A5069189563- Systemic Sclerosis and Related Diseases
- Connective Tissue Growth Factor Research
- Gene expression and cancer classification
- Glioma Diagnosis and Treatment
- Molecular Biology Techniques and Applications
- Bioinformatics and Genomic Networks
- Cancer Genomics and Diagnostics
- RNA modifications and cancer
- Cancer-related molecular mechanisms research
- Inflammatory Myopathies and Dermatomyositis
- Biomedical Text Mining and Ontologies
- Systemic Lupus Erythematosus Research
- Neural Networks and Applications
- Cancer Immunotherapy and Biomarkers
- Medical Imaging Techniques and Applications
- Single-cell and spatial transcriptomics
- Machine Learning in Healthcare
- Scientific Computing and Data Management
- Sarcoma Diagnosis and Treatment
- Kruppel-like factors research
- Immune cells in cancer
- Neuroblastoma Research and Treatments
- Epigenetics and DNA Methylation
- Genetics, Bioinformatics, and Biomedical Research
- Renal Diseases and Glomerulopathies
Alex's Lemonade Stand Foundation
2018-2025
National Institutes of Health
2022
Translational Therapeutics (United States)
2016-2019
University of Pennsylvania
2016-2019
Dartmouth College
2015-2018
California University of Pennsylvania
2018
Clinical Research Consortium
2018
Lehigh University
2013
<h3>Objectives</h3> To characterise renal tissue metabolic pathway gene expression in different forms of glomerulonephritis. <h3>Methods</h3> Patients with nephrotic syndrome (NS), antineutrophil cytoplasmic antibody-associated vasculitis (AAV), systemic lupus erythematosus (SLE) and healthy living donors (LD) were studied. Clinically indicated biopsies obtained at time diagnosis microdissected into glomerular tubulointerstitial compartments. Microarray-derived differential 88 genes...
Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc its progression are poorly understood. intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, limited) observed in multiple clinical cohorts patients with SSc. Analysis longitudinal biopsies suggests that patient's subset assignment stable over 6–12 months. Genetically, multi-factorial many genetic risk loci for generally specific...
Systemic sclerosis (SSc) is a multi-organ autoimmune disease characterized by skin fibrosis. Internal organ involvement heterogeneous. It unknown whether mechanisms are common across all involved affected tissues or if each manifestation has distinct underlying pathology. We used consensus clustering to compare gene expression profiles of biopsies from four SSc-affected (skin, lung, esophagus, and peripheral blood) patients with SSc, the related conditions pulmonary fibrosis (PF) arterial...
Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, Children's Brain Tumor Network (CBTN) Pacific Neuro-Oncology Consortium (PNOC) created a systematic process tumor biobanking, model generation, sequencing with immediate access to harmonized data. We leverage data establish OpenPBTA, an open collaborative project over 40 scalable...
Large compendia of gene expression data have proven valuable for the discovery novel biological relationships. Historically, most available RNA assays were run on microarray, while RNA-seq is now platform choice many new experiments. The structure and distributions between platforms differ, making it challenging to combine them directly. Here we perform supervised unsupervised machine learning evaluations assess which existing normalization methods are best suited combining microarray data....
Genome-wide expression profiling in systemic sclerosis (SSc) has identified four 'intrinsic' subsets of disease (fibroproliferative, inflammatory, limited, and normal-like), each which shows deregulation distinct signaling pathways; however, the full set pathways contributing to this differential gene not been fully elucidated. Here we examine experimentally derived signatures dermal fibroblasts for thirteen different implicated SSc pathogenesis. These data show overlapping sets genes...
ABSTRACT The Pseudomonas fluorescens genome encodes more than 50 proteins predicted to be involved in c-di-GMP signaling. Here, we demonstrated that, tested across 188 nutrients, these enzymes and effectors appeared capable of impacting biofilm formation. Transcriptional analysis network members ∼50 nutrient conditions indicates that altered gene expression can explain a subset but not all formation responses the nutrients. Additional organization is likely achieved through physical...
Tumor-associated macrophages (TAMs) play an important role in tumor immunity and comprise of subsets that have distinct phenotype, function, ontology. Transcriptomic analyses human medulloblastoma, the most common malignant pediatric brain cancer, showed medulloblastomas (MBs) with activated sonic hedgehog signaling (SHH-MB) significantly more TAMs than other MB subtypes. Therefore, we examined MB-associated by single-cell RNA sequencing autochthonous murine SHH-MB at steady state under two...
