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In vitro anticancer drug sensitivity testing

Y V Dobrynin, G V Vyshinskaya

    Antibiotics and Chemotherapy
    |January 1, 1980
    PubMed
    Summary
    This summary is machine-generated.

    This study assessed antitumor drug effectiveness using 3H-thymidine DNA incorporation in human tumor cultures. Laboratory drug sensitivity testing showed an 88.7% correlation with patient clinical response.

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    ESTABLISHMENT AND CHARACTERISTICS OF CELL STRAINS FROM SOME EPITHELIAL TUMORS OF HUMAN ORIGIN.

    Journal of the National Cancer Institute·1963
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    Area of Science:

    • Oncology
    • Molecular Biology
    • Pharmacology

    Background:

    • Accurate prediction of antitumor drug efficacy is crucial for effective cancer treatment.
    • Short-term human tumor cultures offer a model for evaluating drug responses.
    • 3H-thymidine incorporation into DNA serves as a measure of cellular proliferation and drug effect.

    Purpose of the Study:

    • To investigate the utility of 3H-thymidine incorporation into DNA for assessing antitumor drug sensitivity in human tumor cultures.
    • To correlate in vitro drug sensitivity testing with clinical outcomes in cancer patients.

    Main Methods:

    • Short-term cultures of human tumor samples were established.
    • The effect of various antitumor drugs on 3H-thymidine incorporation into DNA was measured.

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  • Drug sensitivity was tested in tumor samples from 104 patients.
  • Clinical responses of 53 treated patients were analyzed and compared to laboratory results.

    • Main Results:

    • The 3H-thymidine incorporation assay was applied to diverse malignant tumors.
    • A significant correlation (88.7%) was observed between in vitro drug sensitivity testing and clinical response in patients.
    • This indicates the predictive value of the laboratory method.

    Conclusions:

    • In vitro drug sensitivity testing using 3H-thymidine incorporation into DNA is a reliable method for predicting clinical response to antitumor drugs.
    • This approach can aid in selecting optimal therapeutic strategies for cancer patients.
    • The findings support the use of personalized medicine in oncology.