14478 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Maturation of Human Intestinal Epithelial Cell Layers Fortifies the Apical Surface against Salmonella Attack

  Pathogen invasion of intestinal epithelial cells (IECs) is a key gut infection event. The dynamics of this process in intact epithelia and the factors governing IEC susceptibility remain underexplored. We present a resource for live-cell infection imaging in human enteroid-/colonoid-derived IEC layers, across maturation states and in the presence or absence of soluble mucus production. Utilization of this resource shows how human IEC maturation fortifies the apical surface against invasion by Salmonella Typhimurium (S.Tm). Immature IEC layers appear permissive to S.Tm invasion, but maturation towards an enterocyte/colonocyte phenotype reduces the susceptibility by up to tenfold. This shift couples to downregulated expression of actin regulatory proteins exploited by the pathogen, an increased dependence on the S.Tm effector SipA, and the build-up of the apical IEC glycocalyx linked to surface-attached mucins like MUC13 and nullifiable by StcE-enzyme treatment. This underscores how the maturation state of human IECs governs susceptibility to bacterial invasion.

  Study EGAS50000001241

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• WGS analysis of Japanese liver cancer

  Liver cancer is prevalent worldwide, mainly associated with virus infection, and its underlying etiology and genomic structure are heterogeneous. Here we provide a whole-genome landscape of somatic alterations in 300 Japanese liver cancers. Our comprehensive analysis elucidated point mutations in non-coding regions, structural variants (SVs), and virus integrations, in addition to coding mutations, and demonstrated new mutational signatures related with liver carcinogenesis, novel recurrently mutated coding and non-coding regions such as lincRNA NEAT1/MALAT1, promoters, CTCF binding sites, and regulatory regions. SV analysis found a significant association with replication timing, and revealed that known cancer genes (CDKN2A, CCND1, APC, and TERT) and new cancer genes (ASH1L, NCOR1, MACROD2) were recurrently affected by SVs, leading to altered expression of nearby genes. These results emphasize the value of whole genome sequencing analysis to discover cancer driver mutations and to understand comprehensive molecular profiles of liver cancer, especially for SVs and non-coding mutations.

  Study JGAS000151

• Variant allele frequency changes in TP53 predict pembrolizumab response in patients with metastatic urothelial carcinoma

  Prognoses for patients with metastatic urothelial carcinoma (mUC) have strikingly improved with pembrolizumab, an immune checkpoint inhibitor (ICI), but clinical benefits are limited to a subset of patients. Therefore, a non-invasive biomarker to predict pembrolizumab response is urgently required. We retrospectively examined genomic alterations in 25 plasma circulating tumor DNA (ctDNA) samples using a targeted sequencing of 77 genes from 16 mUC patients during pembrolizumab treatment. Eleven (68.8%) patients had two or more genomic alterations, including TP53 mutations (as defined by ctDNA-positive status). The proportion of responders to pembrolizumab in the ctDNA-positive group was higher than the ctDNA-negative group (72.7% vs. 20.0%). Furthermore, among all detected genomic alterations, variant allele frequency decreases in TP53 during pembrolizumab treatment were mainly associated with therapeutic response. Collectively, we suggest that profiling of ctDNA in plasma, especially TP53, is useful for predicting and monitoring therapeutic responses to pembrolizumab in mUC patients.

  Study JGAS000622

• Comprehensive assay for the molecular profiling of cancer by target enrichment from formalin-fixed paraffin-embedded specimens

  Tumor molecular profiling is becoming a standard of care for patients with cancer, but the optimal platform for cancer sequencing remains undetermined. We established a comprehensive assay, the Todai OncoPanel (TOP), which consists of DNA and RNA hybridization capture-based next-generation sequencing panels. A novel method for target enrichment, named the junction capture method, was developed for the RNA panel to accurately and cost-effectively detect 365 fusion genes as well as aberrantly spliced transcripts. The TOP RNA panel can also measure the expression profiles of an additional 109 genes. The TOP DNA panel was developed to detect single nucleotide variants and insertions/deletions for 464 genes, to calculate tumor mutation burden and microsatellite instability status, and to infer chromosomal copy number. Clinically relevant somatic mutations were identified in 32.2% (59/183) of patients by prospective TOP testing, signifying the clinical utility of TOP for providing personalized medicine to cancer patients.

