Search Results - EGA European Genome-Phenome Archive

DirectHRD Enables Sensitive Scar-Based Classification of Homologous Recombination Deficiency (HRD)

Homologous recombination deficiency (HRD)-induced genomic scars are an FDA-approved biomarker for identifying cancers likely to respond to PARP inhibitors. However, detecting HRD scars from blood biopsies has been challenging due to the low tumor content in blood samples. To address this limitation, we developed DirectHRD, a genomic scar-based HRD classifier leveraging whole-genome sequencing (WGS) data for non-invasive blood biopsy testing. DirectHRD was applied to 90 cell-free DNA (cfDNA) samples across four cancer types: breast, ovarian, prostate, and pancreatic. The method achieved an AUC of 0.87 and demonstrated the ability to detect HRD at tumor fractions as low as 1%, offering a tenfold increase in sensitivity compared to state-of-the-art methods.

Study phs003760

APOBEC Mutagenesis, Kataegis, Chromothripsis in EGFR-Mutant Osimertinib-Resistant Lung Adenocarcinomas

Expanding on studies investigating apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like (APOBEC) mutagenesis in histological transformation of epidermal growth factor receptor (EGFR)-mutant lung cancers, it has been hypothesized that mutational signature analysis may help better understand acquired resistance to targeted therapies. Using mutational signature analysis in Receptor Tyrosine Kinase (RTK) driven lung adenocarcinomas, more specifically EGFR mutant lung cancer, APOBEC dominant mutational signatures were noted more frequently in subclonal post Tyrosine Kinase Inhibitor (TKI) treatment biospecimen samples and in the presence of large-scale genomic rearrangements. This is hypothesized to be due to the pressure of treatment with TKIs; a fact that should be further explored and can be potentially manipulated in order to overcome drug resistance.

Study phs003812

C-MACH reduced-representation bisulfite sequencing (RRBS)

Umbilical cord blood (CB) has been commonly used as an epigenetic surrogate of fetuses. Here, we propose umbilical cord tissue (UC) as an alternative surrogate for epigenetic studies on fetuses. To explore the feasibility to examine UC epigenome by deep sequencing, we determined CpG methylation profiles of human postnatal UC by reduced representation bisulfite sequencing. We compared DNA methylomes between UC and CB. To investigate the effect of folate during pregnancy on fetal DNA methylation, we compared fetal UC DNA methylation between low and high levels of maternal plasma folate. Our study suggests that UC is useful as an alternative surrogate for studying environmental effects on DNA methylation in human fetuses, compensating CB by providing additional information about epigenetic regulation of genes.

Study JGAS000171

Single cell transcriptomics to characterize the tumor microenvironment of prostate cancer fusion biopsies

The primary objective of this study was to characterize the tumor microenvironment in fusion-guided transperineal biopsy samples from patients undergoing PC diagnosis. For each patient, one biopsy was taken from a suspected tumor region and another from a non-suspicious area, which were later classified as high- or low-tumorigenicity based on anatomopathological analysis. Using scRNA-seq data, we performed cancer-oriented cell annotation, differential expression analysis, and functional pathway enrichment studies across key cellular subpopulations. Additionally, differential abundance analysis was conducted to identify cell groups representative of different tumorigenicity levels. Finally, classification models were developed using gene expression data to differentiate high- vs. low-tumorigenicity samples, with the long-term goal of establishing a diagnostic classifier for PC stratification.

Study EGAS50000000888

Clinical validity of post-surgery circulating tumor DNA (ctDNA) in stage III colon cancer patients treated with adjuvant chemotherapy: the PROVENC3 study

The PROVENC3 study aimed to determine the clinical validity of post-surgery ctDNA testing in patients with stage III colon cancer treated with adjuvant chemotherapy (ACT). Blood was collected pre-surgery, post-surgery and post-adjuvant chemotherapy. Tumor-informed plasma ctDNA detection was performed through integrated whole genome sequencing (WGS) analyses of formalin-fixed paraffin-embedded tumor tissue DNA (80x), white blood cell germline DNA (40x) and plasma cell-free DNA (30x). These raw WGS data for 209 patients are shared in .cram format in this EGA submission. For 196/209 of these patients there is overlapping FFPE tumor RNA sequencing data available, shared in .fastq format in this EGA submission.

