Search Results - EGA European Genome-Phenome Archive

Single cell RNAseq, TCRseq, BCRseq and CITE-seq of deep cervical lymph nodes from healthy donors

These raw sequencing dataset includes 10x Genomics 5' scRNA-seq, TCR-seq, BCR-seq, and CITE-seq profiles of cells isolated from the deep cervical lymph nodes of three healthy controls.

Dataset EGAD50000001232

National Cancer Institute (NCI) Primary Human Melanocyte QTL Study

In order to create a melanocyte-specific QTL resource, we obtained primary human melanocyte cultures isolated from foreskin of 106 healthy newborn males predominantly of European descent. Melanocytes were cultured in lot-matched culture medium in randomized batches to minimize variability that could be introduced by culturing conditions. RNA sequencing and direct SNP genotyping of these samples produced an average of ~87.9 million reads (paired-end, stranded, 126bps), and ~713,000 SNP genotypes, respectively. Illumina 450K methylation array covered over 485,000 CpGs distributed genome wide.

Study phs001500

Childhood Cancer Data Initiative (CCDI): Single-Cell Atlas of NF1 Nerve Sheath Tumors

The worst outcome of NF1 is the development of the aggressive and highly metastatic malignant peripheral nerve sheath tumors (MPNST), which transform from benign plexiform neurofibroma (PN) and lack effective treatment. In this study, we performed single-cell RNA sequencing of 63 clinically annotated NF1-associated peripheral nerve sheath tumors, including 24 PN, 34 premalignant atypical neurofibromas, and 5 MPNSTs. These results improve the ability of identifying high-risk neurofibromas and provide a unique opportunity for early detection of MPNST.

Study phs003519

The genetic analysis of circulating tumor DNA in blood of the digestive cancer patients to investigate the prognostic factors of metastasis and reccurence.

A Darwinian evolutionary shift occurred early in the neutral evolution of advanced colorectal carcinoma (CRC) and copy number aberrations (CNA) were essential in the transition from adenoma to carcinoma. Subsequent to the primary evolution, we now focus on the evolutionary principle of the genome to foster postoperative recurrence of CRC. SO, We compared CNA, single nucleotide variance (SNV), RNA sequences between 8 primary and 11 metastatic sites from 10 CRCR cases.

Study JGAS000221

RNAseq SCLC Cell lines MYC

RNAseq data set (Mollaoglu et al., MYC drives progression of small cell lung cancer to a variant neuroendocrine subtype with vulnerability to Aurora kinase inhibition) RNA isolation from primary tumors and healthy lungs was performed using RNeasy Mini Kit (Qiagen) with the standard protocol. RNA was subjected to library construction with the Illumina TruSeq Stranded mRNA Sample Preparation Kit (cat# RS-122-2101, RS-122-2102) according to manufacturer’s protocol. Chemically denatured sequencing libraries (25 pM) are applied to an Illumina HiSeq v4 single read flow cell using an Illumina cBot. Hybridized molecules were clonally amplified and annealed to sequencing primers with reagents from an Illumina HiSeq SR Cluster Kit v4-cBot (GD-401-4001). Following transfer of the flowcell to an Illumina HiSeq 2500 instrument (HCSv2.2.38 and RTA v1.18.61), a 50 cycle single-read sequence run was performed using HiSeq SBS Kit v4 sequencing reagents (FC-401-4002).

Dataset EGAD00001003099

Whole Genome Sequencing of a Triple Negative Breast Cancer Patient: Matched Primary Tumor, Normal, Metastasis and Xenograft samples

