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• Tapestri_h5

  H5 files generated for each sample with Tapestri Pipeline

  Dataset EGAD00010002559

• Tapestri_loom

  Loom files generated for each sample with Tapestri Pipeline

  Dataset EGAD00010002561

• GermlineSNP

  SNP data for 473 germline samples

  Dataset EGAD00010002039

• PopArg94_raw

  Raw data files for 94 Argentinean samples

  Dataset EGAD00010001913

• CALGB/SWOG 80405 ct DNA Biomarker Evaluation

  To investigate treatment-specific mutations that underlie resistance to treatment with chemotherapy +/- bevacizumab or cetuximab in first line metastatic Colorectal Cancer (mCRC) patients, we performed targeted sequencing of circulating free DNA (cfDNA) from longitudinal plasma samples. These samples were collected at baseline (PRE, n=354), during treatment (OTH, n=254), and/or at progression or end of the protocol treatment (EOT, n=345) from CALGB/SWOG 80405, a randomized phase III trial that evaluated the efficacy of chemotherapy plus bevacizumab or cetuximab treatment in first line colorectal cancer patients (NCT00265850).

  Study phs002941

• Genomic and Transcriptomic Markers Associated with Response to Immune Checkpoint Blockade

  The neoantigen presentation score (NEOPS) study was designed to better understand molecular determinants of response to immunotherapies, including pembrolizumab and nivolumab in stage III or IV melanoma patients. From this work, we developed a composite approach to predicting neoantigens (NEOPS), which takes into account additional escape mechanisms, including HLA LOH (human leukocyte antigen loss of heterozygosity) and the impact of deleterious mutations to the antigen presentation machinery (APM), yielding an improved prediction of response to immunotherapy compared to TMB (tumor mutational burden) or neoantigen burden alone.

  Study phs002388

• Acquired Cross-Resistance in Small Cell Lung Cancer Patient-Derived Xenografts

  Here we present whole genome sequencing and RNA sequencing of patient-derived xenograft (PDX) models of small cell lung cancer (SCLC). These models were derived at a variety of clinical time points from either biopsy/resection samples, malignant effusions, or circulating tumor cells (CTCs), and grown in the subcutaneous flank of NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl /SzJ) mice. The first analysis published with these data was to determine the genomic and transcriptomic features of PDX models derived after relapse that demonstrated in vivo resistance to multiple chemotherapy regimens (cross-resistance).

  Study phs003486

• Phenotypic Signatures of Circulating Neoantigen-Reactive CD8+ T Cells in Patients with Metastatic Cancers

  Following enrichment of neoantigen-reactive T cells using pHLA tetramers or cell-surface markers, we performed single-cell sequencing (RNA-seq and TCR-seq) of circulating CD8+ T cells from metastatic cancer patient samples (Melanoma, Colorectal, and Breast cancer). In samples from previously studied patients, we identified cells bearing neoantigen-reactive T cell receptors and were able to study their phenotypic program. By studying the circulating neoantigen-reactive T cell program, a gene-signature was derived to identify neoantigen-reactive T cells from blood samples prospectively.

  Study phs003064

• An investigation into the effects of progestin on follicular development and oocyte maturation during controlled ovarian stimulation using the Progestin-Primed Ovarian Stimulation (PPOS).

  In recent years, the Progestin-Primed Ovarian Stimulation (PPOS) method, utilizing progestin as ovulation suppressants, has gained traction as a controlled ovarian stimulation (COS) strategy in assisted reproductive technology (ART). However, the impact of progestin agents on follicular fluid, granulosa cells, and cumulus cells at the levels of gene and protein expression has not been fully assessed. This study aims to evaluate the effects of progestin agents, used in the PPOS method, on follicular development and oocyte maturation.

