15040 results for "cancer studies using rna-seq"

in 81.28 milliseconds.

• Single-cell profiling of neoantigen-specific T cells in lung cancers treated with neoadjuvant PD-1 blockade

  This dataset includes 406 samples from non small cell lung cancer patients treated with neoadjuvant anti-PD-1. The Single Cell 5’ V(D)J and 5’ DGE kits (10X Genomics) were used to capture immune repertoire information and gene expression from the same cell in an emulsion-based protocol at the single cell level. Libraries were generated and sequenced on an Illumina NovaSeq instrument using 2x150bp paired end sequencing.

  Dataset EGAD00001007728

• Whole genome sequencing with linked reads of pediatric glioblastoma samples

  Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand mechanisms of tumor evolution in this cancer, we performed whole genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of non-synonymous single nucleotide variants being shared in diagnostic-recurrent pairs. In order to track the origins of the mutational events we observed in pGBM, we generated whole genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) arose de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. Interestingly, radiation and anti-mitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, since slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and to accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM.

  Study EGAS00001003432

• Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

  Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

  Study EGAS00001003964

• Acute Respiratory Distress Network (ARDSNet) Studies 01 and 03 Lower Versus Higher Tidal Volume, Ketoconazole Treatment and Lisofylline Treatment (ARMA/KARMA/LARMA) (ARDSNet-ARMA/KARMA/LARMA-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ARMA/KARMA/LARMA include plasma, serum and urine. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The ARDS Network is a consortium of clinical centers and a coordinating center to design and test novel therapies for the treatment of Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). The primary objective of the KARMA trial was to investigate the efficacy and safety of Ketoconazole and Respiratory Management in the treatment of ALI and ARDS. The Ketoconazole arm of the study was later stopped due to an inability to show efficacy. Participants continued to be randomized to the respiratory management arms of the study (ARMA), which compared two ventilator strategies: a tidal volume of 6 mL/kg versus 12 mL/kg. The LARMA phase of the study investigated the efficacy of Lisofylline and Respiratory Management. Background Participants suffering from ARDS are extremely ill, require mechanical ventilation and, despite improvements in medical care and technology, had a mortality rate as high as 50 percent. An excessive inflammatory response is characteristic of ALI of which ARDS represents the most severe end of the pathophysiologic spectrum. The inflammatory response includes increased numbers of neutrophils activated to produce cytokines, proteases, and reactive oxygen intermediates. Pulmonary injury may also be enhanced by alveolar and tissue macrophages as a producer of vasoactive substances, neutrophil chemoattractants, and procoagulant substances. Ketoconazole, a synthetic antifungal imidazole, also has anti-inflammatory activities and may inhibit neutrophil recruitment via several different pathways known to be involved in the development of ALI and ARDS. Lisofylline causes a marked decrease in the circulating levels of the major oxidizable species of free fatty acids and also inhibits proinflammatory intracellular signaling. Mechanical ventilation in participants with ALI and ARDS have traditionally used tidal volumes of 10 to 15 ml per kilogram of body weight. These large tidal volumes are often necessary to achieve normal partial pressure of arterial carbon dioxide and pH, but may induce inflammatory responses through disruption of pulmonary epithelium and endothelium. Mechanical ventilation at lower tidal volumes may reduce injurious lung stretch and decrease the inflammatory response. Participants The Ketoconazole and Lisofylline trials were designed as 2 x 2 factorials and included 220 participants in each trial. A total of 860 participants were randomized into the ventilator management trial. Participants enrolled in the Lisofylline or Ketoconozole studies had to be concurrently enrolled in the ventilator management study and were first randomized into a ventilator strategy and then to drug or placebo. Conclusions Ketoconazole was found to be safe but did not reduce mortality, duration of mechanical ventilation, or improve lung function. Lisofylline was also found to be safe and to have no beneficial effect for participants with ALI or ARDS. Ventilation at lower tidal volumes resulted in reduced mortality and an increase in the number of days without ventilator support. (PMIDs: 10789668, 11902249, 10793162).

  Study phs003734

• Whole genome sequencing of 63 single cells isolated from bone marrow aspirates of six non-metastatic breast cancer patients after staining for disseminated tumor cells.

  Dataset EGAD00001002745

• SAFIR02_Cytoscan

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Dataset EGAD00010002239

• cfDNA dataset with expanded panel for cfDNA cohort

  Cell free DNA sequencing data for 9 samples with expanded panel across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000667

• TCR β-chain repertoire sequences of regulatory and conventional T cells in peripheral blood from breast cancer patients and healthy individuals

  Dataset EGAD00001004385

• WGS of kidney cancer organoid biobank

  Dataset EGAD00001005319

• Epigenetic Intratumor Heterogeneity and Clonal Evolution in Aggressive Prostate Cancer

  Our study investigated the spatial epigenome variation within 5 aggressive prostate adenocarcinomas.

  Study EGAS00001000682

• Cell_lines_with_telomere_fusion_induced_rearrangements

  Whole-genome somatic rearrangement and point mutation analysis in cell lines with induced telomere fusions.

  Study EGAS00001001059

• Orphan_Tumour_Study___RNAseq

  The aim of this study is to study the genomes of ultra rare childhood tumours

  Study EGAS00001002534

• CRISPR_screen_M14__NCI_H3122

  Genome wide CRISPR screen was performed to find resistance to targeted drugs for melanoma and lung

  Study EGAS00001001060

• Targeted_sequencing_of_embryonic_variants___Warm_Autopsy

  Targeted sequencing of variants previously identified as embryonic from phylogenetic tree building of LCM WGS of PD28690.

  Study EGAS00001003952

• Hyperpolarized 13C MRI in breast cancer

  Transcriptomics for samples obtained from six patients (MBR01, MBR03, MBR05, MBR07, MBR10, MBR11)

  Dataset EGAD00001005760

• OT2_Illumina_RNA_T_CELL

  RNAseq on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer primary tumor sample (OT2_cohort)

  Dataset EGAD00001003368

• Illumina_RNA_MET-CELL

  RNAseq on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample

  Dataset EGAD00001002073

• Illumina_RNA_MET

  RNAseq on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample

  Dataset EGAD00001002072

• OT2_Illumina_WXS_MET_CELL

  Whole-exome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003380

• Integrated Genomic, Epigenetic, and Expression Analyses of Ovarian Cancer Cell Lines

  In this dataset there are 55 whole genome sequencing samples of epithelial ovarian carcinoma (bam files).

  Dataset EGAD00001004532

• Illumina_RNA_T-CELL

  RNAseq on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002078

• OT2_Illumina_WGS_T_XEN

  Whole-genome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer primary tumor sample (OT2_cohort)

  Dataset EGAD00001003376

• Illumina_WGS_MET

  Whole-genome sequencing on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample

  Dataset EGAD00001002084

• BC WGS Dataset 1

  Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

  Dataset EGAD00001001350

• OT2_Illumina_WGS_MET_CELL

  Whole-genome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003373

• OT2_Illumina_WXS_T_XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer primary tumor sample (OT2_cohort)

  Dataset EGAD00001003384

• Illumina_WGS_T-CELL

  Whole-genome sequencing on Illumina HiSeq2000/2500 of PDO culture derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002089

• EPO2_Illumina_RNA_XEN

  RNAseq on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from colorectal cancer primary tumor sample (EPO2_cohort)

  Dataset EGAD00001003362

• Genomic characterization of pancreatic tumours and matched xenograft and organoid models - WGS mapped reads

  Whole Genomes Define Concordance in Matched Primary, Xenograft, and Organoid Models of Pancreas Cancer - WGS mapped reads

  Dataset EGAD00001003586

• Colorectal Microenvironment Spatial Mapping Dataset

  Two samples derived from a colorectal cancer female patient - tumor tissue and normal adjacent tissue analyzed via Visium Spatial Gene Expression.

