 56 genes. Among them, 41 have not been described. The mutation rates varied widely among tumors. The diversity of mutation rates was significantly correlated with the distinct MLH1 copy-number status. Exome-Seq revealed intensive genomic instability in a tumor with MLH1 homozygous deletion, indicated by a dramatically elevated mutation rate of somatic substitutions, small insertions/deletions (indels), as well as indels presented at microsatellites. Notably, we detected MLH1 allelic loss in 4 tumors. MLH1 expression was decreased by nearly half in these cases. While they were negative in the conventional microsatellite instability assay, they showed a 10.5-fold increase in the mutation rate of somatic indels, e.g. truncating indels in TP53 and TGFBR2, indicating MLH1 haploinsufficiency in correction of DNA indel errors. We further analyzed the exomes of 15 renal cell carcinomas (RCCs) and confirmed MLH1 haploinsufficiency. We observed a significant increase in the mutation rate of somatic indels in affected cases and identified recurrent truncating indels in several cancer genes such as VHL, PBRM1 and JARID1C. Together, our data suggest that MLH1 hemizygous deletion, through increasing the mutation rate of somatic indels, could drive the development and progression of sporadic cancers.

  Study EGAS00001000149

• Coding and non-coding drivers of mantle cell lymphoma identified through exome and genome sequencing

  Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent non-coding mutations surrounding a single exon of the HNRNPH1 gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent non-coding mutations in disrupting an auto-regulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly implicate a role for aberrant regulation of mRNA processing in MCL pathobiology.

  Study EGAS00001004289

• Dataset for bone_cancer-RNA

  Rare cancer sequencing data of 55 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008848

• Dataset for breast_cancer-RNA

  Rare cancer sequencing data of 59 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008850

• Dataset for GIST-RNA

  Rare cancer sequencing data of 50 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008852

• Single-cell RNA-Seq of human lymphoma reveals malignant B cell diversity and patterns of T cell immune checkpoint co-expression

  Follicular lymphoma (FL) is a generally incurable B-cell malignancy which has the potential to transform into highly aggressive lymphomas. Genomic studies indicate it is often a small subpopulation rather than the dominant population in the FL that gives rise to the more aggressive subtype. To resolve the underlying transcriptional networks of follicular B-cell lymphomas at single molecule and cell resolution, we leveraged droplet-based barcoding technology for highly parallel single cell RNA-Seq. We analyzed the transcriptomes from tens of thousands of cells derived from five primary FL tumors. Simultaneously, we conducted multi-dimensional flow cell sorting to validate our characterizing of cellular lineages and critical expressed proteins. For each tumor, we identified multiple cellular subpopulations, matching known hematopoietic lineages. Comparison of gene expression by matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin light chain expression (either Ig Kappa or Ig Lambda), as well the expected upregulation of the BCL2 gene, but also down-regulation of the FCER2, CD52 and MHC class II genes. By leveraging the single-cell resolution on large numbers of cells per patient, we were able to examine tumor-resident T cells. We identified pairs of immune checkpoint molecules that were co-expressed, providing a potentially useful strategy for selection of patient-tailored combination immunotherapies. In summary, massively parallel measurement of single-cell expression in thousands of tumor cells and tumor-resident lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.

  Study phs001378

• RNA sequencing in primary inflammatory (TPP) macrophages following deletion of a disease-associated gene desert at chr21q22, disruption of ETS2, or treatment of ETS2-edited macrophages with a HIF1α stabiliser.

  GWAS studies in five different inflammatory diseases have identified a strong genetic association at a gene desert at the chr21q22 locus. We have shown that this locus contains a monocyte/macrophage-specific enhancer that regulates ETS2 - a gene whose role in primary human monocytes/macrophages is incompletely understood. We therefore used a CRISPR-Cas9-based approach to delete the enhancer region or to disrupt ETS2, and performed RNA-sequencing to examine the transcriptional consequences. One effect of ETS2 disruption was upregulation of genes involved in aerobic respiration and oxidative phosphorylation. We therefore treated ETS2-edited inflammatory macrophages with roxadustat, a HIF1α stabiliser that can promote glycolysis via HIF1α-mediated metabolic reprogramming, and performed RNA-sequencing to determine whether this drug might rescue the transcriptional effects of ETS2 disruption.

