14977 results for "cancer studies using rna-seq"

in 12.79 milliseconds.

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005010

• Integrated genomic analysis for HCC

  Liver cancer is a common malignancy and is the third cause of cancer-related death in the world and hepatocellular carcinoma (HCC) is the major type of liver cancer, accounting for ~90% of cases. Only 20 ~ 30% of patients can benefit from combined immunotherapy and targeted therapy due to the high inter-tumor heterogeneity of HCC. This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed whole genome/exome sequencing (WGS/WES) and/or RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the great consistence between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. And we further characterized HCC subtypes using genomic, transcriptomic and clinicopathological features. Among 9 subtypes, 5 subtypes belonged to chromosome instable tumors, while 3 subtypes belonged to chromosome stable tumors. In addition, our subtypes were associated with prognosis and we also found different distributions of subtypes across various features, such as etiology and gender. Our study provided a robust molecular classification based on a large HCC dataset from Western country, it improves our understanding of the mechanisms of carcinogenesis and will facilitate development of genome-based precision medicine in HCC.

  Study EGAS00001007957

• Dysregulation of Alternative Splicing Is a Transcriptomic Feature of Patient Derived Fibroblasts From CAG Repeat Expansion Spinocerebellar Ataxias

  The aim of this study was to characterize transcriptomic changes in patient-derived cell lines of CAG repeat expansion spinocerebellar ataxias (SCAs), using RNA-sequencing (RNA-Seq), to help us better understand disease pathogenesis. The data consists of two SCA1, two SCA3, and one SCA7 cell lines with 5 unaffected controls. Widespread alternative splicing dysregulation was identified across all SCA cell lines. Alternative splicing analysis also revealed that the dysregulation affected disease-relevant pathways with novel skipped-exon splicing events from the RNA-Seq data validated with RT-PCR. These findings are consistent with a previous study that identified robust transcriptomic dysregulation, specifically at the splicing level, in SCA1, -3, and -7 mouse models even at presymptomatic ages. Therefore, alternative splicing has the potential to be used as a biomarker not only in mouse models, but also patient models of repeat expansion SCAs.

  Study phs003759

• Single-Cell RNA-Seq Profiling of Peripheral Immune Responses to Severe Infection in Uganda

  We conducted a prospective observational study (RESERVE-U-2-TOR) of adults admitted to Tororo General Hospital in eastern Uganda with severe, undifferentiated infection (i.e., suspected sepsis). Peripheral blood mononuclear cells (PBMCs) were isolated from freshly collected heparinized whole-blood samples (4 - 5 mL) using a standard density-gradient protocol (STEMCELL Technologies). PBMCs were aliquoted, cryopreserved in CryoStor CS10 (STEMCELL Technologies), stored overnight at -80°C, and transferred to liquid nitrogen for longer-term storage. Upon thawing, viability was assessed using the Nexcelom Cellaca Cell Counter, and cells were diluted to optimal concentrations for loading onto the Chromium Controller (10X Genomics). Each sample targeted the capture of ~10,000 GEMs (gel bead-in-emulsions). Single-cell RNA libraries were prepared using the Chromium Single Cell 3' Reagent Kit v3.1 following the manufacturer's standard protocol. Libraries were quality-assessed using an Agilent TapeStation and quantified using both Qubit 2.0 Fluorometer (Invitrogen) and qPCR (Applied Biosystems). Sequencing was performed on the NovaSeq X Plus platform (Illumina) using a 28×91 read configuration per 10X guidelines, targeting ~50,000 reads per cell. Data from this study available through dbGaP include raw single-cell RNA-seq data generated from PBMC samples collected from a subset of RESERVE-U-2-TOR participants at study enrollment (N=8).

  Study phs004100

• Assessment of genetic and epigenetic variation in human IPS cells-RNA

  In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The transcriptomes of these iPS cells will be compared. Protocol: primary cultures of cells were reprogrammed to iPS cells. RNA was extracted using a standard column extraction kit.

  Dataset EGAD00001000604

• STARR-seq of ERa binding sites in MCF7 and Ishikawa cell lines

  A oligo-captured STARR-seq library was generated using as targets ERa binding regions indetified by ChIP-seq in Ishikawa (Endometrial cancer) and T47D (breast cancer) cell lines and, breast cancer primary tissues. STARR-seq assays have been performed in MCF-7 and Ishikawa cell lines. Cells have been cultured for 3 days in hormone deprivated (phenol-red free) media and stimulated for 6 hours by 10nM estradiol (E2) or DMSO (negative control).