  Dataset EGAD00001015675

• CDK4/6 inhibition in advanced chordoma: final results of the NCT PMO-1601

  Background. Chordoma is a rare bone tumor with no approved systemic therapy. Inactivation of the tumor suppressor p16 (encoded by CDKN2A) leads to aberrant cyclin D-CDK4/6-RB pathway activity, which can be inhibited by palbociclib in chordoma cell lines. Patients and Methods. We conducted a phase II single-arm, open-labeled trial on palbociclib in adult patients with advanced chordomas with p16 loss (by immunohistochemistry) or CDKN2A loss (by genomic analysis) and CDK4/6 and RB1 presence (by immunohistochemistry or RNA-Sequencing). Patients received 125mg palbociclib once daily for 21 days in a 28-day cycle. The study used a Simon optimal 2-stage design. The primary endpoint was disease control rate after six cycles. Response was evaluated according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Secondary endpoints included progression-free survival, overall survival, and biomarker analysis. The study was considered positive if 25% of patients reached the primary endpoint. Results. Between December 2017 and April 2023, 28 patients (median age 60 years, range 31-84) were enrolled. After a median follow-up of 28 months, the disease control rate was 39%, with 11 out of 28 patients achieving stable disease. No objective responses were observed. The median progression-free survival was 5.6 months, and the median overall survival was 24.6 months. Treatment was well tolerated without new safety signals. CDKN2A deletions were the most common genomic alterations underlying p16 loss and were accompanied by MTAP co-deletion. There was no correlation between responder phenotypes by immunohistochemistry and outcome. RNA-based analysis showed heterogeneous pathways deregulation at study entry suggesting underlying primary resistance mechanisms Conclusion. This trial met its primary endpoint with a 39% disease control rate, though antitumor activity was modest. Molecularly tailored combination therapies should be considered to improve efficacy. (ClinicalTrials.gov number, NCT03110744).

  Study EGAS00001007985

• Molecular characterization of Barrett’s esophagus at single cell resolution

  Backgrounds & Aims: Patient with Barrett’s esophagus (BE) have an increased risk to develop esophageal adenocarcinoma and are under periodical endoscopic surveillance for malignant transformation. Pathologists distinguish between different BE stages to identify high-risk patients, but this process remains difficult as stage-specific markers are still missing. We established BE organoid cultures, applied single cell sequencing approaches to identify differences in gene expression and genomic alterations, and validated candidate genes for their predictive value on histological sections. Methods: We collected 43 epithelial biopsies from 21 patients, established organoids for the clonal expansion of matching healthy and diseased tissue from two patients to identify genomic alterations by whole genome sequencing (WGS). We performed single cell DNA-sequencing (scDNAseq) to analyse DNA alterations within biopsies from 8 patients and single cell RNA-sequencing (scRNAseq) to identify gene expression differences between BE stages from 19 patients. Candidate marker genes were then validated by RNA in situ hybridization experiments on histological resection specimen. Results: Most BE biopsies were chromosomal stable (CS) and their single base substitution (SBS) signatures were indistinguishable from the healthy control tissues. Dysplastic BE cells contained areas of chromosomal instabilities (CIN), which differed by the presence of the SBS17 signatures from biopsy-matching CS cells or patient-matching healthy control cells. Such CIN areas affected efficient clustering of the scRNAseq data. We identified two sets of marker genes (SLC5A5, PSCA, LIPF and ANPEP, CEACAM6, REG4), which distinguish columnar BE epithelium from non-dysplastic/dysplastic stages. CLDN2 allowed the distinction between dysplastic and more advanced stages as its expression level increased and spread in dysplastic BE glands. Conclusions: Molecular characterization of BE samples identified a correlation between the presence of CIN and COSMIC signature 17, and we report seven marker genes that help in distinguishing different BE stages.

  Study EGAS00001005221

• Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution

  We have used next generation sequencing to sequence genomes (>43-fold coverage) and transcriptomes of an oestrogen-receptor-alpha-positive metastatic lobular breast cancer at depth. We found 32 somatic non-synonymous coding mutations present in the metastasis, and measured the frequency of these somatic mutations in DNA from the primary tumour of the same patient.

  Study EGAS00000000054

• Molecular Analysis of Alliance A031201 Study

  This is the first study examining the relationship between clonal hematopoiesis and clinical outcomes in prostate cancer patients. We used a targeted gene sequencing panel to identify patients in the A031201 clinical trial with and without clonal hematopoiesis. We found that clonal hematopoiesis did not affect overall or progression free survival in A031201 but was associated more adverse cardiac events.

  Study phs003717

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000737

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000564

• mutational landscape of normal human breast

  The accumulation of somatic mutations in the healthy breast throughout life and pregnancy is poorly understood. Here we describe whole genome sequencing analysis of epithelial and stromal compartments from the normal breast. We aimed to study how pregnancy and age affect both the mutational burden and the clonality of the healthy breast, and the subsequent implications on breast cancer risk.

  Study EGAS00001004672

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (Exome) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006932

• ENU-CCK-81 cetuximab pilot project

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC.

  Dataset EGAD00001001947

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (WG)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010111

• Early onset sporadic rectal cancer exome from Indian population

  Paired tumor-normal exome data from 47 Microsatellite stable Early-onset sporadic rectal cancer exome from the Indian population

  Dataset EGAD00001008504

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005991

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (WG) (2020-02-20)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005990

• March 2018 cumulative data release 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.

  March 2018 cumulative data release (bams,fastqs) 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

  Dataset EGAD00001003963

• ENU-NCI-H508-Cetuximab-SecondRound

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Dataset EGAD00001002065

• ENU-NCI-H508 cetuximab fixed concentration project

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Dataset EGAD00001001948

• March 2019 data update 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.

  March 2019 data update for cord blood CD34+CD38-, CMP, GMP, MEP, monocyte, erythroid precursor, B cell and primary AML total blasts reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium. This dataset contains data for samples: CEMT0158 CEMT0159 CEMT0160 CEMT0161 CEMT0162 CEMT0163 CEMT0164 CEMT0165 CEMT0166 CEMT0167 CEMT0168 CEMT0169 CEMT0170 CEMT0171 CEMT0172 CEMT0189

  Dataset EGAD00001004950

• 76 cancer and normal whole genomes from eleven SI-NET patients

  This dataset comprises of 76 cancer and normal whole genomes obtained from 11 SI-NET patients, in the form of two fastq files (forward and reverse reads) for each genome containing sequences generated by Illumina NovaSeq 6000 system.

  Dataset EGAD00001006161

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38233 (WG) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006930