  Study EGAS00001007553

• Association studies using the Metabochip array - Samples analysed by the WTCCC (1958 British Birth Cohort (58BC), Hypertension cohort (HT), Type 2 Diabetes Cohort (T2D) and Coronary Artery Disease (CAD) cohort)

  Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify common disease-associated variants. Even quite large GWAS, however, have only at best identified moderate proportions of the genetic variants contributing to disease heritability. To provide cost-effective genotyping of common and rare variants to map the remaining heritability and to fine-map established loci, the Metabochip Consortium has developed a 200,000 SNP chip that has been produced in very large numbers for a fraction of the cost of GWAS chips. This chip provides a powerful tool for genetic studies of metabolic, cardiovascular and anthropometric traits (Voight et al., in press PLoS Genetics).

  Study EGAS00000000115

• The Library of Integrated Network-Based Cellular Signatures (LINCS) - NeuroLINCS

  The NeuroLINCS Center is part of the NIH Common Fund's Library of Integrated Network-based Cellular Signatures (LINCS) program, which aims to characterize how a variety of human cells, tissues and the entire organism respond to perturbations by drugs and other molecular factors. As Part of the LINCS program, the NeuroLINCS study concentrates on human brain cells, which are far less understood than other cells in the body. Our initial focus is to produce diseased motor neurons from patients by utilizing high-quality induced pluripotent stem cell (iPSC) lines from Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA) patients in addition to unaffected normal healthy controls. Using state-of-the-art OMICS methods (genomics, epigenomics, transcriptomics, and proteomics), we intend to create a wealth of cellular data that is patient-specific in the context of their baseline genetic perturbations and in the presence of other genetic and environmental perturbagens (e.g. endoplasmic reticulum stress). The primary data will be used to build cell signatures that convey the key features that distinguish the state of a cell and determine its behavior. Ultimately, the analysis of these datasets will lead to the identification of a network of unique signatures relevant to each of these motor neuron diseases. The datasets represented in this study are generated from assays interrogating RNA expression (RNA-seq), chromatin accessibility (ATAC-seq) and whole genome sequencing.

  Study phs001231

• UCL COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of COVID19 patients recruited from University College London. Data represent RNA-seq, surface protein measurements (CITE-seq) of 192 antibody targets, along with VDJ-seq profiling of single T cell and B cell receptors. Samples are pooled, with 4 donors per pool. Germ-line genotypes derived from previous single-cell RNA-sequencing are provided (VCF) to aid demultiplexing of single-cell and assignment to specific patient donor samples.

  Dataset EGAD00001007865

• PE-CGS: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization Studies

  Colorectal Cancer (CRC) is the second leading cause of cancer death in the US. Hispanic/Latinos (H/L) are the largest and fasting growing ethnic group in the US, and cancer is the leading cause of death among H/L in the US. Therefore, we need to fully understand the full complexity of the molecular etiology of cancer in this ethnic group. For instance, although incidence rates of CRC are lower among Latinos as compared to Whites or African Americans, Hispanics with metastatic disease have shorter overall survival when adjusted for health care setting, demographics, disease characteristics and treatment factors. H/L also tend to be diagnosed at a younger age and with higher stage, and we have previously reported that Mexican H/L in California have the greatest proportion of young (The Cancer Genome Atlas has provided a deep overview of the molecular taxonomy of CRC in 594 cases, however, less than 1% of the cases (n=5) were H/L. Therefore, it is imperative for us to take more detailed assessment of the molecular genomic landscape of CRC in H/L. One of the major issues likely limiting our ability to perform these large genomic initiatives in minority patients is that Patient or Participant Engagement practices may not be investigated to identify best practices for accruing and consenting patients into clinical translational biomedical research studies. This concept of Participant Engagement is critically important for both the patients and the translational cancer research community. Optimizing and improving our approaches for directly engaging patients at initial contact, throughout the course of a translational genomic study, and during the time of return of results is likely to lead to stronger relationships between the medical community and patients, but could also lead to significant improvement in outcomes for patients and for the cancer care community as a whole. As such, we propose the creation of the USC Center for Optimization of Participant Engagement in Cancer Characterization (COPECC) with a focus on optimizing the engagement of Latinos in CRC Genomic Characterization research studies. USC COPECC would serve as a member of the NCI U2C Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Our investigative team includes experts in all relevant areas of research for genomic characterization, participant engagement, and engagement optimization. We have an established platform for consenting patients into cancer genomics studies that will serve as a standard process. The overall goal of USC COPECC is to generate results on participant engagement optimization and CRC genomic research that will be shared with the broader community to distribute best practices for engaging Latinos in hopes of improving overall outcomes for CRC in this underserved population.