  Study JGAS000770

• Genomic and Epigenomic Features of Primary and Recurrent Hepatocellular Carcinomas

  Intratumor heterogeneity and divergent clonal lineages within and among primary and recurrent hepatocellular carcinomas (HCCs) produce challenges to patient management. We investigated genetic and epigenetic variations within liver tumors, among hepatic lesions, and between primary and relapsing tumors. We performed whole-genome, whole-exome, or targeted capture sequencing analyses HCC specimens collected from multiple tumor regions and matched initial and recurrent tumors to obtain a systematic evaluation of intra- and intertumor genetic heterogeneity in HCC samples and to identify genetic changes associated with tumor progression and recurrence.

  Study EGAS00001002094

• Alterations in the gut microbiome in inflammatory arthritis implicate key taxa and metabolic pathways across arthritis phenotypes

  The gut microbiome has been implicated in several inflammatory conditions, but large-scale metagenomic evaluations have not yet traced the routes by which immunity in the gut affects systemic inflammatory diseases, such as inflammatory arthritis. To characterize the community structure and associated functional processes driving gut microbial involvement in arthritis, we investigated a total of 440 stool shotgun metagenomes comprising 275 adults diagnosed with rheumatoid arthritis, ankylosing spondylitis, or psoriatic arthritis, along with 165 healthy control individuals and individuals with joint pain without an underlying inflammatory cause.

  Study EGAS00001005525

• An isolated cohort of samples from the Greek island of Crete that have been genotyped on the Illumina CoreExome array.

  Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies. Here we have genotyped individuals from a Greek population isolate on the Illumina CoreExome Beadchip. The HELIC (Hellenic Isolated Cohorts) MANOLIS (Minoan Isolates) collection focuses on Anogia and surrounding Mylopotamos villages. Recruitment of this population-based sample was primarily carried out at the village medical centres. All individuals were older than 17 years and had to have at least one parent from the Mylopotamos area. www.helic.org

  Study EGAS00001000896

• Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild type primary glioblastoma

  We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy.

  Study EGAS00001006989

• Exome Sequencing Reveals Frequent Inactivating Mutations in BAP1, ARID1A, and PBRM1 in Intrahepatic Cholangiocarcinomas

  Through exomic sequencing of 32 intrahepatic cholangiocarcinomas, we discovered frequent inactivating mutations in multiple chromatin remodeling genes (including BAP1, ARID1A, and PBRM1) – mutation in one of these genes occurred in almost half of the carcinomas sequenced. We also identified frequent mutations at previously reported hotspots in genes encoding the metabolic enzymes IDH1 and IDH2 in intrahepatic cholangiocarcinomas. In contrast, TP53 was the most frequently altered gene in a series of nine gallbladder carcinomas. These studies highlight the importance of dysregulation of chromatin remodeling in intrahepatic cholangiocarcinomas.

  Study EGAS00001001108

• Whole Genome sequencing of Angolan and Mozambican individuals

  To support the continued discovery and cataloguing of genomic variation in human populations and to further our understanding of the Bantu Expansion, we sequenced the genomes of 291 individuals from Cabinda, a northern exclave of Angola, and 49 individuals from Maputo, the capital of Mozambique. Utilising the power and flexibility of these whole-genome sequencing datasets, we discover rare variation, fine-scale population structure, and perform analyses using haplotype-based inference tools and our own model-based simulation framework to reconstruct complex dispersals of Bantu speak-ing populations across sub-Saharan Africa.

  Study EGAS00001007458

• Single cell RNA-sequencing (scRNA-seq) of the human hematopoietic stem cell compartment (CD34+CD38-CD45RA-)

  To identify a trajectory of human hematopoietic stem cell (HSC) activation single cell gene expression profiling of RNA from human HSC was performed by flow cytometry-based single cell deposition of CD34+CD38—CD45RA—cells from G-CSF-mobilized peripheral blood from 3 individual donors and 1 bone marrow donor in concert with single cell index-sorting (signals indexed: CD34, CD38, CD45RA, CD90, CD49f) and followed by SMARTseq2 based protocol. We show that INKA1 and CDK6/PAK4 expressing single cells segregate across alternative states of quiescence.