• PyEGA3 download client

  PyEGA3 Checks prior to download - Is the dataset available for download? Most datasets are available using the PyEGA3 Download client, except for specific legacy datasets. For these ones, refer to Live Outbox distribution, an alternative way to download these datasets.If the dataset you've been granted access to begins with the ID EGAD5XXXXXXX, please refer to the Live Outbox distribution. If the dataset you have been granted access to contains encrypted data (filename ending in .gpg), contact EGA Helpdesk for detailed information on how to download these files.General Information The PyEGA3 download client is available at its GitHub repository. In its README you will find a step by step guide on how to use it to download files you have been granted access to. PyEGA3 implements the GA4GH-compliant HTSGET protocol supporting requests over genomic ranges. This enables the download of specific regions of interest rather than the entire file. HTSGET is not possible for all the files held by EGA: if the dataset does not contain index files (e.g. filename ending in *.crai), then genomic range requests cannot be performed. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Check out our video tutorial! Frequently Asked Questions General questions How do I download the datasets to which I have been granted access? After setting up your EGA download account, you can proceed to download using the EGA download client – PyEGA3. The pyEGA3 download client is a python-based tool for viewing and downloading files from authorised EGA datasets. This download client is continuously being developed for more user-friendly download experiences. Can I download the dataset’s metadata via the download client? No, the download client cannot be used to download metadata. Registered EGA users can download metadata of an authorised dataset by logging into the EGA webpage and navigating to the dataset of choice. Approximately two thirds down the page you will find the option to download the metadata as a zip file. How do I download large datasets as quickly as possible? The main EGA download client is pyEGA3 download client, a python-based tool for viewing and downloading files from authorised EGA datasets.We could exceptionally consider the option of an Aspera download for users experiencing very slow download rates or facing particular issues.Contact the EGA Helpdesk for further information. Pre-requirement and Installation What are the major requirements for the PyEGA3 download client installation and usage? The PyEGA3 client is compatible with any OS with Python 3.6+ installed. The client requires a connection to the internet, sufficient space on the destination drive, and the EGA download account credentials. Where can I find the PyEGA3 download client installation and download instructions? We strongly recommend checking our video tutorial demonstrating the usage of PyEGA3 from installation to file download. More detailed information is available at PyEGA3 GitHub. What ports are required for the PyEGA3 download client to function? PyEGA3 makes HTTPS calls to the EGA Data API (https://ega.ebi.ac.uk:8443). This port 8443 must be reachable from the location where PyEGA3 is executed to avoid timeouts. PyEGA3 download client How to update the PyEGA3 download client to be on the latest version? Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 --upgrade I do not have an active EGA account. Can I test the download with the PyEGA3 download client? An EGA download test account (ega-test-data@ebi.ac.uk) has been created for troubleshooting and training purposes. The test account does not require an EGA username and password because it contains publicly accessible files from the 1000 Genomes Project. More information about the use of this account and log in details are available at pyEGA3. I lost my connection while the download was in progress. Does this mean that I have to download the file again from the start? The PyEGA3 download client supports automatic resumption of downloads. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the resume feature, downloads will automatically resume if you encounter any errors or if the connection is interrupted. How can I improve the overall download speed of the PyEGA3 download client? Download speeds can be optimised using the --connections parameter which will parallelise download at the file level. If the --connections parameter is provided, all files >100Mb will be downloaded using the specified number of parallel connections. It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Why is my file taking a long time to be saved? Please note that when a file is being saved, it goes through two processes. First, the downloaded file "chunks" are pieced back together to reconstruct the original file. Secondly, PyEGA3 calculates the checksum of the file to confirm that the file was downloaded successfully. Larger files will take more time to reconstruct and validate the checksum. Why is the HTSGET protocol not working with my dataset of interest? PyEGA3 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file, saving both time and storage space. Please note that in order for the genomic range requests to work for a BAM, CRAM or VCF file there must be an associated BAI, CRAI or TBI file, respectively. If the dataset does not contain these index files then genomic range requests cannot be performed. After download Do I need to decrypt data files downloaded through the pyEGA3 download client? Files are transferred over secure HTTPS connections and received unencrypted, thus there is no need for decryption after data download. What is the purpose of an MD5 file? After the download completes, file integrity is verified using checksums. The PyEGA3 download client automatically verifies each file’s unencrypted md5 after download to ensure that the file was downloaded correctly from the EGA. Errors Why do I get a “400 Client Error” while trying to access the download client? Ensure that your credentials are formatted correctly. Please contact the EGA Helpdesk if you are unsure about your account’s username (i.e. your email address). Why do I get a “500 Server Error”? It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Otherwise, 500 server errors are internal server errors from EGA’s end. Retry after some time and, if the 500 error persists: check our homepage or Twitter for any outage information or report it to EGA Helpdesk. Why do I get a “slice error”? This type of error occurs when one slice download was prematurely interrupted. Please re-start the same download. The download client will pick up any partial download and download any missing slices. Why do I get the error “Dataset' EGADXXXXXXXXXXX' is not in the list of your authorised datasets”? Please note that the data access was given to the email (username) provided to the Data Access Committee (DAC) in your official request. Therefore, you shall check that the account that you are using is the same one that you sent to the DAC. Why do I get “ERROR:root:Failed to obtain IP address”? This might mean that the connection ports are blocked. Check that the port 8443 is reachable.In case the port is reachable and the error persists, please try to modify the file pyega3.py on line 44 in the python module installation: Replace endpoint = 'https://ipinfo.io/json' with endpoint = 'https://api.myip.com' Why do I get the error “Invalid username, password or secret key - please check and retry”? Make sure that you are using the correct credentials (username and password) and there is no typo. Contact EGA Helpdesk if the problem persists.

  Documentation access/download/files/pyega3

• Genomic Resistance Patterns to Second Generation Androgen Blockade in Paired Tumor Biopsies of Metastatic Castrate-Resistant Prostate Cancer

  We examined genetic resistance to second generation androgen targeting therapies (abiraterone acetate or enzalutamide) by analyzing whole exome sequencing of patient-matched pre-treatment and post-resistance tumors from a series of castrate-resistant prostate cancer (CRPC) patients. Abiraterone resistant tumors harbored alterations in AR and MYC, whereas patients treated with enzalutamide had acquired alterations in the cell cycle pathway. We experimentally confirmed expression of cell-cycle kinases sufficed to drive enzalutamide resistance, which was mitigated through CDK4/6 blockade. These observations link genetic resistance to specific therapeutic agents to inform strategies in genomically selected advanced CRPC.

  Study phs001447

• Radiation-Related Genomic Profile of Papillary Thyroid Cancer after the Chernobyl Accident

  The April 26, 1986 accident at the Chernobyl nuclear power plant in northern Ukraine resulted in the release of radioactive contaminants, which were deposited in the surrounding areas in Ukraine, Belarus, and Russia. The main radiation-related health effect resulting from these exposures is the increased occurrence of thyroid cancer among individuals who were children at the time of the accident or born shortly thereafter. The purpose of this study was to conduct a comprehensive genomic landscape analysis of papillary thyroid tumors arising in individuals who were exposed as children to radioactive iodine (I-131) from the Chernobyl nuclear power plant accident.

  Study phs001134

• Sensitive urothelial cancer detection via high volume urine DNA analysis

  Cystoscopy and imaging are the gold standard for urothelial cancer (UC) detection and surveillance, but cystoscopy is an uncomfortable procedure associated with adverse effects and a low diagnostic yield as only 10% of hematuria patients have UC. Urine tumor DNA (utDNA) is a non-invasive UC biomarker that has suffered from poor sensitivity for Ta stage tumors (<80%). We hypothesized that high urine volume analysis with a multi-gene panel could overcome these limitations, and developed a 100 mL utDNA laboratory platform (UroScout) that analyzes 25 commonly mutated UC genes and 8 copy number-altered loci for somatic alterations to detect UC.

  Study EGAS50000000630

• plasma DNA LINE-1 targeted bisulfite sequencing: a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Study EGAS50000000446

• scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment.

  We performed scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment. In order to identify tumor-specific T cells, we selected CD8 T cells that were enriched in the tumor of the patient. We also selected CD8 T cells appearing in the bladder after BCG treatment, with the hypothesis that BCG treatment stimulates tumor-specific CD8 T cells. Next, we cloned the TCR of these T cells in a Jurkat cell line and tested these TCR for recognition of tumor-specific antigens.

  Study EGAS50000001384

• Rapid response of APC/TP53/KRAS mutated stage IV colorectal cancer under FOLFIRI + Bevacizumab detected by liquid biopsy: a case report

  In our non-interventional liquid biopsy study, a male patient in his fifties diagnosed with stage IV colorectal cancer and polytope liver metastases rapidly progressed after completing chemotherapy and deceased 8 months after diagnosis. Retrospective cell free DNA testing showed that the APC/TP53/KRAS major clone responded quickly after 3 cycles of FOLFIRI + Bevacizumab. Retrospective exome sequencing of pre-chemotherapy and post-chemotherapy tissue samples including metastases confirmed that the APC/TP53/KRAS and other major clonal mutations (GPR50, SLC5A, ZIC3, SF3A1 and others) were present in all samples. After the last chemotherapy cycle,

  Study EGAS00001004088

• Inter and intra - tumor heterogeneity in Colorectal Cancer

  We used high depth massive parallel sequencing analyses to study 27 CRC (colorectal cancer) patients, with a total of 97 tumors (both primary and matched metastases) in addition to healthy control samples. We found inter-tumor concordance for coding mutations; in contrast, gene copy numbers were found to be highly discordant between primary tumors and metastases as validated by fluorescent in-situ hybridization. in a further step, we dissected a single tumor into 68 spatially defined samples and sequenced them separately. Here we identify evenly distributed coding mutations in APC and TP53 in all tumor areas, yet highly variable gene copy numbers in numerous genes.

