22940 results for "ega"

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• Unifying recovery dynamics in heterogeneous diseases exemplified by COVID-19

  Studying the recovery dynamics in different diseases poses many difficulties, as patients often display high heterogeneity in their recovery courses. Moreover, most attempts to study disease dynamics focus on disease progression rather than disease recovery mechanisms. To model recovery dynamics, using severe COVID-19 as the example, we align heterogeneous recovery trajectories via a novel computational scheme applied to longitudinally sampled blood transcriptomes. We thus generate pseudotime trajectories, which we then link to cellular and molecular mechanisms based on cell deconvolution analysis and molecular pathway prediction, thus presenting a unique framework for studying recovery processes over time. Specifically, mature neutrophils displayed a gradual decrease during recovery, allowing superior useability for outcome prediction compared to currently used clinical markers. Further, we discovered a recovery-related regulatory change in gene programs resulting in immune rebalancing between interferon and NFkB activity and the restoration of cell homeostasis. We thus propose regulatory mechanisms governing COVID-19 recovery and suggest mature neutrophils and additional gene markers, as novel clinical biomarkers for disease outcome. Overall, we present a novel clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

  Study EGAS00001005735

• Pancreatic tropism of metastatic renal cell carcinoma

  Renal cell carcinoma (RCC) is characterized by a particularly broad metastatic swath, and enigmatically, when the pancreas is a destination, the disease is associated with improved survival. Intrigued by this observation, we sought to characterize the clinical behavior, therapeutic implications, and underlying biology. While pancreatic metastases (PM) are infrequent, we identified 31 patients across two institutional cohorts and show that improved survival is independent of established prognostic variables, that these tumors are exquisitely sensitive to anti-angiogenic agents and resistant to immune checkpoint inhibitors (ICI), and that they are characterized by a distinctive biology. Primary tumors of patients with PM exhibited frequent PBRM1 mutations, 3p loss, and 5q amplification, along with a lower frequency of aggressive features such as BAP1 mutations and loss of 9p, 14q, and 4q. Gene expression analyses revealed constrained evolution with remarkable uniformity, reduced T-effector gene signatures and increased angiogenesis. Similar findings were observed histopathologically. Thus, RCC metastatic to the pancreas is characterized by indolent biology, heightened angiogenesis, and an uninflamed stroma, likely underlying its good prognosis, sensitivity to anti-angiogenic therapies, and refractoriness to ICI. These data suggest that metastatic organotropism may be an indicator of a particular biology with prognostic and treatment implications for patients.

  Study EGAS00001004208

• CancerLocator: Non-Invasive Cancer Diagnosis and Tissue-of-Origin Prediction Using Methylation Profiles of Cell-Free DNA

  Background: The detection and characterization of cell-free DNA in plasma is one of the most promising new areas in cancer diagnosis. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose a variety of different malignancies. Results: Here we propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. We comprehensively evaluate CancerLocator with simulations and real data, and compare its performance with that of two established multi-class classification methods. We show that the predicted tumor burdens are highly consistent with the true values. In addition, when the proportion of tumor-derived DNAs in the cell-free DNAs is low, the two popular machine learning methods completely fail for cancer diagnosis, while CancerLocator successfully overcomes the challenge. CancerLocator also achieves promising results on patient plasma samples, despite the fact that the DNA methylation data from these samples has very low sequencing coverage. Conclusions: CfDNA methylation may be developed as an important approach for non-invasive early cancer diagnosis.

  Study EGAS00001002211

• Host pathogen interaction long read transcriptome

  Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular in transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are predicted to be benign using the reference transcript annotation. In further support of SUsPECT’s utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

  Study EGAS00001006779

• Direct Detection of Early-stage Cancers Using Circulating Tumor DNA

  Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-related genes encompassing 81 kb. Analysis of plasma from 44 healthy individuals identified genomic changes related to clonal hematopoiesis in 16% of asymptomatic individuals but no alterations in driver genes related to solid cancers. Evaluation of 200 patients with colorectal, breast, lung, or ovarian cancer detected somatic mutations in the plasma of 71, 59, 59, and 68%, respectively, of patients with stage I or II disease. Analyses of mutations in the circulation revealed high concordance with alterations in the tumors of these patients. In patients with resectable colorectal cancers, higher amounts of preoperative circulating tumor DNA were associated with disease recurrence and decreased overall survival. These analyses provide a broadly applicable approach for noninvasive detection of early-stage tumors that may be useful for screening and management of patients with cancer.

