12215 results for "cancer rna-seq"

in 166.99 milliseconds.

• Ex vivo RNA-seq in moderate COVID-19 monocytes

  This dataset was used to compare gene expression profiles of ex vivo isolated classical CD14+ monocytes from patients with moderate COVID-19 to those of healthy individuals. Blood samples were taken from patients with moderate COVID-19 admitted to hospitals in London (Hammersmith Hospital, Charing Cross Hospital, Saint Mary’s Hospital) 3-14 days after disease onset and 0-2 days after hospitalization and positive PCR, and before study treatment initiation. Moderate patients displayed mild or moderate COVID-19 pneumonia, defined as grade 3 or 4 WHO severity. Samples were collected from March 2020 to February 2021. Healthy donors were Imperial College staff with no prior diagnosis of or recent symptoms consistent with COVID-19, and where possible, were matched in age and sex distribution with COVID-19 patients. None of the participants of this study were COVID-19 vaccinated. Peripheral blood mononuclear cells (PBMCs) were isolated by Ficoll Hypaque (GE Healthcare) gradient centrifugation <4 hours after blood collection. CD14+ monocytes were isolated using a positive selection magnetic sorting kit (StemCell Technologies, UK) from total PBMC and stimulated with vehicle, UV-inactivated SARS-CoV-2 (CoV-2). RNA was isolated using the RNeasy Micro Plus Kit (QIAGEN) following the manufacturer’s guidelines. RNA-sequencing was performed by the Oxford Genomics Centre. PolyA-enriched strand- specific libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kits (Illumina). All samples were pooled together and 150bp PE reads were sequenced on a Novaseq 6000 system.

  Dataset EGAD00001009800

• FASTQ files of total RNA-Seq data from the POPS SGA (Small for Gestational Age) samples

  All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003507

• FASTQ files of total RNA-Seq data from the POPS PET (pre-eclamptic) samples

  All the samples were obtained from the Pregnancy Outcome Prediction–a prospective cohort study of nulliparous women attending the Rosie Hospital, Cambridge (UK) for their dating ultrasound scan between January 14, 2008, and July 31, 2012. Ethical approval for the study was given by the Cambridgeshire 2 Research Ethics Committee (reference number 07/H0308/163) and all participants provided written informed consent. Cases of preeclampsia (PET) were defined on the basis of the 2013 ACOG criteria and cases of small for gestational age (SGA)infants were confined to severe SGA, i.e. a customized birth weight <5th percentile. Chorionic villi from the corresponding placentas (free from decidua, visible infarction, calcification, hematoma, or damage) were collected and processed within 30 minutes of separation from the uterus. After repeated washes in chilled phosphate buffered saline, the samples were placed in RNA later (Applied Biosystems) and stored at -80°C. Total placental RNA was extracted using mirVana Isolation Kit (Ambion). For each placenta, approximately 5 mg of tissue were homogenized in the Lysis/Binding solution for 20 sec at 6 m/s using a bead beater (FastPrep24) and Lysing Matrix D Tubes (MP Biomedicals). The samples were then spun at 13,000 rpm for 5 min at 4°C and the supernatants recovered. Afterwards, the manufacturer's instructions were followed. Immediately after the RNA extraction, placental RNA samples were DNase-treated using DNA-free DNA Removal Kit (Ambion), aliquoted, and stored in -80°C. Quantity and quality of the RNA samples were assessed using the Agilent 2100 Bioanalyzer, the Agilent RNA 6000 Nano Kit (Agilent Technologies), and Qubit fluorometer. Libraries were prepared starting with 300-500 ng of good quality total RNA (RIN ≥7.5) using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat (Illumina), according to the manufacturer's instructions. The kit contains 96 uniquely indexed adapter combinations in order to allow pooling of multiple samples prior to sequencing. After determining their size (with the Agilent 2100 Bioanalyzer and the Agilent High Sensitivity DNA Kit by Agilent Technologies) and concentration (by qPCR with the KAPA Illumina ABI Prism Library Quantification Kit, Kapa Biosystems), libraries have been pooled and sequenced (single-end, 125 bp) using a Single End V4 Cluster Kit and an Illumina HiSeq2500 or HiSeq4000 instrument.