Breast Cancer Subject Participant ID 700064 (Source Sample names: 6888 and 206). We used massively parallel DNA sequencing technologies to screen entire genomes, in an unbiased manner, for genetic changes associated with tumor growth and metastasis. We describe the complete genome sequence analysis of four DNA samples from a 44-year old African-American patient with basal-like breast cancer: peripheral blood, the primary tumor, a brain metastasis that developed within a year of initial therapy, and a first-passage xenograft derived from the primary tumor. A total of 50 validated mutations were discovered within coding, RNA, or splice site sequences. Of these, 20 mutations were abundantly present in all three tumors, including mutations in CSMD1 and JAK2. These two genes subsequently were found to be mutated in other breast tumors. The metastasis contained two de novo mutations not present in the primary tumor, and was significantly enriched for 20 shared mutations, suggesting that they may be involved in the metastatic process. The xenograft contained no unique coding, RNA, or splice site mutations and retained all primary tumor mutations, albeit at different frequencies. However, a significant increase in copy number alterations was observed in the xenograft as compared to the primary tumor. We validated 28 large deletions and six inversions, as well as seven translocations in at least one of the three tumor samples. Among them, a 26 kb deletion in MECR was solely identified, assembled, and validated in the brain metastasis and two overlapping large deletions on chromosome 5 encompassing CTNNA1, a potential tumor suppressor gene, were identified in all three tumors. The differential mutation frequencies and structural variation patterns between primary and metastatic tumors suggest that metastatic tumors may arise from minor subpopulations of cells within the primary. Namely, the metastatic and xenografting processes apparently select for cells harboring a distinct subset of the primary tumor mutation repertoire.

Study phs000245

Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

Study EGAS50000000470

Single cell RNAseq, TCRseq, BCRseq and CITE-seq of deep cervical lymph nodes from Multiple sclerosis patients

These raw sequencing dataset includes 10x Genomics 5' scRNA-seq, TCR-seq, BCR-seq, and CITE-seq profiles of cells isolated from the deep cervical lymph nodes of six Multiple sclerosis (MS) patients.

Dataset EGAD50000001233

ChIP-seq of blasts from leukemia patients and CD34+ cells from healthy donors

CTCF ChIP-seq of 14 leukemia patients: 6 AML without 3q rearrangements, 1 AML with 3q26, 1 AML with t(3;8) and 6 T-ALL H3K27ac ChIP-seq of AML patients: 4 cases with t(3;8), another with inv(3) and another with normal karyotype. H3K27ac ChIP-seq of CD34+ cells from one healthy donor RUNX1 ChIP-seq of one t(3;8) AML patient

Dataset EGAD00001006817

Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): A Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study

UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI). Due to additional sharing restrictions, data from one site can be found in phs003094.

Study phs003066

Therapeutic Targeting of ATR Yields Durable Regressions in High Replication Stress Tumors

Patients with relapsed or recurrent small cell lung cancer or extra-pulmonary small cell cancers were enrolled on an investigator-initiated, single-arm, phase 2 trial (NCT02487095) combining an ATR inhibitor M6620 (VX-970, berzosertib) administered at 210 mg/m2 intravenously over 60 minutes on day 2 and day 5, and topotecan 1.25 mg/m2 intravenously over 30 minutes every 23 hours on days 1 through 5, with a support of pegfilgrastim 6mg subcutaneously on day 6 in 21-day cycles. Tumor samples were collected either just before starting the treatment or before starting treatment prior to be enrolled in the trial. Whole exome and RNA were sequenced to evaluate genomic and transcriptomic characteristics associated with the response to the combination treatment.

Study phs002327

Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): a Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study - for Samples Collected at Johns Hopkins

UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI).The larger dataset for this study can be found in dbGaP study phs003066.

Study phs003094

Genomics of Pediatric Renal Medullary Carcinomas

Version 1We derived faithful cancer cell lines from patients with a diagnosis of renal medullary carcinomas (RMC). These models have been sequenced with whole genome, exome and transcriptome technologies along with the patient's primary germline and tumor samples. We took these faithful models and performed loss-of-function genetic perturbation screens (e.g. RNAi and CRISPR-Cas9) along with an orthogonal small molecule screen. We identified the ubiquitin-proteasome system as an important target in RMC as well as other SMARCB1 deficient cancers.Version 2We have collaborated with the Children's Oncology Group and the study AREN03B2 to study the cohort of patients with a central diagnosis of RMC. Here, we used 10x linked read sequencing along with RNA-sequencing to profile these matched tumor-normal pairs.

