10158 results for "cancer rna-seq"

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• PDAC organoid genomic heterogeneity

  Two primary tumor-derived PDAC organoids were subjected to SNP array, RNA-seq, and single-cell WGS.

  Dataset EGAD00001009741

• Covacta RNAseq counts

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes read counts per gene. Read counts were generated for the Gencode v27 annotation using the summarize Overlaps method from bioC in mode “IntersectionStrict”

  Dataset EGAD00001011164

• RNA-seq of whole blood and PBMC samples from immunotherapy treated NSCLC patients

  This dataset contains 228 paired fastq files sequenced with Illumina Novaseq 6000, and the file with the sample and clinical data.

  Dataset EGAD50000000389

• scRNA-seq of bulk and sorted NK

  Here we performed single-cell RNA sequencing to characterize NK cell subsets. Sorted NK cell subsets representing discrete stages of NK cell differentiation as well as bulk NK cells were sequenced.

  Dataset EGAD50000000020

• Comprehensive Genomic Characterization of Acral Melanoma

  In this study, we performed paired tumor/normal long insert whole genome and exome sequencing and tumor RNA sequencing on primary or metastatic acral melanoma tumors collected from 34 patients. Patients were enrolled from either Vanderbilt University or the Memorial Sloan-Kettering Cancer Center. We report an integrated analysis of DNA and RNA sequencing data to describe genomic and transcriptomic characteristics of acral melanoma.

  Study phs001036

• 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

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models: validation cohort

  While cell-free DNA (cfDNA) in liquid biopsies is widely being used and investigated, free circulating RNA (extracellular RNA, exRNA) has the potential to improve therapy response monitoring and cancer detection due to its dynamic nature. A fundamental open question hampering the initiation of large-scale liquid biopsy collections for tumour exRNA analysis is that it remains unclear in which blood subcompartment tumour-derived exRNAs primarily reside. We set out to develop a host-xenograft deconvolution framework, exRNAxeno, with cDNA mapping strategies to either a combined human-mouse reference genome or both species genomes in parallel, that can be applied to exRNA sequencing data from liquid biopsies of human xenograft mouse models, enabling to distinguish (human) tumoural RNA from (murine) host RNA, and as such to specifically analyse tumour-derived exRNA. Subsequently, the preferred exRNAxeno combination pipeline was applied to total exRNA sequencing data from blood platelets and three plasma fractions from a breast cancer patient-derived and neuroblastoma cell line-derived xenograft mouse model. We show that tumoural exRNA concentrations are not determined by plasma platelet levels, while host exRNA concentrations increase with platelet content. Furthermore, a large variability in exRNA levels and gene content across individual mice is observed. In general, the tumoural gene detectability in plasma is correlated with the RNA expression levels in the tumour tissue or cancer cell line. Our results unravel new aspects of tumour-derived exRNA biology in xenograft mouse models.

  Study EGAS00001006582

• Cell Type-Specific and Disease-Associated eQTL in the Human Lung

  This study was conducted to investigate the genetic control of gene expression in a cell-type and context-specific manner in the human lung. We performed single-cell RNA-sequencing (scRNA-seq) of lung tissue from 66 Interstitial Lung Disease (ILD) cases and 48 unaffected donors. Employing a pseudo-bulk approach, we mapped expression quantitative trait loci (eQTL) across 38 cell types. The scRNA-seq data presented here include previously published (PMID 34262047) and unpublished samples. ILD tissue samples were obtained from lungs removed at the time of lung transplantation at either Vanderbilt University Medical Center (VUMC) or the Norton Thoracic Institute (NTI). Control tissue samples were obtained from lungs declined for organ donation either at the Donor Network of Arizona (DNA) or VUMC. The self-reported ethnicities of donors were 66.7% European, 9.6% African American, 17.5% not available (N/A), and 6.1% other. The smoking history includes 46.5% ever smoker, 29.8% never smoker, 23.7% N/A. For genotyping, flash-frozen tissue in DNA/RNA shield was homogenized via a bullet blender. Genomic DNA was extracted using Zymo Quick DNA/RNA microprep plus kit. Library preparation and low-pass Whole Genome Sequencing (WGS) were carried out at TGen or by Gencove Inc. At TGen, libraries were prepared using PCR-free Watchmaker kits (Watchmaker Genomics) with 200 ng input. Genomes were sequenced on NovaSeq at low coverage (typically 0.4–1x). The resulting sequence data were processed and imputed using Gencove's imputation platform.