  Study phs003985

• RNA-seq of non-LPS treated (N), non-tolerized (NT), and tolerized (T) IFNg-primed macrophages pretreated with or without HDAC3i

  In this experiment we investigated the effect of HDAC3 inhibition on the transcriptome of IFNg-primed macrophages under different tolerization conditions. Peripheral blood mononuclear cells (PBMCs) were isolated from 3 healthy donors. PBMCs were isolated from whole blood of healthy donors using Ficoll gradient (Invitrogen). Monocytes (CD14+ cells) were positively selected from PBMCs using CD14 Microbeads according to the manufacturer’s instructions (Miltenyi Biotec). Monocytes were subsequently treated with or without 500 nM HDAC3i (ITF3100) for 30 minutes prior to overnight IFNg priming (50 ng/mL). Cells were then kept without LPS (non-LPS; N), treated with 10 ng/mL LPS once (non-tolerized; NT), or treated with LPS twice (tolerized; T; second LPS concentration: 100 ng/mL). In total, there were 18 samples included.

  Dataset EGAD00001005959

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Study EGAS00001005530

• CARE iSGS single nucleus RNA-seq

  This study contains single nucleus RNA-sequencing data from healthy controls, iSGS, and traumatic subglottic stenosis patients.

  Study EGAS50000000878

• Cancer-associated fibroblasts promote drug resistance in ALK-driven lung adenocarcinoma cells by upregulating lipid biosynthesis

  Targeted therapy interventions using tyrosine kinase inhibitors (TKIs) provide encouraging treatment responses in ALK-rearranged lung adenocarcinomas, yet resistances occur almost inevitably. Apart from tumor cell-intrinsic resistance mechanisms, accumulating evidence supports a role of cancer-associated fibroblasts (CAFs) in affecting the therapeutic vulnerability of lung cancer cells. Here, we aimed to investigate underlying molecular networks shaping the therapeutic susceptibility of ALK-driven lung adenocarcinoma cells via tumor microenvironmental cues using three-dimensional (3D) spheroid co-culture settings. We show that CAFs promote therapy resistance of lung tumor cells against ALK inhibition by reducing apoptotic cell death and increasing cell proliferation. Using single-cell RNA-sequencing analysis, we show that genes involved in lipogenesis constitute the major transcriptional difference between TKI-treated homo- and heterotypic lung tumor spheroids. CAF-conditioned medium and CAF-secreted factors HGF and NRG1 were both able to promote resistance of 3D-cultured ALK-rearranged lung tumor cells via AKT signaling, which was accompanied by enhanced de novo lipogenesis and supression of lipid peroxidation. Notably, simultaneous targeting of ALK and SREBP-1 was able to overcome the established CAF-driven lipid metabolic-supportive niche of TKI-resistant lung tumor spheroids. Our findings highlight a crucial role of CAFs in mediating ALK-TKI resistance via lipid metabolic reprogramming and suggest new ways to overcome resistance towards molecular directed drugs by targeting vulnerabilities downstream of oncogenic signaling.