Study phs001800

Evolution of Chromatin Architecture and Transcriptional Regulation in Mammals

Changes in gene expression are a critical force driving the evolution of form and function. As a result, the mechanisms by which gene expression evolves have become a subject of intense interest. A number of investigators have measured evolutionary changes in gene expression at the chromatin, mRNA, and protein levels, leading to new insights about how species evolve. However, studies of different stages in gene expression have not always been in agreement. For example, the extremely rapid rates of evolutionary changes that have been widely observed at enhancers appear to conflict with the slower rates observed in mRNA abundance. We recently completed a major comparative study in primates showing that this disparity between enhancer and mRNA evolution, in part, reflects extensive compensation at enhancers that jointly determine transcription at target genes. Likewise, related findings have demonstrated that post-transcriptional changes buffer protein abundance to relatively more common differences in mRNA expression. Together, these recent findings demonstrate that evolutionary changes affecting multiple stages of transcriptional regulation often have interdependent effects on gene expression. Here we propose to determine how stages early during transcriptional regulation work in concert, either to conserve gene expression through compensatory changes across stages, or, in rare cases, to change mRNA in ways that alter organism phenotypes. Our central hypothesis is that interactions between stages are common, especially at long evolutionary time-scales. To test this hypothesis we propose an ambitious plan to collect rich genomic data profiling distinct stages of gene expression in two cell types and three tissues from nine mammalian species. We have focused our study on several early rate-limiting steps in mRNA production, using molecular assays selected to provide orthogonal sources of information about chromatin architecture (Hi-C/Hi-ChIP), accessibility (ATAC-seq), transcription (PRO-seq), and mRNA levels (RNA-seq). This project will produce the largest resource of genomic data uniformly collected across mammals to date. We will integrate genomic data using a suite of new computational tools, which together will provide a new understanding of how distinct regulatory stages work in concert during regulatory evolution.

Study phs002146

DNA-Sequencing of Baseline Plasma From the Phase III Alliance A031201 Trial

Liquid biopsy assays tailored for metastatic castration-resistant prostate cancer (mCRPC) patients are needed to identify molecular alterations and predict survival in the context of androgen receptor (AR) inhibitors. We developed a novel plasma cell-free DNA (cfDNA) sequencing assay to detect circulating tumor DNA (ctDNA) and alterations in key mCRPC driver genes, and tested associations with clinical features and survival outcomes in a phase III trial. cfDNA was isolated from evaluable baseline plasma specimens of untreated mCRPC patients (n=790) enrolled in the Alliance A031201 randomized phase III trial (NCT01949337) prior to enzalutamide therapy with or without abiraterone acetate and prednisone. A customized targeted cfDNA sequencing assay was used to detect AR and non-AR alterations in mCRPC. For this, DNA-seq libraries were constructed from cfDNA using Takara ThruPLEX Tag-Seq or Plasma-Seq kits, and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. ctDNA positivity was defined as >20% ctDNA using an aneuploidy-based estimate derived from ichorCNA (Group 1) or a novel definition of ≤20% ctDNA, but with detection of any alteration in AR, or gain of MYC and/or MYCN (Group 2). cfDNA sequencing data was obtained from 776 patients. There were 480/776 (62%) ctDNA-positive patients, with 324 (42%) in Group 1 and an additional 156 (20%) in Group 2 with AR or MYC/MYCN alterations detected. ctDNA-positive patients in Groups 1 and 2 had similarly poor median overall survival (OS) of 25.4 months (95% CI: 21.8-29.0) and 29.7 months (95% CI: 27.3-35.5), respectively, as compared to ctDNA-negative patients who had a median OS of 49.1 months (95% CI: 42.3-53.5). Relative to ctDNA-negative patients, OS was inferior in ctDNA-positive patients in Group 1 (HR 2.3, 95% CI: 1.9-2.9, P AR inhibitors in a contemporary phase III trial.

Study phs003325

Whole genome and RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

Paediatric glioblastoma (pedGBM) is characterised by substantial intertumoural heterogeneity. In order to identify the genetic lesions underlying tumourigenesis, we analysed whole genomes and transcriptomes of pedGBMs and in vitro model systems by next generation sequencing. Novel fusions of the receptor tyrosine kinase MET lead us to investigate targeted therapy using MET inhibitors. This study is part of the International Cancer Genome Consortium PedBrain Tumor Project (ICGC PedBrain, http://www.pedbraintumor.org/).