  Dataset EGAD00001003508

• Genetic Aberrations and Subclonal Structure Impact Chronic Lymphocytic Leukemia

  Large-scale whole-exome sequencing (WES) of primary tumor samples enables the unbiased discovery of recurrent putative driver events and patterns of clonal evolution. We report the identification of 44 recurrently mutated genes and 11 recurrent CNVs through the WES of 538 chronic lymphocytic leukemia (CLL) and matched germline DNAs. These include previously unrecognized cancer drivers (e.g., RPS15, IKZF3), and collectively identify nuclear export, MYC activity and MAPK signaling as central pathways affected by somatic mutation in CLL. A clonality analysis of this large dataset further enabled the reconstruction of temporal relationships between these driver events. Several drivers were associated with shorter progression-free survival (PFS) in 280 samples that were collected prior to uniform treatment with front line chemo-immunotherapy, with mature follow up of greater than 10 years. Direct comparison between matched pretreatment and relapse CLL from 59 samples demonstrated marked clonal evolution occurring in more than 95% of these patients. Distinct patterns of clonal evolution in relationship to specific gene alteration were observed, suggesting a hierarchy of fitness amongst mutations. Thus, large WES datasets of clinically informative samples enable the discovery of novel driver genes as well as the network of relationships between the drivers and their impact on disease relapse and clinical outcome.Additionally, we performed RNA-seq for 268 CLL samples (including 26 follow-up samples) and used them to identify expression subtypes of CLL. RRBS for 30 of these samples was also generated. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

  Study phs000922

• ovarian cancer sample exome seq

  Tissue samples were collected from 18 ovarian cancer patients. After mechanical and enzymatic dissociation, a part of these tissues underwent growth factoromics analysis. For four cases, single-cell sequencing analysis was conducted under conditions with or without estradiol. Additionally, the remains of the tissues were frozen and subsequently subjected to exome sequencing on 16 of these samples. Sixteen cases were diagnosed as HGSOC, while two samples were clear cell or mucinous type (Extended Data Table 1). All cases were grade 3, and none had received neoadjuvant chemotherapy.

  Dataset EGAD50000002057

• PROMETEO

  The SOLTI-1503 PROMETEO trial was a single-arm, preoperative, window-of-opportunity phase II study conducted at four sites in Spain between December 2018 and February 2022. It enrolled female patients with operable HER2-negative breast cancer (triple-negative or Luminal B-like) and residual disease after neoadjuvant chemotherapy. Tumor biopsies were collected at five time points (baseline, post-NAC screening, C2D1, C3D1, and surgery) for translational research. This dataset includes raw paired-end RNA sequencing data (~110M reads per library) generated from the 113 biopy samples, archived in FASTQ format.

  Study EGAS50000001499

• Diversity of the immune microenvironment and response to checkpoint inhibitor immunotherapy in mucosal melanoma

  Mucosal melanoma (MucM) is a rare cancer with a poor prognosis and low response rate to immune checkpoint inhibition (ICI) compared to cutaneous melanoma (CM). To explore the immune microenvironment and potential drivers of MucM’s relative resistance to ICI drugs, we characterized 101 MucM tumors (43 head and neck, 31 female urogenital, 13 male urogenital, 11 anorectal, and 3 other gastro-intestinal) using bulk RNA-sequencing (RNAseq). The original publication is written by JL Vos, JJH Traets, et al. and published in JCI Insight in 2024.

  Study EGAS50000000631

• University of Washington Cerebrospinal Fluid Biomarker Study for Parkinson disease