  Dataset EGAD50000000015

• RNA-Seq Profiles from CA017-003 Clinical Trial

  The dataset contains RNAseq profiles of 182 patients from the CA017-003 clinical trial. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. RNAseq libraries (50PE, 50M) were constructed using Illumina TruSeq RNA Access method. Fastq files are included.

  Dataset EGAD50000000991

• MAITS in HCC

  Hepatocellular Carcinoma (HCC) is a leading cause of cancer-related death and can be considered a prototype of inflammation-derived cancer arising from chronic liver injury. The cell composition of the HCC tumor immune microenvironment (TiME) has a major impact on cancer biology as the TiME can have divergent capacities on tumor initiation, progress, and response to therapy. Recent development of multi-omics and single-cell technologies help us to comprehensively quantify the cellular heterogeneity and spatial organization of the TiME and to further our understanding of antitumor immunity. We investigated the cellular composition of liver cancer patient samples (n=8) using single-cell RNA-seq. For this purpose, mononuclear cells were isolated from human liver cancer samples. Three locations within the tumor-bearing liver were used: adjacent liver, rim and tumor core. Then, cells were FACS sorted (either CD45+ cells or MAIT cells) and subjected to 10X Chromium-based scRNA-seq. We investigated immune cell changes and the cellular heterogeneity of the HCC TiME with a focus on MAIT cells. Annotated H5 files are provided. Clinical metadata including TMN stage, sex, gender, ethnicity, pretreatment, and histopathological reports are available for all patient samples. Further details on the study can be obtained in our paper once it’s published.A complementary dataset derived from ultrahighplex CO-Detection by indEXing (CODEX) from paired patient samples can be accessed through The Cancer Imaging Archives (TCIA) under DOI: https://doi.org/10.7937/bh0r-y074.

  Study phs003279

• mUM patient biopsies pre and post treatment with tebentafusp

  The dataset includes 141 RNA-seq samples form mUM patietns. Tumour biopsies were obtained from uveal melanoma patients pre and post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system.

  Dataset EGAD50000001258

• Bulk RNA sequencing of Singapore colorectal cancer patients (SG-BULK)

  RNA-seq libraries were prepared using the KAPA Stranded RNA-Seq Kit with RiboErase (Kapa Biosystems, Wilmington, MA) and sequenced to a target depth of 200-M reads on the Illumina HiSeq platform (Illumina, San Diego, CA).

  Dataset EGAD00001008512

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001006088

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001006122

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001005827

• Single Cell and Spatial Transcriptomic Profiling of Haemophilus ducreyi Infection

  We investigated the immune response in end-point pustules formed by Haemophilus ducreyi in volunteers using an experimental infection model. Six volunteers were infected in the skin of the upper arm at three sites with 41-85 CFU of H. ducreyi loaded on an allergy testing device; a sham-inoculated (e.g., wound) site was also performed. Five volunteers (4 men and 1 woman; 2 Asians and 3 Whites; aged 27-46 years) formed pustules 6-8 days post infection; 1 volunteer spontaneously resolved all sites. If a volunteer formed pustules, biopsies were performed to collect their pustule and wound sites. Biopsy pairs for all 5 pustule formers were subjected to single cell (sc) RNA-seq. Sequencing libraries were prepared using the 10X Genomics Single-cell 3' RNA-seq kit. Spatial transcriptomics was performed on biopsy pairs from 4 of the 5 pustule formers. Ten micron sections were placed on 10X Genomics Visium slides for fresh-frozen tissue, and libraries were prepared with the 10X Genomics Visium spatial 3' gene expression kit. All samples were sequenced on an Illumina NovaSeq 6000. Count tables were produced with CellRanger and SpaceRanger, respectively, and Seurat was used to analyze the data. We identified 13 major cell types by scRNA-seq; the proportion of some immune cell subsets was increased in pustules compared to wound sites. We also localized the major cell types within the tissue by using the scRNA-seq data to deconvolve the spatial transcriptomic data. The FASTQ files and count tables from CellRanger and SpaceRanger are provided.

  Study phs003754