Study EGAS00001001139

RNA sequencing of NK cells in human lung

Human lung tissue-resident NK cells (trNK cells) are likely to play important roles in viral infections, inflammation and cancer. However, knowledge about lung trNK cells is lacking but is fundamental for exploiting these cells in therapeutic approaches. Here we analysed the transcriptome of CD69+CD49a+CD103+CD16-CD56bright, CD69+CD49a+CD103-CD16-CD56bright, CD69+CD49a-CD103-CD16-CD56bright, CD69-CD49a-CD103-CD16-CD56bright, and CD56dimCD16+NKG2A+CD57- NK cells isolated from human lung.

Study EGAS00001003544

Combinatorial CRISPR screen identifies fitness effects of paralogues FAM50A and FAM50B

Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1,191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. This dataset includes CRISPR screening of cancer cell lines, RNA sequencing studies of cancer cell lines and also data from the sequencing of tumour xenografts collected from mice.

Dataset EGAD00001006648

Oesophageal adenocarcinoma scRNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

This dataset contains single-cell RNA-seq generated from the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19) and additional donors with Barrett's oesophagus using the 5' Single Cell Gene Expression assay from 10x Genomics. Samples were generated from oesophageal tumours, Barrett's oesophagus, and normal oesophagus and gastric tissues, with the aim of generating a reference atlas for cell types found in normal and disease-associated tissue states in the upper GI tract. This reference atlas was used as the basis for a deconvolution workflow to estimate the cell composition of bulk transcriptomes from these tissues, and to assess cell type-specific expression patterns of potential predictive biomarkers for immunochemotherapy regimens in this setting.

Dataset EGAD00001009401

Dataset for study Genome-wide gene expression analysis following CRISPRi of transposable elements

Transposable elements (TEs), once regarded as parasitic genomic remnants, are now recognized as key regulators of gene expression and genome evolution, yet the functional specificity of individual TE subfamilies remains largely unexplored. This dataset investigates the transcriptional consequences of targeted repression of MER57E3 and LTR10B2 elements using CRISPR interference (CRISPRi) in human induced pluripotent stem cells (hiPSCs). hiPSCs expressing CRISPRi machinery (n = 2 biological replicates) were transduced with guide RNAs targeting individual or grouped copies of MER57E3 and LTR10B2, as well as the ZNF678 promoter or a lacZ non-targeting control. Transduced cells were subsequently differentiated into neural progenitor cells (NPCs), and total RNA was extracted for mRNA library preparation and sequencing. The dataset comprises 24 single-end mRNA-seq FASTQ files generated from these NPCs and wild-type controls.

Dataset EGAD00001015689

Transcriptome analysis of a novel human iPSC-derived 3D cortical tissue model - WT, APP KI, Abeta-treated, Abeta/Aducanumab-treated

Single-cell RNA-seq analysis of human iPSC-derived microglia/astrocytes/neurons in a novel, human in vitro 3D cortical tissue model. Samples include distinct conditions (each as biological duplicates): - wild-type cells from cultures after 1 month (WT_1mo, cell lines: A18, KOLF) and 3 months (WT_3mo, cell lines: SA2, KOLF, A18) of culturing - knock-in cells from cultures carrying three familial AD mutations in the APP gene (Swedish, Iberian, Arctic; introduced by CRISPR/Cas9-mediated knock-in) after 3 months of culturing (KI_3mo, cell lines: SA2, A18) - subset of WT 1 month-old samples were exposed to 500nM synthetic Abeta42 for 2 consecutive feeds, and a subset of these subsequently treated with 1µg/ml Aducanumab antibody for 14 days

Dataset EGAD50000002031

WGS/RNA-seq pair of an inflammatory hepatocellular adenoma (IHCA)

A 49 years old female patient consulted for diarrhea, rectal bleeding and lower limbs edema and was diagnosed with systemic AA amyloidosis. An inflammatory hepatocellular adenoma was further identified and resected, resulting in the improvement of amyloidosis-related symptoms. Molecular analyses of the tumor tissue revealed a somatic chromosome rearrangement responsible for interleukin-6 mRNA stabilization leading to an inflammatory acute response with serum amyloid A protein production by both neoplastic and normal hepatocytes.

Study EGAS00001003025

Single-cell RNA-seq of human kidney tumors

The aim of this study is to analyze the transcriptomic information of fresh single cells originating from human clear cell renal cell carcinomas (ccRCC). Samples have been experimentally enriched in malignant cells in order to address specific questions regarding heterogeneity and clonality in ccRCC. Samples include one set of long-term frozen and thawed single cells in order to explore the impact of liquid nitrogen freezing on ccRCC single cells.

