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• Sensitive Monogenic Noninvasive Prenatal Diagnosis by Targeted Haplotyping

  During pregnancy, cell-free DNA (cfDNA) in maternal blood encompasses a small percentage of cell-free fetal DNA (cffDNA), an easilyaccessible source for determination of fetal disease status in risk families through non-invasive procedures. In case of monogenic heritabledisease, background maternal cfDNA prohibits direct observation of the maternally inherited allele. Non-invasive prenatal diagnostics(NIPD) of monogenic diseases therefore relies on parental haplotyping and statistical assessment of inherited alleles from cffDNA,techniques currently unavailable for routine clinical practice. Here, we present monogenic NIPD (MG-NIPD), which requires a bloodsample from both parents, for targeted locus amplification (TLA)-based phasing of heterozygous variants selectively at a gene of interest.Capture probes-based targeted sequencing of cfDNA from the pregnant mother and a tailored statistical analysis enables predicting fetalgene inheritance. MG-NIPD was validated for 18 pregnancies, focusing on CFTR, CYP21A2, and HBB. In all cases we could predict theinherited alleles with >98% confidence, even at relatively early stages (8 weeks) of pregnancy. This prediction and the accuracy ofparental haplotyping was confirmed by sequencing of fetal material obtained by parallel invasive procedures. MG-NIPD is a robustmethod that requires standard instrumentation and can be implemented in any clinic to provide families carrying a severe monogenicdisease with a prenatal diagnostic test based on a simple blood draw.

  Study EGAS00001002622

• Exome sequencing data for the DIRECT study.

  This dataset contains all available fastq files for gemline, baseline plasma/biopsy, and response assessment patient samples for the DIRECT study. The total number of samples was 729 (188 germline, 190 baseline plasma, 159 baseline biopsy, and 192 response assessment). The dataset files were generated from targeted (exome) Illumina sequencing performed on paired biopsy tissue and plasma cell free DNA.

  Dataset EGAD50000001409

• A Somatic Reference Standard for Cancer Genome Sequencing

  In this study, we separately performed PCR-free whole genome sequencing on the paired tumor/normal melanoma COLO-829 and lymphoblastoid COLO-829BL cell lines across three separate institutions (TGen, Illumina, Genome Sciences Centre at the British Columbia Cancer Agency). We performed a meta-analysis of all data, in combination with the originally reported analysis of these cell lines by Pleasance et al., and report a somatic reference standard based on consensus events. This standard can be used as a reference for tumor/normal whole genome analyses.

  Study phs000932

• CTSP: Clinical Trial Sequencing Project

  For the Clinical Trials Sequencing Project (CTSP), National Cancer Institute (NCI) will utilize whole genome sequencing and/or whole exome sequencing in conjunction with transcriptome sequencing to try to identify recurrent genetic alterations (mutations, deletions, amplifications, rearrangements) and/or gene expression signatures that would be important to the hypothesis(es) submitted by the investigators. The samples will be processed and submitted for genomic characterization using pipelines and procedures established within The Cancer Genome Analysis (TCGA) project. Data analysis will be performed as a collaboration between the National Clinical Trials Network (NCTN) Group and its investigators submitting the proposal. The investigators at the NCI-sponsored Genomic Data Analysis Center (GDAC) will characterize the samples. The NCTN Group will be responsible for providing the clinical data needed for the proposal to the open clinical system maintained by NCI CCG's Biospecimen Core Resource (BCR) at Nationwide Children's Hospital in Columbus, Ohio. The project team (Network Group/investigators and GDAC) will analyze the data together. Additionally, clinical and genomic data related to the analyses will also need to be registered by NCI and will be made available to qualified researchers via a controlled-access database (e.g., dbGaP) upon publication of the primary analysis described in the study proposal. A substudy description and its molecular data information are provided under its own page: phs001184 CTSP Diffuse Large B-Cell Lymphoma (DLBCL) CALGB 50303

  Study phs001175

• Genome-Wide Analysis of Aberrant Position and Sequence of Plasma DNA Fragment Ends in Patients With Cancer

  This study investigated fragmentation characteristics in plasma cell-free DNA and evaluated the relevance of such analysis for cancer diagnostics. Specifically, we performed whole genome sequencing (WGS) of healthy individuals and cancer patients, and evaluated genome-wide coverage and sequences surrounding fragment ends. This was a retrospective study of archived plasma samples. The WGS data are available through this submission. Detailed study design and findings were published in Budhraja et al. Science Translational Medicine 2023.

