15130 results for "cancer studies using rna-seq"

in 17.77 milliseconds.

• Human Neuroblastoma

  This dataset comprises single-nucleus transcriptomic profiles from 10 human neuroblastoma samples. Nuclei were isolated and processed using the SMART-Seq2 protocol to enable full-length, high-resolution RNA sequencing at the single-nucleus level. cDNA libraries were generated and sequenced on the Illumina HiSeq 2500 platform. The resulting raw sequencing data are provided as .fastq files for downstream analysis.

  Dataset EGAD50000001596

• Human Paraganglioma

  This dataset comprises single-nucleus transcriptomic profiles from 9 human paraganglioma samples. Nuclei were isolated and processed using the SMART-Seq2 protocol to enable full-length, high-resolution RNA sequencing at the single-nucleus level. cDNA libraries were generated and sequenced on the Illumina HiSeq 2500 platform. The resulting raw sequencing data are provided as .fastq files for downstream analysis.

  Dataset EGAD50000001689

• DCIS_FF_RNAseq

  This RNAseq dataset contains full transcriptome data on n=77 pure DCIS samples. The RNA is derived from fresh-frozen DCIS samples, obtained from two hospital based cohorts (NKI cohort and Oslo cohort). The libraries were sequenced with 54 bp paired end reads using a Novaseq instrument (Illumina). We share fastq data files of paired end sequencing (two files per sample).

  Dataset EGAD50000002123

• SCNA-Seq of plasma DNA samples

  Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping in plasma DNA of prostate cancer patients

  Dataset EGAD00001002149

• Tumor-resident T-cell regulate responses to checkpoint blockade immunotherapies

  In cancer models, CD103+CD8 TRM cells are implicated in the response to anti-PD-1 immunotherapy, and a subset of CD4 TRM cells expressing the integrin CD49a is required for response to anti-CTLA-4 immunotherapy. We performed single-cell RNA sequencing on tumour-infiltrating T lymphocytes (TILs) isolated from colon carcinoma et unsupervised analyses reveal several TRM populations.

  Study EGAS50000000826

• Exome and RNA sequencing of pancreatic cancer biopsies and PDX models

  Pancreatic cancer biopsies and matching normal controls from 10 patients were exome sequenced. The same biopsies and PDX models derived from these were also subject to RNA sequencing.

  Dataset EGAD00001008113

• Sequencing cancer mutations in various types of lung cancer using the long-read, portable sequencer

  In this study, we used a long-read and portable sequencer MinION to identify cancer mutations in lung adenocarcinoma cells. We performed cDNA amplicon sequencing for various types of mutations such as point mutations in EGFR and KRAS and oncogenic fusion transcripts in ALK and RET. Using the long reads of MinION, we also conducted mutation phasing of EGFR TKI-sensitive and resistant mutations, which would provide useful information to next thrapeutic approaches for cancers. We applied this method to identify mutation genotypes of eight clinical samples from Japanese lung adenocarcinomas. This method could provide new sequencing-based diagnostic approaches for lung cancers. Additinally we also performed cancer mutation identification of risk-dependent unique samples. Usual interstitial pneumonia (UIP) is a risk factor for lung carcinogenesis. This study was performed to characterize mutagenesis and mutational target genes underlying lung carcinogenesis in patients with UIP.We performed whole exome sequencing of lung adenocarcinoma with usual interstitial pneumonia.

