15038 results for "cancer studies using rna-seq"

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• Epigenetic Landscape of Human Parathyroids

  The goal of this study is to produce a comprehensive map of the chromatin landscape of human parathyroids. Data from 20 subjects with parathyroid adenoma causing primary hyperparathyroidism were used. For the sequencing platform, Illumina HiSeq 2000 with V3 high-output kits were used. For the data processing pipeline, reads were aligned to hg19 using Bowtie or BWA. For RNA-seq data, transcript levels were estimated per gene to RPKM using Cufflink. For ChIP-seq and ATAC-seq data, enrichment peaks were estimated compared to inputs or background using MACS2 after merging reads from replicates. For DNase-seq, significant peaks compared to background distribution were computed using Hotspot. For Hi-C data, significant interactions were detected using Juicer HiCCUPS and 5 kb resolution for the merged data from replicates. Chromatin states for parathyroids were computed using ChromHMM based on ChIP-seq profiles in parathyroids of H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K27me3 and H3K9me3 and the emission matrix from 18 states pre-trained in the Roadmap Epigenomics. Gene expression, binding positions of transcription factor, open chromatin regions, 3D-chromatin interaction, and chromatin states are submitted.

  Study phs003302

• Single-cell RNA sequencing of metastatic colorectal cancer organoids treated with cetuximab

  Single-cell RNA sequencing was performed on metastatic colorectal cancer (mCRC) organoids derived from a cetuximab-sensitive patient-derived xenograft (PDX) model. The objective of this analysis was to investigate, at single-cell resolution, the transcriptional changes previously identified in bulk RNA-seq analyses of PDX models exposed to anti-EGFR therapeutic pressure.

  Study EGAS50000001460

• Transcriptomics of Liver and PBMCs in Alcohol-Associated Liver Disease

  This study was designed to characterize the transcriptome of alcohol-associated hepatitis using RNA sequencing (RNA-seq) technology for both liver tissue biopsies and peripheral blood mononuclear cells (PBMCs) extracted from blood samples, in order to identify expressed genes that are markers of the disease. To distinguish genes that differentiate alcohol-associated hepatitis from other inflammatory liver diseases, we compared the RNA-seq data generated from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, non-alcohol-associated fatty liver disease, and healthy controls. We utilized computational approaches to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to identify a small set of gene biomarkers to distinguish between these liver diseases. The raw RNA-seq data will be available through dbGaP.

  Study phs003112

• GWA Study of Oral Cavity, Pharynx and Larynx Cancers in European, and North and South American Populations - CIDR

  There is striking geographical variation in head and neck cancer (HNC) incidence globally. Some of the highest incidence rates have been observed in Southern and Eastern Europe and South America. The goal of this project is to assess susceptibility loci across and within ancestral backgrounds, using the All of Us array. Ten studies have come together in this initiative.

  Study phs002503

• 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

• Indonesian RNA-seq dataset

  This dataset contains 4 batches of Indonesian RNA-seq data from Mentawai, New Guinea and Sumba islands. One RNA-seq batch was prepared without Globin depletion, and three batches were Globin depleted using the Illumina Globin-Zero Gold Kit. There are 179 runs in total, including 119 unique samples. Dataset includes multiple batch control samples.

  Dataset EGAD00001005053

• RNA-seq of multi-regional CRC samples

  BAM files of RNA sequencing (RNA-seq) experiment on multi-regional colorectal cancer (CRC) samples. 58 samples corresponding to 16 patients were sequenced and there is one BAM file for each sample.

  Dataset EGAD00001006164

• GM adipose tissue study

  The Greek Metabolic (GM) adipose study was carried out in 106 individuals living in Greece and consists of genotyping data (chip), RNA-Seq and ATAC-Seq (for a subset of individuals) data from paired biopsies of Subcutaneous and Visceral adipose tissue. eQTL mapping was performed to study gene regulation and findings compared to those from adipose tissue GTEX data. The focus of this project was to study an underexplored population living in different environmental conditions in order to reveal novel regulatory effects for genes that shape complex traits and disease risk. Our results highlight the utility of modest-sized studies in adding to our understanding of the molecular basis of complex traits and to the identification of mechanisms that drive disease in specific tissues.