  Study phs003170

• Germline genome-wide association studies in women receiving neoadjuvant chemotherapy with or without bevacizumab on NSABP B-40

  Neoadjuvant chemotherapy (NAC) for breast cancer is widely employed. We performed genome-wide association studies (GWAS) to determine if germline genetic variability was associated with benefits, in terms of pathological complete response (pCR), disease-free survival (DFS), and overall survival (OS), in patients entered on the NSABP B-40 NAC (National Surgical Adjuvant Breast and Bowel Project, B-40, Neoadjuvant Chemotherapy) trial where some patients were randomized to receive bevacizumab, in addition to chemotherapy.

  Study phs001365

• Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL)

  Enteropathy associated T cell lymphoma (EATL) is frequently preceded by a state of refractoriness to the gluten-free diet, called “refractory celiac disease” or RCD. We aim to study which mutations and copy number aberrations are already manifest in RCD and to identify differences between RCD patients that do, and do not, develop EATL. We have applied whole exome sequencing to detect mutations and copy number aberration predictive for progression from RCD to EATL.

  Study EGAS00001006669

• Targeted plasma cell-free DNA sequencing for tissue-of-origin determination and donor-derived cell-free DNA quantification in organ transplant recipients and healthy controls

  The dataset comprises targeted deep methylation sequencing data used for both tissue-of-origin determination and donor-derived cfDNA quantification. It includes plasma cfDNA data from stable kidney transplant recipients (n = 31), stable liver transplant recipients (n = 20) and healthy controls (n = 23). In addition, plasma cfDNA samples collected early after transplantation were analyzed from kidney transplant recipients (n = 44) and liver transplant recipients (n = 40). The dataset also features genomic DNA data generated from whole blood (n = 10) and buffy coat (n = 3) from healthy controls, as well as from T cells (n = 1), B cells (n = 2), hepatocytes (n = 1) and kidney epithelium (n = 1). Lastly, genomic DNA data was generated from buffy coat of transplant recipients (n = 17). Here, “n” indicates the sample number.

  Dataset EGAD50000001446

• Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

  Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no comprehensive and direct accuracy evaluations of these tools is published. Here, we evaluate and determine the precision of five commonly used computational NIPT aneuploidy analysis tools, considering diverse sequencing depth (coverage), arbitrary sequencing read placement, and fetal DNA fraction on clinically validated NIPT samples.

  Study EGAS00001005323

• cfDNAme allows early prediction of PE

  Preeclampsia (PE) is a leading cause for peripartal morbidity, especially if developing early in gestation. To enable prophylaxis to prevent PE, it is essential that pregnancies at risk of PE are identified early, in the first trimester. To identify patients at risk, we profiled methylomes of plasma-derived cell-free DNA (cfDNA) from pregnant women. We detected DNA methylation differences between control and PE pregnancies that enable risk stratification of patients, at PE diagnosis but also presymptomatically, around 12 weeks of gestation.

  Study EGAS00001007071

• Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  Determining response to therapy for patients with pancreatic cancer can be challenging. We evaluated methods for assessing therapeutic response using cell-free DNA (cfDNA) in plasma samples from 40 patients with metastatic pancreatic cancer as part of the CheckPAC trial (NCT02866383). Patients were evaluated before and after initiation of therapy using tumor-informed plasma whole-genome sequencing (WGMAF), and genome-wide cfDNA fragmentation profiles and repeat landscapes (ARTEMIS-DELFI). Of those assessed with WGMAF, molecular responders had a median overall survival (OS) of 319 days compared to 126 days for non-responders (HR=0.29, 95% CI=0.11–0.79, p=0.011). For ARTEMIS-DELFI, patients with low scores after therapy initiation had a longer median OS than patients with high scores (233 days versus 172 days, HR=0.12, 95% CI=0.046-0.31, p<0.0001). We validated ARTEMIS-DELFI in a separate cohort of 40 patients with pancreatic cancer who were part of the PACTO trial (NCT02767557). These analyses suggest that non-invasive mutation and fragmentation-based cfDNA approaches can identify therapeutic response of individuals with pancreatic cancer.