  Study EGAS50000000135

• Single-cell Analysis of Neoplastic Plasma Cells Identifies Myeloma Pathobiology Mediators and Potential Targets

  Multiple myeloma is a clonal plasma cell (PC) dyscrasia that arises from precursors and has been studied utilizing approaches focused on CD138+ cells. By combining single-cell (sc)RNA- with scB-cell receptor (BCR)-sequencing, we differentiate monoclonal/neoplastic from polyclonal/normal PCs, and find more dysregulated genes, especially in precursor patients, than by analyzing bulk PCs. To determine if this approach can identify oncogenes that contribute to disease pathobiology, MAD2L1 and MAT2A are validated as targets with drug-like molecules that suppress myeloma growth in pre-clinical models. Moreover, functional studies show a role of LAMP5, which is uniquely expressed in neoplastic PCs, in tumor progression and aggressiveness via interactions with c-MYC. Finally, a monoclonal antibody recognizing cell-surface LAMP5 shows efficacy as an antibody-drug conjugate and in a chimeric antigen receptor-guided T-cell format. These studies provide additional insights into myeloma biology and identify potential targeted therapeutic approaches that can be applied to reverse myeloma progression.

  Study EGAS50000000802

• Genomic Analysis of Low Grade B-Cell Lymphoma

  We included tumors from 64 newly diagnosed or untreated Low Grade B-Cell Lymphoma (LGBCL) patients, consisting of SMZL (n = 48), NMZL (n = 6), EMZL (n = 2), LPL (n = 5), and B-NOS (n = 3) in this study. Samples were selected from cases consented to the Molecular Epidemiology Resource (MER) of the University of Iowa and Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). RNA or DNA were extracted from 64 frozen LGBCLs tumors (with available matched germline DNA for N=61. For RNA sequencing, library preparation was done using the Illumina TruSeq RNA Exome Kit and sequenced with 100 nucleotide paired-end reads using the HiSeq 4000. For WES, library preparation was done using the Agilent SureSelect XT kit and sequenced with 100 nucleotide paired-end reads using the Illumina HiSeq 4000.

  Study phs002552

• MDS-HSC-RNA-SEQ

  Dac EGAC00001000185

• utero-tubal lavage RNA seq DAC

  Dac EGAC00001002241

• GLASS-NL RNA-seq Data access committee

  Dac EGAC00001003470

• RNA sequencing

  For RNA sequencing: All sample numbers starting with 6717 are tumor samples which has been sequenced using transcriptomics (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata). RNA sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000383

• Identifying Novel Small RNA Biomarkers Unique to Patients with Gastric Cancer

  The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented. Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: 30097497 DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States).

  Study phs001767

• Etiologic Studies of Macular Degeneration

  This is a genotyping study of selected participants in an ongoing study of macular degeneration and related ocular disorders. DNA samples were obtained from 1985 (study initiation) to 2018. Phenotypes were determined using the validated Clinical Age-Related Maculopathy Grading System (Ophthalmol 2006, PMID 16458093).

  Study phs001896

• Single Cell RNA-Seq Reveals Malignant and Stromal Programs Associated with Metastasis in Head and Neck Cancer

  This study of head and neck cancer aimed to profile individual malignant, stromal, and immune cells in treatment-naive oral cavity squamous cell carcinoma, with or without matched metastatic cervical lymph nodes. Clinical and pathologic information was collected on all patients, in addition to a fresh biopsy sample from the primary tumor and/or metastatic lymph node at the time of initial surgery. Biopsy specimens were processed for single cell RNA-seq (scRNA-seq) and/or whole exome sequencing (WES). A total of ~6,000 single cells from 18 participants were included in the final dataset. Stromal and immune cells had consistent expression programs across patients. Conversely, malignant cells varied within and between tumors in their expression of signatures related to cell cycle, stress, hypoxia, epithelial differentiation, and partial epithelial-to-mesenchymal transition (p-EMT). One of the top scoring genes in this program was TGFβ-induced (TGFBI), implicating the classic EMT regulator TGFβ. Cells expressing the p-EMT program spatially localized to the leading edge of primary tumors. By integrating single-cell transcriptomes with bulk expression profiles for hundreds of tumors, we refined Head and Neck Squamous Cell Carcinoma (HNSCC) subtypes by their malignant and stromal composition, and established p-EMT as an independent predictor of nodal metastasis, grade, and adverse pathologic features. Our results provide insight into the HNSCC ecosystem and define stromal interactions and a p-EMT program associated with metastasis.