  Study EGAS00001004769

• Genomic analysis of HPV positive versus HPV negative esophageal adenocarcinoma

  High-risk human papillomavirus (hr-HPV) has been implicated in a subset of patients with esophageal adenocarcinoma (EAC). We therefore hypothesized that HPV associated EAC may have distinct genomic aberrations compared with viral negative esophageal cancer as shown in Head and Neck cancer and cervical cancer. Whole exome sequencing (WES) was performed to explore the mutational landscape and potential molecular signature of HPV positive versus HPV negative EAC, which includes four hr-HPV-positive and 8 HPV-negative treatment naive fresh-frozen EAC tissue specimens and matched normal tissues.

  Study EGAS00001001340

• Precursor_lesions__clonal_architecture_and_relapse_in_Wilms_nephroblastoma

  Targeted resequencing at high depth (21 genes, 9 chromosomal regions): at least 4 FFPE samples per case and matched germline DNA: •100 cases with detailed outcome data, including 15 cases with tumour relapse (515 samples)•40 cases with matched pre-chemotherapy biopsies (240 samples)•50 nephrogenic rests matched to above cases (50 samples)We expect a proportion (possibly 10%) of cases to be mutationally silent on the above studies, and propose to subsequently carry out integrated whole-genome, methylome and transcriptome studies on matched frozen tissue from these cases

  Study EGAS00001001422

• Nurminen et al ("GP2Men") Study Primary and Metastatic Prostate Cancer Whole Genome Sequence Data

  We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

  Study EGAS50000000005

• Comparing sequencing of four proto-typical Burkitt lymphomas (BL) with IG-MYC translocation.

  By whole-genome, exome, transcriptome and methylome sequencing of four proto-typical Burkitt lymphomas (BL) with IG-MYC translocation we identified seven recurrently mutated genes including ID3. In an extended cohort, 36/53 (68%) molecularly-defined BL carried potentially damaging mutations of ID3 which were enriched at somatic hypermutation motifs. Only 6/47 (13%) other IG-MYC-positive B-cell lymphomas carried ID3 mutations suggesting cooperation of ID3 inactivation and IG-MYC translocation to be a hallmark of Burkitt lymphomagenesis.

  Study EGAS00001000271

• RNASeq of PDX and CDX tumours treated with ADC

  Enapotamab vedotin (EnaV), an antibody-drug conjugate (ADC) targeting AXL, effectively targets tumors that display insensitivity to immunotherapy and/or tumor-specific T cells in several melanoma and lung cancer models. Mechanistically, EnaV treatment induced an inflammatory response and immunogenic cell death in tumor cells, and promoted induction of a memory-like phenotype in cytotoxic T cells. Combining EnaV with tumor-specific T cells proved superior to any treatment alone in models of melanoma and lung cancer, and increased ICB benefit in models otherwise insensitive to anti-PD-1 treatment.

  Study EGAS00001004562

• Gene expression profiling of nasopharyngeal carcinoma

  We retrospectively collected 150 non-metastatic, pretreatment, formalin-fixed, paraffin-embedded (FFPE) nasopharyngeal carcinoma (NPC) samples as validation cohort 1. Also, we prospectively collected 32 FFPE samples from NPC patients enrolled in a trial evaluating anti-PD-1 antibody as validation cohort 2. Total RNA was extracted and hybridised to an Affymetrix HTA 2.0 microarray. In this study, we investigated the immune status of the tumour microenvironment (TME) based on gene expression profiles to classify NPC into biologically distinct immune subtypes, and clarify their associations with prognosis and immunotherapy response.

  Study EGAS00001004542

• AfricanNeo aDNA Study

  With the largest genomic dataset to date of Bantu-speaking populations, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we shed fresh light on the expansion of peoples speaking Bantu languages that started ~4000 years ago in western Africa. We have generated whole-genome sequences from 12 Late Iron Age individuals. Our comprehensive genetic analysis of the expansion of people speaking Bantu languages reveals a complex history of serial founder events, variable levels of contact with local groups, and spread-over-spread events.