  Study JGAS000065

• Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma

  Background:Malignant pleural mesothelioma (MPM) is a heterogeneous cancer. Better knowledge of molecular and cellular intra-tumor heterogeneity throughout the thoracic cavity is required to develop efficient therapies. This study focuses on molecular intra-tumor heterogeneity using the largest series to date in MPM and is the first to report on the multi-omics profiling of a substantial series of multi-site tumor samples. Methods:Intra-tumor heterogeneity was investigated in 16 patients from whom biopsies were taken at distinct anatomical sites. The paired biopsies collected from apex, side wall, costo-diaphragmatic or highest metabolic sites as well as 5 derived cell lines were screened using targeted sequencing. Whole exome sequencing, RNA sequencing, and DNA methylation were performed on a subset of the cohort for deep characterization. Molecular classification, recently defined histo-molecular gradients, and cell populations of the tumor microenvironment were assessed. Results:Sequencing analysis identified heterogeneous variants notably in NF2, a key tumor suppressor gene of mesothelial carcinogenesis. Subclonal tumor populations were shared among paired biopsies, suggesting a polyclonal dissemination of the tumor. Transcriptome analysis highlighted dysregulation of cell adhesion and extracellular matrix pathways, linked to changes in histo-molecular gradient proportions between anatomic sites. Methylome analysis revealed contribution of epigenetic mechanisms in two patients. Finally, significant changes in the expression of immune mediators and genes related to immunological synapse, as well as differential infiltration of immune populations in the tumor environment were observed and led to a switch from a hot to a cold immune profile in three patients. Conclusions:This comprehensive analysis reveals patient-dependent spatial intra-tumor heterogeneity at the genetic, transcriptomic and epigenetic levels and in the immune landscape of the tumor microenvironment. Results support

  Study EGAS00001005328

• Fibroblast heterogeneity drives metastatic spread in breast cancer through distinct mechanisms

  The major cause of death among breast cancer patients is metastatic dissemination, suggesting that understanding the mechanisms driving this process remains an unmet medical need. Here, by concomitantly using 5 markers, we identify 4 Carcinoma-Associated Fibroblasts (CAF) subsets in primary tumors and corresponding metastatic lymph nodes (LN). Two CAF subsets, called CAF-S1 and CAF-S4, correlate with the proportion of cancer cells in invaded LN and exert distinct functions in tumor cell spread. CAF-S1 promote cancer cell migration and initiates an epithelial to mesenchymal transition through a CXCL12 / TGFb positive loop. For their part, the highly contractile CAF-S4 foster cancer cell motility and invasion in 3-dimensional matrix via Notch pathway activation. Finally, CAF-S1 and CAF-S4 accumulation in LN is a new prognostic factor at diagnostic, independent of breast cancer subtypes and LN status, strengthening the validity of our findings in human breast cancer pathophysiology.

  Study EGAS00001003238

• Healthy control cfMeDIP-seq

  This dataset comprises 46 raw fastq files derived from 23 plasma cfDNA samples from 23 healthy (CTL) cancer-free donors. For each sample, 10ng of cfDNA was used for library preparation utilizing the cfMeDIP-seq technology based on the 5mC antibody-immunoprecipitation strategy. Libraries were validated via Bioanalyzer trace analysis and sequenced on the Illumina NovaSeq 6000 platform with paired-end 150-bp model for ~100 million reads per sample.

  Dataset EGAD50000000652

• Chromatin accessibility of clear cell renal cell carcinoma

  To investigate chromatin accessibility in ccRCC, we performed ATAC-seq in 3 ccRCC cell lines (786-O, A498, UMRC-2), and 1 normal kidney epithelium cell line (HK-2), cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions

  Study EGAS50000001325

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of the study "Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy". This dataset contains the cellranger's gene-expression matrices for the 5 prime single-cell RNA sequencing experiments

  Dataset EGAD50000000748

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  The dataset for the study “Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer” includes 173 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 32 individuals with esophageal/gastroesophageal junction cancer, who received immunotherapy-containing regimens.

  Dataset EGAD00001011822

• Whole Exome Sequencing for Colorectal Cancer

  This project was designed to use next generation sequencing technology to screen the protein coding regions of the genome for low frequency variants in a panel of high-risk colorectal adenocarcinoma cases. Blood and cell-line DNA for colorectal cancer patients and a subset of quality control samples that had existing whole exome sequence data were analyzed using Illumina HiSeq sequencers. Samples from this project were from participants in the Women's Health Initiative (WHI) and the Diet, Activity, and Lifestyle Study (DALS).

  Study phs000410

• Melanoma_Til_Study_RNAseq

  In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

  Study EGAS00001000251

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML___part2

  Genomic libraries will be generated from total genomic DNA derived from 4000 samples with Acute Myeloid Leukaemia. Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 64 Samples will be individually barcoded and subjected to up to one lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.

