14476 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Integrated Analysis of Multimodal Single-Cell Data

  The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce 'weighted nearest neighbor' analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. All CITE-seq and ECCITE-seq raw matrices are available in GEO database under the accession number GEO: GSE164378.

  Study phs002315

• Pharmacogenomic Interactions in Glioblastoma Cell Line Models

  Glioblastoma (GBM) is a lethal disease without effective treatments. To advance toward effective therapeutic approaches that are biomarker-driven, there is a need for new targeted agents and to develop accurate preclinical models that encompass its cellular and molecular diversity. Historical cell line models poorly represent molecular diversity of GBMs, so we developed a living tissue bank encompassing 103 patient-derived GBM cell lines (PDGCLs) as a platform for preclinical pharmacogenomic investigation at scale. Thirty-four PDGCLs were submitted to a comprehensive molecular characterization of copy number alterations and mutations using whole exome sequencing (WES) and gene expression (microarrays), and tested against a panel of 390 small molecules at sixteen different duplicated concentrations. After integrating and systematically correlating molecular alterations with drug sensitivities, we yielded 8,083,140 pharmacogenomic interactions, and discovered novel drug and biomarker combinations which help to prioritize highly effective novel candidate treatments in GBM. Our findings demonstrate the utility of deep characterization of large numbers of models from a single disease to detect complex predictors of compound sensitivity, and indicate novel therapeutic approaches for a large fraction of patients with GBM.

  Study phs001793

• Methotrexate Clearance GWAS in Acute Lymphoblastic Leukemia (ALL) Patients

  We estimated the plasma clearance of methotrexate from 1279 acute lymphoblastic leukemia (ALL) patients treated on the Children Oncology Group 9904 and 9905 trials (http://clinicaltrials.gov/show/NCT00005585 and http://clinicaltrials.gov/show/NCT00005596). Patients received either a 24-hour infusion of a 1 g/m2 dose or 4-hour infusion of a 2 g/m2 dose). Methotrexate clearance was lower in older children (p=7 x 10-7), females (p=2.7 x 10-4), and patients who received a delayed intensification phase (p=0.0022). In a genome-wide analysis, methotrexate clearance was associated with polymorphisms in the SLCO1B1 gene (p=2.1 x 10-11), which encodes for an organic anion transporter. This replicates findings using different schedules of high-dose methotrexate in ALL patients treated on St. Jude protocols. A combined meta-analysis yields a p-value of 5.7 x 10-19 for the association of methotrexate clearance with SLCO1B1 SNP rs4149056 (Trevino et al, PMID 19901119 and Ramsey et al, PMID 23233662). This data set includes the dependent variable of methotrexate clearance and all of the SNP data available from arrays.

  Study phs000637

• Functional Enhancer Elements Drive Subclass-Selective Expression From Mouse to Human Neocortex

  A complete epigenomic map of human brain cell types will be necessary to fully understand their genetic regulation, and to create the next generation of non-species-restricted genetic tools for their functional characterization. Here we performed both bulk and single-nucleus ATAC-seq studies of fresh human neocortical samples excised during neurosurgery, in order to discover the functional genomic elements that discriminate cell types. This dataset contains 78 bulk layer-dissected ATAC-seq samples, and 3660 single-nucleus ATAC-seq samples from fresh acutely isolated human neurosurgical samples. Furthermore, from these data we identified and validated several enhancers for use in AAV context. We also provide validation single cell RNA-seq for 456 human acutely labeled neurosurgical neurons labeled by 3 unique enhancer-AAV vectors, and single cell RNA-seq for 1483 mouse neurons labeled in vivo by 11 unique enhancer-AAV vectors. Together these datasets provide high-resolution maps of single human neocortical cell types, as well as proof of the functional utility of the genomic elements discovered. As a whole these data will be important to furnish the next generation of cell type-specific functional tools and therapies in neuroscience.  

  Study phs002292

• Resistance Development in Basal Cell Nevus Syndrome through the Basal to Squamous Transition

  While basal cell carcinomas (BCCs) arise from ectopic hedgehog pathway activation and can be treated with pathway inhibitors, sporadic BCCs display high resistance rates, while tumors arising in Gorlin syndrome patients with germline Patched (PTCH1) mutations are uniformly suppressed by inhibitor therapy. In rare cases, Gorlin syndrome patients on long-term inhibitor therapy will develop individual resistant tumor clones that rapidly progress, but the basis of this resistance remains unstudied. Here we report a case of a Smoothened inhibitor (SMOi)-resistant tumor arising in a Gorlin patient on suppressive SMOi for nearly a decade. Using a combination of multi-omics and spatial transcriptomics, we define the tumor populations at the cellular and tissue level to conclude that Gorlin tumors can develop resistance to SMOi through the previously described basal to squamous cell carcinoma transition (BST). Intriguingly, through spatial whole exome genomic analysis, we nominate PCYT2, ETNK1, and the phosphatidylethanolamine biosynthetic pathway as novel genetic suppressors of BST resistance. These observations provide a general framework for studying tumor evolution and provide important clinical insight into mechanisms of resistance to SMOi for not only Gorlin syndrome but sporadic BCCs as well.