  Study EGAS00001007519

• Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002974

• Genome and transcriptome sequence data from a metastatic neuroendocrine carcinoma of unknown primary patient

  Genome and transcriptome sequence data from a metastatic neuroendocrine carcinoma of unknown primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002975

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002977

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002978

• Genome and transcriptome sequence data from a GI primary (prev breast cancer) patient

  Genome and transcriptome sequence data from a GI primary (prev breast cancer) patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002979

• Genome and transcriptome sequence data from a metastatic fibrolamellar hepatocelluar carcinoma patient

  Genome and transcriptome sequence data from a metastatic fibrolamellar hepatocelluar carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002980

• Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002981

• Genome and transcriptome sequence data from a metastatic rectosigmoid adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic rectosigmoid adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002982

• Genome and transcriptome sequence data from a metastatic carcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002983

• Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002984

• Genome and transcriptome sequence data from a adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from a adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002985

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002986

• Genome and transcriptome sequence data from a metastatic endocervical adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic endocervical adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002987

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002988

• Genome and transcriptome sequence data from a medullary thyroid cancer patient

  Genome and transcriptome sequence data from a medullary thyroid cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002989

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002990

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002992

• Genome and transcriptome sequence data from a metastatic carcinoma of primary unknown patient

  Genome and transcriptome sequence data from a metastatic carcinoma of primary unknown patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002993

• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of anus patient

  Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of anus patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002994

• Genome and transcriptome sequence data from a carcinosarcoma of the uterus patient

  Genome and transcriptome sequence data from a carcinosarcoma of the uterus patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002995

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002997

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002048

• Genome and transcriptome sequence data from a liposarcoma patient

  Genome and transcriptome sequence data from a liposarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002046

• Genome and transcriptome sequence data from a lung cancer patient

  Genome and transcriptome sequence data from a lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002045

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002044

• Genome and transcriptome sequence data from a recurrent glioma patient

  Genome and transcriptome sequence data from a recurrent glioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002043

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002041

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002036

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002035

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002034

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002033

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002031

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002030

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002028

• Genome and transcriptome sequence data from a colorectal cancer patient

  Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002027

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002026

• Genome and transcriptome sequence data from a colorectal cancer patient

  Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002025

• Genome and transcriptome sequence data from a lung cancer patient

  Genome and transcriptome sequence data from a lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002023

• Genome and transcriptome sequence data from a colorectal cancer patient

  Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002022

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002021

• Genome and transcriptome sequence data from a metastatic NPC patient

  Genome and transcriptome sequence data from a metastatic NPC patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002020

• Genome and transcriptome sequence data from a colon cancer patient

  Genome and transcriptome sequence data from a colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005826

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005852

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005838

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005841

• Genome and transcriptome sequence data from a chondrosarcoma patient

  Genome and transcriptome sequence data from a chondrosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005848

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005849

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005851

• Smart-seq 2 single cell sequencing of CD4 and CD8 T cells from the blood and synovial fluid of 4 psoriatic arthritis patients.

  This dataset was used to characterise T cell gene expression and clonality at sites of active inflammation within the joints of psoriatic arthritis (PsA) patients, and to compare these results with T cells from the peripheral blood of those same patients. Freshly sorted CD45RA negative CD3+CD4+ and CD3+CD8+ single cells from four patients were individually flow sorted into 96-well full-skirted plates (Eppendorf) containing 10µL of a 2% Dithiothreitol (DTT, 2M Sigma-Aldrich), RTL lysis buffer (Qiagen) solution. Cell lysates were sealed, mixed and spun down before storing at -80 ºC. Paired-end multiplexed sequencing libraries were prepared following the Smart-seq 2 protocol using the Nextera XT DNA library prep kit (Illumina). A pool of barcoded libraries from four different plates were sequenced across two lanes on the Illumina HiSeq 2500.