  There is a clear need to develop biomarkers for Parkinson disease (PD) diagnosis and monitoring disease progression. In this study we evaluated cerebrospinal fluid (CSF) proteins, which are known to be critically involved in PD or identified in our preliminary profiling studies, aptamers, and RNAs as potential PD biomarkers. Access to subjects for this study was via the Pacific Northwest Udall Center (PANUC) and the Alzheimer's Disease Research Center (ADRC) at the University of Washington and Oregon Health and Sciences University (OHSU). Using CSF samples from 30 well-characterized patients with PD and 30 age-, sex-matched healthy controls, we prepared RNA seq libraries and performed deep sequencing of all RNA species, including small and long RNA, mRNAs, noncoding RNAs and differentially spliced transcripts. We then tried several methods for RNAseq data analysis to optimize our analysis pipeline. We identified a total of 3381 transcripts corresponding to 182 long intergenic RNAs (LincRNAs), 11 microRNAs (miRNAs), 2861 protein-coding transcripts, 200 pseudogenes and 127 antisense RNAs; some of them were differentially expressed between PD and control groups. Selected differentially expressed RNAs have been validated in the same set of CSF samples using real-time PCR (RT-PCR). Further validations in independent, larger cohorts of samples are still ongoing. Our results obtained so far suggested that CSF proteins and RNAs could be used as good indexes for PD diagnosis and disease severity/progression. This study is a part of the NIDDS-funded Parkinson's Disease Biomarkers Program (PDBP).

  Study phs000901

• Transcriptome profiling of megakaryocytes and platelets: application to GP9- and IKZF5-related thrombocytopenia

  Platelets are anucleate cells produced in the bone marrow and derived from large progenitor cells called megakaryocytes (MKs). Platelets receive RNA transcripts from their progenitorial MKs during thrombopoiesis. However, the correspondence between platelet and MK transcriptomes is poorly understood, particularly in the context of germline mutations that cause platelet formation defects or thrombocytopenia. We have studied the effects of two such mutations on MK and platelet transcriptomes. We generated immortalized MK cell line (imMKCL)-based models of Bernard-Soulier syndrome and IKZF5-related thrombocytopenia. MKs derived from imMKCLs with either a homozygous deletion of GP9 (GP9-/-) or a heterozygous Y121F variant in IKZF5 (IKZF5WT/Y121F) exhibited reduced proplatelet formation (reductions of 96% and 57%, respectively). Platelets from patients with either GP9-/- or IKZF5WT/Y121F genotypes had broad transcriptomic dysregulation, suggesting that (pro)platelet formation defects due to mutations in glycoprotein receptor and transcription factor genes such as GP9 and IKZF5 affect the trafficking of transcripts from MKs into platelets. RNA-seq data from MKs at four stages of differentiation revealed widespread but distinct changes in expression over time between the GP9-/- and the IKZF5WT/Y121F genotypes. Dysregulated genes in GP9-/- MKs were enriched for RNA metabolism and actin/tubulin folding pathways while those in IKZF5WT/Y121F MKs were enriched for cell cycle pathways. Most of these genes were also dysregulated in the platelets of patients with the corresponding diseases. Our results suggest that patients with inherited forms of thrombocytopenia present with a transcript trafficking defect during platelet formation.

  Study EGAS50000001276

• PD1-targeted delivery of an IL-2 variant induces a multifaceted anti-tumoral T cell response in human lung cancer

  To explore PD1-IL2v-specific effects on CD8 and CD4 T cells at a transcriptomic level, we performed single-cell RNA sequencing of patient-derived tumor fragments (PDTFs) which were treated with either Isotype (DP47), Isotype-IL2v (DP47-IL2v), anti-PD1 (PembroPGLALA) or PD1-IL2v (PembroPGLALA-IL2v) for 48 hours.

  Study EGAS50000000396

• RNA and whole-exome sequencing of 22 patients with non-small cell lung cancer

  Whole exome sequencing from pre-treatment samples and matched blood normals from 22 patients. Of these individuals, on-treatment samples are available for a subset of 18 patients. RNA sequencing from pre-treatment samples from 21 patients. Of these individuals, on-treatment samples are available for a subset of 15 patients.

  Dataset EGAD00001008733

• 10X whole single cell RNA-seq from pre-frontal cortex biopsy

  The biopsy procedure was performed by a standard operative procedure under general anaesthesia. The placement of burr hole on the frontal lobe, opening of dura and cortex was performed in a routine fashion for VP shunt or VCS surgery. The biopsy was sharp dissected with knife through the leptomeninges, forming a tissue block consisting of cortex and subcortex, and placed in a sterile tube containing CSF. Fresh tissue sample processing was performed within the hours after surgery. The tissue was dissociated followed by red cell and debris removal and counting of the cells to be sequenced with (scRNA-seq; 10x Genomics). After dissociation only non neuronal cells were retrieved.