  Study EGAS00001007126

• RNA-seq BAM files from newborn screening dried blood spot samples

  Paired-end RNA-seq BAM files from 21 newborn screening dried blood spot (DBS) samples. These DBS samples were obtained from extremely low gestional age newborns, where 10 of them were affected by a fetal inflammatory response (FIR) before birth, and 11 were unaffected. Total RNA was sequenced using an Illumina NextSeq-500 instrument. The sample preparation protocol included the depletion of rRNA and globin mRNA using the Globin Zero Gold rRNA Removal Kit from Illumina. Libraries were prepared using the NebNext Ultra TM II Directionl RNA LIbrary Prep Kit (New England Biolabs). There is one BAM file per sample and there is an additional BAM file, corresponding to sample BS13, which was downsampled to 1/4 of its original depth (see BS13_README file for details).

  Dataset EGAD00001005009

• scRNA-seq Next GEM-X Flex

  Single-cell RNA sequencing (scRNA-seq) was generated using the 10x Genomics GEM-X Flex Gene Expression Multiplexed platform

  Dataset EGAD50000001186

• Genetic and Genomic Analysis of Primary Human Chondrocytes

  Osteoarthritis (OA) is a common, degenerative joint disease characterized by the gradual breakdown of the cartilage in the joints. Despite osteoarthritis affecting over 500 million individuals, the lack of a comprehensive mechanistic understanding of the disease has greatly hindered the development of adequate treatment options. To address this, we generated RNA-seq, Hi-C, and ATAC-seq data in primary human chondrocytes treated with either PBS as resting or a fibronectin fragment (FN-f) to model the OA chondrocyte phenotype. We mapped expression quantitative trait loci and splicing quantitative trait loci, and performed colocalization with OA GWAS data to identify putative OA risk genes. Integration of ATAC-seq and Hi-C data provided insights into the regulatory mechanisms. This study revealed both expression-based and splicing-based OA risk genes, several of which had not been previously identified in chondrocyte studies.

  Study phs003581

• ECM-free patient-derived organoids preserve diverse prostate cancer lineages and uncover in vitro-enriched cell types

  Patient-derived organoids (PDOs) hold promise for modeling various cancers, yet their application in prostate cancer (PCa) has been limited due to low culture success and the predominance of non-tumor-like cells. Using 164 PCa samples and optimizing culture conditions, we demonstrate that an extracellular matrix (ECM)-free culture method improves PDO take-rates, fostering cell populations with luminal and PCa-specific characteristics. Single-cell RNA sequencing (scRNA-seq) reveals that these ECM-free PDOs closely mirror their original tumors at the transcriptomic level and maintain a diverse array of tumor cell types, unlike traditional Matrigel-based cultures which predominantly yield benign-like cells. This study introduces a PCa PDO single-cell atlas, providing a valuable resource for advancing prostate cancer research.

  Study EGAS50000000807

• RNA-Seq of acute lymphoblastic leukemia in LLAG-0707 study

  This dataset contains RNA-Seq data of acute lymphoblastic leukemia in LLAG-0707 study. Diagnostic samples of 188 patients were sequenced. Reads were aligned to hg19 genome reference using STAR. Aligned bam files are provided in this dataset.

  Dataset EGAD50000001181

• Human tumor single-cell RNAseq

  We profiled 7 high-grade gliomas patient brain tumor samples by single-cell RNA-seq and 18 single-nuclei RNA-seq using 10X Chromium 3' techonology. The raw fastq files are provided.

  Dataset EGAD00001008351

• Human tumour and matched-normal single-cell RNAseq

  We profiled 16 high-grade gliomas patient tumour samples by single-cell and single-nuclei RNA-seq and 3 normal-matched single-cell RNA-seq using 10X Chromium 3'. The fastq files are provided.

  Dataset EGAD00001006097

• Whole Exome Sequencing and RNA Sequencing of High Grade Serous Ovarian Cancer in Black and White Patients

  In this study, we generated new RNA and whole exome sequencing data from high-grade serous ovarian cancer tumor samples of self-identified Black and White individuals. Our RNA-Seq analysis revealed that, while the prevalence of subtypes varied across racial groups, the cluster-specific gene expression patterns were consistent. Despite these differences in subtype prevalence, the subtype-specific survival rates were similar across racial groups. Additionally, we used the WES-Seq data to characterize mutational signatures and their underlying causes in Black high-grade serous ovarian cancer (HGSC) cases, and compared the prevalence and distribution of these signatures with those in White TCGA cases.