  Dataset EGAD00001006342

• WGS and RNA-Seq data from a GBM patient PT-SJ5453

  WGS and RNA-Seq data from a GBM patient PT-SJ5453

  Dataset EGAD00001008529

• WGS and RNA-Seq data from a GBM patient PT-PV2594

  WGS and RNA-Seq data from a GBM patient PT-PV2594

  Dataset EGAD00001008526

• WGS and RNA-Seq data from a GBM patient PT-SS3647

  WGS and RNA-Seq data from a GBM patient PT-SS3647

  Dataset EGAD00001008530

• RNA-seq dataset: Single-cell spatial analysis of pediatric high-grade glioma reveals a novel population of immunosuppressive and tumor-promoting SPP1+/GPNMB+ myeloid cells

  Our study utilizes two novel techniques, cyclical immunofluorescence imaging and single-cell spatial transcriptomics, to spatially map the tumor microenvironment of a large sample set of pediatric high-grade gliomas (pHGG). Using these methods, we have identified an abundant immunosuppressive myeloid cell population that has not been described in the context of pediatric high-grade gliomas. We validate our findings using an in vitro assay, spatial analysis on additional pHGG biopsies, independent spatial transcriptomic data, bulk RNA sequencing data of an expanded cohort of in-house patients, and publicly available bulk RNA sequencing data of an even larger cohort of pHGG patients.

  Dataset EGAD00001015450

• Identifying Novel Small RNA Biomarkers Unique to Patients with Gastric Cancer

  The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented. Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: 30097497 DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States).

  Study phs001767

• Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud university medical center

  Dac EGAC00001003193

• DAC for genomic data obtained within the Micrometastasis (Oslo1) project from Oslo, Norway

  Dac EGAC00001000558

• DAC for Transcriptome analysis in very preterm infants with chronic lung disease after birth

  Dac EGAC00001000698

• DAC for Cardiac Translatomes of 80 Human Samples (65 DCM cases 15 controls)

  Dac EGAC00001001040

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee

  Dac EGAC00001001226

• Genomics to select patients with metastatic breast cancer for targeted therapy DAC

  Dac EGAC00001002293

• Data Access Committee for the project: Epic arrays from human OB and their mimics

  Dac EGAC00001002482

• The Data Access Committee for Human Olfactory Mucosa Cells (DAC_HOM) at UEF

  Dac EGAC00001002527

• The EMC-NICHE DAC considers appeals for hematopoietic/niche-related data sets.

  Dac EGAC00001001897

• Translational Gastroenterology Unit, University of Oxford Data Access Committee for the EPIC-CD study

  Dac EGAC00001003481

• Cyr61-MAC DAC

  DAC for access to dataset on Cyr61-MAC and HUVEC

  Dac EGAC50000000355

• Data access committee for datasets generated by the Tampere University Computational Biology research group

  Dac EGAC50000000177

• DAC PRECISE Bennstein

  Data access control for datasets submitted by SysMed - PRECISE

  Dac EGAC50000000476

• Transcriptome sequencing in monozygotic twins discordant for Mayer-Rokitansky-Küster-Hauser syndrome

  Study EGAS00001006370

• Exploration of neuroblastoma xenograft models for tumor extracellular RNA profiling in murine blood plasma

  Study EGAS00001007295

• Mesothelima_OSCHP_Files

  Oncoscan CHP files for the Mesothelemia Project

  Dataset EGAD00010001540

• Cancer Alliance Exome

  Exome sequencing for individualized cancer interpretation

  Dataset EGAD00001006236

• Hostage_2_phenotype_basic

  Basic phenotypes for Hostage2 cohort.

  Dataset EGAD00001007840

• BelCovid_2_phenotype_basic

  Basic phenotypes for BelCovid2 cohort.

  Dataset EGAD00001007834

• BRACOVID_phenotype_lab

  Lab values for BRACOVID cohort.

  Dataset EGAD00001007833

• BRACOVID_phenotype_basic

  Basic phenotypes for BRACOVID cohort.

  Dataset EGAD00001007832

• Hostage_3_phenotype_basic

  Basic phenotypes for Hostage3 cohort.

  Dataset EGAD00001007842

• SPGRX_phenotype_basic

  Basic phenotypes for SPGRX cohort.

  Dataset EGAD00001007848