  Study EGAS00001002150

• Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

  The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying ‘personal’ gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genome of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers.

  Study EGAS00001002571

• Combination Therapies for Personalised Cancer Medicine in 11-18

  This study involves mutagenizing 11-18 with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002579

• Exome array analysis of adverse reactions to fluoropyrimidine-based therapy for gastrointestinal cancer

  Fluoropyrimidines, including 5-fluororacil (5FU) and its pro-drug Capecitabine, are the common treatment for colorectal, breast, neck and head cancers – either as monotherapy or in combination therapy. Adverse reactions (ADRs) to the treatment are common and often result in treatment discontinuation or dose reduction. Factors contributing to ADRs, including genetic variation, are poorly characterized. We performed exome array analysis to identify genetic variants that contribute to adverse reactions.Our final dataset consisted of 504 European ancestry individuals undergoing fluoropyrimidine-based therapy for gastrointestinal cancer. A subset of 254 of these were treated with Capecitabine. All individuals were genotyped on the Illumina HumanExome Array.

  Study EGAS00001002763

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD38234__Targeted_

  Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003325

• Mutational signatures in head and neck cancer (H019)

  Genomic alterations are a driving force in the multistep process of head and neck cancer (HNC) and result from the interaction of exogenous environmental exposures and endogenous cellular processes. Each of these processes leaves a characteristic pattern of mutations on the tumor genome providing the unique opportunity to decipher specific signatures of mutational processes operative during HNC pathogenesis and to address their prognostic value. Computational analysis of whole exome sequencing data of the HIPO-HNC (n=83) and TCGA-HNSC (n=506) cohorts revealed five common mutational signatures (COSMIC signature 1, 2, 3, 13 and 16), and demonstrated their significant association with etiological risk factors (tobacco, alcohol and HPV16).

  Study EGAS00001004588

• Partner independent fusion gene detection by multiplexed CRISPR Cas9 enrichment and long read Nanopore sequencing (FUDGE)

  Targeted long-read nanopore sequencing. Abstract: Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment. Fusion gene partner choice and breakpoint-position promiscuity restricts diagnostic detection, even for known and recurrent configurations. To accurately and impartially identify fusions, we developed FUDGE: FUsion Detection from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for fusion gene driver enrichment - without prior knowledge of fusion partner or breakpoint-location – to long-read Nanopore sequencing with the bioinformatics pipeline NanoFG. FUDGE has flexible target-loci choices and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in one sequencing run. We observe on-average 665 fold breakpoint-site enrichment and identify nucleotide resolution fusion breakpoints - within two days. The assay identifies cancer cell line and tumor sample fusions irrespective of partner gene or breakpoint-position. FUDGE is a rapid and versatile fusion detection assay, providing unparalleled opportunity for diagnostic pan-cancer fusion detection.

  Dataset EGAD00001006111

• Ovarian Cancer Organoid Biobank

  WGS of ovarian cancer organoids, tumor samples and blood references. Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004387

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• Quantitative Exploratory Proteomics Analysis of Glioblastoma in Initial and Recurrent Tumors

  Shotgun Proteomics; Glioblastoma samples from 11 patients were obtained at initial and recurrent tumor stages. Proteins were extracted, identified and quantified via tandem mass spectrometry based on a TMT isobaric labelling approach. Quatitative proteomics reveals 146 differentially abundant proteins using a patient-matched statistical modelling. Analysis of proteolytic processing reveals differential proteolytic patterns in recurrent tumors. Proteogenomics reveals the presense of 30 single-amino acid variants present in glioblastoma tumor and 1 of those as increased in recurrent tumor.

  Dataset EGAD00010002350

• ATAC sequencing raw data files of human Treg cell subsets

  Assay for Transposase-Accessible Chromatin using sequencing (ATAC) sequencing of human CD38+, HLA-DR+, CD38+ HLA-DR+, and CD38- HLA-DR- regulatory T (Treg) cell subsets sorted from peripheral blood pooled from 4 healthy donors. After isolation and purification of Treg cell subsets with flow cytometry, samples were frozen and transferred to Active Motif for ATAC sequencing. The dataset contains one raw sequencing file (fastq) of accesible regions for each of the above-mentioned Treg cell subsets.

  Dataset EGAD50000000664

• Illumina GSA-MD v3 genotyping arrays for 183 samples

  Genotyping arrays for 183 samples from patients with a neuroendocrine tumor of the small intestine. All samples have been hybridized on Illumina GSA-MD v3 arrays with standard automated protocols. Reading of the chips was performed on Illumina iScan+ scanners and this file is the result of primary analysis done using Illumina GenomeStudio software. It contains data for 147 tumors, 2 adenomas, 1 lymph node, 19 mesenteric nodules, 6 liver metastasis and 8 normal ileum samples.

  Dataset EGAD50000000905

• Transcriptome sequencing of neuroendocrine tumors of the small intestine

  This dataset contains 206 RNASeq samples from a cohort of patients with neuroendocrine tumors of the small intestine. Libraries were prepared using a Illumina TruSeq Stranded mRNA kit following the manufacturer’s recommendations. Sequencing was performed on Illumina Novaseq6000 machine with a 2x75bp paired-end fashion. This dataset contains data for 169 tumors, 22 mesenteric nodules, 8 liver metastases, 2 adenomas, 1 lymph node and 4 normal ileum samples.

  Dataset EGAD50000000906

• Dataset belonging to the article "Genotyping from targeted NGS data based on a small set of SNPs correctly matches patient samples"

  This dataset consists of raw sequencing data from targeted next generation sequencing of samples from patients with chronic lymphocytic leukaemia. These samples were used to validate an approach for detection of sample mislabelling and swapping in clinical cohorts using single nucleotide polymorphisms (SNPs), as described in the associated article. The data are divided into two parts - data from the initial validation experiment (discovery cohort) and data from an additional independent cohort.

  Dataset EGAD50000000757

• Transrenal DNA Analysis

  The current sequencing dataset consists of 91 whole genome sequencing data files (Fastq files) of human cell-free DNA (cfDNA) obtained from plasma and urine samples. Specifically, we extracted 20 ucfDNA and 17 plasma DNA samples from healthy pregnant women, 11 ucfDNA samples from pregnant women with preeclampsia, 19 ucfDNA samples from healthy controls, and 24 ucfDNA samples from patients with proteinuria. These extracted cfDNA samples were then constructed into DNA libraries using the TruSeq Nano DNA Library Prep Kit (Illumina) and subsequently sequenced on the Nextseq2000 platform (Illumina).

  Dataset EGAD50000001127

• NAR-GAB 2025 deposit data

  Paired-end whole-exome sequencing data derived from Illumina hybrid-capture experiments (Agilent SureSelect Human All Exon kits). Six human probands with rare diseases; one sample per subject. Sequencing reads from each individual were processed into analysis-ready gVCF files following standard best-practice pipelines, including alignment, duplicate marking, base quality calibration, and variant calling. All gVCF files are encrypted using Crypt4GH and are available under controlled access through our DAC in accordance with a strict DUO-based policy.

  Dataset EGAD50000002100

• Shallow Whole-Genome Sequencing of Plasma ctDNA in Relapsed/Refractory Germ Cell Tumors

  This dataset comprises shallow whole-genome sequencing data (~3× coverage) of circulating tumor DNA extracted from baseline and on-treatment plasma samples of patients with relapsed or refractory germ cell tumors treated with salvage high-dose chemotherapy. Libraries were generated from 20 ng of cfDNA using the KAPA Hyper Prep protocol with unique dual indexing and sequenced on an Illumina NovaSeq 6000 platform to enable genome-wide copy number and biomarker analyses associated with treatment response and clinical outcome.

