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Volume 20 Issue 6, June 2020

Modifications light up RNA, inspired by the Review on p303.

Cover design: Lara Crow.

Research Highlights

  • The group of Sangeeta Bhatia have leveraged a set of nanosensors to diagnose lung cancer in mice by detecting and amplifying the activity of dysregulated extracellular proteases, offering a urine-based readout.

    • Anna Dart
    Research Highlight

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  • Klichinsky et al. have engineered macrophages to express chimeric antigen receptors (CARs) that target their phagocytic activity towards tumour cells. These macrophages (CAR-Ms) reduced tumour burden and prolonged overall survival in mice.

    • M. Teresa Villanueva
    Research Highlight
  • Roulis, Kaklamanos et al. have identified a population of rare fibroblasts present in intestinal crypts that promote intestinal tumorigenesis in a paracrine manner through prostaglandin E2 signalling.

    • Sarah Seton-Rogers
    Research Highlight
  • Chung et al. studied drivers of obesity-associated pancreatic ductal adenocarcinoma in a leptin-deficient mouse model and identified the hormone cholecystokinin, upregulated in islet beta cells in the context of obesity, to be promoting pancreatic tumorigenesis.

    • Ulrike Harjes
    Research Highlight
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Reviews

  • After synthesis, all RNA molecules are subject to covalent modifications. This Review presents the evidence that RNA modification pathways are misregulated in cancer and suggests that they may be ideal targets for cancer therapy.

    • Isaia Barbieri
    • Tony Kouzarides

    Collection:

    Review Article
  • Peripheral T cell lymphomas (PTCLs) are a heterogeneous group of rare neoplasms. This Review outlines our current understanding of the genomic defects and host environment characteristics that promote PTCL development with the aim of improving molecular stratification and targeted therapy for PTCLs.

    • Danilo Fiore
    • Luca Vincenzo Cappelli
    • Giorgio Inghirami
    Review Article
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Perspectives

  • This Perspective discusses how executable computational models, integrating various data sets derived from preclinical models and cancer patients, can be used to represent the dynamic biological behaviours inherent in cancer. The article argues that these models might be used as patient avatars to improve personalized treatments.

    • Matthew A. Clarke
    • Jasmin Fisher
    Perspective
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Amendments & Corrections

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