  Study phs003521

• Aggregated panel-seq VCF for initial cohort screened for BoB

  Aggregated VCF file from cancer genes panel seq for the initial (n=500) cohort of solid tumors screened for the Basket of Baskets study

  Dataset EGAD00001008437

• SCLC MeDIP-seq

  Methylation profile of 33 patients with small cell lung cancer (SCLC) for both, tumour and normal lung samples using MeDIP-seq.

  Dataset EGAD50000000724

• Stromal and dendritic cells from lymph nodes: single-cell RNA-seq

  Although cross-species transcriptional analysis has been generated for DCs, transcriptomic conservation between mouse and human FRCs at single-cell resolution has been unclear. To test whether GREM1+ FRCs might also play a role in DC homeostasis in humans, we performed scRNA-seq of CD45–PDPN+ stromal cells, as well as CD45+CD11c+ immune cells from healthy human LNs of three human donors. Data was generated using the 10x platform.

  Dataset EGAD00001008731

• cfDNA methylation dataset for colon cancer

  Enzymatic conversion-based methylation sequencing data (EM-seq) for colon cancer used in the MESA study

  Dataset EGAD50000000075

• Molecular Characterization for Nasopharyngeal Carcinoma (NPC)

  Total RNA was isolated from 50 formalin-fixed paraffin-embedded nasopharyngeal cancer (NPC) specimens using the RecoverAll Total Nucleic Acid Isolation kit (Ambion). Tumor RNA libraries were prepared with 200ng RNA using the Illumina TruSeq Stranded Total RNA kit with Ribo-Zero Gold, and sequenced with >80 million 100 bp paired-end reads.

  Dataset EGAD00001009047

• RNA-seq on patient-derived, stage II, CRC cell lines

  The gut microbiome is a key player in the immunomodulatory and pro-tumorigenic microenvironment in colorectal cancer (CRC). It is well established that Fusobacterium’s virulence factors are responsible for its pro-tumorigenic properties, however the role of its metabolic cross-talk with the tumor remains unexplored. Here we use in vitro, in vivo, and in silico methods to describe a novel microbe-host interaction keystone: formate. Omics data reveals molecular signatures, linking a metabolically driven CRC phenotype with Fusobacteria. We observed a metabolic shift towards increased F. nucleatum formate secretion in gut-on-chip model co-cultures with patient-derived CRC cells, along with an accelerated cancer glutamine metabolism. We show that high formate levels trigger AhR signaling, increase cancer stemness and cellular invasion. Finally, we observed an expansion of Th17 cells accompanying F. nucleatum-induced tumorigenesis. Moving beyond observational studies, we applied new experimental approaches for gaining ecosystem-level mechanistic understanding of F. nucleatum’s role in cancer pathogenesis.

  Study EGAS00001005948

• ChIP-Seq (H3K27me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K27me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001230

• Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001227

• ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001229

• ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001231

• ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001232

• ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001233

• ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001234

• ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001235

• Fastq data for stranded mRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for stranded mRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001402

• Differential Presence of Exons in Cell-Free DNA Reveals Different Patterns in Colorectal Cancer Between Metastatic and Non-Metastatic Patients

  Tumor genotyping during disease follow-up is gaining an increasing interest for monitoring and clinical management in colorectal cancer (CRC). Growing evidences suggest that single biopsies are inefficient for molecular profiling, due to clonal evolution and intratumoral heterogeneity of primary tumors and/or metastasis. Circulating free DNA (cfDNA) has emerged as an alternative source of genetic material that seems to be representative of the continuously changing tumor molecular features. Thus, the so-called 'liquid biopsy' also offers the additional advantages of accessibility and non-invasiveness for the patient. Novel strategies based on next-generation sequencing (NGS) of cfDNA are being currently developed, with most studies focusing on targeted deep sequencing panels of potential clinically actionable genes. Here we describe an alternative approach, consisting of exome-sequencing in cfDNA at a relatively shallower depth to provide a more general overview of the circulating genome. In this study, two groups of colorectal cancer patients, with either disseminated (M) or localized disease (N), were compared using whole-exome sequencing and a RNA-seq bioinformatics analysis pipeline. Thus, a set of 379 exons present at different levels in cfDNA from both groups were identified, giving rise to a completely new concept in this field, termed as 'Differential Presence of Exons'. Differentially present exons (DPEs) were subsequently used for M and N patients clustering and classification, allowing for the design of a predictive algorithm with encouraging preliminary results in a small subset of patients that could not be initially classified attending to the selection criteria (U group, unassignable).

  Study EGAS00001002687

• Multiregion Whole Exome and Smart-Seq3 single cell RNA sequencing of Breast Tumors

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Study EGAS00001006851