  Dataset EGAD50000002183

• Targeted Next-Generation Sequencing Data of IDH1 Exon 4 in Intrahepatic Cholangiocarcinoma Samples

  This dataset contains targeted next-generation sequencing data from 76 FFPE tumor tissues focusing on IDH1 exon 4 and codon 132. Genomic DNA was isolated using the QIAamp DNA FFPE Tissue Kit and sequenced on the Illumina MiSeq platform with 200x minimum coverage. The results are provided as encrypted somatic variant call files (VCF) generated through the Nextera XT library preparation protocol. This collection represents the specific somatic mutation profiles of the intrahepatic cholangiocarcinoma cohort for controlled access.

  Dataset EGAD50000002345

• Whole-transcriptome sequencing of MPN patients and controls.

  This dataset contains whole-transcriptome sequencing data of 113 myeloproliferative neoplasms (MPN) patients and 15 controls. Patients were diagnosed with essential thrombocythemia, polycythemia vera, primary myelofibrosis, and secondary acute myeloid leukemia. The data were pooled from 5 different sequencing experiments as indicated using an Illumina HiSeq2000 machine. All samples were sequenced paired-end. Sequenced samples were processed with custom workflows for discovery of fusion genes, SNVs and Indels calling, and identification of splicing abnormalities.

  Dataset EGAD00001004788

• WGS data subfolder HFFWLCCXY from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data (subfolder HFFWLCCXY) for multifocal ileal tumor samples from one patient. Samples were sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001008495

• Panel-based NGS data for ADME genes in human liver samples

  Panel-based next-generation sequencing data of 150 human surgical liver samples from Caucasian donors. The panel was designed for 340 ADME (absorption, distribution, metabolism and excretion) and ADME-related genes. NGS was carried out on the Illumina HiSeq2500 system (Illumina Inc., San Diego, CA, United States) at high depth with 2 × 100 bps paired-end reads. Variants were called using samtools and varscan (2.3.5). Data on n=15,727 filtered variants for the 150 patients are comprised in one vcf file.

  Dataset EGAD00001005116

• Single cell resolution of human CNV body map (2019-10-02)

  12 tissues from the warm autopsy are selected for this project. Using 10X Chromium technology we will generate ~1000 single cell/nulei genomic libraries per tissue. Each tissue will be whole genome sequenced (~2 lanes per 1000 cells) on hiseq X10. per single cell we will generate CNV profile and we investigate the level of genomic heterogenity with in tissue and across different tissues. . This dataset contains all the data available for this study on 2019-10-02.

  Dataset EGAD00001005372

• WES patient 368

  Whole Exome Sequencing of blood and FFPE tumour of patient #368.  150–300 ng of DNA was fragmented to approximately 200 bp using a focal acoustic device. Libraries were prepared with the Kapa Hyper Prep Kit and SureSelectXT adaptors. Hybridisation capture was performed with SureSelect Clinical Research Exome V2 baits following the SureSelectXT recommended protocol (Agilent). Indexed libraries were sequenced on an Illumina NovaSeq 6000 to generate paired-end 150 bp reads with average of 70-fold base coverage for the germline sample and 330-fold coverage for tumour sample.

  Dataset EGAD00001011272

• WGS data subfolder HF3NYCCXY from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data (subfolder HF3NYCCXY) for multifocal ileal tumor samples from one patient. Samples were sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001008494

• Ultra-deep sequencing of cell-free DNA derived from reference materials and a patient with asymmetric overgrowth

  This dataset contains: Ultra-deep sequencing data using the Duplex sequencing technology of: 1.) SeraSeq cfDNA reference materials with spike-in variants with allele frequencies from 0% to 5% 2.) One cfDNA sample from a CRC patient 3.) One cfDNA sample from a patient with asymmetric overgrowth Paired-end sequencing was performed with 2x151 bp reads on the NextSeq 500 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38).

  Dataset EGAD00001009784

• 33 Paired (Normal-Tumor1-Tumor2) MM whole-exome data

  Samples were sequenced from 33 multiple myeloma patients including tumor presentation and relapse samples and a matched patient control sample. Tumor DNA was isolated from CD138-positive plasma cells. Control DNA originated from peripheral blood leukapheresis products collected after induction therapy. Libraries were prepared using the SureSelectQXT sample prep kit and the SureSelect Clinical Research Exome kit (Agilent), with additional baits covering the Ig and MYC loci. Paired-end sequencing was performed to an average sequencing depth of 118× on a HiSeq2500 (Illumina).

  Dataset EGAD00001002165

• MGUS/SMM to MM WES

  This dataset contains raw sequencing reads for matched MGUS/SMM to MM patient samples, including normal germline controls. FASTQ files were generated on Illumina NextSeq 500 and HiSeq 4000 machines following exome capture using the Agilent Clinical Research Exome kit. DNA was extracted from CD138+CD38++ cells (representing MGUS/SMM/MM cells) and CD138-CD38- (representing normal cells) isolated from bone marrow. 10 patients are included with 3 samples each representing normal, MGUS/SMM, MM stages.

  Dataset EGAD00001004190

• DNA Methylation-based diagnostic biomarkers for ESCC in Han Chinese population

  To validate the methylation status of the four candidate tumor suppressor genes (ADHFE1, EOMES, SALL1, TFPI2) in Han Chinese ESCC patients, we recruited 103 patients and obtained the paired tumors(entitled as T) and adjacent normal tissues (entitled as N) as well. Targeted bisulfite sequencing was conducted to detect the methylation profiles of these four genes in these 103 paired tissues. Furthermore, the raw sequence data (fastq files) was aligned using the BSseeker2 and this dataset included all of the bam file after alignment.

  Dataset EGAD00001004288

• Genomic profiling of Follicular thyroid adenomas and carcinomas using exome-sequencing analyses

  This dataset was conceived to characterize the genomic differences among different types of follicular-like thyroid lesions. To do so, we performed whole exome sequencing experiments on human biopsies corresponding to nodular hyperplasias, follicular thyroid adenomas, follicular thyroid carcinomas and Follicular Variant Thyroid Gland Papillary Carcinomas.

  Dataset EGAD00001008022

• Pseudotime ordering of cell cycle state (2020-01-29)

  We will be using G&amp;T method to sequence single cell genome and transcriptome derived from FS13B iPSCs cell line. The cell cycle state of each of the single cells is known. Hence, we will be analysing the genome and transcriptome of single cells from each of the cell cycle state to generate a copy number profile and transcriptome profile per given cell cycle stage: G1, S, G2, S. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005919

• WGS data subfolder HFF7VCCXY from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data (subfolder HFF7VCCXY) for multifocal ileal tumor samples from one patient. Samples were sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001007075

• The impact of the human leukaemia virus HTLV-1 on host gene expression

  PBMCs were purified from blood samples of 8 HTLV-1 infected individuals, and cryo-preserved in fetal calf serum containing 10% DMSO. DNA from each samples was extracted using Qiagen Blood &amp; Tissue kit according to the manufacturer's protocol. 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 please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001004169

• WCDT Hi-C assays performed mCRPC biopsies

  Paired FASTQ files from a Hi-C assay performed on mCRPC tumors. Sequencing was performed using 150nt paired reads generated by a Novaseq 6000 instrument.

  Dataset EGAD00001009408

• Amplicon-based sequencing of drug resistant organoids

  A BRAF V600E colorectal organoid which is sensitive to MAP kinase inhibition was mutagenised with the chemical mutagen ENU and then drug selected using a combination of Trametinib, Dabrafenib and Cetuximab. Single cell derived organoids were then manually picked and expanded in drug. Resistance was confirmed in a 14 day assay and DNA was collected. These then underwent targeted amplicon-based sequencing to confirm candidate resistance effectors from a screen in 2 2D BRAF V600E colorectal cell lines. Pools of resistant clones were also sequenced.