Study EGAS00001006534

RNA-seq study of longitudinal blood cell samples drawn from children at risk of type 1 diabetes

The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing-based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (case subjects) at a young age and matched control subjects.

Dataset EGAD00001005767

Identification of immune mechanisms associated with the high rate of relapse in patient with visceral leishmaniasis and HIV co-infection

RNA-seq transcriptomics of whole blood samples from longitudinal follow-up of a cohort of visceral leishmaniasis (VL) patients with and without HIV coinfection, from active disease through apparent cure and potential relapse. Analysis will identify potential correlates of relapse to identify immune mechanisms underlying the high rate of relapse in HIV/VL coinfection. 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 EGAD00001008361

NGS data of human NES cells and tumors

Raw RNA-seq data for WT and 2 Gorlin NES cells, tumors derived from MYCN mis-expressed WT NES cells, tumors derived from Gorlin NES cells, and tumors derived from Gorlin NES cells transduced with mutant DDX3X (R351W and R534S) and CRISPR/Cas9 targeting GSE1 (each sample has 3 replicates/tumors except Gorlin NES cell tumors have 4). Raw whole exome sequencing data for WT and Gorlin 1 NES cells, tumors derived from MYCN mis-expressed WT NES cells, and tumors derived from Gorlin NES cells (each sample has 3 replicates/tumors except Gorlin NES cell tumors have 4). Raw data for amplicon sequencing of GSE1 and KDM3B at regions targeted by CRISPR/Cas9 in Gorlin NES cells.

Dataset EGAD00001004990

RNA-seq of non-LPS treated (N), non-tolerized (NT), and tolerized (T) IFNg-primed macrophages pretreated with or without HDAC3i

In this experiment we investigated the effect of HDAC3 inhibition on the transcriptome of IFNg-primed macrophages under different tolerization conditions. Peripheral blood mononuclear cells (PBMCs) were isolated from 3 healthy donors. PBMCs were isolated from whole blood of healthy donors using Ficoll gradient (Invitrogen). Monocytes (CD14+ cells) were positively selected from PBMCs using CD14 Microbeads according to the manufacturer’s instructions (Miltenyi Biotec). Monocytes were subsequently treated with or without 500 nM HDAC3i (ITF3100) for 30 minutes prior to overnight IFNg priming (50 ng/mL). Cells were then kept without LPS (non-LPS; N), treated with 10 ng/mL LPS once (non-tolerized; NT), or treated with LPS twice (tolerized; T; second LPS concentration: 100 ng/mL). In total, there were 18 samples included.

Dataset EGAD00001005959

Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

Study EGAS00001007327

ChIP-Seq of TFEB in LT-HSC

Study EGAS00001005462

WGBS data of solid liver tumor DNA, and WGBS data of cell-free DNA derived from human blood, for CancerDetector study

The blood samples of four liver cancer patients and four healthy people, and the solid liver tumor samples of two liver cancer patients are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

Dataset EGAD00001004317

Cellular Profiling Identifies Targetable T Cell Phenotypes in Lymphocytic Variant Hypereosinophilic Syndrome

Lymphocytic variant hypereosinophilic syndrome (LHES) is driven by aberrant Th2‑skewed lymphocyte clones that promote tissue eosinophilia. We performed multimodal single‑cell RNA‑sequencing (scRNA‑seq), cell‑surface protein (ADT) profiling, and paired αβ‑TCR sequencing on peripheral‑blood mononuclear cells (PBMCs) from two clinically characterized LHES patients and one idiopathic HES control. One LHES patient was sequenced at two timepoints, pre-JAK inhibitor treatment and post-JAK inhibitor treatment. Single‑cell regulatory‑network inference (SCENIC), CellChat ligand–receptor modelling, and scRNA variant calling were integrated with flow‑cytometric validation and 5,000× amplicon sequencing. Two clonally expanded CD3‑CD4⁺ central‑/effector‑memory T‑cell clusters were observed exclusively in LHES. These cells showed Th2‑associated regulons (GATA3, BATF, MAF), high expression of CCR4, CD52, PTGDR2 and IL13, and down‑regulation of CD247 (CD3ζ), a mechanism experimentally confirmed to abolish surface CD3/TCR. Autocrine IL‑7 signaling, predicted by CellChat, provides an antigen‑independent proliferative cue. Therapeutically actionable targets (CCR4, CD52, IL‑5, IL‑7, TNF) were prioritized; one refractory patient achieved complete clinical and cytologic remission after mogamulizumab (anti‑CCR4) therapy. Longitudinal sequencing revealed clonal evolution with acquisition of a STAT3 p.G618R mutation under JAK‑inhibition, highlighting a resistance mechanism. Raw scRNA‑seq (5′ cDNA, VDJ, ADT) data, and sample‑level metadata will be distributed through dbGaP. These resources provide the first high‑resolution immune atlas of LHES and a framework for rational, precision immunotherapy in eosinophilic disorders.

