15016 results for "cancer studies using rna-seq"

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• Whole exome and transcriptome analysis of UV-exposed epidermis and carcinoma in situ reveals early drivers of carcinogenesis

  Squamous cell carcinoma in situ (SCCIS) is a prevalent precancerous lesion that can progress to cutaneous squamous cell carcinoma (cSCC). Although SCCIS is common, its pathogenesis remains poorly understood. To better understand SCCIS development, we performed laser-captured microdissection of human SCCIS and adjacent epidermis to isolate genomic DNA and RNA for next generation sequencing. Whole exome sequencing (WES) identified UV-signature mutations in multiple genes including Notch 1-3 (GeneID:4851, GeneID:4853, GeneID:4854) in the epidermis and SCCIS and oncogenic TP53 (GeneID:7157) mutations in SCCIS. Novel gene families, including SCHLAFEN genes, contained UV/oxidative-signature disruptive (UVD) epidermal mutations that manifested positive selection in SCCIS. The frequency and distribution of NOTCH and TP53 mutations indicate that NOTCH mutations may precede TP53 mutations. RNA sequencing identified 1166 differentially expressed genes; the top 5 enriched GO biological processes included: 1) immune response, 2) epidermal development, 3) protein phosphorylation, 4) regulation of catalytic activity, and 5) cytoskeletal regulation. The NEURL1 ubiquitin ligase, which targets Notch ligands for degradation, was upregulated in SCCIS. Neuralized 1 protein was found to be elevated in SCCIS suggesting that increased levels could represent a novel mechanism for downregulating Notch during UV-induced carcinogenesis. The data from DNA and RNA sequencing of epidermis and SCCIS provide insights regarding SCCIS formation.

  Study phs002019

• DUX4 activates novel intergenic transcripts and isoforms in a tissue-specific context

  DUX4, a transcription factor driving zygotic genome activation during the embryonic cleavage stage in mammals, regulates the expression of genic and non-genic elements and modulates chromatin accessibility. Its misexpression in skeletal muscle causes Facioscapulohumeral muscular dystrophy (FSHD). The sporadic expression of DUX4 in FSHD muscle and the limitations of short-read RNA sequencing challenge, however, a comprehensive grasp of its consequences on the muscle transcriptome. Here, leveraging full-length isoform RNA sequencing with short-read RNA sequencing on DUX4-inducible myoblasts, we elucidated DUX4-induced transcriptomic changes within a myogenic context. DUX4 yields a complex transcriptome featuring numerous unannotated isoforms from known and novel loci. Moreover, we observed distinct isoform usage of DUX4 target genes between myogenic and embryonic cleavage states highlighting the distinct differences between DUX4 transcription factor activity in skeletal muscle and during the cleavage stage. We also identified ~1,400 unannotated intergenic isoforms predominantly originating from repetitive elements such as LTRs, LINEs, and SINEs. Integration with available datasets delineates the transcriptional and epigenetic landscape of these loci across myogenic and embryonic backgrounds. Like the cell type-specific isoform production, the usage of DUX4 binding sites at these intergenic loci is in part cell type-specific. Collectively, these findings demonstrate substantial and context-specific transcriptomic alterations induced by DUX4 further enriching our understanding of DUX4-induced muscle pathology.

  Study EGAS50000000503

• Mapping the Evolution of T Cell States During Response and Resistance to Adoptive Cellular Therapy

  We investigated single T cell transcriptional states that define donor lymphocyte infusion (DLI) response and resistance from cryopreserved bone marrow mononuclear cells from 15 patients with relapsed chronic myeloid leukemia (CML) after allogeneic hematopoietic stem cell transplant. By integrating bulk ATAC-seq data from sorted T cell populations from these bone marrow samples, we also defined gene regulatory networks that underlay these clusters.

  Study phs002877

• DAC for a single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  Nodal B-cell non-Hodgkin lymphomas (B-NHL) are a clinically diverse set of cancers thought to originate from distinct stages of B-cell maturation. To characterize intratumor heterogeneity across B-NHL entities, we performed CITE-Seq (cellular indexing of transcriptomes and epitopes) on 51 lymph node samples including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL, n = 11) tumors, in addition to non-malignant reactive lymph nodes (rLN, n = 8). We also performed 5 prime scRNA-seq with immune receptor profiling for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL, and 2 MZL).

  Dac EGAC50000000226

• SUM-seq data for Primary T-cells differentiated to helper subtypes

  Briefly, naive CD4+ T cells were isolated from PBMCs obtained from buffy coats from three healthy human donors, and differentiated into Th0, iTreg, Th2, Th1, Th17, and IFN-β-activated subsets. This allowed us to study the differentiation of naive CD4+ T cells into distinct helper subsets under the influence of a specific cytokine environment. Following 5 days of differentiation, T cells were left unstimulated or re-stimulated with phorbol 12-myristate 13-acetate (PMA) and ionomycin to assess their functional responses. Thus, this SUM-seq experiment consisted of 36 multiplexed conditions (3 donors x 6 stimulations x with/without re-stimulation). Single-cell chromatin accessibility and gene expression data is provided as demultiplexed fastq files.

