26 research outputs found

    Runx1 stabilizes the mammary epithelial cell phenotype and prevents epithelial to mesenchymal transition

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    Runx1 is a well characterized transcription factor essential for hematopoietic differentiation and Runx1 mutations are the cause of leukemias. Runx1 is highly expressed in normal epithelium of most glands and recently has been associated with solid tumors. Notably, the function of Runx1 in the mammary gland and how it is involved in initiation and progression of breast cancer is still unclear. Here we demonstrate the consequences of Runx1 loss in normal mammary epithelial and breast cancer cells. We first observed that Runx1 is decreased in tumorigenic and metastatic breast cancer cells. We also observed loss of Runx1 expression upon induction of epithelial-mesenchymal transition (EMT) in MCF10A (normal-like) cells. Furthermore depletion of Runx1 in MCF10A cells resulted in striking changes in cell shape, leading to mesenchymal cell morphology. The epithelial phenotype could be restored in breast cancer cells by re-expressing Runx1. Analyses of breast tumors and patient data revealed that low Runx1 expression is associated with poor prognosis and decreased survival. We addressed mechanisms for the function of Runx1 in maintaining the epithelial phenotype and find Runx1 directly regulates E-cadherin; and serves as a downstream transcription factor mediating TGFbeta signaling. We also observed through global gene expression profiling of growth factor depleted cells that induction of EMT and loss of Runx1 is associated with activation of TGFbeta and WNT pathways. Thus these findings have identified a novel function for Runx1 in sustaining normal epithelial morphology and preventing EMT and suggest Runx1 levels could be a prognostic indicator of tumor progression

    Runx1 stabilizes the mammary epithelial cell phenotype and prevents epithelial to mesenchymal transition

    Get PDF
    Runx1 is a well characterized transcription factor essential for hematopoietic differentiation and Runx1 mutations are the cause of leukemias. Runx1 is highly expressed in normal epithelium of most glands and recently has been associated with solid tumors. Notably, the function of Runx1 in the mammary gland and how it is involved in initiation and progression of breast cancer is still unclear. Here we demonstrate the consequences of Runx1 loss in normal mammary epithelial and breast cancer cells. We first observed that Runx1 is decreased in tumorigenic and metastatic breast cancer cells. We also observed loss of Runx1 expression upon induction of epithelial-mesenchymal transition (EMT) in MCF10A (normal-like) cells. Furthermore depletion of Runx1 in MCF10A cells resulted in striking changes in cell shape, leading to mesenchymal cell morphology. The epithelial phenotype could be restored in breast cancer cells by re-expressing Runx1. Analyses of breast tumors and patient data revealed that low Runx1 expression is associated with poor prognosis and decreased survival. We addressed mechanisms for the function of Runx1 in maintaining the epithelial phenotype and find Runx1 directly regulates E-cadherin; and serves as a downstream transcription factor mediating TGFbeta signaling. We also observed through global gene expression profiling of growth factor depleted cells that induction of EMT and loss of Runx1 is associated with activation of TGFbeta and WNT pathways. Thus these findings have identified a novel function for Runx1 in sustaining normal epithelial morphology and preventing EMT and suggest Runx1 levels could be a prognostic indicator of tumor progression

    Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

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    Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

    The study of atmospheric ice-nucleating particles via microfluidically generated droplets

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    Ice-nucleating particles (INPs) play a significant role in the climate and hydrological cycle by triggering ice formation in supercooled clouds, thereby causing precipitation and affecting cloud lifetimes and their radiative properties. However, despite their importance, INP often comprise only 1 in 10³–10⁶ ambient particles, making it difficult to ascertain and predict their type, source, and concentration. The typical techniques for quantifying INP concentrations tend to be highly labour-intensive, suffer from poor time resolution, or are limited in sensitivity to low concentrations. Here, we present the application of microfluidic devices to the study of atmospheric INPs via the simple and rapid production of monodisperse droplets and their subsequent freezing on a cold stage. This device offers the potential for the testing of INP concentrations in aqueous samples with high sensitivity and high counting statistics. Various INPs were tested for validation of the platform, including mineral dust and biological species, with results compared to literature values. We also describe a methodology for sampling atmospheric aerosol in a manner that minimises sampling biases and which is compatible with the microfluidic device. We present results for INP concentrations in air sampled during two field campaigns: (1) from a rural location in the UK and (2) during the UK’s annual Bonfire Night festival. These initial results will provide a route for deployment of the microfluidic platform for the study and quantification of INPs in upcoming field campaigns around the globe, while providing a benchmark for future lab-on-a-chip-based INP studies

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts
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