14976 results for "cancer studies using rna-seq"

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• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from Depression individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000044

• Dataset for other_cancer-RNA

  Rare cancer sequencing data of 95 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008847

• comparing the snRNA-seq from placentas of mothers with or without obesity

  Obesity poses risks to maternal health and increases the likelihood of short- and long-term adverse pregnancy outcomes in the offspring. The placenta, a key organ at the maternal-fetal interface, responds to maternal obesity and regulates fetal growth. To investigate the molecular features of physiological adaptation, we perform single-nuclei RNA-seq on human placentas and compared the transcriptomic profiles of women with obesity delivering appropriate- or large-for-gestational age (i.e., AGA and LGA) babies with those from normal-weight healthy controls with AGA babies. The snRNA-seq libraries were generated with Chromium Single Cell 3’ kit v3.1 (10X Genomics) and sequenced on Illumina NovaSeq 6000 at Novogene.

  Study EGAS50000000834

• Elucidation of the association between viruses and autoimmune diseases and COVID-19

  We determined the presence or absence of endogenous herpesvirus 6 (eHHV-6) and calculated annelovirus levels from whole genome sequencing of 2,238 patients with autoimmune diseases and 2,919 controls. We performed genome-wide association analysis using WGS of 22 eHHV-6B-positive cases and -negative cases. Single-cell RNA sequencing was performed using human peripheral blood mononuclear cells from 3 eHHV-6B-positive SLE patients and 5 -negative SLE patients.

  Study JGAS000741

• Bone morphogenetic protein-9 controls pulmonary vascular growth and remodeling

  Human PMECs from 10 donor lungs were isolated, cultured (passages 3 to 4), synchronized by serum starvation (0.3% FCS), and stimulated with 10 ng/mL BMP-9 for 4 h. Single-cell profiling was performed using the 10X Genomics Chromium RNA 3' V3.1 kit. Five experimental groups were analyzed using cell hashing and sequenced on an Illumina NextSeq500. Data were processed with Cell Ranger and Seurat for differential gene expression and functional enrichment analysis.

  Study EGAS50000001026

• RNA sequencing of Ewing sarcoma and CIC-DUX4 sarcoma

  RNA sequencing of a collection of 6 Ewing sarcoma and 3 CIC-DUX4 sarcoma tumoroids plus 3 matched patient tumors. Tumoroids were established from digested patient tumor material as 3D culture in Matrigel. After 2-3 month of growth, RNA was isolated from individual tumoroid models using the RNeasy Kit (Qiagen) and used for whole exome sequencing. RNA from corresponding patient tumors was tested in parallel, if available.

  Dataset EGAD50000000557

• MiRNome_pituitary_adenoma

  Small RNA (<100 bases in length) were purified from total RNA using miRNeasy kit (Qiagen), then sequenced. Libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq small RNA protocol (Illumina), starting from 1 µg of high quality total RNA. Single read (1 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on miRBase v.2052, then counted with STAR (v.2.5.2a).

  Dataset EGAD00001004998

• WGS and WTS data of patients diagnosed with MEITL.

  WGS from 4 patients, WTS from only 3 patients (insufficient tissue from 4th patient for WTS). Whole-genome sequencing (WGS) was performed for 60 pairs of tumor-normal samples from patients diagnosed with NKTL. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 2000. Whole-transcriptome sequencing (WTS): 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 Illumina HiSeq 2500 with 2x101 bp read length. Description of prefix used in filenames: T: Tumor samples N: Normal samples (Blood) P: PDX samples

  Dataset EGAD00001005341

• Discordant_Monozygotic_Twins_ALS(Transcriptomics)

  Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by motor neuron degeneration. Despite known genetic contributions to both familial and sporadic ALS cases, much of ALS heritability remains unexplained, suggesting the involvement of other genetic and epigenetic factors. To address this gap, we used a comprehensive multi-omics approach, in a pair of Italian monozygotic twins discordant for ALS, integrating DNA methylation, transcriptomics, and whole exome sequencing (WES). Here we share transcriptomic data derived from bulk RNA-seq on RNA extracted from PBMCs of the twin pair. This analysis revealed distinct transcriptomic profiles underlying the discordant disease phenotypes.

  Study EGAS50000000909

• Shallow whole genome sequencing of ctDNA samples from DETECT study

  A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival from the paper "A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival", by Beddowes et al. Mol.Onc.

  Study EGAS50000000911

• MIBC NAC2020 cohort RNA sequencing

  The dataset contains RNA sequencing data from N=48 transurethral resections of bladder tumours (TURBTs) from N=48 patients with muscle-invasive bladder cancer. All TURBTs originate from formalin-fixed paraffin embedded tissue. We used the Illumina TruSeq RNA exome kit, previously known as the TruSeq RNA Access Library Prep Kit. This kit converts total RNA into template molecules of known strand origin, followed by sequence-specific capture of coding RNA. All samples were run in an Illumina NovaSeq6000 instrument. Paired FASTQ files from all 48 patients are provided.

