13 research outputs found

    DNA methylation-based classification of sinonasal tumors

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    The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs

    Vormgeving van honoursactiviteiten

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    In dit artikel worden verschillende aanpakken van honoursprogramma’s in het Nederlandse onderwijs met elkaar vergeleken en worden steutelfactoren voor effectieve honoursprogramma’s geïdentificeerd. Een van de honoursprogramma’s betreft het honoursprogramma van het domein Onderwijs en Opvoeding dat in het artikel uitgebreid wordt beschreven

    Stromal-derived interleukin 6 drives epithelial-to-mesenchymal transition and therapy resistance in esophageal adenocarcinoma

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    Esophageal adenocarcinoma (EAC) has a dismal prognosis, and survival benefits of recent multimodality treatments remain small. Cancer-associated fibroblasts (CAFs) are known to contribute to poor outcome by conferring therapy resistance to various cancer types, but this has not been explored in EAC. Importantly, a targeted strategy to circumvent CAF-induced resistance has yet to be identified. By using EAC patient-derived CAFs, organoid cultures, and xenograft models we identified IL-6 as the stromal driver of therapy resistance in EAC. IL-6 activated epithelial-to-mesenchymal transition in cancer cells, which was accompanied by enhanced treatment resistance, migratory capacity, and clonogenicity. Inhibition of IL-6 restored drug sensitivity in patient-derived organoid cultures and cell lines. Analysis of patient gene expression profiles identified ADAM12 as a noninflammation-related serum-borne marker for IL-6-producing CAFs, and serum levels of this marker predicted unfavorable responses to neoadjuvant chemoradiation in EAC patients. These results demonstrate a stromal contribution to therapy resistance in EAC. This signaling can be targeted to resensitize EAC to therapy, and its activity can be measured using serum-borne markers
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