Search Results - EGA European Genome-Phenome Archive

Comprehensive characterization of pre- and post-treatment samples of breast cancer reveal potential mechanisms of chemotherapy resistance

When locally advanced breast cancer is treated with neoadjuvant chemotherapy, the recurrence risk is significantly higher if no complete pathologic response is achieved. Identification of the underlying resistance mechanisms is essential to select treatments with maximal efficacy and minimal toxicity. Here we employed gene expression profiles derived from 317 HER2-negative treatment-naïve breast cancer biopsies of patients who underwent neoadjuvant chemotherapy, deep whole exome and RNA-sequencing profiles of 22 matched pre- and post-treatment tumors, and treatment outcome data to identify biomarkers of response and resistance mechanisms. Molecular profiling of treatment-naïve breast cancer samples revealed that expression levels of proliferation, immune response and extracellular matrix (ECM) organization combined predict response to chemotherapy. Triple negative patients with high proliferation, high immune response and low ECM expression had a significantly better treatment response and survival benefit (HR 0.29, 95% CI 0.10-0.85; p=0.02), while in ER+ patients the opposite was seen (HR 4.73, 95% CI 1.51-14.8; 0=0.008). The characterization of paired pre-and post-treatment samples revealed that aberrations of known cancer genes were either only present in the pre-treatment sample (CDKN1B) or in the post-treatment sample(TP53, APC, CTNNB1). Proliferation-associated genes were frequently down-regulated in post-treatment ER+ tumors, but not in triple negative tumors. Genes involved in ECM were upregulated in the majority of post-chemotherapy samples. Genomic and transcriptomic differences between pre- and post-chemotherapy samples are common and may reveal potential mechanisms of therapy resistance. Our results show a wide range of distinct, but related mechanisms, with a prominent role for proliferation- and ECM-related genes.

Study EGAS00001005876

Multi-omic analysis of the tumor microenvironment shows clinical correlations in Ph1 study of atezolizumab +/- SoC in MM

Multiple myeloma (MM) remains incurable, and treatment of relapsed/refractory (R/R) disease is challenging. There is an unmet need for more targeted therapies in this setting; deep cellular and molecular phenotyping of the tumor and microenvironment in MM could help guide such therapies. This phase 1b study (NCT02431208) evaluated the safety and efficacy of the anti-programmed death-ligand 1 monoclonal antibody atezolizumab (Atezo) alone or in combination with the standard of care (SoC) treatments lenalidomide (Len) or pomalidomide (Pom) and/or daratumumab (Dara) in patients with R/R MM. Study endpoints included incidence of adverse events (AEs) and overall response rate (ORR). A novel unsupervised integrative multi-omic analysis was performed using RNA sequencing, mass cytometry immunophenotyping, and proteomic profiling of baseline and on-treatment bone marrow samples from patients receiving Atezo monotherapy or Atezo+Dara. A similarity network fusion (SNF) algorithm was applied to preprocessed data. Eighty-five patients were enrolled. Treatment-emergent deaths occurred in 2 patients; both deaths were considered unrelated to study treatment. ORRs ranged from 11.1% (Atezo+Len cohorts, n=18) to 83.3% (Atezo+Dara+Pom cohort, n=6). High-dimensional multi-omic profiling of the tumor microenvironment and integrative SNF analysis revealed novel correlations between cellular and molecular features of the tumor and immune microenvironment, patient selection criteria, and clinical outcome. Atezo monotherapy and SoC combinations were safe in this patient population and demonstrated some evidence of clinical efficacy. Integrative analysis of high dimensional genomics and immune data identified novel clinical correlations that may inform patient selection criteria and outcome assessment in future immunotherapy studies for myeloma.

