Search Results - EGA European Genome-Phenome Archive

Digital tEchnology For Lung Cancer Treatment

The aim of the DEFLeCT project (Digital tEchnology For Lung Cancer Treatment) is to generate a technological platform for precision medicine in order to set predictive personalised algorithms for patient diagnosis and therapy. All resectable patients having histologically confirmed stage IB-IIIA non-small cell lung cancer(NSCLC) will be enrolled in the PROMOLE study, a related and ongoing observational prospective clinical study, for tissue sampling. A large biobank of lung cancer samples and the corresponding healthy tissues and biological components (ie, blood, stools, etc.) with complete clinical, pathological and molecular information will be collected. The project will lay the basis of a knowledge hub and qualified technology aimed not only at answering the medical and scientific community's questions, but also meant to be useful to individual patients by predicting the response to adjuvant and second-line drugs in case of relapse of the disease.

Study EGAS00001007219

RNAseq_of_healthy_mesothelial_cells_and_primary_mesothelioma_cell_lines

Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, including anti-angiogenic therapies, immunotherapy, antibody-drug conjugates and oncolytic viruses, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, in this project we aim at performing a comprehensive transcriptomic analysis of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

Study EGAS00001005728

Sequencing data from a highly cost-effective cell-free DNA methylome test

Plasma cell-free DNA (cfDNA), originating from multiple organs, holds significant potential for non-invasive diagnostics and prognostics. Current cfDNA methylation assays primarily focus on single clinical indications by targeting specific genomic loci. In contrast, comprehensive profiling of cfDNA methylome can enable simultaneous detection of multiple diseases by capturing organ-specific methylation signatures, thereby offering a holistic view of health, when disease etiology is unclear or when conventional biochemical diagnostics are unavailable. However, deep sequencing required for sensitive detection of methylation abnormalities remains prohibitively expensive, limiting widespread clinical use. To overcome this barrier, we developed MethylScan, a highly cost-effective approach for cfDNA methylome sequencing. We demonstrated its broad clinical utility in a cohort of 1,061 individuals across diverse applications, including multi-cancer detection in general population, liver cancer surveillance in high-risk individuals, liver disease classification, identification of organ abnormalities, and race prediction from cfDNA.

Study EGAS00001008125

Chromothripsis followed by circular recombination drives oncogene amplification in human cancer

The mechanisms behind the evolution of complex genomic amplifications in cancer have remained largely unclear. We here identified a type of amplification, termed as “seismic amplification”, that is characterized by multiple rearrangements and discontinuous copy number levels. Seismic amplifications occurred in 9.9% (274/2,756) of cases across 38 cancer types and were associated with massively increased copy numbers and elevated oncogene expression. Reconstruction of the development of seismic amplification revealed a stepwise evolution, starting with a chromothripsis event, followed by formation of circular extrachromosomal DNA that subsequently underwent repetitive rounds of circular recombination. The resulting amplicons persisted as extrachromosomal DNA circles or had reintegrated into the genome in overt tumors. Together, our data indicate that the sequential occurrence of chromothripsis and circular recombination drives oncogene amplification and over-expression in a substantial fraction of human malignancies.

Study EGAS00001005424

Spatial atlas of clonal copy number alterations in co-existing benign and malignant tissue

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

Study EGAS00001006124

POPCOL: population-based colonoscopy.

PopCol is a cohort study in Stockholm, Sweden that includes a data-rich set of individuals with data available from bowel symptoms questionnaires, gastroenterology visits and biospecimens (genotype and 16S sequencing from blood and stool samples, respectively). Genotyping was carried out using the Illumina HumanOmniExpressExome-8v1 arrays at the SciLifeLab NGI facility in Uppsala, Sweden. Fecal DNA was extracted from samples kept at -80°C using Qiagen 5 QIAamp DNA Stool Mini Kits and analyzed using 16S rRNA gene amplicon sequencing (in the V1-V2 hypervariable region). This was performed on the Illumina MiSeq platform at the Institute of Clinical Molecular Biology (IKMB) in Kiel, Germany. Of these, six PopCol participants were PPI users and 12 used antibiotics. The study was approved by the local Committee of Research Ethics (Forskningskommitté Syd) at Karolinska Institutet, Stockholm, in November 2001. Written informed consent was obtained from all participants

Study EGAS00001004869

Single-cell analysis reveals transcriptomic and epigenomic impacts on the maternal-fetal interface upon SARS-CoV-2 infection