Study phs004041

Mutational patterns and regulatory networks in epigenetic subgroups of meningioma (H033)

DNA methylation patterns delineate clinically relevant subgroups of meningioma. We previously established the six meningioma methylation classes (MC) benign-1, 2, 3, intermediate-A, B and malignant. Here, we set out to identify subgroup-specific mutational patterns and pathway regulation. Whole-genome-sequencing was performed on 62 samples across all MCs and WHO grades from 62 patients with matched blood control, including 40 sporadic and 22 radiation-induced (Mrad) meningiomas. RNA sequencing was added for 18 cases and chromatin-immunoprecipitation for the enhancer mark H3K27ac followed by sequencing (ChIP-seq) for 16 samples. Besides the known mutations in meningioma, structural alterations were found to contribute to the spectrum of mechanisms inactivating NF2 in sporadic meningioma similar to previous reports for Mrad. Aberrations of DMD were found to be enriched in MCs with NF2 mutations and DMD was among the most differentially upregulated genes in NF2 mutant compared to NF2 wild-type cases. The mutational signature AC3 was detected in both sporadic meningioma and Mrad, but distributed across the genome in sporadic cases and enriched near genomic breakpoints in Mrad. In general, the malignant MC presented a significantly higher exposure to AC3 and higher genomic instability beyond the mutational load than the other MCs. Pathway analysis of the ChIP-seq clusters revealed that the FOXM1 is most differentially activated in high-grade cases, along with super enhancer recruitment near HOX genes and respective upregulation of expression. This data further elucidate the biological mechanisms differentiating meningiomas of different WHO grade and epigenetic subgroups and suggest leveraging the genomic instability as novel therapeutic targets.

Study EGAS00001003481

H3K27ac ChIP-seq of lung neuroendocrine tumors

Study EGAS50000000057

Chip-Seq

27 Chip-Seq samples from Human CD4+ T cells

Dataset EGAD00001010181

CD4 T-Cell ChIP-Seq

Dataset EGAD00001002686

Single-cell RNA sequencing of human skin tumors (BCC, SCC and Melanoma)

Cancer-associated fibroblasts (CAFs) play a key role in cancer progression and treatment outcome. Here, we elucidate the yet unresolved intra-tumoral CAF variety in three skin cancer types at molecular and spatial single-cell resolution in a large cohort. We show that two out of three CAF subtypes contribute to tumor immune surveillance with distinct mechanisms. Matrix CAFs (mCAFs) ensheath tumor nests and synthesize extracellular-matrix to prevent T cell invasion. Immunomodulatory CAFs (iCAFs), which express proinflammatory and immunomodulatory factors, are only detected in high abundance in aggressive tumors. Strikingly, iCAFs but not tumor cells are (apart from immune cells) the exclusive cell type producing chemokines and, thus, play a key role in immune cell recruitment and activation. Mechanistically, we show that cancer cells transform adjacent healthy fibroblasts into cytokine-expressing iCAFs, which subsequently recruit immune cells and modulate the immune response. In conclusion, targeting CAF variants holds promise for improved efficacy of immunotherapy.

Study EGAS50000000365

ATAC-seq and ChIP-seq analysis of patient-derived normal pancreas and pancreas neoplasm organoids

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

Study JGAS000264

scRNA-seq, scTCR-seq and scBCR-seq of 21 individuals post Covid'19 vaccination.