  Study JGAS000164

• Transcriptome alterations underlying metabolic dysfunction and liver disease in myotonic dystrophy type 1

  Myotonic dystrophy type 1 (DM1) is a multisystem disorder affecting various organs, including the skeletal muscles, eyes, heart, central nervous system, and endocrine system. Liver dysfunction and lipid metabolism abnormalities are frequently observed in DM1 but are not fully understood. To explore the molecular basis of these abnormalities, transcriptome analysis was performed on postmortem liver samples from DM1 patients DM1 patients (n = 11) and disease control patients (n = 9) using bulkRNA sequencing (RNA-seq) on the MGI DNBSEQ-G400RS. Differential gene expression and alternative splicing analyses revealed significant transcriptomic changes associated with lipid metabolism, liver fibrosis, and glucose homeostasis. Interestingly, transcriptome changes in DM1 livers also revealed partial resolution of sexual dimorphism in gene expression, along with unique sex-specific pathway alterations. A correlation between serum GGT levels and splicing abnormalities in DM1 patients was identified, suggesting a link between transcriptomic changes and clinical outcomes. This dataset provides valuable insights into the molecular mechanisms underlying DM1-related liver dysfunction and metabolic abnormalities.

  Study JGAS000814

• STimage: Robust and interpretable prediction of gene markers and cell types from spatial transcriptomics data

  Spatial transcriptomics (ST) links tissue morphology with gene expression values, opening new avenues for digital pathology. Deep learning models are used to predict gene expression or classify cell types directly from images, offering significant clinical potential but still requiring improvements in interpretability and robustness. We present STimage as a comprehensive suite of models to predict spatial gene expression and classify cell types directly from standard H\&E images. STimage enhances robustness by estimating gene expression distributions and quantifying both data-driven (aleatoric) and model-based (epistemic) uncertainty using ensemble approach with foundation models. Interpretability is achieved through attribution analysis at single-cell resolution integrated with histopathological annotations, functional genes, and latent representations. We validated STimage across diverse datasets, demonstrating its performance across various platforms. STimage-predicted gene expression can stratify patient survival and predict drug response. By enabling molecular and cellular prediction from routine histology, STimage offers a powerful tool to advance digital pathology.

  Study EGAS50000001503

• TONIC-Trial-cfDNA-Project

  Cell-free DNA (cfDNA) is an emerging technology to predict and monitor response to cancer treatment, including immune checkpoint blockade (ICB). However, data on cfDNA dynamics during ICB in metastatic triple negative breast cancer (mTNBC) are limited. While most applications of cfDNA involve assays that focus on mutation detection, mTNBC and multiple other cancer types are driven by copy number alterations (CNAs). We evaluate cfDNA-based copy number profile abnormality (CPA) score as a potential biomarker for monitoring ICB response in mTNBC, analyzing data from 87 patients enrolled in stage 1 and stage 2 of the TONIC-trial. We find significant concordance between cfDNA-based and tissue-based CNA profiles. Additionally, responders show a decrease in CPA scores upon ICB at week 6 (3 cycles of nivolumab). These findings underscore the potential of cfDNA-based CNA dynamics as a non-invasive biomarker for ICB early response assessment in patients with mTNBC.

  Study EGAS50000001308

• Recurrent COPA mutation drives R-spondin-independent Wnt activation in intestinal tumors

  The majority of intestinal tumors harbor mutations in canonical Wnt pathway genes such as APC, whereas the lack of such alterations in a subset of tumors implies alternative tumorigenic routes. Here, we identify recurrent in-frame deletion in COPA, frequently co-occurring with USP9X truncating mutation, in small intestinal adenoma and adenocarcinoma. Patient-derived and CRISPR-engineered small intestinal organoids carrying COPA in-frame deletions exhibit R-spondin-independent yet Wnt ligand-dependent growth, maintaining LGR5 expression without canonical Wnt drivers. Mechanistically, COPA mutation stabilizes frizzled co-receptor LRP6 irrespective of R-spondin, sustaining Wnt pathway activation under growth factor-restricted conditions. USP9X loss further potentiates this phenotype. Unlike canonical Wnt pathway members, COPA encodes the alpha-subunit of coatomer complex I, which engages in vesicle trafficking with little prior linkage to intestinal tumorigenesis. Our findings establish COPA mutation as a novel and atypical intestinal tumor driver and implicate USP9X loss as a cooperating lesion.

  Study JGAS000868

• Chordoma_Sequencing_Project_Whole_Genome

  This is a continuation of the Chordoma Sequencing Project, prelim #G0175-122-CF. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. The Chordoma Foundation will fund the RNA Sequencing/Methylation and SNP6 costs for this project while the whole genome and library sequencing will be covered under the CGP, 2012-2013 core WTSI internal funding. An additional sequencing of three cancer cell lines will be added to this work, financed by the Chordoma Foundation. In this project, the Chordoma foundation will pay for the additional costs of methylation, RNA Seq,

  Study EGAS00001000409