12405 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

in 27.40 milliseconds.

• Single molecule molecular inversion probe capture developed using the CIViC database

  This study evaluated the use of the Clinical Interpretations of Variants in Cancer database (CIViC) to develop an Open-sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP is a resource that allows users to develop a clinical capture panel that can be linked back to clinical summaries within the CIViC database. This method for capture panel development and variant annotation was tested using 27 cancer samples from 5 tumor subtypes with original exome or genome sequencing. Specifically, using OpenCAP, 111 variants were identified as relevant for the capture panel and 2,027 smMIPs were designed to target these variants. The smMIPs panel design was employed on all samples to validate the capture panel design. When compared to original sequencing, the CIViC smMIPs capture panel demonstrated a 95% sensitivity for variant detection (n = 61 variants). Additionally, the CIViC smMIPs capture panel identified 182 additional clinically relevant variants that had been missed on original sequencing.

  Study phs001890

• The Microbial Ecology of Bacterial Vaginosis: A Fine Scale Resolution Metagenomic Analysis

  Archived self-collected vaginal swabs were utilized from a pilot study of vaginal douching cessation (NIH/NIAID R03-AI061131). Thirty-nine non-pregnant, reproductive-age women who reported the use of vaginal douche products in the two months prior to screening were enrolled. Thirty-three of these successfully completed the 16-week longitudinal study. Participants self-collected vaginal swabs and smears twice weekly. We report sequences based on the analysis of 16S rRNA gene sequences amplified from whole genomic DNA isolated from the swabs. Bacterial vaginosis (BV) is defined by Gram's stain of vaginal fluid (Nugent's score =7). The large body of information generated will facilitate understanding of vaginal microbial community dynamics, the etiology of BV, and drive the development of better diagnostic tools for BV. Furthermore, it is hoped that the information will enable a more personalized treatment of BV and ultimately, prevent adverse sequelae associated with BV.

  Study phs000261

• Towards a Genomic Understanding of Myeloma

  This project was designed to describe genetic abnormalities in primary samples from patients with multiple myeloma by next generation sequencing. We generated sequence data from multiple myeloma (MM) patients analyzing DNA both from tumor cells (purified from bone marrow using CD138 selection as a marker of plasma cells) and from normal peripheral blood cells (either whole blood or Ficoll-purified mononuclear cells). Using massively parallel sequencing technology (Illumina GA-2 or HiSeq)), we performed whole-genome sequencing (WGS) and/or whole-exome sequencing (WES). The initial set currently deposited contains data from 38 MM patients (23 patients surveyed by WGS and 16 patients by WES, with one patient analyzed by both approaches). Genomes were sampled to high depth, obtaining an average of 33X coverage and 104X coverage for WGS and WES tumors, respectively. The normal samples had similar coverage. Our goal is to help researchers understand the complex genetic landscape of multiple myeloma and provide a resource for the generation of biological hypotheses.

  Study phs000348

• Genome-Wide Association Study of Parkinson Disease: Genes and Environment

  This is a gene-environment study of Parkinson's disease. PD is a common, progressive, age-related, movement disorder that affects 1-2% of the people over the age of 65. The NeuroGenetics Research Consortium (NGRC) is the infrastructure of the study. Protocols and methods are standardized across NGRC clinics and labs as much as possible. The 2000 patients and 2000 control subjects selected for this GWAS were recruited at the NGRC-affiliated movement disorder clinics in Oregon, Washington, Georgia and New York. All 4000 subjects were white and all DNA samples were extracted from whole blood and unamplified. Seventy-five percent of subjects have data on cigarette smoking and caffeinated coffee consumption, which are inversely associated with PD risk. This study population represents the norm for clinical genetic studies of PD; i.e., NGRC estimates of risk to relatives, heritability, genotype frequencies, and exposure frequencies (see references) are very close to estimates from meta-analyses.

  Study phs000196

• NHLBI TOPMed: Pediatric Asthma Controller Trial (PACT)

  After a 2-4 week assessment/characterization run-in period, 6-14 year-old children who met NAEPP criteria for mild-moderate persistent asthma specifically based on symptom criteria and methacholine PC20 ≤ 12.5 mg/ml and FEV1 ≥ 80% were randomized to one of the three active treatment arms for 12 months. Randomization was stratified according to clinical center, bronchodilator response (< 12% or ≥ 12%), race (Caucasian or non-Caucasian), and methacholine PC20 (< 2 or ≥ 2 mg/ml). The primary outcome variable was the proportion of asthma-free days during the 12-month treatment period. Secondary outcomes included other measures of asthma control (percentage of rescue-free days, albuterol-free days, and episode-free days; the number of asthma exacerbations requiring prednisone therapy and the time to the first asthma exacerbation), forced oscillation and spirometry, reversibility (FEV1 pre- and post 2 puffs of albuterol MDI), methacholine PC20, exhaled nitric oxide, and asthma-related quality of life.

