Evaluation of chemosensitivity prediction using quantitative dose-response curve classification for highly advanced/relapsed gastric cancer

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Abstract

Background: The use of standard chemotherapy regimens has changed the application of chemosensitivity tests from all chemotherapy-eligible patients to those who have failed standard chemotherapy, which includes patients with highly advanced, relapsed, or chemoresistant tumors.Methods: We evaluated a total of 43 advanced primary and relapsed gastric cancers for chemosensitivity based on drug dose response curves to improve the objectivity and quality of quantitative measurements. The dose response curves were classified based on seven expected patterns. Instead of a binary chemosensitivity evaluation, we ranked drug sensitivity according to curve shapes and comparison with the peak plasma concentration (ppc) of each drug.Results: A total of 193 dose response curves were obtained. The overall informative rate was 67.4%, and 85.3% for cases that had a sufficient number of cells. Paclitaxel (PXL)and docetaxel tended to show a higher rank, while cisplatin (CIS) and 5-fluorouracil (5-FU) tended to show resistance, particularly among the 20 cases (46.5%) that had recurrent disease after receiving chemotherapy with CIS and S-1 (5-FU). As such, we speculate that the resistant pattern of the chemosensitivity test suggests that cells with acquired drug resistance were selected by chemotherapy. Indeed, we observed a change in the chemosensitivity pattern of a sample before and after chemotherapy in terms of PXL sensitivity, which was used after primary chemotherapy.Conclusions: These results suggest that: (i) the dose-response pattern provides objective information for predicting chemosensitivity; and (ii) chemotherapy may select resistant cancer cell populations as a result of the therapy. © 2013 Matsuo et al.; licensee BioMed Central Ltd.

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Matsuo, T., Nishizuka, S. S., Ishida, K., Endo, F., Katagiri, H., Kume, K., … Wakabayashi, G. (2013). Evaluation of chemosensitivity prediction using quantitative dose-response curve classification for highly advanced/relapsed gastric cancer. World Journal of Surgical Oncology, 11. https://doi.org/10.1186/1477-7819-11-11

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