11925 results for "cancer rna-seq"

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• Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Study EGAS50000001313

• Integrative genomic analyses reveal androgen-driven somatic alteration landscape in early-onset prostate cancer

  Early-onset prostate cancer (EO-PCA) represents the earliest clinical manifestation of prostate cancer. To compare the genomic alteration landscapes of EO-PCA with "classical" (elderly-onset) PCA, we performed deep sequencing-based genomics analyses in eleven tumors diagnosed at young age, and pursued comparative assessments with seven elderly-onset PCA genomes. Remarkable age-related differences in structural rearrangement (SR) formation became evident, suggesting distinct disease pathomechanisms. Whereas EO-PCAs harbored a prevalence of balanced SRs, with a specific abundance of androgen-regulated ETS gene fusions including TMPRSS2:ERG, elderly-onset PCAs displayed primarily non-androgen-associated SRs. Data from a validation cohort of >10,000 patients showed age-dependent androgen receptor levels and a prevalence of SRs affecting androgen-regulated genes, further substantiating the activity of a characteristic "androgen-type" pathomechanism in EO-PCA.

  Study EGAS00001000400

• Single-cell analysis reveals fibroblast clusters linked to immunotherapy resistance in cancer

  A subset of Cancer-Associated Fibroblasts (CAF-S1) mediates immunosuppression in breast cancers (BC), but its heterogeneity and its impact on immunotherapy response remain unknown. Here, we identify 8 CAF-S1 clusters by analyzing more than 18000 single CAF-S1 fibroblasts from BC. We validate the 5 most abundant clusters by flow cytometry and in silico analyses in other cancer types, highlighting their relevance. Myofibroblasts from clusters 0 and 3, characterized by extra-cellular matrix proteins and TGF signaling respectively, are indicative of primary resistance to immunotherapies. Cluster 0 up-regulates PD-1 and CTLA-4 protein levels in regulatory T lymphocytes (Tregs), which in turn increases CAF-S1 cluster 3 cellular content. Thus, our study highlights a positive feedback loop between specific CAF-S1 clusters and Tregs and uncovers their role in immunotherapy resistance.

  Study EGAS00001004030

• Hereditary Cancer Diagnostics with I2HCP gene panel

  This dataset contains targetted DNA sequencing data generated in the context of genetic diagnostics of hereditary cancer. Target enrichment was performed with the I2HCP, a custom hereditary cancer gene panel based in Agilent SureSelect and developed by the Germans Trias i Pujol Research Institute (IGTP, Badalona, Catalonia, Spain) and the Catalan Institute of Oncology (ICO, L'Hospitalet de Llobregat, Catalonia, Spain). After the enrichment, 108 samples were sequenced in Illumina HiSeq machines and 130 in MiSeq machines. Some of the samples were sequenced on both platforms. The dataset also includes MLPA validation data for all identified copy-number alterations, annotated with exon resolution and information about negative MLPA results. All this data was generated in the context of routine diagnostics and compiled together with MPLA validation data for a genetic diagnostics oriented benchmark of germline CNV calling tools.

  Study EGAS00001004316

• Chromothripsis followed by circular recombination drives oncogene amplification in human cancer

  The mechanisms behind the evolution of complex genomic amplifications in cancer have remained largely unclear. We here identified a type of amplification, termed as “seismic amplification”, that is characterized by multiple rearrangements and discontinuous copy number levels. Seismic amplifications occurred in 9.9% (274/2,756) of cases across 38 cancer types and were associated with massively increased copy numbers and elevated oncogene expression. Reconstruction of the development of seismic amplification revealed a stepwise evolution, starting with a chromothripsis event, followed by formation of circular extrachromosomal DNA that subsequently underwent repetitive rounds of circular recombination. The resulting amplicons persisted as extrachromosomal DNA circles or had reintegrated into the genome in overt tumors. Together, our data indicate that the sequential occurrence of chromothripsis and circular recombination drives oncogene amplification and over-expression in a substantial fraction of human malignancies.

  Study EGAS00001005424

• Application of high-throughput, high-depth, targeted single-nucleus DNA sequencing in pancreatic cancer

  Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimized a highly automated nuclei extraction workflow that achieved fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals novel genomic evolution patterns of PDAC as well.

