14508 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Genomic Profiling of Pediatric Tumors by Cell Free DNA Sequencing

  BACKGROUND Analysis of cell-free DNA (cfDNA) from peripheral blood has been studied extensively for detection and monitoring therapy response in adult cancers, but utility in pediatric tumors is unclear. METHODS We studied 233 children with hematologic, solid and brain tumors. cfDNA was extracted from 1 mL of plasma collected at diagnosis. Circulating tumor DNA (ctDNA) in cfDNA was quantified and diverse classes of somatic genomic variants were detected using PeCan-Seq. PeCan-Seq findings were compared with matched tumor whole-genome and whole-exome sequencing data. Minimal residual disease (MRD) status was evaluated by cfDNA PeCan-Seq in 14 patients with B-cell acute lymphoblastic leukemia. RESULTS Plasma cfDNA yields at diagnosis were higher for hematologic malignancies than for solid and brain tumors. Patients with hematologic malignancy were 100% ctDNA-positive, the median ctDNA fraction in cfDNA was 0.77. We detected 97% variants that were present in tumors and covered by the capture panel, and 50 subclonal variants that were present in cfDNA only. Our approach enabled detection of sequence and structural variants in B-ALL ctDNA at varying levels of MRD. Nineteen of 38 patients with solid tumors were ctDNA-positive, with high prevalence in Ewing Sarcoma, liver tumors and osteosarcoma. One of 19 brain tumor patients was ct-DNA positive, indicating lack of utility for plasma-derived cfDNA in this disease. Notably, cfDNA analysis of a single plasma sample identified genomic features in ctDNA derived from B-ALL, concurrent primary neuroblastoma, and a later neuroblastoma relapse, indicating that genomic variations from multiple tumors could be detected simultaneously. CONCLUSIONS Pediatric patients with hematologic malignancy had an abundance of plasma ctDNA at diagnosis. Plasma ctDNA levels varied between different solid tumor types, more studies are needed to determine utility. Panel-based cfDNA sequencing could serve as a non-invasive approach for pediatric cancer diagnosis and disease monitoring.

  Study EGAS50000000072

• Gene expression signatures associated with chronic endometritis revealed by RNA sequencing

  Chronic endometritis (CE) is a persistent inflammatory condition of the endometrium characterized by the infiltration of plasma cells. CD138 immunohistochemistry is considered to improve the CE diagnosis rate. Using the number of CD138-positive cells equal or greater than five as a diagnostic criterion for CE, we identified 24 CE and 33 non-CE cases among women with infertility. We conducted RNA-sequencing analysis for these 57 cases in total as an attempt to elucidate the molecular pathogenesis of CE and to search for new biomarkers for CE. By comparing CE and non-CE groups, we identified 20 genes upregulated in the endometria of CE patients, including 12 immunoglobulin-related genes and eight non-immunoglobulin genes as differentially expressed genes. The eight genes were MUC5AC, LTF, CAPN9, MESP1, ACSM1, TVP23A, ALOX15, and MZB1. By analyzing samples in the proliferative and secretory phases of the menstrual cycle separately, we also identified four additional non-immunoglobulin genes upregulated in CE endometria: CCDC13 by comparing the samples in the proliferative phase, and OVGP1, MTUS2, and CLIC6 by comparing the samples in the secretory phase. Although the genes upregulated in CE may serve as novel diagnostic markers of CE, many of them were upregulated only in a limited number of CE cases showing an extremely high number of CD138-positive cells near or over one hundred. Exceptionally, TVP23A was upregulated in the majority of CE cases regardless of the number of CD138-positive cells. The upregulation of TVP23A in the endometria of CE cases may reflect the pathophysiology of a cell-type or cell-types intrinsic to the endometrium rather than the accumulation of plasma cells. Our data, consisting of clinical and transcriptomic information for CE and non-CE cases, helped us identify gene expression signatures associated with CE.