  Study phs001730

• Structurally Complex Osteosarcoma Genomes Exhibit Limited Heterogeneity within Individual Tumors and across Evolutionary Time

  A key characteristic of osteosarcoma is extensive and complex genomic rearrangements. However, published models explaining how these genomic rearrangements occur disagree about if these rearrangements occur early in tumor progression and then are stable afterwards, or if there is ongoing genomic instability. Previous studies have employed bulk sequencing technologies to characterize genomic alterations. A limitation of this approach is that it averages all changes within the bulk sample, essentially masking intra-sample heterogeneity and making evaluation of ongoing genomic instability difficult. To overcome this limitation and compliment previous work, we utilized single-cell whole genome sequencing to quantify somatic copy number alterations (SCNA). By interrogating individual cells within a sample, we were able to examine intra-sample heterogeneity. We found that the SCNA patterns between cells within a single sample were remarkably consistent, which supports the concept that the genomes of osteosarcoma tumors are relatively stable after early genome fragmentation events.

  Study phs003209

• Multi-Ethnic Study of Atherosclerosis (BioLINCC)

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics).

  Study phs003288

• Genomics and Methylation of Neuroendocrine Prostate Cancer from cfDNA (Cornell/Trento 2019)

  A subset of castration resistant prostate cancers develop small cell neuroendocrine prostate cancer (NEPC) as a mechanism of treatment resistance. Metastatic tissue biopsies to evaluate for NEPC transformation are invasive and challenging to perform serially. We performed whole exome and whole genome bisulfite sequencing of plasma cfDNA and matched tumor biopsy samples from 62 patients with metastatic prostate cancer along the disease spectrum to evaluate for NEPC associated genomic and epigenomic features. Multiple tissue biopsies and/or plasma time points were included for a subset of patients to characterize disease heterogeneity and dynamic changes. Computational analysis of clonality and allele specific quantification allowed for detailed comparison of matched tumor tissue and cfDNA data (CLONET v2). Methylation profiles detected from tissue and plasma data were compared and NEPC specific alterations were evaluated in cfDNA. The study supports the feasibility of a plasma based assay for the detection of NEPC.

  Study phs001752

• Childhood Cancer Data Initiative (CCDI): Integrating Longitudinal Clinical, Sociodemographic and Genomic Data into the NCCR

  The goal of this study is to contribute clinical and genomic data from a large institutional cohort of pediatric cancer patients who had tumor genomic profiling between 2013 and 2019 at Dana-Farber/Boston Children's Hospital Cancer and Blood Disorders Center. Clinical data include demographics, diagnosis (classified according to the International Classification of Diseases for Oncology (ICD-O-3.2), stage, and biospecimen associated data. Tumors were sequenced with OncoPanel, a targeted next-generation DNA sequencing panel of up to 447 cancer genes for detection of single-nucleotide variants (SNV), insertions, and deletions, and copy number alterations (CNA), as well as selected intronic regions for up to 60 genes for the detection of structural variants (SV). This dataset includes a patient and sample identifier (GENIE ID) that can be used to link the genomic data included in this dataset to additional longitudinal clinical cancer data on a subset of patients that was submitted to the National Childhood Cancer Registry (NCCR).

  Study phs002677

• Type I Interferon Exacerbates Mycobacterium Tuberculosis Induced Human Macrophage Death

  In this study, we tested whether type I interferons (IFN-I), namely IFN-alpha and IFN-beta, may promote Mycobacterium tuberculosis (Mtb) pathogenesis by exacerbating cell death of human monocyte-derived macrophages (MDM) infected with Mtb. We differentiated the MDM under two different published methods (see Document Method.pdf for Table 1 of Methods). To determine if MDM infected with Mtb upregulates IFN-I transcripts, signaling factors, or IFN-I stimulated genes (ISGs), the MDM were infected with Mtb or treated with an activator of stimulator of IFN genes (STING), diamidobenzimidazole (di-ABZI). STING activation acted as a positive control for IFN-I induction and ISG upregulation. Indeed, di-ABZI treated MDM differentiated under both methods upregulated ISGs 24 hpi. At 24 hour post treatment, MDM differentiated under one method, but not under another method, upregulated ISGs, such as ISG15, IFITM3, and CXCL10, upon Mtb infection. MDM differentiated under both methods upregulated ISGs upon di-ABZI treatment.