  Study EGAS50000001058

• Genomic and Genetic Analysis of Brain Tumors and Analysis of Their Clinicopathological Significance

  The treatment outcome of glioma patients remains disappointing, and more studies are needed to improve therapeutic strategies. In particular, it is crucial to understand the mechanisms underlying resistance to treatment and malignant transformation, as well as the intratumoral heterogeneity and interaction of tumor cells and host immunity. Recent advances in omics analysis techniques, such as next-generation sequencing (NGS), have enabled us to obtain omics data more easily and accelerated our ability to integrate this information and precisely characterize cases. In our project, we have already collected more than 100 pairs of human glioma/normal tissue samples, of which some are multiple specimens collected from initial and recurrent tumors, and some include multiple specimens collected from different regions within a single tumor. We used our in-house algorithms, composed of alignment and variant calling programs, to analyze omics data from multiple platforms, such as whole-exome sequencing (WES), RNA sequencing (RNA-seq), and methylation array, with our original cohort of glioma patients. Using several informatics tools, the information about genetic and epigenetic status and expression signatures were analyzed. Those data are expected to provide key information for investigating the mechanisms discussed above. Through this project, we hope to improve strategies for personalized therapy based on comprehensive omics data.

  Study JGAS000004

• Use of new methodologies to achieve a thorough molecular characterization in pediatric acute leukemia

  In childhood leukemia, a better genetic characterization is needed to define new clinic-biological entities, refine the risk-stratification of patients and help to reduce the toxicity by applying a risk-directed therapy. This project aims to obtain information that will allow us to personalize the management of pediatric patients with leukemia as much as possible, so that we can offer a complete diagnosis, a sensitive follow-up and a more targeted treatment to the real risk of each case. The use of massive genome analysis technologies such as transcriptome sequencing (RNA-Sequencing) will allow a comprehensive biological characterization of pediatric leukemia patients, especially those cases that we have not been able to characterize by conventional diagnostic techniques. We believe that the RNA-Seq technique will allow us to identify new biomarkers that will be useful for: 1) defining new biological entities with their own clinical behavior; 2) refining the stratification of patients into risk groups; 3) finding targets for a better follow-up of MRD and 4) identifying therapeutic targets for the application of targeted therapies to reduce toxicity. PI: Camós-Guijosa, Mireia; Vega-García, Nerea Funding: PI21/00213 Instituto de Salud Carlos III (ISCIII)

  Study EGAS50000000701

• Long-read whole genome sequencing of gastric cancer

  Gastric cancer (GC) remains a significant health challenge globally, with a particularly high incidence in Asia, including Singapore. Understanding the genomic landscape of normal gastric and the different GC subtypes along with its precursor lesions such as intestinal metaplasia (IM) as well as GC metastatic sites is crucial for advancing diagnostics, prognostics, and therapeutics. Long-read sequencing technologies offer an opportunity to delve deeper into the genomic and epigenetic alterations underlying these conditions and to complement existing short-read omics data. By integrating these data with previously generated in-house multi-omics data (such as RNA sequencing and whole exome sequencing), we hope to better elucidate the molecular mechanism underlying GC initiation and progression.

  Study EGAS50000001607

• Single cell transcriptomics to characterize the tumor microenvironment of prostate cancer fusion biopsies

  The primary objective of this study was to characterize the tumor microenvironment in fusion-guided transperineal biopsy samples from patients undergoing PC diagnosis. For each patient, one biopsy was taken from a suspected tumor region and another from a non-suspicious area, which were later classified as high- or low-tumorigenicity based on anatomopathological analysis. Using scRNA-seq data, we performed cancer-oriented cell annotation, differential expression analysis, and functional pathway enrichment studies across key cellular subpopulations. Additionally, differential abundance analysis was conducted to identify cell groups representative of different tumorigenicity levels. Finally, classification models were developed using gene expression data to differentiate high- vs. low-tumorigenicity samples, with the long-term goal of establishing a diagnostic classifier for PC stratification.