Study EGAS00001007286

Molecular Subtyping Reveals Immune Alterations Associated with Progression of Bronchial Premalignant Lesions

Exposure to cigarette smoke creates a field of injury throughout the entire respiratory tract inducing genomic alterations that lead to an "at-risk" airway where lung cancers develop. Lung squamous cell carcinoma (SCC) arises in the epithelial layer of the bronchial airways and is often preceded by the development of premalignant lesions (PMLs). Effective tools to identify and treat premalignant lesions at highest risk of progression to invasive carcinoma are not available. Endobronchial biopsies and brushings were obtained from high-risk subjects undergoing lung cancer screening at approximately 1-year intervals by white light and auto-fluorescence bronchoscopy and computed tomography at the Roswell Park Cancer Institute in Buffalo, NY. Subjects were selected that had biopsies collected in repeat locations via serial bronchoscopies. mRNA sequencing was performed on a discovery cohort (DC) of samples comprising endobronchial biopsies and brushes collected between 2010 and 2012 (n=30 subjects, n=197 biopsies, and n=91 brushings). mRNA sequencing was subsequently performed on a validation cohort (VC) of samples comprising endobronchial biopsies and brushes collected between 2010 and 2015 (n=20 subjects, n=111 biopsies, and n=49 brushings). Data analysis identified four distinct molecular subtypes (Proliferative, Inflammatory, Secretory, and Normal) in the bronchial biopsies that correspond to a spectrum of biological and morphological alterations. The Proliferative subtype was enriched with dysplastic PMLs from current smokers that exhibit up-regulation of metabolic and cell cycle pathways and down-regulation of cilium-associated processes. Molecular subtype classification in the validation cohort biopsies replicated these significant clinical and biological associations. Airway brushes from normal fluorescing areas of the large airway classified as the Proliferative subtype specifically predict the presence of biopsies of this same subtype. Within the Proliferative subtype, genes associated with interferon signaling and antigen processing and presentation were observed to be down-regulated among dysplastic biopsies that persist or progress in the future. Innate and adaptive immune cells were computationally predicted to be depleted in these biopsies and this was confirmed via immunofluorescence staining of adjacent biopsies. These findings provide a proof of concept that molecular biomarkers of endobronchial biopsies can enhance histopathological grading and that immunoprevention strategies are an important future direction in intercepting the progression of PMLs to lung cancer.FASTQ files from the RNA sequencing of these biopsies and brushings will be available via dbGaP.

Study phs003185

Targeted_sequencing_of_genes_recurrently_mutated_in_AML

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

Study EGAS00001000408

RNA sequencing of CCO- and CCO+ human hepatocytes

RNAseq data from Passman et al 2023. Clonal CCO-deficient hepatocyte patches and nearby CCO-proficient hepatocytes were identified in morphologically normal human livers and sampled at varying distances along the PT-CV axis. Samples are named according to their location within the liver lobule, with "PT" denoting samples abutting the portal triad, "CV" denoting samples abutting the central hepatic vein, and "Mid" sampled acquired midway between these structures. Normal human liver is thought to be generally quiescent, however clonal hepatocyte expansions have been observed but neither their cellular source nor their expansion dynamics have been determined. Knowing the hepatocyte cell of origin, and their subsequent dynamics and trajectory within the human liver will provide an important basis to understand disease-associated dysregulation. Here we use in vivo lineage tracing and a combination of methylation sequence analysis to demonstrate normal human hepatocyte ancestry. We exploit next generation mitochondrial sequencing to determine hepatocyte clonal expansion dynamics across spatially-distinct areas of laser-capture microdissected clones, in tandem with computational modelling in morphologically-normal human liver.

Study EGAS00001006984

Childhood Cancer Data Initiative (CCDI): Molecular Characterization across Pediatric Brain Tumors and Other Solid and Hematologic Malignancies for Research, Diagnostic, and Precision Medicine