  Study phs003607

• Genomic Profiling of Melanoma

  This study reports on genomic profiling [whole-exome sequencing (WXS), bulk RNA sequencing (RNA-seq), and/or single-cell RNA sequencing (scRNA-seq)] of patient-derived melanoma samples and matched normal samples. The goal is to elucidate the genetic and cellular basis of sun-exposed and sun-shielded melanomas and to relate these findings to survival and regional metastasis. Specimens were collected by the Tissue Resource Core of the Yale SPORE in Skin Cancer with participants' informed signed consent according to Health Insurance Portability and Accountability Act (HIPAA) regulations with a Human Investigative Committee protocol. The melanomas used for sequencing were from fresh or snap-frozen tumors, or from short-term cell cultures. The cell cultures were routinely checked for mycoplasma contamination and were discarded when found positive. Matching normal DNA was from circulating lymphocytes or normal skin. We also include 77 WES-sequenced samples from the Yale Spitzoid neoplasm repository, which collects specimen and data according to a protocol approved by the Yale Human Investigative Committee.

  Study phs000933

• 1000 Genomes Used for Cloud Testing

  WARNING: This is a test data set. The phenotype data was not checked to match 1000 Genomes project. Use with caution.This study provides public access to a demonstration subset of 1000 genomes sequence data in dbGaP. It is intended to be used by software developers who design, implement and validate pipelines for dbGaP data. While this project distributes only public data, it uses dbGaP security mechanisms which include a project-specific security key and a decryption password. Since the data are public, the key and password for this project will be included by SRA into public demonstration packages that permit users to test and validate the security of their computational pipelines. Note that all public users of this data will be logged under the same project and account ID. The datasets attached to this project must be restricted to 1000 Genomes data identical to the project's public FTP site. To access these test data using SRA toolkit use prj_phs710EA_test.ngc.

  Study phs000710

• Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics - RNAseq

  Targeting cancer-specific HLA-peptide complexes is a promising immunotherapy approach, with mutated neoantigens offering high value for their immunogenicity and cancer-specificity. Selecting immunogenic targets requires personalized prioritization of cancer-specific immunopeptides. Mass spectrometry (MS)-based immunopeptidomics supports this process by directly identifying cancer-specific antigens and informing global presentation patterns to refine immunogenicity predictions. Clinical pipelines, however, must balance global depth and target sensitivity compounded by low input samples and time constraints. Here, we present NeoDiscMS, an extension of the NeoDisc pipeline, enabling personalized immunopeptidomics data acquisition. By leveraging real-time NGS-guided spectral acquisitions, NeoDiscMS maximizing sensitivity with minimal loss of global depth. NeoDiscMS improves TAA-derived peptide detection up to 20% and enhances neoantigen identification confidence compared to the clinical gold standard method. Designed for effectiveness and ease of use, it requires minimal effort for implementation. NeoDiscMS advances personalization in clinical antigen discovery by enabling more sensitive neoantigen detection while seamlessly integrating into existing workflows.

  Study EGAS50000000977

• High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. These tumors were profiled using whole-genome sequencing (WGS) or whole-exome sequencing (WES) to identify somatic mutations, WGS or low-pass WGS to detect copy number alterations, targeted capture sequencing to assess MYC and BCL2 structural variants, and RNA sequencing. The genetic features of HGBCL-NOS were compared to those of diffuse large B-cell lymphoma (DLBCL-NOS) and EBV-negative adult Burkitt lymphoma (BL). DLBCL-NOS tumors underwent targeted capture sequencing using a panel of 125 genes recurrently mutated in aggressive B-cell lymphomas. BL biopsies were drawn from the Burkitt Lymphoma Genome Sequencing Project and had available WGS (dbGaP Study Accession: phs000527.v18.p6).