  Study EGAS00001006024

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination.

  Dataset EGAD00001008696

• Construction of Thousands of Single Cell Genome Sequencing Libraries Using Combinatorial Indexing

  Single-cell genome sequencing has proven valuable for the detection of somatic variation, particularly in the context of tumor evolution. Current technologies suffer from high library construction costs which restrict the number of cells that can be assessed and thus impose limitations on the ability to measure heterogeneity within a tissue. Here, we present Single cell Combinatorial Indexed Sequencing (SCI-seq) as a means of simultaneously generating thousands of low-pass single cell libraries for somatic copy number variant detection. We constructed libraries for 16,698 single cells from a combination of cultured cell lines, primate frontal cortex tissue, and two human adenocarcinomas, including a detailed assessment of subclonal variation within a pancreatic tumor. "Reprinted from Vitak, S.A., et. al. 2017 with permission from Nature Methods."

  Study phs001268

• Ribosome profiling shows variable sensitivity to detect open reading frames for conventional and different types of cryptic T cell antigens

  The aim of the study was to explore the sensitivity of ribosomal profiling to detect ORFs for cryptic antigens targeted by T cells in immune responses. Ribosomal profiling was performed for six EBV-LCLs. Detection of conventional and cryptic MiHA-encoding ORFs was compared. The data showed that open reading frames (ORFs) for conventional MiHAs as well as cryptic MiHAs in upstream ORFs were frequently detected with similar sensitivity. However, only a limited number of MiHAs in in reading frames alternative to protein-coding sequences and no ORFs derived from long non-coding RNAs were detected. In conclusion, Ribo-seq for identification of antigen-encoding ORFs is useful to screen for cryptic antigens in upstream ORFs as potential targets for immunotherapy.

  Study EGAS50000000322

• XClone for analyzing somatic copy number alterations

  Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

  Study EGAS00001007854

• INTEGRATIVE MOLECULAR ANALYSIS OF SKIN TUMORS FROM CYLD CUTANEOUS SYNDROME PATIENTS

  CYLD cutaneous syndrome (CCS) is a rare autosomal dominant disorder characterized by germline CYLD mutations and by multiple benign skin tumors dependent on NF-kB pathway. We assembled a large cohort of CCS rare skin tumors that was profiled with whole exome or genome sequencing, RNA sequencing and methylation arrays to better understand genetic mechanisms of CCS tumorogenesis.

  Dataset EGAD50000000362

• Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution

  Ischemia reperfusion is an unavoidable step of organ transplantation. Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from six human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single cell RNA sequencing.

  Dataset EGAD50000000704

• Single-cell Transcriptome Analysis of Plasma Cells Across the Disease Spectrum of Multiple Myeloma

  This dataset includes FastQ files of single-cell RNA sequencing data of 5' GEX and VDJ libraries from CD138+ plasma cells enriched from 72 bone marrow aspirates from patients diagnosed with a monoclonal gammopathy from the multiple myeloma spectrum, including MGUS (n=13), SMM (n = 22), NDMM (n = 17), RRMM (n = 15) and PCL (n = 2); and 3 controls.

  Dataset EGAD50000001179

• Transcriptome profiling of head and neck squamous cell carcinomas with paired patient-derived xenografts

  This dataset includes transcriptome profiling of 88 head and neck primary patient tumor samples and 45 paired patient-derived xenograft samples that successfully engrafted in mice. NGS was performed using the Illumina TruSeq stranded total RNA sample preparation kit on the Illumina NovaSeq X Plus platform at the Princess Margaret Genomics Centre. This dataset consists of paired-end fastq files.

  Dataset EGAD50000000995

• scRNAseq of co-culture of human organoids with polarized pro-inflammatory or anti-inflammatory macrophages

  In order to know if the mechanisms we identified in mice – demonstrating that macrophages are able to orchestrate the intestinal regenerative process – are conserved in humans we develop a co-culture system with human intestinal organoids and human polarized macrophages. We co-culture human organoids with pro-inflammatory or anti-inflammatory macrophages for 48h. On day 3 cells were collected to perform single cell RNA sequencing.