  Study EGAS50000000923

• Identification of putative multiple myeloma (MM) susceptibility genes

  We sought to identify novel MM susceptibility genes using a collection of families with multiple cases of MM/MGUS, including 189 affected individuals from 40 families, and index cases from an additional 88 families, along with 170 early-onset (EO) MM cases (≤ 55 years). We analyzed a total of 347 affected individuals using whole exome (N=321) and whole genome (N=26) sequencing. Samples were identified and collected through nation-wide efforts in France, Sweden and Greece. We focused on rare (MAF<0.5%) germline protein truncating and likely deleterious missense variants in genes harboring variants in at least two families showing variant-disease segregation, and in additional index (≥2) and/or early-onset (≥2) cases.

  Study EGAS50000001259

• Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing (WGS) data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional and mutation type specific frequencies in tissue and cell-free DNA (cfDNA) of cancer patients that were associated with replication timing and other chromatin features. A machine learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected &gt;90% of lung cancer patients, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches, and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

  Study EGAS00001007248

• Covid19 WGS BAM files

  The Samples were collected from Saint James's Hospital, Dublin, and after informed consent Extracted Genomic DNA samples were prepared and sequenced using the Automated Illumina TruSeq PCR-free methodology.

  Study EGAS00001007048

• Privacy Notice for EGA Web user

  Privacy Notice for EGA Public Website This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by Mallory Freeberg, by: email at: mfreeberg@ebi.ac.uk , or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? For providing you access to the website and for offering support whilst using the website, we need your consent under Article 5 (2) of the IP 68 (equivalent to Article 6 (1)(a) of the GDPR). For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: IP addressesDate and time of a visit to the service website Operating systemAmount of data transmittedBrowserEmail address (only when support is requested by the user) The data controller will use your personal data for the following purposes: To provide the user access to the serviceTo better understand the needs of the users and guide future improvements of the serviceTo monitor website activities according to and in compliance with the Terms of UseTo better understand the needs of the website visitors and guide future improvements of the serviceTo conduct and monitor website security activitiesTo create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organisations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration.Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period.Request information to understand data processing activities when the results of these activities are applied to you.Object at any time to the processing of your personal data unless we can demonstrate that we have legitimate reasons to process your personal data.Request free of charge and without excessive delay rectification or erasure of your personal data if we have not been processing it respecting the data protection policies of the respective controllers. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. 9. CookiesWe use cookies and similar technologies that are strictly necessary for the correct functioning and security of the EGA website (for example, to enable core site features and to help protect the service). These cookies do not store information that directly identifies you.You can set your browser to block or delete cookies. Please note that if you disable strictly necessary cookies, parts of the website may not function properly.Published on February 6, 2019

  Documentation data-protection/privacy-notice/ega-website

• WGS

  Whole Genome sequencing. 1 ug of genomic DNA from each lymph node sample was used for the construction of a TruSeq DNA PCR Free (350) library before sequencing in a Illumina HiSeq X Ten (2 × 151 bp). Mean coverage 30x.

  Dataset EGAD00001005423

• cell-free methylated DNA immunoprecipitation and high-throughput sequencing data for samples from liver transplant recpients with graft pathologies

  Bam and indexed bam files after removal of duplicates and trimming of the unique molecular identifiers. Sequencing was performed on NovaSeq 6000 platform.

  Dataset EGAD00001010305

• Long-read sequencing for cell-free DNA analysis (human)

  31 pregnant women at different trimesters, 6 hepatitis B carriers, and 8 patients with hepatocellular carcinoma

  Dataset EGAD00001008980

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001010139

• Gene Expression Signatures in CATHGEN

  Case control cohort: The details have been previously published: American Heart Journal. 2010;160:371-379 e372. Briefly, a nested case:control cohort of CATHGEN participants who had experienced death or MI (n = 250) after their index catheterization and age-, sex-, and race-matched controls (n = 250) who were free of death/MI &#62; 2 years after cardiac catheterization was identified as part of the MURDOCK Horizon 1 Cardiovascular Disease Study.21 Sufficient RNA for microarray analysis was available in 447 members of this cohort. Observational cohort: 224 sequential CATHGEN samples were selected for whole blood RNA analysis, of which, 191 had sufficient RNA for microarray analysis.