  Dataset EGAD00001003248

• Deep WGS of matched tumor-normal pairs for HGSOC copy-number signatures study

  This dataset includes 111 bam files from WGS sequence data aligned to human genome assembly GRCh37 (hg19) from 56 tumour and matched normal samples. Libraries were constructed with ~350-bp insert length using the TruSeq Nano DNA Library prep kit (Illumina) and sequenced on an Illumina HiSeq X Ten System in paired-end 150-bp reads mode. The average depth was 60× (range 40-101×) in tumours and 40× (range 24-73×) in matched blood samples.

  Dataset EGAD00001004189

• Deep sequencing analysis of human iPSC-specific SNVs in donor cell population

  CR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. 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 EGAD00001000605

• VCF file from 16 patients affected by acute intermittent porphyria

  VCF file from 16 patients affected by acute intermittent porphyria. Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). BAM files were processed at the CNAG (Barcelona) with their pipeline, including GATK v3.6 for genotyping and other tools such as snpEff for annotating variants, to produce this VCF file with a total of 10,630,259 variants, out of which 8,731,523 are SNVs.

  Dataset EGAD00001006952

• HuBMAP: KULMAP - Human Kidney, Urinary Tract, and Lung Mapping Center

  The major goal of the Human Kidney, Urinary Tract, and Lung Mapping Center (KULMAP) is to generate multi-omic and spatially resolved molecular anatomical maps of the human bladder, ureter and kidneys (BUKMAP) and the lung airways and parenchyma (LAPMAP) at a single cell resolution. This entails sequencing of the transcriptomes and epigenomes of dissociated single cells in a massively parallel manner. These profiles will then inform on highly multiplexed RNA in situ imaging for spatial mapping of hundreds of molecular targets in the tissue sections, at a subcellular resolution. These spatial molecular maps will serve as scaffolds for computational registration of cell types and the associated transcriptome/chromatin maps to the tissue space. The combination of sequencing single dissociated cells and multiplexed in situ mapping will allow the construction of detailed spatial maps for these large organs.

  Study phs002249

• University of Texas at Austin (UTA) Histone Modification and Gene Expression Profiling in 9 Primary Glioblastoma Multiforme, 2 Anaplastic Astrocytomas and Two Meningiomas

  The primary goal of this study was to collect and analyze genomic data from primary glioblastoma multiforme tumors. Our collaborators at St David&#39;s Medical Center (SDMC) obtained informed consent from patients undergoing surgery to remove a tumor in the brain. After consent was obtained, specimens were removed from the operating suite and flash frozen in liquid nitrogen. Tumors were analyzed if they were a grade III (anaplastic astrocytoma) or grade IV glioma (glioblastoma multiforme). Tumors were transported from SDMC to UT Austin, then weighed and homogenized. Chromatin immunoprecipitation was performed for 7 proteins in each tumor (histone modifications H3K4me3, H3K4me1, H3K9ac, H3K9me3, H3K27ac, H3K27me3, and the multifunctional insulator binding protein CTCF) and no-antibody input was also sequenced. An aliquot of tumor material was set aside for isolation of total RNA.

  Study phs001389

• Modeling Malignant Progression in Glioma

  Gliomas are the most common primary brain tumor in humans. Low-grade gliomas (WHO grade II) invariably progress to high-grade gliomas (WHO grade III or IV). Although malignant progression may take many years, the survival rate after transformation to a high-grade glioma is poor, often only 12-15 months. In this data set, we have identified low-grade gliomas that have progressed to high-grade gliomas or high-grade gliomas that have progressed from low-grade gliomas. Some cases are matched pairs (meaning we have both the original low-grade tumor and the subsequent high-grade tumor). The samples deposited have been analyzed with bulk-RNA sequencing. They are also de-identified but are clinically annotated. When available, genetic information including IDH mutation status, 1p/19q deletion and histological subtype are also included.

  Study phs002607

• A Human Lymphoma Organoid Model for Evaluating and Targeting the Follicular Lymphoma Tumor Immune Microenvironment

  Heterogeneity in the tumor microenvironment (TME) of follicular lymphoma (FL) can affect clinical outcomes. We developed a new organoid culture method for cultivating patient-derived lymphoma organoids (PDLOs), which include cells from the native FL TME. We generated organoids from 12 FL patients at diagnosis, clinical progression, or relapse. These organoids were profiled with targeted DNA sequencing and mRNA sequencing. We evaluated the stability of organoids in culture at serial weekly timepoints (D0, D7, D14, D21). We treated organoids with CD19:CD3 or CD20:CD3 bispecific antibodies or unconjugated anti-CD20, anti-CD19, and anti-CD3 as a control, and profiled DNA/RNA at D11 to evaluate treatment response. This system is intended as a platform for advancing precision medicine efforts in FL through patient-specific modeling, high-throughput screening, TME signature identification, and treatment response evaluation.

  Study phs003410

• Pediatric Preclinical Testing Consortium (PPTC)

  The Pediatric Preclinical Testing Consortium (PPTC) is addressing the unmet need of streamlining the development of new therapies for childhood cancers. The PPTC seeks to develop robust biomarkers of anticancer drug activity, and the majority of these are predicted to be genetic mutations that can be detected in tumor DNA and/or RNA. In order to design the most impactful experiments that can be rapidly translated to the clinic, PPTC investigators require a complete genomic characterization of the patient-derived xenograft tumor models that are utilized across the consortium. This will not only allow for the most robust experimental design, but also will increase the engagement of industry partners who seek collaborators poised to provide the proof-of-concept necessary for drugs in their development pipelines. All data and models will be made available to academically qualified investigators.

  Study phs001437

• Recurrent CLTC::SYK fusions and CSF1R mutations in juvenile xanthogranuloma of soft tissue

  In this study, the genomic landscape of extracutaneous juvenile xanthogranuloma (JXG) was analyzed. By leveraging the Dutch Nationwide Pathology Databank (Palga), tumor samples were obtained from different academic medical centers in the Netherlands. The study was approved by the Palga Scientific Council and Privacy Committee (LZV-2016-183) and the Institutional Review Board of Leiden University Medical Center (B19.074). In addition, the study was approved by the Biobank and Data Access Committee of the Princess Máxima Center for Pediatric Oncology (PMCLAB2024.0512). Provided are whole transcriptome sequencing (WTS) data of 3 histiocytic tumors with CLTC::SYK fusions. WTS was performed in the routine workflow of the Princess Máxima Center for Pediatric Oncology (as described in Hehir-Kwa, et al. JCO Precis Oncol 2022). RNA was derived from formalin-fixed paraffin-embedded tumor tissue (n=1) or from frozen tumor tissue (n=2).

  Study EGAS50000000584

• Genetic and transcriptional landscape of plasma cells in POEMS syndrome

  POEMS syndrome is a rare paraneoplastic disease, associated with monoclonal plasma cells whose pathogenic importance remains unclear. We performed comprehensive genetic analyses of plasma cells in 20 patients with POEMS syndrome. Whole exome sequencing and targeted sequencing identified 7 recurrently mutated genes: KLHL6, LTB, EHD1, EML4, HEPHL1, HIPK1, and PCDH10. None of the driver gene mutations frequently found in multiple myeloma (MM) such as NRAS, KRAS, BRAF, and TP53 was detected. Copy number analysis showed chromosomal abnormalities shared with monoclonal gammopathy of undetermined significance (MGUS). RNA sequencing revealed a transcription profile specific to POEMS syndrome, especially in terms of tumorigenesis. Unexpectedly, disease-specific VEGFA expression was not increased in POEMS syndrome. Our study illustrates that the genetic and transcriptional profiles of plasma cells in POEMS syndrome are distinct from MM and MGUS, indicating its unique pathogenesis.