  Study JGAS000621

• Population Structure and Genetic Diversity in Argentinean populations

  Argentina was one of the last places peopled when humans entered the Americas. Its earliest archeological sites are dated from 13,000 years BP, and throughout its history the region has exhibited broad cultural diversity, involving both hunter-gatherer and agro-pastoral societies, different linguistic families, the Southern expansion of the Inca Empire, the arrival of the Spanish conquistadors and slave trade from Africa. More recently, Argentina has had the highest proportion of influx of transoceanic migration between 1850 and 1940 of any Latin American country. Furthermore, the geographical distribution of immigrants was oriented towards the Pampa region of central-eastern Argentina and the Northeast, so different patterns of mixed ancestry throughout the country are expected. In this present work we aim to describe the history and structure of the Argentinean population. Thus far, we have collected DNA samples from 2904 participants from 15 dispersed regions in Argentina, from the Andean populations in the Northwest to the river lands of the Northeast. Our preliminary data includes genome-scale Illumina Exome Array 250K genotypes, plus next-generation sequencing data from uniformly spaced genomic regions targeted with a genotype-by- sequencing strategy (which covers 1.5% of the genome), for 375 participants from 9 of the 15 populations. We will identify proportions and patterns of European, African and Indigenous American ancestry in the Argentinean cohort via local ancestry inference. The first series of analyses will focus on genomic tracts of Indigenous American ancestry for fine-scale examination of sub-continental structure by comparing to a panel of 493 samples from 52 Indigenous American populations from throughout the Americas. Furthermore, this work will serve as a test of different low-cost strategies (exome genotype array vs. genotype-by-sequencing) for accurate inference of population structure in extant populations.

  Study EGAS00001001663

• Intra-tumor heterogeneity of localized lung adenocarcinomas defined by multi-region sequencing

  Background: Intra-tumor heterogeneity (ITH) may have profound impacts on biopsy strategy, characterization of actionable targets, treatment planning, and drug resistance. ITH of lung cancers has not been well studied. Methods: We performed multi-region whole exome sequencing (average sequencing depth 277x) on 48 tumor regions from 11 resected lung adenocarcinomas (8 stage I, 2 stage II and one stage III tumors) followed by deep sequencing validation (average sequencing depth 863x). Results: All tumors showed clear evidence of spatial ITH. On average, 76% of all mutations and 20/21 known cancer gene mutations were present in all regions of individual tumors (trunk mutations). Copy number analysis did not show substantial difference in large-scale chromosome aberrations. A canonical KRAS p.G12C mutation was detected in only 1 of 4 tumor regions (branch mutations) at exome depth but detected in all four tumor regions (trunk mutations) at increased sequencing depth. In addition, many heterogeneous branch mutations defined by exome sequencing were detectable in all regions of individual tumors with increasing sequencing depth. Significant differences in mutational spectrum were observed in 6 tumors indicating that specific mutational processes were likely operative at different times during development of these tumors. With a median follow up of 21 months post surgery, 3 patients have relapsed and all 3 patients presented with significantly larger fractions of subclonal mutations in their primary tumors. Conclusions: Although multi-region sampling is still required to fully assess ITH complexity, single biopsy analysis at appropriate depth might be sufficient to identify the majority of known cancer gene mutations in localized lung adenocarcinomas. Larger subclonal mutation fractions may be associated with increased likelihood of postsurgical relapse in patients with localized lung adenocarcinomas. Studies on larger cohort, ideally with comprehensive clinical annotation and repeat biopsy at relapse are needed to fully understand the clinical impact of ITH.

  Study EGAS00001000930

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• Reduced Representation Bisulfite Sequencing (RRBS) in various tissues to discover DNA methylation markers for the diagnosis of breast and ovarian cancer.

  Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. In addition, monitoring treatment and early detection of fatal breast cancer (BC) remains a major unmet need. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.In order to discover the most relevant CpG regions, we used RRBS and analysed several tissue samples: 11 prospectively collected invasive epithelial ovarian cancer samples (high grade serous n=8, low grade serous n=1, endometrioid n=1, mucinous n=1, mean age = 54.7 years), 8 prospectively collected invasive ductal breast cancer samples (2/8 triple negative; mean age = 56.6 years), one benign tumor (papillary serous cystadenoma, age = 86 years), 18 non-neoplastic tissue samples (breast n=7 and adnexal n=11, mean age = 60.2 years), two non-neoplastic endometrial tissues (mean age = 68 years) and twenty three white blood cell samples (mean age = 57.8 years) were assessed by RRBS. Genome wide methylation analysis was performed by Reduced Representation Bisulfite Sequencing (RRBS) at GATC Biotech. DNA was digested with MspI followed by size selection of the library, providing enhanced coverage for the CpG-rich regions. The digested DNA was adapter ligated, bisulfite modified and PCR amplified. The libraries were sequenced on Illumina’s HiSeq 2500. Analysis of the first samples sequenced with 100bp paired-end mode showed that the library insert size was small. Therefore, the remaining samples were sequenced with 50 bp paired-end mode. Using Genedata Expressionist® for Genomic Profiling v9.1, we established a bioinformatics pipeline for the detection of cancer specific differentially methylated regions (DMRs). The most promising DMRs were taken forward for the development and validation of serum based clinical assays.

