14667 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• BPH Tissues for Cell Culture and Analysis - A Patient-Derived Xenograft Model Using Benign Prostatic Tissues

  Our goal was to establish and characterize a patient-derived xenograft model for benign prostatic hyperplasia (BPH) using human benign prostatic tissues. Characterization of the model was done by histology, immunohistochemistry, proteomics, and transcriptome analysis (RNAseq). The RNAseq data will be deposited in dbGaP. Subjects were undergoing prostatectomy for prostate or bladder cancer, with concurrent BPH, and consented to the use of surplus tissue for research studies. The RNAseq studies included 6 patients. Phenotypic data include patient age, sex, prostate size, serum prostate-specific antigen (PSA) level, and international prostate symptom score (IPSS). Sequencing was done on an Illumina NovaSeq 6000, and data were analyzed using Kallisto. Data are submitted as raw sequencing (fastq) files.

  Study phs003692

• DAC for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is a leading cause of death from gynecological malignancies worldwide. No effective screening methods exist resulting in tumor detection at advanced stages where treatment is less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women, mostly post-menopausal, from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we evaluated the detection of ovarian cancer in two clinical settings, detection of ovarian cancers among a healthy population, and classification of adnexal masses as benign or malignant. The combined approach detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach differentiated benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Dac EGAC50000000332

• Transcriptome analysis of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A (H3N2) virus.

  Transcriptome analysis of influenza A (H3N2) human challenge samples. Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Study EGAS50000000679

• AYA glioma NGS

  Gliomas are a major cause of cancer-related death in adolescents and young adults (AYA, ages 15-39 years). Different molecular alterations drive gliomas in children and adults leading to distinct biology and clinical consequences. At the convergence of these age groups - the AYA population – little is known about the implications of pediatric vs adult-type alterations. To address this, we analyzed a population-based cohort of 1456 clinically and molecularly characterized gliomas aged 0-39 years. Potentially targetable pediatric-type alterations were found in 31% of AYA gliomas and conferred superior outcomes compared to adult-type alterations. This submission includes the generated NGS data for children, adolescent, and young adults with gliomas. Data includes targeted panel of glioma genes and low-pass WGS (1x coverage).

  Study EGAS50000000383

• Mapping Genotypes to Chromatin Accessibility Profiles in Single Cells

  In somatic tissue differentiation, chromatin accessibility changes govern priming and precursor commitment towards cellular fates1–3. Therefore, somatic mutations likely alter chromatin accessibility patterns, as they disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wild-type cells. To chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed Genotyping of Targeted loci with single-cell Chromatin Accessibility (GoT-ChA). This high-throughput platform links genotypes to chromatin accessibility at single-cell resolution, across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from myeloproliferative neoplasm (MPN) patients with JAK2V617F-mutated hematopoiesis.

  Study EGAS50000000164

• Single-Cell ATAC and RNA Sequencing of Human Breast Cancer Reveals Salient Cancer-Specific Enhancers

  Matched single-cell chromatin accessibility sequencing (scATAC-seq) and single-cell transcriptomic sequencing (scRNA-seq) were performed for 12 human breast tumor samples, 4 normal human mammary reduction samples, and 4 human breast cancer cell lines (HCC1143, SUM149PT, MCF7, and T47D). Both scATAC-seq and scRNA-seq assays resolved the underlying cellular heterogeneity in chromatin accessibility and transcriptional output for each patient sample. In this work, we quantitatively linked variation in chromatin accessibility to gene expression across malignant and non-malignant cell types from patient samples. We then showed that our findings were recapitulated in the breast cancer cell line samples. These data will serve as an important resource for the single-cell genomics and breast cancer research communities.

  Study phs003253

• DirectHRD Enables Sensitive Scar-Based Classification of Homologous Recombination Deficiency (HRD)

  Homologous recombination deficiency (HRD)-induced genomic scars are an FDA-approved biomarker for identifying cancers likely to respond to PARP inhibitors. However, detecting HRD scars from blood biopsies has been challenging due to the low tumor content in blood samples. To address this limitation, we developed DirectHRD, a genomic scar-based HRD classifier leveraging whole-genome sequencing (WGS) data for non-invasive blood biopsy testing. DirectHRD was applied to 90 cell-free DNA (cfDNA) samples across four cancer types: breast, ovarian, prostate, and pancreatic. The method achieved an AUC of 0.87 and demonstrated the ability to detect HRD at tumor fractions as low as 1%, offering a tenfold increase in sensitivity compared to state-of-the-art methods.

  Study phs003760

• Genome-wide NanoRCS sequencing of cfDNA and ctDNA from liquid biopsies of healthy individuals and cancer patients

  Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant molecules, extremely sensitive sequencing methods are required. We developed a new technique, NanoRCS, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule for genome-wide sequencing, and applied this to plasma of healthy individuals, Esophageal cancer patients and Granulosa cell tumor patients and ascites of Ovarian cancer patients. We also sequenced these samples on Illumina Novaseq, to compare the two techniques.

  Study EGAS50000000154

• 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

• DNA Repair Capacity for Lung Disease Risk Assessment

  A focus of this work was to address the extent to which susceptibility for lung cancer varies by gene-environment-phenotype interactions involving DNA repair capacity and differences in risk from environmental stressors. GWAS from a subset of subjects from the Lovelace Smokers Cohort and New Mexico Lung Cancer cohort were used to derive polygenic risk scores for DNA repair pathways (nucleotide excision, base excision, single strand break, non-homologous, homologous recombination). Logistic regression analysis was used to examine the association between polygenic risk score and lung cancer status. Polygenic risk scores were grouped by quartiles. Only diminished base excision repair was associated with increased risk for lung cancer at the 25-50% quartile and approached significance at the 50-75% quartile.

  Study phs004063