15013 results for "cancer studies using rna-seq"

in 18.02 milliseconds.

• Shallow whole genome sequencing

  This dataset contains a collection of tumour samples from high grade serous ovarian carcinoma patients with recurrent disease collected near the point of diagnosis as well as tumour samples collected after patient relapse upon or some time after study entry. The majority of diagnosis samples were preserved in neutral buffered formalin whereas the majority of post-relapse samples were preserved in universal molecular fixative (UMFIX, Sakura Finetek USA, Inc). DNA was extracted and whole genome sequencing libraries were prepared either using the TruSeq DNA Nano kit (Illumina) or the ThruPLEX DNA-Seq Kit (Takara Bio), which were respectively sequenced at low depth (~0.1-0.5X) on illumina HiSeq 2500 and HiSeq 4000 sequencing platforms. Sequenced reads were aligned to the GRCh37 reference genome (release hs37d5).

  Dataset EGAD00001011049

• Prediction of Trastuzumab Benefit in Adjuvant Breast Cancer: Gene Expression Profiling in NSABP B31

  Background National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-31 suggested the efficacy of adjuvant trastuzumab, even in HER2-negative breast cancer. This finding prompted us to develop a predictive model for degree of benefit from trastuzumab using archived tumor blocks from B-31. Methods Case subjects with tumor blocks were randomly divided into discovery (n = 588) and confirmation cohorts (n = 991). A predictive model was built from the discovery cohort through gene expression profiling of 462 genes with nCounter assay. A predefined cut point for the predictive model was tested in the confirmation cohort. Gene-by-treatment interaction was tested with Cox models, and correlations between variables were assessed with Spearman correlation. Principal component analysis was performed on the final set of selected genes. All statistical tests were two-sided. Results Eight predictive genes associated with HER2 (ERBB2, c17orf37, GRB7) or ER (ESR1, NAT1, GATA3, CA12, IGF1R) were selected for model building. Three-dimensional subset treatment effect pattern plot using two principal components of these genes was used to identify a subset with no benefit from trastuzumab, characterized by intermediate-level ERBB2 and high-level ESR1 mRNA expression. In the confirmation set, the predefined cut points for this model classified patients into three subsets with differential benefit from trastuzumab with hazard ratios of 1.58 (95% confidence interval [CI] = 0.67 to 3.69; P = .29; n = 100), 0.60 (95% CI = 0.41 to 0.89; P = .01; n = 449), and 0.28 (95% CI = 0.20 to 0.41; P < .001; n = 442; P interaction between the model and trastuzumab < .001). Conclusions We developed a gene expression-based predictive model for degree of benefit from trastuzumab and demostrated that HER2-negative tumors belong to the moderate benefit group, thus providing justification for testing trastuzumab in HER2-negative patients (NSABP B-47). ** Reprinted from J Natl Cancer Inst;2013;105:1782-1788 with permission from Oxford University Press.

  Study phs000826

• Data upcycling, powered by EGA

  In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

  Blog data-upcycling-powered-by-ega

• Phase II Study of Cryoablation and Post-Progression Immune Checkpoint Inhibition in Metastatic Melanoma

  Percutaneous cryoablation guided by imaging is a well-established, minimally invasive treatment for oncological conditions. We posited that cryoablation could alter the immune microenvironment by directly influencing the tumor, potentially eliciting an anti-tumor response in cases resistant to immune checkpoint inhibition (ICI). In this non-randomized phase II single-center study (NCT03290677), individuals with unresectable melanoma experiencing progression on ICI underwent cryoablation in a single progressing metastasis, while ICI was continued for at least two additional cycles. The main objectives were to assess safety and feasibility and to evaluate tumor response in non-ablated lesions. Between May 2018 and July 2020, 17 patients participated in the study. The treatment regimen proved safe, revealing an objective response rate of 23.5% and a disease control rate of 41% (comprising 4 partial responses and 3 stable diseases). In our investigation into the factors influencing response to cryoablation therapy in ICI-resistant melanoma, we conducted single-cell RNA sequencing (scRNA-seq) using both 10x Genomics and Smart-seq2 technologies on biopsies from metastatic sites of 15 patients. We collected pre-treatment samples from all patients and post-treatment samples from 5 patients, totaling 20 samples. After quality control, excluding cells specific to anatomical sites or rare cell types (e.g., alveolar type II, neurons), and batch correction, we analyzed 49,071 single cells spanning melanocyte, endothelial, stromal, T, myeloid, and B/plasma cell lineages. Differential gene expression (DGE) analysis between myeloid cells identified the genes MARCKS and IL10, two genes involved in anti-inflammatory responses that can inhibit macrophages activation to be associated with failed response. Moreover, DGE analysis of T cells identified the gene TXK, which acts as a Th1 transcription factor, and the gene CMKLR1 (chemerin-like-receptor-1), which triggers migration of CD8 T-cells to be upregulated in patients who benefited from cryoablation treatment. In contrast, MTHFD2 and GGH, two genes involved in one-carbon metabolism and the folate cycle, were upregulated in T cells from patients who did not respond to therapy. Our analysis revealed a significant increase in B/plasma cells in patients who responded positively to the therapy combination, along with an enrichment of oxidative phosphorylation in T cells among non-responsive patients with progressive disease. These findings advocate for further investigation into this innovative and synergistic therapeutic approach.