  Study EGAS00001002609

• INCLUDE: The Epidemiology of Transient Leukemia in Newborns with Down Syndrome

  The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality-of-life for people with Down syndrome. The INCLUDE Project Data Coordinating Center and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions.Down syndrome (DS) is associated with a remarkably high risk of childhood acute myeloid leukemia (AML), with an approximately 500-fold increased risk of the rare subtype acute megakaryoblastic leukemia. Though largely treatable, a proportion of myeloid leukemia in DS (ML-DS) patients relapse with dismal survival. ML-DS is preceded by a preleukemia, transient abnormal myelopoiesis (TAM), which presents clinically at birth and is driven by somatic truncating mutations in the erythro-megakaryocytic transcription factor gene GATA1. Up to 15% of DS newborns have TAM, and this can be fatal in up to 20% of cases. A further 10-15% of newborns with DS harbor subclonal GATA1 mutations with clinically silent disease (i.e., Silent TAM). Of the DS newborns with either TAM or Silent TAM (i.e., transient leukemia), up to 15% will acquire additional somatic mutations and progress to ML-DS. We predict that germline variation modifies the risk of developing somatic truncating GATA1 mutations, the first step towards ML-DS, however this has yet to be examined. To address this, the main aim of this X01 study is to perform the first genetic association study of GATA1 mutations in DS, through whole-genome sequencing (WGS) of 470 DS newborns in the Oxford Down Syndrome Cohort Study (ODSCS). Targeted sequencing of GATA1 has already been performed in the 470 DS newborns in the ODSCS, with 130 (28%) confirmed to harbor a somatic truncating GATA1 mutation. We will perform a genome-wide association study (GWAS) of GATA1 mutations to assess genetic variation genome-wide, in particular focusing on variants in candidate genes on the trisomic chromosome 21, RUNX1, ERG, ETS2, and DYRK1A, which have previously been associated with upregulation of GATA1. We will also carry out a chromosome X-wide association study (XWAS) to investigate genetic variation at the GATA1 gene, which resides on chromosome X. WGS data will also enable us to assess the potential role of copy number variation in the risk of transient leukemia in DS. Discovering genetic risk factors for GATA1 mutations in DS may reveal targets for new targeted therapies for TAM, and also inform the etiology of ML-DS as well as AML in the non-DS population. Finally, the ODSCS includes rich phenotypic data for the 470 DS newborns, including clinical diagnosis of TAM and other hematologic complications, complete blood counts, maternal pregnancy complications, and information on congenital heart disease and other birth defects. Thus, whole genome sequencing data in DS newborns from the ODSCS will provide a rich resource for the DS research community.

  Study phs002982

• The Human Virome in Children and its Relationship to Febrile Illness

  Definition of the human microbiome is an important scientific priority. This study will expand the scope of the investigation to include viruses, which account for a substantial proportion of infectious disease morbidity and mortality, especially in children. The long-term goal of this project is to describe the human virome in children and to investigate its relevance to febrile illnesses in children. The project will also seek to understand the relationship of the immune system to the composition of the virome. Thus, the project's specific aims are 1) To elucidate the spectrum of viruses that can be detected using non-biased, high throughput sequencing on samples of blood, respiratory, and gastrointestinal secretions from healthy children and to use this information as a basis for understanding the role of viruses in acute febrile illnesses without an obvious source, and 2) to investigate the effect of various forms of immunosuppression on the spectrum of viruses detected in children, and to use this information as a basis for understanding the role of viruses in acute febrile illnesses occurring in these children. Our preliminary studies show that diverse viruses can be detected in children having undiagnosed fever. To carry out the specific aims, well children will be enrolled prior to having elective surgery, and febrile otherwise well children will be enrolled from the Emergency Department at St. Louis Children's Hospital. Immunocompromised children will be recruited from hematopoietic stem cell and solid organ transplant clinics, the HIV/AIDS clinic, and the rheumatology/immunology clinic from the same hospital. Children with fever will have samples obtained at the time of the febrile illness and at 1 and 6-month follow-up visits. Selected samples from each study group will be analyzed at the Genome Center at Washington University (GCWU) using next generation 454 high throughput sequencing to detect and sequence all viral sequences present. We anticipate detecting and sequencing a broad range of viruses, including previously unrecognized agents. A variety of techniques will be used to investigate the significance of viruses detected. Virus-specific PCR assays will be used to determine the frequency and extent of viruses detected by sequencing, using the full range of samples collected. Host response to the detected viruses will be investigated using serologic analysis, cytokine profiling, and microarrays to characterize host gene expression. These studies will take advantage of follow-up samples to compare the acute response with the response in the convalescent period. This study will draw upon the expertise and technological assets of one of the world's most powerful sequencing centers to provide the research community with a comprehensive sequence data base of the viruses that are present in children, which can be used to improve our understanding of the causes of febrile illnesses in young children, many of which are currently undiagnosed.