  Study phs003632

• Innate and Adaptive Immunity in Parkinson Disease-P20

  Increasing evidence supports the role of brain and systemic inflammation in the etiology of Parkinson disease (PD). We used gene expression profiling (RNA-seq) to examine the activation state of peripheral blood monocytes in 18 patients with early, untreated PD and 16 healthy control (HC) subjects. Monocytes were isolated by negative selection, and gene expression studied by RNA-seq and gene set enrichment analysis. A computational model that incorporated case/control status, sex, and the interaction between case/control status and sex was utilized. We found that there was a striking effect of sex on monocyte gene expression. There was inflammatory activation of monocytes in females with PD, with enrichment of gene sets associated with interferon gamma stimulation. In males, the activation patterns were more heterogeneous. These data point to the importance of systemic monocyte activation in PD, and the importance of studies which examine the differential effects of sex on pathophysiology of the disease.

  Study phs002063

• Neoadjuvant Breast Cancer Validations

  This study aims to re-sequence findings from whole genome studies using a bespoke pulldown method to validate mutations in those genomes sequenced.

  Dataset EGAD00001000663

• Comparison of capture-based method for transcriptome profiling of formalin-fixed paraffin embedded tumor samples

  Background: The need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. Methods: Transcriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. Results: The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p < 0.01). Both Agilent and IDT detected all the clinically relevant fusions that were initially identified in FF-TruSeq. Conclusion: All exome capture-based methods had comparable performance and concordance with FF-TruSeq. By enabling the interrogation of FFPE tumor samples, our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

  Study EGAS00001005255

• DNA and RNA Profiling Using Simultaneous Sequencing (Simul-seq)

  Paired DNA and RNA profiling is increasingly employed in genomics research to uncover molecular mechanisms of disease and to explore personal genotype and phenotype correlations. We developed a novel simultaneous DNA and RNA sequencing approach (Simul-seq) that enables comprehensive genomic and transcriptomic profiles from small quantities of cells or tissues. In this study, Simul-seq was performed on patient-derived fibroblast cells as well as an esophageal adenocarcinoma tumor sample and compared with standard DNA and RNA-sequencing approaches.

  Study phs001214

• Gene_regulation_of_human_CD4__Treg_cells_

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ChM-seq (118 H3K4me3, 118 H3K27ac and 6 inputs), ATAC-seq (114 samples) and whole transcriptome (141 samples). All individuals were genotyped (130 samples) using coreExome Illumina SNP chip array. The final quality filtered set included 123 individuals with RNA-seq data, 73 with ATAC-seq, 91 with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq data. A total of 62 individuals had QCed data for all the assays.

  Study EGAS00001003516

• Evolution of Core Archetypal Phenotypes in High-Grade Serous Ovarian Cancer (HGSOC)

  The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells in response to chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we performed single-cell RNA-sequencing (scRNA-seq) or whole-genome sequencing of 23 total patients, with longitudinal samples collected from 9, treatment-naïve samples from 8 patients, and post-treatment samples from 6 patients. Our study revealed that the HGSOC transcriptome could be described using three core archetypal phenotypes, defined as oncogenic tasks that describe majority of the transcriptional data. We implemented a multi-task learning approach to identify the biological tasks of each archetype and identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The “metabolism and proliferation” archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently linked to specific whole-genome driver mutations. However, archetypes were closely associated with sub-clonal clusters at the single-cell level, indicating that cancer cell sub-populations specialize in particular biological tasks. Our study reveals a defining principle of ovarian tumor evolution using temporal scRNA-seq profiles, identifies the key phenotypic features across patients and links metabolic shifts with a response to chemotherapy.

  Study phs002294

• Elucidation of the association of the HPV integration and oropharyngeal cancer

  Whole-genome sequencing was performed using tumor and blood samples from 14 patients with HPV-associated oropharyngeal cancer. Bulk RNA sequencing was performed using tumor samples from 19 patients with HPV-associated oropharyngeal cancer and 17 patients with non-HPV-associated oropharyngeal cancer and normal tonsil samples from 2 healthy controls.

  Study JGAS000751

• RNA-seq libraries from FFPE samples using Illumina Ribo-Zero Plus kit

  RNA was extracted from FFPE human tissue samples and used to prepare RNA-seq libraries with the Illumina Stranded Total RNA Prep Ligation kit with Ribo-Zero Plus. cDNA synthesis was performed starting from 100 ng of DNA-free RNA. Libraries were amplified with 16 PCR cycles and sequenced in paired-end mode (2×150 bp) on the Illumina NextSeq 550 platform. Library quality was assessed with Bioanalyzer and Qubit.