This study contains tumor and germline WGS, RNA-Seq, Clinical Panel Sequencing, and other omics and molecular data for patients with pediatric brain tumors and other solid and hematologic malignancies. This data has been collected from multiple organizations including the multi-institute Children's Brain Tumor Network (CBTN), the Pacific Pediatric Neuro-Oncology Consortium (PNOC), and the Children's Hospital of Philadelphia Division for Genomic Diagnostics (CHOP DGD). In addition to being available pre-publication and without embargo via dbGaP and the NCI Cancer Research Data Commons, this data is made available via Cavatica, PedcBioPortal and the Kids First Data Resource Portal. Collectively, this availability strives to accelerate the research process and enable members of the scientific and patient communities to partner and make discoveries faster than ever before.In 2019, the CBTN launched the Pediatric Brain Tumor Atlas, which now comprises the largest collection of childhood brain tumor data in the world. This resource is helping accelerate not only brain tumor research, but is also empowering discovery for other rare childhood conditions. Brain tumors are the most common form of cancer in children aged 0-19 in the United States, and are the largest cause of cancer-related deaths. The estimated number of new cases in 2019 is nearly 3,800, and thus brain tumors are a rare disease. Despite their relative rarity, the years of potential life lost due to brain tumors in 2009 was estimated at 47,631 years for children and adolescents aged 0-19 in the United States; this is a disproportionate amount of life lost compared to adult cancers and represents an unrecognized societal threat. There is an urgent need to improve therapies for these children. This sequencing cohort defines the largest, clinically annotated pediatric brain tumor cohort study to date and seeks to define the intersection of germline and somatic underpinnings of pediatric brain tumors across a shared developmental context of cancer and structural birth defects.

Study phs002517

Kids First: Genomic Etiologies of CHARGE Syndrome, Related Conditions and Structural Anomalies

Developmental disorders with structural birth defects account for the majority of morbidity and mortality in children's hospitals, and the genetic bases of many clinical phenotypes remain unknown. Genetic testing for individuals with structural malformations has uncovered the basis of many such birth defects; however, many more cases remain unsolved, posing challenges for diagnosis, treatment, and prevention. Multiple anomaly conditions are particularly challenging to diagnose, since they often present with unique combinations of clinical features that vary widely between affected individuals, even in the same family. CHARGE Syndrome (Coloboma of the eye, Heart Defects, Atresia of the choanae, Retardation of growth and development, Genital abnormalities including pubertal delay and infertility, Ear abnormalities with deafness and vestibular disorders) is a multiple anomaly condition that affects a wide variety of organ systems. CHARGE Syndrome is caused in most cases by monoallelic pathogenic variants in CHD7, the gene encoding ATP-dependent helicase chromodomain DNA binding protein 7. Both de novo and inherited variants in CHD7 have been reported in CHARGE, and a growing number of families present with individuals who test positive for a pathogenic CHD7 variant yet exhibit only mild features. Similarly, individuals with CHARGE Syndrome often exhibit broad variability and reduced penetrance of clinical features, consistent with pleiotropic roles for CHD7 during development and/or additional genetic contributors or modifying alleles. Recent work has also implicated RERE, KMT2D, EP300, and PUF60 in having a role in CHARGE Syndrome.We hypothesize that (1) some cases of CHARGE are due to other genetic etiologies including oligogenicity, and (2) genetic modifiers contribute to the broad clinical variability and reduced penetrance of CHARGE features. To address these hypotheses, we have generated a cohort of 223 deeply clinically phenotyped individuals with CHARGE Syndrome and related disorders and structural anomalies who tested negative by chromosomal microarray, single gene sequencing, next generation panel sequencing, or exome sequencing. These individuals exhibit clinical CHARGE-like features including structural birth defects affecting craniofacial, ocular, neurosensory, brain, heart, mediastinal, renal, genitourinary, and skeletal organs. Our cohort includes these 223 individuals as well as affected and unaffected family members who consented to clinical and research genetic testing and donated blood samples for DNA and RNA isolation and sequencing. Building on this valuable cohort, we propose to use exome and genome sequencing to identify novel genetic etiologies of CHARGE and related developmental disorders for which alternative genetic tests have been inconclusive. Identification of novel pathogenic genetic variants and contributing modifier alleles within the coding and non-coding portion of the genome of these individuals will improve genetic diagnosis and provide important insights toward understanding the developmental mechanisms of structural birth defects.