Study EGAS50000000804

Team

The Team Mallory Freeberg Roderic Guigó Arcadi Navarro Helen Parkinson Jordi Rambla Ana T. Alonso Silvia Bahena Àlex Bedmar Kenneth Buckley Aldar Cabrelles Ángel Carreño Marcos Casado Giulia Cellerino Amy Curwin Teresa D'Altri Abeer Fadda Teresa Garcia Sara Gregorio Max Fischer Bela Juhasz Oriol Lopez-Doriga Mireia Marin Óscar Martínez Andrea Mero Akiris Moctezuma Aurora Moreno Liina Nagirnaja Francesc de Puig Santiago Rensonnet Gabriele Rinck Aravind Sankar Andres Silva Coline Thomas Sabela de la Torre Gemma Vicente The EGA Team at the CRG co-manages the European Genome and phenome Archive together with the EGA Team at the European Bioinformatics Institute. In addition to maintaining and distributing data, we enrich the contents of the EGA contributing with our knowledge about genomics and the relationship between genomes and phenomes. Previous Team Members Alexander Vikhorev Jeff Almeida-King Mario Alberich Sergi Aguilo Pablo Arce Minjie Ding Alfred Gil Leslie Glass Jag Kandasamy Vasudev Kumanduri llkka Lapalainen Audald Lloret i Villas Sira Martinez Anand Mohan Dietmar Orth Justin Paschall Saif Ur Rehman Gary Saunders Thomas Smith Ashutosh Shimpi Marc Sitges Dhvani Solanki Giselle Kerry Nino Spataro Dylan Spalding Matthieu Vizuete-Forster Cristina Yenyxe Gonzalez Garcia Paul Flicek Anna Foix Emilio Garcia Rios Jorge Izquierdo Roberto Ariosa Marta Ferri Peradalta Daniel Barrowdale Babita Singh Umuthan Uyan Aleix Canalda Dona Shaju Mauricio Moldes Carles Garcia Frédéric Haziza Alegria Aclan Lauren Fromont Alvis Brazma Marta Huertas Arnau Soler Gemma Milla Claudia Vasallo Aina Jené Csaba Halmagyi Raül Garcia Thomas Keane Mei Gascón

Documentation about/team

DPY30_ChIP_seq

H9 human embryonic stem cells (hESCs) were cultured in feeder-free chemically-defined conditions in medium containing 10ng/ml Activin A and 12ng/ml FGF2 (Vallier L. 2011, Methods in Molecular Biology, 690: 57–66). Chromatin immunoprecipitation was performed as described in Brown S. et al. 2011. Stem Cells 29: 1176–85 by using 5ug of anti-DPY30 antibody (Sigma, cat. number HPA043761). This protocol was performed in control hESCs (expressing a scrambled shRNA) and in hESCs stably expressing an shRNA against DPY30 (Sigma, clone n. TRCN0000131112).This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001001132

Low_coverage_whole_genome_sequencing_of_samples_from_the__Cretan_Greek_isolate_collection_HELIC_MANOLIS

Whole-genome sequencing at 1x of samples from the Cretan Greek isolate collection HELIC-MANOLIS. Genome-wide association studies of complex traits have been successful in identifying common variant associations, but a substantial heritability gap remains. The field of complex trait genetics is shifting towards the study of low frequency and rare variants, which are hypothesised to have larger effects. The study of these variants can be empowered by focusing on isolated populations, in which rare variants may have increased in frequency and linkage disequilibrium tends to be extended. This work focuses on an isolated population from Crete, Greece. Sequencing is very efficient in isolated populations, because variants found in a few samples will be shared by others in extended haplotype contexts, supporting accurate imputation.