  Study phs001474

• WTS data of patients diagnosed with angiosarcoma

  Whole-transcriptome sequencing (WTS) of 6 tumor-normal and 6 tumor-only samples from patients diagnosed with angiosarcoma. Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on HiSeq 2500 and HiSeq 3000 (Illumina) with 2x101 bp and 2x151 bp read length, respectively.

  Dataset EGAD00001005367

• WTS data of patients diagnosed with NKTL

  Whole-transcriptome sequencing (WTS) of 36 samples from patients diagnosed with NKTL. Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on HiSeq 2500 and HiSeq 3000 (Illumina) with 2x101 bp and 2x151 bp read length, respectively.

  Dataset EGAD00001005230

• Genomic Sequencing of Lung Adenocarcinoma

  Lung carcinoma is the leading cause of cancer death in the United States and world-wide; lung adenocarcinoma is the most common cause of lung cancer. Pilot studies of lung adenocarcinoma with hybrid-capture based whole exome sequencing will enable us to identify new targets for therapy and improve diagnosis. We will analyze a blend of whole exome and whole genome sequencing data as well as copy number and somatic mutation calls for 200 tumor and matched normal controls. When completed this study will represent the most comprehensive lung adenocarcinoma genome dataset to date.

  Study phs000488

• Chronic lymphocytic leukemia patient-derived xenografts recapitulate clonal evolution to Richter transformation

  Whole-genome sequencing (WGS) and RNA-seq data from patient-derived xenografts (PDXs) obtained from CLL and RT primary samples as described in Playa-Albinyana et al.

  Study EGAS00001006965

• RNA-seq on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics

  RNA-sequencing on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics. Three samples from each of the treatment condition were analysed. Next-Seq platform was used for sequencing.

  Dataset EGAD00001007754

• PPGL RNA-Seq dataset

  Dataset includes fastq files for RNA-Seq experiments for tumor samples of PPGL patients. Single end reads fastq files are available for 102 different samples

  Dataset EGAD00001008578

• Paired RNA-Seq of Tumor Organoids from glioblastoma, 2 patients, treated with different small molecule inhibitors

  Tumor Organoids from glioblastoma, 2 patients, treated with different small molecule inhibitors. Paired RNA-Seq was done on NovaSeq 6000 with the Illumina TruSeq stranded mRNA Kit. The small inhibitors GW2580, BLZ945 and PLX3397 were used. DMSO was used as control.

  Dataset EGAD00001011274

• bulk RNA-Seq samples of CRC patients

  The dataset contains samples of 30 CRC patients (3 samples for each patient, tumor and 2 normal adjacent tissue sites, 90 samples in total). Dataset is composed by fastq file (paired end) type from bulk RNA-Seq.

  Dataset EGAD00001009635

• RNA-seq data of 370 high grade ovarian tumors from the ICON7 trial

  Collection of RNA-seq, Illumina, paired-end fastq files for 370 archival tissues from a subset of patients with high grade serous ovarian carcinoma enrolled in the phase 3 ICON7 trial. Clinical data and digital pathology information for CD8 is also available.

  Dataset EGAD00001004988

• Single-cell RNA-seq and spatial transcriptomics data of patients with sarcoidosis

  Single-cell RNA-seq and spatial transcriptomics data for 12 patients with sarcoidosis. From each patient, we analyzed skin biopsies of both lesional and non-lesional skin and we performed spatial transcriptomics for lesional skin samples. The data are provided as aligned BAM files.

  Dataset EGAD00001010020

• BLUEPRINT release August 2016, RNA-Seq for monocyte - T=0days, on genome GRCh38

  RNA-Seq data for 4 monocyte - T=0days sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002360

• BLUEPRINT release August 2015, RNA-Seq for plasma cell, on genome GRCh38

  RNA-Seq data for 4 plasma cell sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001523

• BLUEPRINT release August 2015, RNA-Seq for monocyte - None, on genome GRCh38

  RNA-Seq data for 4 monocyte - None sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001532

• BLUEPRINT release August 2016, RNA-Seq for monocyte - None, on genome GRCh38

  RNA-Seq data for 4 monocyte - None sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002338