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    Home > Active Ingredient News > Antitumor Therapy > PNAS: A drop of blood may be able to quickly detect early human lung cancer

    PNAS: A drop of blood may be able to quickly detect early human lung cancer

    • Last Update: 2022-01-08
    • Source: Internet
    • Author: User
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    Lung cancer is the main cause of death in cancer patients.
    It is only diagnosed in the late stage of the disease , and the survival rate of patients at this time is often low; most early lung cancers are asymptomatic, and the current methods for detecting early lung cancer lesions -Low-dose spiral CT does not seem to be feasible as a wide-ranging screening of the general population because of its high cost and repeated screening will bring certain radiation hazards to patients
    .


    Recently, in a research report titled " Screening human lung cancer with predictive models of serum magnetic resonance spectroscopy metabolomics " published in the international journal PNAS, scientists from Harvard Medical School and other institutions have revealed through research that using a drop of blood may be It can reveal lung cancer in asymptomatic patients


    Lung cancer is the main cause of death in cancer patients.


     

    Image source: James Heilman, MD/Wikipedia

    Image source: James Heilman, MD/Wikipedia

     

    Researcher Cheng said that our research shows that in the future we may be expected to develop a sensitive screening method for the early diagnosis of lung cancer; the predictive model we have created can help identify people who may develop lung cancer.
    Then, the suspicious people will be further evaluated by imaging tests, such as low-dose CT, so as to give a clear diagnosis to the individual
    .

    Researcher Cheng said that our research shows that in the future we may be expected to develop a sensitive screening method for the early diagnosis of lung cancer; the predictive model we have created can help identify people who may develop lung cancer.
    Then, the suspicious people will be further evaluated by imaging tests, such as low-dose CT, so as to give a clear diagnosis to the individual
    .


    In the article, the researchers established a lung cancer prediction model based on the metabolomics data in the body’s blood.
    Metabolomics analysis revealed the metabolic flow of cells, and by studying the metabolome (that is, all cells, body fluids and tissues found in the body) The dynamic biochemical component) can analyze the health and pathological state of the body; the existence of lung cancer and its altered physiological and pathological characteristics may cause changes in blood metabolites produced or consumed by cancer cells in lung cancer.
    Researchers use High-resolution nuclear magnetic resonance spectroscopy measures the characteristics of metabolomics in the blood .
    This tool can examine a series of compounds in living cells by measuring the collective response of metabolites
    .

    In the article, the researchers established a lung cancer prediction model based on the metabolomics data in the body’s blood.
    Metabolomics analysis revealed the metabolic flow of cells, and by studying the metabolome (that is, all cells, body fluids and tissues found in the body) The dynamic biochemical component) can analyze the health and pathological state of the body; the existence of lung cancer and its altered physiological and pathological characteristics may cause changes in blood metabolites produced or consumed by cancer cells in lung cancer.
    Researchers use High-resolution nuclear magnetic resonance spectroscopy measures the characteristics of metabolomics in the blood .
    This tool can examine a series of compounds in living cells by measuring the collective response of metabolites
    .


    The existence of lung cancer and its altered physiological and pathological characteristics may cause changes in the blood metabolites produced or consumed by cancer cells in lung cancer.


    In addition, the researchers also screened tens of thousands of blood samples stored in the Biobank of Massachusetts General Hospital and other places, and found 25 patients with non-small cell lung cancer.


    The value of the predictive model measured from the blood sample before diagnosis may predict the patient's survival rate in the next 5 years, which may be expected to help guide clinical strategies and the role of therapy.


     

    Image source: https:// source: https:// the researchers also analyzed the metabonomics characteristics of the clinical features of lung cancer, aiming to understand the entire metabolic profile of the disease, which may help to select targeted therapies; in addition, the researchers also measured more than 400 prostate cancers The metabolomics characteristics of the patient’s body can be used to create a model to distinguish between “lazy” cancers that need to be monitored and more aggressive types of cancer that need to be understood and treated; the same researchers have also developed the same technology to use blood The samples and cerebrospinal fluid are screened for Alzheimer's disease
    .

    Next, the researchers also analyzed the metabonomics characteristics of the clinical features of lung cancer, aiming to understand the entire metabolic profile of the disease, which may help to select targeted therapies; in addition, the researchers also measured more than 400 prostate cancers The metabolomics characteristics of the patient’s body can be used to create a model to distinguish between “lazy” cancers that need to be monitored and more aggressive types of cancer that need to be understood and treated; the same researchers have also developed the same technology to use blood The samples and cerebrospinal fluid are screened for Alzheimer's disease
    .


    In summary, the results of this study indicate that the value of the metabolomics prediction model measured before the diagnosis of the patient may help predict the 5-year survival rate of locally affected patients
    .

    In summary, the results of this study indicate that the value of the metabolomics prediction model measured before the diagnosis of the patient may help predict the 5-year survival rate of locally affected patients
    .


    Original source:

    Original source:

    Tjada A.


    Tjada A.
    Schult,Mara J.
    Lauer, Yannick Berker, et al.
    Screening human lung cancer with predictive models of serum magnetic resonance spectroscopy metabolomics, Proceedings of the National Academy of Sciences (2021).
    DOI: 10.
    1073/pnas.
    211063311 is here message
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