  Study phs003579

• CTCF-ChIP-Seq of cohesin-mutated and wildtype adult AMLs

  ChIP-Seq targeting CTCF in cohesin-mutated (STAG2 or RAD21 mutations) and wildtype adult AMLs (CTRL-AMLs).

  Dataset EGAD00001011200

• CPC-GENE H3K27ac ChIP-seq

  CPC-GENE H3K27ac ChIP-seq data comprises 48 tumour samples and 6 benign samples sequenced with single end Illumina HiSeq 2000.

  Dataset EGAD00001010296

• BLUEPRINT Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

  Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

  Study EGAS00001001638

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Study EGAS00001006935

• Myeloid-specific KDM6B inhibition sensitizes Glioblastoma to PD1 blockade

  This data set include FASTQ files for five experiments: Human scRNA-Seq data (6 samples), Human Visium spatial transcriptomic data (3 samples), Mouse scRNA-seq data (4 samples), Mouse scATAC-seq data (2 samples), Mouse ChIP-seq data (8 samples). For the mouse scATAC-seq data (2 samples), there are originally three FASTQ files, R1, R2 and R3 files. The R1 and R2 FASTQ files were merged into one larger file ("R1R2") per sample for submission as paired-end sequencing setting to follow the EGA guidelines. They can be split into individual R1 and R2 files in order to be processed by Cell Ranger software. The files with IC1 suffix are CHIP-seq Input control for anti-KDM6B antibody pull down experiments and the files with IC2 suffix are CHIP-seq Input control for anti-H3K27ME3 antibody pull down experiments in murine model.

  Dataset EGAD00001010073

• Whole exome sequencing of tumors from the Precision Medicine Program in Pediatric and Adolescent Patients with Recurrent Malignancies

  Sequencing libraries were constructed according to standard procedures from 600 ng of tumor and paired constitutional DNA. WES was captured using Agilent SureSelect V5 (50 Mb), Clinical Research Exome (54 Mb) kit, SureSelect XT human All exon CRE version 1 or 2, or Twist Human Core Exome Enrichment System. Sequencing of subsequent libraries was performed using Illumina sequencers (Next-Seq 500 or Hiseq 2000/2500/4000) in 75 bp paired-end mode, aiming for a mean depth of coverage of 100x.

  Dataset EGAD00001010928

• Reference epigenome ADMSC02_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC02_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003855

• Reference epigenome ADMSC01_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC01_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003854

• Chip-Seq sequencing data of Atypical teratoid/rhabdoid tumors (ATRT)

  Chip-Seq sequencing data of Atypical teratoid/rhabdoid tumors (ATRT)

  Dataset EGAD00001003408

• Reference epigenome ADMSC04_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC04_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003857

• Reference epigenome ADMSC03_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC03_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003856

• Single cell and plasma RNA sequencing

  Single cell and plasma RNA sequencing for RNA liquid biopsy for hepatocellular carcinoma

  Study EGAS00001005194

• ChIP-seq fastq and alignment files

  ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

  Dataset EGAD00001006279

• Gene regulation of human CD4+ Treg ChM-seq

  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). The final quality filtered set included 91 individuals with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq.

  Dataset EGAD00001004828

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Dataset EGAD00001002738

• 13 WGS and 8 TCS data of ENKL patients treated with pembrolizumab.

  Whole-genome sequencing (WGS) was performed for 13 pairs of tumor-normal samples from patients diagnosed with NKTL. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 2000 or HiSeq X Ten as 2x101 bp or 2x151 bp, respectively. 8 NKTL FFPE specimens were screened for somatic mutations using deep targeted capture sequencing (TCS). FFPE rolls or slides were extracted using QIAamp DNA FFPE Tissue kit (QIAGEN). The FFPE genomic DNA was treated with NEBNext FFPE DNA Repair Mix and assessed by Quant-it PicoGreen dsDNA Assay Kit (Invitrogen). The library was generated from 10-200 ng DNA with SureSelectXT Low Input Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent Technologies) according to manufacturer’s instructions. RNA based probe was designed with SureDesign (Agilent Technologies) to target-capture 140 genes. Next, the captured libraries were pooled in equimolar concentration and sequenced on Illumina Novaseq 6000 platform with SP or S1 chip. Reads aligning to 40 selected genes were isolated post-alignment for this submission. Prefix used in filenames: T - Tumor samples N - Matched-Normal samples

  Dataset EGAD00001004140

• Versatile workflow for cell-type resolved transcriptional and epigenetic profiles from cryopreserved human lung

