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    Home > Biochemistry News > Biotechnology News > Genomic Medicine: Understanding the aggressiveness of lung squamous cell carcinoma through the tumor stroma

    Genomic Medicine: Understanding the aggressiveness of lung squamous cell carcinoma through the tumor stroma

    • Last Update: 2023-01-05
    • Source: Internet
    • Author: User
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    Scientists at the Gavin Institute of Medical Research in Australia have identified a molecular profile of the surrounding stroma of a common subtype of lung cancer, which promises to indicate which patients are likely to progress to aggressive tumors
    .

    Squamous cell carcinoma of the lungs is the second most common subtype of lung cancer, after lung adenocarcinoma
    .
    However, treatment options for these patients remain limited and largely unchanged
    for decades.
    It has a high relapse rate, develops resistance to chemotherapy, and less than one in five patients survives more than
    five years after diagnosis.

    In addition to studying cancer cells, the researchers also turned their attention to the environment
    around cancer cells in tumors.
    The main component of this environment is the extracellular matrix (ECM), a 3D network of
    about 300 core molecules.
    This matrix is found in all tissues of the body and normally provides structural and functional support
    to cells.
    But in cancer, this matrix undergoes fundamental changes that promote tumor growth
    .

    Dr Amelia Parker, lead author of the study, said: "Our research focuses on how the stroma changes in lung squamous cell carcinoma, how it makes tumours more aggressive, and how it can be used to judge patient outcomes
    .

    "The tumor is an ecosystem that binds cancer cells together
    through the stroma.
    We believe that it is this matrix that supports the continued growth and spread of cancer cells, leading to poor
    prognosis for some patients.
    We don't really know what the matrix looks like, though, or why it makes lung cancer resistant
    .
    If we can understand this part of the tumor, we may be able to find more effective treatments
    .

    The findings, published this week in the journal Genomic Medicine, are expected to be used in the development of biomarkers to determine which patients may benefit from more aggressive and targeted therapies
    .

    Led by Associate Professor Thomas Cox at the Gavin Institute of Medicine, the research team comprehensively analyzed the molecular and protein composition
    of the matrix surrounding lung squamous cell carcinoma.

    They identified two tumor matrix profiles – one with a good prognosis and the other with a poor
    prognosis.
    These matrix maps appear to be established early in tumorigenesis and persist as tumors grow, controlling the tumor's response
    to chemotherapy.

    For patients whose condition worsens, more collagen and more fibrosis (hardening of the tumor structure) appear in the tumor stroma, indicating that the tumor stroma is remodeled to protect itself from treatment
    .

    The researchers also found that while lung adenocarcinoma and lung squamous cell carcinoma are clinically similar, their stromal composition is very different
    .
    These differences have the potential to be exploited
    by existing therapies to treat other diseases.

    "The two tumors look very similar under the microscope and are often treated with the same approach, but are very different at the molecular level," Cox said
    .
    "This illustrates why some patients are progressing well and others are not, and how we can stratify patients to provide more personalized care
    .
    "

    As a next step, they intend to conduct clinical trials with clinical partners to find ways to stop stromal remodeling in lung cancer patients and improve their response
    to treatment.

    Original search

    Parker, A.
    L.
    , Bowman, E.
    , Zingone, A.
    et al.
    Extracellular matrix profiles determine risk and prognosis of the squamous cell carcinoma subtype of non-small cell lung carcinoma.
    Genome Med 14, 126 (2022).
    https://doi.
    org/10.
    1186/s13073-022-01127-6


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