  Study EGAS50000000741

• Subtype specific progression from DCIS to invasive breast cancer

  Breast cancer consists of at least five main molecular “intrinsic” subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.

  Study EGAS00001001866

• Feasibility and safety of a multi-cancer blood test for screening and intervention

  We evaluated the feasibility and safety of blood testing for cancer in an interventional study of 10,006 women. Positive tests for DNA or protein were independently confirmed and diagnostic PET-CT imaging was used to localize disease. During the study, 26 cancers were first detected by blood testing, 24 more by standard-of-care screening, and 46 by neither approach. Surgicalexcision of the primary tumors was performed on 12 cancers first detected by blood testing.1.0% of participants underwent PET-CT imaging based on false positive blood tests, and 0.22% underwent a futile invasive diagnostic procedure. These data demonstrate that multi-cancer blood testing, when followed by PET-CT localization, can be safely incorporated into routineclinical care, in some cases leading to surgery with intent to cure. Further studies will be required to determine the clinical validity and utility of multi-cancer blood testing.

  Study EGAS00001004372

• Transcriptome analysis of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A (H3N2) virus.

  Transcriptome analysis of influenza A (H3N2) human challenge samples. Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Study EGAS50000000679

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• Transcriptome - Uveal Melanomas

  Total RNA sequencing on 9 uveal melanomas. Libraries were prepared using the TruSeq Stranded Total RNA Library Prep Gold (Illumina, 20020599). Paired-end libraries (2 x 100 bp) were sequenced on a NovaSeq 6000 instrument (Illumina).

  Dataset EGAD50000000763

• Single cell RNA-sequencing of glioblastoma tumours

  Single cell RNA-sequencing of fresh glioblastoma tumor biopsies with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome using CellRanger.

  Dataset EGAD00001006803

• Spatial transcriptomic data of breast cancer

  Fastq files from spatial transcriptomic of breast cancer coming from 8 Breast cancer sections. Sample preparation: frozen BC samples were chosen based on tissue structure and RNA quality (RIN > 8). The “Visium Spatial Tissue Optimization Slide and Reagent Kit” (10X Genomics; #PN-1000193) was then used to optimize permeabilization conditions for BC tissues. Briefly, sections were fixed, stained and then permeabilized at different time points to capture mRNA, and the reverse transcription was performed to generate fluorescently labeled cDNA. The permeabilization time that resulted in the highest fluorescence signal with the lowest background diffusion was chosen. The best permeabilization time for BC tissue was 18 min. Cryostat sections of 10 μm of thickness were cut and placed on Visium Spatial Gene Expression slides (10X Genomics, PN-1000184). The slide was incubated for 1 min at 37°C, then fixed with methanol for 30 min at -20°C followed by Hematoxylin and Eosin (H&E) staining and images were taken under a high-resolution microscope. After imaging, the coverslip was detached by holding the slide in water and the slide was mounted in a plastic slide cassette. The spatial gene expression process, including tissue permeabilization, second strand synthesis and cDNA amplification, was performed according to the manufacturer’s instructions (10X Genomics; #CG000239). cDNA quality was next assessed using Agilent High sensitivity DNA Kit (Agilent, #5067-4626). The spatial gene libraries were constructed using Visium Spatial Library Construction Kit (10X Genomics, PN-1000184).

  Dataset EGAD50000000322

• Immune Responses in Checkpoint Myocarditis Across Heart, Blood, and Tumor

  Immune checkpoint inhibitors (ICIs) are widely used in anti-cancer therapies, but they can cause morbid and potentially fatal immune-related adverse events (irAEs), such as ICI-related myocarditis (irMyocarditis). The pathogenesis of irMyocarditis and its relationship to anti-tumor immunity remain poorly understood. We sought to define immune responses in heart, tumor, and blood in irMyocarditis patients and controls by leveraging single‐cell RNA sequencing (scRNA‐seq) coupled with T-cell Receptor Sequencing (TCR-Seq). Our analysis demonstrated increased frequencies of cytotoxic T cells, inflammatory mononuclear phagocytes (MNPs), conventional dendritic cells (cDCs), and inflammatory fibroblasts in irMyocarditis heart tissue. Additionally, we revealed decreased frequencies of plasmacytoid dendritic cells, cDCs, and B lineage cells but an increased frequency of MNPs in the blood of irMyocarditis patients. Raw data for heart and blood can be found in dbGaP. All processed data and raw TCRseq data from heart tissue and tumor samples for this study can be found in GEO (Accession number GSE228597).Subject IDs with the prefix "SIC" were collected by the Severe Immunotherapy Complications (SIC) service at MGH due to suspicion of immune-related adverse events. Subject IDs with the prefix "donor" were collected by the MGH Melanoma Biobank at scheduled timepoints; this biobank systematically collects samples from patients at MGH at clinically relevant timepoints.