  Study EGAS50000000888

• snRNA-seq schizophrenia control Prefrontal cortex

  Human Brodmann Area 8/9 tissue from 43 schizophrenia subjects and 42 control individuals was obtained from three sources, NBB (Netherlands Brain Bank), Craig A. Stockmeier (University of Mississippi Medical Center), Macedonian/New York State Psychiatric Institute Brain Collection (Andrew J. Dwork, Columbia University). All subjects included in the study were matched between the two groups for age, gender, and postmortem interval. Nuclei were isolated and enriched for 85% neuronal nuclei before single nucleus RNA sequencing was performed with 10x Genomics Chromium Single Cell protocol v3.

  Dataset EGAD50000002447

• RNA-seq of granulosa cells from 8 IVF patients in two age groups

  This dataset contains raw sequencing data of mRNA from granulosa cell samples from 8 human patients undergoing in vitro fertilization. All patients were normal responders referred for male infertility and were grouped into two age groups (younger than 31 or older than 38 years old). Each sample contains all granulosa cells collected from one patient on one collection date. Raw sequencing fastq files are available in this dataset, count tables are available in ArrayExpress (E-MTAB-13496).

  Dataset EGAD50000001210

• RNA-Seq Brest Patient-derived Tumor Organoids

  This dataset includes 14 RNASeq samples from 8 patients. For some patients, organoids at different passages have been profiled. They can be identified by their alias, composed of the following structure: <subjectId>_O<organoid_number>_<passage>_RNA. For example, ICSBCS002_O1_1_RNA indicates the earlier passage of organoid 1 for subject ICSBCS002, and ICSBCS002_O1_2_RNA indicates the later passage. Additionally, WCM2137_O1_RNA and WCM2137_O2_RNA indicate two organoids (O1 and O2) derived from different tissues. More information about the passages and tissues can be found in the sample information table.

  Dataset EGAD50000000960

• Bulk Iso-Seq from brain tissue and exosomes isolated from brain tissue using long-read PacBio sequencing of poly-adenylated transcripts

  Human brain sEVs were isolated from postmortem human brain tissue. RNA was extracted from both the source brain tissue and sEVs and prepared for long-read sequencing. cDNA was sequenced on the PacBio Sequel II. The data provided have undergone processing using the tool ccs (v6.0.0) to generate circula consensus reads. For further processing, it is recommended to follow the guidelines at https://isoseq.how/, starting with using lima to remove cDNA primers.

  Dataset EGAD50000000043

• Exploring the heterogeneity of sarcoma using single cell sequencing

  Multi region samples are collected from patients, with consent, immediately after resection of the tumour. Samples are digested and sorted using FACS as single cells into lysis buffer. Cells are then stored until further processing for G&amp;T-seq. After sequencing, we will explore intra-tumour heterogeneity using computational approaches to integrate RNA and DNA data onto the tumour phylogeny 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/ .

  Dataset EGAD00001006786

• Transcriptome sequencing of hepatocellular carcinoma biopsies (TACE study)

  Illumina-based RNA-Seq analysis of 93 liver samples. Biopsies of tumors and non-tumor tissues are included. Samples are stratified by response and non-response to TACE treatment.

  Dataset EGAD00001008158

• Whole genome sequence and RNA-seq data from paired tumour and germline samples from mesothelioma patients

  Whole genome sequencing from paired tumour and germline malignant pleural mesothelioma samples

  Dataset EGAD00001008341

• LCM-RNAseq on human lung macrophages

  In the reported study, we employed Laser Capture Microdissection (LCM) for the transcriptome profiling of lung macrophages cells populations as a function of location within the healthy tissue. In detail, macrophage mini-bulks (100 cells each) were collected by LCM from 4 healthy human donors in 5 different locations of the airways (a total of 20 biopsies), including parenchyma (L1 – lower left lobe (LLL); L6 – 80% distance from LLL tip), trachea (L2), bronchi (L3 – 1st/2nd generation; L5 – 3rd/4th generation) and processed for RNA-seq.

  Dataset EGAD00001008694

• Dataset RNA-Seq of tumors for ImmuNEO already used in study EGAS00001004813

  Sequencing data of 20 tumor runs (different tumors), which were uploaded to EGAS00001004813 and used in the ImmuNeo publication. The sequencing was always paired and run on Illumina HiSeq sequencers.

  Dataset EGAD00001009670