Objective Understanding the pathogenesis of systemic sclerosis (SSc) is confounded by considerable disease heterogeneity. Animal models SSc that recapitulate distinct subsets at molecular level have not been delineated. We applied interspecies comparative analysis genomic data from multiple mouse and patients with to determine which animal best reflect intrinsic subsets. Methods Gene expression measured in skin mice sclerodermatous graft‐versus‐host (GVHD), bleomycin‐induced fibrosis, Tsk1/+...
Abstract The Open Single-cell Pediatric Cancer Atlas (OpenScPCA) project is an open, collaborative created to analyze publicly available data from the (ScPCA) Portal, with goal of improving quality and usability single-cell pediatric cancer driving insights into biology through deeper analysis sets. ScPCA Portal (https://scpca.alexslemonade.org/), developed maintained by Alex’s Lemonade Stand Foundation (ALSF), open-source resource for single-nuclei RNA sequencing tumors. currently contains...
Abstract The Single-cell Pediatric Cancer Atlas (ScPCA) Portal ( https://scpca.alexslemonade.org/ ) is a data resource for uniformly processed single-cell and single-nuclei RNA sequencing (RNA-seq) de-identified metadata from pediatric tumor samples. Originally comprised of 10 projects funded by Alex’s Lemonade Stand Foundation, the currently contains summarized gene expression over 500 samples 50 types cancers ALSF-funded community-contributed datasets. In addition to RNA-seq, holds...
Autoantibody profiles represent important patient stratification markers in systemic sclerosis (SSc). Here, we performed serum-immunoprecipitations with antibodies followed by mass spectrometry (LC-MS/MS) to obtain an unbiased view of all possible autoantibody targets and their associated molecular complexes recognized SSc. HeLa whole cell lysates were immunoprecipitated (IP) using sera patients SSc clinically positive for autoantibodies against RNA polymerase III (RNAP3), topoisomerase 1...
Abstract Sperm‐associated α‐ L ‐fucosidases have been implicated in fertilization many species. Previously, we documented the existence of ‐fucosidase mouse cauda epididymal contents, and showed that sperm‐associated is cryptically stored within acrosome reappears sperm equatorial segment after reaction. The enrichment membrane‐associated acrosome‐reacted cells implicates its roles during fertilization. Here, document absence oocytes early embryos, define associated using specific inhibitors...
Abstract Millions of transcriptomic profiles have been deposited in public archives, yet remain underused for the interpretation new experiments. We present a method interpreting datasets through instant comparison to without high-performance computing requirements. apply Principal Component Analysis on 536 studies comprising 44,890 human RNA sequencing and aggregate sufficiently similar loading vectors form Replicable Axes Variation (RAV). RAVs are annotated with metadata originating by...
Neurofibromatosis type 1 (NF1) is a monogenic syndrome that gives rise to numerous symptoms including cognitive impairment, skeletal abnormalities, and growth of benign nerve sheath tumors. Nearly all NF1 patients develop cutaneous neurofibromas (cNFs), which occur on the skin surface, whereas 40-60% plexiform (pNFs), are deeply embedded in peripheral nerves. Patients with pNFs have ~10% lifetime chance these tumors becoming malignant (MPNSTs). These severe prognosis few treatment options...
Motivation: Large compendia of gene expression data have proven valuable for the discovery novel biological relationships. The majority available RNA assays are run on microarray, while RNA-seq is becoming platform choice new experiments. structure and distributions between platforms differ, making it challenging to combine them. We performed supervised unsupervised machine learning evaluations, as well differential analyses, assess which normalization methods best suited combining...
Clusters of differentiation (CD) are cell surface biomarkers that denote key biological differences between types and disease state. CD-targeting therapeutic monoclonal antibodies (mABs) afford rich trans-disease repositioning opportunities. Within a compendium systemic lupus erythematous (SLE) patients, we applied the Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB) to profile de novo gene expression features affecting CD20, CD22 CD30 aberrance. First, novel...
SUMMARY Unsupervised machine learning methods provide a promising means to analyze and interpret large datasets. However, most gene expression datasets generated by individual researchers remain too small fully benefit from these methods. In the case of rare diseases, there may be few cases available, even when multiple studies are combined. We trained Pathway Level Information ExtractoR (PLIER) model using on public data compendium comprised experiments, tissues, biological conditions. then...
Abstract Background Gene fusion events are significant sources of somatic variation across adult and pediatric cancers some the most clinically-effective therapeutic targets, yet low consensus RNA-Seq prediction algorithms makes prioritization difficult. In addition, such as polymerase read-throughs, mis-mapping due to gene homology, fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers clinicians rapidly discern that might be true...