  Study phs003415

• Molecular Determinants of Esophageal Cancer in Tanzania

  We describe the genomic profiles of 61 esophageal squamous cell carcinoma (ESCC) cases from Tanzania and compare them to profiles from an existing cohort of ESCC cases from Malawi. We also provide a comparison to ESCC tumors in The Cancer Genome Atlas Program (TCGA). Despite a high burden of ESCC in Eastern Africa, investigations into the genomics in this region are nascent. This represents the largest comprehensive genomic analysis of ESCC from sub-Saharan Africa to date. We observed substantial transcriptional overlap with other squamous histologies via comparison with TCGA PanCan dataset. DNA analysis revealed known mutational patterns, both genome-wide as well as in genes known to be commonly mutated in ESCC. TP53 mutations were the most common somatic mutation in tumors from both Tanzania and Malawi but were detected at lower frequencies than previously reported in ESCC cases from other settings. In a combined analysis, two unique transcriptional clusters were identified: a proliferative/epithelial cluster and an invasive/migrative/mesenchymal cluster. Mutational signature analysis of the Tanzanian cohort revealed common signatures associated with aging and cytidine deaminase activity and an absence of signature 29, which was previously reported in the Malawi cohort.

  Study phs003217

• Single Duplex DNA Sequencing with CODEC Detects Mutations with High Sensitivity

  Detecting mutations from single DNA molecules is crucial in many fields but challenging. Next generation sequencing (NGS) affords tremendous throughput but cannot directly sequence double-stranded DNA molecules (single duplexes) to discern the true mutations on both strands. Here, we present Concatenating Original Duplex for Error Correction (CODEC) which confers single duplex resolution to NGS. CODEC affords 1,000-fold higher accuracy than NGS, using up to 100-fold fewer reads than Duplex Sequencing. CODEC revealed mutation frequencies of 2.72 x 10-8 in sperm of a 39-year-old individual, and somatic mutations acquired with age in blood cells. CODEC detected genome-wide clonal hematopoiesis mutations from single DNA molecules, single mutated duplexes from tumor genomes and liquid biopsies, microsatellite instability (MSI) with 10-fold greater sensitivity, and mutational signatures and specific tumor mutations with up to 100-fold fewer reads. CODEC enables more precise genetic testing and reveals biologically significant mutations which are commonly obscured by NGS errors. We applied CODEC to clinical colon and breast neoplasm samples and uncovered expected mutational signatures including homologous recombination deficiency (HRD) and MSI.

  Study phs003255

• A Microwell Platform for High-Throughput Longitudinal Phenotyping and Selective Retrieval of Organoids

  In traditional bulk culture, organoids tend to overlap, hindering the analysis of individual organoid characteristics in a high-throughput manner. Additionally, variations in the local spatial properties of the bulk matrix make it challenging to distinguish whether phenotypic differences between organoids stem from inherent cellular disparities or disparities in the microenvironment. To address these challenges, we have developed a microwell-based technique that facilitates the quantification of image-based parameters for organoids grown from single cells. Furthermore, these organoids can be easily retrieved from their respective microwells for molecular profiling. By employing a deep-learning image processing pipeline, we conducted a comprehensive assessment of various phenotypic traits in two CRISPR-engineered human gastric organoid models. This analysis encompassed growth rates, cellular movement, and apical-basal polarity. Through our investigation, we successfully identified genomic alterations associated with increased growth rate, as well as changes in accessibility and expression patterns correlated with apical-basal polarity. This novel methodology offers a valuable tool for studying organoid behavior at a single-cell level, enabling researchers to gain deeper insights into organoid biology and associated genetic modifications.

  Study phs003315

• Detecting and Subtyping Lung Cancer Through Analysis of Circulating Tumor DNA

  Small cell lung cancer (SCLC) is among the most aggressive tumors with poor clinical outcomes. Tumors are rarely resected, which is a major barrier to molecular profiling of tumor tissue; therefore, non-invasive approaches using circulating tumor DNA (ctDNA) from liquid biopsies are needed to help advance research and clinical care for patients with SCLC. We developed a targeted capture panel that profiles SCLC genes and transcriptional regulation sites, including transcription start sites (TSS) and transcription factor binding sites (TFBS). This is a single assay that detects genomic mutations and transcriptional regulation activity based on ctDNA fragment patterns reflecting epigenetic nucleosomal positions. We applied this assay to sequence patient-derived xenograft (PDX) and patient plasma samples. We also performed whole genome sequencing (WGS) for a subset of the PDX plasma samples to validate the capture data. We developed new algorithms to quantify activity of key SCLC marker genes of ASCL1, NEUROD1, POU2F3, and ATOH1 and to classify SCLC subtypes based on activity of these markers. Furthermore, we developed a model to classify SCLC from non-small cell lung cancer (NSCLC), which has potential important applications for monitoring transdifferentiation and tumor plasticity.

  Study phs003570

• Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution

  Ischemia reperfusion is an unavoidable step of organ transplantation. Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from six human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single cell RNA sequencing. Donor and recipient origin of cells from the reperfusion timepoint were deconvolved. Gene expression profiles were (1) compared between each donor cell type between timepoints and (2) compared between donor and recipient cells. Inflammatory responses from donor lung macrophages were found after reperfusion with upregulation of multiple cytokines and chemokines, especially IL-1 and IL-1. Significant inflammatory responses were found in alveolar epithelial cells (featured by CXCL8) and lung endothelial cells (featured by IL-6 upregulation). Different inflammatory responses were noted between donor and recipient monocytes and CD8+ T cells. The inflammatory signals and differences between donor and recipient cells observed provide insight into the cellular and molecular mechanisms of ischemia reperfusion induced lung injury. Further investigations may lead to the development of novel targeted therapeutics.

  Study EGAS50000000490