The human tumor clonogenic assay in the treatment of patients with lung cancer

Prediction of Cancer Drug Resistance and Implications for Personalized Medicine

Drug resistance still impedes successful cancer chemotherapy. A major goal of early concepts in individualized therapy was to develop in vitro tests to predict tumors’ drug responsiveness. We have developed an in vitro short-term test based on nucleic acid precursor incorporation to determine clinical drug resistance. This test detects inherent and acquired resistance in vitro and transplantable syngeneic and xenografted tumors in vivo. In several clinical trials, clinical resistance was predictable with more than 90% accuracy, while drug sensitivity was detected with less accuracy (~60%). Remarkably, clinical cross-resistance to numerous drugs (multidrug resistance, broad spectrum resistance) was detectable by a single compound, doxorubicin, due to its multifactorial modes of action. The results of this predictive test were in good agreement with predictive assays of other authors. As no predictive test has been established as yet for clinical diagnostics, the identification of sensitive drugs may not reach sufficiently high reliability for clinical routine. A meta-analysis of the literature published during the past four decades considering test results of more than 15,000 tumor patients unambiguously demonstrated that, in the majority of studies, resistance was correctly predicted with an accuracy between 80 and 100%, while drug sensitivity could only be predicted with an accuracy of 50–80%. This synopsis of the published literature impressively illustrates that prediction of drug resistance could be validated. The determination of drug resistance was reliable independent of tumor type, test assay, and drug used in these in vitro tests. By contrast, chemosensitivity could not be predicted with high reliability. Therefore, we propose a rethinking of the “chemosensitivity” concept. Instead, predictive in vitro tests may reliably identify drug-resistant tumors. The clinical consequence imply to subject resistant tumors not to chemotherapy, but to other new treatment options, such as antibody therapy, adoptive immune therapy, hyperthermia, gene therapy, etc. The high accuracy to predict resistant tumors may be exploited to develop new strategies for individualized cancer therapy. This new concept bears the potential of a revival of predictive tests for personalized medicine.

In vitro sensitivity assays in cancer: a review, analysis, and prognosis

Tumors are complex systems consisting of heterogeneous cancer cells as well as normal cells with each exhibiting unique drug sensitivity spectra. There have been many attempts to design in vitro systems to determine drug response to tumors. The most widely used system is the clonogenic assay. which has demonstrated some clinical predictivity. However, the clonogenic assay has been shown to have negative aspects, including low frequency of evaluation, clump artifacts, lack of cytotoxic end-points and disruption of normal cell-cell interactions existing in a true tissue environment. Newer models are described utilizing cytotoxic as well as cell-proliferation end-points, and maintenance of three-dimensional tissue architecture in vitro. It is concluded that less artifactual, more realistic models can be used to select more tumor-specific drugs which themselves in turn will make in vitro chemosensitivity assays more useful for cancer patients.

Time-schedule dependency of the inhibiting activity of various anticancer drugs in the clonogenic assay

To analyze the discrepancy between the in vitro response in the clonogenic assay and the clinical response, the time-schedule dependencies of various anticancer drugs were determined by comparing the inhibiting effect against colony formation by PC-7 cells treated with the drugs for 1 h with that of those treated for 24 h. According to their schedule dependency the drugs can be divided into a schedule-dependent drug group (5-fluorouracil, methotrexate, bleomycin, pepleomycin, etoposide, cisplatin, teniposide, vindesine, and vinblastine) and a non-schedule-dependent drug group (adriamycin, actinomycin D, ranomustine, mitomycin C, aclacinomycin, daunomycin, nimustine, melphalan, and KW 2083). In the clonogenic assay, the 1-h exposure schedule is appropriate for predicting clinical response for the non-schedule-dependent drugs. However, the effect of the schedule-dependent drugs was underestimated in the same conditions. Therefore, it is necessary to test these drugs in the assay by 24-h exposure for a more accurate assessment of their antitumor activity.