Study phs002592

Transcriptomic Analysis of Pluripotent Stem Cell-Based Model of Human Amniogenesis

The amniotic epithelium is the innermost layer of the amniochorionic membrane that physically divides the maternal and fetal environments. Amniogenesis is initiated during implantation in humans. In implanting blastocysts, the pluripotent epiblast cells undergo apical-basal polarization to form a cyst with a central lumen, the future amniotic cavity. This event is followed by the fate transition of pluripotent epiblast cells at the uterine-proximal pole of the cyst to squamous amniotic ectoderm, forming a sharp boundary between amnion and pluripotent epiblast portions of the cyst. To enable mechanistic investigations into amnion fate progression, several in vitro models based on human pluripotent stem cells were recently developed. In this study, transcriptomic features of human pluripotent stem cell-derived amniogenesis models were examined.

Study phs002184

Multi-omics profiling identifies two epithelioid sarcoma molecular subtypes with distinct signaling and immune characteristics

Epithelioid sarcoma (EpS) is an aggressive sarcoma, characterized by the loss of SMARCB1 expression. EpS is traditionally classified as distal or proximal according to clinicopathological features, but its molecular characteristics remain largely unknown. To establish an EpS molecular classification and uncover determinants of inter- and intra-patient heterogeneity in EpS, we used multi-omics profiling and integrated the genomic, transcriptional and methylome landscapes with single-cell RNA sequencing on fresh samples as well as spatial transcriptomics. We identified two molecular subtypes of EpS: “distal-like” and “proximal-like”, which were distinct from the histological subtypes. Distal-like tumors include all morphological distal subtypes and a subset of proximal and hybrid EpS. They express a specific molecular single-cell derived epithelial-to-mesenchymal transition signature, which associates with improved patient survival and includes Desmoglein 2 (DSG2), which we identify as a potential routine immunohistochemical biomarker to improve diagnosis. Distal-like EpS also display increased peri-tumoral CD8+ T cell infiltrates and specific tumor-immune cell interactions. Conversely, proximal-like EpS harbor a higher inter-tumoral molecular heterogeneity with some cases resembling other SMARCB1-deficient tumors by DNA methylation profiling, and increased intra-tumoral pro-tumoral macrophage infiltrates. Our study introduces a novel molecular classification of EpS with prognostic value, associated diagnostic biomarkers and distinct tumor immune microenvironments, which extends beyond traditional clinicopathological classification. This paves the way for precision medicine-based therapeutic strategies for patients with EpS.

Dac EGAC50000000552

Single Cell and Tissue Level Functional Genomics Analysis of Astrocyte-Related Mechanisms in Taupathy

This data is the first part of a larger single cell and tissue level functional genomics analysis of dementias with tau pathology.  Cellular resolution will clarify the role of glial genes and pathways in neurodegenerative disease. This includes understanding the role of microglia and astrocytes in neurodegenerative disorders characterized by Tau protein pathology. To achieve a refined view of microglial neuroinflammatory signaling in tau-associated neurodegeneration, we performed a functional genomic analysis that integrated time-course gene expression data from mouse models expressing human mutant MAPT (the tau gene) with single nuclear sequencing data obtained from patients with frontotemporal dementia with Tau protein pathology (Pick’s disease). This included microglia-specific gene expression data obtained from single nuclear sequencing of postmortem frozen precentral gyrus samples collected from 16 total individuals, including 8 subjects with clinical diagnosis of behavior variant frontotemporal dementia and neuropathological diagnosis of Pick’s disease (Tau protein pathology) and controls (n=8). Our findings present detailed molecular profiles of disease-associated microglial transitions over the course of tau-associated neurodegeneration. Furthermore, we demonstrate overlap between microglia profiles obtained from precentral gyrus of patients with Pick’s disease with those up-regulated during the neurodegenerative stage in mice expressing human MAPT mutations.

Study phs002197

3659 results for "RNA AND sequencing OR transcriptome"

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