Study EGAS00001000392

PCa-LINES

PCa-LINES: Ribo-minus RNA-seq of 4 patient samples and 2 PCa cell lines ---- Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data Youri Hoogstrate, Malgorzata A. Komor, René Böttcher, Job van Riet, Harmen J. G. van de Werken, Stef van Lieshout, Ralf Hoffmann, Evert van den Broek, Anne S. Bolijn, Natasja Dits, Daoud Sie, David van der Meer, Floor Pepers, Chris H. Bangma, Geert J. L. H. van Leenders, Marcel Smid, Pim French, John W.M. Martens, Wilbert van Workum, Peter J. van der Spek, Bart Janssen, Eric Caldenhoven, Christian Rausch, Mark de Jong, Andrew P. Stubbs, Gerrit A. Meijer, Remond J.A. Fijneman, Guido Jenster bioRxiv 2021.05.17.441778; doi: https://doi.org/10.1101/2021.05.17.441778 https://www.biorxiv.org/content/10.1101/2021.05.17.441778v1

Study EGAS00001004613

Hematopoietic differentiation at single-cell resolution in NPM1-mutated AML

To investigate the relationship between somatic mutations and phenotypic hematologic differentiation at the single-cell level, we used a droplet-based multi-omics single-cell platform on eleven NPM1-mutated AML diagnostic samples. We developed a bioinformatics framework to perform phylogeny-driven genotype correction, that allowed us to study 52 103 single cells. Intra-leukemic genetic heterogeneity was detectable in all patients, including a branched architecture in nine of them, always owing to co-occurring signaling mutations. We identified two groups of NPM1-mutated AML, one characterized by a progenitor immunophenotype and a second one with a predominant monocytic differentiation. We also identified various degrees of intra-leukemic immunophenotype heterogeneity, sometimes associated with strong genetic/phenotype correlations.

Study EGAS00001006565

Targeted deep sequencing on Pediatric MDS

Targeted NGS using custom panels with SAMD9, SAMD9L genes and 22 single nucleotide polymorphisms (SNP) on chromosome 7q (allele frequency >35% in all ethnic sub-populations in gnomAD) (Ampliseq #IAD10417) was performed in 667/669 cases. Additionally, 559 cases were sequenced using 28 pediatric MDS genes (GATA2, RUNX1, HOXA9, CEBPA, GATA1, KRAS, NRAS, CBL, PTPN11, ASXL1, EZH2, SETBP1, FLT3, KIT, JAK2, JAK3, CSF3R, MPL, SH2, BCOR, BCORL1; RAD21, STAG2, CTCF, TP53, PTEN, CALR, VPS45; Ampliseq #IAD51150). Libraries for targeted NGS were prepared using NEBNext Ultra II DNA library prep kit (New England BioLabs, cat#E7645S/L) per manufacturer’s instruction and samples were sequenced on an Illumina Miseq 2000 with 2 x 150 bp reads. The BAM files are uploaded here.

Study EGAS00001005431

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

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

Dataset EGAD00001001426

GoNL aligned sequence data in BAM format.

We mapped the data to the UCSC human reference genome build 37 using BWA 0.5.9-r16. We first mapped each read pair separately using bwa aln. Then we used bwa sampe to map the paired reads together to a BAM9 file. The BAM file was then sorted by genomic position and indexed using PicardTools-1.32 SortSam. To prevent PCR artifacts from influencing the downstream analysis of our data, we used Picard to mark the duplicate reads, which were ignored in downstream analysis. We used GATK IndelRealigner on our data around known indels (from 1KG Pilot). The IndelRealigner creates all possible read alignments using the source and computes the likelihood of the data containing the indel based on the read pileup. Whenever the maximum likelihood contains an indel, the reads are realigned accordingly. Each base is associated with a phred-scaled base quality score. Calibration of Phred scores is crucial as they are used in some of the downstream analysis models. We used GATK to recalibrate the base qualities with respect to (i) the base cycle, (ii) original quality score, and (iii) dinucleotide context. To minimize issues stemming from mapping problems around indels, we decided to undergo a second round of indel realignment using the GATK IndelRealigner by family rather than by individual. For this second round, we considered two sources of possible indels: 1KG Phase 1 indels and indels aligned by BWA in the GoNL data.