  The complexity of the lung microenvironment and changes in cellular composition during disease progression make it exceptionally hard to understand molecular mechanisms leading to the development of chronic lung diseases. Although recent advances in cell-type resolved and single-cell sequencing approaches hold great promise for studying complex diseases, their implementation relies on local access to fresh tissue, as traditional tissue storage methods do not allow viable cell isolation. To overcome these hurdles, we developed a novel, versatile workflow that allows long-term storage of human lung tissue with high cell viability, permits thorough sample quality check before cell isolation, and is compatible with sequencing-based profiling, including single-cell approaches. We demonstrate that cryopreservation is suitable for the isolation of multiple cell types from human lung and is applicable to both healthy and diseased tissue, including COPD and tumour samples. Basal cells isolated from cryopreserved airways retain the ability to differentiate, indicating that cellular identity is not altered by cryopreservation. Importantly, using RNA sequencing and EPIC Array, we show that genome-wide gene expression and DNA methylation signatures are preserved upon cryopreservation, emphasizing the suitability of our workflow for -omics profiling of human lung cells. In addition, we obtained high-quality single-cell RNA sequencing data of cells isolated from the cryopreserved human lung, demonstrating that cryopreservation empowers single-cell approaches. Overall, thanks to its simplicity, our cryopreservation workflow is well-suited for prospective tissue collection by academic collaborators and biobanks, opening worldwide access to human tissue.

  Study EGAS00001004477

• TGS - Comprehensive Molecular Characterization of Colorectal Cancer Metastases (2015-07-02)[MOSAIC]

  Systematic next generation sequencing efforts are beginning to define the genomic landscape across a range of primary tumours, but we know very little of the mutational evolution that contributes to disease progression. We therefore propose to obtain a comprehensive description of genomic, transcriptomic and epigenomic changes in a cohort of matched primary and metastatic colorectal cancers, and additionally to explore the extent to which those mutations identified as recurrent in the metastatic setting are able to subvert normal biological processes using both genetically engineered mouse models and established cancer cell lines. This study will enable us to define to what extent primary tumour profiling can capture the biological processes operative in matched metastases as well as the significance of intratumoural heterogeneity. This dataset contains all the data available for this study on 2015-07-02.

  Dataset EGAD00001001426

• bulk TCR seq

  bulk TCR-seq data IMCISION on the PBMCs of responding patients bulkTCR-seq data generated with the immunoSEQ platform (Adaptive Biotechnologies) on PBMCs of responding patients, pre- and post-treatment.

  Dataset EGAD00010002546

• Integrated Analysis of Multimodal Single-Cell Datasets for SARS-CoV-2 Vaccination

  The study aimed to explore immune responses during a time course of BNT162b2 mRNA vaccination. To better characterize these responses, we utilize a suite of multi-modal single-cell sequencing technologies to identify and characterize antigen-specific CD8+ T cells. We leverage an integrative analysis strategy to characterize five molecular modalities in these cells. Our dataset enables the discovery of new subpopulations, molecular signatures, and developmental regulators of these cells. Moreover, we identify these cells in SARS-CoV-2 infected patients and demonstrate their positive predictive value for subsequent clinical recovery. The sequence data of CITE-seq, ASAP-seq and ECCITE-seq experiments are deposited in dbGaP. Peripheral blood mononuclear cell (PBMC) samples for CITE-seq and ASAP-seq were collected from six healthy donors at four time points: immediately before (Day 0) vaccination, after primary vaccination (Day 2, Day 10), and seven days after boost vaccination (Day 28). PBMC samples for ECCITE-seq were collected from eight healthy donors on Day 28.

  Study phs003322

• Single-cell transcriptome of T-ALL P1

  In this study, we profiled single-cell transcriptome (10X genomics) of Patient-derived xenografts (PDX) T-ALL replase samples from P1 patient. Primary human T-ALL cells were recovered from cryopreserved bone marrow aspirates of patients enrolled in the ALL-BFM 2009 study. Patient-derived xenografts (PDX) were generated as previously described by intrafemoral injection of 1 Million viable primary ALL cells in NSG mice110 PDX-derived (P1)28 cells were frozen until processing. For scRNA-seq library preparation, cryopreserved cells were thawed rapidly at 37 ℃ and resuspended in 10 ml warm Roswell Park Memorial Institute (RPMI) medium with 100 μg/ml Dnase I. Cells were centrifuged for 5 mins at 300 g, and resuspended in ice-cold phosphate buffered saline (PBS) with 2% foetal bovine serum (FBS) and 5mM EDTA. Cells were stained on ice with anti-murine-CD45-PE (mCD45)(clone 30-F11; BioLegend; 1:20) in the dark for 30 mins. 1:100 DAPI was added and incubated in the dark for 5 mins before sorting. Triple negative cells (DAPI-mCD45-GFP-) were sorted (Fig. S27) using a BD FACSAria™ Fusion Cell Sorter into ice cold 0.03% bovine serum albumin (BSA) in PBS. All isolated cells were immediately used for scRNA-seq libraries, which were generated as per the standard 10x Genomics Chromium 3′ (v.3.1 Chemistry) protocol. Completed libraries were sequenced on a NextSeq5000 sequencer (HIGH-mode, 75 bp paired-end).

  Dataset EGAD00001008325