This data includes scRNA-seq, scTCR-seq and scBCR-seq of 21 individuals post Covid'19 vaccination. Individuals range from the ages 52 to 75. Samples were genotype multiplexed in an overlapping mixture design, pooled, and sequenced on 16 lanes (10X, 5' GEM).

Dataset EGAD00001011201

DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

Study phs000597

Bulk RNA sequencing of Singapore colorectal cancer patients (SG-BULK)

The study was approved by the institutional review board of Singhealth (2018-2795). Ten 5-µm tissue sections were cut using standard microtomy techniques. Each collected cell population was then extracted using the allprep kit. Extracted material was then quantified using a Qubit fluorometer.

Study EGAS00001005978

Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

Dataset EGAD00001006415

Dataset for Ewing_sarcoma_PNET-RNA

Rare cancer sequencing data of 28 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008845

mFAST-SeqS

Recent progress in the analysis of cell-free DNA fragments (cell-free circulating tumor DNA, ctDNA) now allows monitoring of tumor genomes by non-invasive means. However, previous studies with plasma DNA from patients with cancer demonstrated highly variable allele frequencies of ctDNA. The comprehensive analysis of tumor genomes is greatly facilitated when plasma DNA has increased amounts of ctDNA. Therefore, a fast and cost-effective pre-screening method to identify such plasma samples without previous knowledge about alterations in the respective tumor genome could assist in the selection of samples suitable for further extensive qualitative analysis. To address this, we adapted the recently described FAST-SeqS method, which was originally established as a simple and effective, non-invasive screening method for fetal aneuploidy from maternal blood. We show that our modified FAST-SeqS method (mFAST-SeqS) can be used as a pre-screening tool for an estimation of the ctDNA percentage. Using a combined evaluation of genome-wide and chromosome-arm specific z-scores from dilution series with cell line DNA and by comparisons of plasma-Seq profiles with data from mFAST-SeqS, we established a detection limit of 10% or more of mutant alleles. Plasma samples with an mFAST-SeqS z-score above 5 showed highly concordant results compared to copy number profiles obtained from our previously described plasma-Seq approach.

Study EGAS00001001133

Targeted_sequencing_of_genes_recurrently_mutated_in_AML

Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

Study EGAS00001000408

Stand Up To Cancer East Coast Prostate Cancer Research Group

Most prostate cancer deaths are caused by metastatic, castration resistant disease (mCRPC). To develop a precision medicine framework for mCRPC, we established a multi-institutional, international clinical sequencing infrastructure to enroll and carry out prospective whole exome and transcriptome sequencing of tumors from a cohort of mCRPC patients. We obtained high quality DNA and RNA sequence data from 150 bone or soft tissue biopsies. Central pathology revealed high-grade adenocarcinoma with only four cases (3.6%) showing neuroendocrine differentiation. Aberrations of AR, ETS genes, TP53 and PTEN were frequent (40-60% of cases), with TP53 and AR alterations being the most enriched in mCRPC compared to primary prostate cancer. We identified novel genomic alterations in PIK3CA/B (fusions and mutations); R-spondin, BRAF and RAF1 (fusions); APC (inactivating mutations); delta-catenin (missense mutations); and ZBTB16/PLZF (homozygous deletions). Aberrations of BRCA2, BRCA1 and ATM were observed at substantially higher frequencies (19.3% overall) than seen in primary prostate cancers, with 56% of these being exclusively somatic. Putative driver gene alterations were identified in nearly all patients, and over half also harbored driver gene fusions, homozygous deletions and/or amplifications. Moreover, 89% of patients harbored a clinically actionable aberration including 62.7% with aberrations in AR, 65% in other cancer-related genes, and 8% with actionable pathogenic germline alterations. Overall, integrative clinical sequencing analysis can be safely and efficiently performed in mCRPC, yields findings that may be actionable for enrolling patients in clinical trials of targeted therapies, and may inform the basis of individual clinical responses.

Study phs000915

A Clone's Genomic Stability as a Biomarker of Its DNA-Damage Resilience

A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified “more-is-better” and “one-size-fits-all” principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell “genomic instability” as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.

Study phs003762

11976 results for "cancer rna-seq"

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