  Study phs003413

• scRNAseq of colonic organoids derived from biopsies taken from healthy human individuals treated with IL22

  scRNAseq dataset of colonic organoids derived from epithelium from biopsies taken from three healthy human individuals. The organoids have either been grown in standard conditions (control) or treated with IL22 (treated). Includes 6 samples in total, one control from each individual (ctrl1, ctrl2, ctrl3) and one treated from each (treat1, treat2, treat3). The samples have been multiplexed using the antibody hashing technique. The 6 samples have been pooled into the one organoids sample. In order to analyse the raw files, they have to be demultiplexed first. Information necessary for demultiplexing, as well as which files belong to which sample, can be found in the map_file.csv, attached to each sample. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into HTO (hashtag) and RNA (transcriptome) files. HTO has one index (I1) and two read (R1, R2) files and RNA has two index (I1, I2) and two read (R1, R2) files. The fastq files are for the pooled (organoids) sample and need to be demultiplexed. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Since count matrices have been created after the demultiplexing step, there’s one matrix for each of the 6 individual samples. scRNA-seq data from human colon organoids was analysed in the same manner as for the Colitis dataset, apart from the following changes. Data was generated with the Cell Hashing technique, which uses oligo-tagged antibodies against surface proteins to barcode single cells. This allows for samples to be multiplexed together and run in a single experiment. The data was demultiplexed using the HTODemux() function from Seurat (Hao et al., 2021).

  Dataset EGAD00001010168

• Whole scRNA-seq from pre frontal cortex patient biopsy

  The single- cell RNA-seq prefrontal cortex sample was selected from a cohort of patients with hydrocephalus ≥18 years of age planning to undergo CSF diversion surgery either with a ventriculoperitoneal shunt placement (VP) or ventriculocisternostomy (VCS). The tissue was dissociated followed by red cell and debris removal and counting of the cells to be sequenced with (scRNA-seq; 10x Genomics kit v2). After dissociation only non neuronal cells were retrieved.

  Dataset EGAD50000001542

• Multiplexed scRNA-Seq Reveals Cellular and Genetic Correlates of SLE

  Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and cell states associated with SLE remains incomplete. We profiled over 1.2 million PBMCs (160 cases, 98 controls) with multiplexed single-cell RNA-seq (mux-seq). Cases exhibited prominent expression of type-1 interferon-stimulated genes (ISG) in monocytes, reduction of naïve CD4+ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH+ CD8+ T cells. Cell-type-specific expression features accurately predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data, mapping cell-type-specific cis-eQTLs and linked known and novel SLE-associated variants to cell-type-specific gene expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.

  Study phs002812

• G&T-seq: parallel sequencing of the genomes and transcriptomes of single cells

  The ability to simultaneously sequence the genome and transcriptome of the same single cell offersa powerful means to dissect functional genetic heterogeneity at the cellular level. Here we describeG&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from singlecells. By applying G&T-seq to over 220 single cells we reveal cellular properties that cannot beinferred from DNA or RNA sequencing alone, including associations between DNA copy numbervariation and gene expression dosage. We further demonstrate the detection of coding interchromosomalfusions and single nucleotide variants in both the genomes and transcriptomes ofindividual cells. G&T-seq enables the study of genotype-phenotype associations in single cells, andthe investigation of DNA cell lineage trees of healthy and diseased tissues with transcriptome inferredcell types and states.

  Study EGAS00001001204

• RNA sequencing of a glioblastoma PDX cohort

  Patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In this project, we molecularly characterized a comprehensive panel of glioma PDX models with well conserved molecular and pathological features over multiple passages. PDX samples were subjected to next generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in glioblastoma. In summary, we reported a newly established and molecularly characterized panel of glioma PDX models with high relevance for translational preclinical research.

  Study EGAS00001007119

• Linking genes, genomic instability and molecular subgroups in medulloblastoma

  Brain tumors are the second most common pediatric cancer and carry the highest mortality rates in this age group. Medulloblastoma is the most frequent malignant brain tumor of childhood. Recent studies indicate that medulloblastoma comprises at least four sub-entities (SHH-signaling, WNT-signaling, Group-C, Group-D) that differ in molecular alterations, cell of origin, clinicopathological features and outcome. Further characterization of the entire spectrum of genomic alterations underlying the formation of these distinct groups is urgently needed to identify diagnostic and prognostic biomarkers for clinical management and uncover novel therapeutic targets.

  Study EGAS00001000085