  Study phs000264

• Thymic epithelial transplantation for complete DiGeorge syndrome: RNA (2025-07-22)

  Single cell transcriptomics study of thymic transplant biopsies Allogeneic thymus transplantation is the only curative therapy for complete DiGeorge Syndrome (cDGS), a rare severe primary immunodeficiency characterised by athymia. GOSH is one of only two centres worldwide to offer this treatment. Despite a lack of major histocompatibility complex (MHC)-matching between donor and host, transplanted thymus becomes repopulated by recipient bone marrow derived precursor cells and supports development of functional T-cells. The mechanisms underlying thymopoiesis in this context are poorly understood, but over time we observe reconstitution of T-cell immunity, with the ability to produce host naïve T-cells showing a broad T-cell receptor (TCR) repertoire and to generate MHC-restricted T-cell proliferative responses. Although lifesaving, the achieved immunological reconstitution is typically not complete with circulating T-cell numbers usually remaining below the age related normal ranges. Additionally, we observe persistence of donor-derived T-cells of unknown clinical significance. To gain more insight into the mechanisms by which MHC-mismatched transplanted thymus supports T-cell development with self-tolerance, as well as into the basis of suboptimal T-cell immunity, we now aim to investigate immune reconstitution after thymus transplantation in further detail by using single-cell transcriptomics, applied to thymic transplant biopsies and peripheral blood samples collected during standard post-transplant patient care. By identifying which lineages of host- derived cells repopulate the thymic tissue after transplantation, we will be able to address the role of MHC in positive and negative T-cell selection during T-cell differentiation. We will also be able to clarify the exact ontogeny of the persistent donor T-cells, as well as their possible role. Understanding the mechanisms of action of HLA-mismatched transplanted thymus will contribute to treatment optimisation. Additionally, our research provides a unique opportunity to further investigate key immunological concepts, such as tolerance and autoimmunity, challenging existing paradigms in thymus immunology. 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/ . This dataset contains all the data available for this study on 2025-07-22.

  Dataset EGAD00001015648

• Kids First: Genomic Studies of Orofacial Cleft Birth Defects

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. The Kids First study of nonsyndromic orofacial cleft birth defects (OFCs) is a whole genome sequencing study of 415 White parent-case trios drawn from ongoing collaborations led by Dr. Mary L. Marazita of the University of Pittsburgh Center for Craniofacial and Dental Genetics, including collaborations with Dr. George Wehby of the University of Iowa, Dr. Jacqueline Hecht of the University of Texas, and Dr. Terri Beaty of Johns Hopkins University. Sequencing was done by the Washington University McDonell Genome Institute. The case in each of the Kids First trios has cleft lip (CL, Figure A), cleft palate (CP, Figure B), or both (CL+CP, Figure C): OFCs are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans, affecting approximately 1 in 700 newborns, and are one of the most common structural birth defects worldwide. On average a child with an OFC initially faces feeding difficulties, undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Further, individuals born with an OFC have higher infant mortality, higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genome-wide linkage and association studies have now identified at least 18 genomic regions likely to contribute to the risk for nonsyndromic OFCs. Despite this substantial progress, the functional/pathogenic variants at OFC-associated regions are mostly still unknown. Because previous OFC genomic studies (genome-wide linkage, genome-wide association studies (GWAS), and targeted sequencing) are based on relatively sparse genotyping data, they cannot distinguish between causal variants and variants in linkage disequilibrium with unobserved causal variants. Moreover, it is unknown whether the association or linkage signals are due to single common variants, haplotypes of multiple common variants, clusters of multiple rare variants, or some combination. Finally, we cannot yet attribute specific genetic risk to individual cases and case families. Therefore, the goal of the current study is to identify specific OFC risk variants in Whites by performing whole genome sequencing of parent-case trios.

  Study phs001168