  Study JGAS000150

• Raw human sequencing data for “Characterization of intestinal immune responses in generalized human and murine lipodystrophy”

  This dataset contains raw FASTQ files generated from peripheral blood and intestinal biopsy samples collected for the study “Characterization of intestinal immune responses in generalized human and murine lipodystrophy.” Peripheral blood sequencing was performed on samples from three healthy donors as controls and from a patient with acquired generalized lipodystrophy and Crohn’s disease (AGLCD) at two distinct timepoints. Intestinal biopsy–derived immune cells were sequenced from three individuals with Crohn’s disease as disease controls, as well as from the AGLCD patient (single timepoint). The data include paired-end FASTQ files derived from single-cell RNA sequencing and T-cell receptor repertoire profiling, enabling analyses of immune composition, transcriptional states, and clonal T-cell expansion. All data are controlled-access human genomic datasets and require appropriate authorization for secondary use.

  Study EGAS50000001517

• Cell-type, allelic and genetic signatures in the human pancreatic beta cell transcriptome

  Pancreatic beta cells within the islets of Langerhans are centrally involved in the pathogenesis of both type 1 and type 2 diabetes. Describing the differentiated state of the human beta cell has been hampered so far by technical (low resolution microarrays) and biological limitations (whole islet preparations rather than isolated beta cells). We circumvent these by deep RNA sequencing of purified beta cells from 11 individuals, presenting here the first characterization of the human beta cell transcriptome. Additionally, we perform the first comparison of gene expression profiles between beta cells, whole islets (N=7) and beta cell depleted islet preparations (N=5), revealing thus beta cell specific expression signatures. Finally, we combine this with whole-genome sequencing data for 7 of our donors, describing here the first set of genetic variants controlling inter-individual variability in beta cell gene expression.

  Study EGAS00001000442

• SPECTA RP-1759-AYA Sarcoma cohort

  EORTC-SPECTA RP1759 study focuses on cancers in adolescent and young adult (AYA), age 12 to 29 years. This study explicitly recruited AYA patients and therefore collected empirical data to bridge the molecular gap between pediatric and adult oncology. The initial pilot study, activated in February 2019 across Europe, aimed to recruit 100 AYA patients (aged 12-29 years) with newly diagnosed or relapsed high-grade gliomas and high-grade bone and soft tissue sarcomas. The primary objective of the pilot is to determine feasibility and recruitment rates. Here we submit the data from patients with newly diagnosed, recurrent intermediate or high-grade sarcoma that were collected and analyzed during the study. More specifically, we submit raw FASTQ files obtained from whole exome sequencing (WES) of matching tumor and blood samples, tumor RNA sequencing and DNA methylation profiling.

  Study EGAS00001005840

• Genomic and transcriptional landscape of P2RY8-CRLF2-positive childhood acute lymphoblastic leukemia

  The mutational and transcriptional landscape of P2RY8-CRLF2-positive ALL was defined in 41 major clone fusion-positive cases including 19 matched diagnosis and relapse pairs by an integrated analysis of whole-exome and RNA sequencing. We detected a variety of frequently subclonal and highly unstable JAK/STAT but also RTK/Ras pathway activating mutations in 76% of cases at diagnosis and virtually all relapses. Unlike P2RAY8-CRLF2 that was lost in 32% of relapses, all other genomic deletions affecting lymphoid development and cell cycle remained stable. Only IKZF1 alterations predominated in relapsing cases and increased from initially 36 to 58% in matched cases. IKZF1¹s transcriptional signature revealed compromised stem cell features with signs of impaired lymphoid differentiation, enhanced focal adhesion, activated hypoxia pathway, deregulated cell cycle and increased drug resistance.

  Study EGAS00001001847

• Measuring the level of relatedness between NGS datasets

  Sequencing technologies are providing increasingly detailed insight in genetic makeup are paving their way into molecular diagnostics. The field will benefit from rigorous and bias-free measures for the quality of sequence data and for the proper representation of the complexity of the original samples. While current methodologies rely on the availability of a well-characterized reference genome, we propose kMer profiling for alignment-free assessment of the quality, comparability, and complexity of sequencing datasets. We show that kMer detects technical artefacts such as high duplication rates, library chimaeras, and differences in library preparation protocols in whole-genome, whole-exome, and RNA sequencing data. Additionally, it successfully captures the complexity and diversity of microbiomes. Thus, kMer allows for a robust evaluation of the quality and complexity of sequencing data without relying on any prior information and opens the way to a more reliable biological reasoning.

  Study EGAS00001000600

• Molecular dissection of germline chromothripsis in a developmental context

  Complex germline genomic rearrangements can affect many genes and regulatory elements, but the precise mechanisms that caused the phenotype of patients with such rearrangements are often unknown. To dissect the impact of germline chromothripsis in a relevant developmental context, we performed trio-based RNA expression analysis on blood cells,induced pluripotent stem (iPS) cells and iPS-cell derived neuronal cells from a patient with de novo germline chromothripsis and both healthy parents. In addition, we performed Hi-C on iPS cell-derived neural progenitors of the patient and the father to study the effects of the chromothripsis rearrangements on the architecture of the derivative chromosomes. We demonstrate that a combination of patient-derived iPS cell differentiation and trio-based molecular profiling is a powerful approach to improve the interpretation of pathogenic complex genomic rearrangements.

  Study EGAS00001001896

• mRNA and T cell receptor sequencing of patients with Pandemrix-associated narcolepsy type 1

  Increased risk of Narcolepsy type 1 (NT1) was reported among children and adolescents vaccinated with AS03-adjuvanted pandemic influenza A vaccine (H1N1; Pandemrix®). We hypothesized that viral T cell epitope(s) in Pandemrix mimicked self-epitope(s), and that recognition of these cross-reactive epitopes contributed to disease-specific autoimmunity. We demonstrate that pediatric, Pandemrix-associated NT1 patients had enhanced T-cell immunity against dominant T-cell epitopes of Pandemrix vaccine viral proteins neuraminidase (NA) and nucleoprotein (NP), and also responded against a self-epitope in brain-expressed protein-O-mannosyltransferase 1 (POMT1). Here, the gene expression profiles and TCR repertoire of PBMC from patients and healthy controls were compared. PBMC samples were stimulated with peptides NA-175-189 or POMT1-675-589, and bulk RNA isolated and sequenced (RNAseq and TCRseq).

  Study EGAS00001004886

• Multi-omic single-cell profiling of peripheral blood immune cells from COVID-19 patients and controls.

  The COVID-19 pandemic, caused by SARS coronavirus 2 (SARS-CoV-2), has resulted in excess morbidity and mortality as well as economic decline. To characterise the systemic host immune response to SARS-CoV-2, we performed single-cell RNA-sequencing coupled with analysis of cell surface proteins, providing molecular profiling of over 800,000 peripheral blood mononuclear cells from a cohort of 130 patients with COVID-19. Our cohort, from three UK centres, spans the spectrum of clinical presentations and disease severities ranging from asymptomatic to critical. Three control groups were included: healthy volunteers, patients suffering from a non-COVID-19 severe respiratory illness and healthy individuals administered with intravenous lipopolysaccharide to model an acute inflammatory response. Full single cell transcriptomes are coupled with quantification of 188 cell surface proteins, and T and B lymphocyte antigen receptor repertoires.

  Study EGAS00001005465

• COPD and neutrophils

  Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small airway inflammation, emphysema and severe breathing difficulties. Low-grade systemic inflammation is an established hallmark of severe disease, however, the molecular changes in peripheral immune cells remain far from understood. We combined multi-color flow cytometry with single-cell RNA sequencing and showed that blood neutrophil numbers are significantly increased in COPD and they are a heterogeneous population. A transcriptomic state that expressed interferon response genes correlated with alveolar damage and acute exacerbations. Furthermore, bronchoalveolar neutrophils expressed gene signatures corresponding to certain blood neutrophil states. Last, our data in a murine model of cigarette smoke exposure demonstrated that bone marrow neutrophil progenitors are expanded in smoke-treated animals and display signs of immune activation. Our study provides evidence that COPD systemic inflammation may derive from an activated haematopoietic precursor compartment.