  Study EGAS00001002577

• 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

• Long-term organoid culture of a small intestinal neuroendocrine tumor

  Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare and highly heterogeneous neoplasms whose incidence has markedly increased over the last decades. A grading system based on the tumor cells' proliferation index predicts high-risk for G3 NETs. However, low-to-intermediate grade (G1/G2) NETs have an unpredictable clinical course that varies from indolent to highly malignant. Cultures of human cancer cells enable to perform functional perturbation analyses that are instrumental to enhance our understanding of cancer biology. To date, no tractable and reliable long-term culture of G1/G2 NET has been reported to permit disease modeling and pharmacological screens. Here, we report of the first long-term culture of a G2 metastatic small intestinal NET that preserves the main genetic drivers of the tumor and retains expression patterns of the endocrine cell lineage. Replicating the tissue, this long-term culture showed a low proliferation index, and yet it could be propagated continuously without dramatic changes in the karyotype. The model was readily available for pharmacological screens using targeted agents and as expected, showed low tumorigenic capacity in vivo. Overall, this is the first long-term culture of NETs to faithfully recapitulate many aspects of the original neuroendocrine tumor.

  Study EGAS00001007093

• High Grade Serous Ovarian Carcinomas Originate in the Fallopian Tube

  High-grade serous ovarian carcinoma (HGSOC) is the most frequent type of ovarian cancer and has a poor outcome. It has been proposed that fallopian tube cancers may be precursors of HGSOC but evolutionary evidence for this hypothesis has been limited. To provide insights into the origins of HGSOC, we We performed whole-exome sequence and copy number analyses of laser-capture microdissected fallopian tube lesions (p53 signatures, serous tubal intraepithelial carcinomas (STICs), and fallopian tube carcinomas), ovarian cancers, and metastases from nine patients with HGSOC. The majority of tumor-specific sequence and structural alterations in ovarian cancers were present in STICs, including those affecting TP53, BRCA1, BRCA2 or PTEN genes. An eEvolutionary analyseis revealed that p53 signatures and STICs were are the precursors of ovarian carcinoma which in turn gave rise to metastatic lesionsand identify a. In one patient we identified a second STIC as a metastasis in the fallopian tube opposite from the affected ovary. These analyses revealed a window of seven years between the development of a STIC and the initiation of ovarian carcinomas, with development of metastases following rapidly thereafter. Our results provide insights into the etiology of ovarian cancer and have implications for the prevention, early detection and therapeutic intervention of this disease.

  Study EGAS00001002589

• Mapping_gene_environment_interactions_in_macrophages

  Immune cells sense and respond to external stimuli such as pathogens and initiate an inflammatory response. Genetic variants altering the behaviour and responses of immune cells may inform the results of disease association studies and provide an insight into the regulation of immune response. Studies mapping quantitative trait loci (QTL) are usually performed in quiescent or naïve cells and therefore any variants with a condition-specific manner (e.g. those with an effect only detectable in a specific time-point after cell stimulation) are likely to remain undiscovered. So far, only a handful of studies have attempted to study QTL in multiple states and even on those studies the number of states has remained relatively low (<5). Only very recently Horst and colleagues published the largest study to date investigating the effect of host variable (e.g. age, sex, contraceptive use etc.) on protein levels in macrophages stimulated with 19 different conditions (Horst et al, 2016). This project aims to develop a high-throughput experimental platform to detect QTL in a large number of states using iPSC derived macrophages. 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 EGAS00001002268

• Single cell transcriptomic landscape of pediatric B-cell acute lymphoblastic leukemia: dissection of transcriptional heterogeneity and B-cell developmental state

  Introduction: Genomic analyses of bulk ALL samples have improved our understanding of the genetic basis and risk stratification of B-ALL, but do not directly examine intratumor heterogeneity or enable inference of leukemia developmental state and cell of origin. Methods: We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) (10X Genomics 5’v2) and compared them to a scRNA-seq reference map of normal human B-cell development. Results: Analysis of heterogeneity of inferred DNA copy number alterations at single cell level showed that aneuploid ALL with near haploidy and hyperdiploid harbor chromosomal losses or gains in all blasts, consistent with early, synchronous origin rather than sequential accumulation. Intra-sample heterogeneity was driven by five gene expression signatures: cell cycle, metabolism, differentiation, inflammation, refining leukemic subtyping. An atlas of B cell development was established to map B-ALL samples to specific developmental states. Hyperdiploid samples resembled pro-B cells, while MEF2D-r and TCF3::PBX1 showed high pre-B abundance. Patients with high early lymphoid abundance had poorer outcomes. Conclusions: Understanding variation in transcriptional programs and developmental states of B-ALL blasts by sc transcriptome refines existing clinical and genomic classifications and provides novel prognostic markers.

  Study EGAS00001007512