Dataset EGAD00001001038

Exome trios in patients with gastroschisis (2019-04-08)

Gastroschisis (MIM 230750) is a herniation of the intestines through a defect of the abdominal wall lateral to the umbilicus (usually on the right side), and it is not covered by a membrane [Ledbetter, 2012]. Gastroschisis is a congenital anomaly with increasing incidence, easy prenatal diagnosis and extremely variable postnatal outcomes. On the basis of clinical manifestations, epidemiologic charateristics, and the presence and type of additional malformations, gastroschisis could be considered a heterogeneous condition with no gene/s discovered yet. This congenital anomaly affects approximately 1-3 infancts per 10,000 live births [Calzolari et al.1995;Parker et al.,2010] Current knowledge about causative mutations/variants. To date, no single gene has been linked to gastroschisis. Some publications have tried to link this malformation to variants in genes (such as AEBP1 (adipocyte enhancer binding protein) gene [Feldkamp et al,. 2012] or the VEGF-NOS3 pathway [Lammer et al., 2008]. Previously, a Scribble mutant mouse model (circletail) was reported to exhibit gastroschisis, however recent studies demonstrated that the Scribble knockout fetus exhibits exomphalos phenotype of gastroschisis [Carnagham et al., 2013]. 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/ . This dataset contains all the data available for this study on 2019-04-08.

Dataset EGAD00001004942

Multi-region sequencing of RCC with VTT and metastasis using WES and RNAseq

This dataset contains multi-region sequencing of 16 RCC patients with venous tumor thrombus (VTT), 11 of which were either metastatic on diagnosis or recurred with metastasis. Whole exome sequencing is available for 94 samples across all 16 patients, including 1 matched normal sample per patient, 2-3 primary tumor samples per patient, 1-2 VTT samples per patient, and 0-3 metastasis samples per patient (metastatic lesions were only sampled for 8 of the 11 metastatic patients). RNAseq, generated by exome capture, is available for 67 samples across 12 patients, including 0-1 matched normal samples per patient, 3 primary tumor samples per patient, 0-1 VTT samples per patient, and 0-3 metastasis samples per patient (RNAseq was only available for 4 of the 8 patients from whom metastatic lesions were sampled).

Dataset EGAD00001008441

Molecular characterization of NASH-HCC

We collected 80 NASH-HCCs formalin fixed paraffin-embedded (FFPE) samples from 5 different institutions. NASH was diagnosed in FFPE samples by at least two expert pathologists following a described histological algorithm (Bedossa et al., Hepatology, 2012). All NASH patients included in the study were HBV- and HCV-negative. Patients reporting alcohol consumption ≥ 20 g/day for women and 30 g/day for men, as well as patients with a known liver disease superimposed to NASH were excluded. Tumour and paired non-tumour gDNA of NASH-HCC FFPE samples was submitted to Whole Exome Sequencing (WES). Exome capture and sequencing library preparation were performed using the SureSelect Human All Exon V5, no UTR hybridization capture kit from Agilent (Target Size 50 Mb). Libraries were sequenced on an Illumina HiSeq 4000 instrument with 100-bp paired-end reads.

Dataset EGAD00001007524

Single-cell transcriptome of T-ALL P1

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

Dataset EGAD00001008325

CRUK-ICGC Prostate DNA Methylation Sequencing Dataset (Prostatectomy Batches 1-6)

This dataset includes Illumina EPIC Capture Sequencing Data of 376 samples from 188 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy, with matched pathologically assessed non-cancer control material. This DNA methylation data includes donors and samples included in previously published WGS datasets (from CRUK-ICGC batches 1 to 3 [EGAD00001001116] and batches 4 to 6 [EGAD00001003225]; including the majority of donors used in Wedge et al, Nature Genetics 2018 [PMID: 29662167]). The targeted DNA methylation sequencing data in this EGA dataset were generated using the Illumina TruSeq methyl capture method (EPICseq), covering over 3.3 million CpGs in the human genome, representing a total targeted hybridisation capture panel of 107Mbp. According to the EPICseq protocol, DNA samples extracted from prostatectomy tissue samples were enriched for target regions using hybridisation capture, prior to bisulfite conversion, amplification and sequencing in pools of 12 samples (150 single end reads over two Illumina HiSeq4000 lanes). This approach generated DNA methylation profiles from prostate cancer and control samples at base-pair resolution across millions of CpGs in the human genome.

Dataset EGAD00001010184

Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

Dac EGAC00001001387

The data access committee for Detection and characterization of lung cancer using cell-free DNA fragmentomes

Dac EGAC00001002184

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