  Study EGAS00001006281

• COPD and neutrophils sc

  Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small airway inflammation, emphysema and severe breathing difficulties. Low-grade systemic inflammation is an established hallmark of severe disease, however, the molecular changes in peripheral immune cells remain far from understood. We combined multi-color flow cytometry with single-cell RNA sequencing and showed that blood neutrophil numbers are significantly increased in COPD and they are a heterogeneous population. A transcriptomic state that expressed interferon response genes correlated with alveolar damage and acute exacerbations. Furthermore, bronchoalveolar neutrophils expressed gene signatures corresponding to certain blood neutrophil states. Last, our data in a murine model of cigarette smoke exposure demonstrated that bone marrow neutrophil progenitors are expanded in smoke-treated animals and display signs of immune activation. Our study provides evidence that COPD systemic inflammation may derive from an activated haematopoietic precursor compartment.

  Study EGAS00001006322

• COPD and neutrophils sc rhapsody

  Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small airway inflammation, emphysema and severe breathing difficulties. Low-grade systemic inflammation is an established hallmark of severe disease, however, the molecular changes in peripheral immune cells remain far from understood. We combined multi-color flow cytometry with single-cell RNA sequencing and showed that blood neutrophil numbers are significantly increased in COPD and they are a heterogeneous population. A transcriptomic state that expressed interferon response genes correlated with alveolar damage and acute exacerbations. Furthermore, bronchoalveolar neutrophils expressed gene signatures corresponding to certain blood neutrophil states. Last, our data in a murine model of cigarette smoke exposure demonstrated that bone marrow neutrophil progenitors are expanded in smoke-treated animals and display signs of immune activation. Our study provides evidence that COPD systemic inflammation may derive from an activated haematopoietic precursor compartment.

  Study EGAS00001006323

• Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT-BioLINCC)

  Data Access NOTEPlease refer to the "Authorized Access" section below for information about how access to the data from this accession. Access differs from many other dbGaP accessions. BiospecimensAccess to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from TOPCAT include Buffy Coat, DNA, Plasma, Serum, Urine, and Whole Blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The TOPCAT trial evaluated the effectiveness of aldosterone antagonist therapy in reducing cardiovascular mortality, aborted cardiac arrest, and heart failure hospitalization in patients who have heart failure with preserved systolic function. Background Many patients with heart failure have a normal, or near-normal, left ventricular ejection fraction (LVEF). Such patients share similar signs and symptoms as patients who have heart failure and a reduced LVEF, as well as an impaired quality of life and a poor prognosis. However, at the time of TOPCAT, the benefit of medical therapies for heart failure were limited to those with a reduced LVEF. Due to a lack of favorable evidence from clinical trials, clinical guidelines offered no specific recommendations for the management of heart failure in patients with preserved LVEF, except for attention to coexisting conditions. Among patients with heart failure and a reduced LVEF and those with myocardial infarction complicated by heart failure and left ventricular dysfunction, mineralocorticoid receptor antagonists have been shown to be effective in reducing overall mortality and hospitalizations for heart failure. In small mechanistic studies involving patients with heart failure and preserved left ventricular function, mineralocorticoid receptor antagonists improved measures of diastolic function. However, rigorous testing was needed regarding their effect on clinical outcomes in patients with preserved LVEF. Therefore, the TOPCAT trial was initiated to determine whether treatment with spironolactone, an aldosterone antagonist, would improve clinical outcomes in patients with symptomatic heart failure and a relatively preserved LVEF. Participants A total of 3445 participants were enrolled, with 1722 assigned to the spironolactone group and 1723 assigned to the placebo group. Among these, 2464 participants were enrolled via the hospitalization stratum and 981 were enrolled via the BNP stratum. Design TOPCAT was a phase 3, multicenter, international, randomized, double-blind, and placebo controlled trial. Eligible participants were randomly assigned to receive either spironolactone or placebo in a 1:1 ratio. Randomization was stratified according to whether the patient met the criterion for previous hospitalization or BNP elevation. The baseline visit included assessment of socio-demographics, physical characteristics, medical history, lifestyle factors, laboratory measures, electrocardiography variables and health-related quality of life and functional status. Study drugs were initially administered at a dose of 15 mg once daily, which was increased as tolerated to a maximum of 45 mg daily during the first four months after randomization. Subsequent dose adjustments were made as required and subjects continued to receive other treatments for heart failure and co-existing illnesses. Measurement of potassium and creatinine levels was required within 1 week after a change in the study-drug dose and at each scheduled study visit. Follow-up visits to monitor symptoms, medications, and events and to dispense study drug were scheduled every four months during the subject's first year on the study, and every six months thereafter. The mean follow-up interval was 3.3 years in each study group. Repository blood and urine samples were collected at the baseline and 1 year visits from consenting subjects. The primary endpoint was a composite of cardiovascular mortality, aborted cardiac arrest or hospitalization for the management of heart failure. Secondary endpoints included all-cause mortality, hospitalization for heart failure management, new onset of diabetes mellitus or atrial fibrillation, and quality of life. A subset of subjects also participated in the Echocardiography or Echocardiography and Vascular Stiffness ancillary studies. Echocardiography, and additionally tonometry in the Echocardiography and Vascular Stiffness study, were performed at baseline and at either 12 or 18 months following randomization. If the subject was already enrolled in the TOPCAT trial at the time the ancillary study was initiated, but had not yet reached the 18 month visit, baseline was determined via a retrospective analysis performed on any echocardiographic images completed within 60 days prior to TOPCAT enrollment and no tonometry was performed if applicable. Conclusions In patients with heart failure and a preserved ejection fraction, treatment with spironolactone did not significantly reduce the incidence of the primary composite outcome of death from cardiovascular causes, aborted cardiac arrest, or hospitalization for the management of heart failure. However, the drug reduced the secondary endpoint of heart failure hospitalization incidence.

  Study phs003665

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

  The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

  Study EGAS00001002604

• BASIS_450k

  BASIS breast cancer DNA methylation Illumina 450k

  Dataset EGAD00010000916

• The evolution of ovarian high grade serous carcinoma from STIC lesions

  We performed Ampliseq on 11 samples on a targeted panel of 17 genes.

  Study EGAS50000000361

• cfDNA dataset with whole genome sequencing for cfDNA cohort

  Cell free DNA sequencing data for 13samples with whole genome sequencing across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000666

• Data Access Committee for Translational analyses from a phase II study of pembrolizumab and epigenetic modification with azacitidine in platinum-resistant epithelial ovarian cancer

  This DAC is responsible for request review and handling related to the study above.

  Dac EGAC50000000697

• CRC and UC WES samples

  This is the dataset used to produce results for the report "NOUS-209 off-the-shelf immunotherapy has the potential to hit primary and metachronous colorectal and urothelial cancer in Lynch syndrome"

  Dac EGAC50000000782

• IDH1 Somatic Mutation Profile in Intrahepatic Cholangiocarcinoma

  The objective of this study is to identify somatic IDH1 mutations in intrahepatic cholangiocarcinoma samples.

  Study EGAS50000001638

• Use_of_deep_sequencing_to_detect_clonal_mutations_in_sun_exposed_human_epidermis___whole_genome

  Deep sequencing of two skin biopsies to study the landscape of somatic mutations in human adult tissues.

  Study EGAS00001000860

• Psoriatic_arthritis

  This is a pilot single cell mRNA sequencing experiment to study immune cells in psoriatic arthritis.

  Study EGAS00001002104

• Benchmarking_CRISPR_Whole_genome_Drop_out_Screen___B_S

  This study is a benchmarking exercise to explore potential source of variation between different CRISPR drop out libraries.

  Study EGAS00001002931

• FWO_project_G_0687_12_X10_WGS

  Profiling subclonal architecture and phylogeny in tumors by whole-genome sequence data mining and single-cell genome sequencing

  Study EGAS00001001145

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015302