17 research outputs found

    LMTK3 confers chemo-resistance in breast cancer

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    Lemur tyrosine kinase 3 (LMTK3) is an oncogenic kinase that is involved in different types of cancer (breast, lung, gastric, colorectal) and biological processes including proliferation, invasion, migration, chromatin remodeling as well as innate and acquired endocrine resistance. However, the role of LMTK3 in response to cytotoxic chemotherapy has not been investigated thus far. Using both 2D and 3D tissue culture models, we found that overexpression of LMTK3 decreased the sensitivity of breast cancer cell lines to cytotoxic (doxorubicin) treatment. In a mouse model we showed that ectopic overexpression of LMTK3 decreases the efficacy of doxorubicin in reducing tumor growth. Interestingly, breast cancer cells overexpressing LMTK3 delayed the generation of double strand breaks (DSBs) after exposure to doxorubicin, as measured by the formation of ÎłH2AX foci. This effect was at least partly mediated by decreased activity of ataxia-telangiectasia mutated kinase (ATM) as indicated by its reduced phosphorylation levels. In addition, our RNA-seq analyses showed that doxorubicin differentially regulated the expression of over 700 genes depending on LMTK3 protein expression levels. Furthermore, these genes were found to promote DNA repair, cell viability and tumorigenesis processes / pathways in LMTK3-overexpressing MCF7 cells. In human cancers, immunohistochemistry staining of LMTK3 in pre- and postchemotherapy breast tumor pairs from four separate clinical cohorts revealed a significant increase of LMTK3 following both doxorubicin and docetaxel based chemotherapy. In aggregate, our findings show for the first time a contribution of LMTK3 in cytotoxic drug resistance in breast cancer

    ICAR: endoscopic skull‐base surgery

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    An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples.

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    MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed.  Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination

    Pf7: an open dataset of Plasmodium falciparum genome variation in 20,000 worldwide samples

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    We describe the MalariaGEN Pf7 data resource, the seventh release of Plasmodium falciparum genome variation data from the MalariaGEN network.  It comprises over 20,000 samples from 82 partner studies in 33 countries, including several malaria endemic regions that were previously underrepresented.  For the first time we include dried blood spot samples that were sequenced after selective whole genome amplification, necessitating new methods to genotype copy number variations.  We identify a large number of newly emerging crt mutations in parts of Southeast Asia, and show examples of heterogeneities in patterns of drug resistance within Africa and within the Indian subcontinent.  We describe the profile of variations in the C-terminal of the csp gene and relate this to the sequence used in the RTS,S and R21 malaria vaccines.  Pf7 provides high-quality data on genotype calls for 6 million SNPs and short indels, analysis of large deletions that cause failure of rapid diagnostic tests, and systematic characterisation of six major drug resistance loci, all of which can be freely downloaded from the MalariaGEN website
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