During pregnancy, the maternal-fetal interface plays vital roles in fetal development. Its disruption is frequently found in pregnancy complications. Recent works show increased incidences of adverse pregnancy outcomes in COVID-19 patients; however, the mechanism remains unclear. Here, we analyzed the molecular impacts of SARS-CoV-2 infection on the maternal-fetal interface. Generating bulk and single-nucleus transcriptomic and epigenomic profiles from COVID-19 patients and control samples, we discovered aberrant immune activation and angiogenesis patterns in distinct cells from patients. Surprisingly, retrotransposons were also dysregulated in specific cell types. Notably, reduced enhancer activities of LTR8B elements were functionally linked to the downregulation of Pregnancy-Specific Glycoprotein genes in syncytiotrophoblasts. Our findings revealed that SARS-CoV-2 infection induced significant changes to the epigenome and transcriptome at the maternal-fetal interface, which may be associated with pregnancy complications.

Study EGAS00001006263

Genomic landscape and molecularly-informed therapy in thymic carcinoma and other advanced thymic epithelial tumors (H021, HIPO)

The molecular landscape of malignant thymic epithelial tumors (TET) is largely unknown. To better understand and target these clinically challenging entities, we characterize 81 patients harboring 46 thymus carcinomas (TC), 8 neuroendocrine tumors of the thymus (NET) and 27 thymomas using WGS/WES, transcriptome and methylome analysis. TC harbor different molecular alterations compared to thymoma and NET and have higher tumor mutational burden than thymomas. 14/76 TET patients show (likely) pathogenic germline alterations. Composite biomarker analysis indicates homologous repair deficiency in a subset of patients. We identify immunologically hot and cold TC. Cold TC show significantly shorter overall survival. 71/81 patients receive molecularly-informed therapy recommendations, which are applied in 28/71 cases leading to a DCR of 60% and an ORR of 24% (both n=25). 8/23 patients reach PFS ratios > 1.3, seven of them having TC.

Study EGAS00001006408

DNA methylation-based classification of sinonasal tumors [Proteomics data]

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. The repository includes the raw mass spectrometry-based proteomics data

Study EGAS00001006712

DNA methylation-based classification of sinonasal tumors [DNA sequencing]

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent previously misclassified adenoid cystic carcinomas. This repository includes the results from DNA sequencing and mass spectrometry-based proteomics.

Study EGAS00001006713

The impact of mutational clonality in predicting the response to anti-PD-L1/PD-L1 in advanced urothelial cancer

The advent of immune checkpoint inhibitors (ICI) has radically changed the management and therapeutic treatment landscape for patients with cancer. It has been shown that the use of these inhibitors can result in long-term complete remissions even in cases with advanced stages of the disease. However, only a small fraction of patients respond to the treatment. A better understanding of which factors could drive this clinical benefit is fundamental to building more accurate predictive biomarkers and developing alternative therapeutic options for patients who are unlikely to benefit. In order to address this issue, we have generated and analyzed whole exome sequencing (WES) and RNA sequencing (RNASeq) data from a cohort of metastatic urothelial carcinoma patients (N = 27) treated with ICI such as anti-PD-(L)1 monoclonal antibodies.

Study EGAS00001007086

Genomic and transcriptomic landscape of T-cell lymphoblastic lymphoma compared to T-cell acute lymphoblastic leukemia: similar subtypes and different fusions

Due to the lower incidence of T-LBL and difficulties in obtaining diagnostic T-LBL material, extensive research on T-LBL has been hampered whereas genetic aberrations in T-ALL are thoroughly characterized. Given the similarities and differences between T-LBL and T-ALL, the question has been raised whether T-LBL and T-ALL represent two different diseases or different manifestations of the same disease. This study aims to identify the genomic and transcriptomic landscape of T-LBL and compare the findings to what is found T-ALL. Comparison of the molecular aberrations between T-LBL and T-ALL can provide insights into the overlap and differences in malignant development between the two entities, which could lead to improved risk stratification in T-LBL in order to eventually adapt T-LBL treatment protocols based on molecular-genetic prognostic factors.

Study EGAS00001007767

Colorectal Microenvironment Spatial Mapping

In colorectal cancer (CRC), interactions between tumor and immune cells within the tumor microenvironment are critical drivers of tumorigenesis, immune evasion, prognosis, and therapeutic response. Therefore, a deeper understanding of the spatial organization of cancer and immune cells within the CRC microenvironment is urgently needed. In this study, we aimed to characterize distinct cell populations and patterns of spatial gene expression associated with CRC tumorigenesis and immune infiltration. Spatial transcriptomics (ST) was performed on CRC and adjacent normal tissues to investigate the patterns of gene expression. Integrative ST data and publicly available single-cell RNA sequencing (scRNA-seq) data analysis tools were used for data integration, dimension reduction, clustering, and differential expression analysis. This study identified novel immunosuppressive cell populations and immune regulatory factors in CRC. Further functional validation of these findings will be essential to assess their potential as therapeutic targets.