  Study EGAS00001000570

• Genotyping by OncoArray and Global Screening Array for colorectal cancer risk prediction

  The study was conducted to build a Polygenic risk scores (PRS) based on a reported set of 140 single nucleotide polymorphisms that were identified to be associated with a higher risk of colorectal cancer (CRC). Genotyping by OncoArray and Global Screening Array was performed using DNA extracted from blood samples collected at baseline of 187 participants who develop CRC and 176 randomly selected controls without diagnosis of CRC identified within 14 years of follow-up.

  Study EGAS00001005411

• IMMUcan Upstream SCCHN3 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients from the UPSTREAM trial, with squamous cell carcinoma of the head and neck (SCCHN) cancer which has spread (metastatic) or the tumour has come back after previous treatment (recurrent). Comprehensive profiling data are integrated with longitudinally collected clinical information. Cellular profiling of the same tumor samples was performed using multiplex immunofluorescence imaging, imaging mass cytometry, and H&E staining.

  Study EGAS50000001505

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• A system-wide approach to monitor responses to synergistic BRAF and EGFR inhibition in colorectal cancer cells

  Molecular heterogeneity of tumors, epigenetic changes and a diverse range of molecular mechanisms are main contributors to drug resistance, which represents one of the great challenges in cancer treatment. A deeper understanding of the molecular biology of cancer has resulted in better targeted therapies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has to some extent also been observed in colorectal cancer (CRC) patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block resistance. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant CRC cells as a well-define model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both well-known and novel responses. We primarily observe widespread upregulation of tyrosine kinases (RTKs) and and metabolic pathways. This points to by which the treated cells switch energy sources as a defensive response entering a quiescent like state, while activating signalling to re-activate the MAPK pathway.

  Study EGAS00001002654

• Multi-Omic Investigation of Beckwith-Wiedemann Syndrome Wilms Tumor

  Wilms’ Tumor (WT), also known as nephroblastoma, is one of the most common malignant kidney tumors diagnosed in children. One of the most common WT predisposition syndromes is Beckwith-Wiedemann Syndrome (BWS, OMIM: 130650), which affects approximately 1/10,000 live births. In this study, we perform Whole Exome Sequencing (WES), DNA methylation array, and messenger RNA-Sequencing (mRNA-Seq), to examine the genomic, methylomic, and transcriptomic signature of BWS WT. We analyzed six tumor-normal paired samples, three BWS tumor only samples, and four non-BWS control samples to identify BWS WT drivers.

  Study phs002769

• ABHD11 inhibition drives sterol metabolism to modulate T cell effector function and alleviate autoimmunity

  Chronic inflammation in autoimmunity is driven by hyperactive T cells with dysregulated metabolism. ABHD11 is a mitochondrial hydrolase that supports alpha-ketoglutarate dehydrogenase function and has been associated with remission in rheumatoid arthritis. To explore its role in T cell function, we used CRISPR/Cas9 to knock down ABHD11 in Jurkat T cells and performed RNA-Seq analysis. Differential gene expression revealed widespread transcriptional changes, with sterol-related pathways among the most significantly enriched. These findings highlight ABHD11 as a potential regulator of metabolic programming in T cells with implications for autoimmunity.

  Study EGAS50000001297

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the regulation of B cell recptor repertoire in B cell subsets and its contribution to autoimmune diseases, B cell subsets from 36 Systemic Lupus Erythematosus(SLE), 90 Systemic Sclerosis(SSc), 85 Myositis(IIM), 21 Mixed Connective Tissue Disease(MCTD), 18 Sjogren's syndrome(SjS), 27 Rheumatoid Arthritis(RA), 23 Behcet's disease(BD), 18 Adult Onset Still���s Disease(AOSD), 24 ANCA-associated Vasculitis(AAV), 16 Takayasu���s Arteritis(TAK) and 137 healthy controls(HC) were collected (Naive_B, USM_B, SM_B, DN_B, Plasmablast. RNA-seq and BCR-mapping was performed with each B cell subset samples.

  Study JGAS000485

• An Integrated Approach to Patient Stratification and Therapy Selection in Acute Myeloid Leukemia

  As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we developed and validated a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of RNA-Seq to whole genome and exome sequencing revealed that as a standalone assay, RNA-Seq offered the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data were used to develop a novel risk score which, when combined with molecular risk guidelines, allowed for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identified a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase (PTK2), demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.

  Dataset EGAD00001006701