  Dataset EGAD50000001204

• cfMeDIP-seq for 18 patients with pleural mesothelioma

  The dataset contains cfMeDIP-sequencing data (bam files) for 18 plasma samples from pleural mesothelioma patients. The libraries were prepared according to the published protocol (Shen, S. Y., Burgener, J. M., Bratman, S. V. & De Carvalho, D. D. Preparation of cfMeDIP- seq libraries for methylome profiling of plasma cell-free DNA. Nat. Protoc. 14, 2749–2780 (2019)). Whole genome sequencing (WGS) was performed for pre-made libraries on NovaSeq X Plus with a 150 paired-end strategy. Low-quality reads and adapters were removed with Trim Galore version 0.6.6 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore). The trimmed reads were aligned to hg38 with Bowtie2 version 2.3.4.3. SAMTools version 1.9 was used to convert the SAM alignment files to BAM files, sort and index reads, and remove duplicates.

  Dataset EGAD50000002126

• GEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the GEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008418

• ADT/SPEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the ADT/SPEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008419

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.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/

  Study EGAS00001000947

• The landscape of cancer genes and mutational processes in breast cancer

  The landscape of cancer genes and mutational processes in breast cancer

  Dataset EGAD00001000133

• Defining T cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

  Study phs001680

• Blood Somatic Mutations in TCGA Donors Suffering from Solid Tumors

  Blood somatic mutations identified across 8,530 solid tumor patients in TCGA cohort. We reasoned that low-coverage whole-genome sequencing of blood samples routinely carried out in cancer genomics projects may be repurposed to detect clonal hematopoiesis (CH). Thus, inspired by a previous approach to identify early mutations in the development of the hematopoietic system, we implemented a pipeline to systematically carry out this "reverse" somatic mutation calling on the paired blood/tumor samples. Blood somatic mutations were called using a 'reverse' approach, in which the tumor sample taken from each patient was used as control of their germline genome. Blood somatic mutations are thus detected as variants in the blood (with respect to the human reference genome) that are absent in the tumor sample. The variant calling was carried out in our in house cluster on downloaded blood/tumor BAM files. The matched blood and tumoral BAM files -- masked and deduplicated using GATK -- of 8,530 whole-exome patients were obtained as described above. The variant calling was carried out using Strelka2 (employing default parameters) with the blood sample as the tumoral input and the tumor sample as control (reverse calling). All variants with two or more supporting reads matching the caller PASS filter and with VAF<0.5 were kept. Mutations in lowly mappable regions as defined by the DUST algorithm (k=30) and UMAP68 (36-kmers) were excluded. Contiguous variants were merged into double-base substitutions. Variants with greater frequency across the cohorts than the DNMT3A R882H or JAK2 V617F hotspot in a cohort-specific Panel of Normals and in gnomAD v2.1 were removed. This was equivalent to discarding variants present in these datasets with an allele frequency greater than 0.008 in PoN TCGA and 0.0003 in gnomAD v2.1. Additionally, common SNPs as defined by the dbSNP 151 Common UCSC track and dbSNP were excluded. Mutations within segmental duplications, simple repeats and masked regions as defined in UCSC tracks were also removed. Finally, samples with the mutation count above the 97.5 percentile of the mutation burden across the cohort were deemed unreliable and excluded for further analyses. We call the set of variants obtained after the application of these filters the full set. A more conservative subset of somatic mutations was generated from the full set of blood somatic mutations. To this end, we applied MosaicForecast, a software designed to phase mutations to polymorphisms with the aim of identifying somatic mutations in a small number of cells and also predict mosaicism for the unphased ones with a random forest classifier. As a result, we obtained a subset of mosaic-phased mutations, and a subset of mutations likely to be somatic (mosaic set).In order to obtain access to this study, please first obtain access to TCGA study (phs000178).

  Study phs002867

• WTCCC case-control study for Hypertension - Combined Controls

  WTCCC genome-wide case-control association study for Hypertension (HT) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000010

• SCLC

  The aim of this study is to use sequence data generated from 500 bp paired end reads using the Illumina platform to characterise the breakpoints of chromosomal translocations, amplifications and deletions at high resolution (to the bp).

  Study EGAS00001000009

• Saliva Microbiota of Finnish children from the PANIC study

  Saliva microbiota of 407 participants of PANIC study, is profiled with 16S rRNA gene sequencing (regions V3-V4). Amplification was performed using the TruSeq-switched tail amplicons. The sequencing was performed using the 2 × 301 base-pair on the Illumina MiSeq PE300 platform. Data includes information on sex, age, and caries status of participants. File format is fastq.gz.

  Dataset EGAD50000000989