  Study EGAS50000000932

• Sensitive neoantigen discovery by real-time mutanome-guided immunopeptidomics - WES

  Targeting cancer-specific HLA-peptide complexes is a promising immunotherapy approach, with mutated neoantigens offering high value for their immunogenicity and cancer-specificity. Selecting immunogenic targets requires personalized prioritization of cancer-specific immunopeptides. Mass spectrometry (MS)-based immunopeptidomics supports this process by directly identifying cancer-specific antigens and informing global presentation patterns to refine immunogenicity predictions. Clinical pipelines, however, must balance global depth and target sensitivity compounded by low input samples and time constraints. Here, we present NeoDiscMS, an extension of the NeoDisc pipeline, enabling personalized immunopeptidomics data acquisition. By leveraging real-time NGS-guided spectral acquisitions, NeoDiscMS maximizing sensitivity with minimal loss of global depth. NeoDiscMS improves TAA-derived peptide detection up to 20% and enhances neoantigen identification confidence compared to the clinical gold standard method. Designed for effectiveness and ease of use, it requires minimal effort for implementation. NeoDiscMS advances personalization in clinical antigen discovery by enabling more sensitive neoantigen detection while seamlessly integrating into existing workflows.

  Study EGAS50000000976

• Genomic Landscape of Apical Periodontitis

  We undertook the first genome-wide association (GWAS) study of apical periodontitis, enrolling 932 patients with deep carious lesions at UTHealth School of Dentistry and the University of Pittsburgh School of Dental Medicine. We used a case-control design to compare those with apical periodontitis to those without. Genotype data was generated for all participants and imputed using the TOPMed reference panel. We performed a single-variant association testing, a subphenotype analysis, and a genetically regulated expression association analysis, and generated a polygenic risk score and performed phenome-wide association analysis. We identified eight near-genome-wide significant loci for our primary outcome, eight genes where genetically regulated expression was associated with apical periodontitis status, and 33 phecodes that were associated with the generated polygenic risk score. We also replicated three loci previously reported in the literature. Genotype, phenotype, and results from the primary association analysis will be available via dbGaP.

  Study phs003252

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies

  Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with our atlas of pineal gland development to retrace cellular origins. Integrative computational analyses maps pineoblastoma origins to transient cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncovers a tumor-associated photoreceptor signature common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.

  Study EGAS50000001457

• STimage: Robust and interpretable prediction of gene markers and cell types from spatial transcriptomics data

  Spatial transcriptomics (ST) links tissue morphology with gene expression values, opening new avenues for digital pathology. Deep learning models are used to predict gene expression or classify cell types directly from images, offering significant clinical potential but still requiring improvements in interpretability and robustness. We present STimage as a comprehensive suite of models to predict spatial gene expression and classify cell types directly from standard H\&E images. STimage enhances robustness by estimating gene expression distributions and quantifying both data-driven (aleatoric) and model-based (epistemic) uncertainty using ensemble approach with foundation models. Interpretability is achieved through attribution analysis at single-cell resolution integrated with histopathological annotations, functional genes, and latent representations. We validated STimage across diverse datasets, demonstrating its performance across various platforms. STimage-predicted gene expression can stratify patient survival and predict drug response. By enabling molecular and cellular prediction from routine histology, STimage offers a powerful tool to advance digital pathology.

  Study EGAS50000001503

• Quick Guide for data submission

  Quick Guide This is a quick guide to submit data to the EGA. Please select data type to display the right detailed instructions. Sequence data Array-based data Get your submission account You first need to create your EGA user. Then, once your account has been verified by the Help Desk team, request your submission account and provide details of the data type and platform(s) in your submission. Register Study/DAC Use Submitter Portal to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the and upload it to your inbox using SFTP. Register experiments and runs Associate each data file to a registered sample and study by Linking files to samples. Details of the experimental procedure you followed must be provided. Finalise your submission Group your runs/analysis into datasets and link them to your new or existing DAC and policy using DAC Portal. Data request are done at a dataset level, thus files within a datasets must share release conditions. Release and admin When finalising the submission, set a released date to instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released. Get your submission account Fill the submission form and provide details of the data type and platform(s) in your submission. Register Study/DAC Use EGA Programmatic submission to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the EgaCryptor and upload it using default FTP clients or Aspera. Complete the Array-Format (AF) spreadsheet Download the AF spreadsheet and complete all four sections. Return the spreadsheet to the EGA helpdesk. Release and admin Instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released.