Study EGAS00001008254

Cooperative activity of BRAF F595L and mutant HRAS in histiocytic sarcoma provides new insights into oncogenic BRAF signaling

Mutations that activate the RAF-MEK-ERK signaling pathway, in particular BRAFV600E, occur in many cancers, and mutant BRAF-selective inhibitors have clinical activity in these diseases. Activating BRAF alleles are usually considered to be mutually exclusive with mutant RAS, whereas inactivating mutations in the D594F595G596 motif of the BRAF activation segment can coexist with oncogenic RAS and cooperate via paradoxical MEK/ERK activation. We determined the functional consequences of a largely uncharacterized BRAF mutation, F595L, which was detected along with an HRASQ61R allele by clinical exome sequencing in a patient with histiocytic sarcoma and also occurs in epithelial cancers, melanoma, and neuroblastoma, and investigated its interaction with mutant RAS. We demonstrate that, unlike previously described DFG motif mutants, BRAFF595L is a gain-of-function variant with intermediate activity towards MEK that does not act paradoxically, but nevertheless cooperates with mutant RAS to promote oncogenic signaling. Of immediate clinical relevance, BRAFF595L shows divergent responses to different mutant BRAF-selective inhibitors, whereas signaling driven by BRAFF595L with and without mutant RAS is efficiently blocked by pan-RAF and MEK inhibitors. Mutation data from primary patient samples and cell lines show that BRAFF595L, as well as other BRAF mutations with intermediate activity, frequently coincide with mutant RAS in a broad spectrum of cancers. These data define a novel class of activating BRAF mutations that cooperate with oncogenic RAS in a non-paradoxical fashion to achieve an optimal level of MEK-ERK signaling, extend the spectrum of patients with systemic histiocytic disorders and other malignancies who are candidates for therapeutic blockade of the RAF-MEK-ERK pathway, and underscore the value of comprehensive genetic profiling for understanding the signaling requirements of individual cancers.

Dataset EGAD00001001384

De novo mutations in cell-free foetal DNA (cffDNA)

This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women. 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 EGAD00001000596

Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

Most patients with late stage high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy but inevitably relapse and develop resistance, highlighting the need for novel therapies to improve patient outcomes. The MEK/ERK pathway is activated in a large subset of HGSOC, thus making it an attractive therapeutic target. Here, we systematically evaluated the extent of MEK/ERK pathway activation and efficacy of pathway inhibition in a large panel of well-annotated HGSOC patient-derived xenograft (PDX) models. The vast majority of models were nonresponsive to the MEK inhibitor cobimetinib (GDC-0973) despite effective pathway inhibition. Proteomic analyses of adaptive responses to GDC-0973 revealed that GDC-0973 upregulated the pro-apoptotic protein BIM, thus priming the cells for apoptosis regulated by BCL2-family proteins. Indeed, combination of both MEK inhibitor and dual BCL-2/XL inhibitor (ABT-263) significantly reduced cell number, increased cell death and displayed synergy in vitro in most models. In vivo, the GDC-0973 and ABT-263 combination was well tolerated and resulted in greater tumor growth inhibition than single agents. Detailed proteomic and correlation analyses identified two subsets of responsive models – those with high BIM at baseline that was increased with MEK inhibition and those with low basal Bim and high pERK levels. Models with low BIM and low pERK were non-responsive. Our findings demonstrate that combined MEK and BCL-2/XL inhibition has therapeutic activity in HGSOC models and provide a mechanistic rationale for clinical evaluation of this drug combination as well as the assessment of the extent to which BIM and/or pERK levels predict drug combination effectiveness in chemoresistant HGSOC.

Dataset EGAD00001005111

MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

Dataset EGAD00001005994

Longitudinal profiling of the immune response to Plasmodium vivax in naive hosts by RNA-sequencing

Plasmodium vivax offers unique challenges for control and elimination, and may prove a tougher hurdle to overcome than Plasmodium falciparum. And yet compared to P. falciparum we know very little about the innate and adaptive immune responses that need to be harnessed to reduce disease and transmission. We recently generated a blood bank of a new clonal field isolate of P. vivax (PvW1) for human challenge studies and used systems immunology tools to track the host response throughout infection and convalescence. As part of this study, RNA-sequencing was used to resolve changes in whole blood gene expression through time in 6 volunteers (7-9 time-points per volunteer). In summary, these data show that P. vivax induces two distinct transcriptional programmes in whole blood during and after infection. During infection, transcriptional profiling reveals the rapid mobilisation of an emergency myeloid response, which leads to systemic inflammation and the recruitment of all major T cell subsets into lymphoid tissues. Six days after infection, this innate response subsides and a transcriptional signature of proliferation is revealed. This most likely represents widespread activation of lymphocytes, which return to the circulation after parasite clearance - transcriptional profiling of T cells at this time-point could therefore reveal the outcomes of critical cell-cell interactions that take place within the spleen during infection. 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 EGAD00001006924

Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

Dataset EGAD00001009482

Genome-wide cell-free DNA biological patterns in patients with cancer

The structure of cell-free DNA (cfDNA) is altered in the blood of cancer patients. From whole genome sequencing we retrieved the cfDNA fragment-end composition using a new software (FrEIA), as well as the cfDNA size and tumor fraction in three independent cohorts (n=925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% of cancer samples using at least one cfDNA measure, including 64% of early-stage cancer (n=220). cfDNA detection correlates with a shorter overall (p=0.018) and recurrence-free (p=0.006) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n=396 cancer, 90 controls) achieve a detection accuracy of 82% and AUROC of 96%. In conclusion, harnessing the biological features of cfDNA can improve at no-extra cost the diagnostic performance of liquid biopsies.

Study EGAS00001007400

RNA sequencing in primary inflammatory (TPP) macrophages following deletion of a disease-associated gene desert at chr21q22, disruption of ETS2, or treatment of ETS2-edited macrophages with a HIF1α stabiliser.

GWAS studies in five different inflammatory diseases have identified a strong genetic association at a gene desert at the chr21q22 locus. We have shown that this locus contains a monocyte/macrophage-specific enhancer that regulates ETS2 - a gene whose role in primary human monocytes/macrophages is incompletely understood. We therefore used a CRISPR-Cas9-based approach to delete the enhancer region or to disrupt ETS2, and performed RNA-sequencing to examine the transcriptional consequences. One effect of ETS2 disruption was upregulation of genes involved in aerobic respiration and oxidative phosphorylation. We therefore treated ETS2-edited inflammatory macrophages with roxadustat, a HIF1α stabiliser that can promote glycolysis via HIF1α-mediated metabolic reprogramming, and performed RNA-sequencing to determine whether this drug might rescue the transcriptional effects of ETS2 disruption.

Study EGAS00001007553

DAC for study: "Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer."

This is Data Access Committee will oversee data sharing for sequence data in the EGA study: "Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer." This dataset includes 116 bam files from whole exome sequencing on the Illumina HiSeq2500, 102 fastq files from RNA sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor/normal DNA samples and tumor RNA samples from 72 individuals with non-small cell lung cancer treated with pembrolizumab and SBRT or pembrolizumab alone on the NCT02492568 trial.

Dac EGAC50000000202

Profiling of 27 type 2 diabetes GWAS loci using next-generation (NG) capture C in a human beta-cell model

Most type 2 diabetes association signals are due to variants that impact gene regulation but identifying the genes they impact is challenging. We generated interaction profiles at 27 T2D GWAS loci using next-generation (NG) capture C (6 replicates) in the human beta-cell model, EndoC-betaH1, along with chromatin accessibility profiling using ATAC-Seq (9 replicates).

Dataset EGAD00001008655

DAC for human-derived clonal organoid studies

This is the DAC for human-derived clonal organoid culture studies. It includes the study to investigate the clonal evolution of metastatic CRC at the single-cell level, where we performed WGS in 58 clonal organoids and 18 fresh-frozen (FT) bulk-tissue samples from surgically resected primary and metastatic tumors before and after anticancer therapies in 6 patients. This approach enabled detailed phylogenetic reconstruction of individual clones. We discovered the timing and burden of treatment-related mutations as well as the heterogeneous evolution in driver mutations and genomic rearrangements in late-stage clonal evolution under anticancer therapies in metastatic CRC.

Dac EGAC50000000628

Neo-RT sWGS

Paired plasma cell-free DNA (cfDNA) samples were collected from 11 breast cancer patients before and after radiotherapy. Sequencing libraries were prepared using the Agilent SureSelect XT HS2 kit and sequenced on the Illumina NovaSeq 6000 platform. Neo-RT (NCT03818100) is a non-randomised, single-arm feasibility study evaluating neoadjuvant radiotherapy combined with endocrine therapy in women with ER-positive, HER2-negative breast cancer. Eligible patients had grade 1 or 2 disease (grade 3 permitted if chemotherapy was contraindicated) and a palpable tumour size ≥20 mm, for whom radiotherapy was intended to facilitate breast-conserving surgery.

Dataset EGAD50000002238

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