FB2025_01 , released February 20, 2025
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Citation
Aida, A., Yuswan, K., Kawai, Y., Hasegawa, K., Nakajima, Y.I., Kuranaga, E. (2023). Drosophila innate immunity suppresses the survival of xenografted mammalian tumor cells.  Sci. Rep. 13(1): 12334.
FlyBase ID
FBrf0257133
Publication Type
Research paper
Abstract
Patient-derived xenograft (PDX) is an emerging tool established in immunodeficient vertebrate models to assess individualized treatments for cancer patients. Current xenograft models are deficient in adaptive immune systems. However, the precise role of the innate immunity in the xenograft models is unknown. With conserved signaling pathways and established genetic tools, Drosophila has contributed to the understanding of the mechanism of tumor growth as well as tumor-host interactions for decades, making it a promising candidate model for studying whether or not the hosts' innate immunity can accommodate transplanted human tumor cells. Here we show initial observations that assess the behavior and impact of several human tumor cell lines when transplanted into Drosophila. We found that some injected cell lines persisted for a longer duration and reduced hosts' lifespan. In particular, the human lung cancer cell line A549 were observed adjacent to the fly host tissues. We examined two factors that affect the survivability of cancer cells: (1) the optimal temperature of each cell line and (2) the innate immunity of Drosophila hosts. Especially, transplanted human tumor cells survived longer in immunodeficient flies, suggesting that the host innate immune system impedes the growth of xenografted cells. Our attempts for xenografting fly models thus provide necessary steps to overcome for establishing PDX cancer models using invertebrates.
PubMed ID
PubMed Central ID
PMC10387472 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Sci. Rep.
    Title
    Scientific reports
    ISBN/ISSN
    2045-2322
    Data From Reference
    Genes (5)
    Human Disease Models (1)