  Dataset EGAD50000000675

• Whole exome sequencing and RNA sequencing of patient-derived pancreas neoplasm organoids

  Pancreatic cancers arise from two different precursors; intraductal papillary mucinous neoplasms (IPMN) and pancreatic intraepithelial neoplasm (PanIN), while biological differences in cancers originated from them remain obscure. Here, we analyzed their genomic and transcriptomic landscapes using patient-derived organoids.

  Study JGAS000263

• scRNA and V(D)J sequencing of WM under ibrutinib

  Single-cell RNA sequencing (5′ gene expression) and single-cell V(D)J sequencing (B-cell receptor and T-cell receptor) were performed on bone marrow mononuclear cells from patients with Waldenström macroglobulinemia treated with ibrutinib monotherapy. Sequential bone marrow aspirate samples were collected at baseline and after treatment. A total of 222 BAM files are included in this dataset.

  Dataset EGAD50000002279

• Analysis of resistance to PLX4032 (2019-08-21)

  We have collected material from a patient who had BrafV600E mutant melanoma that was treated with PLX4032. We have germline DNA from the patient and DNA and RNA from distinct lesions before and after treatment with PLX4032. We would like to exome sequence these samples to gain a snap shot of the mechanisms of resistance that are operative. . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005278

• Single-cell RNA sequencing of cytokine-induced T cell responses

  Cytokines affect T cell responses by polarising them to different phenotypes. We isolated T cells from healthy platelet donors and cultured them in resting and stimulated condition, as well as in the presence of Th2, iTreg and Th17 polarizing cocktail. To characterize the efficacy of cytokine induced porization and subpopulation specific response, we profiled single cell transcriptome five days following polarization using 10x platform (3' v2).

  Dataset EGAD00001005290

• Transcriptome sequencing of myelodysplasia

  Transcriptome sequencing was performed on 214 patients with myelodysplasia in this study. RNA was obtained from bone marrow CD34+ cells (n=100) and/or bone marrow mononuclear cells (n=165). Transcriptome sequencing was performed for both cell fractions in 51 patients. A total of 211 patients were genotyped by targeted deep sequencing. We also studied bone marrow CD34+ cells and bone marrow mononuclear cells obtained from three healthy adults each.

  Dataset EGAD00001003891

• RNA sequencing of NK cells in human lung

  The dataset contains RNAseq data from 5 subsets of NK cells isolated from human lung: 1) CD69+CD49a+CD103+CD16-CD56bright NK cells 2) CD69+CD49a+CD103-CD16-CD56bright NK cells 3) CD69+CD49a-CD103-CD16-CD56bright NK cells 4) CD69-CD49a-CD103-CD16-CD56bright NK cells 5) CD56dimCD16+NKG2A+CD57- NK cells The dataset contains paired data for the subsets from 2 donors with 2 biological replicates/donor and subset.

  Dataset EGAD00001004850

• Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets

  Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) 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 EGAD00001006331

• Genomics of enteropathy-associated T cell lymphoma (EATL)

  Whole exome sequencing of enteropathy-associated T cell lymphoma (EATL) tumors and paired normals, as well as RNA-sequencing of EATL tumors: including (1) 69 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples, (2) 36 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL paired normal samples, and (3) 32 RNAseq, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples.

  Dataset EGAD00001003284

• Raw sequencing data for donor and patient fecal samples

  Microbiome analysis was performed on the patient samples collected pre-FMT and on days after FMT, and on samples collected from the FMT donor. Genomic bacterial DNA was extracted from fecal samples using the QIAamp DNA Stool kit (Qiagen, Hilden, Germany), with the addition of a bead-beating lysis step. Genomic 16S ribosomal-RNA V4 variable regions were amplified and sequenced on the Illumina MiSeq platform.

  Dataset EGAD00001004371

• Characterization of Leukemic Stem Cells in DNMT3Amut and NPM1mut AMLs

  Using a novel sorting strategy, we performed ultra low input RNAseq from FACS-sorted populations from diagnostic DNMT3Amut and NPM1mut AML patients. Primary samples were retrospectively collected based on their mutational profile. Samples were thawed, stained and FACS sorted using combination of lineage markers, CD34, GPR56 and NKG2DLigands. RNA was extracted and library prepared from 13 samples.

  Dataset EGAD00001009293