  Dataset EGAD50000001553

• Cancer RNA-seq consisting of FASTQ paired-end reads from melanoma and lung cancer sample

  Cancer RNA-seq consisting of FASTQ paired-end reads from 6 individuals (4 melanoma, 1 lung cancer). RNASEQ was performed on illumina, Truseq capture kit, 40M-80M clusters. 2 Melanoma datasets contain reads from 1 tumor region and from a tumor derived cell line 2 Melanoma, 1 Colon and 1 lung datasets contain each reads from a single region.

  Dataset EGAD00001007951

• RNA-Seq data from 34 CAF-S3 subset in human breast and ovarian cancers

  This dataset is related to publications Costa et al. Cancer Cell 2018 and Givel et al. Nat. Commun. 2018 which describe the identification of 4 Cancer Associated Fibroblasts (CAF) in breast and ovarian cancer. This dataset contains transcriptomic profiles obtained by RNA-Seq of 34 CAF-S3 samples from breast and ovarian Tumors.

  Dataset EGAD00001004810

• MARS-seq dataset of five obese human subjects and a lean human subject

  Biopsies from visceral adipose tissue from the omental depot (OAT) were obtained from five obese individuals and one lean donor with participant informed consent obtained after the nature and possible consequences of the studies were explained under protocols approved by the Institutional Review Boards of the Perelman School of Medicine at the University of Pennsylvania, the Children’s Hospital of Philadelphia, or the Tel Aviv Sourasky Medical Center. The obese donors underwent bariatric surgery, the lean donor underwent cholecystectomy. OAT samples were placed in 1 mL of DMEM, and finely minced under sterile conditions before digestion in 50 mL of DMEM with 3 mg/1 mL collagenase IV (Gibco). Samples were incubated at 37°C in a rotating oven for 20-60 min. Adipocyte and stromal vascular fractions (SVF) were separated by centrifugation, and red blood cells (RBCs) were removed from the SVF by histopaque gradient (Sigma). Single-cell RNA-sequencing libraries were prepared using the MARS-seq pipeline, and sequenced on the MiSeq 500 or HiSeq 2500 Sequencing System (Illumina).

  Dataset EGAD00001005100

• Paired RNA-Seq for Sarcoma tumors

  Paired RNA-Seq of 199 samples of Sarcoma tumors. The sequencing was done mostly on HiSeq 4000 with Illumina TruSeq Stranded mRNA, ist was also done on NovaSeq 6000 using the same kit. Very few samples were sequenced on HiSeq X Ten with Illumina TruSeq RNA or Illumina TruSeq Stranded mRNA.

  Dataset EGAD00001010256

• Research on the identification of cancer stem cells for peidatric and adult malignancies.

  In recent years, "cancer stem cells" have been reported to exist in many cancers. Many reports have shown that they are the main cause of cancer recurrence. The aim of this study is to test whether cancer stem cells can be identified using patient samples. We will perform omics analysis of rare pediatric cancers by integrating genomics, transcriptomics, proteomics and metabolomics, including somatic and germline mutations, to deepen our understanding of the biological characteristics of the target disease. Based on the knowledge gained and clinical information from patients, we will conduct preclinical pharmacological studies using mouse models and in vitro models to investigate the therapeutic effects of novel therapeutic agents and novel therapeutic strategies such as cellular therapies.

  Study JGAS000623

• scRNA-seq Next GEM Single Cell 3ʹ

  Single-cell RNA sequencing (scRNA-seq) was generated using the 10x Genomics Chromium Next GEM Single Cell 3ʹ platform

  Dataset EGAD50000001185

• The RNA, ChIP and whole exome sequencing analysis of human colorectal cancer organoids and normal colon organoids treated with (+)-JQ1

  To reveal the mechanism of anti-tumor effect of (+)-JQ1, we performed RNA, ChIP and whole exome sequencing using human colorectal cancer and normal colon organoids.

  Study JGAS000378

• Circulating RNAs prior to endometrial cancer diagnosis

  We analyzed circulating RNA levels using small RNA sequencing, targeting RNA in the size range 17 to 47 nucleotides, in samples collected prior to endometrial cancer diagnosis compared to cancer-free controls. The analysis included 316 cases with samples collected 1-11 years prior to diagnosis , and 316 matched controls, both from the Janus Serum Bank Cohort in Norway.

  Study EGAS50000000267