  Documentation submission/quickguide

• Uterine_Atlas_Endometriosis

  Uterine Atlas Endometriosis Endometriosis is a chronic inflammatory disease driven by oestrogen, affecting around 10% of women of child-bearing again world-wide. It is described by the presence of endometrium-like tissue outside of the uterus (ectopic endometriosis tissue) and debilitating chronic pain. There is a lack of understanding of endometriosis pathogenesis, as well as cellular composition of both the eutopic endometrium and ectopic endometriosis tissue of endometriosis patients.There are therefore two main aims for this study. Using single cell genomics and spatial methods we aim to: I) characterise endometrial cellular census in women with and without endometriosis II) characterise cellular census of ectopic endometriosis tissue Furthermore, we aim to establish endometrial organoids and endometriosis organoids from the samples collected and characterise these using single cell genomics and spatial methods. 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 EGAS00001004725

• Whole_genome_sequencing_in_a_multiplex_Crohn_s_disease_family

  In 2009 we identified a four-generation family with over 700 members and 41 affected with Crohn's disease (CD). At the time we sequenced the exome of 6 affected individuals but did not identify any coding variants which appear to explain the high prevalence of disease. Since then we have collected DNA from a large number of additional family members, genotyped linkage arrays on the entire family to refine genomic regions shared by identity by descent and genotyped affected and unaffected members at known CD risk loci identified by Genome Wide Association Studies (GWAS). These analyses have confirmed that a significant unexplained excess of disease remains after accounting for all known genetic factors, and that several regions of the genome are shared by a large fraction of affected individuals. We therefore perform whole genomes sequencing from 8 individuals which will allow us to impute the complete sequence of nearly all the members of the two largest and most severely affected branches of the family.

  Study EGAS00001000060

• Searching for variants associated with endometriosis

  We explored regulatory mechanism of a SNP on chromosome 9p21 associated with endometriosis by leveraging “allele-specific” functional genomic approaches. By re-sequencing 1.29 Mb of 9p21 region and scrutinizing DNase-seq data from the ENCODE project, we prioritized rs17761446 as a candidate functional variant that was in perfect linkage disequilibrium with the original GWAS SNP (rs10965235) and located on DNase I hypersensitive site. Chromosome conformation capture followed by high-throughput sequencing revealed that the protective G allele of rs17761446 exerted stronger chromatin interaction with ANRIL promoter. We demonstrated that the protective allele exhibited preferential binding affinities to TCF7L2 and EP300 by bioinformatics and chromatin immunoprecipitation (ChIP) analyses. ChIP assays for histone H3 lysine 27 acetylation and RNA polymerase II reinforced the enhancer activity of the SNP site. The allele specific expression analysis for eutopic endometrial tissues and endometrial carcinoma cell lines showed that rs17761446 was a cis-regulatory variant where G allele was associated with increased ANRIL expression.

  Study EGAS00001001741

• Single cell RNA sequencing and Whole Genome Sequencing on different cells from the same sample for a triple negative patient derived xenograft and ovarian cancer cell lines.

  Measuring gene expression of genomically defined tumour clones at single cell resolution would associate functional consequences to somatic alterations, as a prelude to elucidating pathways driving cell population growth, resistance and relapse. In the absence of scalable methods to simultaneously assay DNA and RNA from the same single cell, independent sampling of cell populations for parallel measurement of single cell DNA and single cell RNA must be computationally mapped for genome-transcriptome association. Here we present clonealign, a robust statistical framework to assign gene expression states to cancer clones using single-cell RNA-seq and DNA-seq independently sampled from an heterogeneous cancer cell population. We apply clonealign to triple-negative breast cancer patient derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either DNA-Seq or RNA-Seq alone.

  Study EGAS00001003387

• Tracking the genomic evolution of esophageal adenocarcinoma through neoadjuvant chemotherapy

  Esophageal adenocarcinomas (EACs) are associated with dismal prognosis. Deciphering the evolutionary histories of this disease may shed light on therapeutically tractable targets and reveal changing mutational processes during the disease course and following neoadjuvant chemotherapy (NAC). We exome sequenced 40 tumor regions from 8 patients with operable EACs both before and after platinum-containing NAC. This revealed the evolutionary genomic landscape of EACs with the presence of heterogeneous driver mutations, parallel evolution, early genome doubling events and an association between high intratumor heterogeneity and poor response to NAC. Multi-region sequencing demonstrated a significant reduction in T>G mutations within a CTT context when comparing early and late mutational processes and the presence of a platinum signature with enrichment of C>A mutations within a CpC context following NAC. EACs are characterized by the presence of amplifications containing targetable oncogenes present before and after chemotherapy that may provide a rationale for future therapeutic approaches.

  Study EGAS00001001254