  Study phs000551

• EGA FUSE Client

  EGA FUSE Client What is EGA FUSE Client? The EGA FUSE Client is a Java Native Runtime (JNR) based Filesystem in Userspace (FUSE) client that allows users to access authorised EGA files by presenting them in a virtual directory. This means that users can use authorised EGA files like regular files without having to download them first. The EGA FUSE Client is a useful tool for researchers who need to access and work with large amounts of EGA data. Why use EGA FUSE Client? The EGA FUSE Client provides several benefits for researchers working with EGA data: Efficient use of storage space: With the EGA FUSE Client, users can access authorised EGA files without having to download them first. This means that users can save storage space on their local machines. Faster access to data: Since users can access authorised EGA files directly through the EGA FUSE Client, they can work with the data more quickly than if they had to download the files first. Simplified workflow: The EGA FUSE Client presents authorised EGA files in a virtual directory, allowing users to work with the files like regular files. This simplifies the workflow for researchers who need to access and work with large amounts of EGA data. Get started with EGA FUSE Client To get started with EGA FUSE Client visit the EGA FUSE Client GitHub repository for more information and installation instructions.

  Documentation access/download/visualisation/fuse-client

• Platinum Genomes

  Improvement of variant calling in next-generation sequence data requires a comprehensive, genome-wide catalogue of high-confidence variants called in a set of genomes for use as a benchmark. We generated deep, whole-genome sequence data of seventeen individuals in a three-generation pedigree and called variants in each genome using a range of currently available algorithms. We used haplotype transmission information to create a phased "platinum" variant catalogue of 4.7 million single nucleotide variants (SNVs) plus 0.7 million small (1-50bp) insertions and deletions (indels) that are consistent with the pattern of inheritance in the parents and eleven children of this pedigree. Platinum genotypes are highly concordant with the current catalogue of the National Institute of Standards and Technology for both SNVs (&#62;99.99%) and indels (99.92%), and add a validated truth catalogue that has 26% more SNVs and 45% more indels. Analysis of 334,652 SNVs that were consistent between informatics pipelines yet inconsistent with haplotype transmission ("non-platinum") revealed that the majority of these variants are de novo and cell-line mutations or reside within previously unidentified duplications and deletions. The reference materials from this study are a resource for objective assessment of the accuracy of variant calls throughout genomes.

  Study phs001224

• Spatiotemporal Genomic Profiling of Intestinal Metaplasia Reveals Clonal Dynamics of Gastric Cancer Progression

  Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. We analyzed 1256 gastric samples (1152 IMs) from 692 subjects from a 10-year prospective study. We identified 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9), largely occurring as subclonal events. Analysis of clonal dynamics between and within subjects, and also longitudinally across time, revealed that IM clones are likely transient but increase in size upon progression to dysplasia, with eventual transmission of genetic events to paired GCs. Single-cell and spatial profiling highlighted changes in tissue ecology and lineage heterogeneity in IM, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling revealed expression-based molecular subtypes of IM, including a body-resident “pseudoantralized” subtype associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to progress. Our results raise opportunities for GC precision prevention and interception by highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression.

  Study EGAS00001007067

• Heat selection enables highly scalable methylome profiling in cell-free DNA for noninvasive monitoring of cancer patients

  Genome-wide analysis of cell-free DNA (cfDNA) methylation profile has been recognized as a promising approach for sensitive and specific detection of many cancers. However, scaling such genome-wide assays for clinical translation is impractical due to the high cost of whole genome bisulfite sequencing. We have shown that the small fraction of GC-rich genome is highly enriched in CpG sites and disproportionately harbors the majority of cancer-specific methylation signature. Here, we report on the simple but effective Heat enrichment of CpG-rich regions for Bisulfite Sequencing (Heatrich-BS) platform that allows for focused methylation profiling in these highly informative regions. Our novel method and bioinformatics algorithm enable accurate tumor burden estimation with high sensitivity and quantitative tracking of colorectal cancer patient’s response to treatment, at much reduced sequencing cost suitable for frequent monitoring. We also show, for the first time, tumor epigenetic subtyping from cfDNA using Heatrich-BS, which could enable patient stratification from non-invasive liquid biopsy. As such, Heatrich-BS holds great potential for highly scalable screening and regular monitoring of cancer using liquid biopsy.

  Study EGAS00001006198